一个反队列网络模型用于交叉点的交通信号控制,考虑到动态随机环境中的拥堵传播
Bin Zhao1,2,3,4, Yanni Ju2, Shengyang Jiao5
1Sichuan Vocational and Technical College of Communications, Chengdu, Sichuan, China.
PloS one
|December 2, 2025
概括
本研究引入了一种新的反流体排队网络模型,用于在过度和条件下管理交通拥堵的传播. 开发的模型和滚动优化策略显著降低了平均车辆延迟和总成本,优于现有方法.
科学领域:
- 交通工程是交通工程.
- 运营研究 运营研究
- 排队理论 排队理论
背景情况:
- 在动态随机环境中的交叉点上交通拥堵的传播,特别是在过度和的条件下,带来了重大挑战.
- 现有的模型往往难以准确地捕捉随机流量需求和时间变化的网络动态的复杂性.
研究的目的:
- 开发一个强大的反流体排队网络模型,用于分析拥堵传播和延迟.
- 为交通信号控制建立优化框架,旨在最大限度地减少车辆延迟和总成本.
- 为动态交通管理实施实时滚动优化策略.
主要方法:
- 一个反流体队列网络模型,集成随机流量需求,时间变化的过渡概率和状态依赖的服务功能.
- 一个用于分析队列网络的递归算法.
- 一个滚动优化策略,使用网格自适应直接搜索算法来控制交通信号.
主要成果:
- 拟议的模型和算法在不同的交通强度中表现出有效性,平均绝对 (0.5152辆) 和相对 (6.43%) 误差较低.
- 确定了滚动优化的最佳中等时间步骤,以最大限度地减少延迟和成本.
- 与Synchro软件相比,该方法在特定条件下实现了高达70%的延迟减少.
结论:
- 反流体排队网络模型为了解和管理交通拥堵提供了一种有效的方法.
- 滚动优化战略为交通信号控制提供了显著的改进,减少了车辆延迟和运营成本.
- 结果强调了最佳时间步骤选择的重要性,并证明了在城市交通管理中大幅提高效率的潜力.
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