This technology provides an Autonomous Vehicle (AV) Control System that includes a sensing module for gathering driving environment data and an onboard unit (OBU) for vehicle control. The OBU fuses data from the vehicle and data from a Traffic Control Center/Traffic Control Unit (TCC/TCU), a Roadside Unit (RSU), or another vehicle. The OBU comprises a vehicle control module and communication modules for information exchange with TCC/TCU, RSU, or another vehicle. The AV control system receives targeted guidance instructions and information, such as vehicle maneuvering, safety maintenance, traffic control, and special conditions, to enhance driving tasks. The AV control system collaborates with TCC/TCU, RSU, or another AV, which provides redundancy and a fail-safe mechanism for increased safety and reliability. The system is designed with wireless communication capabilities for efficient information exchange and is applicable to autonomous vehicles (AVs).
G08G 1/0968 - Systems involving transmission of navigation instructions to the vehicle
H04L 67/00 - Network arrangements or protocols for supporting network services or applications
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
Provided herein is technology relating to automated driving, particularly, but not exclusively, to an enterprise active safety system (EASS) that is configured to improve safety or minimize losses from safety events. More specifically, the EASS is configured to provide system-based safety functions by integrating one or more of the vehicle components, road components, cloud components, pedestrian components, and map components. These safety functions include one or more of crash detection, crash prediction, crash warning, crash avoidance, crash impact reduction, and emergency response functions.
The technology provides designs and methods for the transit management system, which facilitates transit vehicle operations and control for connected automated transit vehicles (CATVs) systems. The transit management system provides transit vehicles with customized/non-customized information and time-sensitive control instructions for transit vehicle to fulfill the driving tasks such as vehicle routing, lane changing, turning. The transit management system also realizes transit vehicle lane design, transportation operations and management services for transit vehicle. The transit management system consists of one of more of the following physical subsystems: (1) Roadside Unit (RSU) network, (2) Traffic Control Unit (TCU) and Traffic Control Center (TCC) network, (3) Vehicle Onboard Unit (OBU), (4) Traffic Operations Centers (TOCs), (5) Cloud platform. The transit management system realizes one or more of the following function categories: sensing, transportation behavior prediction and management, planning and decision making, and vehicle control. The transit management system is supported by road infrastructure, real-time wired and/or wireless communication, the power supply networks, and cyber safety and security services.
This invention provides an Autonomous Vehicle (AV) Control System comprising a sensing module for gathering driving environment data and an onboard unit (OBU) for vehicle control. The OBU comprises a vehicle control module and communication modules for information exchange with a Traffic Control Center/Traffic Control Unit (TCC/TCU) or Roadside Units (RSUs). The AV Control System receives targeted guidance instructions and information, such as vehicle maneuvering, safety maintenance, traffic control, and special conditions, to enhance driving tasks. The AV Control System collaborates with a TCC/TCU or RSUs, providing redundancy and a fail-safe mechanism for increased safety and reliability. The system is designed with wireless communication capabilities for efficient information exchange and is applicable to autonomous vehicles (AVs).
G08G 1/0968 - Systems involving transmission of navigation instructions to the vehicle
H04L 67/00 - Network arrangements or protocols for supporting network services or applications
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
Provided herein is technology relating to roadway design and traffic control systems and methods for connected and automated vehicle and highway (CAVH) systems, and particularly, but not exclusively, to systems and methods for controlling switching of vehicles between automated mode and human-driven mode, systems and methods for vehicle merging, diverging, and overtaking on automated lanes of multiple lane highways, systems and methods for emergency management and roadside assistance on automated lanes, and/or systems and methods for managing automated vehicle lanes on urban major and minor expressways.
This technology provides an autonomous vehicle (AV) system that integrates a localized generative artificial intelligence (AI) system with a world model for automated vehicle control and traffic operations. The AI system comprises a machine learning component that uses historical and real-time environmental or road data to improve models and algorithms for identifying vehicles and objects and predicting vehicle movements. The AI system features an environment prediction component configured to generate road and environmental condition forecasts based on both historical and real-time information. The AI system is configured to generate numerous long-tail cases that are challenging or impractical to be collected directly from real-world scenarios, such as traffic accidents, adverse weather conditions, natural hazards, pavement breakdown, traffic events, and/or communication malfunction.
Provided herein is an intelligent system for microscopic motion control of autonomous vehicles. The autonomous vehicle intelligent system comprises an onboard unit (OBU) in a vehicle. The OBU comprises a sensing module, a communication module, a data fusion module, and/or a prediction module. The OBU is capable of generating guidance information and targeted instructions for individual vehicles. The sensing module is designed to detect the surrounding environment. The communication module enables seamless connectivity with nearby autonomous vehicles (AVs), roadside units (RSUs), cloud platform, and traffic control center or traffic control unit (TCC/TCUs). The data fusion module integrates multi-source information collected from onboard sensors and the cloud. The prediction module delivers advanced forecasting capabilities.
The technology described herein provides an Intelligent Driving System for Adverse Weather Conditions (IDS-AWC) to enhance the safety and efficiency of autonomous vehicles (AVs). The system comprises an onboard unit (OBU) and/or a cloud platform, which integrate multi-source weather and environmental information from vehicle sensors, AVs, roadside units (RSUs), cloud platforms, and/or traffic control centers/traffic control units (TCC/TCU). The OBU processes data using learning-based, statistical, and empirical models to optimize vehicle control. The IDS-AWC improves situational awareness with high-definition maps for lane and road geometry recognition in low visibility and applies weather-adaptive control strategies, such as speed adjustments on slippery or icy roads. The cloud platform provides vehicle-specific weather forecasts and planning outputs to enhance decision-making. By integrating real-time perception, predictive analytics, and adaptive control, the IDS-AWC enhances AV robustness in rain, snow, fog, storm, and sandstorms, ensuring safer and more reliable operations under adverse weather conditions.
The technology relates to a systematic intelligent system (SIS) configured to train and optimize trip profile models through dynamic distribution of computing resources and model parameters across vehicle intelligent units (VIUs) and roadside intelligent units (RIUs). The SIS comprises a system intelligent unit (SIU) configured to generate and maintain a trip profile model using aggregated historical trip data. Based on this model, the SIU coordinates distributed training, schedules model updates, allocates computing resources, and issues task assignments to VIUs and RIUs provided by multiple automated driving system service providers. The system further supports pre-trip planning, en-route updates, and post-trip feedback to continuously refine training processes and optimize deployment. Communication among SIS components is enabled through unified data interfaces and formats to ensure cross-system coordination, efficient model calibration, and adaptive resource management.
Provided herein is technology relating to automated driving and particularly, but not exclusively, to a modular Vehicle Intelligence Unit (VIU) comprising a sensing and perception fusion module, a collaborative decision-making module, and an intelligent control/assistance module. The VIU is designed to dynamically upgrade or adaptively restore autonomous driving levels based on vehicle conditions and driving conditions. The VIU enables progressive autonomy restoration or elevation from Level 1 to Level 2, 3, 4, or 5; from Level 2 to Level 3, 4, or 5; or from Level 3 to Level 4 or 5. The system features a dynamic recovery mechanism for downgraded systems. When adverse conditions trigger temporary downgrades (e.g., from Level 4 to Level 2), the VIU autonomously restores the original autonomy level through multi-module coordination and improvement. The adaptive algorithms ensure safe transitions and continuous optimization across autonomy levels, maintaining operational reliability under dynamic vehicle and driving conditions.
Provided herein is technology relating to automated driving and particularly, but not exclusively, to a communication-based Connected Reference Marker (C-CRM) system for precise, real-time vehicle localization in connected and automated driving environments. The system comprises CRMs, Wireless Signal Units, an Onboard Module, and/or a Central Operations Unit, which uses two-dimensional and three-dimensional triangular position identification methods for level grade roads and for upgrade or down grade roads, respectively. This method enhances localization accuracy in conditions where GPS or onboard sensors fail. The system also enables virtual roadway configuration, allowing vehicles to maintain lane position without relying on high definition (HD) maps. Importantly, the C-CRM system improves detection and positioning of Vulnerable Road Users, including pedestrians and bikes, offering critical support in urban driving scenarios. The infrastructure is cost-effective, easily deployable, and compatible with cloud-based control architectures for scalable autonomous vehicle operations.
Provided herein is a Device Allocation System (DAS) for distributed autonomous vehicle-cloud operations. The technology provides a simplified DAS design in which an intelligent roadside toolbox is provided as a cloud-based platform of an Intelligent Roadside Infrastructure System. Cloud resources are used to supplement a connected and automated vehicle (CAV) to maintain the automation level of the CAV during abnormal driving conditions. Specifically, cloud resources comprise one or more of: computational resources, system security and backup resources, sensing resources, transportation behavior prediction and management resources, planning and decision-making resources, and/or vehicle control resources and/or instructions. Accordingly, the distributed autonomous vehicle-cloud operations maintain or restore the automation level of the CAV during abnormal driving conditions such as extreme weather or complex road geometry.
H04W 4/44 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G05D 1/247 - Arrangements for determining position or orientation using signals provided by artificial sources external to the vehicle, e.g. navigation beacons
H04W 72/51 - Allocation or scheduling criteria for wireless resources based on terminal or device properties
13.
AUTONOMOUS VEHICLE INTELLIGENT CONTROL SYSTEM WITH DRIVING TASK DISTRIBUTION
This technology provides an Autonomous Vehicle (AV) Intelligent Control System (ICS) that integrates a sensing module for collecting driving environment data and an onboard unit (OBU) for vehicle control. The OBU includes a vehicle control module and communication modules for interacting with Traffic Control Centers (TCC/TCU) and Roadside Units (RSUs). These modules exchange information at the control level, such as vehicle positioning, speed, and environmental conditions, enabling the AV to operate safely and efficiently. The system also features redundancy through dual-security mechanisms, enhancing safety and reliability. The AV ICS is designed to distribute driving tasks and functions, utilizing both TCC/TCU and RSU data for vehicle control and monitoring, with wireless communication capabilities for seamless information exchange.
G08G 1/0968 - Systems involving transmission of navigation instructions to the vehicle
H04L 67/00 - Network arrangements or protocols for supporting network services or applications
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
The technology described herein provides systems and methods for an Autonomous Vehicle Cloud Control System (AVCCS) with a World Model. The AVCCS comprises a cloud-based platform, a communication module, and/or an onboard unit (OBU). The AVCCS leverages generative models, predictive models, and reinforcement learning methods to generate and synthesize comprehensive information at real-time, short-term, and long-term scales for sensing, transportation behavior prediction and management, planning and decision-making, and/or vehicle control. The comprehensive information generated from the World Model comprises vehicle surrounding information, weather information, vehicle attribute data, traffic state information, road information, and incident information. Additionally, the AVCCS is configured to provide one or more of data fusion, sensing, prediction, planning, decision-making, and control functions to generate detailed customized information at microscopic, mesoscopic, and macroscopic levels, and to generate time-sensitive control instructions for vehicles to fulfill driving tasks and provide operations and maintenance services.
The technology described herein provides systems and methods for an Automated Driving Cloud System (ADCS) for long-tail corner cases. The ADCS for long-tail corner cases comprises a cloud-based platform, a communication module, and/or an onboard unit (OBU). The ADCS leverages world models to provide automated driving functions including sensing, prediction, planning, decision making, and control at microscopic, mesoscopic, and/or macroscopic levels. The system is specifically designed to address long-tail corner cases, which include work zones, special events, reduced speed zones, incident detection, buffer spaces, and adverse weather conditions. Additionally, the ADCS is configured to provide safety and efficiency measures for vehicle operations and control at various special scales that require additional system coverage, including construction zones, special event zones, and special weather conditions. The ADCS enables adaptive and reliable automated driving in highly uncertain and dynamic environments.
The technology described herein provides a cloud-based learning system (CLS) for end to end and/or sequential models for autonomous driving. The CLS provides high-performance computation capability that allocates computation power for sensing, prediction, planning and decision making, and control at a microscopic level, a mesoscopic level, and/or a macroscopic level. The CLS can acquire computation resources from a cloud system and from one or more of a roadside unit network, a network of vehicles comprising onboard units, a traffic control center/traffic control unit, or a traffic operations center. Additionally, the CLS is configured to optimize and generate detailed customized information and time-sensitive control instructions for vehicles by processing data through learning models to fulfill driving tasks and provide operations and maintenance services for vehicles.
The technology disclosed herein pertains to the field of automated driving and, more particularly, to an automated driving system (ADS) comprising a Connected Automated Vehicle subsystem capable of real-time interaction with an Intelligent Road Infrastructure System. To mitigate the adverse effects of varying weather conditions on vehicles and other components within the system, the ADS employs methods of coordinated sensing, coordinated prediction and decision-making, and coordinated control to supplement, enhance, and reinforce the automated driving capabilities of vehicles. Furthermore, through a multi-agent allocation design, the ADS enables functional and device allocation among multiple entities, including a Traffic Control Center, Vehicle Intelligence Unit, and cloud platform, ensuring the safe and efficient operation of the system under various weather conditions.
This application describes a proactive sensing system for an autonomous vehicle. This system fuses vehicle sensing data and sensing data from a roadside unit, a Traffic Control Unit, and/or a cloud to provide full 360-degree coverage and birds-eye view of the driving environment. This proactive sensing system cooperatively uses vehicle-based sensor data and sensor data from external sources to provide better and more efficient sensing of longtail or corner cases, such as blind spots and blockage by surrounding objects. Specifically, this proactive sensing system effectively identifies major sensing points where vulnerable road users, such as pedestrians and bicycles, are major challenges for autonomous vehicles at intersections, roundabouts, or work zones. Accordingly, the technology significantly improves the safety of autonomous vehicles.
This invention presents a vehicle safety system (VSS) for autonomous vehicles (AVs) utilizing an onboard unit (OBU) capable of communicating with various entities, comprising roadside units (RSUs), other OBUs, and cloud platforms. The OBU incorporates a safety subsystem designed to implement proactive, active, and passive safety measures. The proactive safety measures comprise incident prediction and warnings. The active safety measures comprise emergency braking, and the passive safety measures comprise incident response and dynamic routing. This VSS can be further enhanced by incorporating sensing and processing capabilities of the RSU network or the cloud platform, enabling distributed and integrated safety functions and improved environmental awareness. The system aims to enhance AV safety by addressing incidents before, during, and after their occurrence through comprehensive safety measures at a system level, comprising a vehicle centric system, a vehicle-road system, or a vehicle cloud system.
H04W 4/44 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
G08G 1/01 - Detecting movement of traffic to be counted or controlled
H04W 4/46 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for vehicle-to-vehicle communication [V2V]
H04W 4/80 - Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication
This technology provides systems and methods for a vehicle computing system (VCS) for autonomous driving. This VCS furnishes End-to-End models that provide sensing, prediction, planning, decision-making, and control functions. The VCS executes vehicle control algorithms, trains general AI models, and makes inferences from those AI models. Specifically, a computing subsystem of the VCS performs computation methods that train a tensor-centered model and/or make inferences from a tensor-centered model. Additionally, the VCS gathers data from a roadside unit network, an onboard unit, a cloud platform, a traffic control center/traffic control unit, and a traffic operations center (TOC), thereby enhancing the safety and efficiency of autonomous driving.
H04W 4/44 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
G08G 1/01 - Detecting movement of traffic to be counted or controlled
H04W 4/46 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for vehicle-to-vehicle communication [V2V]
H04W 4/80 - Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication
21.
INTELLIGENT INFORMATION CONVERSION SYSTEM FOR AUTONOMOUS VEHICLES
The Intelligent Information Conversion System (IICS) facilitates real-time dynamic information exchange among connected and automated vehicle (CAV), roadside intelligent unit (RIU), and cloud platform. The system comprises a codebook, coding module, connector module, and supporting system. The codebook provides a standardized format for information exchange, using a sequence of integers corresponding to various categories such as vehicle automation level, vehicle type, and road category. The coding module encodes and decodes information to enable seamless communication among CAV, RIU, and cloud platform, optimizing data transmission and service levels for autonomous driving. The system supports sorting, encoding, and decoding information into a codebook string, improving real-time interaction and information flow across connected environments. It enhances vehicle automation and supports dynamic, context sensitive data exchanges between different entities in the autonomous ecosystem.
B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles
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
G08G 1/0967 - Systems involving transmission of highway information, e.g. weather, speed limits
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
22.
VEHICLE-BASED CLOUD COMPUTING SYSTEM FOR AUTONOMOUS DRIVING
The invention provides systems and methods for a vehicle-based cloud computing system (VCCS) for autonomous driving. This VCCS builds world models based on a series of complex scenario data to optimize sensing, prediction, planning, decision making, and control for autonomous driving. The VCCS can execute vehicle control algorithms, train general AI models, and make inferences to optimize autonomous driving. Specifically, it dynamically adjusts driving strategies based on long tail scenarios including but not limited to weather, work zone information, and traffic status, ensuring safe and efficient vehicle operation. Additionally, the VCCS can gather supplementary data from (a) a roadside unit (RSU) network, (b) another OBU, (c) a cloud platform, (d) a traffic control center/traffic control unit (TCC/TCU), and (e) a traffic operations center (TOC), thereby further improving control and efficiency in complex driving environments.
H04W 4/44 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
G08G 1/01 - Detecting movement of traffic to be counted or controlled
H04W 4/46 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for vehicle-to-vehicle communication [V2V]
H04W 4/80 - Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication
23.
COMPUTING POWER ALLOCATION SYSTEM FOR AUTONOMOUS DRIVING
The invention provides systems and methods for a computing power allocation system for autonomous driving (CPAS-AD), which is a component of an Intelligent Road Infrastructure System (IRIS). The CPAS-AD incorporates advanced computing capabilities that effectively allocate computational power for sensing, prediction, planning, decision-making, and control functions to enable end-to-end driving functions. In addition to the vehicle, the CPAS-AD can acquire additional computation resources from one or more of: (a) a roadside unit (RSU) network, (b) a cloud platform, (c) a traffic control center/traffic control unit (TCC/TCU), and (d) a traffic operations center (TOC). Additionally, tailored to different traffic scenarios, the CPAS-AD can allocate data and computation resources (including but not limited to CPU and GPU) for vehicle sensing, prediction, planning, decision-making, and control functions, thereby enabling safe and efficient autonomous driving.
The invention provides systems and methods for a function-based computing power allocation system (FCPAS), which is a component of an Intelligent Road Infrastructure System (IRIS). The FCPAS incorporates advanced computing capabilities that effectively allocate computational power for prediction, planning, and decision making functions. Specifically, through the FCPAS, an AV can acquire additional computational resources for vehicle prediction, planning, and decision-making functions, thereby enabling safe and efficient autonomous driving. Additionally, tailored to different traffic scenarios, the FCPAS can allocate data and computational resources (including but not limited to CPU and GPU) for vehicle automation.
Provided herein is technology relating to a function allocation system (FAS) that deploys artificial intelligence models for a connected automated highway (CAH) system and a connected automated vehicle (CAV) system to distribute driving intelligence between the CAV system and the CAH system. The FAS comprises a communication module, a data module, and a computing module. The computing module is configured to analyse scenes using sensing data, determine automated driving function requirements, deploy function allocation methods, and analyse CAH system and CAV system functions. The function allocation methods provide analysis, guidance, and optimization capabilities for sensing, decision-making, and control functions. The FAS allocates automated driving functions to the CAV system and the CAH system based on their respective intelligence levels. The technology aims to enhance automated driving and ensure driving safety by leveraging function allocation models and algorithms for optimal function distribution between vehicles and the infrastructure.
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
H04W 4/44 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
26.
Roadside edge computing system for autonomous vehicles
The invention provides a roadside computing system (RCS), or an edge computing system, for an autonomous vehicle. The RCS comprises a hierarchy of roadside unit (RSU) and an onboard unit (OBU) in an individual vehicle. The RSU comprises a data processing module and a communication module, and is capable of generating guidance information and targeted instructions for individual vehicle. The data processing module of the RSU comprises two processors: an External Object Calculating Module (EOCM) and an AI processing unit. Thus, the RCS utilizes roadside edge computing power and AI models to support autonomous driving for the vehicle. The OBU comprises a data processing module, a communication module, and a vehicle control module, and is capable of generating vehicle-specific targeted instruction for the vehicle based on guidance information and targeted instructions received from RSUs, and controlling the vehicle based on vehicle-specific targeted instruction.
The invention presents a cloud-based model deployment and control system (CMDCS) for providing automated driving services. The CMDCS comprises a cloud-based platform, an onboard unit (OBU), and a Vehicle-to-System component. The cloud-based platform comprises a localization-enhancement subsystem and a cloud computing module. The CMDCS is configured to collect detectable data and undetectable data from vehicles, road, and cloud. Then, the CMDCS deploys a set of end-to-end AI models and methods for automated driving services, comprising sensing, prediction, planning, and control services. The AI models and methods are trained and optimized to process collected data for providing operating parameters for vehicles. Then, the vehicles can be effectively and efficiently controlled and operated by the CMDCS. In addition, the CMDCS is configured to generate and provide detailed time-sensitive vehicle specific control instructions.
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
H04W 12/02 - Protecting privacy or anonymity, e.g. protecting personally identifiable information [PII]
H04W 12/03 - Protecting confidentiality, e.g. by encryption
Provided herein is an artificial intelligence-based mobile roadside intelligent unit (MRIU) for providing, supplementing, and/or enhancing the control and operation of autonomous vehicles in normal and long-tail scenarios. The MRIU comprises a computing module configured to provide supplemental computation capability for autonomous driving. The MRIU comprises a communication module to communicate and exchange data with a vehicle or a cloud. The MRIU provides prediction, decision-making, and/or control functions for autonomous driving. The MRIU provides edge computing capability for autonomous vehicles to train and operate artificial intelligence-based intelligent driving models in a distributed fashion. Specifically, an edge computing unit conducts data fusion and data feature extraction, provides prediction, formulates control strategies, generates vehicle control instructions, and/or distributes vehicle control information and/or instructions for an autonomous vehicle.
H04W 4/44 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
29.
Autonomous vehicle and center control system (AVCCS) for drone/tele driving or digital twins
The invention provides systems and methods for an autonomous vehicle and center control system (AVCCS), which is a component of a Connected Automated Vehicle Highway (CAVH) system. The AVCCS is configured to realize drone/tele driving or digital twins by providing automated vehicles (AVs) or connected automated vehicles (CAVs) with vehicle-specific control instructions comprising instructions for vehicle longitudinal and lateral position, speed, and steering and control. Specifically, through the system, AVs or CAVs can be effectively and efficiently controlled by the AVCCS. In addition, the AVCCS is configured to provide vehicle-specific control instructions to AVs or CAVs and control them through a hierarchy of traffic control centers/units (TCCs/TCUs) or the combination of TCCs/TCUs and the onboard units (OBUs) with a vehicle control module, wherein said TCCs/TCUs are configured to fulfill vehicle maneuver tasks, monitor safety maintenance tasks, and take over if the system fails.
G08G 1/0968 - Systems involving transmission of navigation instructions to the vehicle
H04L 67/00 - Network arrangements or protocols for supporting network services or applications
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
The invention provides an autonomous vehicle and center guidance system (AVCGS) for drone/tele driving or digital twins by sending guidance instructions to an autonomous vehicle (AV) or a connected automated vehicle (CAV). The AVCGS is a component of a Connected Automated Vehicle Highway (CAVH) system. This AVCGS is configured to operate AVs or CAVs using a hierarchy of traffic control centers/units (TCCs/TCUs). The AVCGS comprises automatic or semi-automated computational modules, a TCC/TCU communication module, and/or an onboard unit (OBU) communication module and a vehicle control module. The AVCGS communicates with one or more entities. The vehicle-specific guidance instructions and information comprise vehicle maneuver, safety maintenance, traffic control/road condition, and special information. The AVCGS provides backup in case of any errors or failures. Specifically, through the AVCGS, AVs or CAVs can be effectively and efficiently operated.
G08G 1/0968 - Systems involving transmission of navigation instructions to the vehicle
H04L 67/00 - Network arrangements or protocols for supporting network services or applications
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
The invention provides an autonomous vehicle and intelligent control (AVIC) system with distributed AI computing, which is a component of a Connected Automated Vehicle Highway (CAVH) system. This AVIC system is configured to realize training and application for distributed AI computing by providing automated vehicles (AVs) and/or connected automated vehicles (CAVs) with vehicle-specific control instructions comprising instructions for vehicle longitudinal and lateral position, speed, and steering and control. Detailed and time-sensitive vehicle-specific control instructions comprise control instructions for speed, spacing, lane designation, vehicle following, lane changing, and/or route guidance. Specifically, through the system, CAVs can be effectively and efficiently controlled by the AVIC system. In addition, the AVIC system is configured to provide vehicle-specific control instructions to CAVs and control them through a hierarchy of traffic control centers/traffic control units (TCCs/TCUs) or the combination of TCCs/TCUs and the onboard units (OBUs) with vehicle control modules.
G08G 1/0968 - Systems involving transmission of navigation instructions to the vehicle
H04L 67/00 - Network arrangements or protocols for supporting network services or applications
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
This invention presents a function allocation system for an autonomous vehicle (AV). During the operations of the AV, some or all of its automated driving capabilities or functions could be downgraded due to long-tail events or malfunctioning. The roadside intelligent infrastructure, or the cloud platform, could supplement some or all of AV's automated driving functions, including sensing, prediction and decision-making, and/or control functions. The function allocation system dynamically allocates these functions between AV and intelligent infrastructure, achieving a higher system intelligence level S than the downgraded vehicle intelligence level V. In addition, a function allocation system could dynamically allocate sensing, prediction and decision-making, and/or control functions between AV and a cloud platform. This invention also presents a function integration system or a fusion system for an AV. The fusion system integrates data across these functions to optimize automated driving performance and collaboration between AV and intelligent infrastructure.
This invention presents an automated driving system with distributed computing (ADS-DC). During the operation of a connected automated vehicle (CAV), some or all of its automated driving capabilities for sensing, prediction, planning, decision-making, or control may be downgraded due to long-tail events or malfunctions. The intelligent roadside toolbox (IRT) functions as an edge server or a cloud, and can supplement CAV's sensing functions, prediction and management functions, planning and decision-making functions, and vehicle control functions by providing customized, on-demand, and dynamic computing resources and functions to the CAV. In addition, the IRT computing functions provide the computation support for sensing, prediction, planning, decision-making, and/or control functions of said CAV. Namely, the IRT functions as an edge server or a cloud to provide processing, training or optimization of CAV driving models as well as facilitate the implementation of the driving models in the CAV.
This technology relates to autonomous vehicle (AV) control systems tailored for critical points of a partially instrumented infrastructure. The first system integrates an onboard unit (OBU) and communication modules to interact with roadside units (RSUs) or a cloud platform, delivering time-sensitive control instructions to vehicles at critical points. The OBUs execute these instructions for driving tasks. The second system combines an OBU with a cloud platform, leveraging cloud services for enhanced functionality like storage and computing. It adapts to diverse critical point scenarios, employing proactive incident prediction and rapid detection methods for optimized performance.
B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles
G08G 1/01 - Detecting movement of traffic to be counted or controlled
H04W 4/44 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
H04W 4/46 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for vehicle-to-vehicle communication [V2V]
35.
Vehicle AI computing system (VACS) for autonomous driving
The invention provides a vehicle AI computing system (VACS) that supports autonomous driving through an Onboard Unit (OBU) for vehicle-based computing and distributed computing based on vehicle-road-cloud. The vehicle-based computing can effectively complete various computational tasks by using onboard computing resources. The distributed computing allows the vehicle to work in collaboration with roadside units (RSUs) and/or the cloud to effectively complete various computational tasks. The VACS features an OBU with a sensing module, a communication module, and a data processing module that integrates data from vehicle sensors, RSUs, and the cloud. The OBU also includes a vehicle control module that helps control the vehicle based on the data of RSU and cloud. The VACS leverages high-performance computation resources to implement end-to-end driving tasks including sensing, prediction, planning and decision-making, and control. The VACS features large-scale parallel data processing by using GPU either onboard or based on vehicle-road-cloud.
The invention provides an autonomous vehicle (AV) system with an artificial intelligence (AI) system for automated vehicle control and traffic operations. This AI system comprises a computation component configured to provide sensing, behavior prediction and management, decision making, and vehicle control for the vehicle. This AI system is configured to receive local knowledge, information, data, and models from a roadside unit (RSU) or a cloud to improve performance and efficiency of the vehicle. The AI system is configured to train models with heuristic parameters obtained from a local traffic control center/traffic control unit (TCC/TCU) or the cloud to provide an improved model. The AI system is configured to provide intelligence coordination to distribute intelligence among vehicles, RSUs and cloud. The system also provides localized self-evolving artificial intelligence.
This technology provides an Autonomous Vehicle (AV) Intelligent Control System (ICS) that integrates a sensing module for collecting driving environment data and an onboard unit (OBU) for vehicle control. The OBU includes a vehicle control module and communication modules for interacting with Traffic Control Centers (TCC/TCU) and Roadside Units (RSUs). These modules exchange information at the control level, such as vehicle positioning, speed, and environmental conditions, enabling the AV to operate safely and efficiently. The system also features redundancy through dual-security mechanisms, enhancing safety and reliability. The AV ICS is designed to distribute driving tasks and functions, utilizing both TCC/TCU and RSU data for vehicle control and monitoring, with wireless communication capabilities for seamless information exchange.
G08G 1/0968 - Systems involving transmission of navigation instructions to the vehicle
H04L 67/00 - Network arrangements or protocols for supporting network services or applications
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
This technology provides an Autonomous Vehicle (AV) Intelligent Driving System (IDS) that includes a sensing module for gathering driving environment data and an onboard unit (OBU) for vehicle control. The OBU features a vehicle control module and communication modules for guidance-level interaction with Traffic Control Centers (TCC/TCU) and Roadside Units (RSUs). The system receives targeted guidance instructions and information, such as vehicle maneuvering, safety maintenance, traffic control, and special conditions, to enhance driving tasks. The IDS collaborates with TCC/TCU and RSUs, providing redundancy and a fail-safe mechanism for increased safety and reliability. The system is designed with wireless communication capabilities for efficient information exchange and is applicable to connected and automated vehicles (CAVs).
G08G 1/0968 - Systems involving transmission of navigation instructions to the vehicle
H04L 67/00 - Network arrangements or protocols for supporting network services or applications
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
This technology provides an Autonomous Vehicle (AV) Intelligent Driving System (IDS) that uses weather information or special information to provide vehicle operation or control. The Onboard Unit (OBU) uses a traffic control center/traffic control unit (TCC/TCU) communication module or a roadside unit (RSU) communication module to receive vehicle-specific targeted weather information and/or special information at the Guidance Level of vehicle driving tasks from the TCC/TCU or the RSU. The special information comprises activity, accidents, and hazards/obstacles information. The vehicle control module enhances driving safety by integrating vehicle-specific weather, pavement condition, activity, accidents, and hazards/obstacles information.
G08G 1/0968 - Systems involving transmission of navigation instructions to the vehicle
H04L 67/00 - Network arrangements or protocols for supporting network services or applications
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
Provided herein is a technology for an Autonomous Vehicle Intelligent System (AVIS), which facilitates vehicle operations and control for autonomous driving. The AVIS and related methods provide vehicles with vehicle-specific information for a vehicle to perform driving tasks such as car following, lane changing, and route guidance. The AVIS comprises an onboard unit (OBU), wherein the OBU comprises a communication module communicating with one or more of other autonomous vehicles (AV), a roadside unit (RSU), a cloud platform, and a traffic control center/traffic control unit (TCC/TCU). The AVIS implements one or more of the following functions: sensing, prediction, decision-making, and vehicle control using onboard information and vehicle-specific information received from other AVs, the RSU, the cloud platform, and/or the TCC/TCU.
Provided herein is a technology for an Autonomous Vehicle Cloud System (AVCS). This AVCS provides sensing, data fusion, prediction, decision-making, and/or control instructions for specific vehicles at a microscopic level based on data from one or more of other vehicles, roadside unit (RSU), cloud-based platform, and traffic control center/traffic control unit (TCC/TCU). Specifically, the AVs can be effectively and efficiently operated and controlled by the AVCS. The AVCS provides individual vehicles with detailed time-sensitive control instructions for fulfilling driving tasks, including car following, lane changing, route guidance, and other related information. The AVCS is configured to predict individual vehicle behavior and provide planning and decision-making at a microscopic level. In addition, the AVCS is configured to provide one or more of virtual traffic light management, travel demand assignment, traffic state estimation, and platoon control.
Provided herein is technology related to a distributed driving system (DDS) by using flexible, on-demand, and customized resources and functions from an intelligent roadside toolbox (IRT). These resources comprise computational resources, cloud resources, system security resources, backup and redundancy resources. The functions comprise sensing, transportation behavior prediction and management, planning and decision-making, and vehicle control functions. The DDS and IRT technologies described herein are vehicle oriented, modular, and customizable for each vehicle to meet the specific needs of each individual vehicle as an on-demand and dynamic service. The DDS is configured to provide customized, on-demand, and dynamic IRT resources and functions to individual CAVs to supplement the CAV's sensing, transportation behavior prediction and management, planning and decision-making, and/or vehicle control.
Provided herein is technology relating to roadway design and traffic control systems and methods for connected and automated vehicle and highway (CAVH) systems, and particularly, but not exclusively, to systems and methods for controlling switching of vehicles between automated mode and human-driven mode, systems and methods for vehicle merging, diverging, and overtaking on automated lanes of multiple lane highways, systems and methods for emergency management and roadside assistance on automated lanes, and/or systems and methods for managing automated vehicle lanes on urban major and minor expressways.
The present invention relates to systems and methods that allocate, arrange, and distribute certain types of functions and intelligence, for connected automated vehicle highway (CAVH) systems, to facilitate vehicle operations and controls, to improve the general safety of the whole transportation system, and to ensure the efficiency, intelligence, reliability, and resilience of CAVH systems. The present invention also provides methods to define CAVH system intelligence and its levels, which are based on two dimensions: the vehicle intelligence and infrastructure intelligence.
G08G 1/01 - Detecting movement of traffic to be counted or controlled
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
G08G 1/0967 - Systems involving transmission of highway information, e.g. weather, speed limits
45.
Autonomous vehicle control system with roadside unit (RSU) network's global sensing
This invention provides a system-oriented and fully-controlled connected automated vehicle highway system for various levels of connected and automated vehicles and highways. The system comprises one or more of: 1) a hierarchical traffic control network of Traffic Control Centers (TCC's), local traffic controller units (TCUs), 2) A RSU (Road Side Unit) network (with integrated functionalities of vehicle sensors, I2V communication to deliver control instructions), 3) OBU (On-Board Unit with sensor and V2I communication units) network embedded in connected and automated vehicles, and 4) wireless communication and security system with local and global connectivity. This system provides a safer, more reliable and more cost-effective solution by redistributing vehicle driving tasks to the hierarchical traffic control network and RSU network.
G08G 1/0968 - Systems involving transmission of navigation instructions to the vehicle
H04L 67/00 - Network arrangements or protocols for supporting network services or applications
G08G 1/04 - Detecting movement of traffic to be counted or controlled using optical or ultrasonic detectors
G08G 1/042 - Detecting movement of traffic to be counted or controlled using inductive or magnetic detectors
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
The present technology relates to an intelligent road infrastructure system and, more particularly, to systems and methods for a heterogeneous connected automated vehicle highway (CAVH) network in which the road network has various RSU and TCU/TCC coverages and functionalities. The heterogeneous CAVH network facilitates control and operations for vehicles of various automation level and other road users by implementing various levels of coordinated control among CAVH system entities and providing individual road users with detailed customized information and time-sensitive control instructions, and operations and maintenance services.
B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles
G08G 1/01 - Detecting movement of traffic to be counted or controlled
H04W 4/44 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
H04W 4/46 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for vehicle-to-vehicle communication [V2V]
Provided herein is technology relating to automated driving and particularly, but not exclusively, to a connected reference marker technology configured to serve automated driving systems by providing, supplementing, and/or enhancing autonomous driving functions for connected automated vehicles under normal and abnormal driving scenarios.
Provided herein is technology relating to automated driving and particularly, but not exclusively, to a connected reference marker technology configured to serve automated driving systems by providing, supplementing, and/or enhancing autonomous driving functions for connected automated vehicles under normal and abnormal driving scenarios.
This invention provides a system-oriented and fully-controlled connected automated vehicle highway system for various levels of connected and automated vehicles and highways. The system comprises one or more of: 1) a hierarchical traffic control network of Traffic Control Centers (TCC's), local traffic controller units (TCUs), 2) A RSU (Road Side Unit) network (with integrated functionalities of vehicle sensors, I2V communication to deliver control instructions), 3) OBU (On-Board Unit with sensor and V2I communication units) network embedded in connected and automated vehicles, and 4) wireless communication and security system with local and global connectivity. This system provides a safer, more reliable and more cost-effective solution by redistributing vehicle driving tasks to the hierarchical traffic control network and RSU network.
G08G 1/0968 - Systems involving transmission of navigation instructions to the vehicle
H04L 67/00 - Network arrangements or protocols for supporting network services or applications
G08G 1/04 - Detecting movement of traffic to be counted or controlled using optical or ultrasonic detectors
G08G 1/042 - Detecting movement of traffic to be counted or controlled using inductive or magnetic detectors
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
The technology provided herein relates to a roadside infrastructure sensing system for Intelligent Road Infrastructure Systems (IRIS) and, in particular, to devices, systems, and methods for data fusion and communication that provide proactive sensing support to connected and automated vehicle highway (CAVH) systems.
The invention provides systems and methods for an autonomous vehicle (AV) control system comprising an onboard unit (OBU) and a roadside unit (RSU), which are two components of an Intelligent Road Infrastructure System (IRIS). This integrated vehicle-road system provides sensing, prediction, decision-making, and control instructions for specific vehicles at a microscopic level. Specifically, through the AV control system, an AV can be effectively and efficiently controlled by the AV itself and/or by the RSU. The AV control system provides individual vehicles with detailed time-sensitive control instructions for vehicles to fulfill driving tasks. In addition, the RSU conducts behavior prediction for individual vehicles at a microscopic level from 1 to 10 milliseconds, which is critical for connected and automated vehicle (CAV) operations.
The invention provides systems and methods for an autonomous vehicle (AV) and cloud control system, which comprises an AV control system comprising an onboard unit (OBU), a roadside unit (RSU) network, and a cloud-based platform. This integrated vehicle-road-cloud system provides traffic state estimation, prediction, computing, and control instructions for specific vehicles by the cloud-based platform. The cloud-based platform also provides safety and efficiency measures for vehicle operations and control under adverse weather conditions, and provides security, redundancy, and resiliency measures to improve system reliability. In addition, the RSU network provides high-resolution maps for specific vehicles.
The invention provides systems and methods for an autonomous vehicle and cloud control system comprising an autonomous vehicle (AV) control system and a cloud-based platform, which are two components of an Intelligent Road Infrastructure System (IRIS). This integrated vehicle-cloud system provides sensing, prediction, decision-making, and control instructions for specific vehicles at a microscopic level. Specifically, through the system, AVs can be effectively and efficiently controlled by AV itself and/or by the cloud. The AV and cloud control system provides individual vehicles with detailed time-sensitive control instructions for vehicles to fulfill driving tasks. In addition, the cloud-based platform is configured to predict behavior of individual vehicles and provide planning and decision making at a microscopic level from 1 to 10 milliseconds, which is critical for AV operations.
This invention provides a system-oriented and fully-controlled connected automated vehicle highway system for various levels of connected and automated vehicles and highways. The system comprises one or more of: 1) a hierarchical traffic control network of Traffic Control Centers (TCC's), local traffic controller units (TCUs), 2) A RSU (Road Side Unit) network (with integrated functionalities of vehicle sensors, I2V communication to deliver control instructions), 3) OBU (On-Board Unit with sensor and V2I communication units) network embedded in connected and automated vehicles, and 4) wireless communication and security system with local and global connectivity. This system provides a safer, more reliable and more cost-effective solution by redistributing vehicle driving tasks to the hierarchical traffic control network and RSU network.
G08G 1/0968 - Systems involving transmission of navigation instructions to the vehicle
H04L 67/00 - Network arrangements or protocols for supporting network services or applications
G08G 1/04 - Detecting movement of traffic to be counted or controlled using optical or ultrasonic detectors
G08G 1/042 - Detecting movement of traffic to be counted or controlled using inductive or magnetic detectors
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
The invention provides systems and methods for an Intelligent Road Infrastructure System (IRIS), which facilitates vehicle operations and control for connected automated vehicle highway (CAVH) systems. IRIS systems and methods provide vehicles with individually customized information and real-time control instructions for vehicle to fulfill the driving tasks such as car following, lane changing, and route guidance. IRIS systems and methods also manage transportation operations and management services for both freeways and urban arterials. In some embodiments, the IRIS comprises or consists of one of more of the following physical subsystems: (1) Roadside unit (RSU) network, (2) Traffic Control Unit (TCU) and Traffic Control Center (TCC) network, (3) vehicle onboard unit (OBU), (4) traffic operations centers (TOCs), and (5) cloud information and computing services. The IRIS manages one or more of the following function categories: sensing, transportation behavior prediction and management, planning and decision making, and vehicle control. IRIS is supported by real-time wired and/or wireless communication, power supply networks, and cyber safety and security services.
A Vehicle Intelligent Unit (VIU) is configured to provide vehicle operations and control for Connected Automated Vehicles (CAV) and, more particularly, to connect with a Collaborative Automated Driving System (CADS) and manage and/or control information exchange between CAV and CADS and manage and/or control CAV lateral and longitudinal movements, including vehicle following, lane changing, and route guidance.
Provided herein is technology relating to automated driving and particularly, but not exclusively, to a Vehicle Intelligent Unit (VIU) configured to provide vehicle operations and control for Connected Automated Vehicles (CAV) and, more particularly, to a VIU configured to connect with a Collaborative Automated Driving System (CADS) and manage and/or control information exchange between CAV and CADS and manage and/or control CAV lateral and longitudinal movements, including vehicle following, lane changing, and route guidance.
Provided herein is technology relating to automated driving and particularly, but not exclusively, to a mobile intelligent road infrastructure technology configured to serve automated driving systems by providing, supplementing, and/or enhancing autonomous driving functions for connected automated vehicles under common and unusual driving scenarios.
H04W 4/44 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
Provided herein is technology relating to automated driving and particularly, but not exclusively, to a system configured to provide full vehicle operations and control for connected and automated vehicles (CAV) and, more particularly, to a system configured to manage and/or control CAV by sending individual vehicles with detailed and time-sensitive control instructions for lateral and longitudinal movement of vehicles, including vehicle following, lane changing, route guidance, and related information.
G08G 1/01 - Detecting movement of traffic to be counted or controlled
G08G 1/0967 - Systems involving transmission of highway information, e.g. weather, speed limits
B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles
G05D 1/02 - Control of position or course in two dimensions
H04W 4/44 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
Provided herein is technology relating to automated driving and particularly, but not exclusively, to a system configured to provide full vehicle operations and control for connected and automated vehicles (CAV) and, more particularly, to a system configured to manage and/or control CAV by sending individual vehicles with detailed and time-sensitive control instructions for lateral and longitudinal movement of vehicles, including vehicle following, lane changing, route guidance, and related information.
Provided herein is technology relating to automated driving and particularly, but not exclusively, to an intelligent information conversion system and related methods for providing collaborative automatic driving to intelligent transportation systems, vehicle networking systems, collaborative management control systems, vehicle-road collaborative systems, automated driving systems, and the like.
B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles
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
G08G 1/0967 - Systems involving transmission of highway information, e.g. weather, speed limits
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
G07C 5/00 - Registering or indicating the working of vehicles
The technology relates to a systematic intelligent system (SIS) configured to share data and allocate computing resources among automated driving systems (ADS), e.g., using unified data specifications and interfaces. The SIS comprises systematic intelligent units (SIU) that serve components of ADS, including vehicle intelligent units (VIU) and roadside intelligent units (RIU), and is configured to perform methods to serve an entire trip.
Provided herein is technology relating to intelligent transportation systems and automated vehicles and particularly, but not exclusively, to function allocation systems and methods for a connected automated vehicle highway system that provides transportation management and operations and vehicle control for connected and automated vehicles.
G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
H04W 4/44 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
64.
Coordinated control for automated driving on connected automated highways
Provided herein is technology relating to automated driving and, more particularly, to an automated driving system comprising a Connected Automated Vehicle Subsystem that interacts in real-time with a Connected Automated Highway Subsystem to provide coordinated sensing; coordinated prediction and decision-making; and coordinated control for transportation management and operations and control of connected automated vehicles.
Provided herein is technology relating to automated driving and particularly, but not exclusively, to systems comprising roadside intelligent units (RIU) and infrastructure of specific intelligence levels and related methods for providing and/or supplementing automated driving capabilities of connected and automated vehicles (CAV).
The technology described herein provides Automated Driving System (ADS) methods and systems for coordinating and/or fusing intelligence and functions between Connected Automated Vehicles (CAV) and ADS infrastructure to provide target levels of automated driving. The technology provides systems and methods for function allocation comprising sensing allocation, prediction and decision-making allocation, and control allocation. The ADS operates across various intelligence levels, identified during vehicle operation. The function allocation system dynamically allocates essential functions based on the intelligence levels of both vehicles and infrastructures, ensuring that ADS achieves a system intelligence that surpasses that of individual components. This methodical function distribution enables ADS to manage both vehicles and infrastructures in a manner that enhances vehicular operations and control. The system further integrates a fusion system to support various ADS functions through data integration from multiple sources, which optimizes the driving tasks performed by CAVs.
Provided herein is technology relating to aspects of a Distributed Driving System (DDS) for managing Connected and Automated Vehicles (CAV) and particularly, but not exclusively, to systems, designs, and methods for a Device Allocation System (DAS) configured to allocate and distribute resources to devices of a Distributed Driving Systems (DDS).
H04W 4/44 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
H04W 72/51 - Allocation or scheduling criteria for wireless resources based on terminal or device properties
Provided herein is technology relating to transportation operations and management services and particularly, but not exclusively, to systems and methods for an intelligent roadside toolbox (IRT) that facilitates vehicle operations and control for distributed driving systems (DDS).
The invention provides systems and methods for an Intelligent Road Infrastructure System (IRIS), which facilitates vehicle operations and control for connected automated vehicle highway (CAVH) systems. IRIS systems and methods provide vehicles with individually customized information and real-time control instructions for vehicle to fulfill the driving tasks such as car following, lane changing, and route guidance. IRIS systems and methods also manage transportation operations and management services for both freeways and urban arterials. In some embodiments, the IRIS comprises or consists of one of more of the following physical subsystems: (1) Roadside unit (RSU) network, (2) Traffic Control Unit (TCU) and Traffic Control Center (TCC) network, (3) vehicle onboard unit (OBU), (4) traffic operations centers (TOCs), and (5) cloud information and computing services. The IRIS manages one or more of the following function categories: sensing, transportation behavior prediction and management, planning and decision making, and vehicle control. IRIS is supported by real-time wired and/or wireless communication, power supply networks, and cyber safety and security services.
G08G 1/09 - Arrangements for giving variable traffic instructions
G08G 1/0967 - Systems involving transmission of highway information, e.g. weather, speed limits
B60W 30/165 - Control of distance between vehicles, e.g. keeping a distance to preceding vehicle automatically following the path of a preceding lead vehicle, e.g. "electronic tow-bar"
Provided herein is technology related to a distributed driving system (DDS) that provides transportation management and operations and vehicle control for connected and automated vehicles (CAV) and intelligent road infrastructure systems (IRIS) and particularly, but not exclusively, to methods and systems for sending individual vehicles with customized, detailed, and time-sensitive control instructions and traffic information for automated vehicle driving, such as vehicle following, lane changing, route guidance, and other related information.
Provided herein is technology related to a distributed driving system (DDS) that provides transportation management and operations and vehicle control for connected and automated vehicles (CAV) and intelligent road infrastructure systems (IRIS) and particularly, but not exclusively, to methods and systems for sending individual vehicles with customized, detailed, and time-sensitive control instructions and traffic information for automated vehicle driving, such as vehicle following, lane changing, route guidance, and other related information.
Provided herein is technology relating to connected and automated highway systems and particularly, but not exclusively, to systems and methods for providing localized self-evolving artificial intelligence for intelligent road infrastructure systems.
The present technology relates to an intelligent road infrastructure system and, more particularly, to systems and methods for a heterogeneous connected automated vehicle highway (CAVH) network in which the road network has various RSU and TCU/TCC coverages and functionalities. The heterogeneous CAVH network facilitates control and operations for vehicles of various automation level and other road users by implementing various levels of coordinated control among CAVH system entities and providing individual road users with detailed customized information and time-sensitive control instructions, and operations and maintenance services.
B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles
G08G 1/01 - Detecting movement of traffic to be counted or controlled
H04W 4/46 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for vehicle-to-vehicle communication [V2V]
H04W 4/44 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
74.
Proactive sensing systems and methods for intelligent road infrastructure systems
The technology provided herein relates to a roadside infrastructure sensing system for Intelligent Road Infrastructure Systems (IRIS) and, in particular, to devices, systems, and methods for data fusion and communication that provide proactive sensing support to connected and automated vehicle highway (CAVH) systems.
The invention provides systems and methods for an Intelligent Road Infrastructure System (IRIS), which facilitates vehicle operations and control for connected automated vehicle highway (CAVH) systems. IRIS systems and methods provide vehicles with individually customized information and real-time control instructions for vehicle driving tasks such as car following, lane changing, and route guidance. IRIS systems and methods also manage transportation operations and management services for both freeways and urban arterials. The IRIS manages one or more of the following function categories: sensing, transportation behavior prediction and management, planning and decision making, and vehicle control. IRIS is supported by real-time wired and/or wireless communication, power supply networks, and cyber safety and security services.
G06F 19/00 - Digital computing or data processing equipment or methods, specially adapted for specific applications (specially adapted for specific functions G06F 17/00;data processing systems or methods specially adapted for administrative, commercial, financial, managerial, supervisory or forecasting purposes G06Q;healthcare informatics G16H)
G06G 7/70 - Analogue computers for specific processes, systems, or devices, e.g. simulators for vehicles, e.g. to determine permissible loading of ships
G06G 7/76 - Analogue computers for specific processes, systems, or devices, e.g. simulators for traffic
G08G 1/00 - Traffic control systems for road vehicles
G08G 1/01 - Detecting movement of traffic to be counted or controlled
G08G 1/0967 - Systems involving transmission of highway information, e.g. weather, speed limits
G08G 1/0968 - Systems involving transmission of navigation instructions to the vehicle
This technology provides designs and methods for the vehicle on-board unit (OBU), which facilitates vehicle operations and control for connected automated vehicle highway (CAVH) systems. OBU systems provide vehicles with individually customized information and real-time control instructions for vehicle to fulfill the driving tasks such as car following, lane changing, route guidance. OBU systems also realize transportation operations and management services for both freeways and urban arterials. The OBU composed of the following devices: 1) a vehicle motion state parameter and environment parameter collection unit; 2) a multi-mode communication unit; 3) a location unit; 4) an intelligent gateway unit, and 5) a vehicle motion control unit. The OBU systems realize one or more of the following function categories: sensing, transportation behavior prediction and management, planning and decision making, and vehicle control. OBU is supported by real-time wired and/or wireless communication, the power supply networks, the cloud, cyber safety, security services, and the human machine interface.
H04W 4/44 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G08G 1/01 - Detecting movement of traffic to be counted or controlled
H04W 4/46 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for vehicle-to-vehicle communication [V2V]
H04W 4/80 - Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication
This technology describes one type of CAVH services focusing on fixed-route trips such as commuting, shopping, school, and other trips that users previously travel recurrently and frequently. The technology describes the system architecture of the proposed fixed-route services. The technology includes methods of calibrating, providing, and optimizing the functionalities of such fixed-route services. The detailed methods are proposed for pre-trip, enroute, trip chaining, and post-trip operations, the cyber-physical security, and privacy protection for the users and participating vehicles.
G08G 1/08 - Controlling traffic signals according to detected number or speed of vehicles
G08G 1/01 - Detecting movement of traffic to be counted or controlled
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G08G 1/00 - Traffic control systems for road vehicles
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
G05D 1/02 - Control of position or course in two dimensions
G08G 1/0967 - Systems involving transmission of highway information, e.g. weather, speed limits
78.
SAFETY TECHNOLOGIES FOR CONNECTED AUTOMATED VEHICLE HIGHWAY SYSTEMS
The present technology relates generally to systems and methods for safe vehicle operations and control of connected automated vehicle highway (CAVH) systems to operate and manage connected and automated vehicles.
This technology describes one type of CAVH services focusing on fixed-route trips such as commuting, shopping, school, and other trips that users previously travel recurrently and frequently. The technology describes the system architecture of the proposed fixed-route services. The technology includes methods of calibrating, providing, and optimizing the functionalities of such fixed-route services. The detailed methods are proposed for pre-trip, enroute, trip chaining, and post-trip operations, the cyber-physical security, and privacy protection for the users and participating vehicles.
The technology provides designs and methods for the transit management system, which facilitates transit vehicle operations and control for connected automated transit vehicles (CATVs) systems. The transit management system provides transit vehicles with customized/non-customized information and time-sensitive control instructions for transit vehicle to fulfill the driving tasks such as vehicle routing, lane changing, turning. The transit management system also realizes transit vehicle lane design, transportation operations and management services for transit vehicle. The transit management system consists of one of more of the following physical subsystems: (1) Roadside Unit (RSU) network, (2) Traffic Control Unit (TCU) and Traffic Control Center (TCC) network, (3) Vehicle Onboard Unit (OBU), (4) Traffic Operations Centers (TOCs), (5) Cloud platform. The transit management system realizes one or more of the following function categories: sensing, transportation behavior prediction and management, planning and decision making, and vehicle control. The transit management system is supported by road infrastructure, real-time wired and/or wireless communication, the power supply networks, and cyber safety and security services.
The technology provides systems and methods for a system providing customized and route-specific operations, control, and services for connected and automated vehicles (CAVs) according to user origin and destination requests, based on connected automated vehicle highway (CAVH) systems which includes an intelligent road infrastructure system providing transportation management and operations and individual vehicle control for CAV.
G08G 1/01 - Detecting movement of traffic to be counted or controlled
H04W 12/02 - Protecting privacy or anonymity, e.g. protecting personally identifiable information [PII]
G06F 21/62 - Protecting access to data via a platform, e.g. using keys or access control rules
H04L 67/10 - Protocols in which an application is distributed across nodes in the network
H04W 4/44 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
82.
VEHICLE ON-BOARD UNIT FOR CONNECTED AND AUTOMATED VEHICLE SYSTEMS
This technology provides designs and methods for the vehicle on-board unit (OBU), which facilitates vehicle operations and control for connected automated vehicle highway (CAVH) systems. OBU systems provide vehicles with individually customized information and real-time control instructions for vehicle to fulfill the driving tasks such as car following, lane changing, route guidance. OBU systems also realize transportation operations and management services for both freeways and urban arterials. The OBU composed of the following devices: 1) a vehicle motion state parameter and environment parameter collection unit; 2) a multi-mode communication unit; 3) a location unit; 4) an intelligent gateway unit, and 5) a vehicle motion control unit. The OBU systems realize one or more of the following function categories: sensing, transportation behavior prediction and management, planning and decision making, and vehicle control. OBU is supported by real-time wired and/or wireless communication, the power supply networks, the cloud, cyber safety, security services, and the human machine interface.
The technology provides designs and methods for the transit management system, which facilitates transit vehicle operations and control for connected automated transit vehicles (CATVs) systems. The transit management system provides transit vehicles with customized/non-customized information and time-sensitive control instructions for transit vehicle to fulfill the driving tasks such as vehicle routing, lane changing, turning. The transit management system also realizes transit vehicle lane design, transportation operations and management services for transit vehicle. The transit management system consists of one of more of the following physical subsystems: (1) Roadside Unit (RSU) network, (2) Traffic Control Unit (TCU) and Traffic Control Center (TCC) network, (3) Vehicle Onboard Unit (OBU), (4) Traffic Operations Centers (TOCs), (5) Cloud platform. The transit management system realizes one or more of the following function categories: sensing, transportation behavior prediction and management, planning and decision making, and vehicle control. The transit management system is supported by road infrastructure, real-time wared and/or wireless communication, the power supply networks, and cyber safety and security services.
The technology provides systems and methods for a system providing customized and route-specific operations, control, and services for connected and automated vehicles (CAVs) according to user origin and destination requests, based on connected automated vehicle highway (CAVH) systems which includes an intelligent road infrastructure system providing transportation management and operations and individual vehicle control for CAV.
This technology described herein provides embodiments of a cloud-based mobility service system for a Connected Automated Vehicle Highway (CAVH). In some embodiments, the technology provides a cloud-based mobility service system to provide the services and functionalities of different components of a CAVH system including, for example, user, vehicle, infrastructure, system, roadside, and CAVH traffic control layers. Detailed cloud-based data interfaces and services are described for each component, e.g., regarding their data needs to and from the cloud system. Cloud functionalities including the communication, computational, and analytic needs are described for each system component. The CAVH cloud services also provide integrated CAVH functionalities including planning, control, sensing, prediction, and analytics at macroscopic, mesoscopic, and microscopic levels of CAVH systems.
G08G 1/01 - Detecting movement of traffic to be counted or controlled
G06F 21/62 - Protecting access to data via a platform, e.g. using keys or access control rules
G08G 1/00 - Traffic control systems for road vehicles
G08G 1/0968 - Systems involving transmission of navigation instructions to the vehicle
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
H04W 12/02 - Protecting privacy or anonymity, e.g. protecting personally identifiable information [PII]
H04W 12/03 - Protecting confidentiality, e.g. by encryption
86.
CLOUD-BASED TECHNOLOGY FOR CONNECTED AND AUTOMATED VEHICLE HIGHWAY SYSTEMS
This technology described herein provides embodiments of a cloud-based mobility service system for a Connected Automated Vehicle Highway (CAVH). In some embodiments, the technology provides a cloud-based mobility service system to provide the services and functionalities of different components of a CAVH system including, for example, user, vehicle, infrastructure, system, roadside, and CAVH traffic control layers. Detailed cloud-based data interfaces and services are described for each component, e.g., regarding their data needs to and from the cloud system. Cloud functionalities including the communication, computational, and analytic needs are described for each system component. The CAVH cloud services also provide integrated CAVH functionalities including planning, control, sensing, prediction, and analytics at macroscopic, mesoscopic, and microscopic levels of CAVH systems.
The invention provides designs and methods for a heavy vehicle operations and control system for heavy automated vehicles, which facilitates heavy vehicle operation and control for connected automated vehicle highway (CAVH) systems. The heavy vehicle management system provides heavy vehicles with individually customized information and real-time vehicle control instructions to fulfill the driving tasks such as car following, lane changing, route guidance. The heavy vehicle management system also realizes heavy vehicle related lane design, transportation operations, and management services for both dedicated and non-dedicated lanes. The heavy vehicle management system consists of one or more of the following physical subsystems: (1) Roadside unit (RSU) network, (2) Traffic Control Unit (TCU) and Traffic Control Center (TCC) network, (3) vehicles and onboard units (OBU), (4) traffic operations centers (TOCs), and (5) cloud platform. The heavy vehicle management system realizes one or more of the following function categories: sensing, transportation behavior prediction and management, planning and decision making, and vehicle control. The heavy vehicle management system is supported by road infrastructure design, real-time wired and/or wireless communication, power supply networks, and cyber safety and security services.
The invention provides designs and methods for a heavy vehicle operations and control system for heavy automated vehicles, which facilitates heavy vehicle operation and control for connected automated vehicle highway (CAVH) systems. The heavy vehicle management system provides heavy vehicles with individually customized information and real-time vehicle control instructions to fulfill the driving tasks such as car following, lane changing, route guidance. The heavy vehicle management system also realizes heavy vehicle related lane design, transportation operations, and management services for both dedicated and non-dedicated lanes. The heavy vehicle management system consists of one or more of the following physical subsystems: (1) Roadside unit (RSU) network, (2) Traffic Control Unit (TCU) and Traffic Control Center (TCC) network, (3) vehicles and onboard units (OBU), (4) traffic operations centers (TOCs), and (5) cloud platform. The heavy vehicle management system realizes one or more of the following function categories: sensing, transportation behavior prediction and management, planning and decision making, and vehicle control. The heavy vehicle management system is supported by road infrastructure design, real-time wired and/or wireless communication, power supply networks, and cyber safety and security services.
The present invention relates to systems and methods that allocate, arrange, and distribute certain types of functions and intelligence, for connected automated vehicle highway (CAVH) systems, to facilitate vehicle operations and controls, to improve the general safety of the whole transportation system, and to ensure the efficiency, intelligence, reliability, and resilience of CAVH systems. The present invention also provides methods to define CAVH system intelligence and its levels, which are based on two dimensions: the vehicle intelligence and infrastructure intelligence.
The present invention relates to systems and methods that allocate, arrange, and distribute certain types of functions and intelligence, for connected automated vehicle highway (CAVH) systems, to facilitate vehicle operations and controls, to improve the general safety of the whole transportation system, and to ensure the efficiency, intelligence, reliability, and resilience of CAVH systems. The present invention also provides methods to define CAVH system intelligence and its levels, which are based on two dimensions: the vehicle intelligence and infrastructure intelligence.
The present invention relates to systems and methods that allocate, arrange, and distribute certain types of functions and intelligence, for connected automated vehicle highway (CAVH) systems, to facilitate vehicle operations and controls, to improve the general safety of the whole transportation system, and to ensure the efficiency, intelligence, reliability, and resilience of CAVH systems. The present invention also provides methods to define CAVH system intelligence and its levels, which are based on two dimensions: the vehicle intelligence and infrastructure intelligence.
G08G 1/01 - Detecting movement of traffic to be counted or controlled
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
G08G 1/0967 - Systems involving transmission of highway information, e.g. weather, speed limits
92.
Connected automated vehicle highway systems and methods
This invention provides a system-oriented and fully-controlled connected automated vehicle highway system for various levels of connected and automated vehicles and highways. The system comprises one or more of: 1) a hierarchical traffic control network of Traffic Control Centers (TCC's), local traffic controller units (TCUs), 2) A RSU (Road Side Unit) network (with integrated functionalities of vehicle sensors, I2V communication to deliver control instructions), 3) OBU (On-Board Unit with sensor and V2I communication units) network embedded in connected and automated vehicles, and 4) wireless communication and security system with local and global connectivity. This system provides a safer, more reliable and more cost-effective solution by redistributing vehicle driving tasks to the hierarchical traffic control network and RSU network.
G08G 1/017 - Detecting movement of traffic to be counted or controlled identifying vehicles
H04L 67/00 - Network arrangements or protocols for supporting network services or applications
G08G 1/04 - Detecting movement of traffic to be counted or controlled using optical or ultrasonic detectors
G08G 1/042 - Detecting movement of traffic to be counted or controlled using inductive or magnetic detectors
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
This invention describes the detailed implementation of a Connected Automated Vehicle Highway (CAVH) on all roadway types. As CAVH vehicles travel within a transportation network, they will pass through different types of facilities such as basic segment, freeway or arterial segment, traffic bottlenecks, weaving and merging segment, intersections, first- and last-mile segment, parking, bridges, tunnel, multi-modal terminals and etc. Those different segments and nodes within a transportation network sometimes have drastically different geometric, design, and infrastructure characteristics. In this invention, detailed subsystem design will be described for each type of roadway segment for CAVH system to execute the entire trip door-to-door.
B61L 23/24 - Control, warning or like safety means along the route or between vehicles or trains for controlling traffic in two directions over the same pair of rails using token systems, e.g. train staffs, tablets
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G06F 19/00 - Digital computing or data processing equipment or methods, specially adapted for specific applications (specially adapted for specific functions G06F 17/00;data processing systems or methods specially adapted for administrative, commercial, financial, managerial, supervisory or forecasting purposes G06Q;healthcare informatics G16H)
94.
INTELLIGENT ROAD INFRASTRUCTURE SYSTEM (IRIS): SYSTEMS AND METHODS
The invention provides systems and methods for an Intelligent Road Infrastructure System (IRIS), which facilitates vehicle operations and control for connected automated vehicle highway (CAVH) systems. IRIS systems and methods provide vehicles with individually customized information and real-time control instructions for vehicle to fulfill the driving tasks such as car following, lane changing, and route guidance. IRIS systems and methods also manage transportation operations and management services for both freeways and urban arterials. In some embodiments, the IRIS comprises or consists of one of more of the following physical subsystems: (1) Roadside unit (RSU) network, (2) Traffic Control Unit (TCU) and Traffic Control Center (TCC) network, (3) vehicle onboard unit (OBU), (4) traffic operations centers (TOCs), and (5) cloud information and computing services. The IRIS manages one or more of the following function categories: sensing, transportation behavior prediction and management, planning and decision making, and vehicle control. IRIS is supported by real-time wired and/or wireless communication, power supply networks, and cyber safety and security services.
The invention provides systems and methods for an Intelligent Road Infrastructure System (IRIS), which facilitates vehicle operations and control for connected automated vehicle highway (CAVH) systems. IRIS systems and methods provide vehicles with individually customized information and real-time control instructions for vehicle to fulfill the driving tasks such as car following, lane changing, and route guidance. IRIS systems and methods also manage transportation operations and management services for both freeways and urban arterials. In some embodiments, the IRIS comprises or consists of one of more of the following physical subsystems: (1) Roadside unit (RSU) network, (2) Traffic Control Unit (TCU) and Traffic Control Center (TCC) network, (3) vehicle onboard unit (OBU), (4) traffic operations centers (TOCs), and (5) cloud information and computing services. The IRIS manages one or more of the following function categories: sensing, transportation behavior prediction and management, planning and decision making, and vehicle control. IRIS is supported by real-time wired and/or wireless communication, power supply networks, and cyber safety and security services.
This invention provides a system-oriented solution for mobility sharing service providers to support reliable and safe operations of connected automated vehicles on major urban roads. This system can provide individual vehicles with detailed customized information and time-sensitive control instructions for vehicles to fulfill the driving tasks. The system comprises one or more of: 1) a hierarchical traffic control network of Traffic Control Centers (TCC's), local traffic controller units (TCUs), 2) A RSU (Road Side Unit) network (with integrated functionalities of vehicle sensors, I2V communication to deliver control instructions), 3) OBU (On-Board Unit with sensor and V2I communication units) network embedded in connected and automated vehicles, 4) wireless communication and security system with local and global connectivity, 5) the road network management system managing, 6) a cloud based computing and information platform, and 7) fleet operations and management subsystems.
The invention provides systems and methods for an Intelligent Road Infrastructure System (IRIS), which facilitates vehicle operations and control for connected automated vehicle highway (CAVH) systems. IRIS systems and methods provide vehicles with individually customized information and real-time control instructions for vehicle to fulfill the driving tasks such as car following, lane changing, and route guidance. IRIS systems and methods also manage transportation operations and management services for both freeways and urban arterials. In some embodiments, the IRIS comprises or consists of one of more of the following physical subsystems: (1) Roadside unit (RSU) network, (2) Traffic Control Unit (TCU) and Traffic Control Center (TCC) network, (3) vehicle onboard unit (OBU), (4) traffic operations centers (TOCs), and (5) cloud information and computing services. The IRIS manages one or more of the following function categories: sensing, transportation behavior prediction and management, planning and decision making, and vehicle control. IRIS is supported by real-time wired and/or wireless communication, power supply networks, and cyber safety and security services.
G08G 1/09 - Arrangements for giving variable traffic instructions
G08G 1/0967 - Systems involving transmission of highway information, e.g. weather, speed limits
B60W 30/165 - Control of distance between vehicles, e.g. keeping a distance to preceding vehicle automatically following the path of a preceding lead vehicle, e.g. "electronic tow-bar"
The invention provides systems and methods for an Intelligent Road Infrastructure System (IRIS), which facilitates vehicle operations and control for connected automated vehicle highway (CAVH) systems. IRIS systems and methods provide vehicles with individually customized information and real-time control instructions for vehicle driving tasks such as car following, lane changing, and route guidance. IRIS systems and methods also manage transportation operations and management services for both freeways and urban arterials. The IRIS manages one or more of the following function categories: sensing, transportation behavior prediction and management, planning and decision making, and vehicle control. IRIS is supported by real-time wired and/or wireless communication, power supply networks, and cyber safety and security services.
G06G 7/70 - Analogue computers for specific processes, systems, or devices, e.g. simulators for vehicles, e.g. to determine permissible loading of ships
G08G 1/00 - Traffic control systems for road vehicles
G01C 22/00 - Measuring distance traversed on the ground by vehicles, persons, animals or other moving solid bodies, e.g. using odometers or using pedometers
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G08G 1/01 - Detecting movement of traffic to be counted or controlled
G08G 1/0967 - Systems involving transmission of highway information, e.g. weather, speed limits
G08G 1/0968 - Systems involving transmission of navigation instructions to the vehicle
B60Q 1/54 - Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor the devices being primarily intended to indicate the vehicle, or parts thereof, or to give signals, to other traffic for indicating other intentions or conditions, e.g. request for waiting or overtaking for indicating speed
99.
Connected automated vehicle highway systems and methods
This invention provides a system-oriented and fully-controlled connected automated vehicle highway system for various levels of connected and automated vehicles and highways. The system comprises one or more of: 1) a hierarchical traffic control network of Traffic Control Centers (TCC's), local traffic controller units (TCUs), 2) A RSU (Road Side Unit) network (with integrated functionalities of vehicle sensors, I2V communication to deliver control instructions), 3) OBU (On-Board Unit with sensor and V2I communication units) network embedded in connected and automated vehicles, and 4) wireless communication and security system with local and global connectivity. This system provides a safer, more reliable and more cost-effective solution by redistributing vehicle driving tasks to the hierarchical traffic control network and RSU network.
This invention provides a system-oriented and fully-controlled connected automated vehicle highway system for various levels of connected and automated vehicles and highways. The system comprises one or more of: 1) a hierarchical traffic control network of Traffic Control Centers (TCC's), local traffic controller units (TCUs), 2) A RSU (Road Side Unit) network (with integrated functionalities of vehicle sensors, I2V communication to deliver control instructions), 3) OBU (On-Board Unit with sensor and V2I communication units) network embedded in connected and automated vehicles, and 4) wireless communication and security system with local and global connectivity. This system provides a safer, more reliable and more cost-effective solution by redistributing vehicle driving tasks to the hierarchical traffic control network and RSU network.
patents
