Abstract: A method, a vehicle and a system that identify and use a location significant to a person associated with a vehicle based on vehicle probe data are described. Vehicle transportation network information representing a vehicle transportation network is identified, the vehicle transportation network information including destinations of a vehicle obtained from vehicle probe data. For at least some of the destinations, density-based clustering is performed using temporal data associated with the at least some of the destinations to form at least two spatio-temporal clusters. A contextual label is assigned to a location associated with a first spatio-temporal cluster of the at least two spatial-temporal clusters based on the temporal data associated with the first spatio-temporal cluster, the location being a labeled location, and the labeled location is used for vehicle operation. The labeled location may be used for navigation or service, for example.

Abstract: Service request are transmitted to multiple vehicles. Each service request is associated with a time and a location. Driving histories of at least some vehicles are known. A first location associated with a first service request is compared with a known location in a vehicle driving history, the known location comprising a first cell identifier of a first grid where a size of the cells of the first grid indicating a maximum acceptable deviation of the vehicle from a travel segment in the first driving history that includes the first cell identifier. When the first location matches the known location and the associated time overlaps a start time or an end time of the travel segment that includes the first cell identifier, the first service request is identified to the vehicle. The vehicle sends an indicator that it will perform at least a portion of a service, and an instruction is transmitted to the vehicle that causes the vehicle to perform the service.

Abstract: Vehicle data exchange may include receiving, from a subscriber device associated with a subscribing entity, a vehicle data exchange request including a vehicle sensor type identifier and vehicle data exchange request target information, wherein the vehicle data exchange request target information includes an indication of a defined geospatial region. Vehicle data exchange may include identifying, based on the vehicle data exchange request, a publishing entity, and transmitting a vehicle data exchange request execution notification to a publisher device associated with the publishing entity. Vehicle data exchange may include receiving, from the publisher device, vehicle sensor data generated by a sensor of a vehicle associated with the publishing entity within the defined geospatial region, generating a vehicle data exchange response based on the vehicle sensor data, and transmitting the vehicle data exchange response to the subscriber device.

Abstract: For each vehicle of multiple vehicles, a first location for a service is associated with a first cell identifier of a grid, which is in turn compared to travel segments based on historical trips of the vehicle. At least some of the grid cells are associated with the historical trips, and the cell size indicates a maximum acceptable deviation from a travel segment. Travel segments include a start cell identifier, a start time, an end cell identifier, and an end time. When the first cell identifier matches the start or end cell identifier, whether the first time associated with the first location overlaps the start or end time is determined. When such an overlap exists, the vehicle is identified in a list of candidate vehicles for the service. An instruction to a candidate vehicle in the list causes the candidate vehicle to perform at least a portion of the service.

Abstract: A method and apparatus for associating a person with a portion of transportation network information based on vehicle operating information are described. The information includes a plurality of destinations. First vehicle operating information for a vehicle is identified, which information includes a first plurality of vehicle operations occurring during a first plurality of time windows. First values for a plurality of features are extracted from the first plurality of vehicle operations. A portion of the vehicle transportation network is associated with an owner/operator of the vehicle based on the first values. For consecutive time windows thereafter, second values for the features are extracted from second vehicle operating information for the vehicle that includes a second plurality of vehicle operations occurring during the consecutive time windows. Based on changes, a determination can be made as to whether an identity of the person associated with the vehicle has changed over time.

Abstract: A method and apparatus for identifying parking areas may include identifying a plurality of coordinates representing vehicle spatial data, partitioning the plurality of coordinates into at least two groups of vehicle locations based on at least one condition existing when the plurality of coordinates was identified, clustering the vehicle spatial data for a first group of the at least two groups of vehicle locations based on proximity, comparing dimensions of the clustered vehicle spatial data for the first group with other location data within the vehicle transportation network information, and defining a respective location of the clustered vehicle spatial data as a parking area of a plurality of parking areas. Each parking area is associated with a respective location in a vehicle transportation network. The parking area information may be used in the identification of a route from an origin to a primary destination.

Abstract: Automatically identifying associations between vehicle operating data and non-vehicle operating data may include identifying vehicle transportation network data representing a vehicle transportation network, identifying vehicle operating data reported for a plurality of vehicles, wherein the vehicle operating data includes vehicle operation records, identifying non-vehicle operating data reported for a plurality of users, wherein the non-vehicle operating data includes non-vehicle operation records, automatically identifying an association between the vehicle operating data and the non-vehicle operating data, and generating updated vehicle transportation network data based on the vehicle transportation network data.

Abstract: A method and apparatus for associating parking areas with destinations based on automatically identified associations between vehicle operating information and non-vehicle operating information may include a vehicle identifying vehicle transportation network information including a primary destination, such that the vehicle transportation network information includes parking area information, and such that the parking area information includes parking area association information describing an association between at least one parking area from the plurality of parking areas and the primary destination based at least in part on an automatically identified association between vehicle operating information and non-vehicle operating information.

Abstract: A method, a vehicle and a system that identify and use a location significant to a person associated with a vehicle based on vehicle probe data are described. Vehicle transportation network information representing a vehicle transportation network is identified, the vehicle transportation network information including destinations of a vehicle obtained from vehicle probe data. For at least some of the destinations, density-based clustering is performed using temporal data associated with the at least some of the destinations to form at least two spatio-temporal clusters. A contextual label is assigned to a location associated with a first spatio-temporal cluster of the at least two spatial-temporal clusters based on the temporal data associated with the first spatio-temporal cluster, the location being a labeled location, and the labeled location is used for vehicle operation. The labeled location may be used for navigation or service, for example.

Abstract: A method and apparatus for associating a person with a portion of transportation network information based on vehicle operating information are described. The information includes a plurality of destinations. First vehicle operating information for a vehicle is identified, which information includes a first plurality of vehicle operations occurring during a first plurality of time windows. First values for a plurality of features are extracted from the first plurality of vehicle operations. A portion of the vehicle transportation network is associated with an owner/operator of the vehicle based on the first values. For consecutive time windows thereafter, second values for the features are extracted from second vehicle operating information for the vehicle that includes a second plurality of vehicle operations occurring during the consecutive time windows. Based on changes, a determination can be made as to whether an identity of the person associated with the vehicle has changed over time.

Abstract: A method and apparatus for identifying parking areas may include identifying a plurality of coordinates representing vehicle spatial data, partitioning the plurality of coordinates into at least two groups of vehicle locations based on at least one condition existing when the plurality of coordinates was identified, clustering the vehicle spatial data for a first group of the at least two groups of vehicle locations based on proximity, comparing dimensions of the clustered vehicle spatial data for the first group with other location data within the vehicle transportation network information, and defining a respective location of the clustered vehicle spatial data as a parking area of a plurality of parking areas. Each parking area is associated with a respective location in a vehicle transportation network. The parking area information may be used in the identification of a route from an origin to a primary destination.

Abstract: A method and apparatus for associating parking areas with destinations based on automatically identified associations between vehicle operating information and non-vehicle operating information may include a vehicle identifying vehicle transportation network information including a primary destination, such that the vehicle transportation network information includes parking area information, and such that the parking area information includes parking area association information describing an association between at least one parking area from the plurality of parking areas and the primary destination based at least in part on an automatically identified association between vehicle operating information and non-vehicle operating information.