Abstract
Given a transportation network, a population, and a set of destinations, the goal of Conflict-Free Evacuation Route Planning (CF-ERP) is to produce routes that minimize the evacuation time for the population with no spatiotemporal movement-conflicts. The CF-ERP problem is an essential component of civic emergency preparedness in the wake of man-made or natural disasters (e.g., terrorist acts, hurricanes, or nuclear accidents). This problem is challenging because of the large size of network data, the large number of evacuees, and the need to account for capacity constraints and the conflict-free constraint. Previous work has focused on minimizing the evacuation time on spatiotemporal networks. However, these approaches cannot minimize potential movement-conflicts that cause traffic accidents, congestion, and delays. We propose novel approaches for CF-ERP to meet the conflict-free constraint while minimizing the evacuation time for the population. Experiments using real-world datasets demonstrate that the proposed algorithms produce evacuation routes with no movement-conflicts and have comparable solution quality to related work.
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Ahuja R, Magnanti T L, Orlin J B (1993) Network flows: theory, algorithms and applications. Prentice-Hall, New Jersey
Aljubayrin S, Qi J, Jensen C S, Zhang R, He Z, Wen Z (2015) The safest path via safe zones. In: 2015 IEEE 31st international conference on data engineering. IEEE, pp 531–542
Ben-Akiva M, et al. (2002) Development of a deployable real-time dynamic traffic assignment system: dynamit and dynamit-p user’s guide. Intelligent Transportation Systems Program Massachusetts Institute of Technology
Burkard R E, Dlaska K, Klinz B (1993) The quickest flow problem. Z Oper Res 37(1):31–58
Cormen T H, Leiserson C E, Rivest R L, Stein C (2009) Introduction to algorithms, MIT Press, Cambridge
Cova T J, Johnson J P (2003) A network flow model for lane-based evacuation routing. Transp Res Part A: Policy Pract 37(7):579–604
Dai J, Yang B, Guo C, Jensen C S, Hu J (2016) Path cost distribution estimation using trajectory data. Proc VLDB Endow 10(3):85–96
Diestel R (2005) Graph theory. Grad. Texts in Math 101
Fleischer L, Skutella M (2007) Quickest flows over time. SIAM J Comput 36(6):1600–1630
Ford L R Jr, Fulkerson DR (1958) Constructing maximal dynamic flows from static flows. Oper Res 6(3):419–433
Francis R, Saunders P (1979) Evacnet: prototype network optimization models for building evacuation (rep. no. nbsir 79-1593). Natl Bur Stand (US)
Furth P G, Cesme B, Muller T H J (2009) Lost time and cycle length for actuated traffic signal. Transp Res Rec 2128(1):152–160. https://doi.org/10.3141/2128-16
Gastner M T, Newman M E (2006) The spatial structure of networks. Eur Physi J B-Condens Matter Complex Syst 49(2):247–252
George B, Shekhar S (2008) Time-aggregated graphs for modeling spatio-temporal networks. In: Journal on Data Semantics XI. Springer, pp 191–212
Hamacher H, Tjandra S (2002) Mathematical modelling of evacuation problems: state of the art. In: Pedestrian and evacuation dynamics. Springer, pp 227–266
Herschelman R, Yang K (2019) Conflict-free evacuation route planner. In: Proceedings of the 27th ACM SIGSPATIAL international conference on advances in geographic information systems. ACM, pp 480–483
Hoppe B, Tardos É (1994) Polynomial time algorithms for some evacuation problems. In: SODA, vol 94, pp 433–441
Hoppe B, Tardos E (2000) The quickest transshipment problem. Math Oper Res 25(1):36–62
Kim S, George B, Shekhar S (2007) Evacuation route planning: scalable heuristics. In: Proceedings of the 15th annual ACM international symposium on advances in geographic information systems, pp 1–8
Lu Q, George B, Shekhar S (2005) Capacity constrained routing algorithms for evacuation planning: a summary of results. In: International symposium on spatial and temporal databases. Springer, pp 291–307
Lu Q, George B, Shekhar S (2007) Evacuation route planning: a case study in semantic computing. Int J Semant Comput 1(2):249–303
Mahmassani H, Sbayti H, Zhou X (2004) Dynasmart-p: intelligent transportation network planning tool: version 1.0 user’s guide. Maryland Transportation Initiative, University of Maryland, College Park
Pedersen S A, Yang B, Jensen C S (2020) Fast stochastic routing under time-varying uncertainty. VLDB J 29(4):819–839
Pel A J, Bliemer M C, Hoogendoorn S P (2012) A review on travel behaviour modelling in dynamic traffic simulation models for evacuations. Transportation 39(1):97–123
Regan A (2017) Hurricane Irma could create one of the largest mass evacuations in U.S. history. https://www.usatoday.com/story/news/nation-now/2017/09/07/hurricane-irma-evacuations-florida/643045001/ Online; Accessed: 12 June 2020
Shekhar S, Yang K, Gunturi V M, Manikonda L, Oliver D, Zhou X, George B, Kim S, Wolff J M, Lu Q (2012) Experiences with evacuation route planning algorithms. Int J Geogr Inf Sci 26(12):2253–2265
Southworth F (1991) Regional evacuation modeling: A state-of-the art review (Technical Report). Center for Transportation Analysis Oak Ridge National Laboratory, Oak Ridge, TN, https://www.survivalring.org/classics/RegionalEvactuationModeling-StateOfTheArtReview-Mar1991-ORNL-TM-11740.pdf. Accessed 31 May 2020.
State of Florida (2018) Select Committee on Hurricane Response and Preparedness (Final Report). https://www.myfloridahouse.gov/. Online; Accessed 31 May 2020
Wardrop J (1952) Some theoretical aspects of road traffic research. In: Proceedings of the institution of civil engineers, 2(1). Thomas Telford Ltd
www.openstreetmap.org: Online; Accessed 31 Mar 2020
Yang K, Gunturi V M, Shekhar S (2012) A dartboard network cut based approach to evacuation route planning: a summary of results. In: International conference on geographic information science. Springer, pp 325–339
Yang B, Guo C, Jensen C S, Kaul M, Shang S (2014) Stochastic skyline route planning under time-varying uncertainty. In: 2014 IEEE 30th International conference on data engineering. IEEE, pp 136–147
Yang K, Shekhar A H, Rehman F U, Lahza H, Basalamah S, Shekhar S, Ahmed I, Ghafoor A (2015) Intelligent shelter allotment for emergency evacuation planning: a case study of makkah. IEEE Intell Syst 30(5):66–76
Yang K, Shekhar S (2017) Spatial network big databases: queries and storage methods. Springer, Cham
Acknowledgements
We would like to thank the National Science Foundation CAREER under Grant No. 1844565. We also thank Prof. Shashi Shekhar from University of Minnesota for his helpful comments and discussions.
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Herschelman, R., Qutbuddin, A. & Yang, K. Conflict-Free Evacuation Route Planning. Geoinformatica 25, 655–678 (2021). https://doi.org/10.1007/s10707-021-00435-0
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DOI: https://doi.org/10.1007/s10707-021-00435-0