A system for managing energy usage in a vehicle is provided. The system includes a vehicle control system, an artificial intelligence system, and an energy management module. The vehicle control system is operable to adjust at least one operational parameter of the vehicle. The artificial intelligence (AI) system includes a hybrid neural network configured to: process vehicle operational state and energy consumption information; classify a plurality of operational states of the vehicle; and determine an optimized vehicle operating state based on the classified operational states. The energy management module is coupled to the AI system and the vehicle control system, and: receives operational state and energy consumption information from the vehicle; and modifies the at least one operational parameter to optimize electricity usage of the vehicle.
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 30/0208 - Trade or exchange of goods or services in exchange for incentives or rewards
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
G06Q 50/40 - Business processes related to the transportation industry
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
2.
Vehicles with brain-computer interfaces for emotional states of riders
Systems for vehicles are provided. A system includes a brain-computer interface, an artificial intelligence system, and a vehicle control system. The brain-computer interface is configured to interact with the vehicle, to interact with a rider of the vehicle, and to generate output data. The artificial intelligence system is configured to receive the output data and to analyze an emotional state of the rider based on the output data. The vehicle control system is configured to optimize at least one operating parameter of the vehicle based on the emotional state of the rider as analyzed by the artificial intelligence system.
G05D 1/81 - Handing over between on-board automatic and on-board manual control
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G06Q 50/40 - Business processes related to the transportation industry
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
The present disclosure relates to transportation and related methods and systems including software-defined vehicles, vehicle operating states, an identity management system, an intelligent digital twin system that creates, manages, and provides digital twins for transportation systems using sensor data and other data, quantum computing methods and systems, including a set of quantum computing services, generative-AI methods and systems, and biology-based systems and methods for communicating and/or handling data.
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
B60W 50/16 - Tactile feedback to the driver, e.g. vibration or force feedback to the driver on the steering wheel or the accelerator pedal
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
A system for representing multiple operating states of a vehicle includes a digital twin system configured to create and manage a digital twin of the vehicle. A data collection system is configured to receive one or more data inputs indicating vehicle parameter data of the vehicle. A state determination system is configured to determine multiple operating states of the vehicle based on the vehicle parameter data. An interface system is configured to present the multiple operating states of the vehicle to a user via the digital twin of the vehicle.
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05B 13/04 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
G06N 3/044 - Recurrent networks, e.g. Hopfield networks
A transportation system and method for managing rewards in the transportation system includes using a merchant interface to a cognitive system for managing the offering or fulfillment of a reward to a rider of a vehicle, where a merchant may specify parameters of the reward that can be earned by the rider as a result of performing an action while in the vehicle.
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G06Q 50/40 - Business processes related to the transportation industry
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
6.
Neural net optimization of continuously variable powertrain
A method for optimizing a vehicle system involves using a neural network to optimize at least one operating parameter of a transmission portion of a continuously variable powertrain based at least in part on a classified current state of a vehicle, wherein the current state is associated with a predicted future vehicle state.
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G06Q 50/40 - Business processes related to the transportation industry
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
7.
Vehicle dynamics control using deep learning to update an operational parameter of a vehicle drive train
A system may include sensors, provided on a vehicle, to sense one or more operational states of the vehicle and output the sensed operational states. A system may include a cloud computing platform to receive the sensed operational states, a modeling application, provided at the cloud computing platform, having a processor to execute software to generate and operate a digital twin of the vehicle, the digital twin encompassing twin subsystems of the vehicle and simulating operations thereof; and an artificial intelligence system, associated with the cloud computing platform, to receive and process the sensed operational states and updates an operational parameter of the drive train of the vehicle based on the modeling application.
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05B 13/04 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
G06N 3/044 - Recurrent networks, e.g. Hopfield networks
A method for controlling a transportation system includes using an output from a device within a vehicle interior to update a command input to a transportation system in response to detecting a triggering condition from the device within the vehicle interior affecting the transportation system.
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05B 13/04 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
G06N 3/044 - Recurrent networks, e.g. Hopfield networks
A vehicle routing system and method involves coordinating a route for a vehicle to a geographic point of interest based at least in part on monitoring an action of a rider of a vehicle to determine if the action is among a plurality of actions classified as a rewardable action, and presenting a reward-based routing to the vehicle within a transportation system upon detection that the action of the rider is a rewardable action.
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G06F 40/40 - Processing or translation of natural language
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
G06Q 50/40 - Business processes related to the transportation industry
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
10.
Intelligent transportation systems including digital twin interface for a passenger vehicle
Transportation systems can represent a set of operating states of a vehicle to a user of the vehicle and generally include a system for representing a set of operating states of a vehicle to a user of the vehicle. The system includes a portion of the vehicle having a vehicle operating state; a digital twin system receiving vehicle parameter data from one or more inputs to determine the vehicle operating state; and an interface for the digital twin system to present the vehicle operating state to the user of the vehicle.
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05B 13/04 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
G06N 3/044 - Recurrent networks, e.g. Hopfield networks
A system may include a first neural network trained to determine an operating state of a vehicle from data about the vehicle captured in an operating environment of the vehicle, where the first neural network processes information about the vehicle captured by at least one Internet-of things device while the vehicle is operating. A data structure facilitates determining operating parameters configured to influence an operating state of a vehicle. A second neural network operates to: a) process information about a state of the rider occupying the vehicle, b) determine a correlation between the operating state and an effect on the state of the rider, and c) improve at least one of the determined operating parameters of the vehicle based on i) the determined operating state of the vehicle and ii) the correlation between the operating state of the vehicle and the effect on the state of the rider.
G06Q 50/40 - Business processes related to the transportation industry
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
12.
Vehicle having neural network based optimization system to vary an operating parameter and augmented reality content
A vehicle to operate with a rider according to an operating parameter. The vehicle includes a set of physiological monitoring sensors configured to measure a physiological parameter of a rider within the vehicle. The vehicle further includes a neural network trained on data related to a set of rider in-vehicle experiences to determine a state of the rider by processing outputs of the set of physiological monitoring sensors. The vehicle further includes an augmented or virtual reality system configured to present augmented reality content to the rider within the vehicle based, at least in part, on the physiological parameter. The vehicle further includes an optimization system to automatically identify a variation in the operating parameter to improve a measure of the state of the rider and generate a command to vary the operating parameter and the augmented reality content according to the variation.
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
13.
Optimizing a vehicle operating parameter based in part on a sensed emotional state of a rider
A system may include a first neural network to detect the state of the rider through expert system-based processing of rider state indicative wearable sensor data of a plurality of wearable physiological condition sensors worn by the rider in the vehicle, the state indicative wearable sensor data indicative of at least one of a first state of the rider and a second state of the rider. A system may include a second neural network to optimize, for at least one of achieving and maintaining a first state of the rider, the operating parameter of the vehicle in response to the detected state of the rider, wherein the second neural network optimizes the operational parameter based on a correlation between a vehicle operating state and a rider state, wherein the optimized operational parameter of the vehicle is determined and adjusted to induce the first state in the rider.
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G06Q 50/40 - Business processes related to the transportation industry
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
14.
AI-ENABLED SYSTEM FOR ADJUSTING OPERATION OF A VEHICLE AND COMMUNICATING EMOTIONAL STATE OF THE RIDER HAVING A FEEDBACK LOOP
A system may process a sensory input received from a wearable device in the vehicle to determine the state of the rider in the vehicle, may adjust an operating parameter of the vehicle to improve the state of the rider, and may indicate a change in the state of a rider in the vehicle via recognition of patterns of the wearable sensor data of the rider in the vehicle when compared with rider state patterns located in stored wearable sensor data. A feedback loop is included through which the indication of the change in the state of the rider is communicated between the vehicle control system and the artificial intelligence system, wherein the vehicle control system is further configured to adjust vehicle operating parameters in response to the indication of the change.
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
15.
Method of maintaining a favorable emotional state of a rider of a vehicle by a neural network to classify emotional state indicative wearable sensor data
A method of maintaining a favorable emotional state of a rider of a vehicle. The method includes: receiving emotional state indicative wearable sensor data of the rider in the vehicle; classifying, at a rider emotional state determining neural network, the emotional state indicative wearable sensor data and generating output data indicative of a classification of the rider emotional state as one of a favorable emotional state of the rider or an unfavorable emotional state of the rider; converting the output data from the rider emotional state determining neural network into a vehicle operational state datum; and adjusting a vehicle operating parameter in response to the vehicle operational state datum.
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G06Q 50/40 - Business processes related to the transportation industry
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
16.
TRANSPORTATION SYSTEM TO OPTIMIZE AN OPERATING PARAMETER OF A VEHICLE BASED ON A PHYSIOLOGICAL STATE OF AN OCCUPANT OF THE VEHICLE DETERMINED FROM IMAGES OF A FACE OF THE OCCUPANT
A transportation system to optimize an operating parameter of a vehicle based on a physiological state of an occupant of the vehicle. The transportation system includes a sensor to sense a physiological condition of the occupant and to output data based on the sensed physiological condition. The sensor includes an image capturing device to capture a set of images of a face of the occupant, and an image processing system to produce feature vectors from the set of images. The feature vectors are indicative of an emotional state of the occupant. The transportation system further includes an artificial intelligence system to receive and processes the data to determine an emotional state of the occupant and to optimize, for achieving a favorable emotional state of the occupant, at least one operating parameter of the vehicle in response to the detected emotional state of the occupant.
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G06F 40/40 - Processing or translation of natural language
G06N 3/04 - Architecture, e.g. interconnection topology
G06Q 50/40 - Business processes related to the transportation industry
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
17.
Transportation system to optimize an operating parameter of a vehicle based on a physiological state of an occupant of the vehicle determined from artificial intelligence analysis of a voice of the occupant
A transportation system optimizes an operating parameter of a vehicle based on a physiological state of an occupant of the vehicle. The transportation system includes a sensor to sense a physiological condition of the occupant and to output data based on the sensed physiological condition. The sensor includes a voice capture system to capture a voice of the occupant and includes the voice as at least part of the output data. The transportation system further includes an artificial intelligence system to receive the output data, classifies an emotional state of the captured voice based on analysis of aspects of the output data and processes the classified emotional state of the captured voice to determine an emotional state of the occupant and to optimize, for achieving a favorable emotional state of the occupant, at least one operating parameter of the vehicle in response to the determined emotional state of the occupant.
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
18.
Neural net-based use of perceptrons to mimic human senses associated with a vehicle occupant
A system for operating a vehicle based on a state of a rider includes an artificial intelligence system, a vehicle control system, and a feedback loop. The artificial intelligence system processes a sensory input from a wearable device in a vehicle to determine a state of a rider and optimizes an operating parameter of the vehicle to improve the state of the rider. The artificial intelligence system includes a neural net with a perceptron to mimic human senses to facilitate determining a state of a rider based on an extent to which at least one of the senses of the rider is stimulated. The vehicle control system adjusts vehicle operating parameters and the feedback loop indicates the change in the state of the rider, where the vehicle control system adjusts at least one of the plurality of vehicle operating parameters responsive to the indication of the change.
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G06Q 50/40 - Business processes related to the transportation industry
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
19.
Transportation system to use a neural network to determine a variation in driving performance to promote a desired hormonal state of an occupant
A transportation system includes: a neural network to determine current inferred hormonal state data of an occupant of the vehicle based in part on received sensor data relating to the occupant; and an artificial intelligence-based system trained on a set of outcomes related to occupant in-vehicle experience. The artificial intelligence-based system is configured to: retrieve sensor data of the occupant; identify a difference between the current inferred hormonal state data and a desired hormonal state; determine a variation including one of configuring the vehicle for aggressive driving performance or configuring the vehicle for non-aggressive driving performance to promote the desired hormonal state of the occupant responsive to the current inferred hormonal state; and induce the variation in one or more occupant experience parameters to achieve at least one desired outcome.
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G06Q 50/40 - Business processes related to the transportation industry
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
20.
Robotic process automation for achieving an optimized margin of vehicle operational safety
A system may include an operator data collection module to capture human operator interactions with a vehicle control system interface and may include a vehicle data collection module to capture vehicle response and operating conditions associated at least contemporaneously with the human operator interaction. An artificial intelligence system learns to control the vehicle with an optimized margin of safety while mimicking the human operator, where the artificial intelligence system is responsive to the robotic process automation system and the artificial intelligence system is to detect data indicative of at least one of a plurality of the instances of environmental information associated with the contemporaneously captured vehicle response and operating conditions. The optimized margin of safety is to be achieved by training the artificial intelligence system to control the vehicle based on the set of human operator interaction data collected at the robotic process automation system.
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/02 - Control of position or course in two dimensions
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G06Q 50/40 - Business processes related to the transportation industry
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
21.
METHOD FOR OPTIMIZING A STATE OF A RIDER OF A VEHICLE BASED ON USING A WEARABLE SENSOR TO DETECT A CHANGE IN EMOTIONAL STATE OF THE RIDER
A method of optimizing a state of a rider of a vehicle. The method includes: receiving data from a wearable sensor worn by the rider of the vehicle indicative of an emotional state of the rider; comparing the data received from the wearable sensor to stored wearable sensor data in which quantitative patterns present in the stored sensor data are labelled as emotional states; determining a pattern of an emotional state based on the data received from the wearable sensor and the comparison to the stored wearable sensor data; detecting a change in emotional state of the rider based on a detected change in the data received from the wearable sensor indicative of a change in the emotional state of the rider; and adjusting an operational parameter of the vehicle in real time in response to the detected change in the emotional state of the rider.
G05D 1/226 - Communication links with the remote-control arrangements
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G05D 1/646 - Following a predefined trajectory, e.g. a line marked on the floor or a flight path
G05D 1/69 - Coordinated control of the position or course of two or more vehicles
G06F 40/40 - Processing or translation of natural language
G06N 3/04 - Architecture, e.g. interconnection topology
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
22.
HYBRID NEURAL NETWORK FOR DETERMINING AT LEAST ONE PARAMETER OF A CHARGING PLAN FOR A VEHICLE
A method of executing a charging plan for at least one vehicle in a transportation system includes: receiving, at a charging infrastructure control system, operational state and energy consumption information for a plurality of network-enabled vehicles; predicting a geolocation of one or more vehicles of the plurality of network-enabled vehicles in a geographic region; allocating the one or more vehicles of the plurality of network-enabled vehicles to charging infrastructure in the geographic region; and optimizing, at an artificial intelligence system, a parameter of the charging plan based on the prediction of the geolocation of the one or more vehicles in the geographic region.
G05D 1/226 - Communication links with the remote-control arrangements
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/225 - Remote-control arrangements operated by off-board computers
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
23.
Transportation system to optimize an operating parameter of a vehicle based on an emotional state of an occupant of the vehicle determined from a sensor to detect a physiological condition of the occupant
A transportation system to optimize an operating parameter of a vehicle based on a physiological state of an occupant of the vehicle. The transportation system includes a sensor to sense a physiological condition of the occupant and to output data based on the sensed physiological condition. The sensor includes a movement sensor to detect physical actions of the vehicle occupant. The transportation system further includes a real-time control system to receive and process the data to determine an emotional state of the occupant based on the detected physical actions and to optimize, for achieving a favorable emotional state of the occupant, at least one operating parameter of the vehicle in response to the detected emotional state of the occupant.
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G06Q 50/40 - Business processes related to the transportation industry
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
24.
Robotic process automation for achieving an optimized margin of vehicle operational safety
A system may collect human operator interactions with a vehicle control system interface operatively connected to a vehicle, and may collect vehicle response and operating conditions associated at least contemporaneously with the human operator interaction. Environmental information is collected contemporaneously with the human operator interaction. An artificial intelligence system is trained to control the vehicle with an optimized margin of safety while mimicking the human operator, the training including instructing the artificial intelligence system to take input from an environment data collection module about instances of environmental information associated with the contemporaneously collected vehicle response and operating conditions, where the optimized margin of safety is achieved by training the artificial intelligence system to control the vehicle based on a set of human operator interaction data collected from interactions of an expert human vehicle operator and a set of outcome data from a set of vehicle safety events.
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G06Q 50/40 - Business processes related to the transportation industry
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
25.
Social data sources feeding a neural network to predict an emerging condition relevant to a transportation plan of at least one individual
A system may receive social data from a plurality of social data sources. A system may process the social data using semantic analysis to detect keywords in the social data indicative of a group transportation need. A system may identify a plurality of individuals who share a group transportation need. A system may predict the group transportation need using a neural network trained to predict transportation needs based on the detected keywords. A system may provide a transportation recommendation based on the prediction.
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G06Q 50/40 - Business processes related to the transportation industry
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
26.
Using social media data of a vehicle occupant to alter a route plan of the vehicle
A method of altering an operating state of a transportation system may include: receiving social data from a plurality of social data sources about at least one occupant of a vehicle of the transportation system; analyzing, at a first neural network, the social data and associating the social data with a route plan for the vehicle occupied by the at least one occupant; predicting, by the first neural network, an effect on a satisfaction of the at least one occupant based on the route plan of the vehicle through an analysis of the social data; and altering, by the first neural network, a route plan of the transportation system responsive to the predicted effect.
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G06Q 50/40 - Business processes related to the transportation industry
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
27.
IOT SYSTEM FOR DETERMINING AND OPTIMIZING AN OPERATING PARAMETER
A system for improving a state of a rider in a vehicle includes at least one Internet-of-Things (IoT) device and an artificial intelligence system. The at least one IoT device in disposed in the environment of the vehicle, the at least one IoT device to sense and output data based on at least one of: a state of the rider, a state of the vehicle environment, or a state of the vehicle. The artificial intelligence system for processing the data output by the at least one IoT device to determine a determined state of the vehicle and to improve the at least one operating parameter of the vehicle to improve the state of the rider based on the determined state of the vehicle.
G05D 1/24 - Arrangements for determining position or orientation
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
28.
Robotic process automation system trained to undertake actions with a vehicle based on user interactions with a user interface of the vehicle
A method of operating a vehicle in a transportation system includes: receiving data collected for each of a set of users based on interactions of the set of users with a user interface of the vehicle including at least one of a vehicle data system, a vision system, and a connected system; performing robotic process automation on the interactions; learning changes in driving style using an artificial intelligence system based on the robotic process automation; and undertaking an action within the vehicle on behalf of the user based on the learned changes in driving style.
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G06Q 50/40 - Business processes related to the transportation industry
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
29.
DIGITAL TWIN SIMULATION SYSTEM AND A COGNITIVE INTELLIGENCE SYSTEM FOR VEHICLE FLEET MANAGEMENT AND EVALUATION
A system may include a digital twin management system to one of create, maintain, or render a digital twin based on received sensor data from one or more sensor systems associated with a vehicle. A system may include a digital twin simulation system to execute vehicle performance simulations using the digital twin by adjusting one or more vehicle performance parameters of the digital twin, and collect simulation outcome data resulting from the simulation. A system may include a cognitive process system to train machine learned models using vehicle performance simulation outcome data and makes predictions for providing decision support related to a simulated performance parameter to minimize a cost criterion associated with operating the vehicle.
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05B 13/04 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
G06N 3/044 - Recurrent networks, e.g. Hopfield networks
A system may include an artificial intelligence system for processing data output by at least one Internet-of-Things device associated with the vehicle, wherein the at least one Internet-of-Things device is configured to sense and output data based on at least one of: a state of the rider, a state of the vehicle environment, or a state of the vehicle, and wherein the artificial intelligence system is configured to determine a determined state of the vehicle and to adjust the at least one operating parameter of the vehicle to improve the state of the rider based on the determined state of the vehicle.
G05D 1/24 - Arrangements for determining position or orientation
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
31.
TRANSPORTATION SYSTEMS WITH RIDER SATISFACTION OPTIMIZATION INCLUDING CLOSED LOOP REINFORCEMENT
Improving satisfaction of a rider of a vehicle includes: receiving biometric data from a sensor of a biometric parameter of the rider indicative of a physiological condition of the rider; determining, at a first neural network, a predicted emotional state of the rider based on the biometric data; in response to determining the predicted emotional state of the rider: determining a current operating state of the vehicle; determining, by a second neural network, a corrective operating state for the vehicle based on the predicted emotional state and the current operating state to improve the emotional state of the rider; outputting the set of corrective operating parameters to a vehicle controller; receiving second biometric data from the sensor after the vehicle is operating in the corrective operating state; and updating the second neural network based on the predicted emotional state, the corrective operating state, and the second biometric data.
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/02 - Control of position or course in two dimensions
G06F 40/40 - Processing or translation of natural language
G06N 3/04 - Architecture, e.g. interconnection topology
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
32.
VEHICLE RIDER SATISFACTION PROMOTING SYSTEMS BASED ON ADJUSTING OPERATING PARAMETERS OF THE VEHICLE
Data processing systems disclosed herein may promote satisfaction of a rider of a vehicle and include a machine learning model and a vehicle control system. The machine learning model determines a measure of an emotional state of the rider based on data received from a sensor associated with the rider, where the data is indicative of a physiological condition of the rider. The vehicle control system: determines a target value of an operating parameter of the vehicle based on a correlation between the emotional state of the rider and the target value of the operating parameter; and adjusts the operating parameter of the vehicle based on the target value of the operating parameter.
G06N 3/086 - Learning methods using evolutionary algorithms, e.g. genetic algorithms or genetic programming
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G01C 21/36 - Input/output arrangements for on-board computers
G06Q 30/0208 - Trade or exchange of goods or services in exchange for incentives or rewards
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G06F 40/40 - Processing or translation of natural language
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/02 - Control of position or course in two dimensions
G06N 3/04 - Architecture, e.g. interconnection topology
A transportation system, that optimizes at least one operating parameter of a vehicle based on a physiological state of an occupant of the vehicle, includes a sensor that senses a physiological condition of the occupant and that outputs data based on the sensed physiological condition. The transportation system further includes an artificial intelligence system that receives and processes the data to determine an emotional state of the occupant, and optimizes, for achieving a favorable emotional state of the occupant, the at least one operating parameter of the vehicle in response to detecting the emotional state of the occupant.
G06N 3/086 - Learning methods using evolutionary algorithms, e.g. genetic algorithms or genetic programming
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G01C 21/36 - Input/output arrangements for on-board computers
G06Q 30/0208 - Trade or exchange of goods or services in exchange for incentives or rewards
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G06F 40/40 - Processing or translation of natural language
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/02 - Control of position or course in two dimensions
G06N 3/04 - Architecture, e.g. interconnection topology
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
34.
Augmented reality in a vehicle configured for changing an emotional state of a rider
Vehicles and methods described herein include a vehicle that operates with a rider according to an operating parameter. The vehicle includes: a physiological monitoring sensor configured to measure a physiological parameter of the rider; an experience hybrid neural network trained on outcomes related to a rider in-vehicle experience associated with the physiological parameter to determine an emotional state of the rider; an augmented reality system configured to present augmented reality content to the rider of the vehicle based, at least in part, on the operating parameter; and an optimization hybrid neural network that identifies a variation in the operating parameter to change the emotional state of the rider and that generates a command to vary the operating parameter and the augmented reality content according to the variation.
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G06F 40/40 - Processing or translation of natural language
G06N 3/04 - Architecture, e.g. interconnection topology
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
35.
Parameters of augmented reality responsive to location or orientation based on rider or vehicle
A vehicle includes a display disposed to facilitate presenting an augmentation of content in an environment of a rider of the vehicle; a circuit for registering at least one of location and orientation of the vehicle; a machine learning circuit that determines at least one augmentation parameter by processing at least one input relating to at least one of the rider and the vehicle; and a reality augmentation circuit that, responsive to the at least one of the location or the orientation of the vehicle, generates an augmentation element for presenting in the display, the generating based at least in part on the at least one augmentation parameter.
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G01C 21/36 - Input/output arrangements for on-board computers
G06Q 30/0208 - Trade or exchange of goods or services in exchange for incentives or rewards
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G06F 40/40 - Processing or translation of natural language
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/02 - Control of position or course in two dimensions
G06N 3/04 - Architecture, e.g. interconnection topology
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
36.
Augmented reality rider interface responsive to location or orientation of the vehicle
A rider interface for a vehicle includes a data processor configured to facilitate communication between a rider using the rider interface and the vehicle, the vehicle and the rider interface communicating location and orientation of the vehicle. An augmented reality system with a display is disposed to facilitate presenting an augmentation of content in an environment of the rider using the rider interface, the augmentation responsive to a registration of the communicated location and orientation of the vehicle, wherein at least one parameter of the augmentation is determined by machine learning on at least one input relating to at least one of the rider and the rider interface.
G06N 3/086 - Learning methods using evolutionary algorithms, e.g. genetic algorithms or genetic programming
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G01C 21/36 - Input/output arrangements for on-board computers
G06Q 30/0208 - Trade or exchange of goods or services in exchange for incentives or rewards
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G06F 40/40 - Processing or translation of natural language
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/02 - Control of position or course in two dimensions
G06N 3/04 - Architecture, e.g. interconnection topology
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
37.
Artificial intelligence system for processing voice of rider to improve emotional state and optimize operating parameter of vehicle
A system for transportation includes a vehicle occupied by a rider, and an artificial intelligence system for processing a voice of the rider to classify an emotional state of the rider and optimizing at least one operating parameter of the vehicle to improve the emotional state of the rider.
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G06Q 50/40 - Business processes related to the transportation industry
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
The present disclosure relates to transportation and related methods and systems including vehicle operating states, an identity management system, an intelligent digital twin system that creates, manages, and provides digital twins for transportation systems using sensor data and other data, quantum computing methods and systems, including a set of quantum computing services, and biology-based systems and methods for communicating and/or handling data.
The present disclosure relates to transportation and related methods and systems including vehicle operating states, an identity management system, an intelligent digital twin system that creates, manages, and provides digital twins for transportation systems using sensor data and other data, quantum computing methods and systems, including a set of quantum computing services, and biology-based systems and methods for communicating and/or handling data.
A system for transportation includes a vehicle interface for gathering physiological sensed data of a rider in the vehicle. The system includes an artificial intelligence-based circuit that is trained on a set of outcomes related to rider in-vehicle experience and that induces, responsive to the sensed rider physiological data, variation in one or more of the user experience parameters to achieve at least one desired outcome in the set of outcomes. The inducing variation includes control of timing and extent of the variation.
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G01C 21/36 - Input/output arrangements for on-board computers
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G06F 40/40 - Processing or translation of natural language
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/02 - Control of position or course in two dimensions
G06N 3/04 - Architecture, e.g. interconnection topology
A system for representing a set of operating states of a vehicle to a user of the vehicle includes a vehicle having a vehicle operating state, and a digital twin receiving vehicle parameter data from one or more inputs to determine the vehicle operating state. An interface for the digital twin presents the vehicle operating state to the user of the vehicle. An identity management system manages a set of identities and roles of the vehicle user and determines capabilities to view, modify, and configure the digital twin based on parsing of the set of identities and roles.
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05B 13/04 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
G06N 3/044 - Recurrent networks, e.g. Hopfield networks
A system for representing attributes in a transportation system digital twin includes a digital twin datastore and one or more processors. The digital twin datastore stores a transportation-system digital twin including real-world-element digital twins embedded therein. The transportation system digital twin corresponds to a transportation system. Each real-world-element digital twin provides a digital twin of a respective real-world element that is disposed within the transportation system. The real-world-element digital twins include mobile-element digital twins. Each mobile-element digital twin provides a digital twin of a respective mobile element within the real-world elements. The one or more processors are configured to, for each mobile element, determine, in response to an occurrence of a triggering condition, a position of the mobile element, and update, in response to determining the position of the mobile element, the mobile-element digital twin corresponding to the mobile element to reflect the position of the mobile element.
A method of robotic process automation for achieving an optimized margin of vehicle operational safety includes tracking expert vehicle control human interactions with a vehicle control-facilitating interface, and recording the tracked expert vehicle control human interactions in a robotic process automation system training data structure. The method further includes tracking vehicle operational state information of a vehicle, and recording vehicle operational state information in the robotic process automation system training data structure. The method further includes training, via at least one neural network, the vehicle to operate with an optimized margin of vehicle operational safety in a manner consistent with the expert vehicle control human interactions based on the expert vehicle control human interactions and the vehicle operational state information in the robotic process automation system training data structure, and controlling at least one aspect of the vehicle with the trained artificial intelligence system.
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G06Q 50/40 - Business processes related to the transportation industry
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
44.
Expert system for vehicle configuration recommendations of vehicle or user experience parameters
A system for transportation includes a vehicle configured to have a rider located therein or thereon, and an expert system to produce a recommendation for a configuration of the vehicle, wherein the recommendation includes at least one recommended parameter of configuration for the expert system that controls a parameter selected from the group consisting of a vehicle parameter, a rider experience parameter, and combinations thereof.
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G06Q 50/40 - Business processes related to the transportation industry
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
45.
Using neural network to optimize operational parameter of vehicle while achieving favorable emotional state of rider
A system for transportation includes a vehicle, a rider occupying the vehicle, and a hybrid neural network. The hybrid neural network includes a first neural network to process a sensor input corresponding to the rider to determine an emotional state of the rider, and a second neural network to optimize at least one operating parameter of the vehicle to improve the emotional state of the rider.
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G06Q 50/40 - Business processes related to the transportation industry
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
46.
Wearable device determining emotional state of rider in vehicle and optimizing operating parameter of vehicle to improve emotional state of rider
A transportation system includes an artificial intelligence system for processing a sensory input from a wearable device in a self-driving vehicle to determine an emotional state of a rider and optimizing a vehicle operating parameter to improve the rider emotional state. The artificial intelligence system detects the rider emotional state in the self-driving vehicle by recognition of patterns of emotional state indicative data from a set of wearable sensors worn by the rider. The patterns are indicative of at least one of a favorable emotional state and an unfavorable emotional state of the rider. The artificial intelligence system is to optimize, for achieving at least one of maintaining a detected favorable emotional state of the rider and achieving a favorable emotional state of a rider subsequent to a detection of an unfavorable emotional state, the operating parameter of the vehicle in response to the detected emotional state of the rider.
G06N 3/086 - Learning methods using evolutionary algorithms, e.g. genetic algorithms or genetic programming
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G01C 21/36 - Input/output arrangements for on-board computers
G06Q 30/0208 - Trade or exchange of goods or services in exchange for incentives or rewards
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G06F 40/40 - Processing or translation of natural language
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/02 - Control of position or course in two dimensions
G06N 3/04 - Architecture, e.g. interconnection topology
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
47.
Radial basis function neural network optimizing operating parameter of vehicle based on emotional state of rider determined by recurrent neural network
A transportation system includes an artificial intelligence (AI) system for processing a sensory input from a wearable device in a self-driving vehicle to determine an emotional state of a rider and optimizing a vehicle operating parameter to improve the rider emotional state. The AI system includes a recurrent neural network to indicate a change in the emotional state of the rider by a recognition of patterns of emotional state indicative wearable sensor data from a set of wearable sensors worn by the rider. The patterns are indicative of a first degree of a favorable emotional state of the rider and/or a second degree of an unfavorable emotional state of the rider. The AI system further includes a radial basis function neural network to optimize, for achieving a target emotional state of the rider, the vehicle operating parameter in response to the indication of the change in the rider emotional state.
G06N 3/086 - Learning methods using evolutionary algorithms, e.g. genetic algorithms or genetic programming
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G01C 21/36 - Input/output arrangements for on-board computers
G06Q 30/0208 - Trade or exchange of goods or services in exchange for incentives or rewards
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G06F 40/40 - Processing or translation of natural language
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/02 - Control of position or course in two dimensions
G06N 3/04 - Architecture, e.g. interconnection topology
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
48.
Augmented reality for motorcycle helmet responsive to location or orientation of the motorcycle
A motorcycle helmet includes a data processor configured to facilitate communication between a rider wearing the helmet and a motorcycle, the motorcycle and the helmet communicating location and orientation of the motorcycle. An augmented reality system with a display is disposed to facilitate presenting an augmentation of content in an environment of a rider wearing the helmet, the augmentation responsive to a registration of the communicated location and orientation of the motorcycle At least one parameter of the augmentation is determined by machine learning on at least one input relating to at least one of the rider and the motorcycle.
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G06F 40/40 - Processing or translation of natural language
G05D 1/02 - Control of position or course in two dimensions
G07C 5/00 - Registering or indicating the working of vehicles
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G06N 3/04 - Architecture, e.g. interconnection topology
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
49.
Three different neural networks to optimize the state of the vehicle using social data
A method of optimizing an operating state of a vehicle includes classifying, using a first neural network of a hybrid neural network, social media data sourced from a plurality of social media sources as affecting a transportation system. The method further includes predicting, using a second neural network of the hybrid neural network, one or more effects of the classified social media data on the transportation system. The method further includes optimizing, using a third neural network of the hybrid neural network, a state of at least one vehicle of the transportation system, wherein the optimizing addresses an influence of the predicted one or more effects on the at least one vehicle.
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G06Q 50/40 - Business processes related to the transportation industry
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
50.
Neural network for improving the state of a rider in intelligent transportation systems
A rider state modification system for improving a state of a rider in a vehicle includes a first neural network that operates to classify a state of the vehicle through analysis of information about the vehicle captured by an Internet-of-things device during operation of the vehicle. The rider state modification system further includes a second neural network that operates to optimize at least one operating parameter of the vehicle based on the classified state of the vehicle, information about a state of a rider occupying the vehicle, and information that correlates vehicle operation with an effect on rider state.
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G06Q 50/40 - Business processes related to the transportation industry
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
51.
Inducing variation in user experience parameters based on outcomes that promote rider safety in intelligent transportation systems
A system for transportation includes a vehicle interface for gathering hormonal state data of a rider in the vehicle. The system further includes an artificial intelligence-based circuit that is trained on a set of outcomes related to rider in-vehicle experience and that induces, responsive to the sensed rider hormonal state data, variation in one or more of the user experience parameters to achieve at least one desired outcome in the set of outcomes. The set of outcomes includes at least one outcome that promotes rider safety. The inducing variation includes control of timing and extent of the variation.
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G06Q 50/40 - Business processes related to the transportation industry
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
52.
Artificial intelligence system trained by robotic process automation system automatically controlling vehicle for user
A system for transportation includes a vehicle having a user interface, and a robotic process automation system wherein a set of data is captured for each user in a set of users as each user interacts with the user interface, and wherein an artificial intelligence system is trained using the set of data to interact with the vehicle to automatically undertake actions with the vehicle on behalf of the user.
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/02 - Control of position or course in two dimensions
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
53.
Hybrid neural networks sourcing social data sources to optimize satisfaction of rider in intelligent transportation systems
A system for transportation includes a vehicle having at least one rider located in the vehicle and a data processing system for taking data from a plurality of social data sources. A hybrid neural network is connected to the data processing system. The system for transportation is to optimize satisfaction of the at least one rider based on processing the data from the plurality of social data sources with the hybrid neural network.
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
Transportation systems have artificial intelligence including neural networks for recognition and classification of objects and behavior including natural language processing and computer vision systems. The transportation systems involve sets of complex chemical processes, mechanical systems, and interactions with behaviors of operators. System-level interactions and behaviors are classified, predicted and optimized using neural networks and other artificial intelligence systems through selective deployment, as well as hybrids and combinations of the artificial intelligence systems, neural networks, expert systems, cognitive systems, genetic algorithms and deep learning.
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G06Q 50/40 - Business processes related to the transportation industry
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
A system for transportation includes a self-driving vehicle, an artificial intelligence (AI) system in communication with the vehicle, and a vehicle routing system to plan a planned route for the vehicle to meet a common transportation need. The vehicle is to autonomously follow the planned route. The AI system includes a data processing system to gather social media-sourced data about a plurality of individuals, the data being sourced from a plurality of social media sources, process the data to identify a subset of the individuals who form a social group based on group affiliation references in the data, and detect keywords in the data indicative of the transportation need. A neural network is trained to predict transportation needs based on the detected keywords to identify the common transportation need for the subset of the individuals.
G06Q 10/02 - Reservations, e.g. for tickets, services or events
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G06F 40/40 - Processing or translation of natural language
G06N 3/04 - Architecture, e.g. interconnection topology
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
A system for transportation, includes at least one vehicle and an artificial intelligence (AI) system in communication with the at least one vehicle. The AI system is operative on at least one processor having access to a non-transitory storage medium that stores computer executable instructions to be executed by the at least one processor. The AI system includes a first neural network of a hybrid neural network to classify social media data sourced from a plurality of social media sources as affecting a transportation system, a second neural network of the hybrid neural network to predict at least one vehicle-operating objective of the transportation system based on the classified social media data, and a third neural network of the hybrid neural network to optimize a state of the at least one vehicle in the transportation system to achieve the at least one vehicle-operating objective of the transportation system.
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G06F 40/40 - Processing or translation of natural language
G06N 3/04 - Architecture, e.g. interconnection topology
G06Q 50/40 - Business processes related to the transportation industry
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
A rider satisfaction system for optimizing rider satisfaction, the rider satisfaction system includes an electronic commerce interface deployed for access by a rider in a vehicle, and a rider interaction circuit that captures rider interactions with the deployed interface. The rider satisfaction system also includes a rider state determination circuit that processes the captured rider interactions to determine a rider state, and an artificial intelligence system trained to optimize, responsive to the rider state, at least one parameter affecting operation of the vehicle to improve the rider state.
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G06F 40/40 - Processing or translation of natural language
G05D 1/02 - Control of position or course in two dimensions
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G07C 5/00 - Registering or indicating the working of vehicles
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G06N 3/04 - Architecture, e.g. interconnection topology
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
A method for updating one or more properties of one or more transportation system digital twins includes receiving a request to update the one or more transportation system digital twins; retrieving the one or more transportation system digital twins to fulfill the request from a digital twin datastore; and retrieving one or more dynamic models to fulfill the request from a dynamic model datastore. The method further includes selecting data sources from a set of available data sources for one or more inputs for the one or more dynamic models; retrieving data from the selected data sources; running the one or more dynamic models using the retrieved data as input data to determine one or more output values; and updating the one or more properties of the one or more transportation system digital twins based on the one or more output values of the one or more dynamic models.
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
59.
INTELLIGENT TRANSPORTATION SYSTEMS INCLUDING DIGITAL TWIN INTERFACE FOR A PASSENGER VEHICLE
Transportation systems can represent a set of operating states of a vehicle to a user of the vehicle and generally include a system for representing a set of operating states of a vehicle to a user of the vehicle. The system includes a portion of the vehicle having a vehicle operating state; a digital twin system receiving vehicle parameter data from one or more inputs to determine the vehicle operating state; and an interface for the digital twin system to present the vehicle operating state to the user of the vehicle.
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
A hybrid neural network for rider satisfaction includes a first neural network to detect a detected satisfaction state of a rider occupying a vehicle through analysis of data gathered from sensors deployed in the vehicle for gathering physiological conditions of the rider. The hybrid neural network further includes a second neural network to optimize, for achieving a favorable satisfaction state of the rider, an operational parameter of the vehicle in response to the detected satisfaction state of the rider.
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/646 - Following a predefined trajectory, e.g. a line marked on the floor or a flight path
G05D 1/692 - Coordinated control of the position or course of two or more vehicles involving a plurality of disparate vehicles
G06F 40/40 - Processing or translation of natural language
G06N 3/04 - Architecture, e.g. interconnection topology
G06Q 50/40 - Business processes related to the transportation industry
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
A method of optimizing rider satisfaction includes classifying, using a first neural network of a hybrid neural network, social media data sourced from a plurality of social media sources as indicative of an effect on a transportation system. The method further includes predicting, using a second neural network of the hybrid neural network, at least one aspect of rider satisfaction affected by an effect on the transportation system derived from the social media data classified as indicative of an effect on the transportation system. The method still further includes optimizing, using a third neural network of the hybrid neural network, the at least one aspect of rider satisfaction for at least one rider occupying a vehicle in the transportation system.
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G05D 1/02 - Control of position or course in two dimensions
G06F 40/40 - Processing or translation of natural language
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
62.
Artificial intelligence system for vehicle in-seat advertising
An artificial intelligence system for vehicle in-seat advertising includes a first portion of the artificial intelligence system that determines an operating state of the vehicle by processing inputs relating to at least one parameter of the vehicle. A second portion of the artificial intelligence system determines a state of a rider of the vehicle by processing inputs relating to at least one parameter of the rider. A third portion of the artificial intelligence system determines at least one of a price, classification, content and location of an advertisement to be delivered within an interface of the vehicle to a rider in a seat in the vehicle based on the vehicle state and the rider state.
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G06Q 50/40 - Business processes related to the transportation industry
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
63.
HYBRID NEURAL NETWORK SYSTEM FOR TRANSPORTATION SYSTEM OPTIMIZATION
A hybrid neural network system for transportation system optimization includes a hybrid neural network. The hybrid neural network includes a first neural network that predicts a localized effect on a transportation system through analysis of social medial data sourced from a plurality of social media data sources. The hybrid neural network further includes a second neural network that optimizes an operating state of the transportation system based on the predicted localized effect.
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G06F 40/40 - Processing or translation of natural language
G05D 1/02 - Control of position or course in two dimensions
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G07C 5/00 - Registering or indicating the working of vehicles
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G06N 3/04 - Architecture, e.g. interconnection topology
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
A method for improving a state of a rider through optimization of operation of a vehicle includes capturing vehicle operation-related data with at least one Internet-of-things device, and analyzing the captured data with a first neural network that determines a state of the vehicle based at least in part on a portion of the captured vehicle operation-related data. The method further includes receiving data descriptive of a state of a rider occupying the operating vehicle, and using a neural network to determine at least one vehicle operating parameter that affects a state of a rider occupying the operating vehicle. The method still further includes using an artificial intelligence-based system to optimize the at least one vehicle operating parameter so that a result of the optimizing includes an improvement in the state of the rider.
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G06Q 50/40 - Business processes related to the transportation industry
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
65.
Recommendation system for recommending a configuration of a vehicle
A recommendation system for recommending a configuration of a vehicle includes an expert system that produces a recommendation of a parameter for configuring a vehicle control system that controls at least one of a vehicle parameter and a vehicle rider experience parameter.
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/02 - Control of position or course in two dimensions
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G06Q 50/40 - Business processes related to the transportation industry
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
Transportation systems have artificial intelligence including neural networks for recognition and classification of objects and behavior including natural language processing and computer vision systems. The transportation systems involve sets of complex chemical processes, mechanical systems, and interactions with behaviors of operators. System-level interactions and behaviors are classified, predicted and optimized using neural networks and other artificial intelligence systems through selective deployment, as well as hybrids and combinations of the artificial intelligence systems, neural networks, expert systems, cognitive systems, genetic algorithms and deep learning.
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G06Q 50/40 - Business processes related to the transportation industry
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
Transportation systems have artificial intelligence including neural networks for recognition and classification of objects and behavior including natural language processing and computer vision systems. The transportation systems involve sets of complex chemical processes, mechanical systems, and interactions with behaviors of operators. System-level interactions and behaviors are classified, predicted and optimized using neural networks and other artificial intelligence systems through selective deployment, as well as hybrids and combinations of the artificial intelligence systems, neural networks, expert systems, cognitive systems, genetic algorithms and deep learning.
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G06Q 50/40 - Business processes related to the transportation industry
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
Transportation systems have artificial intelligence including neural networks for recognition and classification of objects and behavior including natural language processing and computer vision systems. The transportation systems involve sets of complex chemical processes, mechanical systems, and interactions with behaviors of operators. System-level interactions and behaviors are classified, predicted and optimized using neural networks and other artificial intelligence systems through selective deployment, as well as hybrids and combinations of the artificial intelligence systems, neural networks, expert systems, cognitive systems, genetic algorithms and deep learning.
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G05D 1/224 - Output arrangements on the remote controller, e.g. displays, haptics or speakers
G05D 1/225 - Remote-control arrangements operated by off-board computers
G05D 1/226 - Communication links with the remote-control arrangements
G05D 1/227 - Handing over between remote control and on-board controlHanding over between remote control arrangements
G05D 1/228 - Command input arrangements located on-board unmanned vehicles
G06Q 50/40 - Business processes related to the transportation industry
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G07C 5/00 - Registering or indicating the working of vehicles
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
Transportation systems have artificial intelligence including neural networks for recognition and classification of objects and behavior including natural language processing and computer vision systems. The transportation systems involve sets of complex chemical processes, mechanical systems, and interactions with behaviors of operators. System-level interactions and behaviors are classified, predicted and optimized using neural networks and other artificial intelligence systems through selective deployment, as well as hybrids and combinations of the artificial intelligence systems, neural networks, expert systems, cognitive systems, genetic algorithms and deep learning.
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G07C 5/00 - Registering or indicating the working of vehicles
G06N 3/086 - Learning methods using evolutionary algorithms, e.g. genetic algorithms or genetic programming
G01C 21/36 - Input/output arrangements for on-board computers
G06Q 30/0208 - Trade or exchange of goods or services in exchange for incentives or rewards
G10L 15/16 - Speech classification or search using artificial neural networks
G10L 25/63 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for estimating an emotional state
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G06F 40/40 - Processing or translation of natural language
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G06N 3/04 - Architecture, e.g. interconnection topology
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
Transportation systems have artificial intelligence including neural networks for recognition and classification of objects and behavior including natural language processing and computer vision systems. The transportation systems involve sets of complex chemical processes, mechanical systems, and interactions with behaviors of operators. System-level interactions and behaviors are classified, predicted and optimized using neural networks and other artificial intelligence systems through selective deployment, as well as hybrids and combinations of the artificial intelligence systems, neural networks, expert systems, cognitive systems, genetic algorithms and deep learning.
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G06F 40/40 - Processing or translation of natural language
G05D 1/02 - Control of position or course in two dimensions
G07C 5/00 - Registering or indicating the working of vehicles
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G06N 3/04 - Architecture, e.g. interconnection topology
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
Transportation systems have artificial intelligence including neural networks for recognition and classification of objects and behavior including natural language processing and computer vision systems. The transportation systems involve sets of complex chemical processes, mechanical systems, and interactions with behaviors of operators. System-level interactions and behaviors are classified, predicted and optimized using neural networks and other artificial intelligence systems through selective deployment, as well as hybrids and combinations of the artificial intelligence systems, neural networks, expert systems, cognitive systems, genetic algorithms and deep learning.
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/02 - Control of position or course in two dimensions
G06F 40/40 - Processing or translation of natural language
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
G06V 20/59 - Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
Transportation systems have artificial intelligence including neural networks for recognition and classification of objects and behavior including natural language processing and computer vision systems. The transportation systems involve sets of complex chemical processes, mechanical systems, and interactions with behaviors of operators. System-level interactions and behaviors are classified, predicted and optimized using neural networks and other artificial intelligence systems through selective deployment, as well as hybrids and combinations of the artificial intelligence systems, neural networks, expert systems, cognitive systems, genetic algorithms and deep learning.
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/02 - Control of position or course in two dimensions
G06F 40/40 - Processing or translation of natural language
G06N 3/04 - Architecture, e.g. interconnection topology
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
Transportation systems have artificial intelligence including neural networks for recognition and classification of objects and behavior including natural language processing and computer vision systems. The transportation systems involve sets of complex chemical processes, mechanical systems, and interactions with behaviors of operators. System-level interactions and behaviors are classified, predicted and optimized using neural networks and other artificial intelligence systems through selective deployment, as well as hybrids and combinations of the artificial intelligence systems, neural networks, expert systems, cognitive systems, genetic algorithms and deep learning.
B60W 20/12 - Controlling the power contribution of each of the prime movers to meet required power demand using control strategies taking into account route information
B60W 30/08 - Predicting or avoiding probable or impending collision
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
B60W 40/12 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to parameters of the vehicle itself
B60W 50/08 - Interaction between the driver and the control system
Transportation systems have artificial intelligence including neural networks for recognition and classification of objects and behavior including natural language processing and computer vision systems. The transportation systems involve sets of complex chemical processes, mechanical systems, and interactions with behaviors of operators. System-level interactions and behaviors are classified, predicted and optimized using neural networks and other artificial intelligence systems through selective deployment, as well as hybrids and combinations of the artificial intelligence systems, neural networks, expert systems, cognitive systems, genetic algorithms and deep learning.
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G06F 40/40 - Processing or translation of natural language
G05D 1/02 - Control of position or course in two dimensions
G07C 5/00 - Registering or indicating the working of vehicles
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G06N 3/04 - Architecture, e.g. interconnection topology
G07C 5/02 - Registering or indicating driving, working, idle, or waiting time only
G06Q 30/02 - MarketingPrice estimation or determinationFundraising
G06Q 50/00 - Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
patents
