A Medium-Scale Network Model for Short-Term Traffic Prediction at Neighbourhood Level

D. Giglio
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引用次数: 2

Abstract

A macroscopic model for predicting the evolution of traffic on medium-scale networks is proposed in this paper. The model takes into consideration the flows of vehicles which move from some origins to some destinations, and it is based on the LWR discrete-time/discrete-space vehicle conservation equation, which leads to quite simple models that can be employed within optimization and control schemes, aimed at regulating traffic and mitigating congestions at neighbourhood level. In the proposed model, vehicles are not constrained to stay in a link for at least one time interval, as they are allowed to enter a link and exit from it within the same interval. This feature requires a particular property (upstream dependence) of the digraph which represents the traffic network, in any case, a modified version of the dynamic model is also proposed in the paper, in order to deal with complex networks which do not have such a property.
邻域短期交通预测的中尺度网络模型
本文提出了一个预测中等规模网络流量演化的宏观模型。该模型考虑了车辆从某些起点移动到某些目的地的流量,并且它基于LWR离散时间/离散空间车辆守恒方程,这导致可以在优化和控制方案中使用非常简单的模型,旨在调节交通和缓解邻里水平的拥堵。在提出的模型中,车辆不被限制至少在一个时间间隔内停留,因为它们被允许在同一时间间隔内进入和退出一个路段。这一特征要求交通网络的有向图具有特定的属性(上游依赖),在任何情况下,本文还提出了一种改进的动态模型,以便处理不具有这种属性的复杂网络。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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