Gm Global Technolgoy Operations, Inc.

Beijing Institute of Technology

The University of Waterloo

Yechen Qin

Amir Khajepour

Ehsan Hashemi

Amin Habibnejad Korayem

SeyedAlireza Kasaiezadeh Mahabadi

Qingrong Zhao

Joseph K Moore

Mansoor Alghooneh

Christopher J Mettrick

Yiwei Huang

Zhenfeng Wang

Gregory P Kakert

A universal machine learning based system for estimating a vehicle state of a vehicle includes one or more controllers executing instructions to receive a plurality of dynamic variables and corresponding historical data. The controllers execute a sensitivity analysis algorithm to determine a sensitivity level for each dynamic variable and corresponding historical data and select two or more pertinent dynamic variables based on the sensitivity level of each dynamic variable and the corresponding historical data. The controllers standardize the two or more pertinent dynamic variables into a plurality of generic dynamic variables, wherein the plurality of generic dynamic variables are in a standardized format that is applicable to any configuration of vehicle, and estimate the vehicle state based on the plurality of generic dynamic variables by one or more machine learning algorithms.

Universal machine learning based system for estimating a vehicle state

A method for determining a tire tread wear estimation of a tire includes receiving, by a controller, a direct tire tread wear measurement, when available, performing an indirect tire tread wear estimation, performing a data fusion of the indirect tire tread wear estimation with the direct tire tread wear measurement when available, estimating a percentage tire life remaining and a mileage to end of tire life, and estimating a refined tire tread wear calibration coefficient for performing future indirect tire tread wear estimations.

Systems and methods for estimating tire wear

The present disclosure relates to a method and system for integrated path planning and path tracking control of an autonomous vehicle. The method includes: obtaining five input control variables and eleven system state variables of an autonomous vehicle at current time; constructing a vehicle path planning-tracking integrated state model according to the obtained variables at the current time; enveloping external contours of two autonomous vehicles using elliptical envelope curves to determine elliptical vehicle envelope curves of the two autonomous vehicles, respectively; determining time to collision (TTC) between the vehicles according to elliptical vehicle envelope curves and vehicle driving states; establishing an objective function of a model prediction controller (MPC) according to the model; and solving the objective function based on the TTC, and determining input control variables to the MPC at the next time. Autonomous vehicle collision avoidance can be achieved according to the present disclosure.

Method and system for integrated path planning and path tracking control of autonomous vehicle

Growing community of inventors

Beijing, China

Yechen Qin