Intelligent vehicle obstacle avoidance strategy application supported by fuzzy control theory

Introduction With the continuous progress of the automotive industry, the safe driving of intelligent vehicles has received increasing attention. Traditional obstacle avoidance techniques are not accurate enough in dealing with fuzzy information encountered in high-speed driving. Therefore, this study aims to improve the obstacle avoidance ability of intelligent vehicles through fuzzy control theory. Methods The study employs fuzzy control theory to enhance the ability of intelligent vehicles to process fuzzy information, thereby improving conventional obstacle avoidance techniques. A combination of visual sensing and ultrasonic detection equipment was used to comprehensively plan the real-time obstacle avoidance routes of the intelligent vehicle. Results and Discussion The improved obstacle avoidance technique achieves an accuracy of 96.11%, which is better than the comparison avoidance technique. In the absence of interfering signals, the running time and overshoot were 2.4 s and 7%, respectively, again superior to the comparison technique. The experimental results show that the obstacle avoidance technique proposed in this study can improve the recognition ability of intelligent vehicles on fuzzy information, so as to improve the accuracy of obstacle recognition and provide certain guarantee for the safe driving of intelligent vehicles.