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Towards Realistic Urban Traffic Experiments Using DFROUTER: Heuristic Validation and Extensions

机译:使用DFROUTER进行逼真的城市交通实验:启发式验证性和扩展性

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摘要

Traffic congestion is an important problem faced by Intelligent Transportation Systems (ITS), requiring models that allow predicting the impact of different solutions on urban traffic flow. Such an approach typically requires the use of simulations, which should be as realistic as possible. However, achieving high degrees of realism can be complex when the actual traffic patterns, defined through an Origin/Destination (O-D) matrix for the vehicles in a city, remain unknown. Thus, the main contribution of this paper is a heuristic for improving traffic congestion modeling. In particular, we propose a procedure that, starting from real induction loop measurements made available by traffic authorities, iteratively refines the output of DFROUTER, which is a module provided by the SUMO (Simulation of Urban MObility) tool. This way, it is able to generate an O-D matrix for traffic that resembles the real traffic distribution and that can be directly imported by SUMO. We apply our technique to the city of Valencia, and we then compare the obtained results against other existing traffic mobility data for the cities of Cologne (Germany) and Bologna (Italy), thereby validating our approach. We also use our technique to determine what degree of congestion is expectable if certain conditions cause additional traffic to circulate in the city, adopting both a uniform pattern and a hotspot-based pattern for traffic injection to demonstrate how to regulate the overall number of vehicles in the city. This study allows evaluating the impact of vehicle flow changes on the overall traffic congestion levels.
机译:交通拥堵是智能交通系统(ITS)面临的一个重要问题,它需要能够预测不同解决方案对城市交通流量影响的模型。这种方法通常需要使用仿真,仿真应该尽可能地切合实际。但是,当通过城市的车辆的起点/终点(O-D)矩阵定义的实际交通模式仍然未知时,实现高度逼真度可能会很复杂。因此,本文的主要贡献是改进交通拥堵建模的启发式方法。特别是,我们提出了一个程序,该程序从交通管理部门提供的实际感应环路测量开始,迭代地完善DFROUTER的输出,DFROUTER是SUMO(城市交通模拟)工具提供的模块。这样,它可以为交通生成类似于真实交通分布的O-D矩阵,并且可以由SUMO直接导入。我们将技术应用于瓦伦西亚市,然后将获得的结果与科隆(德国)和博洛尼亚(意大利)城市的其他现有交通流量数据进行比较,从而验证了我们的方法。我们还使用我们的技术来确定如果某些条件导致城市中额外的交通流通,可预期的拥堵程度,同时采用统一模式和基于热点的模式进行交通注入,以演示如何调节城市中的车辆总数城市。这项研究可以评估车辆流量变化对整体交通拥堵程度的影响。

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