The earthquake which struck Eastern Japan in 2011 caused many casualties. The ratio of the mode of evacuation in areas damaged by the earthquake varied depending on geographical conditions, but cars were the primary mode in many areas. Although the Japanese government has provided guidelines to assist evacuation during a natural disaster, the disaster in 2011 demonstrated that the behavior of refugees did not adhere to these guidelines. This study analyzes refugees’ behavior during evacuations using a dataset gathered through surveys of refugees in 2011. By analyzing their evacuation speed and distance based on their geographical conditions, the necessary distance and available distance for their evacuation are calculated in this study, following which an optimized distance for evacuation is derived. Analyzing various modes of evacuation, such as walking, bicycling, and car travel, this study identifies thresholds for an efficient mode of evacuation based on evacuation distance. In conclusion, this study finds that a walking-based evacuation plan is necessary in most areas, whereas vehicles are required in areas where it is impossible to evacuate by walking.

1. [1] National Police Agency, https://www.npa.go.jp [accessed November 12, 2012]
2. [2] Metropolitan Police Department, https://www.keishicho.metro.tokyo.jp [accessed November 12, 2012]
3. [3] S. Wegscheider et al., “Generating Tsunami Risk Knowledge at Community Level as a Base for Planning and Implementation of Risk Reduction Strategies,” Natural Hazards and Earth System Sciences, Vol.11, No.2, pp. 249-258, 2011.
4. [4] T. Charnkol and Y. Tanaboriboon, “TSUNAMI EVACUATION BEHAVIOR ANALYSIS: One Step of Transportation Disaster Response,” IATSS Research, Vol.30, No.2, pp. 83-96, 2006.
5. [5] T. Limanond et al., “Decision on Tsunami Evacuation Route in Tourism Area: A Case Study of Had Patong, Phuket,” J. of the Eastern Asia Society for Transportation Studies, Vol.9, pp. 16-30, 2011.
6. [6] Ministry of Land, Infrastructure, Transport and Tourism (MLIT), https://www.mlit.go.jp [accessed November 12, 2012]
7. [7] Federal Emergency Management Agency (FEMA), https://www.fema.gov [accessed November 15, 2012]
8. [8] National Fire Agency (NFA), https://www.nfa.go.kr [accessed November 12, 2012]
9. [9] Bureau of Citizens, Culture and Sports, Tokyo Metropolitan Government, https://www.seikatubunka.metro.tokyo.jp [accessed November 13, 2012]
10. [10] MLIT, “Survey Report of Reconstructing Method for Damaged City by Tsunami Disaster,” 2012.
11. [11] Geospatial Information Authority of Japan (GSI), https://www.gsi.go.jp [accessed November 13, 2012]
12. [12] Statistics Bureau of Japan, https://www.stat.go.jp [accessed November 13, 2012]
13. [13] M. Inoguchi, T. Sekikawa, and K. Tamura, “Developing a Web-Based Supporting Application for Individual Evacuation Plans Through Hazard Risk and Geographical Analyses,” J. Disaster Res., Vol.12, No.1, pp. 6-16, 2017.
14. [14] J. Lee, K. Hatoyama, and H. Ieda, “Formulation of Tsunami Evacuation Strategy to Designate Routes for the Car Mode – Lessons from the Three Cities in Tohoku Area, Japan,” Proc. of the Eastern Asia Society for Transportation Studies, Vol.9, 2013.
15. [15] V. J. Blue and J. L. Adler, “Cellular Automata Microsimulation for Modeling Bi-Directional Pedestrian Walkways,” Transportation Research Part B: Methodological, Vol.35, No.3, pp. 293-312, 2001.
16. [16] C. Burstedde, K. Klauck, A. Schadschneider, and J. Zittartz, “Simulation of Pedestrian Dynamics Using a Two-Dimensional Cellular Automation,” Physica A: Statistical Mechanics and its Applications, Vol.295, Nos.3-4, pp. 507-525, 2001.
17. [17] K. Nagel, “From Particle Hopping Models to Traffic Flow Theory,” Transportation Research Record: J. of the Transportation Research Board, Vol.1644, No.1, pp. 1-9, 1998.
18. [18] A. Schadschneider, “Cellular Automation Approach to Pedestrian Dynamics – Theory,” arXiv: cond-mat/0112117, 2001.
19. [19] G. G. Løvås, “Modeling and Simulation of Pedestrian Traffic Flow,” Transportation Research Part B: Methodological, Vol.28, No.6, pp. 429-443, 1994.
20. [20] S. J. Yuhaski, Jr. and J. M. Smith, “Modeling Circulation Systems in Buildings Using State Dependent Queueing Models,” Queueing Systems, Vol.4, No.4, pp. 319-338, 1989.
21. [21] D. Helbing and P. Molnar, “Social Force Model for Pedestrian Dynamics,” Physical Review E, Vol.51, No.5, pp. 4282-4286, 1995.
22. [22] S. Okazaki, “A Study of Pedestrian Movement in Architectural Space: Part 1 Pedestrian Movement by the Application of Magnetic Models,” Trans. of the Architectural Institute of Japan, Vol.283, pp. 111-119, 1979 (in Japanese).
23. [23] https://www.bousai.metro.tokyo.jp [accessed November 15, 2012]
24. [24] N. Wood, J. Jones, J. Peters, and K. Richards, “Pedestrian Evacuation Modeling to Reduce Vehicle Use for Distant Tsunami Evacuations in Hawai‘i,” Int. J. of Disaster Risk Reduction, Vol.28, pp. 271-283, 2018.
25. [25] M. Wooldridge, “An Introduction to MultiAgent Systems,” 2nd Edition, Wiley & Sons, 2009.
26. [26] Y. Hu, X. Liu, F. Wang, and C. Cheng, “An Overview of Agent-Based Evacuation Models for Building Fires,” Proc. of 2012 9th IEEE Int. Conf. on Networking, Sensing and Control, pp. 382-386, 2012.
27. [27] J. Girod and J. Dugdale, “The Psycho-Social Theories in Emergency Evacuation Agent-Based Simulation,” IRL Report, École nationale supérieure d’informatique et de mathématiques appliquées (ENSIMAG), Institut polytechnique de Grenoble (Grenoble INP), 2012.
28. [28] B. E. Aguirre, S. El-Tawil, E. Best, K. B. Gill, and V. Fedorov, “Contributions of Social Science to Agent-Based Models of Building Evacuation,” Contemporary Social Science, Vol.6, No.3, pp. 415-432, 2011.
29. [29] B. Maury, A. Roudneff-Chupin, F. Santambrogio, and J. Venel, “Handling Congestion in Crowd Motion Modeling,” arXiv: 1101.4102, 2011.
30. [30] X. Pan, C. S. Han, K. Dauber, and K. H. Law, “A Multi-Agent Based Framework for the Simulation of Human and Social Behaviors During Emergency Evacuations,” AI & Society, Vol.22, No.2, pp. 113-132, 2007.
31. [31] A. Conca and M. G. Vignolo, “Pedestrian Flow Analysis in Emergency Evacuation,” 15th Edition of the Euro Working Group on Transportation Int. Scientific Conf., 2012.
32. [32] J.-H. Wang, S.-M. Lo, J.-H. Sun, Q.-S. Wang, and H.-L. Mu, “Qualitative Simulation of the Panic Spread in Large-Scale Evacuation,” Simulation, Vol.88, No.12, pp. 1465-1474, 2012.
33. [33] T. Takabatake, K. Fujisawa, M. Esteban, and T. Shibayama, “Simulated Effectiveness of a Car Evacuation from a Tsunami,” Int. J. of Disaster Risk Reduction, Vol.47, Article No.101532, 2020.
34. [34] D. Helbing, I. Farkas, and T. Vicsek, “Simulating Dynamical Features of Escape Panic,” Nature, Vol.407, No.6803, pp. 487-490, 2000.
35. [35] V. A. Oven and N. Cakici, “Modelling the Evacuation of a High-Rise Office Building in Istanbul,” Fire Safety J., Vol.44, No.1, pp. 1-15, 2009.
36. [36] S. P. Hoogendoorn and W. Daamen, “Pedestrian Behavior at Bottlenecks,” Transportation Science, Vol.39, No.2, pp. 147-159, 2005.
37. [37] T. I. Lakoba, D. J. Kaup, and N. M. Finkelstein, “Modifications of the Helbing-Molnár-Farkas-Vicsek Social Force Model for Pedestrian Evolution,” Simulation, Vol.81, No.5, pp. 339-352, 2005.
38. [38] V. Ha and G. Lykotrafitis, “Agent-Based Modeling of a Multi-Room Multi-Floor Building Emergency Evacuation,” Physica A: Statistical Mechanics and its Applications, Vol.391, No.8, pp. 2740-2751, 2012.
39. [39] S. M. Lo, H. C. Huang, P. Wang, and K. K. Yuen, “A Game Theory Based Exit Selection Model for Evacuation,” Fire Safety J., Vol.41, No.5, pp. 364-369, 2006.
40. [40] X. Pan, “Computational Modeling of Human and Social Behaviors for Emergency Egress Analysis,” Ph.D. thesis, Stanford University, 2006.
41. [41] E. Bonabeau, “Agent-Based Modeling: Methods and Techniques for Simulating Human Systems,” Proc. of the National Academy of Sciences of the United States of America, Vol.99, No.Suppl_3, pp. 7280-7287, 2002.
42. [42] G. Antonini, M. Bierlaire, and M. Weber, “Discrete Choice Models of Pedestrian Walking Behavior,” Transportation Research Part B: Methodological, Vol.40, No.8, pp. 667-687, 2006.
43. [43] S. Sharma, “Simulation and Modeling of Group Behavior During Emergency Evacuation,” 2009 IEEE Symp. on Intelligent Agents, pp. 122-127, 2009.
44. [44] M. Muramatsu, T. Irie, and T. Nagatani, “Jamming Transition in Pedestrian Counter Flow,” Physica A: Statistical Mechanics and its Applications, Vol.267, Nos.3-4, pp. 487-498, 1999.
45. [45] J. G. Doheny and J. L. Fraser, “MOBEDIC – A Decision Modelling Tool for Emergency Situations,” Expert Systems with Applications, Vol.10, No.1, pp. 17-27, 1996.
46. [46] H. Klüpfel, “A Cellular Automaton Model for Crowd Movement and Egress Simulation,” Ph.D. thesis, University of Duisburg-Essen, 2003.
47. [47] C. Saloma, G. J. Perez, G. Tapang, M. Lim, and C. Palmes-Saloma, “Self-Organized Queuing and Scale-Free Behavior in Real Escape Panic,” Proc. of the National Academy of Sciences of the United States of America, Vol.100, No.21, pp. 11947-11952, 2003.
48. [48] S. Gwynne, E. R. Galea, P. J. Lawrence, and L. Filippidis, “Modelling Occupant Interaction with Fire Conditions Using the buildingEXODUS evacuation model,” Fire Safety J., Vol.36, No.4, pp. 327-357, 2001.
49. [49] X. Zheng and M. Liu, “Forecasting Model for Pedestrian Distribution Under Emergency Evacuation,” Reliability Engineering & System Safety, Vol.95, No.11, pp. 1186-1192, 2010.
50. [50] M. Madireddy, D. J. Medeiros, and S. Kumara, “An Agent Based Model for Evacuation Traffic Management,” Proc. of the 2011 Winter Simulation Conf. (WSC), pp. 222-233, 2011.
51. [51] A. E. Radwan, A. G. Hobeika, and D. Sivasailam, “Computer Simulation Model for Rural Network Evacuation Under Natural Disasters,” ITE J., Vol.55, No.9, pp. 25-30, 1985.
52. [52] G. Lämmel et al., “Emergency Preparedness in the Case of a Tsunami – Evacuation Analysis and Traffic Optimization for the Indonesian City of Padang,” W. W. F. Klingsch, C. Rogsch, A. Schadschneider, and M. Schreckenberg (Eds.), “Pedestrian and Evacuation Dynamics 2008,” pp. 171-182, Springer, 2010.
53. [53] G. Proulx, “Evacuation Time and Movement in Apartment Buildings,” Fire Safety J., Vol.24, No.3, pp. 229-246, 1995.
54. [54] T. Sugimoto, H. Murakami, Y. Kozuki, K. Nishikawa, and T. Shimada, “A Human Damage Prediction Method for Tsunami Disasters Incorporating Evacuation Activities,” Natural Hazards, Vol.29, No.3, pp. 587-602, 2003.
55. [55] F. Makinoshima, F. Imamura, and Y. Abe, “Behavior from Tsunami Recorded in the Multimedia Sources at Kesennuma City in the 2011 Tohoku Tsunami and its Simulation by Using the Evacuation Model with Pedestrian – Car Interaction,” Coastal Engineering J., Vol.58, No.4, 28pp., doi: 10.1142/S0578563416400234, 2016.
56. [56] E. J. I. Apatu et al., “The September 29, 2009 Earthquake and Tsunami in American Samoa: A Case Study of Household Evacuation Behavior and the Protective Action Decision Model,” EGU General Assembly 2012, p. 101, 2012.
57. [57] E. R. Galea, M. Sauter, S. Deere, and L. Filippidis, “Investigating the Impact of Culture on Evacuation Behavior – A Turkish Data-Set,” Fire Safety Science, Vol.10, pp. 709-722, 2011.
58. [58] N.-Y. Yun and M. Hamada, “Evacuation Behaviors in the 2011 Great East Japan Earthquake,” J. Disaster Res., Vol.7, No.sp, pp. 458-467, 2012.
59. [59] http://fukkou.csis.u-tokyo.ac.jp [accessed November 1, 2012]
60. [60] Japan Meteorological Agency (JMA), www.jma.go.jp [accessed November 1, 2012]
61. [61] J. Lee, M. Heo, I. Park, and J.-H. Chung, “The Rotated Hexagonal Lattice Model for Pedestrian Flows,” J. of the Eastern Asia Society for Transportation Studies, Vol.8, pp. 1357-1367, 2010.