城市轨道交通ZC故障场景下列车运行全过程调整方法
刘循1楚彭子1,2
Adjustment Method for Urban Rail Transit Train Operation Entire Process in ZC Fault Scenarios
LIU XunCHU Pengzi
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作者信息:1.上海申通地铁集团有限公司技术中心， 201103， 上海
2.同济大学电子与信息工程学院， 201804， 上海
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Affiliation:Technology Center of Shanghai Shentong Metro Group Co., Ltd., 201103, Shanghai, China
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关键词:
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Key words:
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DOI:10.16037/j.1007-869x.2023.08.003
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中图分类号/CLCN:U292.4
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栏目/Col:学术专论
摘要:
目的：当城市轨道交通发生控车设备故障时，会导致列车不同程度的运行延误，需及时调整列车运行方案，降低对运营的不利影响。以对运营影响较大的ZC(区域控制器)故障场景为示例，研究论证列车运行全过程调整方法的可行性、实效性。方法：综合考虑列车运行安全限制因素、车站停站时间要求，以及列车正常运行和限速运行条件下的速度控制策略等，构建以列车总延误时间最小为目标的非线性规划模型，并结合问题特征设计相应的启发式算法。结果及结论：将ZC故障场景对列车运行速度、运行间隔控制等的影响纳入模型与算法，可得与多类控车约束条件相符的列车运行全过程调整方案。算例应用结果显示，所提出的启发式算法能够在毫秒级求得近似最优方案，且总晚点列次、终到站最大晚点时间和终到站总晚点时间三项统计指标与数学规划求解器Gurobi求解结果十分接近，耗时仅为该规划器的0387%。提出的针对ZC故障场景下的列车运行全过程调整方法可实时响应应急调整决策需求，高效协调图定列车运行，达到减少列车延误时间与总晚点列次目的。
Abstracts:
Objective: When a control equipment failure occurs in urban rail transit, it can lead to varying degrees of train delays. It is necessary to promptly adjust the train operation plans to minimize the adverse impact on the operation. ZC (zone controller) fault scenarios that impact operation significantly are taken as example, the feasibility and effectiveness of an adjustment method for train OEP (operation entire process) is researched and discussed.Method: By considering factors such as train operation safety constraints, station dwell time requirements, speed control strategies for normal and restricted speed conditions, a nonlinear programming model is constructed with the objective of minimizing the total train delay time, and corresponding heuristic algorithms are designed by referring to the problem characteristics.Result & Conclusion: By incorporating the impact of ZC fault scenarios on train operating speed and operating interval control into the model and algorithms, an adjustment plan for train OEP that satisfies various types of train control constraints can be obtained. The application results of the investigated example show that the proposed heuristic algorithm can achieve the nearoptimal solutions in milliseconds, and the statistical indicators such as total delayed trains, maximum delay time at terminal station, and total delay time at terminal station are very close to the results obtained by the mathematical programming solver Gurobi, taking only 0.387% of the solver time. The proposed adjustment method for train OEP in ZC fault scenarios can respond to emergency adjustment decisionmaking needs in real time, thus effectively coordinating the scheduled train operation while fulfilling the purposes of reducing train delay time and total delayed trains.
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