Identifying the safety factors over traffic signs in state roads using a panel quantile regression approach

This study intended to investigate the interactions between accident rate and traffic signs on state roads located in Croatia and accommodate the heterogeneity attributed to unobserved factors. Data from 130 state roads between 2012 and 2016 were collected from Traffic Accident Database System maintained by the Republic of Croatia's Ministry of the Interior.

To address the heterogeneity, a panel quantile regression model was proposed, in which a quantile regression model offers a more complete view and a highly comprehensive analysis of the relationship between accident rate and traffic signs, and the panel data model accommodates the heterogeneity attributed to unobserved factors.

Results revealed that (1) low visibility of material damage (MD) and death or injury (DI) increased the accident rate; (2) the number of mandatory signs and the number of warning signs were more likely to reduce the accident rate; (3) the average speed limit and the number of invalid traffic signs per kilometer exhibited a high accident rate.

To our knowledge, this study is the first attempt to analyze the interactions between accident consequences and traffic signs by employing a panel quantile regression model; by including visibility, the present study demonstrates that low visibility causes a relatively higher risk of MD and DI. It is noteworthy that average speed limit positively corresponds with accident rate; the number of mandatory signs and the number of warning signs are more likely to reduce the accident rate; and the number of invalid traffic signs per kilometer is significant for the accident rate; thus, regular maintenance should be performed for a safer roadway environment.