An ANFIS controller for the car-following collision prevention system

This paper presents a controller based on an adaptive network fuzzy inferen ce system (ANFIS) for the car-following collision prevention system to nonl inearly control the speed of the vehicle. The distance and speed relative t o the car in front are measured by a radar sensor and applied to the contro ller. The output acceleration or deceleration rate of the controller is bas ed on the characteristics of the vehicles. The initial input and output mem bership functions and 25 rules of ANFIS are constructed by a fuzzy inferenc e system (FIS). The design method of the reference Signals, which is used t o on-line update the consequent parameters of ANFIS according to recursive least square (RLS) algorithm, are proposed. The presented ANFIS controller can solve the problems of the oscillations for final distance between the l eading vehicle (LV) and the following vehicle (FV) and relative speed. The required processing time to achieve safe distance between the LV and the FV is about 7-8s, which is faster than the other models. The ANFIS controller of the car-following collision prevention system proposed in this paper ca n provide a safe, reasonable, and comfortable drive.