DOI QR코드

DOI QR Code

An Evacuation Route Assignment for Multiple Exits based on Greedy Algorithm

탐욕 알고리즘 기반 다중 출구 대피경로 할당

  • 이민혁 (서울시립대학교 공간정보공학과) ;
  • 남현우 (서울시립대학교 공간정보공학과) ;
  • 전철민 (서울시립대학교 공간정보공학과)
  • Received : 2016.02.23
  • Accepted : 2016.03.22
  • Published : 2016.03.31

Abstract

Some studies were conducted for the purpose of minimizing total clearance time for rapid evacuation from the indoor spaces when disaster occurs. Most studies took a long time to calculate the optimal evacuation route that derived minimum evacuation time. For this reason, this study proposes an evacuation route assignment algorithm that can shorten the total clearance time in a short operational time. When lots of exits are in the building, this algorithm can shorten the total clearance time by assigning the appropriate pedestrian traffic volume to each exit and balances each exit-load. The graph theory and greedy algorithm were utilized to assign pedestrian traffic volume to each exit in this study. To verify this algorithm, study used a cellular automata-based evacuation simulator and experimented various occupants distribution in a building structure. As a result, the total clearance time is reduced by using this algorithm, compared to the case of evacuating occupants to the exit within shortest distance. And it was confirmed that the operation takes a short time In a large building structure.

재난 발생 시, 실내 공간에서의 신속한 대피를 위해 총 대피시간 최소화를 목적으로 일부 연구들이 진행되었다. 하지만 대부분의 연구가 총 대피시간이 최소화되는 최적 대피경로를 산출하는데 오랜 연산시간이 소요되어 실제 재난 상황에 적용하기 어렵다는 한계를 가지고 있다. 이에 본 연구는 짧은 연산시간으로 총 대피시간을 단축시킬 수 있는 대피경로 할당 알고리즘을 제안하고자 한다. 대피경로 할당 알고리즘은 다수의 출구가 존재하는 건물에서 대규모 인원 대피 시, 각 출구에 적절하게 대피인원을 할당하여 출구들의 교통 정체 상황을 균형적으로 유지함으로써 총 대피시간을 단축시키는 알고리즘이다. 각 출구에 대피인원을 할당하는 방법은 그래프 이론을 기반으로 탐욕 알고리즘의 접근방식을 활용하였다. 본 연구에서는 알고리즘의 검증을 위해 cellular automata 기반 대피 시뮬레이터를 이용하였으며 실제 건물과 유사한 구조에서 다양한 인원분포를 적용한 뒤 실험을 수행하였다. 결과적으로 최단거리 출구 대피보다 알고리즘을 적용하였을 때 총 대피시간이 감소되었고 대형 건물 구조에서도 짧은 연산시간이 소요되는 것을 확인하였다.

Keywords

References

  1. Cormen, T. H., Leiserson, C. E., Rivest, R. L. and Stein, C., 1990, Introduction to Algorithms, MIT Press, p. 329.
  2. Chalmet, L. G., Francis, R. L. and Saunders, P. B., 1982, Network models for building evacuation, Fire Technology, Vol. 18, No. 1, pp. 90-113. https://doi.org/10.1007/BF02993491
  3. Chen, P. H. and Feng, F., 2009, A fast flow control algorithm for real-time emergency evacuation in large indoor areas, Fire Safety Journal, Vol. 44, No. 5, pp. 732-740. https://doi.org/10.1016/j.firesaf.2009.02.005
  4. Fruin, J. J., 1992, Designing for pedestrians, Public Transportation United States, http://ntl.bts.gov/DOCS/11877/Chapter_8.html
  5. Gwynne, S., Galea, E. R., Owen, M., Lawrence, P. J. and Filippidis, L., 1999, A review of the methodologies used in the computer simulation of evacuation from the built environment, Building and Environment, Vol. 34, No. 6, pp. 741-749. https://doi.org/10.1016/S0360-1323(98)00057-2
  6. Hamacher, H. W. and Tjandra, S. A., 2001, Mathematical modelling of evacuation problems: A state of art, Fraunhofer-Institut fur Techno-und Wirtschaftsmathematik, Fraunhofer (ITWM), pp. 1-44.
  7. Kim, S., Shekhar, S. and Min, M., 2008, Contraflow transportation network reconfiguration for evacuation route planning, Knowledge and Data Engineering, IEEE Transactions on, Vol. 20, No. 8, pp. 1115-1129. https://doi.org/10.1109/TKDE.2007.190722
  8. Kisko, T. M. and Francis, R. L., 1985, EVACNET+: a computer program to determine optimal building evacuation plans, Fire Safety Journal, Vol. 9, No. 2, pp. 211-220. https://doi.org/10.1016/0379-7112(85)90009-8
  9. Kuligowski, E. D., Peacock, R. D. and Hoskins, B. L., 2005, A review of building evacuation models, MD: US Department of Commerce, National Institute of Standards and Technology, pp. 1-29.
  10. Kwak, S. Y., Nam, H. W. and Jun, C. M., 2012, An Optimal Model for Indoor Pedestrian Evacuation considering the Entire Distribution of Building Pedestrians, Journal of the Korean Society for Geospatial Information Science, Vol. 20, No. 2, pp. 23-29.
  11. Lovas, G. G., 1995, On performance measures for evacuation systems, European Journal of Operational Research, Vol. 85, No. 2, pp. 352-367 https://doi.org/10.1016/0377-2217(94)00054-G
  12. Li, Q., Feng, Z., Li, Q. and Zong, X., 2010, Multiobjective evacuation route assignment model based on genetic algorithm, Proc. of the 18th International Conference, Geoinformatics, pp. 1-5.
  13. Lu, Q., George, B. and Shekhar, S., 2005, Capacity constrained routing algorithms for evacuation planning: A summary of results, Advances in spatial and temporal databases, Springer Berlin Heidelberg, pp. 291-307.
  14. Nam, H. W., Kwak, S. Y. and Jun, C. M., 2014, Developing a Cellular Automata-based Pedestrian Model Incorporating Physical Characteristics of Pedestrians, Journal of Korea Spatial Information Society, Vol. 22, No. 2, pp. 53-62.
  15. Pursals, S. C. and Garzon, F. G., 2009, Optimal building evacuation time considering evacuation routes, European Journal of Operational Research, Vol. 192, No. 2, pp. 692-699. https://doi.org/10.1016/j.ejor.2007.10.004
  16. Pursals, S. C. and Garzon, F. G., 2013, Building evacuation: Principles for the analysis of basic structures through dynamic flow networks, Journal of Industrial Engineering and Management, Vol. 6, No. 4, pp. 831-859.
  17. Wang, X. and Liu, H., 2012, An evacuation algorithm for large buildings, Proc. of the 10th World Congress, Intelligent Control and Automation (WCICA), pp. 2497-2502
  18. Xie, J., Li, Q., Wan, Q. and Li, X., 2014, Near optimal allocation strategy for making a staged evacuation plan with multiple exits, Annals of GIS, Vol. 20, No. 3, pp. 159-168. https://doi.org/10.1080/19475683.2014.942363
  19. Yusoff, M., Ariffin, J. and Mohamed, A., 2008, Optimization approaches for macroscopic emergency evacuation planning: a survey, Proc. of the ITSim 2008, Information Technology, Vol. 3, pp. 1-7.