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A risk-based method for planning of bus–subway corridor evacuation under hybrid uncertainties

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  • Lv, Y.
  • Yan, X.D.
  • Sun, W.
  • Gao, Z.Y.

Abstract

Emergencies involved in a bus–subway corridor system are associated with many processes and factors with social and economic implications. These processes and factors and their interactions are related to a variety of uncertainties. In this study, an interval chance-constrained integer programming (EICI) method is developed in response to such challenges for bus–subway corridor based evacuation planning. The method couples a chance-constrained programming with an interval integer programming model framework. It can thus deal with interval uncertainties that cannot be quantified with specified probability distribution functions. Meanwhile, it can also reflect stochastic features of traffic flow capacity, and thereby help examine the related violation risk of constraint. The EICI method is applied to a subway incident based evacuation case study. It is solved through an interactive algorithm that does not lead to more complicated intermediate submodels and has a relatively low computational requirement. A number of decision alternatives could be directly generated based on results from the EICI method. It is indicated that the solutions cannot only help decision makers identify desired population evacuation and vehicle dispatch schemes under hybrid uncertainties, but also provide bases for in-depth analyses of tradeoffs among evacuation plans, total evacuation time, and constraint-violation risks.

Suggested Citation

  • Lv, Y. & Yan, X.D. & Sun, W. & Gao, Z.Y., 2015. "A risk-based method for planning of bus–subway corridor evacuation under hybrid uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 139(C), pages 188-199.
    • Handle: RePEc:eee:reensy:v:139:y:2015:i:c:p:188-199
    DOI: 10.1016/j.ress.2015.03.002
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    Cited by:

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    2. Changxi Ma & Jibiao Zhou & Dong Yang, 2020. "Causation Analysis of Hazardous Material Road Transportation Accidents Based on the Ordered Logit Regression Model," IJERPH, MDPI, vol. 17(4), pages 1-25, February.
    3. Dulebenets, Maxim A. & Abioye, Olumide F. & Ozguven, Eren Erman & Moses, Ren & Boot, Walter R. & Sando, Thobias, 2019. "Development of statistical models for improving efficiency of emergency evacuation in areas with vulnerable population," Reliability Engineering and System Safety, Elsevier, vol. 182(C), pages 233-249.
    4. Teichmann, Dusan & Dorda, Michal & Sousek, Radovan, 2021. "Creation of preventive mass evacuation plan with the use of public transport," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    5. Kai Yu & Nannan Qu & Jifeng Lu & Lujie Zhou, 2022. "Determining Subway Emergency Evacuation Efficiency Using Hybrid System Dynamics and Multiple Agents," Mathematics, MDPI, vol. 10(19), pages 1-18, October.
    6. Zheng, Shuai & Liu, Yugang & Lin, Yexin & Wang, Qiang & Yang, Hongtai & Chen, Bin, 2022. "Bridging strategy for the disruption of metro considering the reliability of transportation system: Metro and conventional bus network," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    7. Liang, Shidong & He, Shengxue & Zhang, Hu & Ma, Minghui, 2021. "Optimal holding time calculation algorithm to improve the reliability of high frequency bus route considering the bus capacity constraint," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    8. Simic, Vladimir, 2016. "End-of-life vehicles allocation management under multiple uncertainties: An interval-parameter two-stage stochastic full-infinite programming approach," Resources, Conservation & Recycling, Elsevier, vol. 114(C), pages 1-17.

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