Abstract: A method, system, and computer readable storage medium are provided for predicting behavior of a vehicle. More specifically, image data of the vehicle is obtained by generating class prediction data for the vehicle and then identifying one or more related points of interest. The method, system, and computer readable storage medium then predict the behavior of the vehicle based upon the one or more points of interest and the class prediction data.

Abstract: An approach is provided for confirming road vector geometry based on aerial image(s). For example, the approach involves retrieving a feature and a vector representation of a road link. The approach also involves processing one or more aerial images depicting the road link to extract a list of spectral pixel values corresponding to the vector representation. The approach further involves determining a degree of misalignment between the spectral pixel values and a spectral signature of the feature of the road link. The approach further involves initiating a confirmation of a geometry of the vector representation based on the degree of misalignment. The approach further involves providing the confirmation as an output.

Abstract: A method, apparatus and computer program product are provided for generating a transition variability index related to autonomous driving. In this regard, a first transition variability index is calculated. The first transition variability index is indicative of a first degree of variability in relation to transition of vehicles from respective autonomous levels while traveling proximate a first spatial reference point. Furthermore, a second transition variability index is generated. The second transition variability index is indicative of a second degree of variability in relation to transition of vehicles from respective autonomous levels while traveling along proximate a second spatial reference point. Updating of transition data associated with one of the first and second spatial reference points relative to another one of the first and second spatial reference points is then prioritized based on a comparison between the first transition variability index and the second transition variability index.

Abstract: A method, apparatus, and computer program product are provided for identifying the reliability of objects within a mapped region for localization and facilitating autonomous control of a vehicle. Methods may include: receiving an indication of an event having event data; assigning at least one object at a location of the event an impact score based on an estimated impact of the event; and providing an indication of a reduction in autonomous vehicle capability in response to the impact score failing to satisfy a predetermined value. The impact score may include a probability that the corresponding object is reliable for localization or autonomous vehicle control. Methods may include providing the indication of a reduction in autonomous vehicle capability to at least one device associated with a vehicle in response to the at least one device associated with the vehicle having a travel path including the at least one road link.

Abstract: A method, apparatus and computer program product are provided for improving user experiences for autonomous driving. In context of a method, the method determines one or more autonomous transition region parameters for a respective autonomous transition region along a route. The method also, based on the one or more autonomous transition region parameters, determines whether an action is to be performed by a vehicle in accordance with user preference data associated with a user. The method also causes the vehicle to perform the action in accordance with a determination that the action is to be performed by the vehicle.

Abstract: An apparatus, method and computer program product are provided for providing audio-based navigation. In one example, the apparatus determines reliability of a navigation technique for a vehicle. If the navigation technique is unreliable, the apparatus causes the vehicle to rely on audio-based navigation to traverse a route. The audio-based navigation provides one or more navigational instructions based on a sound signature associated with a location.

Abstract: Systems and methods for determining utilization of an area for vehicle parking are provided. For example, a method for determining utilization of an area for vehicle parking includes determining an expected level of utilization of an area for vehicle parking. The method also includes based on the determined expected level of utilization, analyzing one or more characteristics associated the area for vehicle parking. The method also includes based on the analysis, providing information for modifying the utility of the area for vehicle parking.

Abstract: Systems and methods for determining an electric vehicle score are provided. For example, a method for determining an electric vehicle score includes receiving mobility pattern data corresponding to an individual. The method also includes analyzing one or more characteristics associated with an area based on the mobility pattern data. The method also includes determining an electric vehicle score corresponding to the individual based on the analysis of the one or more characteristics associated with the area.

Abstract: A method, apparatus and computer program product are provided for managing autonomous vehicles. In this regard, vehicle context data associated with an indication of a change in an autonomous level for a vehicle traveling along a road segment is determined. Furthermore, the vehicle is assigned to a queue of vehicles traveling along the road segment in response to a determination that the vehicle context data corresponds to particular vehicle context data associated with the queue of vehicles. An indication of the queue of vehicles may also be provided to the vehicle to facilitate navigation of the vehicle.

Abstract: An apparatus, method and computer program product are provided for providing availability of designated electric vehicles during an emergency. In one example, the apparatus receives a mobility pattern of a user of an electric vehicle and adds the user and the electric vehicle to an exception list based on the mobility pattern. During an emergency, the apparatus ensures a predetermined amount of state of charge for each electric vehicle that is electrically coupled to an external power source and is indicated in the exception list.

Abstract: Systems and methods for determining a sustainability score are provided. For example, a method for determining a sustainability score includes comparing one or more characteristics of a first geographic area with one or more characteristics of a second geographic area. The method also includes based on the comparison, determining a third geographic area. The third geographic area includes at least one characteristic of the one or more characteristics of the second geographic area. The method also includes determining a sustainability score of the third geographic area.

Abstract: An approach is provided for determining a bicycle lane disruption index based on vehicle sensor data. The approach, for example, involves retrieving sensor data collected from one or more devices within proximity of a bicycle lane. The sensor data is geotagged with location data. The approach also involves processing the geotagged sensor data to identify an observed obstruction to bicycle traffic on the bicycle lane. The approach further involves map-matching the location data to a bicycle lane segment of a geographic database. The approach further involves computing the bicycle lane disruption index for the bicycle lane segment based on the obstruction. The bicycle lane disruption index indicates a probability of encountering any obstruction on the bicycle lane segment. The approach further involves storing the bicycle lane disruption index as an attribute of the bicycle lane segment in the geographic database.

Abstract: Provided herein is a method, apparatus, and computer program product for using isolines representing travel time or distance to points-of-interest to identify a recommended property location.

Abstract: Systems and methods for communicating uncertainty around stationary objects are provided. For example, a method for communicating uncertainty around stationary objects includes receiving sensor data corresponding to a stationary object at a location along a road segment. The sensor data is captured via one or more sensors of a first vehicle. The method also includes based on the sensor data, determining a level of uncertainty corresponding to the stationary object. The method also includes based on the determined level of uncertainty, providing an instruction for one or more sensors of a second vehicle to capture additional sensor data corresponding to the stationary object at the location along the road segment.

Abstract: An approach is provided for location sharing using a LiDAR-based location signature. The approach involves, for example, receiving a Light Detection and Ranging (LiDAR) scan of a location captured by a LiDAR sensor of a portable device. The approach also involves processing the LiDAR scan to generate a LiDAR location signature that is representative of the location of the portable device. The approach further involves transmitting the LiDAR location signature to another device to share the location of the portable device with the another device.

Abstract: An approach is provided for determining an autonomous vehicle reaction strategy when facing a wrong way driving vehicle. The approach, for example, involves processing mapping data, sensor data, or a combination thereof to develop a map of an area within a threshold distance of an autonomous vehicle in response to a detection of an oncoming vehicle that is driving in a wrong direction towards the autonomous vehicle. The approach also involves using a decision tree of a plurality of candidate strategies for avoiding the oncoming vehicle to select a strategy based on one or more attributes of the map. The approach further involves presenting the selected strategy in a user interface of the autonomous vehicle.

Abstract: An approach is provided for creating a LiDAR path signature. The approach involves, for instance, receiving a plurality of Light Detection and Ranging (LiDAR) scans captured by a LiDAR sensor of a portable device as the portable device travels on a path through an environment. The approach also involves processing the plurality of LiDAR scans to generate a LiDAR path signature that is representative of the path of the portable device through the environment. The approach further involves providing the LiDAR path signature as an output.

Abstract: A system, method, and computer program product may be provided for generating a routing graph for a user. A system may include a memory configured to store computer program code instructions; and a processor configured to execute the computer program code instructions to define a geographic area of interest for the user; and identify a cluster of one or more mobility hubs in the area of interest. The processor may be further configured to create the routing graph from an edge of the one or more mobility hubs based on one or more preferences of the user, and provide the routing graph to a routing engine for calculating an intermodal route.

Abstract: Systems and methods for determining a vehicle boarding score are provided. For example, a method for determining a vehicle boarding score includes receiving traffic data corresponding to a vehicle along a route. The route includes one or more stops for boarding the vehicle. The method also includes analyzing the traffic data along the route. The method also includes based on the analysis, determining a vehicle boarding score for boarding the vehicle at the one or more stops.

Abstract: An apparatus, method and computer program product are provided for predicting road locations that are likely to induce tire pressure changes. In one example, the apparatus receives historical data of an event in which a first vehicle is impacted by a first tire pressure change at a first road segment. The historical data indicates point-of-interest (POI) information associated with the first road segment. The apparatus trains a prediction model using the historical data. The prediction model is configured to determine a likelihood in which a second road segment induces a second tire pressure change for a second vehicle based on POI information associated with the second road segment.