Provided are a method, system, and device for verifying quality assurance on a plurality of software parts. The method may include, executing a quality assurance test on each software part of the plurality of software parts to receive result data; processing the result data for each software part to extract metrics; receiving a quality gate configuration for the software part type, wherein the quality gate configuration comprises at least one metric gate; comparing the metrics for each software part based on the at least one metric gate; and based on the comparison and the quality gate configuration, outputting a result of the build and the metrics
Provided are a method, a system, and a device for managing one or more devices in a vehicle system. According to embodiments, the method may be implemented by at least one processor and may include: obtaining, from a first device, a message for requesting a service from a second device, wherein the message comprises information of an identity (ID) of the first device; determining, based on the ID of the first device, whether or not the first device is registered; based on determining that the first device is not registered, performing one or more operations to register the first device; determining whether or not the first device is successfully registered; based on determining that the first device is registered or based on determining that the first device is successfully registered, determining whether or not the first device is authenticated; and based on determining that the first device is authenticated, providing the first device the access to the requested service.
Provided are system, method, and device for performing validations of a system. According to embodiments, the system may include: a memory storage storing computer-executable instructions; and at least one processor communicatively coupled to the memory storage, wherein the at least one processor may be configured to execute the instructions to: receive at least one software part from a user; determine whether the received at least one software part passes a quality check; in response to determining that the received at least one software part passes the quality check: add the received software part to the list; and perform a first validation of the list; wherein each of the plurality of software parts specified in the list include one or more indication of a type of the quality check which a respective one of the plurality of software parts in the list passes.
Systems, methods, and other embodiments described herein relate to estimating lane boundaries using a slicing model with road data for generating maps. In one embodiment, a method includes computing three-dimensional (3D) representations that are discretized from acquired data about road edges associated with driving lanes. The method also includes deriving discrete and lateral slices of the road edges using a slicing model, the road edges are connected in a road graph that describes a mapped area. The method also includes extracting features from the lateral slices individually using a neural model for forming a histogram to estimate lane boundaries about the driving lanes. The method also includes generating a map by linking the lane boundaries individually along the road edges.
A method for detecting and responding to the detection of a compromised vehicle comprises: receiving one or more monitored inputs of a vehicle; predicting, using at least one of the monitored inputs, a predicted vehicle trajectory; detecting a detected vehicle trajectory; comparing the predicted vehicle trajectory to the detected vehicle trajectory; determining a trajectory deviation value of the predicted vehicle trajectory and the detected vehicle trajectory; in response to determining that the trajectory deviation value exceeds a pre-determined trajectory deviation threshold, generating a response action; and implementing the response action.
B60W 50/12 - Limitation de la possibilité de commande du conducteur en fonction de l'état du véhicule, p. ex. moyens de verrouillage des grandeurs d'entrées pour éviter un fonctionnement dangereux
6.
SYSTEMS AND METHODS FOR UPDATING A CURRENT BASE MODEL COMPRISING A PLURALITY OF IMAGES
Systems and methods for updating a current base model are provided. The systems include a controller programmed to obtain a current base model comprising a plurality of images, a 3D pointset, and geometric features, retrieve captured video data comprising a plurality of video frames with location data of a vehicle as the vehicle drives a route, localize the route of the vehicle and determine a pose of the vehicle using the video data from the vehicle and the current base model, identify one or more features, one or more objects, or both, present in the video data and not in the current base model, and perform a triangulation process, using the determined localization including location data of the vehicle and pose data of the vehicle, to position the identified features, the identified objects, or both, within the current base model to update the current base model.
G06V 20/58 - Reconnaissance d’objets en mouvement ou d’obstacles, p. ex. véhicules ou piétonsReconnaissance des objets de la circulation, p. ex. signalisation routière, feux de signalisation ou routes
G06T 7/70 - Détermination de la position ou de l'orientation des objets ou des caméras
G06V 10/24 - Alignement, centrage, détection de l’orientation ou correction de l’image
G06V 10/44 - Extraction de caractéristiques locales par analyse des parties du motif, p. ex. par détection d’arêtes, de contours, de boucles, d’angles, de barres ou d’intersectionsAnalyse de connectivité, p. ex. de composantes connectées
G06V 10/74 - Appariement de motifs d’image ou de vidéoMesures de proximité dans les espaces de caractéristiques
G06V 20/56 - Contexte ou environnement de l’image à l’extérieur d’un véhicule à partir de capteurs embarqués
7.
SYSTEMS AND METHODS FOR DETERMINING DIFFERENCES BETWEEN VECTOR DATASETS
In one embodiment, a method of determining changes between a first vector dataset and a second vector dataset includes receiving the first vector dataset and the second vector dataset, where each of the first vector dataset and the second vector dataset includes a plurality of features, each feature being defined by at least one vertex. The method also includes for each feature in the first vector dataset and the second vector dataset, generating a signature key based on geometric attributes of each feature, storing the signature key for each feature of the first vector dataset in a first data structure, storing the signature key for each feature of the second vector dataset in a second data structure, and comparing the first data structure to the second data structure to determine differences between the first vector dataset and the second vector dataset.
A system for using a machine learning technique to perform data association operations for positions of points that represent objects in images of a location can include a processor and a memory. The memory can store a machine learning module, a production module, and a communications module. The machine learning module can, while operating the machine learning technique, receive information and produce results of the data association operations for the positions of the points. The information can: (1) include: (a) the positions of the points that represent the objects in the images of the location and (b) a pose of a camera that produced the images, but (2) exclude pixel color data. The production module can produce, based on the results, a digital map of the location. The communications module can transmit the digital map to a specific vehicle to be used to control a movement of the specific vehicle.
The present disclosure is directed to methods and systems for tracking roadway lane markings. The method includes collecting a frame of image data of the roadway, separating a first individual lane marking from among the first frame of image data of the roadway, assigning an identifier to the separated individual lane marking, and comparing the first separated individual lane marking to a subsequent frame of image data of the roadway.
G01C 21/00 - NavigationInstruments de navigation non prévus dans les groupes
G06V 10/22 - Prétraitement de l’image par la sélection d’une région spécifique contenant ou référençant une formeLocalisation ou traitement de régions spécifiques visant à guider la détection ou la reconnaissance
G06V 10/26 - Segmentation de formes dans le champ d’imageDécoupage ou fusion d’éléments d’image visant à établir la région de motif, p. ex. techniques de regroupementDétection d’occlusion
G06V 10/62 - Extraction de caractéristiques d’images ou de vidéos relative à une dimension temporelle, p. ex. extraction de caractéristiques axées sur le tempsSuivi de modèle
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Computer application software for providing mobility as a
service [Maas] using information and communication
technology [ICT]; computer software, recorded; computer
software platforms; computer software applications,
downloadable; computer programs for connecting remotely to
computers; computer hardware and software for providing
remote access to computer and communication networks;
computer hardware; computer programs for searching remotely
for content on computers and computer networks; computer
peripheral devices; computer operating programs, recorded;
interfaces for computers; monitors [computer hardware];
wireless controllers to remotely monitor and control the
function and status of security systems; downloadable
computer software for operating, controlling and monitoring
of automated driving cars; downloadable computer software
for remote monitoring and analysis; downloadable maps;
computer software for sharpening electronic images and
compressing capacity of electronic images using deep
learning technologies; navigational instruments; apparatus
for receiving signal and data from navigation maps; computer
software for creating, facilitating, and managing remote
access to and communication with local area networks and
global networks; wireless warning devices by detecting
abnormal signals from various sensors and giving warnings;
personal digital assistants; portable radio communication
machines and apparatus; computer software platforms for
automated driving cars; computer programs for operating
control of automated driving cars; computer software for use
in remote control of automated driving cars; computer
software applications for use in remote control of automated
driving cars, downloadable; personal digital assistants for
use in remote control of automated driving cars;
telecommunication machines and apparatus for use in remote
control of automated driving cars; radio communication
machines and apparatus for use in remote control of
automated driving cars; computer programs for automated
driving cars; dashboard cameras; computer software, recorded
in computers installed with automobiles; computer hardware
installed with automobiles; computer operating programs,
recorded in computers installed with automobiles; computer
software for selecting appropriate communication lines
response to location of vehicles; computer programs for
simulators of automated driving cars; training and testing
simulators for automated driving cars; vehicular radio
communication machines and apparatus; computer programs for
simulating movement for automated driving cars in
resource-saving environmentally conscious city (smart city);
computer programs for controlling movement for automated
driving cars in resource-saving environmentally conscious
city (smart city); computer programs for simulating
management, operation and operational status for commercial
facilities in resource-saving environmentally conscious city
(smart city); computer programs for managing operation and
operational status for commercial facilities in
resource-saving environmentally conscious city (smart city);
computer programs for simulating supplying and management of
electricity, gas, water and other lifeline energy in
resource-saving environmentally conscious city (smart city);
computer programs for supplying and managing electricity,
gas, water and other lifeline energy in resource-saving
environmentally conscious city (smart city); simulators for
the steering and control of vehicles; navigation apparatus
for vehicles [on-board computers]; sensors for speed
measurements; computers and computer programs for providing
map information; computer database programs for creating and
developing map information; computer programs for map
information; telecommunication machines and apparatus; parts
and accessories for telecommunication machines and
apparatus; electronic data processing, telecommunication
machines, apparatus and their parts; electronic components;
electronic circuits, not including those recorded with
computer programs; computer programs; computers and their
peripherals; motion sensors; radio machines and apparatus;
radio communication machines and apparatus; remote controls
for radio communication machines and apparatus; computer
programs for use in operational management of transport
machines and apparatus; computer software for use in remote
control of transport machines and apparatus; computer
software applications for use in remote control of transport
machines and apparatus, downloadable; personal digital
assistants for use in remote control of transport machines
and apparatus; telecommunication machines and apparatus for
use in remote control of transport machines and apparatus;
radio communication machines and apparatus for use in remote
control of transport machines and apparatus; computer
programs for transport machines and apparatus. Software as a service [SaaS] featuring computer application
software for providing mobility as a service [Maas] using
information and communication technology [ICT]; software as
a service [SaaS] featuring computer programs for use in
operational management of automated driving cars via the
internet; computer programming services for automated
driving cars via the Internet; software as a service [SaaS]
featuring computer programs for automated driving cars via
the internet; providing information relating to computer
technology and programming via a website; energy auditing;
software as a service [SaaS]; providing online
non-downloadable software for operating, controlling and
monitoring of automated driving cars; providing online
non-downloadable software for remote monitoring and
analysis; providing online non-downloadable geographic maps;
cloud computing; development of computer platforms; computer
system analysis; design, programming and maintenance of
computer software; providing online non-downloadable
software; updating of computer software; calibration of
computer software; platform as a service [PaaS]; computer
software and hardware testing services; computer programming
services for connecting remotely to computers; providing
non-downloadable computer programs for connecting remotely
to computers; computer programming services for providing
remote access to computer and communication networks;
providing online non-downloadable software for providing
remote access to computer and communication networks;
computer technology consultancy; computer programming
services for searching remotely for content on computers and
computer networks; providing non-downloadable computer
programs for searching remotely for content on computers and
computer networks; computer programming services for
operating programs; providing non-downloadable computer
operating programs; computer programming services for remote
monitoring and analysis; computer programming services for
sharpening electronic images and compressing capacity of
electronic images using deep learning technologies;
providing non-downloadable computer programs for sharpening
electronic images and compressing capacity of electronic
images using deep learning technologies; design services;
cartographic or thermographic measurement services by drone;
computer programming services for creating, facilitating,
and managing remote access to and communication with local
area networks and global networks; providing online
non-downloadable software for creating, facilitating, and
managing remote access to and communication with local area
networks and global networks; off-site data backup;
technological research; research in the field of
environmental protection; architectural design;
architectural consultancy; research on building construction
or city planning; providing search engines for the Internet;
testing or research on prevention of pollution; software as
a service [SaaS] services in the field of automated driving
cars; platform as a service [PaaS] services in the field of
automated driving cars; testing, research, design and
development in the field of autonomous driving technology,
automated driving cars and computer software for automated
driving cars and consultancy relating thereto; scientific
and technological research and development relating to
autonomous driving technology and automated driving cars;
computer programming services for operational management of
automated driving cars; providing non-downloadable computer
programs for use in operational management of automated
driving cars; computer programming services for remote
control of automated driving cars; providing online
non-downloadable software for use in remote control of
automated driving cars; computer programming services for
automated driving cars; providing non-downloadable computer
programs for automated driving cars; computer software
design, computer programming, or maintenance of computer
software used for automated driving cars; programming of
software for selecting appropriate communication lines
response to location of vehicles; providing non-downloadable
computer programs for selecting appropriate communication
lines response to location of vehicles; development of
computer software for automated driving cars; providing
online non-downloadable software for automated driving cars;
development of software for simulator for automated driving
cars; providing online non-downloadable software for
simulator for automated driving cars; development of
simulator for automated driving cars; providing information
relating to development of simulator for automated driving
cars; consultancy in the field of energy-saving; providing
non-downloadable computer programs for simulating movement
for automated driving cars in resource-saving
environmentally conscious city (smart city); providing
non-downloadable computer programs for controlling movement
for automated driving cars in resource-saving
environmentally conscious city (smart city); providing
non-downloadable computer programs for simulating
management, operation and operational status for commercial
facilities in resource-saving environmentally conscious city
(smart city); providing non-downloadable computer programs
for managing operation and operational status for commercial
facilities in resource-saving environmentally conscious city
(smart city); providing non-downloadable computer programs
for simulating supplying and management of electricity, gas,
water and other lifeline energy in resource-saving
environmentally conscious city (smart city); providing
non-downloadable computer programs for supplying and
managing electricity, gas, water and other lifeline energy
in resource-saving environmentally conscious city (smart
city); vehicle roadworthiness testing; information
technology [IT] consultancy; map designing; mapping
services; providing search engines relating to map
information; computer programming services for computer
database for creating and developing map information;
providing online non-downloadable software for map
information; providing geographic information; testing or
research on electricity; technological advice relating to
computers, automobiles and industrial machines; computer
software design, computer programming, or maintenance of
computer software; rental of computers; providing computer
programs on data networks; urban planning; computer
programming services for operational management of transport
machines and apparatus; providing non-downloadable computer
programs for use in operational management of transport
machines and apparatus; computer programming services for
remote control of transport machines and apparatus;
providing online non-downloadable software for use in remote
control of transport machines and apparatus; computer
programming services for transport machines and apparatus;
providing non-downloadable computer programs for transport
machines and apparatus.
A system for generating a heat map corresponding to a difficult road topography includes one or more processors, network interface hardware, and one or more memory modules. When the machine-readable instructions are executed by the one or more processors, the system is caused to: receive vehicle swarm data related to at least the vehicle performance and the vehicle occupant, wherein at least a portion of the vehicle swarm data is generated by one or more vehicle sensors mounted to a vehicle of a vehicle swarm; determine the difficult road topography based on the vehicle swarm data; generate a heat map of the difficult road topography, wherein the heat map is based upon an aggregate number of times that a determination is made that a location has difficult road topography; and provide the heat map to a user though a user device.
Provided are a method, system, and device for generating synthetic images. The method may include, receiving an input image; removing at least one pre-existing object from the input image; inpainting the region where the at least one pre-existing object was removed; estimating a position of another pre-existing object from the input image; generating a layout over the input image based on the estimated position; and generating a synthetic object based on the layout.
Systems, methods, and other embodiments described herein relate to generating maps using transformer encoding that infers lane information from sliced data. In one embodiment, a method includes generating a sequence of lateral slices for a road graph using discrete three-dimensional (3D) representations, and the sequence forms a road edge connected in the road graph that topologically describes a mapped area. The method also includes identifying parameters by channelizing the sequence individually for estimating lane boundaries along the road edge. The method also includes encoding features across the sequence by a transformer correlating context and the parameters about the lateral slices. The method also includes decoding the features across the sequence using a learning model for computing a lane structure along the road graph.
G06V 10/762 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant le regroupement, p. ex. de visages similaires sur les réseaux sociaux
G06V 10/77 - Traitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source
G06V 20/56 - Contexte ou environnement de l’image à l’extérieur d’un véhicule à partir de capteurs embarqués
The present disclosure is directed to methods for estimating a route of an object. The method includes determining a first position of an object at a first time, determining a second position of the object at a second time subsequent to the first time, automatically simulating a plurality of possible routes between the first position and the second position, ranking the plurality of possible routes between the first position and the second position, and estimating a most probable route from among the plurality of possible routes between the first position and the second position.
A system for correcting an alignment of positions of points affiliated with an object, in images of a location, that has one or more of a linear feature or a planar feature can include a processor and a memory. The memory can store an alignment module and a communications module. The alignment module can include instructions to: (1) identify, within data affiliated with the images, the positions of the points affiliated with the object that has the one or more of the linear feature or the planar feature and (2) correct, in a manner that recognizes that the object has the one or more of the linear feature or the planar feature, the alignment of the positions to produce a digital map of the location. The communications module can include instructions to transmit the digital map to a vehicle to be used to control a movement of the vehicle.
G06V 20/56 - Contexte ou environnement de l’image à l’extérieur d’un véhicule à partir de capteurs embarqués
G06T 7/70 - Détermination de la position ou de l'orientation des objets ou des caméras
G06V 20/58 - Reconnaissance d’objets en mouvement ou d’obstacles, p. ex. véhicules ou piétonsReconnaissance des objets de la circulation, p. ex. signalisation routière, feux de signalisation ou routes
16.
AUTOMATED VEHICLE TESTING SYSTEM BASED ON REQUIREMENTS WRITTEN IN NATURAL LANGUAGE
Provided are a method, system, and device for automated vehicle testing. The method may include, generating a ticket, wherein the ticket comprises at least one natural language testing requirement and at least one natural language incident scenario description; determining whether collected sensor data from a vehicle matches the at least one natural language incident scenario description in the ticket; based on determining that the collected sensor data from the vehicle matches the at least one natural language incident scenario description: generating a requirements as code (RaC) file based on the ticket and collected sensor data from a vehicle; and evaluating a ML model based on the RaC file to determine whether the ML model achieves the testing requirement, wherein the ML model is used to implement a vehicle application.
System, methods, and other embodiments described herein relate to implementing surface bias estimation strategies. In one embodiment, a method includes processing probe trace data with a factor graph having nodes and factors that describe an estimate of surface bias; and correcting the probe trace data based on the estimate of surface bias.
A system for producing, from data affiliated with images of a location, a digital map can include a processor and a memory. The memory can store a productions module and a communications module. The production module can include instructions that cause the processor to produce, from the data affiliated with the images of the location, the digital map. The data, for an image, can exclude pixel color data, but can include information about: (1) a pose of a camera that produced the image and (2) one or more of a position of a point on: (a) a lane boundary of a lane of a road in the image, (b) a road boundary of the road, or (c) a landmark in the image. The communications module can include instructions that cause the processor to transmit the digital map to a vehicle to be used to control a movement of the vehicle.
Vehicle recording based terrain objective characteristic determination is performed by detecting a vehicle reaction of a vehicle, the vehicle reaction triggered by a threshold reading of at least one triggering sensor of the vehicle, recording an output of the at least one triggering sensor and at least one related sensor of the vehicle in response to detecting the vehicle reaction, and determining an objective characteristic of a terrain based on the recorded output of the at least one triggering sensor, the recorded output of the at least one related sensor, and at least one characteristic of the vehicle.
G01S 19/45 - Détermination de position en combinant les mesures des signaux provenant du système de positionnement satellitaire à radiophares avec une mesure supplémentaire
Timing-independence is provided for software. Variance is added to software such as non-determinism, randomization, and the like. A distribution of unspecified modalities associated with the software is identified. Unspecified modalities include modalities in a critical path, modalities outside of design timing constraints of the software, modalities at the edge of a timing envelope, and the like. At least part of the software is modified to eliminate the unspecified modalities, such as implementing modifications to prevent over-designing of implemented hardware and overfitting of software into the implemented hardware, optimizing execution of tasks of the software, rearranging an order of execution of non-dependent tasks not in the critical path, and the like.
Provided are a method, system, and device for configuring test parameters used in evaluating a machine learning (ML) model. The method may include: obtaining a user input comprising at least one test parameter; storing the obtained user input in a requirement as code (RAC) file; interpreting, by a requirement management interface, at least one test parameter from the RAC file; and evaluating the ML model based on the interpreted at least one test parameter from the RAC file.
Provided are a system, method, and device for managing one or more test cases of a test for testing a software of a vehicle system. According to embodiments, the method may be implemented by at least one processor and may include: presenting, to a user, a first graphical user interface (GUI) comprises information of one or more test cases available to the user; receiving, from the user, a user input defining a user selection of a test case from among the one or more available test cases; and performing at least one operation for managing the user-selected test case.
System, methods, and other embodiments described herein relate to implementing map curation management strategies. In one embodiment, a method includes receiving map data, using an auto-curation predictive model to update the map data with auto-curated data, and using a manual-curation time predictive model to estimate a manual-curation time and generate a manual-curation heat map based on the map data.
Provided are a method, system, and device for a neural architecture search (NAS) pipeline for performing an optimized neural architecture search (NAS). The method may include obtaining a first search space comprising a plurality of candidate layers for a neural network architecture; performing a training-free NAS in the first search space to obtain a first set of architectures; obtaining a second search space based on the first set of architectures; performing a gradient-based search in the second search space to obtain a second set of architectures; performing a sampling method search utilizing the second set of architectures as an initial sample; and obtaining an output architecture as an output of the sampling method search.
Program operation sequence determination for reduced potential leakage of personally identifiable information is performed by identifying a plurality of candidate program operations for capturing a data sample including first class information and second class information and reducing the second class information of the data sample, assigning a leakage cost representing potential leakage of personally identifiable information associated with each valid combination of a candidate program operation among the plurality of candidate program operations and a computational resource among a plurality of computational resources, and applying an objective function to the valid combinations and assigned leakage costs to determine a sequence of program operations, wherein each program operation of the sequence is performed by one or more selected computational resources such that the sum leakage cost is below a threshold leakage cost, and the amount of first class information is above a data threshold value.
A computer-implemented method for merging a first road graph corresponding to a first area and a second road graph corresponding to a second area that partially overlaps with the first area, the method comprising: a selection step of selecting one edge from a plurality of edges overlapping each other in the first road graph and the second road graph and deleting non-selected edge; and a merging step of determine whether or not to merge a first node, that is a node connected to the deleted edges, and in response to determination to merge the first node, selecting a second node to be merged with the first node, and merge the first node and the second node.
A computer-implemented method for combining a plurality of road graphs that partially overlap with an adjacent area, the method comprising: an acquisition step of acquiring a plurality of road graphs; a labeling step of grouping the plurality of road graphs into groups, and assigning a label to each of the road graphs in each of the groups; and a merging step of selecting one label and executing, in parallel for the groups, a process of merging a first road graph to which the selected label is assigned and a second road graph adjacent to the first road graph, wherein the merging step is repeated, with selecting a different label in each repetition, until all of the plurality of road graphs are merged.
G06T 7/187 - DécoupageDétection de bords impliquant des croissances de zonesDécoupageDétection de bords impliquant des fusions de zonesDécoupageDétection de bords impliquant un étiquetage de composantes connexes
G06T 1/00 - Traitement de données d'image, d'application générale
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Computer application software for providing mobility as a service [Maas] using information and communication technology [ICT]; computer software, recorded; computer software platforms; computer software applications, downloadable; computer programs for connecting remotely to computers; computer hardware and software for providing remote access to computer and communication networks; computer hardware; computer programs for searching remotely for content on computers and computer networks; computer peripheral devices; computer operating programs, recorded; interfaces for computers; monitors [computer hardware]; wireless controllers to remotely monitor and control the function and status of security systems; downloadable computer software for operating, controlling and monitoring of automated driving cars; downloadable computer software for remote monitoring and analysis; downloadable maps; computer software for sharpening electronic images and compressing capacity of electronic images using deep learning technologies; navigational instruments; apparatus for receiving signal and data from navigation maps; computer software for creating, facilitating, and managing remote access to and communication with local area networks and global networks; wireless warning devices by detecting abnormal signals from various sensors and giving warnings; personal digital assistants; portable radio communication machines and apparatus; computer software platforms for automated driving cars; computer programs for operating control of automated driving cars; computer software for use in remote control of automated driving cars; computer software applications for use in remote control of automated driving cars, downloadable; personal digital assistants for use in remote control of automated driving cars; telecommunication machines and apparatus for use in remote control of automated driving cars; radio communication machines and apparatus for use in remote control of automated driving cars; computer programs for automated driving cars; dashboard cameras; computer software, recorded in computers installed with automobiles; computer hardware installed with automobiles; computer operating programs, recorded in computers installed with automobiles; computer software for selecting appropriate communication lines response to location of vehicles; computer programs for simulators of automated driving cars; training and testing simulators for automated driving cars; vehicular radio communication machines and apparatus; computer programs for simulating movement for automated driving cars in resource-saving environmentally conscious city (smart city); computer programs for controlling movement for automated driving cars in resource-saving environmentally conscious city (smart city); computer programs for simulating management, operation and operational status for commercial facilities in resource-saving environmentally conscious city (smart city); computer programs for managing operation and operational status for commercial facilities in resource-saving environmentally conscious city (smart city); computer programs for simulating supplying and management of electricity, gas, water and other lifeline energy in resource-saving environmentally conscious city (smart city); computer programs for supplying and managing electricity, gas, water and other lifeline energy in resource-saving environmentally conscious city (smart city); simulators for the steering and control of vehicles; navigation apparatus for vehicles [on-board computers]; sensors for speed measurements; computers and computer programs for providing map information; computer database programs for creating and developing map information; computer programs for map information; telecommunication machines and apparatus; parts and accessories for telecommunication machines and apparatus; electronic data processing, telecommunication machines, apparatus and their parts; electronic components; electronic circuits, not including those recorded with computer programs; computer programs; computers and their peripherals; motion sensors; radio machines and apparatus; radio communication machines and apparatus; remote controls for radio communication machines and apparatus; computer programs for use in operational management of transport machines and apparatus; computer software for use in remote control of transport machines and apparatus; computer software applications for use in remote control of transport machines and apparatus, downloadable; personal digital assistants for use in remote control of transport machines and apparatus; telecommunication machines and apparatus for use in remote control of transport machines and apparatus; radio communication machines and apparatus for use in remote control of transport machines and apparatus; computer programs for transport machines and apparatus. Software as a service [SaaS] featuring computer application software for providing mobility as a service [Maas] using information and communication technology [ICT]; software as a service [SaaS] featuring computer programs for use in operational management of automated driving cars via the internet; computer programming services for automated driving cars via the Internet; software as a service [SaaS] featuring computer programs for automated driving cars via the internet; providing information relating to computer technology and programming via a website; energy auditing; software as a service [SaaS]; providing online non-downloadable software for operating, controlling and monitoring of automated driving cars; providing online non-downloadable software for remote monitoring and analysis; providing online non-downloadable geographic maps; cloud computing; development of computer platforms; computer system analysis; design, programming and maintenance of computer software; providing online non-downloadable software; updating of computer software; calibration of computer software; platform as a service [PaaS]; computer software and hardware testing services; computer programming services for connecting remotely to computers; providing non-downloadable computer programs for connecting remotely to computers; computer programming services for providing remote access to computer and communication networks; providing online non-downloadable software for providing remote access to computer and communication networks; computer technology consultancy; computer programming services for searching remotely for content on computers and computer networks; providing non-downloadable computer programs for searching remotely for content on computers and computer networks; computer programming services for operating programs; providing non-downloadable computer operating programs; computer programming services for remote monitoring and analysis; computer programming services for sharpening electronic images and compressing capacity of electronic images using deep learning technologies; providing non-downloadable computer programs for sharpening electronic images and compressing capacity of electronic images using deep learning technologies; design services; cartographic or thermographic measurement services by drone; computer programming services for creating, facilitating, and managing remote access to and communication with local area networks and global networks; providing online non-downloadable software for creating, facilitating, and managing remote access to and communication with local area networks and global networks; off-site data backup; technological research; research in the field of environmental protection; architectural design; architectural consultancy; research on building construction or city planning; providing search engines for the Internet; testing or research on prevention of pollution; software as a service [SaaS] services in the field of automated driving cars; platform as a service [PaaS] services in the field of automated driving cars; testing, research, design and development in the field of autonomous driving technology, automated driving cars and computer software for automated driving cars and consultancy relating thereto; scientific and technological research and development relating to autonomous driving technology and automated driving cars; computer programming services for operational management of automated driving cars; providing non-downloadable computer programs for use in operational management of automated driving cars; computer programming services for remote control of automated driving cars; providing online non-downloadable software for use in remote control of automated driving cars; computer programming services for automated driving cars; providing non-downloadable computer programs for automated driving cars; computer software design, computer programming, or maintenance of computer software used for automated driving cars; programming of software for selecting appropriate communication lines response to location of vehicles; providing non-downloadable computer programs for selecting appropriate communication lines response to location of vehicles; development of computer software for automated driving cars; providing online non-downloadable software for automated driving cars; development of software for simulator for automated driving cars; providing online non-downloadable software for simulator for automated driving cars; development of simulator for automated driving cars; providing information relating to development of simulator for automated driving cars; consultancy in the field of energy-saving; providing non-downloadable computer programs for simulating movement for automated driving cars in resource-saving environmentally conscious city (smart city); providing non-downloadable computer programs for controlling movement for automated driving cars in resource-saving environmentally conscious city (smart city); providing non-downloadable computer programs for simulating management, operation and operational status for commercial facilities in resource-saving environmentally conscious city (smart city); providing non-downloadable computer programs for managing operation and operational status for commercial facilities in resource-saving environmentally conscious city (smart city); providing non-downloadable computer programs for simulating supplying and management of electricity, gas, water and other lifeline energy in resource-saving environmentally conscious city (smart city); providing non-downloadable computer programs for supplying and managing electricity, gas, water and other lifeline energy in resource-saving environmentally conscious city (smart city); vehicle roadworthiness testing; information technology [IT] consultancy; map designing; mapping services; providing search engines relating to map information; computer programming services for computer database for creating and developing map information; providing online non-downloadable software for map information; providing geographic information; testing or research on electricity; technological advice relating to computers, automobiles and industrial machines; computer software design, computer programming, or maintenance of computer software; rental of computers; providing computer programs on data networks; urban planning; computer programming services for operational management of transport machines and apparatus; providing non-downloadable computer programs for use in operational management of transport machines and apparatus; computer programming services for remote control of transport machines and apparatus; providing online non-downloadable software for use in remote control of transport machines and apparatus; computer programming services for transport machines and apparatus; providing non-downloadable computer programs for transport machines and apparatus.
29.
METHOD FOR GENERATING A ROAD NETWORK USING SEGMENTATION MASK
A method comprising: selecting a position corresponding to a road from a mask image of road area, estimating road information at the first point; selecting a second point that is advanced a predetermined distance from the first point; and storing a link between the first point and the second point as a road link if it is determined that the link between the first point and the second point does not intersect any other road link already stored, wherein if it is determined that the link between the first point and the second point intersect a road link already stored, the second point is set as a new first point and the above processes are performed again.
G06V 10/26 - Segmentation de formes dans le champ d’imageDécoupage ou fusion d’éléments d’image visant à établir la région de motif, p. ex. techniques de regroupementDétection d’occlusion
G06V 10/44 - Extraction de caractéristiques locales par analyse des parties du motif, p. ex. par détection d’arêtes, de contours, de boucles, d’angles, de barres ou d’intersectionsAnalyse de connectivité, p. ex. de composantes connectées
G06V 10/77 - Traitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source
30.
METHOD FOR EXTRACTING AN INTERSECTION AREA FROM A SEGMENTATION MASK
An intersection area extraction method comprising acquiring a mask image; determining whether a target point selected from the mask image is an intersection point; and obtaining an intersection area by applying a clustering algorithm to intersection points, which are obtained by performing said determining step for a plurality of points in the mask image, and determining a resulting cluster area as the intersection area. The determination of a target point being an intersection point comprises: selecting the target point from the mask image; calculating a distance from the target point to a road boundary for a plurality of directions; and determining the target point is the intersection point if a graph, whose horizontal axis is the direction and whose vertical axis is the distance to the road boundary, has more than two peaks, and the target point is not the intersection point otherwise.
G06V 10/26 - Segmentation de formes dans le champ d’imageDécoupage ou fusion d’éléments d’image visant à établir la région de motif, p. ex. techniques de regroupementDétection d’occlusion
G06V 10/762 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant le regroupement, p. ex. de visages similaires sur les réseaux sociaux
31.
METHODS AND SYSTEMS FOR SHARING DETECTED CHANGES IN ROADS USING BLOCKCHAINS
Methods and systems are presented for sharing detected changes in roads using blockchains in a network. The network includes vehicles operable to detect a change in a road, a plurality of local blockchains, and a global blockchain. The vehicles are divided into groups of local vehicles. The plurality of local blockchains includes local blocks of changes, wherein after a first vehicle publishes a change of the road among a group of local vehicles, a block of the change is integrated into a local blockchain when at least a local threshold number of the local vehicles endorse the change. The global blockchain includes blocks of changes, wherein a block of the change is integrated into the global blockchain when at least a global threshold number of the vehicles endorse the change. A token is awarded to the first vehicle.
G06Q 30/0207 - Remises ou incitations, p. ex. coupons ou rabais
G07C 5/08 - Enregistrement ou indication de données de marche autres que le temps de circulation, de fonctionnement, d'arrêt ou d'attente, avec ou sans enregistrement des temps de circulation, de fonctionnement, d'arrêt ou d'attente
G08G 1/0967 - Systèmes impliquant la transmission d'informations pour les grands axes de circulation, p. ex. conditions météorologiques, limites de vitesse
Mobile computing network queried content capture is performed by receiving, from a server, a task executable by a mobile computing network, and a retention policy, executing the task using the mobile computing network to capture target content, assigning, to a first instance of captured target content, a probability of reducing based on the retention policy, reducing, in response to an amount of available storage becoming equal to or lower than a threshold amount, at least one of the first instance and a portion of other stored data based on the probability of reducing, and transmitting, in response to connecting to a wide area network, each instance of captured target content.
Systems and methods disclosed herein include generating weather data and location data using a sensor provided on a vehicle, determining a confidence level of the weather data and the location data, compiling the weather data and the location data into a weather map by selectively integrating the weather data based on the confidence level of the weather data, and transmitting the weather map to the vehicle for display to a user of the vehicle.
B60W 50/14 - Moyens d'information du conducteur, pour l'avertir ou provoquer son intervention
B60L 58/13 - Maintien de l’état de charge [SoC] à l'intérieur d'une plage déterminée
B60W 40/02 - Calcul ou estimation des paramètres de fonctionnement pour les systèmes d'aide à la conduite de véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier liés aux conditions ambiantes
34.
SYSTEMS AND METHODS FOR MACHINE LEARNING EVALUATION PIPELINE
Provided are a method, system, and device for evaluating a machine learning (ML) model. The method may include: receiving, by a requirements management layer, at least one requirement obtained from a storage layer; interpreting, by the requirements management layer, the at least one requirement; and transmitting, by the requirements management layer, instructions to perform an ML evaluation process to an execution layer based on the interpreted requirements, wherein the execution layer transmits an output signal with the results of the ML evaluation process upon completing the ML evaluation process.
Systems, methods, and other embodiments described herein relate to recommending road infrastructure maintenance tasks based on vehicle sensor data and infrastructure map data. In one embodiment, a system includes a processor and a memory storing machine-readable instructions. The instructions, when executed by the processor, cause the processor to infer a perceived infrastructure element by a motorist within an environment based on sensor data collected from a sensor system of a vehicle. The instructions, when executed by the processor, also cause the processor to retrieve map data associated with the environment. The map data indicates a mapped infrastructure element. The instructions, when executed by the processor, also cause the processor to recommend a maintenance task to be performed based on the map data and the sensor data.
G06Q 10/20 - Administration de la réparation ou de la maintenance des produits
G07C 5/08 - Enregistrement ou indication de données de marche autres que le temps de circulation, de fonctionnement, d'arrêt ou d'attente, avec ou sans enregistrement des temps de circulation, de fonctionnement, d'arrêt ou d'attente
36.
FEATURE IDENTIFICATION DEVICE AND FEATURE IDENTIFICATION METHOD
A feature identification device identifies a type of lane separation equipment, including at least separation poles and separation wire ropes, for separating a road by travel direction. When the type of lane separation equipment is not associated with a predetermined position on the road, the device identifies the type of the lane separation equipment based on an image in which the lane separation equipment is captured at a predetermined position by an algorithm selected from a first algorithm and a second algorithm based on whether the predetermined position is included in the two-way traffic section. When the predetermined position is included in the two-way traffic section, the device identifies the type of the lane separation equipment using the second algorithm which is capable of identifying separation poles and separation wire ropes with higher certainty than the first algorithm.
G06V 20/58 - Reconnaissance d’objets en mouvement ou d’obstacles, p. ex. véhicules ou piétonsReconnaissance des objets de la circulation, p. ex. signalisation routière, feux de signalisation ou routes
37.
POSITION ESTIMATING DEVICE, METHOD, AND COMPUTER PROGRAM FOR ESTIMATING POSITION
A position estimating device includes a processor configured to detect a first position of a vehicle traveling a predetermined road section at a first time, based on a fixed sensor installed on or near the predetermined road section, estimate a second position of the vehicle at a second time, based on the first position of the vehicle at the first time, the second time being a time when a vehicle-captured image representing a predetermined feature is generated by a vehicle-mounted camera mounted on the vehicle, and estimate a real-space position of the predetermined feature, based on the estimated second position.
G06T 7/73 - Détermination de la position ou de l'orientation des objets ou des caméras utilisant des procédés basés sur les caractéristiques
G06V 10/44 - Extraction de caractéristiques locales par analyse des parties du motif, p. ex. par détection d’arêtes, de contours, de boucles, d’angles, de barres ou d’intersectionsAnalyse de connectivité, p. ex. de composantes connectées
G06V 20/52 - Activités de surveillance ou de suivi, p. ex. pour la reconnaissance d’objets suspects
G06V 20/56 - Contexte ou environnement de l’image à l’extérieur d’un véhicule à partir de capteurs embarqués
38.
SYSTEMS AND METHODS FOR ESTIMATING LANE ELEVATION FOR GENERATING 3D MAPS
System, methods, and other embodiments described herein relate to estimating lane elevation using headings for generating three-dimensional (3D) maps. In one embodiment, a method includes augmenting positions of detected lane boundaries with headings of a vehicle from sensor data. The method also includes adding the headings to vertices of two-dimensional (2D) lines using direction vectors between the vertices, wherein the 2D lines are directed towards the detected lane boundaries. The method also includes estimating elevations of the vertices including surrounding lane boundaries using a weighted average and vehicle poses from the sensor data, the surrounding lane boundaries having locations different than the positions and the weighted average factors directional differences between the vertices. The method also includes generating a 3D map of driving lanes having stacked roads identified using the elevations.
A data collecting device includes a processor configured to determine whether snow lies around a vehicle, set a type of feature to be detected, based on the result of determination of the presence or absence of the snow, detect a feature of the set type from an image representing an area around the vehicle generated by a camera mounted on the vehicle, and generate probe data representing the detected feature.
G06V 20/56 - Contexte ou environnement de l’image à l’extérieur d’un véhicule à partir de capteurs embarqués
G06V 10/44 - Extraction de caractéristiques locales par analyse des parties du motif, p. ex. par détection d’arêtes, de contours, de boucles, d’angles, de barres ou d’intersectionsAnalyse de connectivité, p. ex. de composantes connectées
G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p. ex. des objets vidéo
40.
VEHICLE CONTROLLER, METHOD, AND COMPUTER PROGRAM FOR VEHICLE CONTROL
A vehicle controller includes a memory configured to store trajectory distribution information representing distribution of trajectories for each lane in a predetermined section of a road; and a processor configured to set a target trajectory of a vehicle by referring to the trajectory distribution information of a second lane different from a first lane being traveled by the vehicle, when the vehicle travels the predetermined section, and make the vehicle travel along the target trajectory.
The present disclosure is to provide an annotation verification method. In the annotation verification method, a first result which is a verified result of the annotation for a first image sequence included in the image sequence is acquired. Next, first reference information regarding a position of the specified target object range in each image included in the first image sequence is acquired based on the first result. Next, a position of the target object range in a target image is predicted based on reference information including the first reference information. Next, an actually-specified position of the target object range in the target image is acquired based on the result of the annotation for the target image. Then, the result of the annotation for the target image is verified by comparing the target object range at the predicted position and the target object range at the actually-specified position.
G06V 10/776 - ValidationÉvaluation des performances
G06T 7/50 - Récupération de la profondeur ou de la forme
G06T 7/70 - Détermination de la position ou de l'orientation des objets ou des caméras
G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p. ex. des objets vidéo
G06V 10/98 - Détection ou correction d’erreurs, p. ex. en effectuant une deuxième exploration du motif ou par intervention humaineÉvaluation de la qualité des motifs acquis
42.
SYNTHESIZING PROBE DATA FROM OVERHEAD IMAGING DATA
Systems, methods, and other embodiments described herein relate to improving the generation and validation of map data by synthesizing probe data. In one embodiment, a method includes acquiring imaging data about a roadway, the imaging data being from a remote source. The method includes encoding the imaging data using a probe model to generate features. The method includes generating, from the features using the probe model, probe data that compliments the imaging data for the roadway. The method includes providing the probe data that includes a vehicle trace and detections about attributes of the roadway.
A data collection instruction device includes a memory configured to store travel history of each of a plurality of vehicles; and a processor configured to select one or more vehicles satisfying a predetermined condition related to travel in an update target region of map information from among the plurality of vehicles, based on the travel history of each of the plurality of vehicles, instruct the selected one or more vehicles to collect probe data representing a predetermined feature of the update target region, via a communication device, and instruct the plurality of vehicles except the selected one or more vehicles to collect the probe data of a predetermined road section, via the communication device.
Systems, methods, and other embodiments described herein relate to improving the generation multiple vehicle traces for a roadway. In one embodiment, a method includes acquiring sensor data about a roadway, including at least imaging data of an overhead view of the roadway. The method includes generating complementary traces of the roadway using a trace model that iteratively generates the complementary traces according to learned perturbations that imitate information acquired from probe vehicles traversing the roadway, including variations between separate traversals. The method includes providing the complementary traces that include multiple vehicle traces and associated detections about attributes of the roadway.
A map information storage device stores map information which includes information relating to traffic lanes shown as a series of multiple lane position information items, and has a storage device that stores lane position information items in a number necessary for control of a vehicle, for a first zone oriented from a current location of the vehicle toward a traveling direction of the vehicle, and stores lane position information items in a number necessary to verify the end of a region where map information is provided and in a number less than the number necessary for control of the vehicle, for a second zone oriented from an end of the first zone toward the traveling direction of the vehicle.
A trajectory information collecting device includes a processor configured to determine whether a trajectory along which a host vehicle has traveled through a predetermined section is within a predetermined standard travel area, generate trajectory information by including individual position coordinates on the trajectory in the trajectory information when the trajectory is within the standard travel area, generate the trajectory information by including individual position coordinates on the trajectory and operation information indicating how much the host vehicle is operated by a driver in the predetermined section in the trajectory information when the trajectory deviates from the standard travel area, and transmit the generated trajectory information to a server via a communication device mounted on the host vehicle.
A method of collecting data in a vehicle includes receiving sensor data from at least one sensor. The method further includes determining whether one or more predetermined conditions are satisfied, wherein the one or more predetermined conditions relate to a rule for collecting sensor data. The method further includes storing the sensor data in a non-volatile memory (NVM) structure in response to a determination that at least one of the one or more predetermined conditions is satisfied. The method further includes storing the sensor data in a volatile memory (VM) structure in response to a determination that none of the one or more predetermined conditions are satisfied.
G07C 5/08 - Enregistrement ou indication de données de marche autres que le temps de circulation, de fonctionnement, d'arrêt ou d'attente, avec ou sans enregistrement des temps de circulation, de fonctionnement, d'arrêt ou d'attente
G07C 5/00 - Enregistrement ou indication du fonctionnement de véhicules
A map update device stores map information representing, for each of reference points of a predetermined feature, a representative position and a positional condition indicating a range where the reference point exists, in a map storage unit; determines whether the position of each of the reference points represented in pieces of surroundings data representing surroundings including the feature satisfies one or more positional conditions represented in the map information; and updates the map information for each of the reference points, using a position indicated by one of the one or more positional conditions as the representative position of the reference point. Positions of the reference point represented in the pieces of surroundings data obtained in a predetermined period are determined to satisfy the one of the one or more positional conditions at a rate satisfying an update condition.
A filtering device performing processing for excluding vehicle sensor data showing the results of detection of a vehicle sensor mounted in a probe vehicle includes a scoring processing part for scoring the vehicle sensor data, a determination part for comparing score of the vehicle sensor data and a first threshold value, and a filtering processing part for performing processing for excluding the vehicle sensor data based on the results of determination of the determination part.
An information processing device configured to update stored content of a storage device of a vehicle includes an execution device, a first storage unit, and a second storage unit. The execution device is configured to store data received from a different controlling device in a first storage area of the second storage unit, and request, when a prescribed update condition is met, writing of the data stored in the first storage area to the storage device, and thereafter notify the different controlling device that writing of the data has been completed. The execution device is configured to store, when writing of data to the storage device is requested, the data stored in the first storage area in the second storage area of the second storage unit, and thereafter write the data stored in the second storage area to the storage device.
A data collecting device includes a processor configured to store an image representing an area around a vehicle and generated by a camera mounted on the vehicle during travel of the vehicle 2 in a memory, generate probe data representing a predetermined feature detected from the image in the area around the vehicle, store the generated probe data in the memory, set a probe communication band, depending on the amount of a set of probe data stored in the memory, and transmit the set of probe data to a server via a communication device, using the probe communication band, prior to a set of images stored in the memory.
G01C 21/00 - NavigationInstruments de navigation non prévus dans les groupes
H04L 67/12 - Protocoles spécialement adaptés aux environnements propriétaires ou de mise en réseau pour un usage spécial, p. ex. les réseaux médicaux, les réseaux de capteurs, les réseaux dans les véhicules ou les réseaux de mesure à distance
H04N 7/18 - Systèmes de télévision en circuit fermé [CCTV], c.-à-d. systèmes dans lesquels le signal vidéo n'est pas diffusé
52.
METHODS AND NON-TRANSITORY COMPUTER READABLE STORAGE MEDIUM FOR IMAGE ANNOTATION QUALITY ASSURANCE
A method for inspecting image annotation quality in an annotated image dataset, the method including: obtaining an annotated image dataset; implementing a first inspection of X % of the annotated image dataset, the first inspection including at least one of first categories of annotation inspections; implementing a second inspection of a sample of the annotated image dataset, the second inspection including at least one of second categories of annotation inspections; and identifying errors in the annotated image dataset using the first inspection and the second inspection.
Provided are a system, method, and device for intelligent test environment allocation. According to embodiments, the method for intelligently determining one or more test environments for testing software of an embedded system, may include: obtaining, by a task allocator, capability information of a plurality of test environments; obtaining, by the task allocator, policy information of a task to be executed for testing the software of the embedded system; determining, by the task allocator, a test environment, from among the plurality of test environments, that satisfies the policy information; and allocating, by the task allocator, the task to the determined test environment, wherein the embedded system may be an in-vehicle electronic control unit (ECU), and wherein the plurality of tests environments may include at least one software-in-the-loop (SIL) test environment, at least one hardware-in-the-loop (HIL) test environment, and at least one virtual ECU (V-ECU) test environment.
System, methods, and other embodiments described herein relate to managing a unified architecture for controlling a vehicle in multiple different modes. In one embodiment, a system includes a processor and a memory storing machine-readable instructions that, when executed by the processor, cause the processor to receive an instruction that identifies a target operating mode for a vehicle; determine whether the target operating mode is different from a current operating mode of the vehicle; identify components of a unified architecture of the vehicle to activate while in the target operating mode and operating parameters for the components to activate, the unified architecture to control the vehicle in a semi-autonomous mode and an autonomous mode; configure, based on the operating parameters, the components to activate while in the target operating mode; and activate the components according to the target operating mode.
A method of in-vehicle data collection includes determining whether a first rule of a plurality of rules overlaps with any other of the plurality of rules. The method further includes identifying overlapping data collection data in response to determining that the first rule overlaps with at least one other rule of the plurality of rules. The method further includes collecting data associated with the first rule in response to detection of a trigger event. The method further includes storing a single copy of the overlapping data collection data regardless of a number of the plurality of rules that overlap with the first rule.
Mobile computing network programming for queried content capture is performed by receiving, from a client device, a query for a target content of data capturable by a fleet of mobile computing networks, the query including a target content identifier that identifies the target content, programming a task to capture the target content, the task programmed to be executed by each mobile computing network using available resources of the mobile computing network, transmitting the task to each mobile computing network; and receiving data including the target content from each mobile computing network among the fleet of mobile computing networks.
G06F 16/2458 - Types spéciaux de requêtes, p. ex. requêtes statistiques, requêtes floues ou requêtes distribuées
G06F 16/248 - Présentation des résultats de requêtes
H04W 4/44 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour les véhicules, p. ex. communication véhicule-piétons pour la communication entre véhicules et infrastructures, p. ex. véhicule à nuage ou véhicule à domicile
57.
IN-VEHICLE CAPABILITY DETERMINING SYSTEM AND METHOD OF USING
A method of requesting data from a vehicle includes determining a capability of an in-vehicle system, wherein the capability includes at least one of processing capabilities, memory capabilities or sensor capabilities. The method further includes receiving a rule, wherein the rule comprises a data collection request. The method further includes determining whether the capability of the in-vehicle system is able to satisfy the data collection request. The method further includes discarding the rule in response to a determination that the capability of the in-vehicle system is not able to satisfy the data collection request.
G07C 5/08 - Enregistrement ou indication de données de marche autres que le temps de circulation, de fonctionnement, d'arrêt ou d'attente, avec ou sans enregistrement des temps de circulation, de fonctionnement, d'arrêt ou d'attente
G06Q 20/02 - Architectures, schémas ou protocoles de paiement impliquant un tiers neutre, p. ex. une autorité de certification, un notaire ou un tiers de confiance
G06Q 20/34 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des cartes, p. ex. cartes à puces ou cartes magnétiques
G07C 5/00 - Enregistrement ou indication du fonctionnement de véhicules
58.
ASSISTANT SYSTEM, ASSISTANT METHOD, AND NON-TRANSITORY COMPUTER READABLE RECORDING MEDIUM
An assistant system for providing a service in response to a request from a user is provided. The assistant system executes first process and a second process. The first process includes selecting content data to be notified to the user from a plurality of pieces of content data, acquiring an evaluation of the user for the notified content data, and updating a preference model of the user based on the acquired evaluation and preference information linked with the notified content data. The second process includes extracting, based on the preference model, one or more pieces of content data having a high degree of matching with preference of the user, and providing the service using the extracted one or more pieces of content data. from the plurality of pieces of content data.
A data collecting device includes a processor configured to detect a predetermined feature in an area around a vehicle during travel of the vehicle from an image representing the area around the vehicle generated by a camera mounted on the vehicle, generate probe data, based on the detected feature, store the generated probe data in a memory, and transmit, upon or after entry of the vehicle into a collection target region, the probe data generated in the collection target region and an additional section traveled by the vehicle immediately before the entry or immediately after an exit of the vehicle from the collection target region as well as the image generated in the collection target region to a server via a communication device mounted on the vehicle.
G06V 20/56 - Contexte ou environnement de l’image à l’extérieur d’un véhicule à partir de capteurs embarqués
G06V 10/44 - Extraction de caractéristiques locales par analyse des parties du motif, p. ex. par détection d’arêtes, de contours, de boucles, d’angles, de barres ou d’intersectionsAnalyse de connectivité, p. ex. de composantes connectées
60.
MITIGATING AN EFFECT OF A COLLISION BETWEEN A VEHICLE AND AN OBSTACLE
A system for mitigating an effect of a collision between a vehicle and an obstacle can include a processor and a memory. The memory can store a seat occupancy determination module and a set of modules including a candidate response determination module, a candidate response evaluation module, and a controller module. The seat occupancy determination module can determine a state of a seat with respect to being occupied by a living being, the seat being on a first side opposite of a second side at which an operator is located. The set of modules can cause, in response to the state being: (1) occupied, a first set of operations to be implemented and (2) unoccupied, a second set of operations to be implemented. Each of the first set and the second set can be different from a current trajectory of the vehicle and can mitigate the effect of the collision.
B60W 30/09 - Entreprenant une action automatiquement pour éviter la collision, p. ex. en freinant ou tournant
B60W 10/18 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de freinage
B60W 10/20 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de direction
B60W 30/095 - Prévision du trajet ou de la probabilité de collision
B60W 40/08 - Calcul ou estimation des paramètres de fonctionnement pour les systèmes d'aide à la conduite de véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier liés aux conducteurs ou aux passagers
A system for causing a vibration within a vehicle to change a degree of somnolence of an occupant of the vehicle can include a processor and a memory. The memory can store an occupant age discrimination and a controller module. The occupant age discrimination can include instructions that, when executed by the processor, cause the processor to determine that the occupant of the vehicle is a child. The controller module can include instructions that, when executed by the processor, cause the processor to cause, in response to a determination that the occupant is the child, the vehicle to move in a manner to induce the vibration within the vehicle to change the degree of somnolence of the occupant from an undesired state, of the degree of somnolence, to a desired state of the degree of somnolence.
B60W 40/08 - Calcul ou estimation des paramètres de fonctionnement pour les systèmes d'aide à la conduite de véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier liés aux conducteurs ou aux passagers
B60W 40/06 - Calcul ou estimation des paramètres de fonctionnement pour les systèmes d'aide à la conduite de véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier liés aux conditions ambiantes liés à l'état de la route
B60W 60/00 - Systèmes d’aide à la conduite spécialement adaptés aux véhicules routiers autonomes
62.
SYSTEMS AND METHODS FOR AUDITING IMAGE INSPECTION QUALITY
Provided are a method, system, and device for auditing the inspection of image annotation quality in an annotated image dataset. The method may include: obtaining an annotated image dataset; determining, based on a predetermined confidence interval, a predetermined target error ratio, and a predetermined interval width, a minimum number of inspections of the annotated image set; selecting a plurality of frames of the annotated image dataset for inspection based on the minimum number of inspections; and outputting the selected plurality of frames of the annotated image dataset for inspection.
A method of collecting data in a vehicle includes receiving a set of rules; detecting a trigger event using a sensor connected to the vehicle; determining whether the detected trigger event is associated with a plurality of rules of the set of rules; and prioritizing each rule of the plurality of rules in response to a determination that the detected trigger event is associated with each of the plurality of rules. The method further includes determining whether resources within the vehicle are sufficient to implement a first data collection protocol for a highest priority rule; launching the highest priority rule in response to a determination that the resources within the vehicle are sufficient to implement the first data collection protocol; and preventing launch of the highest priority rule in response to a determination that the resources within the vehicle are insufficient to implement the first data collection protocol.
G06F 9/50 - Allocation de ressources, p. ex. de l'unité centrale de traitement [UCT]
G07C 5/12 - Enregistrement ou indication de données de marche autres que le temps de circulation, de fonctionnement, d'arrêt ou d'attente, avec ou sans enregistrement des temps de circulation, de fonctionnement, d'arrêt ou d'attente sous forme de graphique
64.
SYSTEM AND METHOD FOR ONE-SHOT NEURAL ARCHITECTURE SEARCH WITH SELECTIVE TRAINING
A method for performing a one-shot neural architecture search (NAS) includes obtaining an overall network, the overall network including a plurality of candidate subnetworks for the one-shot NAS, obtaining a first subnetwork of the plurality of candidate subnetworks from the overall network, obtaining a first metric value of the first subnetwork, determining whether the first metric value satisfies a first predetermined condition, based on determining that the first metric value does not satisfy the first predetermined condition, determining not to train the obtained first subnetwork for the one-shot NAS and obtaining a second subnetwork of the plurality of candidate subnetworks from the overall network, and training the second subnetwork for the one-shot NAS.
Provided are method, system, and device for performing an optimized neural architecture search (NAS) by using both a gradient-based search and a sampling method on a search space. The method may include obtaining a first search space comprising a plurality of candidate layers for a neural network architecture; performing a gradient-based search in the first search space to obtain a first architecture; performing a sampling method search utilizing the first architecture as an initial sample; and obtaining a second architecture as an output of the sampling method search.
Provided are method, system, and device for collecting data associated with an event from vehicles. The method may be implemented by programmed one or more processors in a server for collecting evidence to investigate an event, and may include: obtaining a time and a location for the event to be investigated; transmitting a signal including the time and the location for requesting sensor data corresponding to the event from a plurality of vehicles; receiving the sensor data corresponding to the event from at least one of the plurality of vehicles; and providing the received sensor data for investigating the event.
G07C 5/00 - Enregistrement ou indication du fonctionnement de véhicules
G01S 17/89 - Systèmes lidar, spécialement adaptés pour des applications spécifiques pour la cartographie ou l'imagerie
G06T 7/50 - Récupération de la profondeur ou de la forme
G07C 5/08 - Enregistrement ou indication de données de marche autres que le temps de circulation, de fonctionnement, d'arrêt ou d'attente, avec ou sans enregistrement des temps de circulation, de fonctionnement, d'arrêt ou d'attente
67.
SYSTEM AND METHOD FOR APPLYING VEHICLE OPERATIONAL RULES ON DEMAND AND OVER THE AIR
Provided are method, system, and device for applying vehicle operational rules on demand and over the air. The method may be implemented by programmed one or more processors in a client terminal, for setting an operational rule of a vehicle, the method comprising; outputting a user interface for setting an operational rule for controlling one or more components of a vehicle; receiving, via a user input to the user interface, a setting of the operational rule; and transmitting the received setting to a server to implement the operational rule on the fly via an over-the-air transmission to the vehicle.
B60K 35/00 - Instruments spécialement adaptés aux véhiculesAgencement d’instruments dans ou sur des véhicules
B60R 16/023 - Circuits électriques ou circuits de fluides spécialement adaptés aux véhicules et non prévus ailleursAgencement des éléments des circuits électriques ou des circuits de fluides spécialement adapté aux véhicules et non prévu ailleurs électriques pour la transmission de signaux entre des parties ou des sous-systèmes du véhicule
G06F 21/32 - Authentification de l’utilisateur par données biométriques, p. ex. empreintes digitales, balayages de l’iris ou empreintes vocales
68.
SYSTEM AND METHOD FOR DETECTION AND REPORTING OF EVENTS
Provided are method, system, and device for detection and reporting of events. The method may be implemented by programmed one or more processors in a vehicle, and may include: obtaining sensor data from at least one sensor device on the vehicle; processing the obtained sensor data to determine whether a predetermined event outside of the vehicle has occurred; and based on the predetermined event being determined to have occurred, transmitting information corresponding to the predetermined event to a server.
Systems and methods are provided for applying shadow assisted driving systems (ADS) to a vehicle. The system can receive sensor data and deliver a takeover request to the vehicle operator based on the sensor data. An end boundary can be determine to disengage an ADS feature from the vehicle. A disengage boundary can be set where the vehicle can disengage before the end boundary. The system can determine when the vehicle operator responds to the takeover request based on the sensor data, which can cause the ADS to shadow the vehicle operator based on a determination that the vehicle operator did not take over operation of the vehicle at the disengage boundary.
B60W 60/00 - Systèmes d’aide à la conduite spécialement adaptés aux véhicules routiers autonomes
B60W 40/08 - Calcul ou estimation des paramètres de fonctionnement pour les systèmes d'aide à la conduite de véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier liés aux conducteurs ou aux passagers
B60W 50/14 - Moyens d'information du conducteur, pour l'avertir ou provoquer son intervention
70.
Systems and methods for triggering lights remotely to measure operator vigilance
System, methods, and other embodiments described herein relate to implementing operator vigilance tests. In one embodiment, a method includes sending from a first vehicle a light activation request to a second vehicle; detecting a light activation by the second vehicle via the first vehicle; and determining a measure of operator vigilance in the first vehicle based on a vehicle operator response to the light activation.
B60W 40/08 - Calcul ou estimation des paramètres de fonctionnement pour les systèmes d'aide à la conduite de véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier liés aux conducteurs ou aux passagers
B60W 50/16 - Signalisation tactile au conducteur, p. ex. vibration ou augmentation de la résistance sur le volant ou sur la pédale d'accélérateur
B60W 60/00 - Systèmes d’aide à la conduite spécialement adaptés aux véhicules routiers autonomes
G06V 20/58 - Reconnaissance d’objets en mouvement ou d’obstacles, p. ex. véhicules ou piétonsReconnaissance des objets de la circulation, p. ex. signalisation routière, feux de signalisation ou routes
G06V 20/59 - Contexte ou environnement de l’image à l’intérieur d’un véhicule, p. ex. concernant l’occupation des sièges, l’état du conducteur ou les conditions de l’éclairage intérieur
B60W 50/14 - Moyens d'information du conducteur, pour l'avertir ou provoquer son intervention
71.
SYSTEMS AND METHODS FOR ESTIMATING OPERATOR VIGILANCE BY ANALYZING OPERATOR TRACKING
System, methods, and other embodiments described herein relate to vigilance evaluator. In one embodiment, a method includes displaying a reference trajectory for a vehicle; constraining vehicle operator inputs applied to the vehicle; receiving tracking performance data from the vehicle; and determining a measure of operator vigilance based on comparing the tracking performance data with the reference trajectory.
B60W 50/12 - Limitation de la possibilité de commande du conducteur en fonction de l'état du véhicule, p. ex. moyens de verrouillage des grandeurs d'entrées pour éviter un fonctionnement dangereux
72.
SYSTEMS AND METHODS FOR IMPLEMENTING LOW COMPLEXITY TAKEOVER REQUEST LOCATIONS
System, methods, and other embodiments described herein relate to implementing low complexity takeover request locations. In one embodiment, a method includes receiving a potential disengagement event; determining a default takeover location based on the potential disengagement event; determining a preferred takeover location prior to the default takeover location; and generating a takeover request at the preferred takeover location.
System, methods, and other embodiments described herein relate to providing post-takeover complexity. In one embodiment, a method includes receiving a potential disengagement event; determining a takeover location based on the potential disengagement event; determining a post-takeover complexity measure based on the takeover location; and generating a notification based on the post-takeover complexity measure.
A reference trajectory generating device includes a processor configured to classify a plurality of trajectories of travel of at least one vehicle through a predetermined section of a road into a plurality of classes by clustering of the trajectories in the predetermined section, select a class including the most trajectories of the classes, and generate a reference trajectory serving as a reference in the predetermined section by averaging individual trajectories included in the class selected from the classes.
B60W 60/00 - Systèmes d’aide à la conduite spécialement adaptés aux véhicules routiers autonomes
B60W 40/06 - Calcul ou estimation des paramètres de fonctionnement pour les systèmes d'aide à la conduite de véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier liés aux conditions ambiantes liés à l'état de la route
A method includes receiving a first model and collecting sensor data acquired by a sensor on a first vehicle. The method also includes identifying a first data item from among the collected sensor data when the first data item is determined to satisfy a criterion. The method further include detecting an object contained in the identified first data item by running the first model with the identified first data item as input and establishing communication with a computer on a second vehicle located at equal to or less than a predetermined distance from the first vehicle. The method also includes receiving a second data item that is indicated as containing the object from the computer on the second vehicle and generating a training dataset. The method further includes training with respect to the first model on the training dataset and transmitting first data representing the trained first model.
Provided are method, system, and device for managing installation order of vehicle applications. According to embodiments, a method for specifying an installation order for application packages in a vehicle is provided, the method including: downloading, by at least one processor of the vehicle, a plurality of application packages; obtaining, by the at least one processor, a user-designated installation order for the plurality of application packages; and installing the plurality of application packages in accordance with the obtained user-designated installation order.
A method for overriding a manually disabled advanced driver assistance system (ADAS) safety feature is described. The method includes activating background operation of the manually disabled ADAS safety feature. The method also includes monitoring driving safety violations by a vehicle operator detected by the background operation of the manually disabled ADAS safety feature during vehicle operation. The method further includes determining whether the vehicle operator is impaired based on monitoring of the vehicle operator. The method also includes re-enabling the manually disabled ADAS safety feature to issue an alert to the vehicle operator when the vehicle operator is impaired and a number of driving safety violations is greater than a predetermined safety threshold.
B60W 50/12 - Limitation de la possibilité de commande du conducteur en fonction de l'état du véhicule, p. ex. moyens de verrouillage des grandeurs d'entrées pour éviter un fonctionnement dangereux
A61B 5/18 - Dispositifs pour l'exécution des tests de capacité pour conducteurs de véhicules
B60W 30/12 - Maintien de la trajectoire dans une voie de circulation
B60W 50/16 - Signalisation tactile au conducteur, p. ex. vibration ou augmentation de la résistance sur le volant ou sur la pédale d'accélérateur
78.
SYSTEMS AND METHODS FOR ANALYZING VERTICAL FORCE ON A STEERING COLUMN FOR DETERMINING OPERATOR VIGILANCE
System, methods, and other embodiments described herein relate to vigilance evaluator. In one embodiment, a method includes receiving a vertical force measurement based on a force sensor attached to a steering column; and estimating a level of operator vigilance based on the vertical force measurement.
B60W 40/08 - Calcul ou estimation des paramètres de fonctionnement pour les systèmes d'aide à la conduite de véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier liés aux conducteurs ou aux passagers
B60W 40/02 - Calcul ou estimation des paramètres de fonctionnement pour les systèmes d'aide à la conduite de véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier liés aux conditions ambiantes
Systems, methods, and other embodiments described herein relate to keeping an operator of a host vehicle that is semi-autonomous or autonomous engaged. In one embodiment, a method includes determining whether a disengagement ratio of the host vehicle is below a predetermined threshold value and determining whether driving conditions at an upcoming road segment are conducive for disengagement of autonomous vehicle control in the host vehicle. The method includes disengaging the autonomous vehicle control in the host vehicle in response to at least the disengagement ratio being below the predetermined threshold value and the driving conditions being conducive for the disengagement of the autonomous vehicle control.
Systems, methods, and other embodiments described herein relate to improving passenger compartment air quality in a vehicle. In one embodiment, a method includes, responsive to acquiring sensor data that includes at least air quality information about a surrounding environment of an ego vehicle, analyzing the sensor data to determine whether the air quality information satisfies an action threshold specifying that air around the ego vehicle is of a poor quality. The method includes identifying a source of the air having the poor quality, including whether a leading vehicle in front of the ego vehicle is the source. The method includes generating a response to the air having the poor quality according to the source. The method includes controlling the ego vehicle according to the response.
A system for aiding an individual to cause a vehicle to make a turn correctly can include a processor and a memory. The memory can store a communications module and a controller module. The communications module can cause the processor to obtain information about a specific side of a road on which the vehicle is to be operated. The communications module can cause the processor to obtain information about a degree of familiarity of the individual in operating the vehicle on the specific side. The communications module can cause the processor to obtain information about a direction of the turn. The controller module can cause the processor to cause, in response to the degree of familiarity being less than a threshold and based on the information about the direction, a visual aid to be possibly presented to aid the individual to cause the vehicle to make the turn correctly.
B60W 50/14 - Moyens d'information du conducteur, pour l'avertir ou provoquer son intervention
B60Q 1/50 - Agencement des dispositifs de signalisation optique ou d'éclairage, leur montage, leur support ou les circuits à cet effet les dispositifs ayant principalement pour objet d'indiquer le contour du véhicule ou de certaines de ses parties, ou pour engendrer des signaux au bénéfice d'autres véhicules pour indiquer d'autres intentions ou conditions, p. ex. demandes d'attente ou de dépassement
B60W 40/08 - Calcul ou estimation des paramètres de fonctionnement pour les systèmes d'aide à la conduite de véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier liés aux conducteurs ou aux passagers
82.
ADJUSTING ARRIVAL TIME BASED ON DESTINATION CONDITIONS
An estimated time of arrival of a vehicle can be adjusted based on conditions at a destination. An arrival time at a destination can be determined. It can be determined whether a condition will exist at the destination at the arrival time. Responsive to determining that the condition will exist at the destination at the arrival time, a route and/or a navigation of the vehicle can be adjusted to arrive at the destination to avoid the condition.
System, methods, and other embodiments described herein relate to mode confusion avoidance. In one embodiment, a method includes selecting a routine path; determining a likelihood of expected autonomous driving assistance based on a location within the routine path; and generating a notification if autonomous driving assistance has not been enabled and the likelihood exceeds a threshold.
Systems and methods for assisting an operator in operating vehicle controls are disclosed herein. One embodiment detects that an operator is touching a control in a vehicle and automatically takes, in response to the operator touching the control, one or more actions to assist the operator with regard to the vehicle being a left-hand-drive vehicle or a right-hand-drive vehicle.
System, methods, and other embodiments described herein relate to enhancing operator vigilance without causing an adverse reaction. In one embodiment, a method includes receiving a disengagement likelihood; operating a steering system controlling one or more wheels based on a steering signal; selecting a stimulus pattern that if executed causes the steering system to deviate the one or more wheels from the steering signal; and executing the stimulus pattern if the disengagement likelihood is above a first threshold.
B60W 40/08 - Calcul ou estimation des paramètres de fonctionnement pour les systèmes d'aide à la conduite de véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier liés aux conducteurs ou aux passagers
B60W 10/20 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de direction
86.
SYSTEMS AND METHODS FOR ENHANCING OPERATOR VIGILANCE
System, methods, and other embodiments described herein relate to enhancing operator vigilance without causing an adverse reaction. In one embodiment, a method includes receiving a disengagement likelihood; selecting a stimulus pattern that if executed adjusts a vehicle function; and executing the stimulus pattern if the disengagement likelihood is above a first threshold and below a second threshold.
B60W 50/16 - Signalisation tactile au conducteur, p. ex. vibration ou augmentation de la résistance sur le volant ou sur la pédale d'accélérateur
B60W 40/08 - Calcul ou estimation des paramètres de fonctionnement pour les systèmes d'aide à la conduite de véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier liés aux conducteurs ou aux passagers
87.
SYSTEM AND METHOD FOR SELF-SUPERVISED FEDERATED LEARNING FOR AUTOMOTIVE APPLICATIONS
A method includes receiving, from one or more server computers through a communication network, an edge model and collecting sensor data acquired by a sensor on a vehicle. The method also includes identifying a first data item from among the collected sensor data when the first data item is determined to satisfy a criterion. The method further includes applying a transformation to the identified first data item to generate a second data item to form a training dataset containing the first data item, the second data item, and a signal representing the transformation between the first data item and the second data item. The method further includes training with respect to the edge model on the training dataset and transmitting first data representing the trained edge model to the one or more server computers though the communication network.
A method includes receiving, from one or more server computers through a communication network, a first model and collecting sensor data acquired by a sensor on a vehicle. The method also includes identifying a first data item from among the collected sensor data when the first data item is determined to satisfy a criterion. The method further include deriving an inference signal by running a trained second model using the first data item as input to the second model to provide a training dataset that contains the identified first data item and the derived inference signal as a supervision signal corresponding to the identified first data item. The method further includes training with respect to the first model on the training dataset and transmitting first data representing the trained first model to the one or more server computers though the communication network.
A method and system for scheduling data transfer requests for a plurality of electronic control units (ECUs) connected to a network in a vehicle. The system includes: at least one memory storing first instructions and second instructions; a first ECU; and a plurality of second ECUs, wherein the first ECU is configured to execute the first instructions to configure a plurality of phases that are time slices for transferring data over the network, and wherein each of the plurality of second ECUs is configured to execute the second instructions to: maintain a data transfer request queue divided into a plurality of priority levels respectively corresponding to the plurality of phases; and transfer a data transfer request in the queue during a phase corresponding to a priority level for the data transfer request.
H04L 47/70 - Contrôle d'admissionAllocation des ressources
H04L 67/12 - Protocoles spécialement adaptés aux environnements propriétaires ou de mise en réseau pour un usage spécial, p. ex. les réseaux médicaux, les réseaux de capteurs, les réseaux dans les véhicules ou les réseaux de mesure à distance
90.
INCREASING OPERATOR VIGILANCE BY MODIFYING LONGITUDINAL VEHICLE DYNAMICS
Systems and methods are provided for modulating longitudinal vehicle dynamics according to a calculated probability of future unplanned disengagement of a driving automation system. In particular, some embodiments aim to alert drivers of both a likelihood of unplanned disengagement, as well as a source of unplanned disengagement.
Systems, methods, and other embodiments described herein relate to generating a semantic map for a road portion. In one embodiment, a method includes receiving sensor data related to a road portion. The sensor data includes trace points and key points associated with the trace points. The trace points are related to positions of a vehicle in the road portion and the key points are related to lane boundaries. The method includes determining a relationship between the trace points based on the key points and determining characteristics of the road portion based on the relationship.
Systems, methods, and other embodiments described herein relate to implementing and calibrating a learning model for inferring operator intent by estimating grip intensity. In one embodiment, a method includes estimating, using a learning model during a driving scenario, first grip intensity on a steering device for a vehicle according to initial image data depicting a hand of an operator gripping outside the set areas that have pressure sensors. The method also includes calibrating the learning model for the operator and the steering device using grip measurements and additional image data acquired from gripping inside the set areas. The method also includes computing, using the learning model during the driving scenario, second grip intensity outside the set areas on the steering device according to hand images acquired about the operator. The method also includes adapting a vehicle parameter of the vehicle according to the second grip intensity.
G06V 20/59 - Contexte ou environnement de l’image à l’intérieur d’un véhicule, p. ex. concernant l’occupation des sièges, l’état du conducteur ou les conditions de l’éclairage intérieur
B60R 1/29 - Dispositions de visualisation en temps réel pour les conducteurs ou les passagers utilisant des systèmes de capture d'images optiques, p. ex. des caméras ou des systèmes vidéo spécialement adaptés pour être utilisés dans ou sur des véhicules pour visualiser une zone à l’intérieur du véhicule, p. ex. pour visualiser les passagers ou le chargement
B60W 50/06 - Détails des systèmes d'aide à la conduite des véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier pour améliorer la réponse dynamique du système d'aide à la conduite, p. ex. pour améliorer la vitesse de régulation, ou éviter le dépassement de la consigne ou l'instabilité
B60W 50/08 - Interaction entre le conducteur et le système d'aide à la conduite
B60W 50/14 - Moyens d'information du conducteur, pour l'avertir ou provoquer son intervention
G01L 5/22 - Appareils ou procédés pour la mesure des forces, du travail, de la puissance mécanique ou du couple, spécialement adaptés à des fins spécifiques pour la mesure de la force appliquée aux organes de commande, p. ex. organes de commande des véhicules, détentes
G06T 7/50 - Récupération de la profondeur ou de la forme
G06V 10/774 - Génération d'ensembles de motifs de formationTraitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source méthodes de Bootstrap, p. ex. "bagging” ou “boosting”
G06V 40/10 - Corps d’êtres humains ou d’animaux, p. ex. occupants de véhicules automobiles ou piétonsParties du corps, p. ex. mains
93.
GUIDING AN INDIVIDUAL TO CAUSE A VEHICLE TO MAKE A TURN CORRECTLY
A system for guiding an individual to cause a vehicle to make a turn correctly can include a processor and a memory. The memory can store a communications module and an actuation module. The communications module can cause the processor to obtain information about a specific side of a road on which the vehicle is to be operated. The communications module can cause the processor to obtain information about a degree of familiarity of the individual in operating the vehicle on the specific side. The actuation module can cause the processor to cause, in response to the degree of familiarity being less than a threshold, a possible change to a normal operation of a steering operator interface of the vehicle, in response to a receipt of an input from the individual, to guide the individual to cause the vehicle to make the turn correctly.
B62D 15/02 - Indicateurs de direction ou aides de direction
B62D 6/00 - Dispositions pour la commande automatique de la direction en fonction des conditions de conduite, qui sont détectées et pour lesquelles une réaction est appliquée, p. ex. circuits de commande
94.
SYSTEM AND METHOD FOR GENERATING A SEMANTIC MAP FOR A ROAD
Systems, methods, and other embodiments described herein relate to generating a semantic map for a road segment. In one embodiment, a method includes receiving sensor data related to a road segment, generating an orthogonal axis related to the road segment, and projecting the sensor data onto the orthogonal axis. The method includes generating a range of weighting functions based on potential characteristics of the road segment and determining a plurality of scores based on applying the range of weighting functions to the sensor data along the orthogonal axis. The method includes selecting one weighting function from the range of weighting functions based on one score of the plurality of scores, where the one score is a highest score. The method includes determining characteristics of the road segment based on the selected weighting function.
Systems, methods, and other embodiments described herein relate to generating a semantic map for a road segment. In one embodiment, a method includes receiving sensor data related to a road segment. The sensor data includes trace points and key points associated with the trace points. The trace points are related to positions of a vehicle in the road segment and the key points are related to lane boundaries. The method includes generating hypothetical lane configurations, generating scores based on how accurately the key points match the hypothetical lane configurations, and selecting one hypothetical lane configuration from the hypothetical lane configurations based on a score among the scores. The score indicating most accurate match. The method includes determining characteristics of the road segment based on the one hypothetical lane configuration.
Described herein are systems and methods for determining a trajectory for a vehicle. In one example, a system includes a processor and a memory in communication with the processor having a planning module. The planning module includes instructions that, when executed by the processor, cause the processor to determine, using a unified neural network based on input information, ego vehicle future trajectories of the ego vehicle and agent future trajectories of one or more agents, select one of the ego vehicle future trajectories as a selected trajectory based on the ego vehicle future trajectories and agent future trajectories using a cost function, and cause the ego vehicle to execute the selected trajectory.
A system for refining a trained autonomous control model is disclosed. The system includes a computing device configured to execute a simulation of a trained autonomous control model for a vehicle model in a simulation environment based on a predefined dataset defining a virtual driving environment and implement a fallback layer configured to detect a failure. In response to the fallback layer detecting the failure of the trained autonomous control model under simulation, the computing device is configured to identify an event in the simulation environment corresponding to the failure of the trained autonomous control model, select additional training data from a data corpus, the additional training data is analogous to the event, and execute a training process to refine the trained autonomous control model using the additional training data such that the trained autonomous control model learns to handle the event with fewer failures.
B60W 50/06 - Détails des systèmes d'aide à la conduite des véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier pour améliorer la réponse dynamique du système d'aide à la conduite, p. ex. pour améliorer la vitesse de régulation, ou éviter le dépassement de la consigne ou l'instabilité
B60W 50/02 - Détails des systèmes d'aide à la conduite des véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier pour préserver la sécurité en cas de défaillance du système d'aide à la conduite, p. ex. en diagnostiquant ou en palliant à un dysfonctionnement
B60W 60/00 - Systèmes d’aide à la conduite spécialement adaptés aux véhicules routiers autonomes
G05B 13/02 - Systèmes de commande adaptatifs, c.-à-d. systèmes se réglant eux-mêmes automatiquement pour obtenir un rendement optimal suivant un critère prédéterminé électriques
98.
Systems and methods for assisting a vehicle driver at a roundabout
Systems and methods for assisting a vehicle driver at a roundabout are disclosed herein. One embodiment determines that a vehicle is approaching and is within a predetermined distance from a roundabout and plays, in a passenger compartment of the vehicle in response to the determining that the vehicle is approaching and is within the predetermined distance from the roundabout, an audio prompt such that the audio prompt is panned from a first speaker on a first side of the vehicle to a second speaker on a second side of the vehicle opposite the first side of the vehicle to indicate, to a driver of the vehicle, a correct direction in which to traverse the roundabout to assist the driver with regard to the roundabout being a right-hand-traffic (RHT) roundabout or a left-hand-traffic (LHT) roundabout.
B60W 30/08 - Anticipation ou prévention de collision probable ou imminente
G08G 1/0967 - Systèmes impliquant la transmission d'informations pour les grands axes de circulation, p. ex. conditions météorologiques, limites de vitesse
Aspects of the present disclosure provide techniques for training a machine-learning model to compress map data for use online by an autonomous vehicle and techniques for compressing map data using the trained machine-learning model. A system includes a computing device configured to deploy a simulation environment initiating an instance of a virtual vehicle, execute iterations of a simulation of the virtual vehicle, wherein each iteration: deploys a set of map data compressed by the machine-learning compression model and causes the virtual vehicle to execute control operations based on the deployed set of map data, evaluate performance of the executed control operations by the virtual vehicle based on the compressed map data for each iteration, and train the machine-learning compression model to compress map data such that the evaluated performance of the executed control operations by the virtual vehicle exceeds a performance threshold.
Systems and methods for training a policy are disclosed. In one example, a system includes a processor and a memory with instructions that cause the processor to train the policy using a training data set with training scenes to generate an identification policy and perform a closed-loop simulation on the identification policy to collect closed-loop metrics. Based on the closed-loop metrics, the instructions cause the processor to construct an error set of the training scenes and construct an upsampled training set by upsampling the error set. After that, the policy is trained using the upsampled training set to generate a final policy.
