【作者】 王磊；

【导师】 李思杰；

【作者基本信息】 上海工程技术大学 ， 交通运输（专业学位）， 2023， 硕士

【摘要】 随着城市化进程的加快,城市居民的出行需求日益增长,城市轨道交通凭借其安全、高效、绿色等特点在各大城市迅速扩张。在城市轨道交通网络化发展的同时也伴随着各类问题的产生,如自然灾害、设施设备故障、人为因素等造成的列车延误甚至中断使得城市轨道交通服务水平和运输能力降低,进一步影响乘客的乘车体验、出行效率甚至危及运营安全。列车运行调整是缓解列车运行延误的关键,如何在保证安全运营的前提下,采取有效的运行调整策略以尽快恢复列车的正常运行,并将列车运行延误对乘客的综合影响降至最低,是目前轨道交通运营企业面临的关键问题,具有重要的理论意义和实际应用价值。本文创新地将韧性理论用于突发事件下城市轨道交通线路服务水平的衡量,并面向韧性提升开展列车运行调整策略及客流管控策略的优化。主要包含以下四个方面的内容:(1)总结了韧性理论的发展进程,剖析韧性与其他系统性能概念间的区别与联系,并分析了常用的韧性定量计算方式;围绕列车延误问题,具体阐释了延误产生的原因、分类、传播机制、影响及调整策略等相关理论。(2)提出了城市轨道交通线路韧性的定义,基于韧性曲线开展韧性的量化研究,设计了基于列车与乘客交互时空网络图的韧性定量指标。基于韧性演化过程,进行不同延误场景下的列车运行调整仿真与韧性评估,验证了韧性指标的有效性。(3)研究了面向韧性提升的列车运行调整优化问题。面向受延误影响的不同列车,结合扣车、跳停、赶点等调整策略,以计划与实际时刻表偏差和乘客总候车时间最小化为目标,以列车到发时间、追踪间隔时间、区间运行时间、停站时间、停站方案、乘客与列车的匹配关系为约束条件,构建了基于组合策略的列车运行调整非线性混合整数规划模型,对模型进行线性化处理后调用求解器GUROBI进行求解。以上海地铁某线路为对象进行案例研究验证了模型的有效性和可行性,所得最优策略有助于乘客服务韧性的提升。(4)研究了面向韧性提升的列车运行调整与客流管控协同优化问题。面向随机客流需求场景,分析了韧性视角下的客流管控策略。基于此,结合扣车、赶点、客流管控方案,以计划与实际时刻表偏差和乘客总候车时间最小化为目标,考虑列车到发时间、追踪间隔时间、区间运行时间、停站时间等为列车调整约束,以列车载客能力、客流流量平衡等为乘客出行约束,建立了延误条件下列车运行调整与鲁棒客流管控协同优化模型,对模型进行线性化处理后调用求解器GUROBI求解。以上海地铁某线路为对象进行案例研究,通过多方案结果对比验证了鲁棒客流管控措施的有效性和的必要性,所得优化方案有助于乘客服务韧性的提升。更多还原

【Abstract】 With the acceleration of urbanization,the travel demand of urban residents is growing day by day.Urban rail transit is expanding rapidly in major cities by virtue of its safety,efficiency and green characteristics.The development of urban rail transit network is accompanied by various problems,such as train delays and even interruptions caused by natural disasters,equipment failures and human factors,which reduce the service level and transportation capacity of urban rail transit,further affecting passengers’ride experience,travel efficiency and even compromise operation safety.Train operation adjustment is the key to alleviate train operation delay.However,how to adopt effective operation adjustment strategy to restore train operation as soon as possible and minimize the comprehensive impact of train operation delay on passengers on the premise of ensuring safe operation is the key issue for rail transit operating enterprises at present,which has important theoretical significance and practical application value.In this thesis,the resilience theory is innovatively applied to measure the service level of urban rail transit lines under emergencies,and the optimization of train operation adjustment strategy and passenger flow control strategy is carried out for the improvement of resilience.It mainly includes the following four aspects:(1)This thesis summarized the evolution process of resilence theory,analyzed the difference and connection between resilience and other system performance concepts,and analyzed the commonly used quantitative calculation methods of resilience.Around the problem of train delay,the thesis explains the cause of delay,classification,transmission mechanism,influence,adjustment strategy and other relevant theories.(2)This thesis put forward the definition of resilience of urban rail transit lines.The quantitative research of resilience was carried out based on the resilience curve,and the quantitative index of resilience was designed based on the time-space network diagram of the interaction between trains and passengers.Based on the evolution process of resilience,simulation of train operation adjustment and resilience assessment under different delay scenarios were carried out to verify the effectiveness of the toughness index.(3)This thesis studied train operation adjustment and optimization for resilience improvement.For different trains affected by delays,combined with adjustment strategies such as detainment,skip-stop and accelerated run,the model takes the deviation between the planned and actual timetable and the total waiting time of passengers as the minimized goal,and takes the train arrival and departure time,tracking interval time,and section running time,stop time,stop plan as constraint conditions around trains,and take the matching relationship between passengers and trains as constraint conditions around passengers.A nonlinear mixed integer programming model for train operation adjustment based on combined strategies was constructed.After linearization,the model was solved using the solver GUROBI.The effectiveness and feasibility of the model was verified by taking a line of Shanghai Metro as a research example.The optimal strategy obtained is helpful to improve the resilience of passenger service.(4)This thesis studied the collaborative optimization problem of train operation adjustment and passenger flow control for toughness improvement.Based on the random passenger flow demand scenario,the passenger flow control strategy is analyzed from the perspective of resilience.Based on this,combined with detainment,accelerated run and passenger flow control schemes and so on,aiming to minimize the deviation between planned and actual schedule and total passenger waiting time,taking train arrival and departure time,tracking interval time,section running time and stop time as train adjustment constraints,and taking passenger carrying capacity and passenger flow balance as passenger travel constraints,a collaborative optimization model of train operation adjustment and robust passenger flow control under delayed conditions was established.The model was linearized and solved by a solver GUROBI.Taking a line of Shanghai Metro as the object of the case study,the effectiveness and necessity of robust passenger flow control measures were verified by comparing the results of multiple schemes.The optimized scheme is conducive to improve the resilience of passenger service.更多还原