Research on a data driven vehicle obstacle avoidance control model

Yuancheng Zhao; Zhongyou Huang

doi:10.1117/12.2646746

7 September 2022 Research on a data driven vehicle obstacle avoidance control model

Yuancheng Zhao, Zhongyou Huang

Proceedings Volume 12329, Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022); 123290T (2022) https://doi.org/10.1117/12.2646746
Event: Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022), 2022, Changsha, China

Abstract

In order to shorten the identification time of vehicle to obstacles and realize the real-time control of vehicle obstacle avoidance, a new method of vehicle obstacle avoidance control based on big data and real-time modeling was proposed. Using real-time modeling technology, a database containing a large number of driving data under different conditions is regarded as the mathematical model of the system, and the gain and control time of the control input are calculated by extracting the data, so as to avoid obstacles. The numerical analysis shows that the method eliminates the complicated mathematical model and only needs simple arithmetic operation and sorting to realize the real-time control, which has the advantage of short computation time. Compared with the previous control method, the new control method can avoid various obstacles more effectively.

Citation Download Citation

Yuancheng Zhao and Zhongyou Huang "Research on a data driven vehicle obstacle avoidance control model", Proc. SPIE 12329, Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022), 123290T (7 September 2022); https://doi.org/10.1117/12.2646746

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