Agent-based modelling and simulation of urban evacuation: relative effectiveness of simultaneous and staged evacuation strategies
Tóm tắt
This study investigates the effectiveness of simultaneous and staged evacuation strategies using agent-based simulation. In the simultaneous strategy, all residents are informed to evacuate simultaneously, whereas in the staged evacuation strategy, residents in different zones are organized to evacuate in an order based on different sequences of the zones within the affected area. This study uses an agent-based technique to model traffic flows at the level of individual vehicles and investigates the collective behaviours of evacuating vehicles. We conducted simulations using a microscopic simulation system called Paramics on three types of road network structures under different population densities. The three types of road network structures include a grid road structure, a ring road structure, and a real road structure from the City of San Marcos, Texas. Default rules in Paramics were used for trip generation, destination choice, and route choice. Simulation results indicate that (1) there is no evacuation strategy that can be considered as the best strategy across different road network structures, and the performance of the strategies depends on both road network structure and population density; (2) if the population density in the affected area is high and the underlying road network structure is a grid structure, then a staged evacuation strategy that alternates non-adjacent zones in the affected area is effective in reducing the overall evacuation time.
Tài liệu tham khảo
Anderson P (1999). Complexity theory and organization science. Organ Sci 10: 216–232.
Batty M, DeSyllas J and Duxbury E (2002). The discrete dynamics of small-scale spatial events: Agent-based models of mobility in carnivals and street parades. Int J Geogr Inf Sci 17: 673–697.
Blue VJ and Adler JL (1998). Emergent fundamental pedestrian flows from cellular automata microsimulation. Transport Res Rec 1644: 29–36.
Bonabeau E (2002a). Agent-based modeling: Methods and techniques for simulating human systems. Proc Natl Acad Sci USA 99: 7280–7287.
Bonabeau E (2002b). Predicting the unpredictable. Harvard Bus Rev 80: 109–115.
Bonabeau E, Dorigo M and Theraulaz G (1999). Swarm Intelligence: From Natural to Artificial Systems. Oxford University Press: New York, NY.
Boxill S and Yu L (2000). An evaluation of traffic simulation models for supporting ITS development. Texas Transportation Institute Report SWUTC/00/167602-1, Southwest Region University Transportation Center, Texas A&M University, College Station, TX.
Cetin N, Nagel K, Raney B and Voellmy A (2002). Large-scale multi-agent transportation simulations. Comput Phys Commun 147: 559–564.
Chen X (2006). Microsimulation of evacuation strategies. PhD dissertation, Texas State University, San Marcos.
Chen X, Meaker JW and Zhan FB (2006). Agent-based modeling and analysis of hurricane evacuation procedures for the Florida Keys. Nat Hazards 38: 321–338.
Choa F, Milam R and Stanek D (2002). CORSIM, PARAMICS and VISSIM—What the manuals never told you. ITE Conference 2002, Philadelphia, PA, 4–7 August.
Church RL and Sexton RM (1998). Modeling small area evacuation: Can existing transportation infrastructure impede public safety? Caltrans Testbed Center for Interoperability Task Order 3021Report, Vehicle Intelligence & Transportation Analysis Laboratory, University of California, Santa Barbara.
Claramunt C and Jiang B (2001). A qualitative model for the simulation of traffic behaviors in a multi-lane environment. J Geogr Sci 11: 29–42.
Cova TJ and Church RL (1997). Modelling community evacuation vulnerability using GIS. Int J Geogr Inf Sci 11: 763–784.
Cova TJ and Johnson JP (2002). Microsimulation of neighborhood evacuations in the urban-wildland interface. Environ Plann A 34: 2211–2229.
Deadman PJ (1999). Modelling individual behaviour and group performance in an intelligent agent-based simulation of the tragedy of the commons. J Environ Manage 56: 159–172.
Dia H and Purchase H (1999). Modelling the impacts of advanced traveler information systems using intelligent agents. Road Transport Res 8: 68–73.
Ebeling W and Schweitzer F (2001). Swarms of particle agents with harmonic interactions. Theor Biosci 120: 207–224.
Farrell J (2005). Alternatives to road building to improve hurricane evacuation in coastal South Carolina. Spring 2005 environmental advocacy seminar, School of Law, University of South Carolina, Columbia, SC.
Fritzsche H-T (1994). A model for traffic simulation. Traffic Eng Control 35: 317–321.
Fuks H and Boccara N (1998). Generalized deterministic traffic rules. Int J Mod Phys C 9: 1–12.
Gilbert N and Bankes S (2002). Platforms and methods for agent-based modeling. Proc Natl Acad Sci USA 99: 7197–7198.
Hobeika AG and Jamei B (1985). MASSVAC: A model for calculating evacuation times under natural disaster. Emerg Plann, Simulation Series 15: 23–28.
Knox PL (1994). Urbanization: An Introduction to Urban Geography. Prentice-Hall: Englewood Cliffs, NJ.
Los Alamos National Laboratory (LANL) (1997). Transportation Analysis Simulation System (TRANSIMS): The Dallas-Ft. Worth Case Study. TRANSIMS Release 1.0, Report LA-UR-97-4502, Los Alamos National Laboratory, Los Alamos, NM.
Nagel K (1996). Particle hopping models and traffic flow theory. Phys Rev E 53: 4655–4672.
Nagel K and Herrmann HJ (1993). Deterministic models for traffic jams. Physica A 199: 254–269.
Nagel K and Paczuski M (1995). Emergent traffic jams. Phys Rev E 51: 2909–2918.
Nagel K, Wagner P and Woesler R (2003). Still flowing: Approaches to traffic flow and traffic jam modeling. Opns Res 51: 681–710.
Oak Ridge National Laboratory (ORNL) (1998). Oak Ridge Evacuation Modeling System (OREMS) Version 2.50 User's Guide. Oak Ridge, TN.
Olstam JJ and Tapani A (2004). Comparison of car-following models. VTI meddelande 960A, Swedish National Road and Transport Research Institute: Linköping, Sweden.
Peat, Marwick, Mitchell and Company (1973). Network flow simulation for urban traffic control, System-phase II. v. 1. Prepared for the Federal Highway Administration, Washington, D.C., 20590.
Pidd M, de Silva FN and Eglese RW (1996). A simulation model for emergency evacuation. Eur J Opl Res 90: 413–419.
Quadstone (2002). Quadstone Paramics V4.0 modeller user guide. Edinburgh, UK.
Sheffi Y, Mahmassani H and Powell WB (1982). A transportation network evacuation model. Transport Res A-Pol 16: 209–218.
Sinuany-Stern Z and Stern E (1993). Simulating the evacuation of a small city: The effects of traffic factors. Socio Econ Plan Sci 27: 97–108.
Stern E and Sinuany-Stern Z (1989). A behavioural-based simulation model for urban evacuation. Pap Reg Sci Assoc 66: 87–103.
Sugiman T and Misumi J (1988). Development of a new evacuation method for emergencies: Control of collective behavior by emergent small groups. J Appl Psychol 73: 3–10.
Teodorovic DA (2003). Transport modeling by multi-agent systems: A swarm intelligence approach. Transport Plan Techn 26: 289–312.
Urbanik T II (2000). Evacuation time estimates for nuclear power plants. J Hazard Mater 75: 165–180.
Wahle J, Neubert L, Esser J and Scherckenberg M (2001). A cellular automaton traffic flow model for online simulation of traffic. Parallel Comput 27: 719–735.
Wolshon B, Catarella-Michel A and Lambert L (2006). Louisiana highway evacuation plan for Hurricane Katrina: Proactive management of a regional evacuation. J Transp Engrg 132: 1–10.