A system for controlling connectivity of feature lines within junction networks is disclosed. The system obtains feature line data of each of a plurality of feature lines associated with a geographical region and selects a pair of adjacent feature lines from the plurality of feature lines based on the feature line data, the pair of adjacent feature lines comprising a first feature line and a second feature line. Based on matched segment data associated with a matched segment between the first feature line and the second feature line, the system further determines a set of connectivity attributes associated with the pair of adjacent feature lines and a junction location associated with the first feature line and the second feature. The system further controls a connectivity of the first feature line and the second feature line within the matched segment based on the set of connectivity attributes and the junction location.
A method is inter alia disclosed, performed at least by a mobile device or a part thereof, the method comprising: providing an indication of a trajectory of the mobile device to a remote server; obtaining, from a remote server, an electronic horizon comprising electronic horizon data for one or more ADAS functions of the mobile device, wherein the electronic horizon has been constructed from map data by the server specifically for enabling the mobile device to provide or for supporting the mobile device in providing the one or more ADAS functions, wherein the electronic horizon covers one or more potential paths predicted to be taken by the mobile device based on the indication of the trajectory; and supporting or performing at least one of the one or more ADAS functions at least partially based on the electronic horizon.
Example embodiments describe a computer-implemented method, an apparatus, and a computer program product for generating personalized content for users traversing a route. The method may obtain a route and its content attention profile, which assigns an estimated content attention level to each road link based on user attention levels corresponding to various road link features. A control prompt may be generated based on this profile and a first content data file containing text, audio, or video data. The control prompt may instruct adjusting the detail level of the content. A generative artificial intelligence component may process the first content data file and control prompt to generate a second content data file. The second content data file may be presented on a user device. This method may provide an adaptive entertainment experience for users along their route, potentially enhancing engagement and enjoyment during travel.
A method, system and computer program product for probe provider attribution are disclosed. The method includes receiving from speed probe sensors, for a given region and within a predefined time window, speed probe data from a plurality of corresponding probe providers reporting both consumer vehicle speed probe data and truck speed probe data; combining the speed probe data from the plurality of corresponding probe providers into a single speed probe set; identifying an optimal number of speed clusters for the combined speed probe set; mapping each of the speed probe data from a plurality of corresponding probe providers to one of the optimal number of speed clusters and calculate a distribution of probe provider probes among the speed clusters; and assigning an attribute to each of the plurality of corresponding probe providers based on the distribution of probe provider probes and according to predefined criterion.
A method, system and computer program product for automated detection of map road segments requiring speed limit correction is disclosed. The method includes receiving a request from a quality estimation scheduler; initiating a computer program that automatically: receives a set of map road segments for a given region; receives a speed traffic report for the map road segments during a predefined time interval; identifies a subset of the map road segments that satisfy a predefined traffic speed criteria; further reduces the subset of the map road segments by corroborating with complementary speed limit signs information; compiles a list of map road segments requiring speed limit correction; comparing traffic speeds of the reduced subset with corresponding speed limit signs reported by a map database; and updating map speed limits where required based on the compared traffic speeds.
G01C 21/00 - NavigationInstruments de navigation non prévus dans les groupes
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
6.
METHOD AND ALGORITHM FOR MAP-MATCHING TRIPS TO POIS
A method, system and computer program product for map-matching a probe to a point-of-interest (POI) during a trip by a vehicle in a region are disclosed. The method includes identifying POIs in the region; determining, for probes in the region, a latitude location of the probes, a longitude location of the probes and a data collection time stamp for the probes; determining, for each of the probes in the region, a proximity between the probes and the POIs within a predetermined radius of the probes; determining, for each of the POIs, a POI geographic coverage area; calculating an observed POI probability from the proximity and the POI geographic coverage area; and using a Hidden Markov Model to sequentially process the observed POI probability from a predetermined number of probes of the trip and to predict a most likely POI at which the probes are clustered.
A road sign detection method comprises obtaining an unlabeled image of a road segment and executing a neural network trained to identify road signs within the unlabeled image. The neural network comprises a first model configured to localize an object in the unlabeled image. The neural network may further comprise a second model configured to generate classification data associated with the cropped image, based on content of the cropped image, where the classification data corresponds to one or more appearance-based attributes of the cropped image and also to determine a category of the cropped image, based on the classification data of the cropped image. The neural network may comprise a third model configured to generate road sign label data based on the determined category of the cropped image, where the road sign label data represents the identified road sign. The method further comprises outputting the road sign label data.
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
G01C 21/00 - NavigationInstruments de navigation non prévus dans les groupes
G06T 7/90 - Détermination de caractéristiques de couleur
G06V 10/56 - Extraction de caractéristiques d’images ou de vidéos relative à la couleur
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
8.
SYSTEMS AND METHODS FOR CHARGING OF VEHICLES BASED ON MOBILITY GRAPHS OF USERS
A system for automated charging of electric vehicles obtains a first route between a source and a destination of the vehicle and computes charging data for the vehicle based on the first route. The system determines one or more private charging stations along the first route, each private charging station being associated with a respective host user. Using one or more constraints associated with each private charging station, the charging data, and a host mobility graph of the host user of each private charging station, the system filters the one or more private charging stations. The system further generates navigation recommendation data for the vehicle, based on the first route and the result of the filtration and outputs the navigation recommendation data.
Systems and methods for optimizing routes for vehicles are provided. For example, a method for optimizing routes for vehicles includes receiving electric vehicle charging constraints of one or more vehicles. The method also includes receiving information corresponding to one or more navigation constraints associated with the one or more vehicles. The method also includes determining a route that satisfies the electric vehicle charging constraints of the one or more vehicles and at least one of the one or more navigation constraints associated with the one or more vehicles. The method also includes providing the route to the one or more vehicles.
A system for validation of road closure events on road segments based on trip data is provided. The system obtains first road closure event data associated with a road closure event on a road segment. The system further determines a first polygon to encompass at least one portion of the road segment based on the first road closure event data and map data associated with the road segment. The system further obtains first trip data based on the first road closure event data. The system further extracts second trip data from the first trip data. The system further outputs a first result based on the extracted second trip data and the determined first polygon. The first result is indicative of an occurrence of the road closure event in the at least one portion of the road segment.
An approach is provided for determining driver stopping locations from crowd sourced data. The approach, for instance, involves processing vehicle drive data to determine aggregated vehicle drive geometries. The approach also involves associating and clustering the aggregated vehicle drive geometries into vehicle drive path segments. The approach further involves joining the vehicle drive path segments in a drive path aggregation model using connectivity coherence of each vehicle drive path segment. The approach further involves aggregating stop data representing drives that stop within a specific range of the node, the segment, or a combination thereof of one or more vehicle drive path segments, and providing the stop data as an output.
An approach is provided for determining driver speed profiles from crowd sourced data. The approach, for instance, involves processing vehicle drive data to determine aggregated vehicle drive geometries. The approach also involves associating and clustering the aggregated vehicle drive geometries into vehicle drive path segments. The approach further involves joining the vehicle drive path segments in a drive path aggregation model using connectivity coherence of each vehicle drive path segment. The approach further involves determining speed profile data indicating a consensus driven speed of drives associated with the node, the segment, or a combination thereof of the one or more vehicle drive path segments, and providing the speed profile data as an output.
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 60/00 - Systèmes d’aide à la conduite spécialement adaptés aux véhicules routiers autonomes
13.
METHOD AND SYSTEM FOR GENERATING MAP DATA BASED ON ENHANCED IMAGES
System for enhancing images receives image data associated with a first image associated with a geographical region. The first image has a first type. The system generates edge map data associated with the first image based on the image data, using a first neural network. The system generates a second image on the edge map data, using a second neural network. The second image has a second type different from the first type. The second neural network is trained on a latent representation of each of a plurality of training images associated with the second type. The system generates a third image based on the second image, using a third neural network. The third image has a first resolution higher than a second resolution of the second image. The system generates map data corresponding to the geographical region based on the third image.
G01C 21/00 - NavigationInstruments de navigation non prévus dans les groupes
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
Methods, apparatuses and computer program products for updating map data are disclosed. The method for updating a map comprises obtaining first map data to be updated, obtaining second map data to be used for updating the first map data, determining a matched second map road segment of a road of the second map data matched to a corresponding matched first map road segment of a road of the first map data, registering the matched second map road segment to the matched first map road segment; and updating the first map data by updating the first map road segment.
In an example embodiment, an apparatus obtains map information corresponding to an event location. Based at least in part on the map information corresponding to the event location, the apparatus determines at least one event action to be performed by a vehicle responsive to a vehicle location indicating a location of the vehicle satisfying a proximity criteria corresponding to the event location. The apparatus causes one or more components of the vehicle to perform the at least one event action responsive to determining that the vehicle location satisfies the proximity criteria corresponding to the event location.
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
B60Q 5/00 - Agencement ou adaptation des dispositifs de signalisation acoustique
G05D 1/226 - Liaisons de communication avec les dispositions de commande à distance
16.
SYSTEM AND METHOD FOR GENERATING TRAFFIC DATA BASED ON TRAJECTORY DATA
A system for generating traffic data based on trajectory data is disclosed. The system obtains the trajectory data associated with a trajectory of a vehicle. The system further determines event data associated with each of one or more stop events in the trajectory based on the trajectory data. The system further associates each of the one or more stop events with a reference location based on the corresponding event data. The system further associates each of the one or more stop events with one of a traffic label or a non-traffic label based on the corresponding reference location. The system further generates the traffic data associated with the trajectory based on at least one of the one or more stop events associated with the traffic label and outputs the generated traffic data.
An approach is provided for determining lane transitions from crowd sourced data. The approach, for instance, involves processing vehicle drive data to determine aggregated vehicle drive geometries. The approach also involves processing vehicle drive data to determine aggregated vehicle drive geometries that reduce the vehicle drive data to one path per lane, one path per maneuver, or a combination thereof. The approach further involves associating and clustering the aggregated vehicle drive geometries into vehicle drive path segments. The approach further involves, for each vehicle drive path segments, determining counts of a number of the one or more vehicles that cross a lane marking, that depart or enter the one or more drive path segments, that have an active turn signal, or a combination thereof. The approach further involves computing one or more lane transition types and/or scores for the vehicle drive path segments based on the counts, and providing the lane transition types and/or scores as an output.
B60W 60/00 - Systèmes d’aide à la conduite spécialement adaptés aux véhicules routiers autonomes
G08G 1/065 - Systèmes de commande du trafic pour véhicules routiers par comptage des véhicules dans une section de la route ou dans un parc de stationnement, c.-à-d. en comparant le nombre des arrivants et celui des partants
18.
VEHICLE ROUTING USING CHARGING ENTITY LOCATION INFORMATION
It is inter-alia disclosed a method performed by at least one apparatus, the method comprising obtaining or causing obtaining first location information representative of a first location associated with a first charging entity for charging a vehicle; obtaining or causing obtaining information representative of a remaining range of the vehicle at a first vehicle location, the first vehicle location being associated with the first location; determining or causing determining if at least one second charging entity for charging the vehicle is present, the at least one second charging entity being associated with at least one second location, the at least one second location being reachable by the vehicle from the first vehicle location based on the remaining range of the vehicle at the first vehicle location; and based at least in part on determining or causing determining that the at least one second charging entity is present, routing or causing routing the vehicle based on the first location information.
A system for determination of accessibility of a usage of vehicles in a geographical region is provided. The system obtains a first set of parameters associated with a consumption of a battery by a set of vehicles in a first geographical region. The system further obtains a second set of parameters associated with at least one of the set of vehicles or a set of charging points within the first geographical region. The system further determines a first index based on the obtained first set of parameters. The system further determines a second index based on the obtained second set of parameters. The system further determines a first accessibility score based on the first index and the second index. The first accessibility score is indicative of an accessibility of a usage of the set of vehicles in the first geographical region. The system further outputs the determined first accessibility score.
A system for generating trip data based on trajectory data is disclosed. The system obtains trajectory data associated with a trajectory of a vehicle. The system further determines event data associated with a stop event of the trajectory based on the trajectory data. The system further determines a stop time period associated with the stop event based on the event data. The stop time period includes a first time instance corresponding to a start of the stop event and a second time instance corresponding to an end of the stop event. The system further generates trip data associated with at least one of a first trip or a second trip based on the stop time period. The system further outputs the trip data associated with the trajectory.
09 - Appareils et instruments scientifiques et électriques
39 - Services de transport, emballage et entreposage; organisation de voyages
42 - Services scientifiques, technologiques et industriels, recherche et conception
45 - Services juridiques; services de sécurité; services personnels pour individus
Produits et services
Downloadable computer software for planning, managing and sharing driving-related data and information; downloadable computer software for managing vehicle information and digital vehicle records, including technical data, maintenance records, service histories, documents and multimedia content; downloadable computer software for navigation purposes; downloadable computer software for route planning, and providing driving route recommendations and guided driving assistance; downloadable computer software for providing customized driving recommendations and adaptive driving assistance; downloadable computer software for storing, organizing, presenting and modifying data featuring driving activity, trip history and driving performance; downloadable computer software for sharing, accessing and interacting with user-generated content relating to driving routes, journeys and driving-related data and information; downloadable computer software for social networking and online community interaction among vehicle drivers; computer software allowing to search and determine the location of lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs); downloadable computer software providing public transports timetables and routes, and traffic, parking, navigation, map, travel and weather information; computer software for creating, using, updating, displaying and manipulating digital maps featuring lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs); digital maps featuring lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs); computer software allowing users, developers and businesses to obtain, share, consume and use real-time data and information of lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs) in connection with control, driving or navigation of vehicles; driver assistance computer software for land vehicles, including speed limit alerts, collision and accident alerts, incorporated GPS, traffic and weather information supply, and correct lane formation; downloadable calendaring computer software. Global positioning system and wireless communication system navigation services regarding the location of lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs); transport, traffic, navigation and travel information services; goods, places, events, objects and people positioning services; providing direction and route information for travel purposes; providing customized driving recommendations information, driving route recommendations information and guided or adaptive driving assistance information for travel purposes; places search services, namely, for locating the geographic position of a place and in the field of transportation, traffic, navigation and travel information. Providing temporary use of on-line non-downloadable software for planning, managing and sharing driving-related data and information; providing temporary use of on-line non-downloadable software for managing vehicle information and digital vehicle records, including technical data, maintenance records, service histories, documents and multimedia content; providing temporary use of on-line non-downloadable software for navigation purposes; providing temporary use of on-line non-downloadable software for route planning, and providing driving route recommendations and guided driving assistance; providing temporary use of on-line non-downloadable software for providing customized driving recommendations and adaptive driving assistance; providing temporary use of on-line non-downloadable software for storing, organizing, presenting and modifying data featuring driving activity, trip history and driving performance; providing temporary use of on-line non-downloadable software for sharing, accessing and interacting with user-generated content relating to driving routes, journeys and driving-related data and information; providing temporary use of on-line non-downloadable software for social networking and online community interaction among vehicle drivers; providing temporary use of on-line non-downloadable computer software allowing to search and determine the location of lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs); providing temporary use of on-line non-downloadable computer software for providing public transports timetables and routes, and traffic, parking, navigation, map, travel and weather information; providing temporary use of on-line non-downloadable computer software for creating, using, updating, displaying and manipulating digital maps featuring lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs); providing temporary use of on-line non-downloadable digital maps featuring lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs); providing temporary use of on-line non-downloadable computer software allowing users, developers and businesses to obtain, share, consume and use real-time data and information of lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs) in connection with control, driving or navigation of vehicles; providing temporary use of on-line non-downloadable driver assistance computer software for land vehicles, including speed limit alerts, collision and accident alerts, incorporated GPS, traffic and weather information supply, and correct lane formation; providing temporary use of on-line non-downloadable calendaring computer software. Online social networking services of sharing, accessing and interacting with user-generated content relating to driving routes, journeys and driving-related data and information; online social networking services and online community interaction among vehicle drives, the services being accessible by means of downloadable mobile applications.
22.
SYSTEM AND METHOD FOR IDENTIFICATION OF TRIP TAKEN BY A VEHICLE USING PROBE DATA
The disclosure provides a system and method for identification of a trip taken by a vehicle using probe data. The system receives probe data associated with the vehicle comprising a plurality of probe points. Further, the system calculates a first distance between a first location associated with a first probe point of the plurality of probe points and a second location associated with a second probe point of the plurality of probe points based on the probe data. Furthermore, the system calculates a first travel time between the first location associated with the first probe point and the second location associated with the second probe point based on the probe data and identifies a first trip of the vehicle based on the calculated distance and the calculated first travel time. The system outputs first trip data associated with the first trip of the vehicle based on the probe data.
A method, system and computer program product for determining personalized recommendations of EVCPs based on contextual charging behavior of a user are disclosed. The method includes determining that the user needs to charge the electric vehicle; determining contextual conditions related to personal preferences of the user, a vehicle type of the electric vehicle and/or a location of the electric vehicle; determining features and contextual conditions related to the EVCPs; preparing a list of EVCPs in a predetermined distance from the location of the electric vehicle; ranking, by a trained machine learning model, the list of EVCPs based on the contextual conditions related to personal preferences of the user, the vehicle type of the electric vehicle and/or the location of the electric vehicle; and providing, by a vehicle interface system, a portion of the ranked list of the one or more EVCPs.
The disclosure provides a system and method to identify the point of interest using the trip start and end algorithm. The system receives trip data associated with each of a plurality of data points of a trip segment of a trip. The system determines a deceleration condition associated with a set of consecutive data points. Further, in response to determining deceleration condition, the system determines a geographical region associated with set of consecutive data points. Further, the system determines geographical region to be associated with a point of interest (POI) location. The system determines, using a machine learning (ML) model, a probability value for occurrence of a stop event of trip based on the determined geographical region to correspond to the POI location. Based on the determination of the probability value to be greater than threshold value, the system stores the trip data in association with stop event of trip.
An approach is provided for matching to directed graph representation of lanes of a road topology network of a digital map. The approach, for instance, involves determining a plurality of lane group centerlines respectively representing a plurality of lane groups of a road network in a geographic database. The approach also involves for each lane group centerline of the plurality of lane group centerlines, determining one or more edges having a pair of node identifiers. The approach further involves inserting the one or more edges and the pair of node identifiers into a lane group routing graph, wherein the lane group routing graph is a directed graph. The approach further involves matching an input directed graph to the lane group routing graph, wherein the input directed graph represents a set of trajectories, and providing a map matching result based on the matching.
An approach is provided for assessing impact of traffic spillover. The approach, for instance, involves receiving training data indicating events and attributes associated with the events, where the events indicate traffic spillover from routes to regions local to the routes. The approach further involves using the training data to train a machine learning model to predict impact of traffic congestion of a first route on a first region local to the first route based on first attributes associated with the first route. The approach further involves receiving as input the first attributes associated with the first route. The approach further involves causing the machine learning model to predict the impact based on the first attributes and providing the impact as output.
An apparatus, method, etc. which updates or generates a repository of real mobile apparatus identifiers and generates artificial mobile apparatus identifiers based at least in part on the real mobile apparatus identifiers, wherein the artificial mobile apparatus identifiers are used to watermark map data. This watermarking of map data may be used for various purposes including data security and version control.
G01S 5/02 - Localisation par coordination de plusieurs déterminations de direction ou de ligne de positionLocalisation par coordination de plusieurs déterminations de distance utilisant les ondes radioélectriques
H04W 12/61 - Sécurité dépendant du contexte dépendant du temps
An apparatus configured to detect one or more mobile networking devices, nodes, apparatus, etc. within a given area, wherein if the concentration of the mobile networking devices exceeds a predefined threshold in the area, the area is labeled as a mobile networking device concentration area. Subsequently detected networking devices within the predefined area may then be flagged for closer examination and/or more readily labeled as a mobile networking device.
G01S 5/02 - Localisation par coordination de plusieurs déterminations de direction ou de ligne de positionLocalisation par coordination de plusieurs déterminations de distance utilisant les ondes radioélectriques
G06F 16/29 - Bases de données d’informations géographiques
H04W 4/021 - Services concernant des domaines particuliers, p. ex. services de points d’intérêt, services sur place ou géorepères
H04W 4/029 - Services de gestion ou de suivi basés sur la localisation
29.
METHOD AND SYSTEM FOR GENERATING LANE-LEVEL OD PATTERN
A system and method for generating demand value for lane level is disclosed. The system receives, from data sources, trip data associated with a plurality of trips. Each of the plurality of trips is associated with a lane of a link segment within a geographical region. The system determines location data associated with each of the plurality of trips based on the trip data. The location data comprises an origin location and a destination location. The system generates subsets of the plurality of trips. Each of the subsets is associated with at least one of: an origin location of each of the plurality of trips, or a destination location of each of the plurality of trips. The system generates a demand value for each of the origin locations and each of the destination locations based on the subsets. The system outputs the demand value associated with the lane.
The present disclosure provides a system and method for supplying power to consumers in an electrical power line network. The system provides automated integration and networking logic for electrical assets. Further, the system provides consumer indexing in an electrical power-line network and facilitates an integrated drive and drone sensor data collection system for surveying and mapping service providers and consumers. The system generates virtual ground control points (GCP's) to form models of an electrical power-line network or grid extending from power generation sites to the end consumer sites.
An apparatus for dynamic determination of deviation in vehicle driving behavior and generating recommendations thereof is disclosed. The apparatus retrieves user profile data associated with a user of a vehicle. The user profile data includes historical usage information of the vehicle during one or more historical driving sessions by the user. The apparatus further obtains first contextual information associated with a first driving session by the user. The apparatus further determines a deviation associated with a usage of the vehicle based on the retrieved user profile data and the obtained first contextual information. The apparatus further generates a recommendation associated with a modification in a driving range of the vehicle based on the determined deviation and provides, via a user interface, the generated recommendation.
B60W 50/14 - Moyens d'information du conducteur, pour l'avertir ou provoquer son intervention
B60H 1/00 - Dispositifs de chauffage, de refroidissement ou de ventilation
G07C 5/00 - Enregistrement ou indication du fonctionnement de véhicules
G07C 5/04 - Enregistrement ou indication du temps de circulation, de fonctionnement, d'arrêt ou d'attente uniquement utilisant des moyens de comptage ou compteurs à horloge
32.
APPARATUS AND METHOD TO RECOMMEND CHARGING POINTS BASED ON PROBE DATA
An apparatus to recommend charging points based on probe data is provided. The apparatus retrieves a first location associated with a first vehicle of a set of vehicles. The apparatus further determines a set of charging points within a first distance of the first vehicle based on the retrieved first location. The apparatus further retrieves, from one or more sources, a set of features comprising at least one of: a first feature, a second feature, and a third feature. At least one feature of the set of features is obtained from probe data associated with the set of vehicles. Further, the apparatus generates one or more recommendations associated with one or more charging points of the set of charging points based on the retrieved set of features. The apparatus further provides, via a user interface, the generated one or more recommendations as an option for selection by a user.
A computer-implemented method for processing vehicular sensor data comprises collecting one or more sensor datapoints corresponding to one or more vehicle functions. Each sensor datapoint of the one or more sensor datapoints comprises an autonomous functionality status identifier of the respective vehicle function of the one or more vehicle functions. The method further comprises filtering each sensor data point into one of autonomous control data or manual control data to generate filtered data, based on the corresponding autonomous functionality status identifier of the respective sensor data point. Further, the method comprises generating at least one of a first dataset or a second dataset, based on the filtered data. The first dataset corresponds to the autonomous control data and the second dataset corresponds to the manual control data.
B60W 50/04 - 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 surveiller le fonctionnement du système d'aide à la conduite
An approach is provided for lane-level direction-of-travel detection from overhead imagery. The approach, for instance, involves processing overhead imagery data of a road network to determine a plurality of features indicative of a direction of travel of at least one road lane of the road network. Each feature of the plurality of features indicates a candidate direction of travel. The approach also involves determining the direction of travel of the at least one road lane based on a weighted voting mechanism applied based on the candidate direction of travel of each feature. The weighted voting mechanism weighs the candidate direction of travel of each feature based on a feature type of each feature. The approach further involves associating the determined direction of travel as an attribute of the at least one road lane in a geographic database.
G01C 21/00 - NavigationInstruments de navigation non prévus dans les groupes
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 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
35.
SYSTEM AND METHOD FOR DETERMINATION OF QUALITY LABEL FOR PROBE DATA
A system for determination of quality label for probe data is disclosed. The system obtains probe data associated with a road segment. The probe data includes a set of probe data records. The system further applies a machine learning (ML) model on the set of probe data records to determine an anomaly score for each probe data record of the set of probe data records. The ML model is trained to detect a set of anomalies associated with the probe data and further assign an anomaly score to each probe data record of the set of probe data records based on the detected set of anomalies. The system further determines a quality label for the probe data based on the anomaly score.
A system for updating a map database obtains observation data associated with each observation of a plurality of observations. The plurality of observations is associated with an object. The system further obtains ground truth data associated with the object and classifies each observation of the plurality of observations as one observation feature of a plurality of observation features based on the obtained observation data and the obtained ground truth data. Furthermore, the system determines a generalized probability distribution for the plurality of observations based on the classification of each observation of the plurality of observations and determines a confidence score based on the generalized probability distribution. Furthermore, the system determines updated status data for the object based on the ground truth data and the confidence score and updates the map database based on the updated status data.
An approach is provided for map matching a vehicle path network to a road topology network of a digital map. The approach, for instance, involves aggregating vehicle trajectory data into a vehicle path network that is a directed graph comprising a plurality of nodes. The approach also involves segmenting the vehicle path network into a plurality of linear features. Each linear feature of the plurality of linear features connects two nodes of the plurality of nodes in the vehicle path network. The approach further involves using a path-based map matcher to separately match each linear feature by incorporating context of the vehicle path network to a map topology of a digital map to generate map matching results. The approach further involves aggregating the map matching results of each linear feature into an overall map matching result for the directed graph, and providing the overall map matching result as an output.
Embodiments of the present disclosure disclose a system for generating driving data for navigation assistance during vehicle transition. The system obtains historical driving data associated with a first vehicle and determines second LOS data associated with a second LOS of a second vehicle. The historical driving data comprises first line of sight (LOS) data. The second LOS comprises a plurality of objects. The system determines an overlapping area based on the first LOS data and the second LOS data. The overlapping area comprises one or more objects from the plurality of objects. The system generates driving data for the second vehicle based on the one or more objects in the overlapping area.
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
G06V 20/56 - Contexte ou environnement de l’image à l’extérieur d’un véhicule à partir de capteurs embarqués
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
39.
SCALABLE GRID BASED IONOSPHERIC CORRECTION SYSTEM AND METHOD
A method, apparatus and computer program product are configured to adaptively adjust ionospheric delay correction grids and data transmitted to a navigation device based on identified ionospheric abnormalities.
G01S 19/07 - Éléments coopérantsInteraction ou communication entre les différents éléments coopérants ou entre les éléments coopérants et les récepteurs fournissant des données pour corriger les données de positionnement mesurées, p. ex. DGPS [GPS différentiel] ou corrections ionosphériques
40.
METHOD TO DETERMINE CONTEXTUAL ROAD CLEARANCE FOR ELECTRICAL VEHICLES
A system to determine a stranded electric vehicle resilience index of an area for an electric vehicle (EV) is disclosed. The system may use an API to determine areas in a region with minimal EV charging capabilities; generate a first trained machine learning model to predict a first probability for a given EV to be stranded in the areas based on a training feature dataset and the areas with minimal EV charging capabilities; label the areas as critical areas based on the first probability; generate a second trained machine learning model based on the labelled critical areas; and predict, using the second trained machine learning model and current features of a link to be traveled by the EV as derived from a map and one or more sensors along the link, a second probability for the EV to be stranded on the link.
A system, method, apparatus, etc., for electric vehicle supply equipment management. More specifically, at least an apparatus which may detect and/or predict the location of one of more dynamic power sharing electric vehicle supply equipment(s) such as a charge point, charge plug, etc. This information may be deduced from charge point data operators or generated by independent analysis.
A system, method, apparatus, etc., for electric vehicle supply equipment management wherein an indication of at least a first location of an electric vehicle and its charging needs are obtained along with charge point data for vehicle chargers proximate to the location of the electric vehicle. Based on this and other data, a dynamic power sharing availability indicator may be determined with this indicator used in map databases, automated vehicle routing, etc.
A system to system to contextualize proximity sensing around vehicles to reduce alarm fatigue for a driver of a vehicle is disclosed. The system may provide different degrees of warning for potential impacts with objects, most specifically centered around if an impact is in fact possible and has some level of severity. If no impact is possible or likely, then a general notice or alert of proximity may be acceptable, but can be handled in a more gentle or unobtrusive way so as not to cause confusion for a driver.
Systems and methods for vehicle routing may be based on wireless network performance data. A vehicle route includes one or more path segments included in the route based on the wireless performance data. The vehicle route may be updated based on updated wireless performance data. Driving assistance features of a vehicle may be enabled by the wireless performance data, and different driving assistance features may be enabled or disabled on the vehicle route according to changes in wireless performance data. As the vehicle traverses the route, the driving assistance features may be enabled or disabled based on the wireless performance data for the path segment. The vehicle route may be updated to continue to enable a set of the driving assistance features.
A system to determine a context and likelihood of a vehicle hitting a guardrail is disclosed. The system is configured to detect, by sensors, where a vehicle hits a guardrail in one or more guardrail collision events; determine metadata elements associated with the one or more guardrail collision events; mapping the one or more guardrail collision events to a region into a vector format; determine, using a first trained machine learning model, a first likelihood if a given vehicle will hit a guardrail in the region on a given link at a given time based on the mapped guardrail collision events and a training feature dataset; and determine, using a second trained machine learning model, a second likelihood that the given vehicle will go over the guardrail into an unsafe area based on the first likelihood and guardrail collision features.
A method, apparatus and computer program product are provided for generating search engine input queries using point-of-interest information and permutations thereof to assess the quality of search results produced by and to improve the search engine. Methods may include: identifying a reference point-of-interest from a reference data database; extracting at least one point-of-interest attribute from the reference point-of-interest; identifying a geographic location of the reference point-of-interest; calculating a test query search center based on the geographic location of the reference point-of-interest; generating a test query based on the at least one point-of-interest attribute from the reference point-of-interest and the test query search center; querying a search engine using the test query; receiving one or more responses to the test query; analyzing the one or more responses to calculate response quality metrics; and modifying the search engine based at least in part on the metrics.
A system for determining critical edges is provided. The system obtains an OD matrix of a predefined time period indicating traffic volume values for OD pairs in a geographical area, identifies OD pairs of the OD pairs having traffic volume values greater than a traffic threshold, and generates a network graph for the predefined time period based on the identified OD pairs. The network graph comprises nodes associated with a plurality of locations within the geographical area, and edges associated with weight values indicative of a trip volume. The system determines critical edges for the predefined time period based on the weight values of the edges, and stores edge data associated with the critical edges for the predefined time period in a map database.
Systems and methods are described for the vehicle emission measurement. An example method may include receiving a plurality of images from a first vehicle traveling on a section of roadway, determining a quantity of surrounding vehicles from the plurality of images, determining a cropped image of at least one of the surrounding vehicles from the plurality of images, identifying a model of the at least one of the surrounding vehicles from the cropped image, and calculating an emission measurement factor for the section of roadway based on at least the quantity of surrounding vehicles for the at least one of the surrounding vehicles.
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
G01C 21/34 - Recherche d'itinéraireGuidage en matière d'itinéraire
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 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
Embodiments of the present disclosure disclose a system for determining an optimal route. The system obtains an origin-destination (OD) matrix comprising historical traffic values for predefined time slots for each route and generates network graphs based on the OD matrix. Each of the network graphs corresponds to one of the predefined time slots, and each of the network graphs comprise nodes, and edges having corresponding weight values. The system determines desired routes from the one or more routes based on the weight values, determines travel frequency data for each of the desired routes at least in the predefined time slots based on the network graphs; and determines a modal route based on the desired routes and the travel frequency data. Each of the desired routes is associated with one of the network graphs.
A system for characterizing congestion queue status on road links is disclosed. The system obtains the first probe data associated with a first plurality of probe points from a first vehicle of a set of vehicles associated with a road segment. The system further generates a plurality of motion components for each of the first plurality of probe points based on the obtained first data. The system further applies a machine learning (ML) model on the generated plurality of motion components for the first plurality of probe points. The system further generates a set of clusters based on the application of the ML model on the generated plurality of motion components. The system further outputs the generated set of clusters.
An apparatus, a method, and a non-transitory computer-readable storage medium for providing strategies for charging vehicles is provided. For example, the apparatus obtains, using a map database, traffic congestion information on a road segment, predicts a traffic congestion status on the road segment based on the traffic congestion information, generates an objective function based on the traffic congestion status, computes a solution of the objective function using an integer programming or a linear programming, generates a recommendation based on the solution, and outputs the recommendation.
Method, apparatuses and computer program products for training machine learning models for logistics robots and routing the robots are disclosed. A method of training an ML model involves providing a route to a logistics robot, obtaining route issue indications from the robot when it fails to traverse the route as expected, and associating map objects with the issue locations. The trained model can then be used to determine the likelihood of route issues for a specific logistics robot type based on the presence of certain map objects along the route. The disclosure further involves calculating route penalty value(s) based on the likelihood and updating the route accordingly, including selection of a logistics robot type for the route.
G06Q 10/047 - Optimisation des itinéraires ou des chemins, p. ex. problème du voyageur de commerce
G01C 21/20 - Instruments pour effectuer des calculs de navigation
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
G05D 105/28 - Applications spécifiques des véhicules commandés pour le transport de marchandises
53.
APPARATUS AND METHOD FOR PREDICTING AVAILABILITY DATA OF ELECTRIC VEHICLE CHARGING POINTS
An apparatus and method for predicting availability data of electric vehicle charging points (EVCPs) are provided. The apparatus receives EVCP data associated with each of a plurality of EVCPs. The apparatus determines clustering features for each of the plurality of EVCPs based on the EVCP data. The clustering features comprise a duration parameter, a predefined charging status parameter, a charging gap parameter, or a combination thereof. The apparatus generates clusters using a first model based on the clustering features. Each of the clusters comprises at least one of the plurality of EVCPs. The apparatus trains a second model to predict availability data associated with each EVCP within each of the clusters based on a data point associated with one or more EVCPs within said cluster.
The disclosure provides an unmanned aerial vehicle, a method, and an apparatus for real-time asset mapping. The unmanned aerial vehicle is configured to, for example, control an image sensor to capture an image of a geographical region. Further, the unmanned aerial vehicle is configured to detect a first object of a set of objects in the captured image based on a segmentation of the captured image into one or more segments. The unmanned aerial vehicle is further configured to generate an association between the detected first object and the captured image. Further, the unmanned aerial vehicle is configured to transmit the generated association to a map database.
G01C 21/00 - NavigationInstruments de navigation non prévus dans les groupes
B64U 20/80 - Disposition de l’électronique à bord, p. ex. systèmes ou câblage d’avionique
B64U 101/30 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques à l’imagerie, à la photographie ou à la vidéographie
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 10/774 - 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 20/17 - Scènes terrestres transmises par des avions ou des drones
55.
METHOD AND SYSTEM FOR DETECTION OF ROAD OBJECTS USING 2D IMAGE SIGN SIGHTINGS
The disclosure provides a method, a system, and a computer program product for object detection using 2D sighting data of the object obtained using a 2D sensor. The method comprises obtaining 2D sighting data of the object using the 2D sensor. Further, the method comprises determining position candidate data for the object based on (i) 2D centroid data associated with the 2D sighting data of the object and (ii) 3D centroid data determined using projection data of one or more skew lines associated with the 2D centroid data. The position candidate data is then filtered based on (i) offset data associated with vector offset between the 2D centroid data and the 3D centroid data, (ii) postprocessing data, and (iii) scaling factor data associated with the position candidate data. Further, the detection data for the object is outputted based on the filtered position candidate data.
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 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
56.
APPARATUS AND METHOD FOR DETERMINATION OF LOW VISIBILITY IN AN ENVIRONMENT AROUND A VEHICLE
An apparatus for determining low visibility of an environment around a vehicle is disclosed. The apparatus obtains location information indicating a location of the vehicle. The apparatus further detects, by using a map database, a road segment satisfying a road attribute requirement proximate to the location based on the location information. The apparatus further obtains, from the map database, at least one attribute associated with the road segment. The apparatus further determines a position of the vehicle with respect to the road segment based on the at least one road attribute. The apparatus further acquires at least one image via at least one image capture sensor equipped by the vehicle based on the position. The apparatus further determines visibility information indicative of visibility of the environment of the vehicle based on the at least one image. The apparatus further outputs the visibility information.
G06V 10/75 - Organisation de procédés de l’appariement, p. ex. comparaisons simultanées ou séquentielles des caractéristiques d’images ou de vidéosApproches-approximative-fine, p. ex. approches multi-échellesAppariement de motifs d’image ou de vidéoMesures de proximité dans les espaces de caractéristiques utilisant l’analyse de contexteSélection des dictionnaires
G06V 20/56 - Contexte ou environnement de l’image à l’extérieur d’un véhicule à partir de capteurs embarqués
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
57.
METHOD, APPARATUS, AND SYSTEM OF PROVIDING ELECTRICAL VEHICLE CHARGING STATION AVAILABILITY
An approach is provided for electric vehicle charging station availability. The approach involves, for example, receiving transmissions from one or more vehicles. Each transmission comprises a list of charging stations, estimated times of arrival for the one or more vehicles to reach each charging station, and values computed to indicate a preference of the one or more vehicles to reach each charging station. The approach also involves processing the list of the one or more charging stations, estimated times of arrival, and preference values to determine respective probabilities that each charging station will be available at the estimated times of arrival. The approach further involves determining at least one recommended charging station from among the charging stations based on the respective probabilities.
Systems and methods for electric vehicle organization are provided. For example, a method for electric vehicle organization includes receiving charging capability information of one or more vehicles. The method also includes receiving information corresponding to charging profiles of the one or more vehicles. The method also includes determining charge point data in a given area associated with the one or more vehicles. The method also includes determining map object data and point of interest data in the given area. The method also includes generating a recommendation for an optimal charge position within the given area for a vehicle of the one or more vehicles based on a charging capability information of the vehicle, a charge profile of the vehicle, the determined charge point data in the given area, and the determined map object data and the point of interest data.
B60L 53/36 - Moyens pour l’ajustement automatique ou assisté de la position relative des dispositifs de charge et des véhicules par le positionnement du véhicule
09 - Appareils et instruments scientifiques et électriques
39 - Services de transport, emballage et entreposage; organisation de voyages
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Computer software for creating, using, updating, displaying
and manipulating digital maps featuring lanes, roads,
streets, cities, towns, goods, objects, people, events, and
buildings, places and points of interests (POIs); digital
maps featuring lanes, roads, streets, cities, towns, goods,
objects, people, events, and buildings, places and points of
interests (POIs); application programming interfaces (APIs)
for creating, using, updating, displaying and manipulating
databases and digital maps featuring lanes, roads, streets,
cities, towns, goods, objects, people, events, and
buildings, places and points of interests (POIs); computer
software development software used to create and use digital
maps and databases; computer software allowing to search and
determine the location of lanes, roads, streets, cities,
towns, goods, objects, people, events, buildings, places and
points of interests (POIs); artificial intelligence computer
software for navigation purposes, route planning, and
searching for lanes, roads, streets, cities, towns, goods,
objects, people, events, and buildings, places and points of
interests (POIs); artificial intelligence computer software
featuring digital maps, and real-time transportation,
traffic, navigation and travel data; driver assistance
computer software for land vehicles, aircraft and
watercraft, including speed limit alerts, collision and
accident alerts, automated lighting, adaptive cruise
control, automated braking, incorporated GPS, traffic and
weather information supply, correct lane formation and blind
spots revelation; computer databases containing digital
maps, historical and real-time traffic, weather, travel,
transportation and navigation data, and information on
lanes, roads, streets, cities, towns, goods, objects,
people, events, and buildings, places and points of
interests (POIs); computer software enabling advanced
driver-assistance systems (ADAS), automated driving and
hands-free driving of land vehicles; none of the
aforementioned goods are used for the purposes of security,
law enforcement, defence and military. Global positioning system and wireless communication system
navigation services regarding the location of lanes, roads,
streets, cities, towns, goods, objects, people, events, and
buildings, places and points of interests (POIs); transport,
traffic and travel information services; Global Positioning
System and wireless communication system navigation services
for the positioning of goods, places, events, objects and
people; providing direction and route information for travel
purposes; transportation, traffic, navigation and travel
information services consisting of the locating of the
geographic position of a place [so-called places search
services]. Designing and developing computer software for creating,
using, updating, displaying and manipulating digital maps
featuring lanes, roads, streets, cities, towns, goods,
objects, people, events, and buildings, places and points of
interests (POIs); providing on-line non-downloadable
computer software for creating, using, updating, displaying
and manipulating digital maps featuring lanes, roads,
streets, cities, towns, goods, objects, people, events, and
buildings, places and points of interests (POIs); providing
temporary use of on-line non-downloadable digital maps
featuring lanes, roads, streets, cities, towns, goods,
objects, people, events, and buildings, places and points of
interests (POIs); providing temporary use of on-line
non-downloadable software for use as an application
programming interface (API) for creating, using, updating,
displaying and manipulating databases and digital maps
featuring lanes, roads, streets, cities, towns, goods,
objects, people, events, and buildings, places and points of
interests (POIs); providing temporary use of on-line
non-downloadable software for use as development software
used to create and use digital maps and databases; software
as a service (SaaS) for creating, using, updating,
displaying and manipulating digital maps featuring lanes,
roads, streets, cities, towns, goods, objects, people,
events, and buildings, places and points of interests
(POIs); providing on-line non-downloadable computer software
allowing to search and determine the location of lanes,
roads, streets, cities, towns, goods, objects, people,
events, buildings, places and points of interests (POIs);
providing on-line non-downloadable artificial intelligence
computer software for navigation purposes, route planning,
and searching for lanes, roads, streets, cities, towns,
goods, objects, people, events, and buildings, places and
points of interests (POIs); providing on-line
non-downloadable artificial intelligence computer software
featuring digital maps, and real-time transportation,
traffic, navigation and travel data; providing on-line
non-downloadable driver assistance computer software for
land vehicles, aircraft and watercraft, including speed
limit alerts, collision and accident alerts, automated
lighting, adaptive cruise control, automated braking,
incorporated GPS, traffic and weather information supply,
correct lane formation and blind spots revelation; providing
temporary use of on-line non-downloadable databases
containing digital maps, historical and real-time traffic,
weather, travel, transportation and navigation data, and
information on lanes, roads, streets, cities, towns, goods,
objects, people, events, and buildings, places and points of
interests (POIs); providing on-line non-downloadable
computer software enabling advanced driver-assistance
systems (ADAS), automated driving and hands-free driving of
land vehicles; none of the aforementioned services are used
for the purposes of security, law enforcement, defence and
military.
60.
LOCATION BASED PAYMENT SYSTEM FOR ELECTRIC VEHICLE CHARGING
A system, method, etc. for method for providing an electric vehicle charging payment comprising obtaining an indication of at least a first location of an electric vehicle, obtaining payment data for one or more electric vehicle charge points proximate to the first location of the end user device, determining a charge point interaction indicator based, at least in part, on the obtained indication of first location and payment data for one or more electric vehicle charge points proximate to the first location, and transmitting at least one charge session payment data to the charge point.
An approach is provided for mock map data for map design validation. For example, the approach involves calculating one or more combinations of one or more map feature attributes, one or more map feature attribute values, or a combination thereof. The approach also involves creating one or more geometric features respectively for the one or more combinations. The approach further involves determining an arrangement of the one or more geometric features within a designated geographic area. The approach further involves generating mock map data based on the arrangement and providing the mock map data to a map client. The map client, for instance, renders the mock map data in a map image based on a map style taxonomy.
The disclosure provides a system, a method, and a computer program product for determining coverage of a vehicle. The system is configured to, for example, acquire sensor data and vehicle data from a user equipment. The sensor data is associated with a region including a plurality of roads. Further, the system is configured to determine a function class of each of the plurality of roads based on the sensor data. Further, the system is configured to determine a type of a vehicle associated with the user equipment, based on the vehicle data. The system is configured to further determine coverage data of the vehicle for each of the plurality of roads based on the function class of a respective road of the plurality of roads and the type of the vehicle. Further, a first notification associated with the coverage of the vehicle, is generated as output.
A method, apparatus, and computer program product are provided for establishing and applying a second level of anonymization of trajectories to improve privacy. Methods may include: receiving anonymized mobility data for a geographic region subdivided into a plurality of map tiles, where the mobility data includes a plurality of probe data points anonymized with a first anonymization level, where sequences of probe data points define trajectories; determining, based on the anonymized mobility data, one or more map tiles of the plurality of map tiles where anonymization of trajectories using the first anonymization level fails to satisfy a predefined anonymity parameter value; removing a subset of the anonymized mobility data corresponding to the one or more map tiles; and publishing the anonymized mobility data without the subset of the mobility data corresponding to the one or more map tiles for use with one or more location-based services.
An apparatus, method and computer program product are provided for determining a location for deploying an electric vehicle charging unit (EVCU). In one example, an apparatus divides a zone into a plurality of subregions and causes a machine learning model to output a probability of which an EVCU is needed at each of the plurality of subregion based on one or more attributes associated with the subregion. The apparatus generates one or more clusters within the zone, where each of the one or more clusters include one or more of the plurality of subregions. The apparatus calculates a value for each of the one or more clusters based on the probability associated with each subregion within said cluster. The apparatus selects one of the one or more clusters based on the value and assigns a location within the one of the one or more clusters for deploying the EVCU.
An approach is provided for the prediction of the usage of smoking products in vehicles using machine learning. The approach, for example, involves obtaining, from at least one sensor, first smoking event data associated with a first smoking event on a first road link. The first smoking event is associated with the usage of at least one smoking product by a first user on the first road link. The approach further involves retrieving a first set of features including road link properties of the first road link and context information associated with the first smoking event on the first road link. The approach further involves training a machine learning (ML) model using the retrieved first set of features to determine an association between the retrieved first set of features and the first smoking event and storing the trained ML model.
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
66.
ERROR PREDICTION IN LOCATION SENSOR DATA USING MACHINE LEARNING MODEL
A method of predicting errors in location sensor data is disclosed. The method may include retrieving, from a map database, lane geometry information associated with a first lane within a first road link in a geographic region and obtaining the first location sensor data for a first set of reference points. The method may further include associating each reference point with a respective portion of the lane geometry information and calculating a first error associated with the obtained first location sensor data based on the respective portion of lane geometry information. The method may further include obtaining a first set of features associated with each of the first set of reference points and training a machine learning (ML) model using the calculated first error and the obtained first set of features.
An approach is provided for large language model (LLM) map feedback reporting. The approach involves, for example, processing an input specifying a map error/feedback using an LLM to classify a map error type. The approach also comprises determining a map error template based on the map error type that specifies structured data fields for the map error type. The approach further involves using the template to construct prompts for the LLM to generate questions to collect data items for populating the data fields, and providing the prompts to the LLM to generate the questions and collect the data items from the user. The approach further involves using template to generate additional prompts to generate a map error report of the data items in a structured data format, and providing the additional prompts to the LLM to generate the map error report for transmission to a map feedback system.
An apparatus configured to, with a processor, cause the apparatus to at least collect real-time driving data for at least one vehicle from a mobile device associated with a user of the vehicle or a navigation unit of the vehicle, wherein the collected real-time driving data includes at least parking location information for the vehicle; retrieve historical driving data associated with the at least one vehicle from one or more databases; retrieve point of interest (POI) data from one or more databases; generate a vehicle type prediction associated with the vehicle based on the collected real-time driving data, the retrieved historical driving data, and the POI data, wherein the generated vehicle type prediction is stored in the one or more databases; and generate an electrical vehicle charge point location prediction based on at least the vehicle type prediction and parking location information for at least one vehicle.
An approach is provided for detecting objects and associated pose from imagery data. The approach, for instance, involves processing an image using a feature representation network to generate a set of points representing the object detected in the image. Each point, for instance, has an attribute indicating a geometric part of the object. The approach also involves using the feature representation network to construct a bounding box around the set of points. The approach further involves determining a pose of the object based on the bounding box and the attribute indicating the geometric part of the object for each point. The approach further involves providing the object, the pose, or a combination thereof as an output.
G06V 10/40 - Extraction de caractéristiques d’images ou de vidéos
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 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
An apparatus and method relate to analyzing metrics relating to EV charging points and facilitating selection of an EV charge point based on metrics associated with the EV charge points. Methods may include: determining locations of one or more electric vehicle charging stations; determining a total power available at the one or more electric vehicle charging stations; determining, for the one or more electric vehicle charging stations, if dynamic load balancing is used; determining occupancy of charge points at each of the one or more electric vehicle charging stations; calculating an available power at a charge point of the one or more electric vehicle charging stations based on the total power available and the occupancy of charge points for the one or more electric vehicle charging stations; and calculating an estimated time to charge a vehicle at the one or more electric vehicle charging stations based on the available power.
09 - Appareils et instruments scientifiques et électriques
39 - Services de transport, emballage et entreposage; organisation de voyages
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Computer software for creating, using, updating, displaying and manipulating digital maps featuring lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs); digital maps featuring lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs); application programming interfaces (APIs) for creating, using, updating, displaying and manipulating databases and digital maps featuring lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs); computer software development software used to create and use digital maps and databases; computer software allowing to search and determine the location of lanes, roads, streets, cities, towns, goods, objects, people, events, buildings, places and points of interests (POIs); artificial intelligence computer software for navigation purposes, route planning, and searching for lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs); artificial intelligence computer software featuring digital maps, and real-time transportation, traffic, navigation and travel data; driver assistance computer software for land vehicles, aircraft and watercraft, including speed limit alerts, collision and accident alerts, automated lighting, adaptive cruise control, automated braking, incorporated GPS, traffic and weather information supply, correct lane formation and blind spots revelation; computer databases containing digital maps, historical and real-time traffic, weather, travel, transportation and navigation data, and information on lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs); computer software enabling advanced driver-assistance systems (ADAS), automated driving and hands-free driving of land vehicles; none of the aforementioned goods are used for the purposes of security, law enforcement, defence and military. Global positioning system and wireless communication system navigation services regarding the location of lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs); transport, traffic and travel information services; Global Positioning System and wireless communication system navigation services for the positioning of goods, places, events, objects and people; providing direction and route information for travel purposes; transportation, traffic, navigation and travel information services consisting of the locating of the geographic position of a place [so-called places search services]. Designing and developing computer software for creating, using, updating, displaying and manipulating digital maps featuring lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs); providing on-line non-downloadable computer software for creating, using, updating, displaying and manipulating digital maps featuring lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs); providing temporary use of on-line non-downloadable digital maps featuring lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs); providing temporary use of on-line non-downloadable software for use as an application programming interface (API) for creating, using, updating, displaying and manipulating databases and digital maps featuring lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs); providing temporary use of on-line non-downloadable software for use as development software used to create and use digital maps and databases; software as a service (SaaS) for creating, using, updating, displaying and manipulating digital maps featuring lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs); providing on-line non-downloadable computer software allowing to search and determine the location of lanes, roads, streets, cities, towns, goods, objects, people, events, buildings, places and points of interests (POIs); providing on-line non-downloadable artificial intelligence computer software for navigation purposes, route planning, and searching for lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs); providing on-line non-downloadable artificial intelligence computer software featuring digital maps, and real-time transportation, traffic, navigation and travel data; providing on-line non-downloadable driver assistance computer software for land vehicles, aircraft and watercraft, including speed limit alerts, collision and accident alerts, automated lighting, adaptive cruise control, automated braking, incorporated GPS, traffic and weather information supply, correct lane formation and blind spots revelation; providing temporary use of on-line non-downloadable databases containing digital maps, historical and real-time traffic, weather, travel, transportation and navigation data, and information on lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs); providing on-line non-downloadable computer software enabling advanced driver-assistance systems (ADAS), automated driving and hands-free driving of land vehicles; none of the aforementioned services are used for the purposes of security, law enforcement, defence and military.
72.
METHOD AND APPARATUS FOR PROVIDING A REAL-TIME ESTIMATED TIME OF ARRIVAL SCORECARD BASED ON REAL-TIME CLASSIFICATION OF LOCATION TRACE DATA
An approach is provided for contextualized determination of estimated times of arrival (ETAs) for trips. The approach involves, for example, computing an original ETA for a vehicle on a route that is subject to required events. The original ETA is computed based on pre-trip predicted events determined based on an initial set of assumptions and the required events. The approach also involves monitoring real-time location trace data of the vehicle during a monitoring period to determine actual events of the vehicle and/or driver. The approach further involves generating a real-time ETA scorecard comparing the actual events to the required events, pre-trip predicted events, and/or prior events determined for previous monitoring periods. The approach further involves determining predicted events for subsequent monitoring periods based on the real-time ETA scorecard, and determining an updated ETA based on the predicted events.
An approach is provided for automated purpose limitation and compatibility verification on a data platform. The approach, for example, involves generating metadata that indicates a purpose that has been allowed for processing a dataset. The approach also involves storing the metadata in a metadata catalog to associate the purpose with the dataset. The approach further involves querying the metadata catalog to perform a verification of a compatibility of the purpose with a requested purpose for a new processing activity of the dataset, to perform a limitation of the new processing activity, or a combination thereof.
The disclosure provides a method, a system, and a computer program product for image processing using segmentation. The system is configured to, for example, obtain image data associated with one or more sensors associated with a user device. Further the system is configured to determine count data associated with one or more cores of a processor of the user device. The image data is segmented into one or more segments based on the count data. Each of the one or more segments of the image data are processed with a corresponding core of the one or more cores of the processor of the user device. Each of the processed one or more segments of the image data are then combined to form combined processed image data.
An apparatus, method and computer program product are provided to update a map layer including one or more light-based objects and use the map layer for localization. For example, the apparatus is configured to receive image data including a plurality of images of a light-based object generated by a source, use the image data to create a representation of the light-based object, and update a map layer to include the representation as a landmark. The apparatus is further configured to receive an image captured by an image capturing device and including the light-based object and perform localization for the image capturing device by using the image and the map layer.
G06T 7/70 - Détermination de la position ou de l'orientation des objets ou des caméras
G06V 10/60 - Extraction de caractéristiques d’images ou de vidéos relative aux propriétés luminescentes, p. ex. utilisant un modèle de réflectance ou d’éclairage
76.
METHOD TO DETECT OPPORTUNISTIC MIXED MODE TRANSPORTATION VIRTUAL HUBS BASED ON MOBILITY PATTERNS
A system, method and computer program product to detect opportunistic mixed mode transportation virtual hubs are disclosed. The system may allow commuters to benefit from more relevant and contextual recommendations for “park and ride” commutes by algorithmically detecting opportunistic mixed mode transportation virtual hubs based on traffic conditions, parking capacity measures and mobility patterns of commuters.
An apparatus and a method for generating sub-trajectories for a trajectory are disclosed. The method includes retrieving trajectory data comprising a plurality of data points defining a trajectory and iteratively executing a set of operations until a termination condition is met. The set of operations include selecting an observation point associated with the plurality of data points and calculating a set of visible points comprising one or more data points from the plurality of data points associated with the observation point based on a predefined visibility context criterion. The method further includes identifying a changing point from the plurality of data points based on the iterative execution of the set of operations, and generating a sub-trajectory for the trajectory such that the changing point indicates a starting point of the sub-trajectory.
H04W 12/00 - Dispositions de sécuritéAuthentificationProtection de la confidentialité ou de l'anonymat
B60R 25/32 - Détection relative au vol ou autres événements relatifs aux systèmes antivol de paramètres dynamiques du véhicule, p. ex. de la vitesse ou de l’accélération
H04W 12/02 - Protection de la confidentialité ou de l'anonymat, p. ex. protection des informations personnellement identifiables [PII]
78.
METHOD, APPARATUS, AND SYSTEM FOR AUTOMATED DETECTION AND CHARACTERIZATION OF A ROAD INTERSECTION AND ADJUSTMENT
An approach is provided for automated detection and/or characterization of road intersections. The approach, for instance, includes determining a set of observables associated with a road intersection. The set of observables comprises a plurality of point observations of road boundaries of the road intersection, and the plurality of point observations are collected using sensors of vehicles traveling in the road intersection. The approach also involves processing the plurality of point observations to generate a triangular mesh to represent a surface of the road intersection. The triangular mesh comprises a plurality of triangles connecting the plurality of point observations as respective vertices of a plurality of triangles. The approach further involves selecting one or more branch triangles of the plurality of triangles. The vertices of the branch triangles reference three different road boundaries of the road intersection. The approach further involves automatically detecting the intersection based on the branch triangles.
A system for generating navigation instructions for delivery of a cargo is provided. The system is configured to obtain geographic area information relating to a geographic area, determine cargo information relating to the cargo, determine one or more aerial routes for a delivery of the cargo based on the geographic area information and the cargo information, estimate a risk value for navigation of an aerial vehicle across each of the one or more aerial routes, identify an aerial route from the one or more aerial routes having lowest estimated risk value based on the estimated risk values for the one or more aerial routes, and generate the navigation instructions for navigation of the aerial vehicle along the identified aerial route for delivery of the cargo.
An approach is provided for probe vehicle analysis across travel zones. The approach involves, for example, determining probe data, sensor data, or a combination thereof collected from a plurality of sensors of a plurality of probe vehicles traveling in a geographic area of interest. The approach also involves for each probe vehicle of the plurality of probe vehicles, determining a vehicle attribute and a vehicle path for each probe vehicle from the probe data, the sensor data, or a combination thereof, and determining a start travel zone and an end travel zone of the vehicle path for each probe vehicle. The approach further involves processing the vehicle path for each probe vehicle to determine trip data crossing travel zones based on the start travel zone and the end travel zone. The approach further involves providing the trip data as an output based on the vehicle attribute.
An approach is provided for zone-to-zone trip reliability. The approach involves, for example, determining probe data collected from a plurality of sensors of a plurality of probe vehicles traveling in a geographic area of interest. The approach also involves processing the probe data to determine a plurality of vehicle trips. The approach further involves clustering the plurality of vehicle trips into one or more zone-to-zone trip categories based on the origin zones and destination zones of the plurality of vehicle trips. The approach further involves, for each zone-to-zone trip category of the one or more zone-to-zone trip categories, computing a zone-to-zone trip category reliability metric based on the plurality of vehicle trips clustered into each zone-to-zone trip category. The approach further involves providing the zone-to-zone trip category reliability metric for each zone-to-zone trip category as an output.
Embodiments described herein may provide a method for establishing traffic patterns in an efficient manner. Methods include: receiving historical probe data associated with a road segment; generating traffic pattern data and short-term traffic pattern data for a plurality of periods of time for the road segment, where the traffic pattern data includes traffic patterns that are consistent with historical traffic patterns during a first period of time, and where short-term traffic pattern data includes traffic patterns that fluctuate relative to historical traffic patterns during a second period of time; receiving real-time probe data associated with the road segment during the first period of time and the second period of time; generating traffic data for the road segment using historical traffic pattern data for the first period of time; and generating real-time traffic data for the road segment using the real-time probe data received during the second period of time.
A method is provided for analyzing data to identify turning circles within a road network, and to generate map data corresponding to the identified turning circles. Methods may include: receiving data corresponding to a geographical region; identifying, from the data, a turning circle in the geographical region; determining a size of the turning circle; generating, at the point location, map data geometry of the turning circle of the size determined; and updating a digital map database to include the map data geometry of the turning circle of the size determined at the point location, where the digital map database provides for at least one of route guidance or at least semi-autonomous vehicle control. According to some embodiments, the data corresponding to the geographical region includes at least one of satellite imagery or aerial imagery.
The disclosure provides a system, and a method for quality estimation of a traffic congestion incident reported by traffic system based on the information from one or more probe vehicles. The system is configured to identify one or more road segments and location information associated with the traffic congestion incident reported by traffic system based on the information from the one or more probe vehicles. A probe-based space-time diagram is generated based on the identified one or more road segments and location information associated with the traffic congestion incident reported by traffic system based on the information from the one or more probe vehicles. Ground truth is inferred for the traffic congestion incident. The generated probe-based space-time diagram is compared with the inferred ground truth for quality estimation of the traffic congestion incident reported by traffic system based on the information from the one or more probe vehicles.
A system and a method for determining lane-level traffic data is provided. The system is configured to obtain sensor data of each of a plurality of vehicles associated with a lane segment. The sensor data comprises at least one of: forward distance data of one or more vehicles in vicinity of each of the plurality of vehicles in the lane segment, or backward distance data of the one or more vehicles in the vicinity of each of the plurality of vehicles in the lane segment. The system is configured to determine lane distance data for the lane segment based on the sensor data, wherein the lane distance data comprises forward average distance data, or backward average distance data. The system is configured to determine traffic data for the lane segment based on the lane distance data.
A system, method and computer program product to predict high gradient wind effects to increase safety of a two-wheeled vehicle are disclosed. The system may detect, from a mobile sensor, one or more instances of high gradient wind effects based on contextual elements related to the high gradient wind effects. The system may map the one or more instances of high gradient wind effects into one or more generalizable feature vectors. The system may generate a trained machine learning model based on a training feature dataset, where the training feature dataset is an aggregation of the one or more generalizable feature vectors; and predict, using the trained machine learning model, a likelihood of high gradient wind effects to take place in a specific time and a specific space partition.
A system to learn parking restrictions of a region based on parking behaviors of vehicle parkers is disclosed. The system is configured for determining one or more contextual factors related to a user parking a vehicle in the region; computing a parking trust index based on the one or more contextual factors related to a user parking a vehicle in a region; classifying the user as a reliable parker if the parking trust index is greater than a reliability threshold and classifying the user as an unreliable parker if the parking trust index is less than a reliability threshold; and determining the parking restrictions of the area based on a parking behavior of the reliable parker and/or a parking behavior of the unreliable parker.
An approach is provided for measuring error in relative position data from a sensor. The approach, for instance, includes determining a pair of position measurements of a point feature. Each of the position measurements is computed from a global position measurement made using a first sensor and a relative position measurement made using a second sensor, and the position measurements of the pair are made within a time threshold or a distance threshold. The approach also involves determining a difference between the first position measurement and the second position measurement. The approach further involves determining an error of the relative position measurement based on the difference. The approach further involves providing the error as an output to indicate a measurement error of the second sensor used to measure the relative position measurement.
A system to predict cancelled ride-hailing rides is disclosed. The system is configured for detecting, from a mobile application, one or more instances of cancelled ride-hailing rides based on contextual elements related to the cancelled ride-hailing rides; mapping the one or more instances of cancelled ride-hailing rides into one or more generalizable feature vectors; generating a trained machine learning model based on a training feature dataset, where the training feature dataset is an aggregation of the one or more generalizable feature vectors; and predicting, using the trained machine learning model, a likelihood of cancelled ride-hailing rides to take place in a specific time and a specific space partition.
A system to assist an owner of a low-profile vehicle to avoid damages related to vehicle impact upon a raised feature of a road is disclosed. The system may be configured to obtain one or more locations of a vehicle impact upon the raised feature by detecting an occurrence of the vehicle impact and recording contextual factors related to the vehicle impact upon the raised feature, where the one or more obtained locations are clustered into a first location bucket defined by a manual detection of the vehicle impact and a second location bucket defined by an automatic detection of the vehicle impact. The locations may be map-matched to map locations. The system may cluster the map-matched locations and automatically predict, using a trained machine learning model trained on ground truth of a region, potential locations of vehicle impact relevant to the owner of the low-profile vehicle.
A method and an apparatus for updating database of network access point location are provided. The apparatus identifies a network access point accessible to a mobile apparatus and receives network access point information of the network access point. The apparatus receives a single-sided round-trip time (RTT) measurement of the network access point. The network access point information comprises identification data and a first signal strength value, and the single-sided RTT measurement comprises a second signal strength value. The apparatus scales the second signal strength value based on the first signal strength value. The apparatus updates the database of network access point location based on the scaled second signal strength value.
An apparatus and a method for determining an impact of high-beam lights on behaviors of vehicle users are disclosed. The apparatus obtains sensor data and map data associated with at a first vehicle, wherein the obtained map data is obtained from a map database. The apparatus further calculates a first probability score indicative of a usage of high-beam lights by the first vehicle based on the obtained sensor data and the obtained map data. Responsive to the calculated first probability score satisfying a threshold, the apparatus calculates a second probability score indicative of an impact on a behavior of a user of a second vehicle within a pre-determined distance of the first vehicle based on the obtained sensor data and the obtained map data. Further, the apparatus stores, in the map database, association data indicative of an association between the obtained map data and the calculated second probability score.
An approach is provided for securing vehicles from relay attacks using map database. The approach, for example, involves determining a first location of a vehicle and a first location of a user associated with the vehicle. The approach further involves determining, using a map database, at least one signal dead zone within a first pre-determined distance from the first location of the vehicle. A distance between the first location of the user associated with the vehicle and the first location of the vehicle exceeds the first pre-determined distance. The approach further involves generating a validation output in response to the first location of the user associated with the vehicle exceeding the first pre-determined distance from the first location of the vehicle.
An apparatus configured to collect and predict charging data for an electric vehicle (EV) from a mobile device associated with a user or the EV or an infotainment unit of the EV.
B60L 53/62 - Surveillance et commande des stations de charge en réponse à des paramètres de charge, p. ex. courant, tension ou charge électrique
B60L 53/63 - Surveillance et commande des stations de charge en réponse à la capacité du réseau
B60L 53/65 - Surveillance et commande des stations de charge impliquant l'identification des véhicules ou de leurs types de batteries
B60L 53/66 - Transfert de données entre les stations de charge et le véhicule
B60L 58/12 - Procédés ou agencements de circuits pour surveiller ou commander des batteries ou des piles à combustible, spécialement adaptés pour des véhicules électriques pour la surveillance et la commande des batteries en fonction de l'état de charge [SoC]
An approach is provided for an electric vehicle navigation system. For example, a destination is received as input. A geographic database is accessed to obtain data that represents a first road segment of a route to the destination. The data of the first road segment includes a first elevation coefficient of energy consumption associated with a first elevation change. The geographic database is accessed to obtain data that represents a second road segment of the route. The data of the second road segment includes a second elevation coefficient of energy consumption associated with a second elevation change. The first elevation coefficient is different than the second elevation coefficient. Energy consumption by the vehicle along the route is calculated based on the first elevation coefficient and the second elevation coefficient. Data representing energy consumption for the route is outputted as a function of the calculated energy consumption.
G01C 21/34 - Recherche d'itinéraireGuidage en matière d'itinéraire
G01C 21/36 - Dispositions d'entrée/sortie pour des calculateurs embarqués
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
96.
SYSTEM AND METHOD FOR ROAD TRAFFIC PATTERN CALCULATION
The disclosure provides a traffic pattern data calculation system, a method and a computer program product for calculating traffic pattern data. The traffic pattern data calculation system is configured to receive, for a road segment, historical traffic data and complementary data, for a predefined time window. The traffic pattern data calculation system is configured to extract from the received historical traffic data and the complementary data, secondary traffic data based on a filtering criterion. The traffic pattern data calculation system is configured to calculate the traffic pattern data for the road segment based on the extracted secondary traffic data. In addition, the traffic pattern data calculation system is configured to update a map database with the traffic pattern data of the road segment based on the calculation.
A system for dynamic determination of safety distance between vehicles is disclosed. The apparatus retrieves a first safety distance between a subject vehicle and a preceding vehicle of a set of vehicles within a first pre-determined distance of the subject vehicle. The preceding vehicle is traveling directly ahead of the subject vehicle. The apparatus further obtains a set of features associated with one or more of the set of vehicles, one or more of a set of users driving the set of vehicles, or a combination thereof. The apparatus further determines a second safety distance to be maintained between the subject vehicle and the preceding vehicle based on the first safety distance and the set of features. The second safety distance is less than the first safety distance. The apparatus further outputs the determined second safety distance on a user interface.
An approach is provided for processing user data. The approach, for example, involves monitoring mobility pattern data of a user for a predetermined time period. The monitoring of the mobility pattern data for the predetermined time period is consented by the user registered on a platform. The approach further involves determining age data of the user based on the monitored mobility pattern data. The approach further involves providing a label to user data associated with the user based on the determined age data. The label comprises one of a legal age user or an underage user. The processing of the labeled user data comprises storing the labeled user data in a user data database when the provided label corresponds to the legal age user, and performing one or more actions on the labeled user data when the provided label corresponds to the underage user.
An approach is provided for generating speed profile data given a road attribute using machine learning. The approach involves, for instance, determining a location of a road attribute in a road network. The approach also involves determining an analysis distance before and after the location of the road attribute in the road network. The approach further involves retrieving probe data collected using one or more location sensors of one or more vehicles traversing the analysis distance before and after the location of the road network. The approach further involves processing the probe data using a machine learning model to determine one or more machine-learned speed profiles of one or more road segments of the road network within the analysis distance and providing the one or more machine-learned speed profiles as an output.
G08G 1/052 - Détection du mouvement du trafic pour le comptage ou la commande avec des dispositions pour déterminer la vitesse ou l'excès de vitesse
G01S 19/01 - Systèmes de positionnement par satellite à radiophares émettant des messages horodatés, p. ex. GPS [Système de positionnement global], GLONASS [Système global de navigation par satellite] ou GALILEO
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
G08G 1/01 - Détection du mouvement du trafic pour le comptage ou la commande
G08G 1/017 - Détection du mouvement du trafic pour le comptage ou la commande par identification des véhicules
G08G 1/048 - Détection du mouvement du trafic pour le comptage ou la commande avec des dispositions pour compenser les conditions ambiantes ou d'autres paramètres, p. ex. la neige, un véhicule arrêté à un détecteur
09 - Appareils et instruments scientifiques et électriques
39 - Services de transport, emballage et entreposage; organisation de voyages
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Computer software for creating, using, updating, displaying and manipulating digital maps featuring lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs); digital maps featuring lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs); application programming interfaces (APIs) for creating, using, updating, displaying and manipulating databases and digital maps featuring lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs); computer software development software used to create and use digital maps and databases; computer software allowing to search and determine the location of lanes, roads, streets, cities, towns, goods, objects, people, events, buildings, places and points of interests (POIs); artificial intelligence computer software for navigation purposes, route planning, and searching for lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs); artificial intelligence computer software featuring digital maps, and real-time transportation, traffic, navigation and travel data; driver assistance computer software for land vehicles, aircraft and watercraft, including speed limit alerts, collision and accident alerts, automated lighting, adaptive cruise control, automated braking, incorporated GPS, traffic and weather information supply, correct lane formation and blind spots revelation; databases containing digital maps, historical and real-time traffic, weather, travel, transportation and navigation data, and information on lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs); computer software enabling advanced driver-assistance systems (ADAS), automated driving and hands-free driving of land vehicles; None of the aforementioned goods are used for the purposes of security, law enforcement, defence and military. Global positioning system and wireless communication system navigation services regarding the location of lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs); transport, traffic and travel information services; goods, places, events, objects and people positioning services; providing direction and route information for travel purposes; places search services, namely, for locating the geographic position of a place and in the field of transportation, traffic, navigation and travel information.. Designing and developing computer software for creating, using, updating, displaying and manipulating digital maps featuring lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs); providing on-line (non-downloadable) computer software for creating, using, updating, displaying and manipulating digital maps featuring lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs); providing on-line (non-downloadable) digital maps featuring lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs); providing temporary use of on-line non-downloadable software for use as an application programming interface (API) for creating, using, updating, displaying and manipulating databases and digital maps featuring lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs); providing temporary use of on-line non-downloadable software for use as development software used to create and use digital maps and databases; software as a service (SaaS) for creating, using, updating, displaying and manipulating digital maps featuring lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs); providing on-line (non-downloadable) computer software allowing to search and determine the location of lanes, roads, streets, cities, towns, goods, objects, people, events, buildings, places and points of interests (POIs); providing on-line (non-downloadable) artificial intelligence computer software for navigation purposes, route planning, and searching for lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs); providing on-line (non-downloadable) artificial intelligence computer software featuring digital maps, and real-time transportation, traffic, navigation and travel data; providing on-line (non-downloadable) driver assistance computer software for land vehicles, aircraft and watercraft, including speed limit alerts, collision and accident alerts, automated lighting, adaptive cruise control, automated braking, incorporated GPS, traffic and weather information supply, correct lane formation and blind spots revelation; providing on-line (non-downloadable) databases containing digital maps, historical and real-time traffic, weather, travel, transportation and navigation data, and information on lanes, roads, streets, cities, towns, goods, objects, people, events, and buildings, places and points of interests (POIs); providing on-line (non-downloadable) computer software enabling advanced driver-assistance systems (ADAS), automated driving and hands-free driving of land vehicles; None of the aforementioned services are used for the purposes of security, law enforcement, defence and military.
