Analyzing Risk Factors for Fatality in Urban Traffic Crashes: A Case Study of Wuhan, China

Zhensheng Wang, Yang Yue, Qingquan Li, Ke Nie, Wei Tu and Shi Liang
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Zhensheng Wang: Shenzhen Key Laboratory of Spatial Smart Sensing and Services, College of Civil Engineering, Shenzhen University, Shenzhen 518060, China
Yang Yue: Shenzhen Key Laboratory of Spatial Smart Sensing and Services, College of Civil Engineering, Shenzhen University, Shenzhen 518060, China
Qingquan Li: Shenzhen Key Laboratory of Spatial Smart Sensing and Services, College of Civil Engineering, Shenzhen University, Shenzhen 518060, China
Ke Nie: Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Land and Resources, Shenzhen 518034, China
Wei Tu: Shenzhen Key Laboratory of Spatial Smart Sensing and Services, College of Civil Engineering, Shenzhen University, Shenzhen 518060, China
Shi Liang: Shenzhen Prevention and Treatment Center for Occupational Diseases, 2019 Buxin Road, Luohu District, Shenzhen 518010, China

Sustainability, 2017, vol. 9, issue 6, 1-13

Abstract: How to maintain public transit safety and sustainability has become a major concern for the department of Road Traffic Administration. This study aims to analyze the risk factors that contribute to fatality in road traffic crashes using a 5-year police-reported dataset from the Wuhan Traffic Management Bureau. Four types of variables, including driving experience, environmental factor, roadway factor and crash characteristic, were examined in this research by a case-control study. To obtain a comprehensive understanding of crash fatality, this study explored a detailed set of injury-severity risk factors such as impact direction, light and weather conditions, crash characteristic, driving experience and high-risk driving behavior. Based on the results of statistical analyses, fatality risk of crash-involved individuals was significantly associated with driving experience, season, light condition, road type, crash type, impact direction, and high-risk driving behavior. This study succeeded in identifying the risk factors for fatality of crash-involved individuals using a police-reported dataset, which could provide reliable information for implementing remedial measures and improving sustainability in urban road network. A more detailed list of explanatory variables could enhance the accountability of the analysis.

Keywords: crash fatality; risk factors; case-control study; urbanization (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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