Applying fractional split model to examine the effects of roadway geometric and traffic characteristics on speeding behavior

Objective: The speed selection behaviour of drivers has been reported to vary across driver demographics, psychological attributes, and vehicle-specific factors. In contrast, the effects of roadway geometric, traffic characteristics, and site-specific factors on speed selection are less known. In addition, the relative degree of speeding has received little attention, and so remains relatively unexplored. This study aims to investigate the effects of roadway geometric, traffic characteristics and site-specific factors on the speed selection behaviour of drivers. Methods: A panel mixed logit fractional split model is estimated to analyse the proportion of speed limit violations across highway segments. To account for possible unobserved heterogeneity, the suitability of latent class model specification is also tested. Speeding data were collected from speed cameras along major arterials and highways in Queensland, Australia and were merged with several other data sources including roadway geometric characteristics, spatial features of the surrounding environment, and driver behavioural factors. Results: The results of the panel mixed logit fractional split model suggest a tendency among drivers to commit minor speed limit violations irrespective of causal factors. Among potential road geometric and traffic factors, radius of horizontal curves, percentage of heavy vehicle traffic on segments with divided median, posted speed limit and road functional classification are factors that influence speeding behaviour. Additionally, the deployment of covert speed cameras is found to decrease the likelihood of major speed limit violations along arterials or highways. Conclusions: An understanding of the influence of roadway geometric and traffic characteristics on speeding behaviour of drivers will inform the design of targeted countermeasures in order to reduce speed limit violations along highways