Abstract: A method, apparatus and computer program product are provided to determine one or more probe point data objects and/or validate one or more probe point data objects for use with determination of traffic conditions. A determined probe point data object may be determined and/or updated with one or more probe point data objects which exclude any probe point data objects determined to correspond to an off-road location. A validated probe point data object may additionally or alternatively be determined using one or more first validation sequence check operations and using one or more second validation sequence check operations. The determined probe point data object and/or validated probe point data object may be used to determine one or more traffic conditions, and as a result, traffic condition determinations may be determined more accurately and efficiently.

Abstract: A method is provided to using a generative adversarial network to generate map geometry from images representing probe data. Methods may include: receiving a rasterized image representative of probe data within a geographic area, where each pixel of the rasterized image includes a property representing at least one component of the probe data; generating a prediction image of road features within the geographic area using a generative adversarial network based on trained model parameters and the rasterized image; determining one or more map elements based, at least in part, on the prediction image and georeferenced locations of the road features within the prediction image; and updating a map of the geographic area with one or more map elements.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: An approach is provided for computation of risk index. The approach, for example, involves acquiring historical probe data associated with an area. The historical probe data comprises data associated with distribution of vehicles entering or leaving the area in a given time partition. The approach further involves obtaining map feature data associated with an entrance or exit of the area, from a geographical database. The map feature data comprises data associated with physical objects in vicinity of the area. The approach further involves computing a risk index for the entrance or the exit for the given time partition, based on the historical probe data and the map feature data. The risk index indicates a probability of occurrence of a hazard in the vicinity of the entrance or the exit. The approach further involves storing the risk index as an attribute of the entrance or the exit in the geographic database.

Abstract: A method, a system, and a computer program product for updating a map database are disclosed herein. The method comprises receiving a map update request including a bloom filter and a bounding box identifying a region of a map. The method may further comprise obtaining a plurality of second map area identifiers and the corresponding area map content. The method may further comprise computing a plurality of second digests corresponding to the plurality of second map area identifiers, based on the plurality of second map area identifiers and the second map area content and generating the map update data for the region, based on the plurality of second digests and the bloom filter.

Abstract: One or more processors obtain GNSS receiver data captured during a time period by a GNSS receiver disposed onboard a constrained vehicle traversing a constrained route. The processor(s) determine a GNSS-based position estimate based on the GNSS receiver data. The position estimate indicates an estimated location of the GNSS receiver during at least a portion of the time period. The processor(s) determine an error characterization corresponding to an offset between the position estimate and an expected location of the GNSS receiver along the constrained route. The processor(s) cause a mobile device to perform a positioning or navigation-related function that accounts for the error characterization.

Abstract: 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.

Abstract: 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.

Abstract: An approach is provided for spatial aggregation for location based services. The approach involves, for example, determining a plurality of partitions for a geographic area. The approach also involves determining a set of destinations that is common to a first partition and a second partition of the plurality of partitions. The set of destinations are associated with a plurality of trips originating from first partition, the second partition, or a combination thereof. The approach further involves determining a statistical property of the plurality of trips between any of the set of destinations and the first partition, the second partition, or a combination thereof. The approach further involves merging the first partition with the second partition into the traffic analysis zone based on the statistical property.

Abstract: Provided herein is a method of estimating a travel time along a route. Methods may include: obtaining a route between an origin and a destination, where the route includes a plurality of road links; identifying a subset of road links of the plurality of road links; providing an identification of each road link of the subset of road links to a service provider; receiving an indication of a pace of travel along each of the subset of road links; computing an estimated travel time along the route based on the pace of travel along each of the subset of road links; and providing an estimated time-of-arrival at the destination based on an identified departure time and the estimated travel time along the route. Methods may include computing an estimated travel time error along the route, and providing the estimated travel time error as a potential error of the estimated time-of-arrival.

Abstract: An approach is provided for detecting road features. The approach, for example, involves receiving image data associated with one or more road features. The received image data may be associated with ground truth label data corresponding to the one or more road features. The approach further involves determining a set of shadowed regions from one or more images of the received image data. The approach further involves generating artificial shadow data based on the determined set of shadowed regions. The approach further involves augmenting the image data with the generated artificial shadow data by applying the generated artificial shadow data to the received image data. The approach further involves training a machine learning (ML) model based on the augmented image data and the ground truth label data. The ML model is trained to detect the one or more road features.

Abstract: A system, a method and a computer program product are provided to determine a left turn decision for a user or autonomous vehicle attempting to turn at an intersection of a road. For example, the system obtains contextual features and/or sensor data related to the intersection of the road. An optimal location on the road is determined for the user or autonomous vehicle to position the vehicle to make the left turn decision, based on the contextual features and/or the sensor data. A left turn risk factor is determined based on the location on the road for the user or autonomous vehicle to position the vehicle to make a left turn. An alert is presented to the user or autonomous vehicle regarding the left turn risk factor with a left turn advisory message.

Abstract: The disclosure provides a system, a method, and a computer program product for validation of sensor data. The system may be configured to receive sensor data associated with a hazard. The sensor data may include at least a first time of occurrence of the hazard. The system may be further configured to determine a second time of occurrence of the hazard based on a time-space diagram associated with one or more vehicles that passed through a location of the occurrence of the hazard. The system may further calculate a validation result for the received sensor data based on a comparison of the first time of occurrence and the second time of occurrence, and an associated first predefined threshold.