Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/105712
Title: Investigation into interactions between accident consequences and traffic signs : a Bayesian bivariate Tobit quantile regression approach
Authors: Xu, Xuecai
Šarić, Željko
Keywords: Bayesian Approach
Engineering::Civil engineering
Bayesian Bivariate Tobit Quantile
Issue Date: 2018
Source: Xu, X., & Šarić, Ž. (2018). Investigation into interactions between accident consequences and traffic signs : a Bayesian bivariate Tobit quantile regression approach. Journal of Advanced Transportation, 2018, 5032497-. doi:10.1155/2018/5032497
Series/Report no.: Journal of Advanced Transportation
Abstract: 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 (1) low visibility and the number of invalid traffic signs per km increased the accident rate of material damage, death, or injury; (2) average speed limit exhibited a close relation with accident rate; and (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 injury.
URI: https://hdl.handle.net/10356/105712
http://hdl.handle.net/10220/49549
ISSN: 0197-6729
DOI: 10.1155/2018/5032497
Rights: © 2018 Xuecai Xu and Željko Šarić. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:CEE Journal Articles

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