Fault Tree and Fuzzy D-S Evidential Reasoning combined approach: An application in railway dangerous goods transportation system accident analysis

Huang, Wencheng; Liu, Yuan‐Kai; Zhang, Yue; Zhang, Rui; Xu, Minhao; Dieu, Gatesi Jean De; Antwi, Eric Ofosu; Shen, Bin

doi:10.1016/j.ins.2019.12.089

Cited by 55 publications

(14 citation statements)

References 22 publications

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“…In the quantitative analysis, owing to the incompleteness of prior information and the complexity of the decision-making environment, every basic event in the fault tree was uncertain. Huang et al [21] proposed a method that included fault tree and fuzzy D-S evidential reasoning to analyze accidents in the railway transport system of dangerous goods, so as to solve problems of uncertainty modeling and information fusion with regard to the analysis of accidents caused by transporting hazardous goods. Huang et al [22] proposed a simple, dynamic, systematic, and quantitative extended safety failure event network (SFEN) method to analyze the reliability and safety with regard to accidents caused by the typical railway dangerous goods transport system in the past.…”

Section: Literature Reviewmentioning

confidence: 99%

Grid-Based Employee Safety Behavior Risk Assessment of the Train Operation Department

Zhang

2022

Processes

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In the train operation department, the most important and dynamic factor is that the department employees are involved in all areas. Realizing the dynamic control of “key person, key event, and key period” to fundamentally curb employee inertia violation is a significant issue that needs to be solved on the railway site. The traditional “probability–severity” two-dimensional risk assessment model is carried out from the perspective of the system, ignoring the spatiotemporal risk characteristics of the individual, and a large amount of hazard factor data generated in the operation process is not applied in the risk assessment process. As a result, safety behavior risk practice lacks pertinence, accuracy, and individuation. This study proposes a safety behavior risk assessment model based on the grid management and hazard factor assignment function to improve the traditional two-dimensional risk matrix. By introducing spatial location variables, the method accurately locates and classifies the site staff and organizes the disorder and lack of associated risk data with regard to time and space. With a focus on the hazard factor, the induced intensity is proposed for the first time and considered as the input of probability calculation to innovate the traditional “probability–severity” risk matrix. Finally, the methodology is applied to the risk event assessment of “the assistant watchman doesn’t appear as required” scenario in the Huangyangcheng station of Shenshuo Railway, and the evaluation results realize the personalized evaluation of the risk event in different cell grids.

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Section: Literature Reviewmentioning

confidence: 99%

Grid-Based Employee Safety Behavior Risk Assessment of the Train Operation Department

Zhang

2022

Processes

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“…e key point for the application of these methods lies in how to reasonably determine the relations between different factors. However, the relations are always measured artificially, e.g., in accordance with expert opinions, which varies considerably from person to person, and compared to using historical case data are criticized for subjectivity [43,44]. Second, in order to increase the effectiveness and accuracy of node importance ranking in complex networks, great endeavor has been made to improve the traditional NNI evaluation methods by a variety of prior studies.…”

Section: Research Gapmentioning

confidence: 99%

Causation of Metro Operation Accidents in China: Calculation of Network Node Importance Based on DEMATEL and ISM

et al. 2021

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Continuous metro-operation accidents lead to serious economic loss and a negative social impact. The accident causation analysis is of great significance for accident prevention and metro operation safety promotion. Network node importance (NNI) evaluation has been widely used as a tool for ranking the nodes in complex networks; however, traditional indicators such as degree centrality (DC) are insufficient for examining accident networks. This study proposed an improved method by integrating decision making trail and evaluation laboratory (DEMATEL) and interpretive structural modeling (ISM) into traditional NNI evaluation, where the key nodes are determined by both the nature of the accident network topology and the contribution of the nodes to accident development. Drawing on this method, 32 accident causal factors were identified and prioritized on the ground of 248 accident cases. It was found that 14 important factors related to staff (e.g., “driver noncompliance”), environment (e.g., “extrinsic nature disturbance”), passenger (e.g., “passenger sudden illness”), and machine (e.g., “track failures”) should be given priority in safety management due to their significant tendency of causing metro accidents. Theoretical and managerial implications were discussed to provide useful insights into the understanding of the causation of metro accidents and form a basis for metro managers to develop targeted safety countermeasures related to metro operation. The proposed hybrid method is proven effective in investigating accident networks involving sequential and casual relationships and revealing factors with high possibility to increase accidents.

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“…Classification models are popular both for the analysis of railroad accidents and all accidents in general [18,19]. The decision to use them is primarily influenced by the form of the dependent variable, as well as the nature of the factors that may affect the number of such incidents or the injuries caused by them.…”

Section: Introductionmentioning

confidence: 99%

Classification Trees in the Assessment of the Road–Railway Accidents Mortality

et al. 2021

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A special element of road safety research is accidents at the interface of the road and rail system. Due to their low share in the total number of incidents, they are not a popular subject of analyses but rather an element of collective studies, whereas the specificity of the road–rail accidents requires a separate characteristic, allowing, on the one hand, to categorize these types of incidents, and on the other, to specify the factors that affect them, along with an assessment of the strength of this impact. It is important to include in such analyses all potential predictors, both qualitative and quantitative. Moreover, the literature considers most often a number of accidents while, according to the authors, it does not fully reflect the scale of the danger. A better evaluation would be the victim’s degree of injury. Therefore, the purpose of this article is to assess the likelihood of occurrence of various effects of road–rail accidents in the aspect of selected factors. Due to the ordinal form of the dependent variable, the classification trees method was used. The results obtained not only allow the characterization and assessment of the danger but also constitute guidelines for taking preventive actions.

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Fault Tree and Fuzzy D-S Evidential Reasoning combined approach: An application in railway dangerous goods transportation system accident analysis

Cited by 55 publications

References 22 publications

Grid-Based Employee Safety Behavior Risk Assessment of the Train Operation Department

Grid-Based Employee Safety Behavior Risk Assessment of the Train Operation Department

Causation of Metro Operation Accidents in China: Calculation of Network Node Importance Based on DEMATEL and ISM

Classification Trees in the Assessment of the Road–Railway Accidents Mortality

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