Abstract: 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.

Abstract: 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.

Abstract: An approach is disclosed for verifying a lane closure using probe data. The approach involves, for example, receiving probe data collected from a probe device traveling a road link. The approach also involves performing a spatial clustering of the probe data with respect to a longitudinal axis of the road link. The approach further involves comparing the spatial clustering of the probe data to a historical spatial clustering of historical probe data of the road link to determine a cluster shift, wherein the cluster shift indicates that a cluster of the spatial clustering has shifted spatially to the left or right relative to at least one other cluster of the historical clustering. The approach also involves detecting a lane closure on the road link based on determining that the cluster shift is greater than a shift distance threshold. The approach further involves providing the detected lane closure as an output.

Abstract: A system is disclosed for estimating intersection connection point. The system, for example, obtains first feature data for a first feature line, obtains second feature data for a second feature line. The second feature line is within a first predefined threshold from the first feature line. The system identifies an intersection area based on the first feature data and the second feature data, the intersection area comprising a candidate intersection point; estimates an offset value for the first feature line and the second feature line within the intersection area; estimates heading information for the candidate intersection point based on the first feature data, the second feature data and the intersection area; and estimates the intersection connection point for the first feature line and the second feature line based on the candidate intersection point, the offset value and the heading information.

Abstract: A method, apparatus and computer program product for determining a road work event confidence are described herein. In the context of a method, the method may determine a road network speed profile corresponding with a road work event location. The method may determine, based at least in part on probe data corresponding with the road work event location, a probe speed profile. The method may determine the road work event confidence based at least in part on evaluation of the road network speed profile and the probe speed profile. Evaluation of the road network speed profile and the probe speed profile may comprise identifying a plurality of road segments corresponding with the road work event location and correlating road network speed profile characteristics and probe data characteristics for each respective road segment.

Abstract: The disclosure provides a method, a system, and a computer program product for generating map data. The method comprises obtaining, from one or more user equipment, user preference data associated with a region, wherein the user preference data is associated with an indication of at least one of routing of traffic through a region or not routing of traffic through the region. The method may further include calculating, by a processor, an aggregate value for the region based on the obtained user preference data and generating map data indicative of the calculated aggregate value for the region.

Abstract: A method, apparatus, and computer program product are provided for providing merging assistance for a vehicle. The method includes capturing a vehicle speed of the vehicle travelling in a lane of roadway. The method also includes receiving adjacent vehicle data relating to an adjacent vehicle in an adjacent lane. The method further includes receiving adjacent lane data relating to a speed of one or more vehicles in the adjacent lane. The method still further includes generating merger information for the vehicle based on the vehicle speed, the adjacent vehicle data, and the adjacent lane data. A corresponding apparatus and computer program product are also provided.

Abstract: A method is provided for selective processing of sensor data, and more particularly, to parsing sensor data from a data stream to identify sensor data relevant to specific requests, and processing the relevant data based on the type of request. Methods include: receiving a campaign management request defining requested source data metrics; receiving source data from a plurality of sources within a geographic area; determining a subset of the source data that satisfies the requested source data metrics; processing the subset of the source data satisfying the requested source data metrics to obtain observations; and updating map data of a map database based on the observations.

Abstract: 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.

Abstract: An approach is provided for a runaway vehicle detection system. The approach, for example, involves processing sensor data to detect that a vehicle is involved in or predicted to be involved in a runaway vehicle event. The approach also involves processing map data, the sensor data, or a combination thereof to determine a runaway vehicle safety location based on at least one attribute of the vehicle. The approach further involves generating an alert message indicating the runaway vehicle safety location. The approach further involves providing the alert message for display on a device associated with the vehicle. In one embodiment, the approach further involves mapping the runaway vehicle safety location, the runaway vehicle event, or a combination thereof to digital map of a geographic database.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A method, apparatus and computer program product are configured to dynamically augment ionospheric correction data. A method receives, from a requesting device, a request for grid layout data, where the grid layout data is associated with one or more geographical areas experiencing atmospheric delay incurred with a satellite-based positioning technique. The method transmits, in response to the request for the grid layout data, a grid layout definition message comprising a grid layout definition associated with the grid layout data associated with the one or more geographical areas. The method generates correction data based in part on the grid layout data, where the correction data is configured to correct the atmospheric delay incurred with the satellite-based positioning technique. The method also generates correction messages comprising at least a portion of the correction data and transmits the correction messages to the requesting device based on a dynamic correction data update rate.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.