Dong Luxi, Xie Xiaolan, Lu Jiali, Feng Liangyuan, Zhang Lieping
College of Earth Sciences, Guilin University of Technology, Guangxi Zhuang Autonomous Region, Guilin 541004, China.
College of Computer Science and Engineering, Guilin University of Technology, Guangxi Zhuang Autonomous Region, Guilin 541004, China.
Sensors (Basel). 2024 Mar 13;24(6):1845. doi: 10.3390/s24061845.
To address traffic flow fluctuations caused by changes in traffic signal control schemes on tidal lanes and maintain smooth traffic operations, this paper proposes a method for controlling traffic signal transitions on tidal lanes. Firstly, the proposed method includes designing an intersection overlap phase scheme based on the traffic flow conflict matrix in the tidal lane scenario and a fast and smooth transition method for key intersections based on the flow ratio. The aim of the control is to equalize average queue lengths and minimize average vehicle delays for different flow directions at the intersection. This study also analyses various tidal lane scenarios based on the different opening states of the tidal lanes at related intersections. The transitions of phase offsets are emphasized after a comprehensive analysis of transition time and smoothing characteristics. In addition, this paper proposes a coordinated method for tidal lanes to optimize the phase offset at arterial intersections for smooth and rapid transitions. The method uses Deep Q-Learning, a reinforcement learning algorithm for optimal action selection (OSA), to develop an adaptive traffic signal transition control and enhance its efficiency. Finally, a simulation experiment using a traffic control interface is presented to validate the proposed approach. This study shows that this method leads to smoother and faster traffic signal transitions across different tidal lane scenarios compared to the conventional method. Implementing this solution can benefit intersection groups by reducing traffic delays, improving traffic efficiency, and decreasing air pollution caused by congestion.
为解决潮汐车道交通信号控制方案变化引起的交通流波动问题，维持交通顺畅运行，本文提出一种潮汐车道交通信号转换控制方法。首先，该方法包括基于潮汐车道场景下的交通流冲突矩阵设计交叉口重叠相位方案，以及基于流量比的关键交叉口快速平稳转换方法。控制目标是使交叉口不同流向的平均排队长度相等，并使平均车辆延误最小化。本研究还基于相关交叉口潮汐车道的不同开放状态分析了各种潮汐车道场景。在对转换时间和平滑特性进行综合分析后，重点研究了相位偏移的转换。此外，本文提出一种潮汐车道协调方法，以优化干线交叉口的相位偏移，实现平稳快速转换。该方法使用深度Q学习（一种用于最优动作选择的强化学习算法）来开发自适应交通信号转换控制并提高其效率。最后，通过交通控制接口进行了仿真实验，以验证所提方法。研究表明，与传统方法相比，该方法在不同潮汐车道场景下能实现更平稳、快速的交通信号转换。实施该解决方案可通过减少交通延误、提高交通效率以及降低拥堵造成的空气污染，使交叉口群组受益。
