US 12,409,841 B2
Systems and methods for updating the parameters of a model predictive controller with learned external parameters generated using simulations and machine learning
Michael Thompson, San Juan Capistrano, CA (US); Carrie Bobier-Tiu, Sunnyvale, CA (US); Manuel Ahumada, San Jose, CA (US); Arjun Bhargava, San Francisco, CA (US); and Avinash Balachandran, Sunnyvale, CA (US)
Assigned to TOYOTA RESEARCH INSTITUTE, INC., Los Altos, CA (US)
Filed by TOYOTA RESEARCH INSTITUTE, INC., Los Altos, CA (US)
Filed on Apr. 12, 2024, as Appl. No. 18/634,715.
Application 18/634,715 is a continuation of application No. 17/165,801, filed on Feb. 2, 2021, granted, now 11,975,725.
Prior Publication US 2024/0270261 A1, Aug. 15, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. B60W 50/00 (2006.01); B60W 30/02 (2012.01); B60W 30/09 (2012.01); B60W 30/10 (2006.01); B60W 40/068 (2012.01); B60W 40/13 (2012.01); B60W 50/14 (2020.01); B60W 60/00 (2020.01); G08G 1/16 (2006.01)
CPC B60W 50/0097 (2013.01) [B60W 30/02 (2013.01); B60W 30/09 (2013.01); B60W 30/10 (2013.01); B60W 40/068 (2013.01); B60W 40/13 (2013.01); B60W 50/14 (2013.01); B60W 60/0015 (2020.02); G08G 1/16 (2013.01); B60W 2040/1315 (2013.01); B60W 2555/20 (2020.02)] 19 Claims
OG exemplary drawing
 
1. A computer implemented method for determining optimal operational parameters for a model predictive controller for controlling a vehicle, the method comprising:
determining a value for an operational parameter amongst a range of potential values of the operational parameter based on:
simulating a vehicle operation across the range of potential values of the operational parameter by determining any change of a command lateral force to satisfy a level of stability of the vehicle; and
determining an output based on a result for the simulated vehicle operation, the output corresponding to the value for the operational parameter; and
training a machine learning vehicle performance circuit based on the output.