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On Identifying Dynamic Intersections in Large Cities

机译:大型城市动态交叉口的识别

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As the complexity of traffic conditions in large cities increases it becomes important and highly desirable to be able to analyse the spatial and temporal nature of such systems. Due to the heterogeneity of traffic demand and road network topology, it is possible to find "hot spots" in a network that present a challenge for city planning and conventional intersection control methods. This paper presents an approach to identify such places as physical intersections in a traffic network with dynamically changing demand conditions in time and to quantify the level of volatility at those locations. We design a model that is used to simulate commuters path choices using a stochastic routing approach. We perform a case study for the city of Singapore and calibrate our model with national survey data describing the travel habits of the population. The results from our simulation are used to analyse the traffic conditions in the city. We are able to identify and study highly dynamic intersections and observe that such locations in fact exist and contribute to the heterogeneous dynamic profile of the road network.
机译:随着大城市交通状况的复杂性增加,能够分析此类系统的时空特性变得非常重要和迫切需要。由于交通需求和道路网络拓扑的异质性,有可能在网络中找到“热点”,这对城市规划和传统的交叉口控制方法提出了挑战。本文提出了一种方法,该方法可识别具有动态变化的需求条件的交通网络中的物理交叉口等地点,并量化这些地点的波动水平。我们设计了一个模型,该模型用于使用随机路由方法模拟通勤者的路径选择。我们针对新加坡市进行了案例研究,并使用描述了人口出行习惯的国家调查数据来校准我们的模型。我们模拟的结果用于分析城市的交通状况。我们能够识别和研究高度动态的十字路口,并观察到实际上存在这样的位置并有助于道路网络的异质动态轮廓。

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