An Anthropomimetic Approach to High Performance Traction Control

• Main Authors: Kirchner William, Southward Steve C.
• Format: Article
• Language: English
• Published: De Gruyter 2011-03-01
• Series: Paladyn: Journal of Behavioral Robotics
• Subjects: traction control; anthropomimetic; vehicle dynamics; human in the loop; adaptive control
• Online Access: https://doi.org/10.2478/s13230-011-0013-9

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.