Fuzzy Longitudinal Controller Design and Experimentation for Adaptive Cruise Control and Stop&Go

This paper presents a fuzzy longitudinal control system with car-following speed ranging from 0 to 120 km/h, thereby achieving the main functions of both adaptive cruise control (ACC) and Stop&Go control. A fuzzy longitudinal controller is synthesized by inputting the difference of the actual relative distance and the safe distance obtained from the preceding vehicle, and the relative speed, and then outputting the pulse-width-modulation (PWM) signal to control the output forces of the vacuum boosters. With the use of the high-level controller from dSPACE, the fuzzy control law is easily and rapidly implemented using Matlab/Simulink for the experimental car, and the controller's parameters can be changed and updated by analyzing data based on the relative distance using Lidar, the speed of the host vehicle, the opening of the throttle and the position of the braking pedal. For the sake of safe driving, experimental results are conducted by simulating the various possible car-following conditions for the ACC and Stop&Go controllers, thereby obtaining virtually relative distances and speeds to tune the controller's parameters and ensure the safety of the controller. Several car following experiments are conducted to show that the proposed fuzzy longitudinal controller is capable of achieving the requirements of comfort and safety, and giving a satisfactory performance at high and low speed conditions.