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Modeling multimodal transportation network emergency evacuation considering evacuees’ cooperative behavior

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  • Yang, Xia
  • Ban, Xuegang (Jeff)
  • Mitchell, John

Abstract

Modeling emergency evacuation could help reduce losses and damages from disasters. In this paper, based on the system optimum principle, we develop a multimodal evacuation model that considers multiple transportation modes and their interactions, and captures the proper traffic dynamics including the congestion effects, the cooperative behavior of evacuees, and the capacities of the transportation system and the shelters. We further develop a Method of Successive Average (MSA)-based sequential optimization algorithm for large-scale evacuation problems. Both the proposed model and the solution algorithm are tested and validated through a set of numerical tests on a small network, and a detailed case study on the Lower Manhattan network. The results of the paper can provide insight on modeling flow interactions of different transportation modes and useful guidance on developing evacuation strategies to reduce the system evacuation time and losses from disasters.

Suggested Citation

  • Yang, Xia & Ban, Xuegang (Jeff) & Mitchell, John, 2018. "Modeling multimodal transportation network emergency evacuation considering evacuees’ cooperative behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 114(PB), pages 380-397.
  • Handle: RePEc:eee:transa:v:114:y:2018:i:pb:p:380-397
    DOI: 10.1016/j.tra.2018.01.037
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    References listed on IDEAS

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    1. Athanasios K. Ziliaskopoulos, 2000. "A Linear Programming Model for the Single Destination System Optimum Dynamic Traffic Assignment Problem," Transportation Science, INFORMS, vol. 34(1), pages 37-49, February.
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    5. Lindell, Michael K., 2008. "EMBLEM2: An empirically based large scale evacuation time estimate model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(1), pages 140-154, January.
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    8. Ma, Rui & Ban, Xuegang (Jeff) & Pang, Jong-Shi, 2014. "Continuous-time dynamic system optimum for single-destination traffic networks with queue spillbacks," Transportation Research Part B: Methodological, Elsevier, vol. 68(C), pages 98-122.
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    Cited by:

    1. Song, Zhuzhu & Tang, Wansheng & Zhao, Ruiqing, 2020. "A simple game theoretical analysis for incentivizing multi-modal transportation in freight supply chains," European Journal of Operational Research, Elsevier, vol. 283(1), pages 152-165.
    2. Wang, Yan & Wang, Junwei, 2019. "Integrated reconfiguration of both supply and demand for evacuation planning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 130(C), pages 82-94.
    3. Sun, Wenjun & Zhu, Changfeng & Li, Hui, 2022. "Evolutionary game of emergency logistics path selection under bounded rationality," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    4. Wang, Bi & Su, Qin & Chin, Kwai Sang, 2021. "Vulnerability assessment of China–Europe Railway Express multimodal transport network under cascading failures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 584(C).
    5. Xinhua Mao & Changwei Yuan & Jiahua Gan & Jibiao Zhou, 2019. "Optimal Evacuation Strategy for Parking Lots Considering the Dynamic Background Traffic Flows," IJERPH, MDPI, vol. 16(12), pages 1-20, June.

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