Abstract: An apparatus, method and computer program product are provided for determining a newly established vehicle-related rule within an area. In one example, the apparatus receives sensor data indicating attributes of an area for a first period. The attributes indicate a number of vehicle-related tickets issued within the area, a parking orientation of each vehicle within the area, or a combination thereof. The apparatus compares the sensor data to historical data associated with the area. The historical data indicate the attributes of the area for one or more second periods preceding the first period. Based on comparison of the sensor data and the historical data, the apparatus determines a likelihood of a vehicle-related rule established for the area, where the vehicle-related rule did not exist during the one or more second periods. The apparatus causes a notification indicating the likelihood at a user interface.

Abstract: An apparatus, method and computer program product are provided for providing autonomous vehicle navigation at intersections. In one example, the apparatus identifies an intersection associated with at least two road signs having the same sign type and facing the same direction. The apparatus updates map data to include a datapoint that provides a representation of a single road sign at the intersection instead of the at least two road signs, thereby enabling an autonomous vehicle relying on the map data to traverse the intersection to adhere to the single road sign in lieu of the at least two road signs.

Abstract: A method, apparatus, and non-transitory computer-readable storage medium for determining an intersection condition are provided. An example embodiment may obtain entity count data of an area comprising an intersection, obtain map feature data of the area comprising the intersection, obtain temporal context data of the area comprising the intersection, and generate an intersection deadlock score based on the entity count data, the map feature data, the temporal context data, or a combination thereof. The generated intersection deadlock score may further be used to provide a prediction of a deadlock condition based on the intersection deadlock score to a traffic application and/or a navigation application.

Abstract: A system, a method and a computer program product are provided, for example, to assist vehicle turns during limited visibility of incoming vehicles based on a turning confidence index for a left turn decision. For example, the system may obtain a plurality of traffic features related to the intersection of the road based on historical road features and/or real-time road features associated with the road. Using a trained machine learning model, a turning confidence index for the intersection of a road and/or a driving decision associated with attempting to turn at the intersection of the road may be determined.

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 method, apparatus, and computer program product are provided for using visual analysis of a road surface to identify markings indicative of road surface anomalies. Methods may include, for example: receiving data from an image sensor associated with a vehicle traveling along a road segment; identifying, within the data, a visual indication of a road surface anomaly, where the visual indication is a result of the road surface anomaly; and cause at least one of: an indication of the road surface anomaly to be provided to a user of the vehicle; a vehicle operational setting to be changed responsive to the road surface anomaly; or a map update to be generated to include the road surface anomaly within a map database.

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: A system, a method and a computer program product are provided to predict vehicle parking bunching in a geographic region. For example, the system is configured to obtain a plurality of contextual features and/or a plurality of sensor data related to parking information in the geographic region. The system is configured to predict a vehicle parking bunching based on a vehicle unparking threshold, a vehicle separation distance cluster threshold and/or unparking vehicle information. The system may also be configured to alert a vehicle of the vehicle parking bunching with a vehicle parking bunching notification.

Abstract: A system, a method and a computer program product to compute a pedestrian real-time vulnerability index are disclosed. For example, the system is configured to obtain static information related to the geographic region near the pedestrian and/or dynamic information related to the geographic region near the pedestrian. The system is configured to compute the real-time vulnerability index for the pedestrian based on the static information related to the geographic region near the pedestrian and/or the dynamic information related to the geographic region near the pedestrian. The system may alert the pedestrian to the real-time vulnerability index with a pedestrian advisory indication.

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: An approach is provided for determining object utility for personalizing service for space utilization. The approach, for example, involves using a sensor to capture sensor data of an environment including an object over a period of time. The approach also involves processing the sensor data to track one or more interactions between at least one user and the object over the period of time. The approach further involves determining a utility value of the object based on the one or more interactions. The approach further involves providing the utility value as an output. In one example embodiment, the approach further involves determining a service, an action, or a combination thereof to apply to the object based on the utility value.

Abstract: An approach is provided for associating an object with a spatial budget. The approach, for example, involves initiating a scan of an object, an available space, or a combination thereof using a sensor to determine a spatial volume of the object, a spatial volume of the available space for a storage or a placement of the object, or a combination thereof. The approach also involves determining a spatial cost of an object based on the spatial volume of the object. The approach further involves determining an available spatial budget based on the spatial volume of an available space. The approach further involves determining a spatial budget for the object based on the spatial cost of the object and the available spatial budget. The approach further involves providing the spatial budget of the object, the spatial cost of the object, the available spatial budget, or a combination thereof as an output.

Abstract: Systems and methods for determining a route for training a machine learning model for mood prediction are provided. For example, an apparatus comprising a processor and a memory comprising computer program code for one or more programs, wherein the memory and the computer program code is configured to cause the processor of the apparatus to determine mood data associated with a plurality of locations based on past vehicle trips. The computer program code is also configured to cause the processor to determine static map features associated with the plurality of locations. The computer program code is also configured to cause the processor to train a machine learning model on the static map features and the mood data associated with the plurality of locations.

Abstract: An apparatus, for example, obtains a trip intent associated with a user; and causes a trip intent engine to determine a trip plan based at least in part on the trip intent using a trip intent model. The trip intent engine comprises the trip intent model, which is a machine learning-trained model. Determining the trip plan comprises identifying a destination based at least in part on point of interest data and the trip intent, determining a route from a current location of the user to the destination, determining a time for beginning a trip to the destination, and/or determining one or more modes of transportation for use in traversing one or more portions of the route. The apparatus causes at least a portion of the trip plan to be provided to the user via a user interface of a user apparatus.

Abstract: An apparatus, method and computer program product are provided for predicting tire temperature levels. In one example, the apparatus receives input data indicating a target route for a target vehicle, attributes associated with the target vehicle, and attributes of the target route and causes a machine learning model to generate output data as a function of the input data. The output data indicate prediction of tire temperature levels of the target vehicle during a period in which the target vehicle traverses the target route. The machine learning model is trained to generate the output data as a function of the input data based on training data indicating events in which vehicles traversed routes. Specifically, the training data include tire temperature levels of the vehicles, vehicle data associated with the vehicles, map data associated with the routes, and environmental data associated with the routes.

Abstract: An approach is provided for providing drop-off locations for passengers of a vehicle to reach different destinations via a multimodal route. A routing platform receives a request to generate a navigation route, i.e., a multi-point intermodal route that directs the passengers to reach the destinations using the vehicle in combination with the other mode of transport. The routing platform further computes the navigation route based on an optimization parameter to include a route taken by the vehicle and at least one intermodal route leg. The navigation route includes drop-off locations where subsets of the passengers access the other mode of transport to complete the at least one intermodal route leg to at least one of the destinations. The optimization parameter is minimized with respect to the route taken by the vehicle and/or the at least one intermodal route leg.

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: The disclosure provides a system, a method, and a computer program product for verification of traffic incident. The system may be configured to receive a traffic incident trigger. Based on the traffic incident trigger, the system may select one or more vehicles for verification of the traffic incident detected at a location. The system may determine a route of travel for each vehicle of the selected one or more vehicles based on the location of the detected traffic incident. The system may reroute the selected one or more vehicles on the respective route of travel determined for each vehicle. The selected one or more vehicles are rerouted to record data of the traffic incident. The system may further verify the detected traffic incident based on the data of the traffic incident recorded by the rerouted one or more vehicles.

Abstract: An apparatus, method and computer program product are provided for providing autonomous vehicle navigation at intersections. In one example, the apparatus identifies an intersection associated with at least two road signs having the same sign type and facing the same direction. The apparatus updates map data to include a datapoint that provides a representation of a single road sign at the intersection instead of the at least two road signs, thereby enabling an autonomous vehicle relying on the map data to traverse the intersection to adhere to the single road sign in lieu of the at least two road signs.

Abstract: System and methods are provided for that allow users of micro mobility and shared mobility services to reduce the uncertainty related to the availability of a shared vehicle by quickly identifying such vehicles using a route that maximizes the visibility of the shared vehicle through line-of-sight computations.