多路口自组织交通信号灯
Self-organizing traffic lights at multiple-street intersections
摘要：
摘要：交通信号灯协调是一个复杂的问题。在本文中，我们扩展了以前的工作，城市交通的抽象模型，允许多个街道交叉口。我们在我们的模型中测试了自组织方法，表明它接近理论最优值，优于传统的交通灯协调方法。翻译后摘要：基本的元胞自动机规则184可以模仿粒子在一个方向上以恒定的速度流动。因此，该自动机可以模拟高速公路交通。在最近的一篇论文中，我们已经将交通灯控制的十字路口纳入到这个模型中，只使用初等元胞自动机。然而，在这样的论文中，我们只研究了矩形网格。我们现在将我们的模型扩展到采用六边形网格的更复杂的场景。这种扩展首先表明，我们的模型可以很容易地将多路交叉口，从而模拟复杂的情况。此外，目前的扩展允许我们研究和评估两种不同类型的交通灯控制器的行为，用于六路街道网格，允许两个或三个街道交叉口：一个试图适应交通量的交通灯（这导致自组织交通灯）和具有协调刚性周期的同步交通灯系统（有时称为“绿波”方法）。我们观察到系统容量和拓扑复杂性之间的权衡。绿波方法无法应对更高容量场景的复杂性，而自组织方法是可扩展的，适应场景的复杂性并利用其最大容量。此外，在本文中，我们提出了一个基准，独立的方法和模型，来衡量一个交通灯控制器的性能比较它对理论上的最佳。
英文摘要：
Summary: Traffic light coordination is a complex problem. In this paper, we extend previous work on an abstract model of city traffic to allow for multiple street intersections. We test a self-organizing method in our model, showing that it is close to theoretical optima and superior to a traditional method of traffic light coordination. Abstract: The elementary cellular automaton following rule 184 can mimic particles flowing in one direction at a constant speed. This automaton can therefore model highway traffic. In a recent paper, we have incorporated intersections regulated by traffic lights to this model using exclusively elementary cellular automata. In such a paper, however, we only explored a rectangular grid. We now extend our model to more complex scenarios employing an hexagonal grid. This extension shows first that our model can readily incorporate multiple-way intersections and hence simulate complex scenarios. In addition, the current extension allows us to study and evaluate the behavior of two different kinds of traffic light controller for a grid of six-way streets allowing for either two or three street intersections: a traffic light that tries to adapt to the amount of traffic (which results in self-organizing traffic lights) and a system of synchronized traffic lights with coordinated rigid periods (sometimes called the "green wave" method). We observe a tradeoff between system capacity and topological complexity. The green wave method is unable to cope with the complexity of a higher-capacity scenario, while the self-organizing method is scalable, adapting to the complexity of a scenario and exploiting its maximum capacity. Additionally, in this paper we propose a benchmark, independent of methods and models, to measure the performance of a traffic light controller comparing it against a theoretical optimum.
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