吉林大学学报(工学版) ›› 2017, Vol. 47 ›› Issue (6): 1728-1737.doi: 10.13229/j.cnki.jdxbgxb201706008

• 论文 • 上一篇    下一篇

对向行人流均衡反馈控制模型

张蜇1, 贾利民1, 2, 3, 秦勇1, 2, 3, 云婷1, 2, 3   

  1. 1.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;
    2.北京交通大学 交通运输学院,北京 100044;
    3.北京交通大学 北京市城市交通信息智能感知与服务工程技术研究中心,北京 100044
  • 收稿日期:2016-08-17 出版日期:2017-11-20 发布日期:2017-11-20
  • 通讯作者: 贾利民(1963-),男,教授,博士生导师.研究方向:交通控制与安全.E-mail:jialm@vip.sina.com
  • 作者简介:张蜇(1988-),男,博士研究生.研究方向:交通运输规划与管理.E-mail:13114245@bjtu.edu.cn
  • 基金资助:
    “十三五”国家重点研发计划项目(2017YFB1201200); 国家自然科学基金项目(71171015)

Equalization-based feedback control model of pedestrian counter flow

ZHANG Zhe1, JIA Li-min1, 2, 3, QIN Yong1, 2, 3, YUN Ting1, 2, 3   

  1. 1.State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China;
    2.Traffic and Transportation School, Beijing Jiaotong University, Beijing 100044, China;
    3.Beijing Research Center of Urban Traffic Information Sensing and Service Technologies, Beijing Jiaotong University,Beijing 100044, China
  • Received:2016-08-17 Online:2017-11-20 Published:2017-11-20

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摘要： 为避免双向通道行人流堵塞,建立了对向行人流反馈控制模型。考虑了对向行人流的干扰特性,利用社会力模型的匀速条件推导了对向行人流基本图。由于行人密度沿通道分布不同,按照行走方向不同,将双向通道分为多个分通道,采用状态空间方程建立了基于行人流量守恒的对向行人流系统动力学模型。为满足对向行人移动需求,提出对向行人流均衡控制目标,并建立了线性反馈控制模型。该模型可通过实时调整行人速度和通道两端的行人流入量,使得通道行人密度收敛于临界密度,从而最大化通道行人流量,提高通道服务水平。本文模型可以作为解决行人流和道路交通实时控制问题的普适方法。

关键词: 交通运输系统工程, 对向行人流, 系统动力, 反馈控制

Abstract: A feedback control model of pedestrian counter flow was established to avoid pedestrian flow blocking in bidirectional corridors. The fundamental diagram of bidirectional pedestrian flow incorporating the conflict characteristic was derived using the social force model under the uniform state. To accommodate the possible inhomogeneous pedestrian density along the corridor, the bidirectional corridor was divided into several sections for different directions. A system dynamics model of pedestrian counter flow was proposed using the conversation law of pedestrian mass and the state space equation. To satisfy the moving demand of pedestrians in both directions, the equalization control objective was proposed based on the user equilibrium theory, and the linear feedback control model was established. The proposed control model can maximize the output flow of the corridor, thus improving the service level of the corridor by adjusting the walking speed of pedestrians and the corridor input flow in real time. The proposed model has the capability to serve as a general control method of both pedestrian flow and vehicle flow.

Key words: engineering of communication and transportation system, pedestrian counter flow, system dynamics, feedback control

中图分类号: 

  • U491
[1] 谢征宇,贾利民,秦勇,等. 铁路客运枢纽视频监控采集点布设模型[J]. 中南大学学报:自然科学版,2013,44(增刊2):254-257.
Xie Zheng-yu, Jia Li-min, Qin Yong, et al. Monitor point layout model of video surveillance in railway passenger transport hub[J]. Journal of Central South University (Science and Technology),2013,44(Sup.2):254-257.
[2] Zhang J, Klingsch W, Schadschneider A, et al. Ordering in bidirectional pedestrian flows and its influence on the fundamental diagram[J]. Journal of Statistical Mechanics:Theory and Experiment,2012,2012(2):1-13.
[3] Lee J, Kim T, Chung J H, et al. Modeling lane formation in pedestrian counter flow and its effect on capacity[J]. KSCE Journal of Civil Engineering,2016,20(3):1099-1108.
[4] Wei J, Zhang H, Guo Y, et al. Experiment of bi-direction pedestrian flow with three-dimensional cellular automata[J]. Physics Letters A,2015,379(16):1081-1086.
[5] Ge Hong-xia, Cheng Rong-jun, Lo Siu-ming. A lattice model for bidirectional pedestrian flow on gradient road[J]. Communications in Theoretical Physics,2014,62(2):259-264.
[6] Hu J, Li Z, Zhang H, et al. Experiment and simulation of the bidirectional pedestrian flow model with overtaking and herding behavior[J]. International Journal of Modern Physics C, 2015,26(11):1550131.
[7] Zhang P, Jian X X, Wong S C, et al. Potential field cellular automata model for pedestrian flow[J]. Physical Review E,2012,85(2):021119.
[8] Chen Y Y, Chen N, Wang Y, et al. Modeling pedestrian behaviors under attracting incidents using cellular automata[J]. Physica A: Statistical Mechanics and Its Applications,2015,432:287-300.
[9] Tajima Y, Takimoto K, Nagatani T. Scaling of pedestrian channel flow with a bottleneck[J]. Physica A: Statistical Mechanics and Its Applications,2001,294(1):257-268.
[10] Nowak S, Schadschneider A. A Cellular Automaton Approach for Lane Formation in Pedestrian Counterflow[M]. Berlin Heidelberg: Springer,2013:149-160.
[11] 李明华,袁振洲,许琰,等. 基于改进格子气模型的对向行人流分层现象的随机性研究[J]. 物理学报,2015,64(1):435-446.
Li Ming-hua,Yuan Zhen-zhou, Xu Yan, et al. Randomness analysis of lane formation in pedestrian counter flow based on improved lattice gas model[J]. Acta Physica Sinica,2015,64(1):435-446.
[12] Feliciani C, Nishinari K. Phenomenological description of deadlock formation in pedestrian bidirectional flow based on empirical observation[J]. Journal of Statistical Mechanics: Theory and Experiment,2015,2015(10):10003.
[13] Wang X, Zheng X, Cheng Y. Evacuation assistants: an extended model for determining effective locations and optimal numbers[J]. Physica A: Statistical Mechanics and Its Applications,2012,391(6):2245-2260.
[14] Takimoto K, Tajima Y, Nagatani T. Effect of partition line on jamming transition in pedestrian counter flow[J]. Physica A:Statistical Mechanics and Its Applications,2002,308(1):460-470.
[15] Helbing D, Farkas I, Vicsek T. Simulating dynamical features of escape panic[J]. Nature,2000,407(6803):487-490.
[16] Yang Xiao-xia, Dong Hai-rong, Yao Xiu-ming. Dynamic feature analysis in bidirectional pedestrian flows[J]. Chinese Physics B,2016,25(2):028901.
[17] Zhou J, Shi Z K, Liu Z S. A novel lattice hydrodynamic model for bidirectional pedestrian flow with the consideration of pedestrian's memory effect[J]. Nonlinear Dynamics,2015,83(4):1-15.
[18] Zhou J, Shi Z K. A new lattice hydrodynamic model for bidirectional pedestrian flow with the consideration of lateral discomfort[J]. Nonlinear Dynamics,2015,81(3):1113-1131.
[19] Zhou J, Shi Z K. A new lattice hydrodynamic model for bidirectional pedestrian flow with the consideration of pedestrian's anticipation effect[J]. Nonlinear Dynamics,2015,81(3):1247-1262.
[20] Zhou J, Shi Z K. Lattice hydrodynamic model for bidirectional pedestrian flow with the consideration of pedestrian density difference[J]. International Journal of Modern Physics C,2015,26(8):1550092.
[21] Chalons C. Numerical approximation of a macroscopic model of pedestrian flows[J]. SIAM Journal on Scientific Computing,2007,29(2):539-555.
[22] Hoogendoorn S P, van Wageningen-Kessels F, Daamen W, et al. Continuum theory for pedestrian traffic flow: local route choice modelling and its implications[J]. Transportation Research Part C: Emerging Technologies,2015,59:183-197.
[23] Hughes R L. A continuum theory for the flow of pedestrians[J]. Transportation Research Part B: Methodological,2002,36(6):507-535.
[24] Shende A, Kachroo P, Reddy K C, et al. Optimal control of pedestrian evacuation in a corridor[C]//IEEE Conference on Intelligent Transportation Systems, Seattle, WA,USA,2007:385-390.
[25] 李曼,王艳辉,贾利民. 城市轨道交通车站客流模态与控制策略[J]. 东南大学学报:自然科学版,2015,45(6):1203-1208.
Li Man, Wang Yan-hui, Jia Li-min. Passenger flow modes and control strategies in urban rail transit station[J]. Journal of Southeast University (Natural Science Edition),2015,45(6):1203-1208.
[26] Shende A, Singh M P, Kachroo P. Optimization-based feedback control for pedestrian evacuation from an exit corridor[J]. IEEE Transactions on Intelligent Transportation Systems,2011,12(4):1167-1176.
[27] Haddad J, Ramezani M, Geroliminis N. Cooperative traffic control of a mixed network with two urban regions and a freeway[J]. Transportation Research Part B:Methodological,2013,54:17-36.
[28] Teodorovic D, Vukadinovic K. Traffic Control and Transport Planning: a Fuzzy Sets and Neural Networks Approach[M]. New York: Springer,2012.
[29] 李志斌,金茂菁,刘攀,等. 提高高速公路通行效率的可变限速控制策略[J]. 吉林大学学报:工学版,2013,43(5):1204-1209.
Li Zhi-bin, Jin Mao-jing, Liu Pan, et al. Evaluation of impact variable speed limits on improving traffic efficiency on freeways[J]. Journal of Jilin University (Engineering and Technology Edition),2013,43(5):1204-1209.
[30] Zohdy I H, Rakha H. Game theory algorithm for intersection-based cooperative adaptive cruise control (CACC) systems[C]//15th International IEEE Conference on Intelligent Transportation Systems, Anchorage, Alaska,USA,2012:1097-1102.
[31] Hafner M R, Cunningham D, Caminiti L, et al. Cooperative collision avoidance at intersections: Algorithms and experiments[J]. IEEE Transactions on Intelligent Transportation Systems,2013,14(3):1162-1175.
[32] 姚荣涵,张晓彤,廉莲. 交叉口可变导向车道控制优化模型[J]. 吉林大学学报:工学版,2017,47(4): 1048-1054.
Yao Rong-han, Zhang Xiao-tong, Lian Lian. Optimization model for controlling reversible approach lanes at signalized intersections[J]. Journal of Jilin University (Engineering and Technology Edition),2017,47(4):1048-1054.
[33] 贾洪飞,李永行,杨丽丽. 基于交通状态估计的快速路交通联合控制[J]. 吉林大学学报:工学版,2017,47(1):76-81.
Jia Hong-fei,Li Yong-xing,Yang Li-li. Expressway traffic joint control based on traffic state estimation[J]. Journal of Jilin University (Engineering and Technology Edition),2017,47(1):76-81.
[34] Kachroo P, Al-Nasur S J, Wadoo S A, et al. Pedestrian Dynamics: Feedback Control of Crowd Evacuation[M]. New York:Springer,2008.
[35] Shende A, Singh M P, Kachroo P. Optimal feedback flow rates for pedestrian evacuation in a network of corridors[J]. IEEE Transactions on Intelligent Transportation Systems,2013,14(3):1053-1066.
[36] Wadoo S A, Kachroo P. Feedback control of crowd evacuation in one dimension[J]. IEEE Transactions on Intelligent Transportation Systems,2010,11(1):182-193.
[37] 曾广湘,薛郁. 准滑模控制应用于行人通道的交通瓶颈[J]. 物理学报,2011,60(1):014502.
Zeng Guang-xiang, Xue Yu. Application of the quasi-sliding-mode control to traffic bottleneck in pedestrian channel[J]. Acta Physica Sinica,2011,60(1):014502.
[38] Nikolić M, Bierlaire M, Farooq B, et al. Probabilistic speed-density relationship for pedestrian traffic[J]. Transportation Research Part B: Methodological,2016,89:58-81.
[39] Greenshields B D, Bibbins J R, Channing W S, et al. A study of traffic capacity[J]. Highway Research Board Proceedings,1935,14:448-477.
[40] Wong S C, Leung W L, Chan S H, et al. Bidirectional pedestrian stream model with oblique intersecting angle[J]. Journal of Transportation Engineering,2010,136(3):234-242.
[41] Gawron C. An iterative algorithm to determine the dynamic user equilibrium in a traffic simulation model[J]. International Journal of Modern Physics C,1998,9(3):393-407.
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