Multi-level Bayesian safety analysis with unprocessed Automatic Vehicle Identification data for an urban expressway
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- 作者：Qi Shia ; shiqi@knights.ucf.edu" class="auth_mail" title="E-mail the corresponding author ; Mohamed Abdel-Atya ; m.aty@ucf.edu" class="auth_mail" title="E-mail the corresponding author ; Rongjie Yub ; yurongjie@tongji.edu.cn" class="auth_mail" title="E-mail the corresponding author
- 关键词：Urban expressway safety ; Automatic Vehicle Identification ; Multi-level model ; Random parameters ; Bayesian inference
- 刊名：Accident Analysis & Prevention
- 出版年：2016
- 出版时间：March 2016
- 年：2016
- 卷：88
- 期：Complete
- 页码：68-76
- 全文大小：990 K
文摘
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The unprocessed Automatic Vehicle Identification data were used in safety models.
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Multi-level model should be implemented if the data exhibit hierarchical structure.
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Random parameters model could deal with unobserved heterogeneity among observations.
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Lower speed and higher speed variation contribute to crashes.
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Segments with auxiliary lanes deserve extra examination in safety evaluation.