交通运输系统工程与信息

交通运输系统工程与信息 ›› 2021, Vol. 21 ›› Issue (1): 101-107.

• 系统工程理论与方法 • 上一篇    下一篇

北京地铁双超列车运行图编制方法

宿帅1a，刘旭2，王学楷1a，唐涛1a，曹源*1b   

  1. 1. 北京交通大学，a. 轨道交通控制与安全国家重点实验室，b. 电子信息工程学院，北京 100044； 2. 北京地铁运营有限公司，北京 100044
  • 收稿日期:2020-10-30 修回日期:2020-11-27 出版日期:2021-02-25 发布日期:2021-02-25
  • 作者简介:宿帅(1987- )，男，北京人，副教授，博士。
  • 基金资助:

    国家重点研发计划/National Key Research and Development Program of China(SQ2020YFB1600702)；轨道交通控制与安全国家重点实验室(北京交通大学)自主研究课题/Independent Research Program of National Key Laboratory of Rail Traffic Control and Safety(RCS2020ZZ004)。

Determining Special Train Timetable in Epidemics for Beijing Metro

SU Shuai1a, LIU Xu2, WANG Xue-kai1a, TANG Tao1a, CAO Yuan*1b   

  1. 1a. State Key Laboratory of Rail Traffic Control and Safety, 1b. School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China; 2. Beijing Metro Operation Co. Ltd, Beijing 100044, China
  • Received:2020-10-30 Revised:2020-11-27 Online:2021-02-25 Published:2021-02-25

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摘要：

为研究疫情期间北京地铁“超常”条件下的“超强”运行图编制方法，根据“双超”运行图编制流程提出一种面向车厢低满载率的双层规划优化模型。上层模型基于客流的时空分布规律优化列车的开行方案；下层模型优化列车运行图中全周转运行时分，停站时分，运行时分，折返时分等要素。双层规划模型转化为线性模型并用CPLEX软件通过迭代算法求解“双超”运行图优化问题。基于亦庄线数据对优化编制方法的有效性进行验证。在车底全部投入运营的条件下，优化后早高峰上行、下行最大列车满载率分别降低了21.1%和16.6%；晚高峰上行、下行最大列车满载率分别降低了23.2%和32.3%。本文方法为疫情下城轨运输体系提供了良好地支撑。

关键词: 智能交通, 列车运行图, 混合整数规划, 城市轨道交通, 重大疫情, 满载率

Abstract:

This paper presents the designing method of the special train timetable with high demands under unusual conditions like epidemics. Considering the designing process of the special train timetable, this paper proposes a bilevel programming optimization model to reduce vehicle's loading rate with high demand. The upper model optimizes the operation plan based on the distribution characteristics of passenger flow in time and space. The lower model optimizes the parameters of train timetable which include the cycle time, dwell time, running time between stations and turn-back time. The optimization problem for the special train timetable can be linearized and then solved iteratively using CPLEX solver. The effectiveness of the proposed optimization method is verified through the data of YIZHUANG line of Beijing Metro. The simulation results show that the maximum train loading rates for inbound and outbound directions are reduced by 21.1% and 16.6% respectively during the morning peak when all available trains are operated for the line. The maximum train loading rates for the inbound and outbound directions are also reduced by 23.2% and 32.3% during the evening peak. The proposed approach can be used to support the urban rail transit timetable creation during the epidemics.

Key words: intelligent transportation, train timetable, mixed integer programming, urban rail transit, major epidemics, loading rate

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