Investigating Contributors to Hit-and-Run Violations in Urban River-Crossing Road Tunnels: A Random Parameter Logit Model With Heterogeneity in Means
The hit-and-run caused a delay in medical assistance to the victim and posed a significant threat to the safety of drivers in road tunnels. This study investigates the potential factors contributing to drivers’ hit-and-run violations in river-crossing tunnels. This paper built three models (the logi...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/atr/5635494 |
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| _version_ | 1832591096185618432 |
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| author | Dengzhong Wang Jiayu Zhou Gen Li Haigen Min Chenming Jiang Linjun Lu |
| author_facet | Dengzhong Wang Jiayu Zhou Gen Li Haigen Min Chenming Jiang Linjun Lu |
| author_sort | Dengzhong Wang |
| collection | DOAJ |
| description | The hit-and-run caused a delay in medical assistance to the victim and posed a significant threat to the safety of drivers in road tunnels. This study investigates the potential factors contributing to drivers’ hit-and-run violations in river-crossing tunnels. This paper built three models (the logit model, the random parameter logit model, and the random parameter logit model with heterogeneity in means) based on a dataset consisting of crashes reported in thirteen river-crossing tunnels in Shanghai, China. Potential contributors from five aspects (offending drivers, vehicle conditions, tunnel characteristics, environmental conditions, and crash information) were explored. Results showed that the random parameter logit model with heterogeneity in means produced the highest fitting accuracy among the three models. Eight important variables (nighttime, single-vehicle, multi-vehicle, two-wheeled vehicle, passenger car, heavy goods vehicle, rear-end, and short tunnel) were found to affect hit-and-run violations significantly. The research has highlighted that nighttime and short tunnel increase the likelihood of hit-and-run and other variables are the opposite. The results of this study could provide useful information for the development of interventions to improve the level of safety in tunnels and reduce the rate of hit-and-run offenses. |
| format | Article |
| id | doaj-art-5a96978e9ebf41f8a92c4cea6021c64e |
| institution | Kabale University |
| issn | 2042-3195 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-5a96978e9ebf41f8a92c4cea6021c64e2025-01-23T05:00:01ZengWileyJournal of Advanced Transportation2042-31952025-01-01202510.1155/atr/5635494Investigating Contributors to Hit-and-Run Violations in Urban River-Crossing Road Tunnels: A Random Parameter Logit Model With Heterogeneity in MeansDengzhong Wang0Jiayu Zhou1Gen Li2Haigen Min3Chenming Jiang4Linjun Lu5Department of Architecture and Urban PlanningDepartment of Automobile and Traffic EngineeringDepartment of Automobile and Traffic EngineeringDepartment of Automobile and Traffic EngineeringDepartment of Information EngineeringSchool of Naval Architecture, Ocean and Civil EngineeringThe hit-and-run caused a delay in medical assistance to the victim and posed a significant threat to the safety of drivers in road tunnels. This study investigates the potential factors contributing to drivers’ hit-and-run violations in river-crossing tunnels. This paper built three models (the logit model, the random parameter logit model, and the random parameter logit model with heterogeneity in means) based on a dataset consisting of crashes reported in thirteen river-crossing tunnels in Shanghai, China. Potential contributors from five aspects (offending drivers, vehicle conditions, tunnel characteristics, environmental conditions, and crash information) were explored. Results showed that the random parameter logit model with heterogeneity in means produced the highest fitting accuracy among the three models. Eight important variables (nighttime, single-vehicle, multi-vehicle, two-wheeled vehicle, passenger car, heavy goods vehicle, rear-end, and short tunnel) were found to affect hit-and-run violations significantly. The research has highlighted that nighttime and short tunnel increase the likelihood of hit-and-run and other variables are the opposite. The results of this study could provide useful information for the development of interventions to improve the level of safety in tunnels and reduce the rate of hit-and-run offenses.http://dx.doi.org/10.1155/atr/5635494 |
| spellingShingle | Dengzhong Wang Jiayu Zhou Gen Li Haigen Min Chenming Jiang Linjun Lu Investigating Contributors to Hit-and-Run Violations in Urban River-Crossing Road Tunnels: A Random Parameter Logit Model With Heterogeneity in Means Journal of Advanced Transportation |
| title | Investigating Contributors to Hit-and-Run Violations in Urban River-Crossing Road Tunnels: A Random Parameter Logit Model With Heterogeneity in Means |
| title_full | Investigating Contributors to Hit-and-Run Violations in Urban River-Crossing Road Tunnels: A Random Parameter Logit Model With Heterogeneity in Means |
| title_fullStr | Investigating Contributors to Hit-and-Run Violations in Urban River-Crossing Road Tunnels: A Random Parameter Logit Model With Heterogeneity in Means |
| title_full_unstemmed | Investigating Contributors to Hit-and-Run Violations in Urban River-Crossing Road Tunnels: A Random Parameter Logit Model With Heterogeneity in Means |
| title_short | Investigating Contributors to Hit-and-Run Violations in Urban River-Crossing Road Tunnels: A Random Parameter Logit Model With Heterogeneity in Means |
| title_sort | investigating contributors to hit and run violations in urban river crossing road tunnels a random parameter logit model with heterogeneity in means |
| url | http://dx.doi.org/10.1155/atr/5635494 |
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