Presentation 2003/3/19
Applicability of Statistical Models for Risk Analyses : A Probabilistic Model of Support Systems for Prevention of Right-Turn Collisions
Haihong Ye, Tsuneharu Shimodaira, Yoshinobu Sato, Koichi Suyama,
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Abstract(in English) In quantitative risk analyses, the top event of fault tree (FT) is originated from basic events through logical causation mechanisms. The occurrences of basic events are often modeled with failure and repair rates with exponential distributions. However, the exponential distribution could not always reflect the reality in some cases where normal or other types of distribution should be adapted. In this paper, Monte Carlo simulations are practiced for the risk estimation of turning to the right collisions caused by automobiles. Comparisons are made between two statistic models, exponential and normal distributions. The result shows the deviation rates are within 10% for those cases. It is concluded that the exponential distribution is applicable to the probabilistic models of FTA where normal distribution would be more suitable.
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Keyword(in English) Right-Turn Collision Prevention System(RCPS) / Sequential Failure Logic(SFL) / Monte Carlo Simulations(MCS)
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Conference Date 2003/3/19(1days)
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Language JPN
Title (in Japanese) (See Japanese page)
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Title (in English) Applicability of Statistical Models for Risk Analyses : A Probabilistic Model of Support Systems for Prevention of Right-Turn Collisions
Sub Title (in English)
Keyword(1) Right-Turn Collision Prevention System(RCPS)
Keyword(2) Sequential Failure Logic(SFL)
Keyword(3) Monte Carlo Simulations(MCS)
1st Author's Name Haihong Ye
1st Author's Affiliation Tokyo University of Mercantile Marine()
2nd Author's Name Tsuneharu Shimodaira
2nd Author's Affiliation Tokyo University of Mercantile Marine
3rd Author's Name Yoshinobu Sato
3rd Author's Affiliation Tokyo University of Mercantile Marine
4th Author's Name Koichi Suyama
4th Author's Affiliation Tokyo University of Mercantile Marine
Date 2003/3/19
Paper #
Volume (vol) vol.102
Number (no) 740
Page pp.pp.-
#Pages 4
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