Bayesian hierarchical analysis on crash prediction models

Huang, Helai, Chin, Hoong Chor, & Haque, Md. Mazharul (2008) Bayesian hierarchical analysis on crash prediction models. In 87th Annual Meeting of Transportation Research Board (TRB), Transportation Research Board, Capital Hilton, Washington DC.

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Traditional crash prediction models, such as generalized linear regression models, are incapable of taking into account the multilevel data structure, which extensively exists in crash data. Disregarding the possible within-group correlations can lead to the production of models giving unreliable and biased estimates of unknowns. This study innovatively proposes a -level hierarchy, viz. (Geographic region level – Traffic site level – Traffic crash level – Driver-vehicle unit level – Vehicle-occupant level) Time level, to establish a general form of multilevel data structure in traffic safety analysis. To properly model the potential cross-group heterogeneity due to the multilevel data structure, a framework of Bayesian hierarchical models that explicitly specify multilevel structure and correctly yield parameter estimates is introduced and recommended. The proposed method is illustrated in an individual-severity analysis of intersection crashes using the Singapore crash records.

This study proved the importance of accounting for the within-group correlations and demonstrated the flexibilities and effectiveness of the Bayesian hierarchical method in modeling multilevel structure of traffic crash data.

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ID Code: 51218
Item Type: Conference Paper
Refereed: Yes
Keywords: Hierarchical regression model, Crash prediction, Bayesian analysis
Subjects: Australian and New Zealand Standard Research Classification > MATHEMATICAL SCIENCES (010000) > STATISTICS (010400) > Applied Statistics (010401)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > CIVIL ENGINEERING (090500) > Transport Engineering (090507)
Divisions: Current > Research Centres > Centre for Accident Research & Road Safety - Qld (CARRS-Q)
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2008 [please consult the author]
Deposited On: 29 Jun 2012 00:33
Last Modified: 26 Jun 2017 14:41

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