Abstract:
An approach is provided for generating parking occupancy data using a machine learning model. The approach involves determining one or more classification features of a road link. The approach also involves processing the one or more classification features using the machine learning model to match the road link to a link category. The approach further involves determining a parking occupancy pattern for the road link based on the link category. The approach further involves creating or updating a parking occupancy record of a geographic record corresponding to road link using the parking occupancy pattern.
Abstract:
An approach is provided for determining safety levels for one or more locations based, at least in part, on signage information. The approach involves determining signage information associated with at least one location. The approach also involves causing, at least in part, a creation of at least one predictor model based, at least in part, on the signage information and one or more attributes associated with the at least one location. The approach also involves causing, at least in part, a classification of the at least one location, one or more other locations, or a combination thereof according to one or more safety levels using, at least in part, the at least one predictor model.
Abstract:
An approach is provided for determining safety scores for locations, frequency of users traversing the locations, or a combination thereof to calculate fee rates. The approach involves determining at least one safety score associated with one or more locations, at least one user traversing the one or more locations, or a combination thereof. The approach also involves determining at least one frequency of traversal of the at least one location by the at least one user. The approach further involves causing, at least in part, a calculation of at least one fee rate for the at least one user based, at least in part, on the at least one safety score and the at least one frequency of traversal.
Abstract:
A method, apparatus and computer program product are provided to process probe data in accordance with a map-centric map matching technique. Methods may include obtaining a road link from a database of a plurality of road links; calculating a boundary separation distance for spacing vertices along a length of the road link; determining a sequence of vertices along the road link according to the boundary separation distance; generating, for each vertex, a spatial boundary where an overlap between spatial boundaries of adjacent vertices extends a first distance from the road link, where the first distance is a minimum distance from the road link; and providing for storage of a spatial boundary structure for the road link including the plurality of spatial boundaries associated with the road link.
Abstract:
A method, apparatus and computer program products are provided for grouping a plurality of vehicles together into a platoon and using navigation and other available data to optimize the efficiencies of operating the vehicles together as a platoon. Methods may include receiving a first trip request including a first vehicle identification, trip destination, and associated preferences; receiving a second trip request including a second vehicle identification, trip destination, and associated preferences; and generating a platooning plan including assignment of platoon leader to the first vehicle identification and a joining location where a vehicle of the first vehicle identification is to form a platoon with a vehicle of the second identification. Methods may include joining the first vehicle and the second vehicle in a secure vehicle-to-vehicle communication session.