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Journal Article

Citation

Yang B, Wu Y, Zhang W. J. Adv. Transp. 2020; 2020: e8890351.

Copyright

(Copyright © 2020, Institute for Transportation, Publisher John Wiley and Sons)

DOI

10.1155/2020/8890351

PMID

unavailable

Abstract

The objective of this study is to analyse the relationship between secondary crash risk and traffic flow states and explore the contributing factors of secondary crashes in different traffic flow states. Crash data and traffic data were collected on the I-880 freeway in California from 2006 to 2011. The traffic flow states are categorised by three-phase traffic theory. The Bayesian conditional logit model has been established to analyse the statistical relationship between the secondary crash probability and various traffic flow states. The results showed that free flow (F) state has the best safety performance of secondary crash and synchronized flow (S) state has the worst safety performance of secondary crashes. The traditional logistic regression model has been used to analyse the contributing factors of secondary crashes in different traffic flow states. The results indicated that the contributing factors in different traffic flow states are significantly different.


Language: en

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