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9 April 2024 Research on obstacle avoidance path planning method for unmanned vehicles
Dapeng Liu, Fei Gao, Qiuhong Tong, Haidong Su, Long Pan, Shengjun Su, Daifang Hu
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Proceedings Volume 12989, Third International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2023); 1298906 (2024) https://doi.org/10.1117/12.3023968
Event: Third International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2023), 2023, Xi'an, China
Abstract
To address the significant impact of different driving paths on vehicle safety and comfort during the driving process of autonomous vehicles, a polynomial function based obstacle avoidance path planning method is proposed. Using the vehicle states at the starting and ending points of the path as boundary conditions, the obstacle avoidance path equation is derived based on polynomial curves. The LQR lateral control algorithm and dual PID longitudinal control algorithm were used to verify the planned path on a real vehicle. The results of the real vehicle test showed that the obstacle avoidance path planning method based on polynomial function has good executable performance, safety, and comfort.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Dapeng Liu, Fei Gao, Qiuhong Tong, Haidong Su, Long Pan, Shengjun Su, and Daifang Hu "Research on obstacle avoidance path planning method for unmanned vehicles", Proc. SPIE 12989, Third International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2023), 1298906 (9 April 2024); https://doi.org/10.1117/12.3023968
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KEYWORDS
Autonomous vehicles
Unmanned vehicles
Safety
Autonomous driving
Boundary conditions
Interpolation
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