Wu, Q., Song, D., Wang, C. et al. (5 more authors) (2023) Analysis of Injury Severity of Drivers Involved Different Types of Two-Vehicle Crashes Using Random-Parameters Logit Models with Heterogeneity in Means and Variances. Journal of Advanced Transportation, 2023. 3399631. ISSN 0197-6729
Abstract
This study proposes random-parameters multinomial logit models, with heterogeneity in means and variances, to explore the differences in the factors influencing injury severities of drivers involved in different types of two-vehicle crashes. The models are verified using crash data from the United Kingdom (UK) over three years (2016–2018). Three types of crashes are separately identified (car-car, car-truck, and truck-truck crashes). In this study, a wide variety of potential variables, including the driver, vehicle, road, and environmental characteristics, are considered, with two possible injury-severity outcomes: severe and slight injury. The results show that unobserved heterogeneity existed for young drivers in both car-car and truck-truck crash models and the 30 mph speed limit in the three separate models. Remarkably variations are observed in crashes involving different types of vehicles. The driver’s age and gender, speeding, sideswipes, presence of junctions, weekdays, unlit, and weather conditions significantly impact driver-injury severities in various types of vehicle crashes. These findings are expected to help policymakers seek to improve highway safety and implement proper safety countermeasures.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023 Qiang Wu et al. 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. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds) > Centre for Spatial Analysis & Policy (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 15 Jul 2024 14:03 |
Last Modified: | 15 Jul 2024 14:03 |
Status: | Published |
Publisher: | Wiley |
Identification Number: | 10.1155/2023/3399631 |
Sustainable Development Goals: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:214729 |