Nissan North America, Inc.

Gregory D Dibb

Siddharth Thakur

Masahide Nakamura

GianLuca Storti

Daisuke Saito

Gian Luca Storti

Mumtaz Vauhkonen

A tire tread wear system may include one or more vehicle sensors and a processor. The processor may include a control module, a geometrical model, a machine learning model, and a switch. The geometrical model may be configured to collect data from the vehicle sensors to determine a dynamic rolling radius of a tire. The geometrical model may be configured to output a tread wear estimation based on the dynamic rolling radius of the tire. The machine learning model may be configured to collect data from the vehicle sensors. The machine learning model may be configured to output a tread wear estimation based on a correlation of the tread wear estimation output from the geometrical model and one or more data instances with a tire tread state. The switch may be configured to activate the geometrical model, the machine learning model, or a combination thereof.

Tire wear estimation using a hybrid machine learning system and method

Methods, apparatuses, systems, and non-transitory computer readable storage media for providing on-demand services to vehicles are described. The disclosed technology determines information associated with a vehicle, generates a request for a fuel delivery on-demand service using the information, confirms identification of the vehicle using a wireless signal of the vehicle, provides access to the vehicle to enable performance of the fuel delivery on-demand service and secures the vehicle after completion of the fuel delivery on-demand service.

Vehicle sensing and access control for on-demand services

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

Methods, apparatuses, systems, and non-transitory computer readable storage media for providing on-demand services to vehicles are described. The disclosed technology determines information associated with the vehicle. The information includes a location of the vehicle. A request is generated for the on-demand service using the information and identification of the vehicle is confirmed using a wireless signal of the vehicle. Access is provided to the vehicle to enable performance of the on-demand service and the vehicle is secured after completion of the on-demand service.

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Mountain View, CA, United States of America

Gregory D Dibb