Investigation of models for relating roundabout safety to predicted speed.
Despite widespread recognition of operating speed as a key safety-related variable for roundabouts, there is no consensus on the best models for capturing the relationship between crashes and speed, or, for that matter, on how speed can be estimated in situations where it cannot be observed (such as when a roundabout is being designed or redesigned). This paper uses US and Italian roundabout approach-level data to investigate models relating safety to various measures of predicted speed. This is an indirect approach for developing safety models for estimating the effects of design features, the premise being that these features can better predict speed, which, in turn, can be used as a predictor of crash frequency. After exploring various possibilities, the approach average speed (AAS) - defined as the average of entry, upstream circulating and exiting speeds in this study - was found to be the speed measure that best predicts safety. US data were used to develop a Bayesian Poisson-gamma safety model based on predicted AAS with random coefficients and varying dispersion parameter. This model structure was not appropriate for the Italian data used to examine whether the approach could be generalized to data for another country. For that data, a zero-inflated Poisson (ZIP) model was found to be suitable. Notwithstanding the heterogeneity of the model structure, the investigation suggests that the indirect approach for evaluating the safety of a roundabout is a sound one in that it can preserve model parsimony while capturing the effects of design changes that affect safety.
Department of Civil Engineering, Ryerson University, 350 Victoria Street, Toronto, Ontario M5B 2K3, Canada. yongsheng.chen@ryerson.ca
Yongsheng
Y
Chen
Bhagwant
B
Persaud
Emanuele
E
Sacchi
Marco
M
Bassani
D000054:Acceleration; D000063:Accidents, Traffic / Q000706:statistics & numerical data*; D001334:Automobile Driving; D004779:Environment Design; D006801:Humans; D007558:Italy / Q000453:epidemiology; D008962:Models, Theoretical; D016012:Poisson Distribution; D011237:Predictive Value of Tests; D011336:Probability; D014481:United States / Q000453:epidemiology