Journal of Jilin University(Engineering and Technology Edition) ›› 2020, Vol. 50 ›› Issue (2): 549-556.doi: 10.13229/j.cnki.jdxbgxb20181163

Previous Articles    

An optimization⁃based evacuation model considering pedestrian heterogeneity

Da-wei ZHANG1(),Hai-tao ZHU1,2   

  1. 1.College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin 150001, China
    2.College of Shipbuilding Engineering, Harbin Engineering University, Harbin 150001, China
  • Received:2018-11-26 Online:2020-03-01 Published:2020-03-08

RICH HTML

 13   

PDF (PC)

423

Abstract:

In order to investigate the personal characteristics in heterogeneous pedestrian crowds during evacuation, an optimization-based evacuation model is proposed. The concepts of visual area of each agent and personal sensitivity to the space availability are introduced. A side preference of each pedestrian is implemented based on traffic social norms. The criteria for the evaluating of space availability are established to depict the personal heterogeneity from the perspective of both behavior and decision-making. The model was employed to simulate overtaking behavior and lane formation and the phase change of pedestrian lanes in heterogeneous pedestrian crowds was observed experimentally. The model was validated by comparing the simulation results with experiment date and with the results obtained by other evacuation model. The fundamental diagram of heterogeneous crowds was also investigated. The results show that the proposed model could simulate reasonably the personal behavior as well as the self-organization phenomena in heterogeneous crowds, thus providing the reasonable and effective strategies for crowds management in emergent situation.

Key words: engineering of communications and transportation system, evacuation model, overtaking behavior, decision-making behavior, lane formation

CLC Number: 

  • U491

Fig.1

Definitions of ‘visual area’"

Fig.2

Basic algorithm for optimization-based evacuation model"

Fig.3

Schematic illustration of a corridor for simulation"

Fig.4

Initial pedestrian formations in each experiment"

Fig.5

Comparisons of results with experiment"

Table 1

Time of each pedestrian flow pattern in unidirectional flow"

人群模式仿真时间/s绝对误差/s
a 22.20.38
a 45.01.80
b 23.40.46
b 44.80.21
c 23.60.20
c 45.80.75

Fig.6

Images captured of pedestrian flow pattern"

Fig.7

Results using proposed model in this paper"

Fig.8

Rresults using FDS+Evac model"

Table 2

Time of each pedestrian flow pattern in bidirectional flow"

人群模式Tr/s Ts/s 绝对误差/s
11.502.10.60
25.236.61.37
37.739.11.37
49.7311.61.87

Fig.9

Schematic illustration of a long corridor"

Fig.10

Comparison of relationship between density andspecific flow rate with experimental data"

Fig.11

Comparison of relationship between density and walking speed with experimental data"

1 马剑, 王若成, 邱谦谦. 紧急情况下城市轨道隧道客流疏散配流模型研究[J]. 铁道学报, 2016, 38( 6): 8- 14.
Ma Jian, Wang Ruo-cheng, Qiu Qian-qian. Passenger assignment model for emergency evacuation in metro rail tunnels[J]. Journal of the China Railway Sciety, 2016, 38( 6): 8- 14.
2 岳昊, 何栋梁, 张滨雅, 等. 行人步行设施空间疏散特征指标[J]. 哈尔滨工业大学学报, 2017, 49( 9): 17- 24.
Yue Hao, He Dong-liang, Zhang Bin-ya, et al. Spatial characteristics indexes of pedestrian walking facilities for evacuation[J]. Journal of Harbin Institute of Technology, 2017, 49( 9): 17- 24.
3 Helbing D, Molnar P. Social force model for pedestrian dynamics[J]. Physical Review E, 1995, 51( 5): 4282- 4286.
4 Hoogendoorn S P, Bovy P H L. Dynamic user-optimal assignment in continuous time and space[J]. Transportation Research Part B: Methodological, 2004, 38( 7): 571- 592.
5 苏书杰, 何露. 步行交通规划交叉路口行人瞬时动态拥塞疏散模型[J]. 吉林大学学报: 工学版, 2018, 48( 2): 440- 447.
Su Shu-jie, He Lu. Transient dynamic congestion evacuation model of pedestrian at walk traffic planning crossroads[J]. Journal of Jilin University (Engineering and Technology Edition), 2018, 48( 2): 440- 447.
6 周继彪, 陈红, 闫彬, 等. 基于云模型的地铁换乘枢纽拥挤度辨识方法[J]. 吉林大学学报： 工学版, 2016, 46( 1): 100- 107.
Zhou Ji-biao, Chen Hong, Yan Bin, et al. Identification of pedestrian crowding degree in metro transfer hub based on normal cloud model[J]. Journal of Jilin University (Engineering and Technology Edition), 2016, 46 ( 1): 100- 107.
7 Smith A, James C, Jones R, et al. Modelling contra-flow in crowd dynamics DEM simulation[J]. Safety Science, 2009, 47( 3): 395- 404.
8 Parisi D R, Gilman M, Moldovan H. A modification of the social force model can reproduce experimental data of pedestrian flows in normal conditions[J]. Physica A: Statistical Mechanics and its Applications, 2009, 388( 17): 3600- 3608.
9 Heliövaara S, Korhonen T, Hostikka S, et al. Counterflow model for agent-based simulation of crowd dynamics[J]. Building and Environment, 2012, 48( 1): 89- 100.
10 Zhang D, Zhu H, Du L, et al. An optimization-based overtaking model for unidirectional pedestrian flow[J]. Physics Letters A, 2018, 382( 44): 3172- 3180.
11 Yuen J K K, Lee E W M. The effect of overtaking behavior on unidirectional pedestrian flow[J]. Safety Science, 2012, 50( 8): 1704- 1714.
12 Moussaïd M, Nelson J D. Simple heuristics and the modelling of crowd behaviours[C]∥ Pedestrian and Evacuation Dynamics 2012, Cham: Springer, 2014: 75- 90.
13 Moussaïd M, Helbing D, Theraulaz G. How simple rules determine pedestrian behavior and crowd disasters[J]. Proceedings of the National Academy of Sciences, 2011, 108( 17): 6884- 6888.
14 Saberi M, Aghabayk K, Sobhani A. Spatial fluctuations of pedestrian velocities in bidirectional streams: exploring the effects of self-organization[J]. Physica A: Statistical Mechanics and its Applications, 2015, 434: 120- 128.
15 Tao Y, Dong L. Investigation on lane-formation in pedestrian flow with a new cellular automaton model[J]. Journal of Hydrodynamics, 2016, 28( 5): 794- 800.
16 Nagatani T. Freezing transition in bi-directional CA model for facing pedestrian traffic[J]. Physics Letters A, 2009, 373( 33): 2917- 2921.
17 Li X, Guo F, Kuang H, et al. Effect of psychological tension on pedestrian counter flow via an extended cost potential field cellular automaton model[J]. Physica A: Statistical Mechanics and its Applications, 2017, 487: 47- 57.
18 Fu L, Song W, Lyu W, et al. Simulation of emotional contagion using modified SIR model: a cellular automaton approach[J]. Physica A: Statistical Mechanics and its Applications, 2014, 405: 380- 391.
19 Batty M. Predicting where we walk[J]. Nature, 1997, 388( 6637): 19- 20.
20 Feliciani C, Nishinari K. An improved cellular automata model to simulate the behavior of high density crowd and validation by experimental data[J]. Physica A: Statistical Mechanics and its Applications, 2016, 451: 135- 148.
21 Shimura K, Ohtsuka K, Vizzari G, et al. Mobility analysis of the aged pedestrians by experiment and simulation[J]. Pattern Recognition Letters, 2014, 44: 58- 63.
22 Seyfried A, Schadschneider A. Fundamental diagram and validation of crowd models[C]∥ International Conference on Cellular Automata. Berlin, Heidelberg: Springer, 2008: 563- 566.
23 Zhang J, Klingsch W, Schadschneider A, et al. Ordering in bidirectional pedestrian flows and its influence on the fundamental diagram[J/OL].[ 2018-09-22].
24 Navin F P, Wheeler R J. Pedestrian flow characteristics[J]. Traffic Engineering, Inst Traffic Engr, 1969, 19( 7): 30- 33, 36.
25 Older S J. Movement of pedestrians on footways in shopping streets[J]. Traffic Engineering & Control, 1968, 10( 4): 160- 163.
[1] Hong-fei JIA,Xin-ru DING,Li-li YANG. Bi-level programming model for optimization design of tidal lane [J]. Journal of Jilin University(Engineering and Technology Edition), 2020, 50(2): 535-542.
[2] Chao-ying YIN,Chun-fu SHAO,Xiao-quan WANG,Zhi-hua XIONG. Influence of built environment on commuting mode choice considering spatial heterogeneity [J]. Journal of Jilin University(Engineering and Technology Edition), 2020, 50(2): 543-548.
[3] Yi-ming BIE,Kai JIANG,Ru-ru TANG,Lin-hong WANG,Xin-yu XIONG. Time of interval partition for traffic control at isolated intersection considering impacts of plan transition [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(6): 1844-1851.
[4] Yuan-li GU, Yuan ZHANG, Xiao-ping RUI, Wen-qi LU, Meng LI, Shuo WANG. Short⁃term traffic flow prediction based on LSSVMoptimized by immune algorithm [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(6): 1852-1857.
[5] Guo-zhu CHENG, Si-he FENG, Tian-jun FENG. Setting condition of on⁃street parking space occupied vehicle lane [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(6): 1858-1864.
[6] Hai-bo LONG,Jia-qi YANG,Xue-yu ZHAO. Optimizing vehicles allocation of multimodal coordinated freight transport based on transshipment delay risks [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(5): 1492-1499.
[7] Quan LIANG,Jian-cheng WENG,Wei ZHOU,Jian RONG. Stability identification of public transport commute passengers based on association rules [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(5): 1484-1491.
[8] Wen⁃jing WU,Run⁃chao CHEN,Hong⁃fei JIA,Qing⁃yu LUO,Di SUN. Collaborative control method of vehicles in U⁃turn zone under environment of cooperative vehicle infrastructure system [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(4): 1100-1106.
[9] Zhao⁃wei QU,Zhao⁃tian PAN,Yong⁃heng CHEN,Peng⁃fei TAO,Di SUN. Car⁃following model with improving safety distance based on optimal velocity model [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(4): 1092-1099.
[10] Lei CHEN,Jiang⁃feng WANG,Yuan⁃li GU,Xue⁃dong YAN. Multi⁃source traffic data fusion algorithm based onmind evolutionary algorithm optimization [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(3): 705-713.
[11] Qiang TU,Lin CHENG,Fen LIN,Chao SUN. Finding shortest path considering traveler′s risk attitude [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(3): 720-726.
[12] Ning⁃bo CAO,Li⁃ying ZHAO,Zhao⁃wei QU,Yong⁃heng CHEN,Qiao⁃wen BAI,Xiao⁃lei DENG. Social force model considering bi⁃direction pedestrian slipstreaming behavior [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(3): 688-694.
[13] Chao⁃ying YIN,Chun⁃fu SHAO,Xiao⁃quan WANG. Influence of urban built environment on car commuting considering parking availability [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(3): 714-719.
[14] Qiao⁃wen BAI,Zhao⁃wei QU,Yong⁃heng CHEN,Shuai XIONG,Chu⁃qing TAO. Modeling on trajectories of through vehicles with an unprotected left⁃turn phase under non⁃strict priority [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(3): 673-679.
[15] CHEN Yong-heng,LIU Fang-hong,CAO Ning-bo. Analysis of conflict factors between pedestrians and channelized right turn vehicles at signalized intersections [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1669-1676.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright © Journal of Jilin University(Engineering and Technology Edition), All Rights Reserved.
Tel: +86-431-85095297　Fax: +86-431-85094074　E-mail: xbgxb@jlu.edu.cn
Powered by Beijing Magtech Co. Ltd