Fuzzy drive expert system for an automobile

Abstract

This paper deals with a fuzzy drive expert system for an auto-cruise car. This system consists of four rule sets such as environment recognition rules, driving control rules, learning-evaluation rules, and management meta-rules. The structure of those rules is hierarchical. The fuzzy drive expert system is structured with live units; the distance extraction and image processing unit, the environment recognition unit, the control unit, the learning-evaluation unit, the I/O unit, the knowledge rule base, and the man-machine interface.

Each unit drives the fuzzy production rules which are described by sentence and symbols based on the if-then type format. Antecedent parts and consequent parts of those rules include the fuzzy words such as big, positive, wide, short, and so on. On the basis of the recognized result of environment, the control unit manipulates the steering and the throttle valve (or fuel injectors, brake pressure) for direction control and speed control of vehicle.

The vehicle drive controls on the straight road and the corner are simulated on the digital computer. The overtaking control, the tracking control, and the avoidance control of obstacles are successful and smoothable.