An Anthropomimetic Approach to High Performance Traction Control

Paladyn: Journal of Behavioral Robotics

Southward Steve C.¹  Kirchner William² 

[1] Associate Professor, Department of Mechanical Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA;Graduate Research Assistant, Department of Mechanical Engineering;

关键词: traction control;    anthropomimetic;    vehicle dynamics;    human in the loop;    adaptive control;   

DOI  :  10.2478/s13230-011-0013-9

来源: DOAJ

【 摘 要 】

The ability to learn and adapt to changing environmental conditions, as well as develop perceptive models based on stimulus-response data, provides expert human drivers with significant advantages. When it comes to bandwidth, accuracy, and repeatability, automatic control systems have clear advantages over humans; however, most high performance control systems lack many of the unique abilities of a human expert. This paper documents our first step toward the development of a novel automatic traction control algorithm using an anthropomimetic approach. The primary objective of this approach was to synthesize a high performance longitudinal traction control system by incorporating desirable human behavior distilled from human-in-the-loop (HIL) testing on a 6-DOF driving simulator. The proposed control algorithm was developed in a general framework, and applied to the specific task of longitudinal traction control. Simulation results confirm that the proposed anthropomimetic traction control algorithm provides improved performance relative to a well-tuned conventional PID-based traction control algorithm. Results are also compared with the HIL response data from a behavioral study.

【 授权许可】

Unknown