Implementation of a Fuzzy Multi-Agent Model for City Evacuation Traffic Management Using Probabilistic Automata
Subject Areas : electrical and computer engineering
A. R. Karbaschian
1
,
Saeed Setayeshi
2
,
arash Sharifi
3
1 -
2 -
3 - Science and Research Branch, Islamic Azad University, Tehran, Iran
Keywords: Traffic management agent base simulation fuzzy system multi-agent system probabilistic automata,
Abstract :
Because of importance of quickly city evacuation during natural or unnatural happenings, it’s essential to apply an optimized control policy to prevent congestion and stop of vehicles. Existing works for traffic management in critical conditions have paid little attention to artificial intelligence approaches. Therefore, the main goal of authors in this research is offering an optimized and intelligent control policy for city evacuation traffic. This policy uses fuzzy inference system for decision making of each agent and probabilistic automata for optimizing performance of agents as for their preferences during time. To check degree of success of offered control policy, Agent Base Simulation in RStudio and Netlogo environments have been implemented using RNetlogo and frbs packages in R language. Simulation results show traffic load distribution, using maximum capacity of roads and congestion prevention by suggested policy. With regard to communication technologies such as GPS, smart phones, automatic tax payment systems in roads and … that have been developed in recent years, it is also possible to implement suggested critical traffic control policy in real world.
[1] V. McKinney, 2007, Sea Level Rise and the Future of the Netherlands, Accessed March 10, 2011, http://www1.american.edu/ted/ice/dutch-sea.html
[2] K. Caruso, 2005, Welcome to Rita Info.com, Accessed March 10, 2011, http://www.ritainfo.com/
[3] S. Kim, S. Shekhar, and M. Min, "Contraflow transportation network reconfiguration for evacuation route planning," IEEE Trans. on Knowledge and Data Engineering, vol. 20, no. 8, pp. 1-15, Aug. 2008.
[4] Y. Liu, An Intelligent Optimal Control System for Emergency Evacaution, Ph. D Thesis, University of Maryland, 2007.
[5] M. Madireddy, D. J. Medeiros, and S. Kumara, "An agent based model for evacuation traffic management," in Proc. of the 2011 Winter Simulation Conf., 2011.
[6] J. Varney, 2008, Contraflow Evacuation a Hurricane Triumph, Accessed March 11, 2011, http://www.nola.com/hurricane/areweready2006/tp/index.ssf?/hurricane/areweready2006/stories/contraflow.html
[7] E. Bonabeau, "Agent - based modeling: methods and techniques for simulating human systems," PNAS vol. 99 no. Suppl 3, May 14, 2002.
[8] F. B. Zhan and X. Chen, "Agent - based modeling and evacuation planning," Geospatial Technologies and Homeland Security, vol. 94, pp. 189-208, 2008.
[9] T. Cova and J. P. Johnson, "A network flow model for lane - based evacuation routing," Transportation Research Part A: Policy and Practice, vol. 37, no. 7, pp. 579-604, 2003.
[10] S. Kim, B. George, and S. Shekhar, "Evacuation route planning: scalable heuristics," in Proc. of the 2007 Int. Sym. on Advances in Geographic Information Systems, Seattle, WA, US, 2007.
[11] H. W. Hamacher and S. A. Tjandra, "Mathematical modeling of evacuation problems: a state of the art," Pedestrian and Evacuation Dynamics, pp. 227-266, 2002.
[12] A. K. Rathi and R. S. Solanki, "Simulation of traffic flow during emergency evacuations: a microcomputer based modeling system," in Proc. of the 1993 Winter Simulation Conf., pp. 1250-1258, 12-15 Dec. 1993.
[13] C. M. Macal and M. J. North, "Agent-based modeling and simulation: desktop ABMS," in Proc. INFORMS Winter Simulation Conf., pp. 95-106, 2007.
[14] B. Zhang, W. Kin, and S. V. Ukkusuri, "Agent - based modeling for household level hurricane evacuation," in Proc. of the 2009 Winter Simulation Conf., pp. 2778-2784, 2009.
[15] A. Shendarkar and K. Vasudevan, "Crowd simulation for emergency response using BDI agent based on virtual reality," in Proc. of the 2006 Winter Simulation Conf., pp. 545-553, 2006.
[16] B. Wolshon, "One-way-out: contraflow freeway operation for hurricane evacuation," Natural Hazards Review, vol. 2, no. 3, pp. 105-112, 2001.
[17] X. Chen and F. Zhan, "Agent - based modelling and simulation of urban evacuation: relative effectiveness of simultaneous and staged evacuation strategies," J. of the Operational Research Society, vol. 59, no. 1, pp. 25-33, Jan. 2008.
[18] X. Chen and F. B. Zhan, "Agent - based modeling and simulation of urban evacuation: relative effectiveness of simultaneous and staged evacuation strategies," Presented at the 83rd Annual Meeting of the Transportation Research Board, Washington, D.C. 2004.
[19] H. Tuydes, Network Traffic Management under Disaster Conditions, Ph. D Thesis, Northwestern University, 2005.
[20] H. Tuydes and A. Ziliaskopoulos, "Tabu - based heuristic approach for optimization of network evacuation contraflow," Transportation Research Record: J. of the Transportation Research Board, vol. 1964, no. 1, pp. 157-168, 2006.
[21] S. Kim and S. Shekhar, "Contraflow network reconfiguration for evacuation planning: a summary of results," in Proc. 13th ACM Symp. Advances in Geographic Information Systems, pp. 250-259, Nov. 2005.
[22] G. K. H. Pang, K. Takahashi, T. Yokota, and H. Takenaga, "Adaptive route selection for dynamic route guidance system based on fuzzy - neural approaches," IEEE Trans. on Vehicular Technology, vol. 48, no. 6, pp. 2028-2041, Nov. 1999.
[23] م. تشنهلب، نيما صفارپور و داريوش افيوني، سیستمهاي فازي و كنترل فازي، انتشارات دانشگاه صنعتي خواجه نصيرالدين طوسي، صص. 79-80، 1389. [24] http://www.rstudio.com/, Accessed Apr. 2013,
[25] http://www.r-project.org/, Accessed Apr. 2013,
[26] http://rnetlogo.r-forge.r-project.org/, Accessed Apr. 2013,
[27] U. Wilensky, 1999, NetLogo (and NetLogo User Manual), Center for Connected Learning and Computer Based Modeling, Northwestern University, http://ccl.northwestern.edu/netlogo/, Accessed Apr. 2013,
[28] L. S. Riza, C. Bergmeir, F. H. Triguero, and J. M. Benitez, frbs: Fuzzy rule-based systems, a package for R Language, http://cran.r-project.org/web/packages/frbs/index.html, Accessed Apr. 2013.
