Pull-over site selection

Patent metadata

Field	Value
Publication number	US-2023339509-A1
Application number	US-202217725602-A
Country	US
Kind code	A1
Filing date	Apr 21, 2022
Priority date	Apr 21, 2022
Publication date	Oct 26, 2023
Grant date	—

Abstract

Techniques and mechanisms for pull-over site selection for an autonomous vehicle. Simulation information is received from an external source. The simulation information corresponds to multiple simulations involving a virtual autonomous vehicle and available pull-over locations for the virtual autonomous vehicle. An indication to cause the autonomous vehicle to search for a pull-over location is received. Potential pull-over locations are analyzed in response to the indication. The potential pull-over locations are compared to simulated pull-over locations to identify a selected pull-over location. The autonomous vehicle navigates the selected pull-over location. The autonomous vehicle stops at the selected pull-over location.

First claim

What is claimed is:

1 . An autonomous vehicle comprising:
sensor systems to detect characteristics of an operating environment; kinematic control systems to provide kinematic controls to the autonomous vehicle; a vehicle control system coupled with the sensor systems and with the kinematic control systems, the vehicle control system to:
receive simulation information from an external source, wherein the simulation information corresponds to multiple simulations involving a virtual autonomous vehicle and available pull-over locations for the virtual autonomous vehicle;
receive an indication to cause the autonomous vehicle to search for a pull-over location;
analyze potential pull-over locations in response to the indication;
compare the potential pull-over locations to simulated pull-over locations to identify a selected pull-over location;
cause the autonomous vehicle to navigate to the selected pull-over location; and
cause the autonomous vehicle to stop at the selected pull-over location.

2 . The autonomous vehicle of claim 1 wherein the vehicle control system is further configured to:
collect operational information for selection and use of the pull-over location; and
transmitting the collected operational information to a repository for use in subsequent simulations.

3 . The autonomous vehicle of claim 1 wherein comparing the potential pull-over locations to simulated pull-over locations to identify a selected pull-over location further comprises:
utilizing weight values received as part of the simulation information in an artificial neural network (ANN) to compare the potential pull-over locations to simulated pull-over locations;
utilizing output values from the artificial neural network to identify the selected pull-over location; and
provide identifying information corresponding to the selected pull-over location to the vehicle control system.

4 . The autonomous vehicle of claim 1 wherein the simulation comprises a reinforcement learning (RL) based simulation.

5 . The autonomous vehicle of claim 1 wherein the pull-over location is for a passenger of the autonomous vehicle is disembark the autonomous vehicle.

6 . The autonomous vehicle of claim 1 wherein the pull-over location is for the autonomous vehicle to accept a passenger.

7 . A non-transitory computer-readable medium having stored thereon instructions that, when executed by one or more processors, are configurable to cause the processors to:
receive simulation information from an external source, wherein the simulation information corresponds to multiple simulations involving a virtual autonomous vehicle and available pull-over locations for the virtual autonomous vehicle; receive an indication to cause the autonomous vehicle to search for a pull-over location; analyze potential pull-over locations in response to the indication; compare the potential pull-over locations to simulated pull-over locations to identify a selected pull-over location; cause the autonomous vehicle to navigate to the selected pull-over location; and cause the autonomous vehicle to stop at the selected pull-over location.

8 . The non-transitory computer-readable medium of claim 7 wherein the one or more hardware processors are further configured to:
collect operational information for selection and use of the pull-over location; and
transmitting the collected operational information to a repository for use in subsequent simulations.

9 . The non-transitory computer-readable medium of claim 7 wherein comparing the potential pull-over locations to simulated pull-over locations to identify a selected pull-over location further comprises:
utilizing weight values received as part of the simulation information in an artificial neural network (ANN) to compare the potential pull-over locations to simulated pull-over locations;
utilizing output values from the artificial neural network to identify the selected pull-over location; and
provide identifying information corresponding to the selected pull-over location to a vehicle control system of the autonomous vehicle.

10 . The non-transitory computer-readable medium of claim 7 wherein the simulation comprises a reinforcement learning (RL) based simulation.

11 . The non-transitory computer-readable medium of claim 7 wherein the pull-over location is for a passenger of the autonomous vehicle is disembark the autonomous vehicle.

12 . The non-transitory computer-readable medium of claim 7 wherein the pull-over location is for the autonomous vehicle to accept a passenger.

13 . An autonomous vehicle control system comprising:
a memory system; and one or more hardware processors coupled with the memory system, the one or more processors to:
receive simulation information from an external source, wherein the simulation information corresponds to multiple simulations involving a virtual autonomous vehicle and available pull-over locations for the virtual autonomous vehicle;
receive an indication to cause the autonomous vehicle to search for a pull-over location;
analyze potential pull-over locations in response to the indication;
compare the potential pull-over locations to simulated pull-over locations to identify a selected pull-over location;
cause the autonomous vehicle to navigate to the selected pull-over location; and
cause the autonomous vehicle to stop at the selected pull-over location.

14 . The autonomous vehicle control system of claim 13 wherein the one or more hardware processors are further configured to:
collect operational information for selection and use of the pull-over location; and
transmitting the collected operational information to a repository for use in subsequent simulations.

15 . The autonomous vehicle control system of claim 13 wherein comparing the potential pull-over locations to simulated pull-over locations to identify a selected pull-over location further comprises:
utilizing weight values received as part of the simulation information in an artificial neural network (ANN) to compare the potential pull-over locations to simulated pull-over locations;
utilizing output values from the artificial neural network to identify the selected pull-over location; and
provide identifying information corresponding to the selected pull-over location to a vehicle control system of the autonomous vehicle.

16 . The autonomous vehicle control system of claim 13 wherein the simulation comprises a reinforcement learning (RL) based simulation.

17 . The autonomous vehicle control system of claim 13 wherein the pull-over location is for a passenger of the autonomous vehicle is disembark the autonomous vehicle.

18 . The autonomous vehicle control system of claim 13 wherein the pull-over location is for the autonomous vehicle to accept a passenger.

Assignees

• Gm Cruise Holdings Llc

Inventors

• Allan Jeremy
• Malaran Adrian Kit
• Rangaswamy Vivek Nagraj
• Hertzberg Alexander Dean
• Aadne Folkestad Carl Axel
• Tang Allen

Classifications

• B60W60/00253 Primary

  Taxi operations · CPC title

• G07C5/008

  communicating information to a remotely located station (transmission systems for measured values G08C) · CPC title

• G06F30/27 Primary

  using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model · CPC title

• B60W2556/45

  External transmission of data to or from the vehicle · CPC title