Multi-Agent based Simulation Modelling for Passenger Flow Emergency Evacuation in Scenic Spots

doi:10.23940/ijpe.20.10.p19.16741684

Int J Performability Eng ›› 2020, Vol. 16 ›› Issue (10): 1674-1684.doi: 10.23940/ijpe.20.10.p19.16741684

Multi-Agent based Simulation Modelling for Passenger Flow Emergency Evacuation in Scenic Spots

Yingfei Zhang^a, Gongpeng Zhang^b,*, Ruixin Wang^c, and XiaoBing Hu^d

^aCollege of Economics and Management, Civil Aviation University of China, Tianjin, 300300, China;
^bCollaborative Innovation Center of eTourism, Beijing Union University, Beijing, 100101, China;
^cSino-European Institute of Aviation Engineering, Civil Aviation University of China, Tianjing, 300300, China;
^dCollege of Electronic Information and Automation, Civil Aviation University of China, Tianjin, 300300, China

Submitted on ; Revised on ; Accepted on
Contact: * E-mail address: gongpeng@buu.edu.cn
About author:Yingfei Zhang is a graduate student of the School of Civil Aviation University of China. Her research interests include personnel evacuation and civil aviation safety.
Gongpeng Zhang (Corresponding author, gongpeng@buu.edu.cn) is an Associate Professor of Tourism College of Beijing Union University. His research interests include management science and engineering, and smart tourism.
Ruixin Wang is a lecturer of the School of Civil Aviation University of China. His research interests include personnel evacuation.
XiaoBing Hu is a professor of the School of Civil Aviation University of China. His research interests include complex network, artificial intelligence, air traffic management and integrated risk governance.

Abstract

Abstract: It is an important issue in the management of scenic passengers to regulate passenger flow during peak hours, especially in emergency situations. Based on passenger flow, routing environment and control measures of a given scenic spot, we built a multi-agent model of the scenic spot. It is a simulation system that mainly consists of two multi-agent methods, i.e., the cellular automata model and ripple-spreading algorithm, and reflects the emergency evacuation of passenger flow in the scenic spot under emergent events. This paper uses a famous Chinese scenic spot, the Summer Palace in Beijing as a research case, and conducts an empirical research. The result shows that the reported simulation system can help to effectively assess the evacuation effect of purpose-designed regulation measures according to passenger distribution and road network characteristics. Thus, this simulation system can provide effective decision-making support to scenic spot managers.

Key words: scenic area, multi-agent, cellular automata, ripple-spreading algorithm, passenger flow, emergence evacuation

Yingfei Zhang, Gongpeng Zhang, Ruixin Wang, and XiaoBing Hu. Multi-Agent based Simulation Modelling for Passenger Flow Emergency Evacuation in Scenic Spots [J]. Int J Performability Eng, 2020, 16(10): 1674-1684.

Add to citation manager EndNote|Reference Manager|ProCite|BibTeX|RefWorks

References

1. X. M.Zheng and C. W. Xie, “Analysis and Outlook of China's Tourism Security Situation from 2018 to 2019,” 2019
2. F. Bronner and R. De Hoog, “Crisis Resistance of Tourist Demand: The Importance of Quality of Life,” Joural of Travel Research, Vol. 55, No. 2, pp. 190-204, February 2016
3. G. Ellison and E. L. Glaeser, “Geographic Concentration in US Manufacturing Industries: A Dartboard Approach,” Journal of Political Economy, Vol. 105, No. 2, pp. 889-927, October 1997
4. X. J.Dai and D. S. Ding, “Correlation Fractal Dimension of Spatial Structure of Tourist Spots Systems—A Case Study in Nanjing City,” Resources Science, Vol. 28, No. 1, pp. 180-185, January 2006
5. J. Yuan, R. L. Yu, C. L. Liu,Y. Y. Jiang, “Research on Spatial Structure of National A-Grade Tourist Districts of Wuhan Metropolitan Area,” Economic Geography, Vol. 30, No. 2, pp. 324-328, February 2010
6. X. G. Mao, J. P. Song,W. Yu, “Space Structure and Its Evolution of A-Grade Tourist Attractions in Beijing,” Economic Geography, Vol. 31, No. 8, pp. 1381-1386, August 2011
7. L. M. Wu, et al., “The Spatiotemporal Evolution and Dynamic Mechanism of A-Grade Tourist Attractions in Jiangsu Province,” Economic Geography, Vol. 33, No. 8, pp. 158-164, August 2013
8. Q. N.Wang and G. N. Sun, “The Time Distribution Characteristics and the Influencing Factor of Passenger Flow in Traditional Scenic Spots——A Case of Langya Mountain Scenic Area,” Journal of Arid Land Resources and Environment, Vol. 29, No. 11, pp. 219-224, November 2015
9. B. F. Cai, Z. M. Tao, M. R. Zhang, T. Li,S. H. Lu, “Seasonal Fluctuation Characteristics and Determinants of Tourist Flows of Mount Tianmu Scenic Area,” Journal of Zhejiang A&F University, Vol. 32, No. 6, pp. 947-957, December 2015
10. P. C.Luo and M. F. Zhang, “The Temporal Characteristics of Tourist Flows to Danxia Landform Scenic Spots in Fujian Province and Its Influence Factors,” Scientia Geographica Sinica, Vol. 30, No. 3, pp. 377-383, June 2010
11. Y. Lei, et al., “Analysis to Temporal Characteristics of Tourist Flows on Jiuzhaigou World Natural Heritage,” Acta Scientiarum Naturalium Universitatis Pekinensis, Vol. 45, No. 1, pp. 171-177, January 2009
12. X. Y. Jiang, “Analysis of Fractal and Fractal Dimension of Tourist Flow in Jiuzhaigou Natural Reserve: A Case of National Day Golden Week,” Journal of Central South University of Forestry and Technology, Vol. 32, No. 11, pp. 144-148, November 2012
13. J. Li, et al., “A Study on the Spatial Move Mode of Tourist Flows in Scenic Area,” Systems Engineering, Vol. 11, pp. 236-246, November 2005
14. L. Lin, “A Study on the Tourist Flows in Mountain Resorts ——A Case Study in Huangshan Mountain,” Acta Geographica Sinica, Vol. 3, pp. 236-246, May 1994
15. X. Y. Yao, et al., “Analysis and Studies on the Time and Space Changes of Tourists Flow Volume in Wulingyuan Scenic Area and Its Characteristics,” Tourism Forum, Vol. 1, pp. 72-76, February 2006
16. X. T. Huang, “A Study on Temporal-Spatial Behavior Pattern of Tourists based on Time-Geography Science——A Case Study of Summer Palace, Beijing,” Tourism Tribune, Vol. 24, No. 6, pp. 82-87, June 2009
17. C. M. Li, Y. J. Wang, Y. Liu, R. C. Dong,J. Z. Zhao, “A Study of the Temporal-spatial Behavior of Tourists based on Georeferenced Photos,” Tourism Tribune, Vol. 28, No. 10, pp. 30-36, October 2013
18. P. Ge, W. M. Zheng, X. H. Xiao, Y. Q. Qiu,P. Y. Ren, “A Simulation Study based on the Regional Space-time Load Balancing of Jiuzhaigou,” Journal of Industrial Engineering and Engineering Management, Vol. 27, No. 2, pp. 99-106, April 2013
19. X. Y.Jiang and P. Y. Ren, “On Model Construction and Analysis of Spatial-Temporal Separate Navigation Management During Eco-Tour Peak Seasons at Nature Reserve Areas,” Tourism Science, Vol. 26, No. 4, pp. 17-25, August 2012
20. R. Z.Wang and W. Y. Miao, “Research on the Internal Queuing Phenomenon in Large Tourist Attractions based on M/M/n Queuing Theory,” Reform of Economic System, Vol. 3, pp. 177-180, May 2012
21. G. E. Zhu, H. Li, Z. H. Zhao,J. T. Li, “Modeling and Multi-Objective Optimization for Queuing System with QuickPass,” Journal of Henan Normal University (Natural Science Edition), Vol. 40, No. 3, pp. 21-23, May 2012
22. B. T. Low, C. H. Cheng, K. F. Wong,J. Motwani, “An Expert Advisory System for the Tourism Industry,” Expert Systems with Applications, Vol. 11, No. 1, pp. 65-77, June 1996
23. D. Martin, A. Alzua,C. Lamsfus, “A Contextual Geofencing Mobile Tourism Service,” Information and Communication Technologies in Tourism, 2011
24. H. Wen, Y. Q. Xu,L. J. Wan, “Design of Intelligent Guide Service Platform based on the Beidou Navigation System,” Electronic Design Engineering, Vol. 21, No. 5, pp. 103-105, March 2013
25. J. H. Wang, “Research on the Personnel Evacuation Simulation Model for Large-Scale Stadium,” in Proceedings of the 2017 7th International Conference on Mechatronics, Computer and Education Information (MCEI 2017), 2017
26. G. Z.Jin and Z. Yu, “Overview of Personnel Evacuation Models,” Industrial and Science Tribune, Vol. 13, No. 13, pp. 135-136, July 2014
27. D. Helbing, I. J. Farkas, P. Molnar,T. Vicsek, “Simulation of Pedestrian Crowds in Normal and Evacuation Simulation,” 2001
28. N. Li, “Agent-based Simulation Modeling of Visitor Behaviors at Tourism Attractions: The Case of the Summer Palace, Beijing,” Tourism Tribune, Vol. 29, No. 11, pp. 62-72, November 2014
29. Y. Zhou, “Simulation Research on Evacuation Algorithm in Emergency State,” Science and Technology and Innovation, Vol. 2009, No. 8, pp. 12-14+18, April 2019
30. Z. R. Jin, et al., “Evacuation Simulation in Narrow Passage Under Fire Scenario based on Cellular Automaton,” Journal of Tongji University (Natural Science), Vol. 46, No. 8, pp. 1026-1034, August 2018
31. W. N. Liu, et al., “Pedestrian Evacuation Model based on CA-IAFSA Algorithm,” Computer Systems and Applications, Vol. 28, No. 5, pp. 131-136, May 2019
32. H. D. Feng, et al., “Pedestrian Evacuation Simulation Research based on Cellular Automata,” Construction Science and Technology, Vol. 7, pp. 64-66, April 2017
33. H. Yue, C. F. Shao,Z. S. Yao, “Pedestrian Evacuation Flow Simulation based on Cellular Automata,” Acta Physica Sinica, Vol. 58, No. 7, pp. 4523-4530, July 2009
34. C. S. Lv, et al., “Fire Evacuation Model based on Motor Schema and Cellular Automaton,” Journal of Tsinghua University (Science and Technology), Vol. 12, pp. 2163-2167, December 2007
35. D. L. Zhao, “Cellular Automata Simulation on Special Human Behavior of Occupant Evacuation in Emergency,” University of Science and Technology of China, 2007
36. L. H.Chen and Y. R. Deng, “Research on Large Building Escape Scheme based on Game Theory and Dijkstra Algorithm,” Digital Technology and Application, Vol. 37, No. 7, pp. 125-127+130, September 2019
37. S. Russell and P.Norvig, “Artifical Intelligence: A Modern Approach,” Prentice Hall, New Jersey, ISBN 0-13-604259-7, 2009
38. E. W. Dijkstra, “A Note on Two Problems in Connexion with Graphs,”Numerische Mathematic, Vol. 1, pp. 269-271, 1959
39. P. E. Hart, et al., “Correction to “A Formal Basis for the Heuristic Determination of Minimum Cost Paths,”” IEEE Transactions on Systems Science and Cybernetics, Vol. 4, No. 2, pp. 100-107, December 1972
40. M. Sniedovich, “Dijkstra's Algorithm Revisited: The Dynamic Programming Connexion,” Control and Applications, Vol. 49, No. 1, pp. 599-620, July 2005
41. D. M.Lei and X. P. Yan, “Multi-Objective Intelligent Optimization Algorithm and Its Application,” Science Press, 2009
42. X. B. Hu, et al., “Deterministic Agent-based Path Optimization by Mimicking the Spreading of Ripples,” Evolutionary Computation, Vol. 24, No. 2, pp. 319-346, August 2016

[1]	Harinee S and Anand Mahendran. Secure ECG Signal Transmission for Smart Healthcare [J]. Int J Performability Eng, 2021, 17(8): 711-721.
[2]	Ankur Bhardwaj, Sanmukh Kaur, A.P. Shukla, and Manoj Shukla. Design and Analysis of Dual Transition Function Cellular Automata-based Filter of Brachial Plexus Ultrasound Images [J]. Int J Performability Eng, 2021, 17(11): 955-965.
[3]	Man Zhao, Zhao Chen, and Hui Li. Multi-Agent Data Collection and Processing based on SNMP / XML [J]. Int J Performability Eng, 2020, 16(9): 1424-1433.
[4]	Honghua Sun, Hongxia Chen, and Chunwei Li. Reliability Modeling and Analysis of Complex Multi-State Systems based on Weighted Triangular Fuzzy Numbers T-S Fault Tree [J]. Int J Performability Eng, 2019, 15(6): 1662-1671.

Multi-Agent based Simulation Modelling for Passenger Flow Emergency Evacuation in Scenic Spots

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 4

Recommended 0