Management Method of Autonomous Vehicles and Pedestrians at Intersections Based on Maximum Pressure Controls

doi:10.12141/j.issn.1000-565X.220489

Abstract

Abstract:

In order to improve the management level of autonomous vehicles and pedestrians at intersections, and thus improve the operational efficiency and stability of traffic flow, the paper constructed a management method for autonomous vehicles and pedestrians at intersections based on maximum pressure control and autonomous vehicle trajectory planning methods. Firstly, the queue length of pedestrians was modeled by the probability distribution function and comprehensively considering the influence of arrival rate, crosswalk length and width, waiting time and arrival distribution on pedestrians. Based on the estimated pedestrian queue length, the maximum pressure control was adopted to develop a queuing length management method for autonomous vehicles and pedestrians at intersections. Then, in order to help the internal autonomous vehicles at the intersection avoid collisions and obtain the best movement trajectory, the maximum pressure control method and the trajectory planning method of the existing intersection were planned on the basis of controlling the queue length of the self-driving vehicles and pedestrians at the intersection. Finally, Python and SUMO, which is an open source traffic simulation software, were used to verify the model. The simulation lasts for 2 hours. The simulation results show that the proposed autonomous car and pedestrian management method can not only control the trajectory of autonomous vehicles, but also quickly stabilize and reduce their delay and queuing lengths, and improve the efficiency of intersection operation.

Key words: autonomous vehicle, pedestrian, maximum pressure control, trajectory planning, management method

CLC Number:

U491.4

CAO Ningbo, ZHAO Liying. Management Method of Autonomous Vehicles and Pedestrians at Intersections Based on Maximum Pressure Controls[J]. Journal of South China University of Technology(Natural Science Edition), 2024, 52(2): 124-135.

Figures/Tables 7

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