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Combining Static and Dynamic Models for Traffic Signal Optimization Inherent Load-dependent Travel Times in a Cyclically Time-expanded Network Model

机译:在循环时间扩展的网络模型中,将静态和动态模型相结合来优化交通信号固有的与负载相关的行驶时间

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Travel times in traffic models are of great interest for developing realistic solutions for traffic assignment and traffic signal coordination in urban traffic networks. In this paper, we present a cyclically time-expanded network for this purpose, which is a static and linear model from its structure. However, it provides enough dynamics to reproduce load-dependent travel times and it is capable to model traffic signals. Thus, this traffic flow model is at the cutting-edge of static and dynamic models, and furthermore, it allows the simultaneous optimization of traffic assignment and signal coordination with exact mathematical programming techniques. We study the inherent properties of the travel times in this model and demonstrate its capabilities by simulation results obtained with state-of-the-art simulation tools.
机译:交通模型中的旅行时间对于开发现实的城市交通网络中交通分配和交通信号协调解决方案非常重要。在本文中,我们为此目的提供了一个周期性的时间扩展网络,从其结构来看,这是一个静态和线性的模型。但是,它提供了足够的动力来重现依赖于负载的行驶时间,并且能够对交通信号进行建模。因此,该交通流模型处于静态和动态模型的最前沿,此外,它还允许使用精确的数学编程技术同时优化交通分配和信号协调。我们研究此模型中旅行时间的固有属性,并通过使用最新的仿真工具获得的仿真结果来证明其功能。

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