Željko Šarić

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

Abstract Objective: 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. Methods: 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: 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. Conclusions: 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.

Turbo Roundabouts: A Brief Safety, Efficiency and Geometry Design Review

The application popularity of various roundabout types around the world has driven substantial efforts to optimize their geometry design. Implementing effective roundabouts requires optimizing traffic safety (TS) and traffic (operational) efficiency (TE) while considering various geometry and other factors. In multi-lane roundabouts driver indecision and misunderstanding of the driving rules and situations can lead to weaving conflicts and accidents. These accidents are frequent and often affect TS and TE. The turbo roundabout concept has emerged as a possible alternative to conventional multi-lane roundabouts, aiming to improve exclusively TS. However, some studies do not allow definitive conclusions about their TE (capacity) influence. To capture a relationship between turbo roundabout design, TS and TE parameters brief overview of the latest guidelines and studies is presented here.

Investigation into Interactions between Accident Consequences and Traffic Signs: A Bayesian Bivariate Tobit Quantile Regression Approach

This study intended to investigate the interactions between accident severity levels and traffic signs in state roads located in Croatia and explore the correlation between accident severity levels and heterogeneity attributed to unobserved factors. The data from 460 state roads between 2012 and 2016 were collected from Traffic Accident Database System maintained by the Republic of Croatia Ministry of the Interior. To address the correlation and heterogeneity, Bayesian bivariate Tobit quantile regression models were proposed, in which the bivariate framework addressed the correlation of residuals with Bayesian approach, while the Tobit quantile regression model accommodated the heterogeneity due to unobserved factors. By comparing the Bayesian bivariate Tobit quantile and mean regression models, the proposed quantile models showed priority to mean model. Results revealed that low visibility and the number of invalid traffic signs per km increased the accident rate of material damage, death, or injury; average speed limit exhibited a close relation with accident rate; and the number of mandatory signs was more likely to reduce the accident rate of material damage, while the number of warning signs was significant for accident rate of death or injury.

Accident severity levels and traffic signs interactions in state roads: a seemingly unrelated regression model in unbalanced panel data approach

This study intended to investigate the interactions between accident severity levels and traffic signs in state roads located in Croatia, and explore the correlation within accident severity levels and heterogeneity attributed to unobserved factors. The data from 410 state roads between 2012 and 2016 were collected from Traffic Accident Database System maintained by the Republic of Croatia Ministry of the Interior. To address the correlation and heterogeneity, a seemingly unrelated regression (SUR) model in unbalanced panel data approach was proposed, in which the seemingly unrelated model addressed the correlation of residuals, while the panel data model accommodated the heterogeneity due to unobserved factors. By comparing the pooled, fixed-effects and random-effects SUR models, the random-effects SUR model showed priority to the other two. Results revealed that (1) low visibility and the number of invalid traffic signs per km increased the accident rate of material damage, death or injured; (2) average speed limit exhibited a high accident rate of death or injured; (3) the number of mandatory signs was more likely to reduce the accident rate of material damage, while the number of warning signs was significant for accident rate of death or injured.