Honda Motor Co., Ltd.

Ting Zhang

Kiyotaka Kawashima

Hidehiro Tsubokura

A vehicle recommendation device and a method for machine learning based recommendation of vehicle is provided. The vehicle recommendation device receives vehicle log data from a plurality of sensors associated with each of a first set of vehicles. The first set of vehicles are classified based on a set of vehicle types. The vehicle recommendation device generates vehicle trip data, associated with a plurality of trips of each of the first set of vehicles, based on the received vehicle log data. The vehicle recommendation device further determines a set of features, associated with the plurality of trips or with information about the first set of vehicles, based on the generated vehicle trip data. The vehicle recommendation device further generates a machine learning model which is trained based on the determined set of features to output a first type of vehicle from the set of vehicle types.

Machine learning based recommendation of vehicle

A system and method for providing point of interest related notifications within a vehicle that include receiving sensor data associated with an opening of at least one vehicle window of the vehicle. The system and method also include storing a first geo-location of the vehicle based on the sensor data and determining if a subsequent geo-location of the vehicle is within a predetermined vicinity of at least one point of interest. The system and method further include providing at least one point of interest related notification associated with the at least one point of interest if it is determined that the subsequent geo-location of the vehicle is within the predetermined vicinity of the at least one point of interest.

System and method for providing point of interest related notifications

A method for identifying prospective purchasers of battery electric vehicles (BEVs) may include defining a predetermined time frame associated with vehicle ownership, receiving a first dataset including a first subset of drivers are drivers who have owned or leased any first internal combustion engine (ICE) vehicle followed by any second ICE vehicle within the predetermined time frame, a second subset of drivers are drivers who have owned or leased any first ICE vehicle followed by any second BEV within the predetermined time frame, and a third subset of drivers are drivers who have not changed vehicles within the predetermined time frame, receiving a second dataset including a set of drivers who own or lease any first ICE vehicle which is in a same vehicle class as a target BEV, and identifying a target set of prospective purchasers of BEVs.

Prospective battery electric vehicle (BEV) buyer analysis

The present disclosure generally relates to methods and systems for determining usage of a vehicle. A vehicle monitoring system may include a memory, at least one processor coupled to the memory, and a sensor system that generates vehicle trip data. The system may periodically determine a location of the vehicle during a trip while an ignition of the vehicle remains on. The system may determine that a duration of the trip is at least a threshold duration. The system may determine a direction of travel for segments between consecutive locations during the trip. The system may determine a ratio of a most common direction of travel for the trip to at least a second most common direction of travel for the trip. The system may determine that the vehicle has been used for commercial purposes in response to the ratio being less than a threshold ratio.

Ride-hailing vehicle identification

A system and method for providing point of interest related notifications within a vehicle that include receiving sensor data associated with an operation of the vehicle or a use of a component of the vehicle. The system and method also include storing a first geo-location of the vehicle based on the sensor data and determining if a subsequent geo-location of the vehicle is within a predetermined vicinity of at least one point of interest. The system and method further include providing at least one point of interest related notification associated with the at least one point of interest if it is determined that the subsequent geo-location of the vehicle is within the predetermined vicinity of the at least one point of interest.

The present disclosure generally relates to methods and systems for determining usage of a vehicle. A vehicle monitoring system may include, a memory, at least one processor coupled to the memory, and a sensory system that generates vehicle trip data during a monitoring window. The vehicle monitoring system may partition the trip data into a base group and a contrast group. The vehicle monitoring system may calculate a similarity score between the contrast group and the base group. The vehicle monitoring system may determine that the vehicle has been used for commercial purposes in response to the similarity score satisfying a threshold.

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Zhejiang, China

Ting Zhang