Modeling and Control Using Stochastic Distribution Control Theory for Intersection Traffic Flow
Modeling and Control Using Stochastic Distribution Control Theory for Intersection Traffic Flow
复制标题
交叉口交通流随机分布控制理论的建模与控制
DOI：
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
S. Young
中科院分区：
文献类型：
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作者：
Hong Wang;Sagar V. Patil;H. M. A. Aziz;S. Young
这项工作研究了基于随机分布控制理论的交通信号优化，以实现车辆通过信号交叉口的平稳和均匀流动。在此背景下，开发了静态和线性动态随机分布模型来表达信号配时与交通队列长度之间的关系及其概率密度函数。设计了两种随机分布控制算法来控制交叉口的信号配时，使得每个交叉口路段的交通队列的概率密度函数尽可能窄和小。此外，还提出了一种递归输入输出交通队列估计模型，该模型本质上是数据驱动的和动态的，以使用交通信号计时和环路检测器数据来计算实时交通队列长度。针对单信号走廊、双信号走廊和 $2 ime 2$ 信号交叉口网络评估了控制算法。提供了 MATLAB 仿真示例来演示所提出算法的使用，并与现有广泛使用的半驱动控制进行了比较。获得了期望的结果。
This work investigated stochastic distribution control theory-based traffic signal optimization to achieve a smooth and uniform flow of vehicles through signalized intersections. In this context, the static and linear dynamic stochastic distribution models were developed to express the relationship between the signal timing and the traffic queue length together with its probability density function. Two stochastic distribution control algorithms were designed to control the signal timing at intersections such that the probability density function of the traffic queue of each intersection road segment is made as narrow and as small as possible. Also, a recursive input-output traffic queue estimation model was proposed, which is data-driven and dynamic in nature, to calculate real-time traffic queue length using traffic signal timings and loop-detector data. The control algorithms were evaluated for a one-signal corridor, two-signal corridor, and $2 imes 2$ network of signalized intersections. MATLAB simulation examples are provided to demonstrate the use of the proposed algorithms and comparison to the existing widely-used semi-actuated control has been made. Desired results were obtained.