Transportation costs and greenhouse gas emissions are important indicators of intelligent transportation systems. Effective transport scheduling can reduce transportation cost and environmental damage. This paper proposes a large-scale vehicle coordinated scheduling and merging strategy for large-scale vehicles based on transportation cyber physical systems (TCPS) to minimize transportation costs and carbon emissions. Firstly, a local scheduling strategy is used in combination with the leader vehicle selection algorithm and cluster analysis to construct the vehicle merging set.Then, through the mathematical programming method, the improvement and optimization of vehicle path and speed in each platooning set are realized. Finally, the expandability of the scheduling strategy is proved by the simple processing of emergency situations. Numerical simulation has shown that the method presented in this paper to schedule vehicle can greatly reduce the overall fuel consumption of vehicle fleets in fact compared to the fixed path merging strategy.%运输成本及温室气体的排放是衡量智能交通系统的重要指标, 有效的运输调度可以降低运输成本和环境损害.针对路网中集成环保型货车的运输问题, 本文提出一种基于交通信息物理系统 (Transportation cyber physical system, TCPS) 的大规模车辆协同调度及合并方案, 以最大限度地降低运输成本和碳排放量.首先, 采用局部调度策略, 结合领队车辆选择算法及聚类分析, 构建可合并车辆集合;然后, 通过数学规划方法, 实现每个车队集合中车辆路径与速度的改进优化处理;最后, 通过突发情况的简易处理说明本文调度策略的可扩展性.仿真实验表明, 用本文方法将车辆编组合并成车队行驶, 较固定路径合并策略可显著降低路网中货运车辆的整体油耗.
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