A Regret Theory-Based Decision-Making Method for Urban Rail Transit in Emergency Response of Rainstorm Disaster

Author:

Wang Yuning1ORCID,Liang Yingzi2,Sun Hui2ORCID

Affiliation:

1. School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin, China

2. School of Management and Economics, Tianjin University, Tianjin, China

Abstract

The decision-making for urban rail transit emergency events takes an important role in both reducing the losses caused by disasters and ensuring the safety of passengers. For the rainstorm emergency decision-making without certain scenario prediction information, considering the characteristic that the predisaster prevention measures will influence the effect of in-process countermeasures, this paper aimed to analyze the whole process scenarios for the occurrence, evolution, and development of rainstorm disaster in urban rail transit by considering the regret aversion of the decision makers. An emergency decision-making method for the beforehand-ongoing two stages rainstorm emergencies was developed to assess the emergency decision-making of urban rail transportation in different rainfall flood scenarios. Besides, the utilities and application costs of the emergency plans are also considered when defining the optimal emergency decision-making. This paper purposes the emergency decision-making model based on regret theory to define the optimal predisaster prevention method and ongoing responding measure for different disaster scenarios. Taking the Tianjin rail transportation as an example, this paper defines the optimal emergency decision-making to respond typhoon “Lekima.” The results show that if this method can be implemented in the rail transportation rainstorm disaster emergency responding and relevant disaster prevention management, then the reliability and risk responding capability of public transportation service can both be improved.

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

Strategy and Management,Computer Science Applications,Mechanical Engineering,Economics and Econometrics,Automotive Engineering

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