Since 9/11, the Indian Ocean tsunami and hurricane Katrina, the number of papers that are being published related to mobility simulation in evacuation conditions has significantly increased. Though several topics have been developed, they tend to be implemented with an isolated and non-system approach and for specific kinds of dangerous events. This work aims to present a classification and specification of demand models for mobility simulation in evacuation conditions under different evacuation scenarios, in respect to different temporal conditions. A general framework is proposed to support the analysis of dangerous events, in respect of type and effects, especially in time. Three different temporal evolutions are identified and systematized: event developments and the relative conditioning on the system; user modification of behavior; and planning and management evolution. Leaving from the integrated temporal evolutions, the user behavior in the system context is analyzed and specificmodels are developed. The importance of SP surveys to analyze user behavior in evacuation conditions is highlighted and a hybrid class of surveys, termed SP with a physical check, is introduced. An integrated demand model is specified and calibrated for a dangerous event with effects on travel demand, with diffuse effects in space and delayed in time, according a behavioral approach.
Evacuation, temporal axis, behavioral demand models
 Domencich, T.A. & McFadden, D., Urban Travel Demand: A Behavioural Analysis, American Elsevier: New York, 1975.
 Ben Akiva, M. & Lerman, S., Discrete Choice Analysis: Theory and Application to Travel Demand, MIT Press: Cambridge, MA, 1985.
 Train, K., Qualitative Choice Analysis, MIT Press: Cambridge, MA, 1986.
 Train, K., Discrete Choice Methods with Simulation, MIT Press: Cambridge, MA, 2003. doi: http://dx.doi.org/10.1017/CBO9780511753930
 Raveau, S., Yáñez, M.F. & Ortúzar, J. de D., Practical and empirical identifi ability of hybrid discrete choice models. Transportation Research Part B, 46(10), pp. 1374–1383, 2012. doi: http://dx.doi.org/10.1016/j.trb.2012.06.006
 Castro, M., Bhat, C.R., Pendyala, R.M. & Jara-Diaz, S.R., Accommodating multiple constraints in the multiple discrete–continuous extreme value (MDCa, EV) choice model. Transportation Research Part B, 46(6), pp. 729–743, 2012. doi: http://dx.doi.org/10.1016/j.trb.2012.02.005
 Cascetta, E., Transportation Systems Analysis. Models and Application, Springer: New York, 2009. doi: http://dx.doi.org/10.1007/978-0-387-75857-2
 Russo, F. & Vitetta, A., Reverse assignment: calibrating link cost functions and updating demand from traffi c counts and time measurements. Inverse Problems in Science & Engineering, 19, pp. 921–950, 2011. doi: http://dx.doi.org/10.1080/17415977.2011.565339
 Russo, F. & Chilà, G., Safety of users in road evacuation: demand models. WIT Transactions on the Built Environment, Urban Transport XIII, Urban Transport and the Environment in the 21st century, ed. C.A. Brebbia, WIT Press: Southampton, 96,
pp. 773–782, 2007. doi: http://dx.doi.org/10.2495/UT070731
 Russo, F. & Vitetta, A., Risk evaluation in a transportation system. International Journal of Sustainable Development and Planning, 1(2), pp. 170–191, 2006. doi: http://dx.doi.org/10.2495/SDP-V1-N2-170-191
 Vorst, H.C.M., Evacuation models and disaster psychology. ScienceDirect, 3, pp. 15–21, 2010.
 Australia Governments, Emergency Management Approaches, available at: http://www.ema.gov.au/ (last access April, 2012).
 USA, Department of Homeland Security Report to congress on catastrophic hurricane evacuation plan evaluation, available at: www.fhwa.dot.gov/reports/hurricanevacuation/(last access April, 2012).
 European Commission, European civil protection, available at: http://ec.europa.eu/echo/civil_protection/civil/ index.htm (last access April, 2012).
 Vitetta, A., Quattrone, A. & Polimeni, A., Safety of users in road evacuation: design of path choice models for emergency vehicles. WIT Transaction on The Built Environment, 96, pp. 41–50, 2007.
 Vitetta, A., Quattrone, A. & Polimeni, A., Safety of users in road evacuation: algorithms for path design of emergency vehicles. WIT Transaction on The Built Environment, 101, pp. 727–737, 2008. doi: http://dx.doi.org/10.2495/UT080701
 Chen, Y. & Xiao, D., Emergency evacuation models and algorithms. Journal of Transportation System Engineering and Information Technology, 8(6), pp. 96–100, 2006. doi: http://dx.doi.org/10.1016/S1570-6672(09)60008-8
 Pel, A.G., Hoogendoorn, S.P. & Bliemer, M.C.J., Evacuation modeling including traveler information and compliance behaviour. Proceedings of the 1st International Conference on Evacuation Modeling and Management, eds. S.P. Hoogendoorn,
A.G. Pel & M.A.P. Mahmassani. Procedia Engineering, Elsevier, 3, pp. 101–111, 2010.
 Li, J., Zhang, B., Liu, W. & Tan, Z., Research on OREMS-based large-scale emergency evacuation using vehicle. Process Safety and Environmental Protection, 89(5), pp. 300–309, 2011. doi: http://dx.doi.org/10.1016/j.psep.2011.06.002
 Daganzo, C.F. & So, S.K., Managing evacuation networks. Transportation Research Part B, 45(9), pp. 1424–1432, 2011. doi: http://dx.doi.org/10.1016/j.trb.2011.05.015
 Sorensen, J., Hazard warning systems: review of 20 years of progress. Natural Hazards Review, 1(2), pp. 119–125, 2000. doi: http://dx.doi.org/10.1061/(ASCE)1527-6988(2000)1:2(119)
 Lindell, M.K. & Prater, C.S., Critical behavioral assumptions in evacuation time estimate analysis for private vehicles: examples from hurricane research and planning. Journal of Urban Planning and Development, 133(1), pp. 18–29, 2007. doi: http://dx.doi.org/10.1061/(ASCE)0733-9488(2007)133:1(18)
 Pel, A.J., Bliemer, M.C.J. & Hoogendoorn, S.P., A review on travel behaviour modelling in dynamic traffi c simulation models for evacuations. Transportation, 39(1), pp. 97–123, 2012. doi: http://dx.doi.org/10.1007/s11116-011-9320-6
 Murray-Tuite, P. & Wolshon, B., Evacuation transportation modelling: an overview of research, development and practice. Transportation Research Part C, 25, pp. 25–45, 2013. doi: http://dx.doi.org/10.1016/j.trc.2012.11.005
 Murray-Tuite, P. & Wolshon, B., Assumptions and processes for the development of no-notice evacuation scenarios for transportation simulation. International Journal of Mass Emergencies and Disasters, 31(1), p. 78, 2013.
 Brebbia, C.A. ed., Disaster Management and Human Health Risk III, WIT Press: Southampton, 2013.
 Molinari, D., Menoni, S. & Ballio, F., Flood Early Warning Systems: Knowledge and Tools for Their Critical Assessment, WIT Press: Southampton, 2013.
 Sbayti, H. & Mahmassani, H., Optimal scheduling of evacuation operations. Transportation Research Record: Journal of the Transportation Research Board, 1964(1), pp. 238–246, 2006. doi: http://dx.doi.org/10.3141/1964-26
 Chen, X. & Zhan, F., Agent-based modelling and simulation of urban evacuation: relative effectiveness of simultaneous and staged evacuation strategies. Journal of the Operational Research Society, 59, pp. 25–33, 2006. doi: http://dx.doi.org/10.1057/palgrave.jors.2602321
 Dow, K. & Cutter, S.L., Emerging hurricane evacuation issue: Hurricane Floyd and South Carolina. Natural Hazard Review, 3(1), pp. 12–18, 2002. doi: http://dx.doi.org/10.1061/(ASCE)1527-6988(2002)3:1(12)
 Wilmot, C.G. & Mei, B., Comparison of alternative trip generation models for hurricane evacuation. Natural Hazards Review, 5(4), pp. 170–178, 2004. doi: http://dx.doi.org/10.1061/(ASCE)1527-6988(2004)5:4(170)
 Solis, D., Thomas, M. & Letson, D., Determinants of household hurricane evacuation choice in Florida. Presentation at the Southern Agricultural Economics Association Annual Meeting, Atlanta, Georgia, January 31–February 3, 2009.
 Hasan, S. & Ukkussuri, S., A threshold model of social contagion process for evacuation decision making. Transportation Research Part B, 45(10), pp. 1590–1605, 2011.doi: http://dx.doi.org/10.1016/j.trb.2011.07.008
 Alsnih, R., Rose, J.M. & Stopher, P., Dynamic travel demand for emergency evacuation: the case of bushfi res. Presented at 27th Australasian Transport Research Forum, Adelaide, Australia, 2004.
 Alsnih, R., Rose, J.M. & Stopher, P., Understanding household evacuation decisions using a stated choice survey - case study of bush fi res. Presented at 84th Annual Meeting of the Transportation Research Board, Washington DC, USA, 2005.
 Wilmot, C.G. & Fu, H., A sequential logit dynamic travel demand model for hurricane evacuation. Transport Research Record, 1882, pp. 19–26, 2004. doi: http://dx.doi.org/10.3141/1882-03
 Russo, F. & Chilà, G., A sequential dynamic choice model to simulate demand in evacuation conditions. WIT Transactions on Ecology and the Environment, Risk Analysis VII and Brownfi elds V, ed. C.A. Brebbia, WIT Press: Southampton, 141, pp. 431–442, 2010.
 Gottman, J.M. & Roy, A.K., Sequential Analysis: A Guide for Behavioural Researchers, Cambridge University Press: Cambridge, 1990. doi: http://dx.doi.org/10.1017/CBO9780511529696
 Chilà, G., Sequential methods for user choices: tests and properties applied to a panel database. WIT Transactions on the Built Environment, Urban Transport XIV, Urban Transport and the Environment in the 21st Century, ed. C.A. Brebbia, WIT Press: Southampton, 101, pp. 121–131, 2008.
 Chiu, Y., Villalobos, J., Gautam, B. & Zheng, H., Modeling and solving the optimal evacuation destination-route-fl ow-staging problem for no-notice extreme events. Proceedings of the 85th Transportation Research Board, Washington, DC, USA, 2006.
 Han, L., Yuan, F., Chin, S. & Hwang, H., Global optimization of emergency evacuation assignments. Interfaces, 36(6), pp. 502–513, 2006. doi: http://dx.doi.org/10.1287/inte.1060.0251
 Cheng, G., Wilmot, C.G. & Baker, R.J., A destination choice model for hurricane evacuation. Transportation Research Board Annual Meeting, Washington, DC, USA, 2008.
 Hasan, S., Mesa-Arango, R., Ukkusuri, S. & Murray-Tuite, P., Transferability of hurricane evacuation choice model: joint model estimation combining multiple data sources. Journal of Transportation Engineering, 138(5), pp. 548–556, 2012. doi: http://dx.doi.org/10.1061/(ASCE)TE.1943-5436.0000365
 Abdelgawad, H. & Abdulhai, B., Towards a complete evacuation demand and supply modeling and management process. Proceedings of 12th WCTR, Lisbon, Portugal, July 11–15, 2010.
 Ortuzar, J. de D. & Willumsen, L.G., Modelling Transport, John Wiley and Sons Ltd: Chichester, 2006.
 Yu, J., Goos, P. & Vandebroek, M., A comparison of different Bayesian design criteria for setting up stated preference studies. Transportation Research Part B, 46(7), pp. 789–807, 2012. doi: http://dx.doi.org/10.1016/j.trb.2012.01.007
 Naser, M. & Birst, S.C., Mesoscopic evacuation modeling for small- to medium-sized metropolitan areas. Department of Transportation, University Transportation Centers Program, North Dakota State University, 2010.
 Lee-Gosselin, M.F.H., Scope and potential of interactive stated response data collection methods. Proceedings of Conference on Household Travel Surveys: New Concepts and Research Needs. Transportation Research Board, Conference Proceedings, 10, pp. 115–133, 1996.
 Train, K. & Wilson, W.W., Monte Carlo analysis of SP-off-RP data. Journal of Choice Modelling, 2(1), pp. 101–117, 2009. doi: http://dx.doi.org/10.1016/S1755-5345(13)70006-X