基于多控制模式的网联车辆信号交叉口通行策略研究

doi:10.3976/j.issn.1002-4026.2025008

Abstract

Abstract: To address the efficiency loss caused by traffic congestion and frequent vehicle stops at signalized intersections, in this study we propose an intersection passing strategy based on multiple control modes. The interactions between vehicles and traffic signals as well as vehicle-to-vehicle interactions are analyzed, and six control modes are developed based on variations in traffic flow, signal cycles, and vehicle behavior. The strategy is dynamically adjusted to real-time traffic conditions. To minimize the impact of abrupt acceleration changes, the concept of vehicle jerk is introduced, and a straight-line trajectory model is developed accordingly. In addition, considering the collision-avoidance constraints of preceding vehicles, a polynomial method is used to construct an optimized lane-changing trajectory model to enhance the lane-changing efficiency. A comparative analysis of four control strategies demonstrates that the proposed multi-mode control strategy reduces delay times by 18.93% and 25.79% under low- and high-traffic flow conditions, respectively, compared to traditional strategies. Furthermore, by analyzing the displacement, speed, and acceleration curves of vehicles during travel, vehicle passing time is reduced by 2.6 to 23.52 s under different control modes, confirming the effectiveness of the proposed strategy in improving intersection traffic efficiency.

Key words: intelligent transportation system, connected and automated vehicles, signalized intersection, trajectory planning, multiple control modes

CLC Number:

U495

ZHANG Huixin, TANG Shaozhi, GU Ming, ZHOU Wenshuai, LIU Bin. Intersection crossing strategy for connected and automated vehicles based on multiple control modes[J].Shandong Science, 0, (): 1-.

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Intersection crossing strategy for connected and automated vehicles based on multiple control modes

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