The Car-Following and Lane-Changing Collision Prevention System Based on the Cascaded Fuzzy Inference System

Abstract

A new design for the collision prevention system based on cascaded fuzzy inference system (CFIS) for lane-changing maneuver and car-following is proposed. The lane-changing is combined with car-following to save the processing time of the lane-changing maneuver. The distance and speed relative to the vehicle in front or in target adjacent lane are measured by the spread spectrum radars and applied to the collision prevention system. The output acceleration or deceleration rate obtained from the CFIS collision prevention system is based on the characteristics of the vehicles. Monte Carlo simulations were conducted to demonstrate that the CFIS collision prevention system could provide a safe, reasonable, and comfortable drive for car-following and lane-changing. The system characteristics for car-following, lane-changing, and emergency braking are verified.