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A fuzzy obstacle avoidance controller is designed for an autonomous vehicle. The controller is given the capability for obstacle avoidance by using negative fuzzy rules in conjunction with traditional positive ones. Negative fuzzy rules prescribe actions to be avoided rather than performed. A rule base of positive rules is specified by an expert for directing the vehicle to the target in the absence of obstacles, while a rule base of negative rules is experimentally determined from expert operation of the vehicle in the presence of obstacles. The consequents of the negative-rule system are codified into a chromosome, and this chromosome is evolved using an evolutionary algorithm. The resulting fuzzy system has far fewer rules than would be necessary for an obstacle avoidance controller using purely positive rules, while in addition retaining greater interpretability.