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Optimisation of recommended speed profile for train operation based on ant colony algorithm

机译:基于蚁群算法的列车运行推荐速度曲线优化

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摘要

An automatic train operation (ATO) system generally consists of the generation of recommended speed profile and the speed tracking strategy. It determines the tracked trajectory and the energy consumption of trains during the trip. Therefore, the optimisation of recommended speed profile and the ATO tracking strategy are regarded as two important means to achieve energy-efficient train operation between the successive stations. By considering the ATO tracking strategy, an optimisation method of the recommended speed profile is proposed in this paper. Based on the approximate calculation, a discrete combination optimisation model is formulated and a modified max-min ant system (MMAS) is taken as the core algorithm. With the integration speed tracking strategy, this method achieves the recommended speed profile with optimised energy consumption and a perfect running punctuality along the actual tracked trajectory. The computation time of the algorithm is shorter and the switching time of operation during the cruising phase is reduced by integrating the drivers' experience, which also reduces the energy consumption of train running between stations. The simulation results of a case study based on Beijing Subway verify the effectiveness of the proposed method, which has a good performance on energy-efficient train operation.
机译:火车自动运行(ATO)系统通常由推荐速度曲线的生成和速度跟踪策略组成。它确定了行驶过程中的跟踪轨迹和火车的能耗。因此,推荐速度曲线的优化和ATO跟踪策略被视为实现连续站点之间的节能列车运行的两个重要手段。通过考虑ATO跟踪策略,提出了推荐速度曲线的优化方法。在近似计算的基础上,建立了离散组合优化模型,并以改进的最大最小二乘系统为核心算法。通过集成速度跟踪策略,该方法可实现建议的速度曲线,并具有优化的能耗和沿实际跟踪轨迹的完美运行守时性。通过结合驾驶员的经验,算法的计算时间更短,巡航阶段的操作切换时间减少,这也减少了车站之间列车运行的能耗。以北京地铁为例的仿真结果验证了该方法的有效性,在高能效列车运行中具有良好的性能。

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