Development and validation of the lane-keeping controller using a similarity-type fuzzy reasoning method

This paper proposes the Similarity-type Fuzzy Reasoning method based on the calculated overlap coefficient of sensor rules and sensor input data for a lane-keeping controller. Fuzzy control reasoned by a membership function and human-adjusted rules. Those are required to improve the control performance. In this paper, instead of using the membership function, the inference result was calculated by the similarity of the rules and the input data. We try to implement the lanekeeping controller using the similarity-type fuzzy reasoning method, and this method has been succeeded to develop new advance two-stage fuzzy control.