Crash frequency analysis of different types of urban roadway segments using generalized additive model Academic Article

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.

authors

• Zhang, Yunlong

published proceedings

• J Safety Res

author list (cited authors)

• Zhang, Y., Xie, Y., & Li, L.

citation count

• 48

complete list of authors

• Zhang, Yunlong||Xie, Yuanchang||Li, Linhua

publication date

• January 2012

publisher

• Elsevier  Publisher

published in

• JOURNAL OF SAFETY RESEARCH  Journal

keywords

• Accidents, Traffic
• Automobile Driving
• Humans
• Models, Statistical
• Poisson Distribution
• Regression Analysis
• Risk Assessment
• Texas

Digital Object Identifier (DOI)

• 10.1016/j.jsr.2012.01.003

start page

• 107

end page

• 114

volume

• 43

issue

• 2

URL

• http://dx.doi.org/10.1016/j.jsr.2012.01.003