Evaluation of an efficient evacuation route search system within an establishment using the D star algorithm
DOI:
https://doi.org/10.26439/ciis2019.5502Keywords:
evacuation systems, search algorithms, D star algorithm, shortest evacuation routes, dynamic obstaclesAbstract
Natural disasters such as earthquakes have aroused great interest among several authors around the world, giving rise to different solutions related to evacuation systems. This research presents the importance of implementing an intelligent evacuation system that recognizes the shortest evacuation route in a real earthquake. Based on this, the research aimed to build a simulator to find the shortest evacuation route using the D star algorithm. In this evaluation, the experimental time taken by the algorithm to find an efficient evacuation route was measured within establishments of different sizes with varying quantities of initial obstacles and varying quantities of obstacles placed in real time. The results of the simulator were favorable since it found an efficient route in 22 milliseconds and a recalculated route in 3 milliseconds for the cases in which obstacles interfered with the initial route.
Downloads
References
Cornejo, M. B. (6 de junio del 2015). 60 % de instituciones sin plan para evacuar. Correo. Recuperado de https://diariocorreo.pe/peru/60-de-instituciones-sin-plan-para-evacuar-592886/
Haghani, M., y Sarvi, M. (2016). Human exit choice in crowded built environments: Investigating underlying behavioural differences between normal egress and emergency evacuations. Fire Safety Journal, 85, 1-9. doi:10.1016/J.FIRESAF.2016.07.003
Hridi, A. P., Das, D., Anjum, M. M., y Das, T. (2016). Faster evacuation after disaster: Finding alternative routes using probable human behavior. ACM DEV’16, Proceedings of the 7th Annual Symposium on Computing for Development, 1-4. doi:10.1145/3001913.3006632
Iizuka, Y., y Iizuka, K. (2015). Disaster evacuation assistance system based on multi-agent cooperation. HICSS’15: Proceedings of the 2015 48th Hawaii International Conference on System Sciences, 173-181. doi:10.1109/HICSS.2015.30
Kocay, W., y Kreher, D. L. (s. f.). Graphs, algorithms, and optimization. Recuperado de https://scholar.google.com.pe/scholar?q=Kocay,+W.,+y+Kreher,+D.+L.+(s.+f.).+Graphs,+algorithms,+and+optimization.&hl=es&as_sdt=0&as_vis=1&oi=scholart
Koo, J., Kim, Y. S., Kim, B.-I., y Christensen, K. M. (2013). A comparative study of evacuation strategies for people with disabilities in high-rise building evacuation. Expert Systems with Applications: An International Journal, 40(2), 408-417. doi:10.1016/j.eswa.2012.07.017
Masudur Rahman Al-Arif, S. M., Iftekharul Ferdous, A. H. M., y Hassan Nijami, S. (2012). Comparative study of different path planning algorithms: A water based rescue system. International Journal of Computer Applications, 39(5), 975-8887. Recuperado de https://pdfs.semanticscholar.org/e59d/c7af0604fced7d124d4f755917725c7892e9.pdf
Microsoft. (s. f.). System. Diagnostics Namespace. Recuperado de https://docs.microsoft.com/en-us/dotnet/api/system.diagnostics?view=netframework-4.8
Pelechano, N., y Badler, N. (2006). Modeling Crowd and Trained Leader Behavior during Building Evacuation. IEEE Computer Graphics and Applications, 26(6), 80-86. doi:10.1109/MCG.2006.133
Stentz, A. (1994). Optimal and efficient path planning for partially-known environments. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA’94), 4, 3310-3317. Recuperado de https://www.ri.cmu.edu/publications/optimal-and-efficient-path-planning-for-partially-known-environments/
Thulasiraman, K., y Swamy, M. N. S. (2011). Basic concepts. En Thulasiraman y M. N. S. Swamy, Graphs: Theory and Algorithms (pp. 1-30). John Wiley & Sons. doi:10.1002/9781118033104.ch1
Ying, Z., Zi-min, Z., y Jian, C. (2017). EvacAgent: A Building Emergency Evacuation Simulation Model Based on Agent. AIACT’17: Proceedings of the 2017 International Conference on Artificial Intelligence, Automation and Control Technologies, 1-7. doi:10.1145/3080845.3080872
