Ford Global Technolgoies, LLC

Rashmi Hegde

Ahmad Khalifeh

Sandro Nuesch

Beni Tang

Mathew Alan Boesch

Scott J Lauffer

Ray C Siciak

Anthony Tsakiris

Kathryn Hamilton

Ahsan Qamar

Sagar Avaneendra Tatipamula

Amy Beth Cronin

Anita Stoffer

Systems and methods are provided herein for managing scooter fleets based on geolocation boundaries. In certain embodiments, individual scooters of the scooter fleet may be associated with geographical areas in which they are allowed to operate, and such areas may be defined by a geolocation boundary. The geographical areas may be provided to prevent scooters from being used and subsequently left in an undesirable location (for example, at an airport terminal or an area where crime is commonplace).

Systems and methods for managing a scooter fleet based on geolocation

A system includes means for identifying a risk condition based on a diagnostic trouble code (DTC) and an operating condition in a vehicle, means for determining an instruction for the vehicle based on the identified risk condition, and means for navigating the vehicle based on the instruction.

Vehicle diagnostic operation

A vehicle computer includes a memory and a processor programmed to execute instructions stored in the memory. The instructions include receiving a first minimum risk condition (MRC) event recommendation from a first platform controller and a second MRC event recommendation from a second platform controller, selecting one of the first and second MRC event recommendations as a selected MRC event, controlling an autonomous host vehicle according to the selected MRC event.

Decentralized minimum risk condition vehicle control

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Royal Oak, MI, United States of America

Rashmi Hegde