Crash frequency analysis of different types of urban roadway segments using generalized additive model.
BACKGROUND
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.


CONCLUSIONS
The generalized additive model provides a very promising alternative for crash frequency modeling and other safety studies.
Zachry Department of Civil Engineering, Texas A&M University, 3136 TAMU, College Station, TX 77843-3136, USA. yzhang@civil.tamu.edu
Yunlong
Y
Zhang
Yuanchang
Y
Xie
Linhua
L
Li
D000063:Accidents, Traffic / Q000706:statistics & numerical data*; D001334:Automobile Driving / Q000706:statistics & numerical data*; D006801:Humans; D015233:Models, Statistical; D016012:Poisson Distribution; D012044:Regression Analysis; D018570:Risk Assessment / Q000379:methods*; D013781:Texas