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Environmentally friendly traffic control strategy - A case study in Xi'an city

机译:环保交通控制策略-以西安市为例

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Given the increasing painful repercussions of air pollution caused by massive vehicular emissions and the unsustainable development of transport sectors, the integration of traffic models with emission estimation models has been investigated in depth to evaluate the performance of the pre-determined environment-friendly transportation policies. Nevertheless, there is a lack of the optimization approach to design the traffic control strategy combining the coupled models. Therefore, an optimization framework is developed to optimize the traffic control strategies to mitigate the vehicular emissions in the considered network. The proposed framework integrates a macroscopic analytical traffic model with a macroscopic emissions estimation model to account for the vehicle emissions, and then genetic algorithm (GA) is employed to minimize vehicle emissions. A congested urban area in Xi'an city that consists of two signalized intersections is selected for a case study. The performance of the signal plans derived by the proposed framework is compared with the currently in use signal plans via the microscopic simulator AIMSUN. It indicates that the proposed traffic control scheme reduces expected vehicle trip travel time and vehicle emissions of four sorts of pollutants for the considered area. This optimization framework helps traffic operators to design environment-friendly traffic signal control strategy. (C) 2019 Elsevier Ltd. All rights reserved.
机译:鉴于大规模的车辆排放和交通运输部门的不可持续发展造成的空气污染日益严重的后果,已经对交通模型与排放估算模型的集成进行了深入研究,以评估预定的环境友好型交通政策的绩效。然而,缺乏优化的方法来设计结合了耦合模型的交通控制策略。因此,开发了优化框架以优化交通控制策略以减轻所考虑的网络中的车辆排放。所提出的框架将宏观分析交通模型与宏观排放估计模型集成在一起,以解决车辆排放问题,然后采用遗传算法(GA)来最大限度地减少车辆排放。案例研究选择了一个由两个信号交叉口组成的西安城市拥挤区域。通过显微镜模拟器AIMSUN,将由所提出的框架得出的信号计划的性能与当前正在使用的信号计划进行比较。它表明,拟议的交通控制方案减少了所考虑区域的预期车辆出行时间和四种污染物的车辆排放。该优化框架可帮助交通运营商设计环境友好型交通信号控制策略。 (C)2019 Elsevier Ltd.保留所有权利。

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