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23 August 2024 Research on lane-changing decision-making model for autonomous driving cars based on game theory
Xingkui Shen, Yu Yu, Weiling Wang
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Proceedings Volume 13250, Fourth International Conference on Image Processing and Intelligent Control (IPIC 2024); 1325025 (2024) https://doi.org/10.1117/12.3038590
Event: Fourth International Conference on Image Processing and Intelligent Control (IPIC 2024), 2024, Kuala Lumpur, Malaysia
Abstract
In order to ensure the safe lane changing of self-driving vehicles and at the same time improve the efficiency of vehicle traffic, a game theory-based vehicle lane changing decision model is proposed. Firstly, the interaction behavior and game relationship between vehicles are analyzed. Then the safety gain, comfort gain and speed gain are established as the game gain function, and the vehicle driving conditions in the NGSIM dataset are clustered and analyzed using Gaussian mixture model (GMM), which divides the driver styles into three categories. The anthropomorphism of the vehicle lane change decision model is improved by considering the effects of different driving styles on the vehicle lane change decision. Finally, SUMO software is used to build a hybrid scenario of human-driven vehicles and self-driven vehicles to compare and analyze with the MOBIL lane change model. The results show that the lane-changing game decision-making model in this paper has higher safety and traffic efficiency.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Xingkui Shen, Yu Yu, and Weiling Wang "Research on lane-changing decision-making model for autonomous driving cars based on game theory", Proc. SPIE 13250, Fourth International Conference on Image Processing and Intelligent Control (IPIC 2024), 1325025 (23 August 2024); https://doi.org/10.1117/12.3038590
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KEYWORDS
Autonomous vehicles
Safety
Decision making
Roads
Data modeling
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