人工智能辅助的城市轨道交通列车运行智能调节方法

Fei An Fei An, Xiu-Juan Chang Fei An, Ya-Ping Liu Xiu-Juan Chang, Bin He Ya-Ping Liu, Dong-Mei Guo Bin He, Yan-Xiang Yao Dong-Mei Guo, Ze Chang Yan-Xiang Yao
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引用次数: 0

摘要

城际轨道交通的运营极大地缓解了城市交通压力。为了提高运营质量和乘客承载能力,城市轨道交通调度策略需要根据客流等干扰因素,特别是疫情爆发带来的交通控制问题,及时进行调整。本文根据疫情和早晚客流高峰的特点,设计了以旅客出行成本和城轨运营公司日常成本最小为目标的优化模型。通过强化学习算法找到模型的最优解。最后,以石家庄地铁的运行参数为基础,通过仿真得到了最优的列车调度方案,验证了本文研究方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial Intelligence Assisted Intelligent Adjustment Method for Urban Rail Transit Train Operation
The operation of intercity rail transit has greatly relieved the pressure of urban traffic. In order to improve the operation quality and passenger carrying capacity, the scheduling strategy of urban rail needs to be timely adjusted according to the passenger flow and other disturbing factors, especially the traffic control problems brought by the outbreak of the epidemic. In this paper, according to the epidemic situation and the characteristics of peak passenger flow in the morning and evening, an optimization model is designed to minimize the travel cost of passengers and the daily cost of the urban rail operation company. The optimal solution of the model is found through the reinforcement learning algorithm. Finally, based on the parameters of Shijiazhuang Metro, the optimal train scheduling scheme is obtained through simulation, which verifies the effectiveness of the research method in this paper.  
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