Nissan North America, Inc.

Nissan Motor Company Limited

Keio University

Daisuke Saito

Siddharth Thakur

Naoki Kojo

Toshiro Muramatsu

Nikhil Lele

Nicolas F Meuleau

Hirofumi Inoue

Mauro Della Penna

Tetsurou Ueda

Michio Ohkubo

Kunihiro Noda

Vikram Krishnamurthy

Hideki Aizawa

Tomohiro Takagi

Tetsuhiko Isobe

Gregory D Dibb

Ryo Asakura

An information processing device includes an input configured to input a starting position, a destination and searching conditions, and processing circuitry configured to transmit the starting position, the destination and the searching conditions, acquire a route and a charging station for a vehicle propelled by a motor and a battery which are generated from travelling history information acquired from plurality of vehicles according to the starting position, the destination and the searching conditions, and information on the searching conditions, and perform control to display the acquired route and the charging station together with the information on searching condition on a screen.

Information provision device

A parking lot mapping system includes a server. The server is remote from a plurality of vehicles, and includes a receiver, an electronic controller and a storage device. The receiver is configured to receive data transmitted from the vehicles, the data including a route traveled and a stopping position of each of the vehicles. The electronic controller is configured to determine that each vehicle has entered a parking lot, and form a map of the parking lot including parking lot routes and parking spots based on accumulation of the data including the stopping position of each vehicle and the route traveled by each of the vehicles after determination that each vehicle vehicles has entered the parking lot. The storage device is configured to store the map of the parking lot.

Parking lot mapping system

Service requests are transmitted to multiple vehicles, each request associated with a time and a location. Driving histories of vehicles are known. A first location associated with a service request is compared with a known location in a vehicle driving history. The known location comprises a first cell identifier of a first grid where a size of the cells indicates a maximum acceptable deviation of the vehicle from a travel segment in the driving history that includes the first cell identifier. When the first location matches the known location and the associated time overlaps a start or end time of the travel segment that includes the first cell identifier, the 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.

Incentivized group shipping system

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.

Automatically identifying associations between vehicle operating data and non-vehicle operating data

A method of monitoring usage of a charging station includes collecting probe data from a plurality of electric vehicles. The probe data includes charging activity history. A usage value associated with a charging station is determined based on the collected probe data. The usage value associated with the charging station is provided to a requesting electric vehicle.

System and method of monitoring usage of a charging station

A parking lot mapping system includes a receiver, a storage device and a controller. The receiver is configured to receive data transmitted from a plurality of vehicles, the data including a parking event and a position of each vehicle of the plurality of vehicles. The storage device is configured to store the data received by the receiver. The controller is programmed to determine that each vehicle of the plurality of vehicles is in a parking lot based on the parking event and to calculate a parking lot route based on accumulation of the data including the position of each vehicle of the plurality of vehicles.

A vehicle information providing device has a history information accumulation unit configured to sequentially acquire at least one of driving location information, power consumption information and charging facility information from an in-vehicle device of a vehicle having at least an electric motor as a traveling drive source and accumulate the at least one information as driving history information, an input unit configured to input at least a departure point and a destination point, a planned route acquisition unit configured to acquire a planned route from the departure point to the destination point, and a map memory configured to store a control map in which a route of section and a characteristic value are associated with each other on a basis of the driving history information accumulated in the history information accumulation unit.

Vehicle information providing device

A method and apparatus for autonomous vehicle routing and navigation using passenger docking locations are disclosed. Autonomous vehicle routing and navigation using passenger docking locations may include an autonomous vehicle identifying map information representing a vehicle transportation network, the vehicle transportation network including a primary destination and a docking location, wherein identifying the map information includes identifying the map information such that the map information includes docking location information representing the docking location. The autonomous vehicle may identify the docking location as a target docking location for the primary destination based on the map information, generate, based on the map information, route information representing a route for the autonomous vehicle to traverse the vehicle transportation network from an origin in the vehicle transportation network to the target docking location, and traverse the vehicle transportation network from the origin to the target docking location in accordance with the route information.

Autonomous vehicle routing and navigation using passenger docking locations

An information provision device has a history information storage part configured to sequentially acquire at least one of traveling location information, power consumption information and charging location information from an in-vehicle device mounted on a vehicle including an electric motor as a driving source for storing as traveling history information, a planned route acquisition part configured to acquire a planned route from a starting position to a destination, a provided route determination part configured to refer to the traveling history information stored in the history information storage part and determine a provided route that is as same as or similar to the planned route acquired by the planned route acquisition part from traveling routes along which the vehicle traveled, and a provided information determination part.

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.

Pattern detection using probe data

A vehicle information providing device provides route information to vehicles. The vehicle information providing device has a history information accumulation unit that sequentially acquires at least one of driving location information, power consumption information and charging location information from vehicle-mounted devices of a plurality of vehicle, and stores as driving history information. A presentation route is determined by extracting the stored driving history information. The stored driving history information is referenced to determine a route travelled from the departure-point range to the target-point range, from among the routes travelled by the vehicle as the presentation route. Also, the vehicle information providing device alters the search conditions and the search is performed again, when there are no routes traveling from the departure location range to the destination range within a predetermined range.

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.

Spatial clustering of vehicle probe data

A method and apparatus for passenger docking location selection are disclosed. Passenger docking location selection may include an autonomous vehicle identifying transportation network information representing a vehicle transportation network, the vehicle transportation network including a primary destination, wherein identifying the transportation network information includes identifying the transportation network information such that it includes docking location information representing a plurality of docking locations, wherein each docking location corresponds with a respective location in the vehicle transportation network, and such that at least one docking location is associated with the primary destination, determining a target docking location for the primary destination based on the transportation network information and pedestrian travel time, identifying a first route from an origin to the target docking location in the vehicle transportation network using the transportation network information, and traveling from the origin to the target docking location using the first route.

Passenger docking location selection

A system and method of predicting future demand of a charging station include collecting probe data from a plurality of electric vehicles. The probe data includes charging activity history of the plurality of electric vehicles. A usage pattern of a charging station is determined based on the probe data for the charging station. A future demand for the charging station is predicted by applying the usage pattern to a factor associated with a requesting electric vehicle. The predicted future demand for the charging station is provided to the requesting electric vehicle.

System and method of predicting future demand of a charging station

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. The vehicle may determine a target parking area from the plurality of parking areas for the primary destination based on the vehicle transportation network information, and identify a route from an origin to the target parking area in the vehicle transportation network using the vehicle transportation network information.

Associating parking areas with destinations based on automatically identified associations between vehicle operating information and non-vehicle operating information

Growing community of inventors

Sunnyvale, CA, United States of America

Daisuke Saito