All Issue

2022 Vol.57, Issue 6 Preview Page

Research Article

Risk Assessments of Crowds at Bottlenecks through Agent Based Modelling

행위자 기반 모델을 활용한 인구과밀 및 병목현상의 위험성 분석

Moongi Choia
,
Jinwoo Parkb
,
Sanghoon Jic*
최 문기a
,
박 진우b
,
지 상훈c*
aPh.D. Student, Department of Geography, University of Utah
bPostdoctoral Research Associate, CyberGIS Center, University of Illinois Urbana-Champaign
cM.S. student, Department of Geography, Kyung Hee University
a유타대학교 지리학과 박사과정
b일리노이대학교 CyberGIS 연구소 박사후연구원
c경희대학교 지리학과 석사수료
*Corresponding Author
31 December 2022. pp. 595-609
PDF XML Citation
Abstract

Crowd crush accidents, one of the catastrophic urban disasters, have become frequent due to urban growth. To alleviate those potential risks, it is critical to not only understand the characteristics of pedestrian flow, but also provide appropriate crowd management, simultaneously. In this sense, our study examines how the population density increases according to the multiple variables associated with pedestrian movements (e.g., population, path width) and crowd control methods (e.g., right- hand traffic) through agent based modeling (ABM). In detail, we first built a passage in a virtual space and measured the population density changes over time with respect to the various pedestrian attributes (e.g., incoming counts and group ratio) and the passage characteristics (e.g., width and length). We then revisited the Itaewon stampede, which occurred in October 2022, and simulated how the population density would be curbed if a side barrier had been removed or the pedestrian rule had been implemented. As results, the pedestrian counts in the passage and the width of the passage were the two most significant variables causing the crowdedness. In addition, two advancements (i.e., right-hand traffic and no barrier in the passage) to the Itaewon stampede would result in meaningful improvement in the population density (i.e., less than six people /m2), which is less than the risky crowd crush threshold. Our study suggests that the population density monitoring system and pedestrian policy should be implemented in the future to effectively prevent the crowd crush accidents.

Keywords
Agent based modelling
Crowd crush
Crowd density
Bottlenecks

급격한 인구밀도의 증가로 인한 군중 충돌 현상은 다수의 사상자를 초래할 수 있는 도시재난으로써 도시의 발달과 함께 그 수가 증가해왔다. 인구과밀에 따라 야기될 수 있는 위험상황을 예방하기 위해서는 보행자 유동 현상에 관한 과학적 이해 및 도시적 차원의 관리가 필수적이다. 따라서 본 연구에서는 행위자 기반 모델을 통하여 보행자 유동 현상 및 상황 통제(우측 통행 등)의 변수에 따라 인구과밀현상의 위험도 변화 양상을 면밀히 분석하였다. 첫째, 가상공간의 통로를 설정하여 다양한 요인(유동 인구 수, 그룹 빈도, 도로의 폭, 길이 및 우측 통행 등)이 시간당 인구밀도 변화에 미치는 영향을 측정 하였다. 둘째, 2022년 10월 발생한 대규모 이태원 압사 사고의 공간 및 인구밀도 상황을 추정 재현하고 상황 통제(차벽 제거, 우측 통행 등) 시나리오를 적용하여 인구과밀에 대한 개선 효과를 추정하였다. 연구 결과로써 보행자 유동 현상 측면에서는 해당 통로를 지나려는 인구수가 주변 유동 인구, 그룹 빈도 변화에 비해 연구지역의 인구밀도 증가에 큰 영향을 주는 것으로 나타났으며, 공간 환경적 요소에서는 통로 폭이 통로 길이보다 더 큰 요인으로 작용하였다. 이태원 참사 추정 분석에서는 통로 상의 가벽 철거 및 우측 통행이 시행되었을 때, 인구밀도가 위험 수준인 6명/m2를 넘지 않는 것으로 나타났다. 다만, 인구밀도는 지속적으로 증가하는 패턴을 보이므로 추후 효과적인 인구통제 및 공간개선을 위하여 보다 넓은 차원의 인구밀도 감시체계 및 보행 정책 개선의 필요성을 시사한다.

키워드
행위자 기반 모델
군중과밀
군중밀도
병목현상
References
1
행정안전부, 행정안전부 재난안전관리본부 이태원 사고 중대본 브리핑(2022년11월18일), https://www.mois.go.kr/frt/bbs/type010/commonSelectBoardArticle.do?bbsId=BBSMSTR_000000000008&nttId=96678.
2
KBS NEWS, 이태원 1동 역대 최다 인파... 데이터로 본 이태원참사(2022년11월4일), https://news.kbs.co.kr/news/view.do?ncd=5593479
3
Aoki, H., Oman, C. M. and Natapoff, A., 2007, Virtual-reality- based 3D navigation training for emergency egress from spacecraft, Aviation, space, and environmental medicine, 78(8), 774-783.
4
Arias, S., La Mendola, S., Wahlqvist, J., Rios, O., Nilsson, D. and Ronchi, E., 2019, Virtual reality evacuation experiments on way-finding systems for the future circular collider, Fire Technology, 55(6), 2319-2340. 10.1007/s10694-019-00868-y
5
Bina, K. and Moghadas, N., 2021, BIM-ABM simulation for emergency evacuation from conference hall, considering gender segregation and architectural design, Architectural Engineering and Design Management, 17(5-6), 361-375. 10.1080/17452007.2020.1761282
6
Bonabeau, E., 2002, Agent-based modeling: methods and techniques for simulating human systems, Proceedings of the National Academy of Sciences, 99(3), 7280-7287. 10.1073/pnas.08208089912011407PMC128598
7
Borshchev, A., 2013, The Big Book of Simulation Modeling: Multimethod Modeling with AnyLogic 6, AnyLogic, North America. 10.1002/9781118762745.ch12
8
Burghardt, S., Seyfried, A. and Klingsch, W., 2013, Performance of stairs-fundamental diagram and topographical measurements, Transportation Research Part C: Emerging Technologies, 37, 268-278. 10.1016/j.trc.2013.05.002
9
Cao, H., Sankaranarayanan, J., Feng, J., Li, Y. and Samet, H., 2019a, Understanding metropolitan crowd mobility via mobile cellular accessing data, ACM Transactions on Spatial Algorithms and Systems, 5(2), 1-18. 10.1145/3323345
10
Cao, L., Lin, J., and Li, N., 2019b, A virtual reality based study of indoor fire evacuation after active or passive spatial exploration, Computers in Human Behavior, 90, 37- 45. 10.1016/j.chb.2018.08.041
11
Chen, J., Liu, R., Wang, J. and Chen, Y., 2017, Experimental influence of pedestrian load on individual and group evacuation speed in staircases, Fire Technology, 53(5), 1745-1763. 10.1007/s10694-017-0655-1
12
Choi, J. H., Galea, E. R. and Hong, W. H., 2014, Individual stair ascent and descent walk speeds measured in a Korean high-rise building, Fire Technology, 50(2), 267-295. 10.1007/s10694-013-0371-4
13
Choi, M. and Hohl, A., 2021, Investigating spatiotemporal indoor contact patterns using ABM and STKDE, In Proceedings of the 4th ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, 1-8. 10.1145/3486184.3491077
14
Choi, M., Cho, S. J. and Hwang, C. S., 2021, Relieving bottlenecks during evacuations using IoT devices and agent-based simulation, Sustainability, 13(16), 9465. 10.3390/su13169465
15
Cosma, G., Ronchi, E. and Nilsson, D., 2016, Way-finding lighting systems for rail tunnel evacuation: A virtual reality experiment with Oculus Rift®, Journal of Transportation Safety & Security, 8, 101-117. 10.1080/19439962.2015.1046621
16
Crociani, L., Vizzari, G., Yanagisawa, D., Nishinari, K. and Bandini, S., 2016, Route choice in pedestrian simulation: design and evaluation of a model based on empirical observations, Intelligenza Artificiale, 10(2), 163-182. 10.3233/IA-160102
17
Crooks, A., Malleson, N., Manley, E. and Heppenstall, A., 2015, Agent-based Modeling and Geographical Information Systems. Geocomputation: A Practical Primer, SAGE Publications Ltd, Thousand Oaks, CA. 10.4135/9781473916432.n4
18
Djehiche, B., Tcheukam, A. and Tembine, H., 2017, A mean- field game of evacuation in multilevel building, Transactions on Automatic Control, 62(10), 5154-5169. 10.1109/TAC.2017.2679487
19
Ezaki, T., Ohtsuka, K., Chraibi, M., Boltes, M., Yanagisawa, D., Seyfried, A. and Nishinari, K., 2016, Inflow process of pedestrians to a confined space, Collective Dynamics, 1, 1-18. 10.17815/CD.2016.4
20
Grimm, V., Berger, U., DeAngelis, D. L., Polhill, J. G., Giske, J. and Railsback, S. F., 2010, The ODD protocol: a review and first update, Ecological Modelling, 221 (23), 2760-2768. 10.1016/j.ecolmodel.2010.08.019
21
Grimm, V., Railsback, S. F., Vincenot, C. E., Berger, U., Gallagher, C., DeAngelis, D. L. and Ayllón, D., 2020, The ODD protocol for describing agent-based and other simulation models: A second update to improve clarity, replication, and structural realism, Journal of Artificial Societies and Social Simulation, 23(2), 7. 10.18564/jasss.4259
22
Guo, R. Y., Huang, H. J. and Wong, S. C., 2013, A potential field approach to the modeling of route choice in pedestrian evacuation, Journal of Statistical Mechanics: Theory and Experiment, 2013(02), P02010. 10.1088/1742-5468/2013/02/P02010
23
Haghani, M., 2020, Empirical methods in pedestrian, crowd and evacuation dynamics: Part II. Field methods and controversial topics, Safety Science, 129, 104760. 10.1016/j.ssci.2020.104760
24
Hawe, G. I., Coates, G., Wilson, D. T. and Crouch, R. S., 2012, Agent-based simulation for large-scale emergency response: a survey of usage and implementation, ACM Computing Surveys (CSUR), 45(1), 1-51. 10.1145/2379776.2379784
25
Henscheid, Z., Middleton, D. and Bitinas, E., 2018, Pythagoras: An Agent-based Simulation Environment, Northrop Grumman Corporation, USA.
26
Hoogendoorn, S. P. and Daamen, W., 2005, Pedestrian behavior at bottlenecks, Transportation Science, 39(2), 147-159. 10.1287/trsc.1040.0102
27
Huo, F., Song, W., Chen, L., Liu, C. and Liew, K. M., 2016, Experimental study on characteristics of pedestrian evacuation on stairs in a high-rise building, Safety Science, 86, 165-173. 10.1016/j.ssci.2016.02.025
28
Isobe, M., Helbing, D. and Nagatani, T., 2004, Experiment, theory, and simulation of the evacuation of a room without visibility, Physical Review E, 69(6), 066132. 10.1103/PhysRevE.69.06613215244692
29
Ji, Q., Xin, C., Tang, S. X. and Huang, J. P., 2018, Symmetry associated with symmetry break: revisiting ants and humans escaping from multiple-exit rooms, Physica A: Statistical Mechanics and its Applications, 492, 941-947. 10.1016/j.physa.2017.11.024
30
Jiang, L., Li, J., Shen, C., Yang, S. and Han, Z., 2014, Obstacle optimization for panic flow-reducing the tangential momentum increases the escape speed, PloS One, 9(12), e115463. 10.1371/journal.pone.011546325531676PMC4274084
31
Kang, J. Y. and Aldstadt, J., 2019a, Using multiple scale space-time patterns in variance-based global sensitivity analysis for spatially explicit agent-based models, Computers, Environment and Urban Systems, 75, 170-183. 10.1016/j.compenvurbsys.2019.02.00631728075PMC6855397
32
Kang, J. Y. and Aldstadt, J., 2019b, Using multiple scale spatio-temporal patterns for validating spatially explicit agent-based models, International Journal of Geographical Information Science, 33(1), 193-213. 10.1080/13658816.2018.153512131695574PMC6834355
33
Keefe, J. and Uzquiano, K., 2021, These are the warning signs that a crowd is dangerously dense, https://www.cnn.com/interactive/2021/11/us/crowd-density-dangerous-warning-signs/
34
Liao, W., Seyfried, A., Zhang, J., Boltes, M., Zheng, X. and Zhao, Y., 2014, Experimental study on pedestrian flow through wide bottleneck, Transportation Research Procedia, 2, 26-33. 10.1016/j.trpro.2014.09.005
35
Liddle, J., Seyfried, A., Klingsch, W., Rupprecht, T., Schadschneider, A. and Winkens, A., 2009, An experimental study of pedestrian congestions: influence of bottleneck width and length, Physics and Society, arXiv: 0911.4350. doi: 10.48550/arXiv.0911.4350. 10.48550/arXiv.0911.4350
36
Lin, P., Ma, J., Liu, T. Y., Ran, T., Si, Y. L., Wu, F. Y. and Wang, G. Y., 2017, An experimental study of the impact of an obstacle on the escape efficiency by using mice under high competition, Physica A: Statistical Mechanics and its Applications, 482, 228-242. 10.1016/j.physa.2017.04.021
37
Liu, S., Lo, S., Ma, J. and Wang, W., 2014, Agent-based microscopic pedestrian flow simulation model for pedestrian traffic problems, Transactions on Intelligent Transportation Systems, 15(3), 992-1001. 10.1109/TITS.2013.2292526
38
Müller, B., Bohn, F., Dreßler, G., Groeneveld, J., Klassert, C., Martin, R. and Schwarz, N., 2013, Describing human decisions in agent-based models-ODD+ D, an extension of the ODD protocol, Environmental Modelling & Software, 48, 37-48. 10.1016/j.envsoft.2013.06.003
39
Nagai, R., Fukamachi, M. and Nagatani, T., 2006, Evacuation of crawlers and walkers from corridor through an exit, Physica A: Statistical Mechanics and its Applications, 367, 449-460. 10.1016/j.physa.2005.11.031
40
Narain, R., Golas, A., Curtis, S. and Lin, M. C., 2009, Aggregate dynamics for dense crowd simulation, Proceedings of ACM SIGGRAPH Asia 2009, 1-8. 10.1145/1661412.1618468
41
Oh, H. and Park, J., 2017, Main factor causing 'faster-is- slower'phenomenon during evacuation: rodent experiment and simulation, Scientific Reports, 7(1), 1-14. 10.1038/s41598-017-14007-629057948PMC5651978
42
Pelechano, N., Allbeck, J. M. and Badler, N. I., 2007, Controlling individual agents in high-density crowd simulation, Proceedings of the 2007 ACM SIGGRAPH/ Eurographics Symposium on Computer Animation, San Diego, CA.
43
Rupprecht, T., Klingsch, W. and Seyfried, A., 2011, Influence of Geometry Parameters on Pedestrian Flow through Bottleneck, Pedestrian and Evacuation Dynamics, Springer, Boston, MA, 71-80. 10.1007/978-1-4419-9725-8_7
44
Rupprecht, T., Seyfried, A., Klingsch, W. and Boltes, M., 2007, Bottleneck capacity estimation for pedestrian traffic, In Proceedings of the Interflam, 1423-1430.
45
Severiukhina, O., Voloshin, D., Lees, M. H. and Karbovskii, V., 2017, The study of the influence of obstacles on crowd dynamics, Procedia Computer Science, 108, 215-224. 10.1016/j.procs.2017.05.162
46
Seyfried, A., Passon, O., Steffen, B., Boltes, M., Rupprecht, T. and Klingsch, W., 2009, New insights into pedestrian flow through bottlenecks, Transportation Science, 43(3), 395-406. 10.1287/trsc.1090.0263
47
Shahhoseini, Z., and Sarvi, M., 2017, Collective movements of pedestrians: how we can learn from simple experiments with non-human (ant) crowds, Plos One, 12(8), e0182913. 10.1371/journal.pone.018291328854221PMC5576663
48
Sharifi, M. S., Stuart, D., Christensen, K. and Chen, A., 2015, Traffic flow characteristics of heterogeneous pedestrian stream involving individuals with disabilities, Transportation Research Record, 2537(1), 111-125. 10.3141/2537-13
49
Shi, X., Ye, Z., Shiwakoti, N., Tang, D. and Lin, J., 2019, Examining effect of architectural adjustment on pedestrian crowd flow at bottleneck, Physica A: Statistical Mechanics and its Applications, 522, 350-364. 10.1016/j.physa.2019.01.086
50
Shiwakoti, N., Sarvi, M. and Burd, M., 2014, Using non- human biological entities to understand pedestrian crowd behaviour under emergency conditions, Safety Science, 66, 1-8. 10.1016/j.ssci.2014.01.010
51
Simonov, A., Lebin, A., Shcherbak, B., Zagarskikh, A. and Karsakov, A., 2018, Multi-agent crowd simulation on large areas with utility-based behavior models: Sochi Olympic Park Station use case, Procedia Computer Science, 136, 453-462. 10.1016/j.procs.2018.08.266
52
Solmaz, G., Wu, F. J., Cirillo, F., Kovacs, E., Santana, J. R., Sánchez, L. and Munoz, L., 2019, Toward understanding crowd mobility in smart cities through the internet of things, Communications Magazine, 57(4), 40-46. 10.1109/MCOM.2019.1800611
53
Still, K., 2000, Crowd Dynamics, Doctoral Dissertation, University of Warwick, Coventry.
54
Still, K., Papalexi, M., Fan, Y. and Bamford, D., 2020, Place crowd safety, crowd science? case studies and application, Journal of Place Management and Development, 13(4), 385-407. 10.1108/JPMD-10-2019-0090
55
Still. K., 2019, Crowd safety and crowd risk analysis, static crowd density visuals, https://www.gkstill.com/Support/crowd-density/100sm/index.html
56
Train, K., 2009, Discrete Choice Methods with Simulation, Cambridge University Press, Cambridge.
57
Ünal, A. E., Gezer, C., Pak, B. K. and Güngör, V. Ç., 2022, Generating emergency evacuation route directions based on crowd simulations with reinforcement learning, In 2022 Innovations in Intelligent Systems and Applications Conference (ASYU), 1-6. 10.1109/ASYU56188.2022.9925560
58
Wang, G. Y., Wu, F. Y., Si, Y. L., Zeng, Q. and Lin, P., 2018, The study of the impact of obstacle on the efficiency of evacuation under different competitive conditions, Procedia Engineering, 211, 699-708. 10.1016/j.proeng.2017.12.066
59
Wang, X., Su, H., Zhou, T. and Miao, X., 2022, A subway station platform crowd simulation system, In Proceedings of the 14th International Conference on Computer Modeling and Simulation, 69-75. 10.1145/3547578.3547589
60
Wolinski, D., J. Guy, S., Olivier, A. H., Lin, M., Manocha, D. and Pettré, J., 2014, Parameter estimation and comparative evaluation of crowd simulations, Computer Graphics Forum, 33(2), 303-312. 10.1111/cgf.12328
61
Xiao, H., Wang, Q., Zhang, J. and Song, W., 2019, Experimental study on the single-file movement of mice, Physica A: Statistical Mechanics and its Applications, 524, 676-686. 10.1016/j.physa.2019.04.032
62
Yanagisawa, D., Kimura, A., Tomoeda, A., Nishi, R., Suma, Y., Ohtsuka, K. and Nishinari, K., 2009, Introduction of frictional and turning function for pedestrian outflow with an obstacle, Physical Review E, 80(3), 036110. 10.1103/PhysRevE.80.03611019905183
63
Zhang, X., Zhong, T. and Liu, M., 2009, Modeling crowd evacuation of a building based on seven methodological approaches, 44(3), 437-445. 10.1016/j.buildenv.2008.04.002
Information
  • Publisher :The Korean Geographical Society
  • Publisher(Ko) :대한지리학회
  • Journal Title :Journal of the Korean Geographical Society
  • Journal Title(Ko) :대한지리학회지
  • Volume : 57
  • No :6
  • Pages :595-609
  • Received Date : 2022-12-12
  • Revised Date : 2022-12-29
  • Accepted Date : 2022-12-30
  • DOI :https://doi.org/10.22776/kgs.2022.57.6.595
Journal Informaiton Journal of the Korean Geographical Society Journal of the Korean Geographical Society
online submission
  • NRF
  • KISTI Current Status
  • KISTI Cited-by
  • KCI 문헌 유사도 검사
  • orcid
  • open access
  • ccl
Journal Informaiton Journal Informaiton - close