Qianqian Wang ^1* Shaolin He ² Zhu Zhao ¹

• ¹ Hunan Communication Polytechnic, Changsha, China
• ² State Grid Changsha Power Supply Company, Changsha, China

With the continuous upgrading of automobiles, the concept of intelligent cars has begun to appear in the public eye. People are also closely monitoring the safety driving issues of smart cars. The traditional obstacle avoidance technology has a low accuracy in identifying fuzzy information encountered during high-speed driving. In response to this problem, fuzzy control theory was used to improve the ability of fuzzy information processing. This improves the traditional obstacle avoidance technology and applies obstacle avoidance technology based on fuzzy control theory to intelligent vehicles. A performance comparison experiment was conducted on the improved obstacle avoidance technology. The results showed that the accuracy of the improved obstacle avoidance technology was 96.11%, which was superior to comparison obstacle avoidance technologies. When there was no interference signal, the running time and overshoot were 2.4s and 7%, which was superior to comparison obstacle avoidance technologies. Subsequently, an empirical analysis was conducted on the application effect of improved obstacle avoidance technology in practice. The results showed that its accuracy rate in judging obstacle categories was 94%, which was higher than the control group, and the technology was the best in planning the driving route of intelligent vehicles in the experiment. In summary, the obstacle avoidance technology proposed in the study can improve the recognition ability of intelligent vehicles to fuzzy information and the accuracy of identifying obstacles, thereby providing certain guarantees for the safe driving of intelligent vehicles.