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Investigating the impact of river floods on travel demand based on an agent-based modeling approach: The case of Liège, Belgium

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Listed:
  • Saadi, Ismaïl
  • Mustafa, Ahmed
  • Teller, Jacques
  • Cools, Mario

Abstract

In Belgium, river floods are among the most frequent natural disasters and they may have important consequences on travel demand. In order to better understand how the travel patterns vary, we propose to set up a large scale scenario based on MATSim for guarantying an accurate assessment of the impact of river floods on the transportation system. As inputs, the current agent-based model requires a base year population. A synthetic population with respective set of attributes is generated as a key input. Afterwards, agents are assigned activity chains through an activity-based generation process. Finally, the synthetic population and the transportation network are integrated into MATSim. Regarding data, households travel surveys, OD matrix of Belgium have been used to set up the demand. For simulating river floods effects, a steady-state inundation map has been integrated within MATSim. In the current study, five scenarios have been tested where critical links are associated various levels of service, i.e. 10%, 25%, 50%, 75% and 100% (base case scenario). They are systematically compared to the standard scenario to estimate the deviations in terms of traffic patterns and travel times. The results suggest that compared to the standard scenario, the average trip travel time increased by 16.36%, 44.44%, 126.77% and 144.44% with respect to scenarios 75%, 50%, 25% and 10% respectively. Also, the traffic flows have been re-distributed more uniformly across the transportation network. Roads with important traffic volumes are subjected to a decrease of activity on the contrary of roads with low traffic volumes. A very few studies have focused on how river floods affect transportation systems, this paper provided new insights in term of methodology and traffic patterns analysis under disruptions.

Suggested Citation

  • Saadi, Ismaïl & Mustafa, Ahmed & Teller, Jacques & Cools, Mario, 2018. "Investigating the impact of river floods on travel demand based on an agent-based modeling approach: The case of Liège, Belgium," Transport Policy, Elsevier, vol. 67(C), pages 102-110.
    • Handle: RePEc:eee:trapol:v:67:y:2018:i:c:p:102-110
    DOI: 10.1016/j.tranpol.2017.09.009
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    References listed on IDEAS

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    1. Saadi, Ismaïl & Mustafa, Ahmed & Teller, Jacques & Farooq, Bilal & Cools, Mario, 2016. "Hidden Markov Model-based population synthesis," Transportation Research Part B: Methodological, Elsevier, vol. 90(C), pages 1-21.
    2. Novosel, T. & Perković, L. & Ban, M. & Keko, H. & Pukšec, T. & Krajačić, G. & Duić, N., 2015. "Agent based modelling and energy planning – Utilization of MATSim for transport energy demand modelling," Energy, Elsevier, vol. 92(P3), pages 466-475.
    3. David Charypar & Kai Nagel, 2005. "Generating complete all-day activity plans with genetic algorithms," Transportation, Springer, vol. 32(4), pages 369-397, July.
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    Cited by:

    1. Yu Han & Kevin Ash & Liang Mao & Zhong-Ren Peng, 2020. "An agent-based model for community flood adaptation under uncertain sea-level rise," Climatic Change, Springer, vol. 162(4), pages 2257-2276, October.
    2. Choi, Sunkyung & Maharjan, Rajali & Hong, Tran Thi Nhat & Hanaoka, Shinya, 2024. "Impact of information provision on tsunami evacuation behavior of residents and international tourists in Japan," Transport Policy, Elsevier, vol. 155(C), pages 264-273.

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