Abstract Introduction This paper utilizes generalized additive model to explore the potential non-linear relationship between crash frequency and exposure on different types of urban roadway segments. Methods Generalized additive models are used to analyze crash frequency data and compared with the commonly used crash rate method and generalized linear models using a five-year crash data set from Houston, Texas. Results The study shows that the relationship between crash frequency and exposure varies by segment type and the linearity may only approximately exist in certain segment types. In addition, the generalized additive modeling results suggest that such relationship curves may not be monotonic. Finally, this study demonstrates that generalized additive models in general provide better flexibility and modeling performance than generalized linear models. Impact on Industry The generalized additive model provides a very promising alternative for crash frequency modeling and other safety studies.
Highlights ► We model crash frequency as function of traffic flow on different roadway segment types. ► Approximately linear relationship may only exist for certain segment types. ► For some segment types, the relationship is nonlinear and not monotonic. ► GAM is capable of identifying nonlinear and non‐monotonic relationships.
Crash frequency analysis of different types of urban roadway segments using generalized additive model
Journal of Safety Research ; 43 , 2 ; 107-114
2012-01-01
8 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Crash Frequency Analysis with Generalized Additive Models
Transportation Research Record | 2008
|Crash Frequency Analysis with Generalized Additive Models
Online Contents | 2008
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