Traffic accidents involving fatigue driving and their extent of casualties |
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| Affiliation: | 1. Center for Studies of Hong Kong, Macao and Pearl River Delta, Sun Yat-Sen University, Xingang Xi Road, Guangzhou, China;2. Department of Management Sciences, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong;3. School of Statistics, Beijing Normal University, Beijing, China;4. China Center for Economic Research, National School of Development, Peking University, Yiheyuan Road, Beijing, China;1. Department de Psychologie, Université de Montréal, Montréal, Québec, Canada;2. Traffic Injury Research Foundation, Ottawa, Ontario, Canada;3. Research Centre of the Douglas Mental Health University Institute, Verdun, Québec, Canada;4. Department of Psychiatry, McGill University, Montreal, Québec, Canada;5. Foster Addiction Rehabilitation Centre, St. Philippe de Laprairie, Québec, Canada;1. Complexity & Computational Population Health Group, Department of Health & Kinesiology, Texas A&M University, 4243 TAMU, College Station, TX 77843-4243, United States;2. Department of Health & Exercise Science, Appalachian State University, 111 Rivers Street, Boone, NC 28608, United States;3. Rosen College of Hospitality Management, University of Central Florida, 9907 Universal Blvd., Orlando, FL 32819, United States;4. Department of Kinesiology, University of North Carolina Greensboro, P.O. Box 26170, Greensboro, NC 27402-6170, United States;1. Urban and Regional Sustainability Group, Universidad de Los Andes, Carrera 1 Este No. 19 A – 40, Edificio Mario Laserna, Bogotá, Colombia;2. Department of Civil and Environmental Engineering, Universidad de Los Andes, Bogotá, Colombia;1. Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan, Hubei, China;2. Department of Civil and Environmental Engineering, University of Alberta, Edmonton, Alberta, Canada |
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| Abstract: | The rapid progress of motorization has increased the number of traffic-related casualties. Although fatigue driving is a major cause of traffic accidents, the public remains not rather aware of its potential harmfulness. Fatigue driving has been termed as a “silent killer.” Thus, a thorough study of traffic accidents and the risk factors associated with fatigue-related casualties is of utmost importance. In this study, we analyze traffic accident data for the period 2006–2010 in Guangdong Province, China. The study data were extracted from the traffic accident database of China's Public Security Department. A logistic regression model is used to assess the effect of driver characteristics, type of vehicles, road conditions, and environmental factors on fatigue-related traffic accident occurrence and severity. On the one hand, male drivers, trucks, driving during midnight to dawn, and morning rush hours are identified as risk factors of fatigue-related crashes but do not necessarily result in severe casualties. Driving at night without street-lights contributes to fatigue-related crashes and severe casualties. On the other hand, while factors such as less experienced drivers, unsafe vehicle status, slippery roads, driving at night with street-lights, and weekends do not have significant effect on fatigue-related crashes, yet accidents associated with these factors are likely to have severe casualties. The empirical results of the present study have important policy implications on the reduction of fatigue-related crashes as well as their severity. |
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| Keywords: | Fatigue driving Traffic accident Road safety |
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