Adaptive driver following model that integrates perception process and driving behavior

In order to meet the personalized needs of Chinese intelligent vehicles and improve the satisfaction and acceptance of human–computer interaction and collaboration in domestic intelligent vehicles. In this paper, we design an adaptive longitudinal following model that integrates the perceptual perturbation process and driver characteristics for simulating driver following behavior and studying the variability of driver following behavior. Firstly, for the independence and randomness of driver perception process, a set of random variables conforming to Wiener process is introduced to simulate the perception process of speed and following distance of the vehicle in front; secondly, for the characteristic differences of different drivers' following behavior, a driver characteristic parameter identification algorithm is designed to identify the expected collision time distance and following distance parameters of different drivers, and the identified parameters will be used for Again, a sliding mode control system based on fuzzy switching gain adjustment is designed to simulate the driver following control system. The results show that the designed following model recognizes the driver's characteristics well and can better simulate the driver's following behavior, and the following index is relatively improved by 80%.