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 201...
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| Format: | Article |
| Language: | English |
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Wiley
2018-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2018/5032497 |
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| _version_ | 1832564694505750528 |
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| author | Xuecai Xu Željko Šarić |
| author_facet | Xuecai Xu Željko Šarić |
| author_sort | Xuecai Xu |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-8c46cedfd89c4850b358c26e49c76cdf |
| institution | Kabale University |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-8c46cedfd89c4850b358c26e49c76cdf2025-02-03T01:10:22ZengWileyJournal of Advanced Transportation0197-67292042-31952018-01-01201810.1155/2018/50324975032497Investigation into Interactions between Accident Consequences and Traffic Signs: A Bayesian Bivariate Tobit Quantile Regression ApproachXuecai Xu0Željko Šarić1School of Civil Engineering and Mechanics, Huazhong University of Science and Technology, Wuhan, ChinaDepartment of Traffic Accident Expertise, Faculty of Transport and Traffic Sciences, University of Zagreb, CroatiaThis 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.http://dx.doi.org/10.1155/2018/5032497 |
| spellingShingle | Xuecai Xu Željko Šarić Investigation into Interactions between Accident Consequences and Traffic Signs: A Bayesian Bivariate Tobit Quantile Regression Approach Journal of Advanced Transportation |
| title | Investigation into Interactions between Accident Consequences and Traffic Signs: A Bayesian Bivariate Tobit Quantile Regression Approach |
| title_full | Investigation into Interactions between Accident Consequences and Traffic Signs: A Bayesian Bivariate Tobit Quantile Regression Approach |
| title_fullStr | Investigation into Interactions between Accident Consequences and Traffic Signs: A Bayesian Bivariate Tobit Quantile Regression Approach |
| title_full_unstemmed | Investigation into Interactions between Accident Consequences and Traffic Signs: A Bayesian Bivariate Tobit Quantile Regression Approach |
| title_short | Investigation into Interactions between Accident Consequences and Traffic Signs: A Bayesian Bivariate Tobit Quantile Regression Approach |
| title_sort | investigation into interactions between accident consequences and traffic signs a bayesian bivariate tobit quantile regression approach |
| url | http://dx.doi.org/10.1155/2018/5032497 |
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