A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Safety evaluation of urban rail transit operation considering uncertainty and risk preference: A case study in China
Abstract Safety evaluation of urban rail transit (URT) operation can not only have a great impact on passenger travel options, but is also related to planning of urban development. The evaluation results of URT operational safety are important for transit operators and passengers. In this study, we develop an integrated multi-stage evaluation framework to assess URT operation from the perspective of safety, which considers information uncertainty of key influence factors (KIFs), and risk preference of decision-makers (DMs). Firstly, to identify and select KIFs, this study makes systematic analysis of impacts on URT operational safety from five aspects: passengers, management, equipment, environment, and disaster respectively. Vensim software is used to build a stock flow model based on system dynamics method, and a two-level index system for assessing URT operational safety is established. Secondly, DMs’ weights are specified based on interval valued triangular fuzzy (IVTF)-TOPSIS method, and IVTF-AHP-entropy is introduced to determine the combined weight of each indicator. Thirdly, an S-shaped utility function under IVTF environment is developed to get the ranking order of research objects, and operational safety levels are determined based on cloud model. Finally, Changsha subway network is selected as a case study to test our proposed evaluation framework, and some related suggestions for operators and managers have been put forward in the future.
Highlights Proposed a hybrid six-phase evaluation model. Identify key influence factors (KIFs) of URT operational safety. Take risk attitude of decision-makers (DMs) into consideration. Verify our proposed method by the Changsha subway network.
Safety evaluation of urban rail transit operation considering uncertainty and risk preference: A case study in China
Abstract Safety evaluation of urban rail transit (URT) operation can not only have a great impact on passenger travel options, but is also related to planning of urban development. The evaluation results of URT operational safety are important for transit operators and passengers. In this study, we develop an integrated multi-stage evaluation framework to assess URT operation from the perspective of safety, which considers information uncertainty of key influence factors (KIFs), and risk preference of decision-makers (DMs). Firstly, to identify and select KIFs, this study makes systematic analysis of impacts on URT operational safety from five aspects: passengers, management, equipment, environment, and disaster respectively. Vensim software is used to build a stock flow model based on system dynamics method, and a two-level index system for assessing URT operational safety is established. Secondly, DMs’ weights are specified based on interval valued triangular fuzzy (IVTF)-TOPSIS method, and IVTF-AHP-entropy is introduced to determine the combined weight of each indicator. Thirdly, an S-shaped utility function under IVTF environment is developed to get the ranking order of research objects, and operational safety levels are determined based on cloud model. Finally, Changsha subway network is selected as a case study to test our proposed evaluation framework, and some related suggestions for operators and managers have been put forward in the future.
Highlights Proposed a hybrid six-phase evaluation model. Identify key influence factors (KIFs) of URT operational safety. Take risk attitude of decision-makers (DMs) into consideration. Verify our proposed method by the Changsha subway network.
Safety evaluation of urban rail transit operation considering uncertainty and risk preference: A case study in China
Chai, Naijie (author) / Zhou, Wenliang (author) / Hu, Xinlei (author)
Transport Policy ; 125 ; 267-288
2022-05-07
22 pages
Article (Journal)
Electronic Resource
English
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