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Performance evaluation of an Adaptive Route Change application using an integrated cooperative ITS simulation platform

机译:使用集成的协作ITS仿真平台的自适应路径变更应用程序的性能评估

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In this paper we present simulation results for our implementation of Adaptive Route Change (ARC) application for cooperative Intelligent Transportation Systems (ITS). The general purpose of the application is to generate recommendations for alternative driving routes in order to avoid traffic congestion. The Adaptive Route Change (ARC) application is implemented in an integrated cooperative ITS simulation platform. For the evaluation we chose a reference scenario defining two distinct traffic flows through an urban area that provides four crossings with traffic light controls. We were interested to evaluate the impacts of ARC on fuel and traffic efficiency. For that we introduced five performance metrics (average trip duration, average fuel consumption, average stop duration, maximum queue size and average queue size behind traffic lights) and evaluated ARC in a series of simulations with varied application penetration rates and traffic volume. The results indicate that ARC systems could reduce traffic congestion in intersections and improve fuel consumption. We observe up to one quarter reduction in average trip time and almost one third reduction in average stop time. Fuel consumption is also reduced by up to 17.3%, while average queue size and maximum queue size reduce more than 50%.
机译:在本文中,我们为合作智能交通系统(ITS)的自适应路线变更(ARC)应用实现提供了仿真结果。该应用程序的一般目的是为替代驾驶路线生成建议,以避免交通拥堵。自适应路由更改(ARC)应用程序在集成的协作ITS仿真平台中实现。为了进行评估,我们选择了一个参考场景,该场景定义了通过市区的两个截然不同的交通流,该市区提供了四个具有交通信号灯控制的交叉口。我们有兴趣评估ARC对燃油和交通效率的影响。为此,我们引入了五个性能指标(平均行程持续时间,平均燃油消耗,平均停车持续时间,最大队列大小和交通信号灯后面的平均队列大小),并在一系列具有不同应用程序渗透率和流量的模拟中评估了ARC。结果表明,ARC系统可以减少交叉路口的交通拥堵并提高燃油消耗。我们观察到平均旅行时间减少了多达四分之一,而平均停车时间减少了近三分之一。燃油消耗也减少了17.3%,而平均队列大小和最大队列大小减少了50%以上。

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