Ford Global Technolgoies, LLC

Arpita Chand

Somak Datta Gupta

Vladyslav Slyusar

Jayanthi Rao

Oliver Lei

Aghapi Mordovanakis

Akhil Perincherry

Subharthi Banerjee

Sutharsan Sivagnanam

Managing vehicle application usage of computing resources is provided. A request for computing resources of a communications network is received from a vehicle application installed to a vehicle. An access point name (APN) is assigned to the vehicle application based on an application identifier corresponding to the vehicle application by accessing stored APN information including a mapping of application identifiers to corresponding APNs. The computing resources are accessed by the vehicle application connecting to the communications network using the APN.

Adaptively selecting network APN for vehicle application remote computing demand

A system includes a plurality of vehicles and at least one first processor in a first vehicle and at least one second processor in each other of the plurality of vehicles. The first vehicle wirelessly receives remote driving commands, from a remote computing system, instructing control of the first vehicle and executes the remote driving commands to control the first vehicle in accordance with the remote driving commands. The first vehicle wirelessly broadcasts the remote driving commands, including a location of the first vehicle where a given of the driving commands was executed. The second vehicle wirelessly receives the broadcast remote driving commands, stores the received remote driving commands in sequence, and executes the given of the driving commands when a location of the second vehicle corresponds to the location of the first vehicle where the given of the driving commands was executed.

Method and apparatus for remote driving a plurality of vehicles in a platoon

An autonomous vehicle may determine that it has an amount of power remaining projected to be needed to reach a recharging point by autonomously traveling with predefined systems disabled. The vehicle may disable the predefined systems and travel towards the recharging point. Subsequent to the disabling, the autonomous vehicle may determine that it no longer has the amount of power remaining projected to be needed to reach the recharging point. The vehicle may then communicate with a server and request assistance. The vehicle may then travel to an instructed rendezvous point with a second autonomous vehicle, the rendezvous received from the server. The two vehicles may then communicate to allow the first vehicle to leverage a capability of the second autonomous vehicle, responsive to the first and second autonomous vehicles being within communication range, allowing the first vehicle to reach the recharging point via the leveraging.

Electric autonomous vehicle ride service assistance

The disclosure generally pertains to systems and methods for providing targeted content to users. In an example method, audio data can be received from a device. Sensor data associated with the device may also be received, and the sensor data may include location data. Upon receiving the audio data, an intent associated with the audio data can be determined. At least one of a product, service, or entity may be determined based on the intent. Content may then be determined based on the sensor data and at least one of the product, service, or entity. The content may be associated with a vehicle. An indication of the content can then be sent to the device.

Systems and methods for providing targeted content to users

Upon identifying image data associated with an object, radar data associated with the object is identified. A semantic point cloud image is generated based on the image data and the radar data. Transformed semantic point cloud image from a perspective of the object is determined with a variational auto-encoder neural network trained to accept the semantic point cloud image of the object and to generate the transformed semantic point cloud image from the perspective of the object. Physical characteristics of the object are determined based on the transformed semantic point cloud image.

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Dearborn, MI, United States of America

Arpita Chand