|Table of Contents|

[1] Zeng Lu, Liu Jun, Qin Yong,. Passenger flow dynamic assignment model of urban mass transitand its application during interval interrupted operation [J]. Journal of Southeast University (English Edition), 2017, 33 (1): 115-122. [doi:10.3969/j.issn.1003-7985.2017.01.019]
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Passenger flow dynamic assignment model of urban mass transitand its application during interval interrupted operation()
中断条件下的城市轨道交通客流动态分配模型及其应用
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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:
33
Issue:
2017 1
Page:
115-122
Research Field:
Traffic and Transportation Engineering
Publishing date:
2017-03-30

Info

Title:
Passenger flow dynamic assignment model of urban mass transitand its application during interval interrupted operation
中断条件下的城市轨道交通客流动态分配模型及其应用
Author(s):
Zeng Lu1,3,Liu Jun1,Qin Yong2
1School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
2State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China
3College of Applied Science, Jiangxi University of Science and Technology, Ganzhou 341000, China
曾璐1,3,刘军1,秦勇2
1北京交通大学交通运输学院, 北京 100044; 2北京交通大学轨道交通控制与安全国家重点实验室, 北京100044; 3江西理工大学应用科学学院, 赣州 341000
Keywords:
urban mass transit dynamic disequilibrium distribution local disruption
城市轨道交通 动态 非均衡分配 局部中断
PACS:
U231
DOI:
10.3969/j.issn.1003-7985.2017.01.019
Abstract:
In order to find a method which can describe the passenger flow dynamical distribution of urban mass transit during interval interrupted operation, an urban railway network topology model was built based on the travel path dual graph by considering interchange, crowd and congestion. The breadth first valid travel path search algorithm is proposed, and the multipath passenger flow distribution logit model is improved. According to the characteristics of passengers under the interruption condition, the distribution rules of different types of passenger flow are proposed. The method of calculating the aggregation number of station is proposed for the case of insufficient transport capacity. Finally, the passenger flow of Beijing urban mass transit is simulated for the case study. The results show that the relative error of most of transfer passenger flow is below 10%. The proposed model and algorithm can accurately assign the daily passenger flow, which provides a theoretical basis for urban mass transit emergency management and decision.
为了较为准确地对城市轨道交通在运营中断等特殊条件下的客流动态分配及其影响进行分析计算,在综合考虑换乘、拥挤、等待等因素基础上构建了基于出行路径对偶图的阻抗模型.采用了基于广度优先的有效路径搜索算法,构建了改进的Logit模型.根据中断条件下乘客的出行特点,给出了不同类别客流的分配规则,并提出了中断运力不足情况下站内聚集人数计算方法.最后,以北京城市轨道交通某日客流量为例进行实验.结果表明,大部分换乘方向的相对误差值在10%左右.该模型与算法能够较为准确地对日常客流量进行分配,为城市轨道交通应急管理及决策支持提供了理论依据.

References:

[1] Wardrop J G. Some theoretical aspects of road traffic research[C]//Proceedings of the Institution of Civil Engineers. London, UK, 1952:325-378. DOI:10.1680/ipeds.1952.11259.
[2] Tian Z, Yang H, Lam W H K. Transit assignment under crowded conditions [J]. Journal of Advanced Transportation, 2003, 31(1):19-38. DOI:10.1002/atr.5670310104.
[3] Poon M H, Wong S C, Tong C O. A dynamic schedule-based model for congested Transit networks [J]. Transportation Research Part B: Methodological, 2004, 38(4): 343-368. DOI:10.1016/s0191-2615(03)00026-2.
[4] Daganzo C F, Sheffi Y. On stochastic models of traffic assignment[J]. Transportation Science, 1977, 11(3): 253-274. DOI:10.1287/trsc.11.3.253.
[5] Dial R B. A probabilistic multipath traffic assignment model which obviates path enumeration[J]. Transportation Research, 1971, 5(2): 83-111. DOI:10.1016/0041-1647(71)90012-8.
[6] Vuk G, Hansen C O. Validating the passenger traffic model for Copenhagen[J]. Transportation, 2006, 33(4):371-392. DOI:10.1007/s11116-005-4335-5.
[7] Schmöcker J D, Bell M G H, Kurauchi F. A quasi-dynamic capacity constrained frequency-based transit assignment model[J]. Transportation Research Part B, 2008, 42(10):925-945. DOI:10.1016/j.trb.2008.02.001.
[8] Kato H, Kaneko Y, Inoue M. Comparative analysis of transit assignment: Evidence from urban railway system in the Tokyo Metropolitan Area [J]. Transportation, 2010, 37(5):775-799. DOI:10.1007/s11116-010-9295-8.
[9] Emmanuel L N, Antonio R T, Ernesto L M. A modeling framework for urban traffic systems microscopic simulation [J]. Simulation Modelling Practice and Theory, 2010, 18(8):1145-1161. DOI:10.1016/j.simpat.2009.09.007.
[10] Grube P, Núnez F, Cipriano A. An event-driven simulator for multi-line metro systems and its application to Santiago de Chile metropolitan rail network [J]. Simulation Modelling Practice and Theory, 2011, 19(1):393-405. DOI:10.1016/j.simpat.2010.07.012.
[11] Schmöcker J D, Fonzone A, Shimamoto H, et al. Frequency-based transit assignment considering seat capacities [J]. Transportation Research Part B: Methodological, 2011, 45(2): 392-408.
[12] Nuzzolo A, Crisalli U, Rosati L. A schedule-based assignment model with explicit capacity constraints for congested transit networks [J]. Transportation Research Part C: Emerging Technologies, 2012, 20(1):16-33.
[13] Shi F, Zhou Z, Yao J, et al. Incorporating transfer reliability into equilibrium analysis of railway passenger flow [J]. European Journal of Operational Research, 2012, 220(2): 378-385. DOI:10.1016/j.ejor.2012.02.012.

Memo

Memo:
Biographies: Zeng Lu(1983—), female, graduate; Qin Yong(corresponding author), male, doctor, professor, qinyong2146@126.com.
Foundation items: The National Natural Science Foundation of China(No.61374157), the Science and Technology Project of the Education Department of Jiangxi Province(No.GJJ151524).
Citation: Zeng Lu, Liu Jun, Qin Yong.Passenger flow dynamic assignment model of urban mass transit and its application during interval interrupted operation[J].Journal of Southeast University(English Edition),2017,33(1):115-122.DOI:10.3969/j.issn.1003-7985.2017.01.019.
Last Update: 2017-03-20