Collision Avoidance Strategy for Self-Driving Vehicles Based on Drivers and Environmental Factors. Issue 1 (1st April 2022) - Zhao, Yibing; Li, Bin; Xiang, Xiumei; Guo, Lie
Abstract: In order to enhance the driving safety, various driving assistant systems are gradually developed and widely used. Based on the safe distance model related to the braking process, one warning/dangerous critical distance model for longitudinal control is proposed in this paper, considering the driver's style and environment factors. The variable driver response time is obtained by employing fuzzy control theory. The author then establishes the vehicle dynamics model and its inverse model. Through the relative distance error and relative speed error, the upper controller is designed to obtain the expected acceleration based on sliding mode control, and the lower controller based on PID control is designed to track the acceleration. In order to solve the chattering problem of sliding mode controller, the author proposes variable gain coefficient control method. The fixed gain parameter in the expected acceleration formula is related to the negative exponential correlation formula, which can effectively depress the chattering of the expected acceleration. Finally, the author uses CarSim and Simulink to establish a co-simulation model of the collision avoidance warning system, and designs the test simulation conditions for typical traffic test scenarios to verify the control algorithm effectiveness.