<p>The emergence of driverless cars brings convenience to people’s travel. However, their obstacle avoidance ability during driving is closely related to the occurrence of safety accidents. Therefore, this study proposed using a time elastic band for local path planning design to improve the safety and reliability of driverless cars during operation. Firstly, a planning model was constructed using time elastic band, followed by setting and solving constraints on the model. Experimental simulation showed that in the planned path under a single obstacle and multiple obstacles, the vehicle’s driving speed and angular velocity curves had overall persistence and good smoothness. Compared with other algorithms, the driving time in the simulation was reduced by 17.73%. The average speed was increased by 0.46&#xa0;s. The proposed path planning method fully considered local path sequences, reducing the time cost in the planned parking path by 44.84% compared to other algorithms. The parking position was more in line with the target position. The TEB algorithm was significantly superior in terms of accuracy and success rate of obstacle avoidance compared to the existing methods. Therefore, using time elastic band for local path planning of driverless cars has ideal reliability and stability. Meanwhile, the obstacle avoidance performance of driverless cars based on the algorithm is better.</p>