×

A-RESCUE: an agent based regional evacuation simulator coupled with user enriched behavior. (English) Zbl 1364.90052

Summary: Household behavior and dynamic traffic flows are the two most important aspects of hurricane evacuations. However, current evacuation models largely overlook the complexity of household behavior leading to oversimplified traffic assignments and, as a result, inaccurate evacuation clearance times in the network. In this paper, we present a high fidelity multi-agent simulation model called A-RESCUE (Agent-based Regional Evacuation Simulator Coupled with User Enriched behavior) that integrates the rich activity behavior of the evacuating households with the network level assignment to predict and evaluate evacuation clearance times. The simulator can generate evacuation demand on the fly, truly capturing the dynamic nature of a hurricane evacuation. The simulator consists of two major components: household decision-making module and traffic flow module. In the simulation, each household is an agent making various evacuation related decisions based on advanced behavioral models. From household decisions, a number of vehicles are generated and entered in the evacuation transportation network at different time intervals. An adaptive routing strategy that can achieve efficient network-wide traffic measurements is proposed. Computational results are presented based on simulations over the Miami-Dade network with detailed representation of the road network geometry. The simulation results demonstrate the evolution of traffic congestion as a function of the household decision-making, the variance of the congestion across different areas relative to the storm path and the most congested O-D pairs in the network. The simulation tool can be used as a planning tool to make decisions related to how traffic information should be communicated and in the design of traffic management policies such as contra-flow strategies during evacuations.

MSC:

90B06 Transportation, logistics and supply chain management
90B20 Traffic problems in operations research
PDFBibTeX XMLCite
Full Text: DOI

References:

[1] Ahmed KI (1999) Modeling drivers’ acceleration and lane changing behavior. Doctoral dissertation, Massachusetts Institute of Technology
[2] Balakrishna R, Wen Y, Ben-Akiva M, Antoniou C (2008) Simulation-based framework for transportation network management for emergencies. Trans Res Record, J Transportation Research Board 2041:80-88 · doi:10.3141/2041-09
[3] Bish DR (2011) Planning for a bus-based evacuation. OR Spectr 33(3):629-654 · Zbl 1231.90077 · doi:10.1007/s00291-011-0256-1
[4] Cova TJ, Johnson JP (2003) A network flow model for lane-based evacuation routing. Transp Res A 37:579-604 · doi:10.1016/S0191-2615(02)00045-0
[5] Farver J (2005) Hybrid vehicle-centric route guidance. Ph.D. Dissertation, Massachusetts Institute Technol
[6] Flötteröd G, Chen Y, Nagel K (2012) Behavioral calibration and analysis of a large-scale travel microsimulation. Networks Spatial Econ 12(4):481-502 · Zbl 1332.90148 · doi:10.1007/s11067-011-9164-9
[7] Franzese O, Han LD (2001) Traffic modeling framework for hurricane evacuation. Internal report, Oak Ridge National Laboratory, Oak Ridge
[8] Gipps PG (1986) A model for the structure of lane-changing decisions. Transp Res B Methodol 20(5):403-414
[9] Han LD, Yuan F (2005) Evacuation modeling and operations using dynamic traffic assignment and most desirable destination approaches. Proceedings of the 84th Annual Meeting Transportation Research Board, Washington
[10] Hasan S, Ukkusuri S, Gladwin H, Murray-Tuite P (2011) A behavioral model to understand household level hurricane evacuation decision making. J Transp Eng 137(5):341-348 · doi:10.1061/(ASCE)TE.1943-5436.0000223
[11] Hasan S, Mesa-Arango R, Ukkusuri S (2013) A random-parameter hazard-based model to understand household evacuation timing behavior. Trans Res Part C: Emerging Technol 27:108-116 · doi:10.1016/j.trc.2011.06.005
[12] He X, Peeta S (2014) Dynamic resource allocation problem for transportation network evacuation. Networks Spatial Econ 14(3-4):505-530 · Zbl 1338.90079 · doi:10.1007/s11067-014-9247-5
[13] Herman R, Rothery RW (1963) Car-following and steady state flow. Theory Traffic Flow Symp Proc, 1-13
[14] Herman R, Montroll EW, Potts R, Rothery RW (1959) Traffic dynamics: analysis of stability in car-following. Operation Res 1(7):86-106 · Zbl 1414.90089 · doi:10.1287/opre.7.1.86
[15] Hobeika AG, Jamei B (1985) MASSVAC: a model for calculating evacuation times under natural disaster. Proceedings of the Computer Simulation in Emergency Planning Conference, La Jolla
[16] Hobeika AG, Kim C (1998) Comparison of traffic assignments in evacuation modeling. IEEE Trans Eng Manag 45(2):192-198 · doi:10.1109/17.669768
[17] Jha M, Moore K, Pashaie B (2004) Emergency evacuation planning with microscopic traffic simulation. Trans Res Record, J Trans Res Board 1886:40-48 · doi:10.3141/1886-06
[18] Klunder G, Terbruggen S, Mak J, Immers B (2009) Large-scale evacuation of the Randstand: evacuation simulations with the dynamic traffic assignment model Indy. Proceedings of the 1st International Conference on Evacuation Modeling and Management, The Hague
[19] Lindell MK, Prater CS (2007) Critical behavioral assumptions in evacuation time estimate analysis for private vehicles: examples from hurricane research and planning. J Urban Planning Dev 133(1):18-29 · doi:10.1061/(ASCE)0733-9488(2007)133:1(18)
[20] Lindell MK, Lu J-C, Prater CS (2005) Household decision making and evacuation in response to Hurricane Lili. Natural Hazards Rev 6(4):171-179 · doi:10.1061/(ASCE)1527-6988(2005)6:4(171)
[21] Lindell MK, Prater CS, Peacock WG (2007) Organizational communication and decision making for hurricane emergencies. Natural Hazards Rev 8(3):50-60 · doi:10.1061/(ASCE)1527-6988(2007)8:3(50)
[22] Lindell MK, Kang JE, Prater CS (2011) The logistics of household hurricane evacuation. Nat Hazards 58(3):1093-1109 · doi:10.1007/s11069-011-9715-x
[23] Macal CM, North MJ (2005) Tutorial on agent-based modeling and simulation. In Proceedings of the 2005 Winter Simulation Conference, eds. Kuhl ME, Steiger NM, Armstrong FB, Joines JA, 2-15. Piscataway, New Jersey: Institute of Electrical and Electronics Engineers, Inc
[24] Mahmassani HS (2001) Dynamic network traffic assignment and simulation methodology for advanced systems management applications. Networks Spatial Econ 1:267-292 · doi:10.1023/A:1012831808926
[25] Mesa-Arango R, Hasan S, Ukkusuri S, Murray-Tuite P (2013) Household-level model for hurricane evacuation destination type choice using hurricane Ivan data. Natural Hazards Rev 14(1):11-20 · doi:10.1061/(ASCE)NH.1527-6996.0000083
[26] Mileti DS, Sorensen JH, O’Brien PW (1992) Toward an explanation of mass care shelter use in evacuations. Int J Mass Emergencies Disasters 10(1):25-42
[27] Mitchell SW, Radwan E (2006) Heuristic prioritization of emergency evacuation staging to reduce clearance time. Proceedings of the 85th Annual Meeting Transportation Research Board, Washington
[28] Murray-Tuite P (2007) Perspectives for network management in response to unplanned disruptions. J Urban Plan Dev 133(1):9-17 · doi:10.1061/(ASCE)0733-9488(2007)133:1(9)
[29] Murray-Tuite P, Wolshon B (2013) Evacuation transportation modeling: an overview of research, development, and practice. Trans Res Part C:Emerg Technol 27:25-45 · doi:10.1016/j.trc.2012.11.005
[30] Naghawi H, Wolshon B (2012) Performance of traffic networks during multimodal evacuations: simulation-based assessment. Natural Hazards Rev 13(3):196-204 · doi:10.1061/(ASCE)NH.1527-6996.0000065
[31] Noh H, Chiu YC, Zheng H, Hickman M, Mirchandani P (2009) An approach to modeling demand and supply for a short-notice evacuation. Trans Res Record, J Trans Res Board 2091:91-99 · doi:10.3141/2091-10
[32] North MJ, Howe TR, Collier NT, Vos JR (2005) The Repast Simphony runtime system. In Proceedings of the Agent 2005 Conference on Generative Social Processes, Models, and Mechanisms
[33] Pidd M, de Silva FN, Eglese R (1993) CEMPS: a configurable evacuation management and planning system— a progress report. In: Proceedings of the 1993 Winter Simulation Conference
[34] Rathi AK, Solanki RS (1993) Simulation of traffic flow during emergency evacuations: a microcomputer based modeling system. In: Proceedings of the 1993 Winter Simulation Conference
[35] Sadri AM, Ukkusuri SV, Murray-Tuite P, Gladwin H (2014a) Analysis of hurricane evacuee mode choice behavior. Trans Res part C: Emerging Technol 48:37-46 · doi:10.1016/j.trc.2014.08.008
[36] Sadri AM, Ukkusuri SV, Murray-Tuite P, Gladwin H (2014b) How to evacuate: model for understanding the routing strategies during hurricane evacuation. J Transp Eng 140(1):61-69 · doi:10.1061/(ASCE)TE.1943-5436.0000613
[37] Sheffi Y, Mahmassani HS, Powell W (1980) NETVAC: a transportation network evacuation model. Center for Transportation Studies, Boston
[38] Sherali HD, Carter TB, Hobeika AG (1991) A location-allocation model and algorithm for evacuation planning under hurricane/flood conditions. Transp Res B 25(6):439-452 · doi:10.1016/0191-2615(91)90037-J
[39] Su X, Cai H, Luong B, Ukkusuri S (2015) From a link-node-based network representation model to a lane-based network representation model: two-dimensional arrangements approach. J Comput Civil Eng 29(3)
[40] Subramanian H (1996) Estimation of a car-following model for freeway simulation. Master’s thesis, Massachusetts Institute of Technology, Cambridge, MA
[41] Tarhini H, Bish DR (2015) Routing strategies under demand uncertainty. Networks Spatial Econ, 1-21 · Zbl 1364.90113
[42] Wang H, Andrews S, Daiheng N, Collura J (2010) Scenario-based analysis of transportation impacts in case of dam failure flood evacuation in Franklin county, Massachusetts. Proceedings of the 89th Annual Meeting of the Transportation Research Board, Washington
[43] Wicks DA (1977) INTRAS - a microscopic freeway corridor simulation model. Overview Simulation in Highway Transportation 1:95-107
[44] Williams B, Tagliaferri A, Meinhold S, Hummer J, Rouphail N (2007) Simulation and analysis of freeway lane reversal for coastal hurricane evacuation. J Urban Plan Dev 133(1):61-72 · doi:10.1061/(ASCE)0733-9488(2007)133:1(61)
[45] Wu HC, Lindell MK, Prater CS (2012) Logistics of hurricane evacuation in Hurricanes Katrina and Rita. Trans Res Part F: Traffic Psychology Behaviour 15(4):445-461 · doi:10.1016/j.trf.2012.03.005
[46] Yang Q (1997) A simulation laboratory for evaluation of dynamic traffic management systems, PhD. Thesis, Massachusetts Institute of Technology
[47] Yao T, Mandala SR, Do Chung B (2009) Evacuation transportation planning under uncertainty: a robust optimization approach. Networks Spatial Econ 9(2):171-189 · Zbl 1170.90328 · doi:10.1007/s11067-009-9103-1
[48] Yin W, Murray-Tuite P, Ukkusuri SV, Gladwin H (2014) An agent-based modeling system for travel demand simulation for hurricane evacuation. Transp Res C 42:44-59 · doi:10.1016/j.trc.2014.02.015
[49] Yu-Ting H, Peeta S (2015) Clearance time estimation for incorporating evacuation risk in routing strategies for evacuation operations. Networks Spatial Econ 15(3):1-22 · Zbl 1338.90051
[50] Zhang Z, Parr SA, Jiang H, Wolshon B (2015) Optimization model for regional evacuation transportation system using macroscopic productivity function. Transp Res B Methodol 81:616-630 · doi:10.1016/j.trb.2015.07.012
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.