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| Research on Decision-making Method for Autonomous Driving Behavior of Connected and Automated Vehicle |
| XU Zezhou1,2, QU Dayi1,2, HONG Jiale2, SONG Xiaochen2
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1. Institute of Urban Transportation, Qingdao 266071;
2. Qingdao University of Technology, Qingdao 266520,China |
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Abstract Aiming at the problem of direct conflict between autonomous vehicles and other human-driven vehicles at intersections, an autonomous vehicle behavior decision model is built, and deep reinforcement learning is used to train autonomous vehicles when passing road intersections, allowing autonomous vehicles to make autonomous decisions and achieve fast control of complex scenarios,and the comparison with the non-dominated sorting genetic algorithm-Ⅱ verifies the stability of the autonomous vehicle.The simulation results show that the autonomous vehicle beha-vior decision-making method using the depth deterministic strategy gradient algorithm has better output speed to ensure the smooth changes of the throttle and brake values, and effectively solve the safety and comfort problems of autonomous vehicles.
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Received: 06 February 2021
Published: 18 June 2021
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