Abstract: A method, apparatus, and computer program product are therefore provided for emulating vehicle features of a first vehicle in a second vehicle having different features. Methods may include: receiving an indication of a user operating an unfamiliar vehicle; determining vehicle features familiar to the user; and providing emulation of one or more features of the vehicle features familiar to the user in the unfamiliar vehicle. According to some embodiments, the vehicle features familiar to the user are determined based on one or more vehicles familiar to the user. According to certain embodiments, vehicle features familiar to the user include one or more of vehicle size, vehicle performance, or vehicle autonomy level.

Abstract: The disclosure provides a system, a method, and a computer program product for updating map data. The system, for example, obtains sensor data from one or more user equipment. The sensor data is associated with a road object. Further, the system, determines a first location of a road observation sight and a second location of the road object based on a timestamp associated with the first location. Further, a distance associated with the second location of the road object and a center point of a link, is calculated. The link is a map matched link associated with the second location. Further, the system updates the map data based on the calculated distance.

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: 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.

Abstract: An apparatus, method and computer program product are provided for providing a tire pressure analysis. In one example, the apparatus receives first sensor data indicating a first tire pressure change associated with a first vehicle and causes a prediction model to generate a predicted cause of the first tire pressure change based on the first sensor data. The prediction model is trained based on historical data, the historical data defining a plurality of tire pressure signatures. Each of the plurality of tire pressure signatures correlates a cause of a second tire pressure change associated with a second vehicle to second sensor data indicating one or more tire pressure levels of the second vehicle over a period in which a wheel of the second vehicle completes a revolution. The apparatus further causes a notification of the predicted cause at a user interface associated with the first vehicle.

Abstract: 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.

Abstract: 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.

Abstract: Embodiments described herein may provide a method for analyzing traffic congestion at a toll plaza and identifying a preferred lane of travel through the toll plaza based on the traffic congestion. Methods may include: determining active toll lanes of all toll lanes at a toll plaza; obtaining probe data for each active toll lane at the toll plaza; determining lane-wise congestion for each active toll lane at the toll plaza; identifying a preferred lane of the active toll lanes; and providing for at least one of a navigational instruction or at least semi-autonomous vehicle control to enter or continue in the preferred lane.

Abstract: A method, apparatus, and user interface are provided for generating personalized splines. For example, one or more geometries that represent a portion of a road network are identified and a first spline curve is calculated from the one or more geometries. One or more additional geometries that represent a different portion of the road network are then interpolated, by a processor, and the processor then calculates at least a second spline curve from the one or more additional geometries, wherein the second spline curve is derived, at least in part, from personalized driving preference data.

Abstract: An apparatus, method and computer program product are provided for predicting tire temperature levels. In one example, the apparatus receives input data indicating attributes of the target vehicle and attributes of target routes for the target vehicle. The apparatus causes a machine learning model to generate output data as a function of the input data, where the output data indicate a subset of the target routes of which the target vehicle can successfully traverse while using the at least one spare tire. The machine learning model is trained to generate the output data as a function of the input data based on training data, where the training data indicate events in which vehicles used spare tires to traverse routes. The training data indicate attributes of the vehicles and attributes of the routes.

Abstract: A system is disclosed for generating speed limit data. The system may include a memory configured to store computer executable instructions and one or more processor configured to execute the instructions to receive sign data relating to one or more traffic entities. The sign data comprises at least one of: a set of speed values, a set of transportation mode values, and one or more entity parameters associated with the corresponding one or more traffic entities. The processors are further configured to generate matching data based on a matching between the set of speed values and the set of transportation mode values, based on the one or more entity parameters. The processors are further configured to generate speed limit data based at least on: the matching data, the sign data and a predefined condition associated with transportation mode.

Abstract: An apparatus, method and computer program product are provided for determining a state of visibility for a road object. In one example, the apparatus receives temporal data, calculates an orientation of a light source with respect to a road object using the temporal data, and predicts a state of visibility for the road object based on the orientation of the light source. In another example, the apparatus determines an artificial light source associated with a road object, receives attribute data associated with the artificial light source, determines a state of the artificial light source using the attribute data, and predicts a state of visibility for the road object based on the state of the artificial light source.

Abstract: A system, a method, and a computer program product for validating a road sign are provided. The method comprises determining a transition location associated with the road sign using map data. The transition location is at least one of a map region start location or a map region end location. The method further comprises determining road sign data associated with the road sign using a sensor data cluster. The method further comprises determining a validity of the road sign based on the road sign data and the transition location.

Abstract: System and methods are provided that allow users of shared vehicles to benefit from an enhanced user experience that seamlessly unlocks and/or provides access to features for autonomous vehicles by proactively computing an interest index based on detected contextual behavioral patterns of the pedestrians such as the trajectory a candidate passenger is walking given a locational context.

Abstract: A system, a method, and a computer program product may be provided for processing event data. For example, event data relating to an occurrence of an event corresponding to a first tile is received, and a first count value associated with the received event data is determined. A threshold count value associated with the event within the first tile is obtained, and dynamic switching between a link-based processing and a tile-based processing is performed, based on a comparison between the first count value and the threshold count value, wherein on determining the first count value to be greater than the threshold count value, the tile-based processing is performed, and on determining the first count value to be lesser than the threshold count value, the link-based processing is performed.

Abstract: A method, apparatus and computer program product are provided for controlling a functional road object. For example, at least one processor receives road sign attribute data indicating at least one attribute of a road sign and receives weather forecast data indicating a weather forecast of a location in which the road sign is disposed. The road sign includes at least one machinery for mitigating exposure to one or more weather conditions. The at least one processor identifies a state of visibility for the road sign using the road sign attribute data and the weather forecast data and generates a control signal for controlling the at least one machinery using the state of visibility.

Abstract: Embodiments described herein may provide a method for using vehicle sensor data to identify where road work exists within a road network. Methods may include: receiving probe data and sensor data from a plurality of probe apparatuses traveling along a sequence of road segments; identifying, from the sensor data, one or more indicators of a beginning of a road work area; identifying, from the sensor data, binary indicators of the presence of road work or a lack of presence of road work along the sequence of road segments; and determining, based on the one or more indicators of a beginning of a road work area and the binary indicators of the presence of road work or the lack of road work along the sequence of road segments, a probability of road work occurring along one or more road segments of the sequence of road segments.

Abstract: An approach for traffic incident verification involves receiving a traffic message channel (TMC) message indicating a traffic incident. The TMC message indicates an extent of the traffic incident in a road graph using TMC location code(s)/offset(s). The approach also involves matching the TMC location code(s)/offset(s) to a first set of map road link(s) and offset(s) of a geographic database, determining sensor data collected from vehicle(s) travelling within the road graph. The sensor data indicates the extent as location point(s) of topology segment(s) (TSs) and TS offset(s), matching the location point(s) of the TS(s) and TS offset(s) to a second set of map road link(s) and offset(s) of the geographic database, determining an intersection set between the first and second sets, and initiating a confirmation of the traffic incident reported in the TMC message based on the sensor data of the location point(s) of the TSs in the intersection set.

Abstract: Embodiments described herein may provide a method for using map data to alter criteria for the identification of road work in locations where false positives are more likely. Methods may include: receiving probe data from a plurality of probe apparatuses traveling within a road network; determining, from the probe data captured at a first location, an indication of road work; determining a type of map area of the first location; applying a suppression method to the probe data captured at the first location in response to the type of map area of the first location corresponding to an area having a relatively high false positive rate of indications of road work; and determining, based on the suppression method to the probe data captured at the first location, the presence or absence of road work occurring at the first location.

Abstract: A method, apparatus, and user interface for road debris detection comprising, in some embodiments, obtaining image data of at least one navigable link and/or road debris, determining a road debris indicator based on the obtained image data, wherein the road debris indicator includes road debris classification data, and associating the determined road debris indicator with one or more navigable links to update a map layer of a geographic database.