Accident analysis model based on Bayesian Network and Evidential Reasoning approach |
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| Authors: | Yan Fu Wang Min Xie Kwai-Sang Chin Xiu Ju Fu |
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| Institution: | 1. Department of Safety Engineering, China University of Petroleum, No.66, Chang Jiang West Road, Qing Dao 266555, China;2. Department of Industrial & Systems Engineering, National University of Singapore, 10 Kent Ridge Crescent, Singapore 119260, Singapore;3. Department of Systems Engineering and Engineering Management, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon Tong, Hong Kong, China;4. Institute of High Performance Computing, 1 Fusionopolis Way, Singapore 138632, Singapore |
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| Abstract: | In this paper, an accident analysis model is proposed to develop the cost-efficient safety measures for preventing accidents. The model comprises two parts. In the first part, a quantitative accident analysis model is built by integrating Human Factors Analysis and Classification System (HFACS) with Bayesian Network (BN), which can be utilized to present the corresponding prevention measures. In the second part, the proposed prevention measures are ranked in a cost-effectiveness manner through Best-Fit method and Evidential Reasoning (ER) approach. A case study of vessel collision is analyzed as an illustration. The case study shows that the proposed model can be used to seek out accident causes and rank the derived safety measures from a cost-effectiveness perspective. The proposed model can provide accident investigators with a tool to generate cost-efficient safety intervention strategies. |
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