Effects of the number of reasoning rules for the lane-keeping controller using a similarity-type fuzzy reasoning method

Abstract

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, we investigated the optimal control rules for calculating similarity. We try to implement the lane-keeping controller using the similarity-type fuzzy reasoning method, and this control rule has been succeeded to improve the running behavior.