Analysis of factors affecting serious multi-fatality crashes in China based on Bayesian network structure

This study aims to identify and analyze risk factors affecting serious multi-fatality crashes using Bayesian networks. First, a Bayesian network structure was constructed based on expert experience and the Dempster–Shafer evidence theory. Second, the structure was amended to satisfy the conditional-...

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Main Authors: Shengxue Zhu, Xiaonan Cai, Jian Lu, Yichuan Peng
Format: Article
Language:English
Published: SAGE Publishing 2017-06-01
Series:Advances in Mechanical Engineering
Online Access:https://doi.org/10.1177/1687814017704145
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spelling doaj-02bad6ffa48346b78566857b92ba60492020-11-25T01:27:33ZengSAGE PublishingAdvances in Mechanical Engineering1687-81402017-06-01910.1177/1687814017704145Analysis of factors affecting serious multi-fatality crashes in China based on Bayesian network structureShengxue Zhu0Xiaonan Cai1Jian Lu2Yichuan Peng3Faculty of Transportation Engineering, Huaiyin Institute of Technology, Huaian, ChinaCCCC Third Harbor Engineering Co. Ltd., Shanghai, ChinaSchool of Transportation Engineering, Tongji University, Shanghai, ChinaSchool of Transportation Engineering, Tongji University, Shanghai, ChinaThis study aims to identify and analyze risk factors affecting serious multi-fatality crashes using Bayesian networks. First, a Bayesian network structure was constructed based on expert experience and the Dempster–Shafer evidence theory. Second, the structure was amended to satisfy the conditional-independence test. Finally, 484 serious multi-fatality crashes for the period 2000–2012 in China were inputted into the Bayesian network to calculate the posterior probability of each factor. Results showed that the most influential factor was driver behavior, followed by vehicle condition, road condition, and external environment. And compared to the other behaviors, speeding and mistaken adjustment had greater influence on serious crashes. The findings in this study provide useful and valuable information for engineers to take corrective and preventative measures to reduce the probability for serious multi-fatality crashes.https://doi.org/10.1177/1687814017704145
collection DOAJ
language English
format Article
sources DOAJ
author Shengxue Zhu
Xiaonan Cai
Jian Lu
Yichuan Peng
spellingShingle Shengxue Zhu
Xiaonan Cai
Jian Lu
Yichuan Peng
Analysis of factors affecting serious multi-fatality crashes in China based on Bayesian network structure
Advances in Mechanical Engineering
author_facet Shengxue Zhu
Xiaonan Cai
Jian Lu
Yichuan Peng
author_sort Shengxue Zhu
title Analysis of factors affecting serious multi-fatality crashes in China based on Bayesian network structure
title_short Analysis of factors affecting serious multi-fatality crashes in China based on Bayesian network structure
title_full Analysis of factors affecting serious multi-fatality crashes in China based on Bayesian network structure
title_fullStr Analysis of factors affecting serious multi-fatality crashes in China based on Bayesian network structure
title_full_unstemmed Analysis of factors affecting serious multi-fatality crashes in China based on Bayesian network structure
title_sort analysis of factors affecting serious multi-fatality crashes in china based on bayesian network structure
publisher SAGE Publishing
series Advances in Mechanical Engineering
issn 1687-8140
publishDate 2017-06-01
description This study aims to identify and analyze risk factors affecting serious multi-fatality crashes using Bayesian networks. First, a Bayesian network structure was constructed based on expert experience and the Dempster–Shafer evidence theory. Second, the structure was amended to satisfy the conditional-independence test. Finally, 484 serious multi-fatality crashes for the period 2000–2012 in China were inputted into the Bayesian network to calculate the posterior probability of each factor. Results showed that the most influential factor was driver behavior, followed by vehicle condition, road condition, and external environment. And compared to the other behaviors, speeding and mistaken adjustment had greater influence on serious crashes. The findings in this study provide useful and valuable information for engineers to take corrective and preventative measures to reduce the probability for serious multi-fatality crashes.
url https://doi.org/10.1177/1687814017704145
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AT xiaonancai analysisoffactorsaffectingseriousmultifatalitycrashesinchinabasedonbayesiannetworkstructure
AT jianlu analysisoffactorsaffectingseriousmultifatalitycrashesinchinabasedonbayesiannetworkstructure
AT yichuanpeng analysisoffactorsaffectingseriousmultifatalitycrashesinchinabasedonbayesiannetworkstructure
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