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Macroscopic traffic model for large scale urban traffic network design

机译:大型城市交通网络设计的宏观交通模型

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摘要

Highlights?A flexible, modular traffic model for large scale urban traffic networks is proposed.?Model parameters can be estimated from measurement data.?Two methods for intersection handling are introduced.?Linear scaling with size allows on-line application.AbstractThis paper presents a flexible macroscopic traffic model that is applicable for large scale urban traffic network simulations. The proposed approach combines several advantages. First, the discretized partial differential equation of the macroscopic model is solved numerically with low computational effort. The spatial and temporal resolution of the discretization are tuning parameters to balance computational effort with model accuracy. Second, the model allows arbitrary functional forms of the fundamental diagram defined by a small number of parameters. Thereby, moving density gradients (jam fronts) are represented accurately. The model parameters are physically meaningful and can readily be estimated from measurement data. Third, two general types of intersection handling are proposed and can be combined with different merge models. The first intersection approach is a binary traffic light, similar to real traffic lights. Detailed insights concerning queue length, flow across intersections and routing decisions can be investigated. The second approach is a continuous valve-like approach that allows investigation of averaged effects and large scale interaction and feedback effects. Fourth, the proposed model scales linearly with spatial and temporal resolution as well as network size and can be partially solved in parallel to increase computational efficiency. To demonstrate the above mentioned qualities of the presented model, two realistic example situations and a comprehensive study on the scaling properties are provided.]]>
机译:<![cdata [ 亮点 提出了一个灵活的,模块化的大型城市交通网络的流量模型。 型号参数可以从测量数据估算。 引入了两种交叉处理方法。 线性缩放,大小允许o n-line应用程序。 抽象 本文提出了一种灵活的宏观流量模型,适用于大规模城市交通网络仿真。所提出的方法结合了几个优点。首先,宏观模型的离散部分微分方程以低计算努力在数值上进行解决。离散化的空间和时间分辨率正在调整参数以通过模型精度平衡计算工作。其次,该模型允许由少量参数定义的基本图的任意功能形式。由此,准确地表示移动密度梯度(堵塞前部)。模型参数物理上有意义,并且可以从测量数据估计。第三,提出了两个一般类型的交叉处理,可以与不同的合并模型组合。第一交叉路口方法是二进制红绿灯,类似于真正的红绿灯。有关队列长度的详细洞察力,可以调查交叉路口和路由决策的流量。第二种方法是一种连续的阀门类似的方法,可以调查平均效应和大规模相互作用和反馈效果。第四,所提出的模型用空间和时间分辨率以及网络尺寸线性缩放,并且可以并行地进行部分解决,以提高计算效率。为了证明所提到的模型的上述品质,提供了两个现实的示例情况和对缩放属性的综合研究。 ]] >

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