Gm Global Technolgoy Operations, Inc.

Doordash, Inc.

Lawrence Oliver Ryan

Usman Ghani

Tobenna Arodigobu

A remote vehicle control system includes a vehicle mounted sensor system including a video camera system for producing video data and a distance mapping sensor system for producing distance map data. A data handling system is used to compress and transmit both the video and distance map data over a cellular network using feed forward correction. A virtual control system acts to receive the video and distance map data, while providing a user with a live video stream supported by distance map data. Based on user actions, control instructions can be sent to the vehicle mounted sensor system and the remote vehicle over the cellular network.

Virtual vehicle control system

Systems and method are provided for controlling a vehicle. In one embodiment, an object classification method includes receiving sensor data associated with an object observed by a sensor system of an autonomous vehicle and determining, with a processor, a bounding curve associated with the sensor data. A plurality of bounding curve features are determined based on a set of convexities and concavities associated with the bounding curve. The object is classified by applying the plurality of bounding curve features to a machine learning model and receiving a classification output.

Systems and methods for object classification in autonomous vehicles

Systems and method are provided for controlling a vehicle. In one embodiment, a vehicle dimension prediction method includes producing a set of simulated observed dimensions based a set of known vehicle dimensions and training a machine learning module based on the set of simulated observed dimensions and the set of known vehicle dimensions. The method further includes acquiring sensor data associated with a first vehicle observed by a sensor system of an autonomous vehicle, determining observed dimensions of the first vehicle based on the acquired sensor data, and determining, with a processor, predicted actual dimensions of the first vehicle by applying the plurality of observed dimensions to the machine learning model.

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Menlo Park, CA, United States of America

Lawrence Oliver Ryan