Signalized and Unsignalized Road Traffic Intersection Models: A Comprehensive Benchmark Analysis

Ibrahima Ba, A. Tordeux
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Abstract

Road traffic flow models allow the development and testing of intelligent transportation solutions. Macroscopic intersection models are especially relevant for the simulation of large traffic networks. In this article, we study four first-order signalized and unsignalized intersection models. The two unsignalized approaches are the first-in-first-out (FIFO) model (roundabout-type intersection) and an optimal non-FIFO model (highway-type intersection). The optimal control operates upstream for the first signalized intersection model. It occurs downstream for the second signalized model. All four models satisfy the expected physical constraints of vehicle conservation, traffic demand, and assignment. The models are minimal and allow a comprehensible analysis of the results. We determine mathematical relationships between the intersection models and empirically analyze the performances using Monte Carlo simulations. The numerical simulations assume random demand, supply, and assignment. Besides average performances, the approach accounts for the flow ranges of variation. A benchmark analysis compares the intersection models. We observe that the optimal signalized intersection models overcome the performances of the FIFO model in congested states. They may even reach the performances of the idealistic non-FIFO model. Further applications for the four intersection models are discussed.
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信号灯和非信号灯道路交通交叉口模型:综合基准分析
道路交通流模型有助于开发和测试智能交通解决方案。宏观交叉口模型对于大型交通网络的模拟尤为重要。本文研究了四种一阶信号灯和非信号灯交叉口模型。两个无信号交叉口模型分别是先进先出(FIFO)模型(迂回型交叉口)和非先进先出优化模型(高速公路型交叉口)。在第一个信号灯路口模型中,优化控制在上游运行。第二个信号灯路口模型的最优控制在下游进行。所有四个模型都满足车辆保护、交通需求和分配等预期物理约束条件。这些模型都是最小的,可以对结果进行可理解的分析。我们确定了交叉口模型之间的数学关系,并通过蒙特卡罗模拟对其性能进行了经验分析。数值模拟假设需求、供应和分配是随机的。除了平均性能,该方法还考虑了流量的变化范围。基准分析对交叉口模型进行了比较。我们发现,最佳信号交叉口模型在拥堵状态下的性能优于先进先出模型。它们甚至可以达到理想化的非先进先出模型的性能。我们还讨论了四种交叉口模型的进一步应用。
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