Investigation on the injuries of drivers and copilots in rear-end crashes between trucks based on real world accident data in China

Abstract This study aimed to investigate the distributing factors affecting the injury severity of drivers and copilots in rear-end crashes between trucks on expressways, based on real world accident data in China. For this purpose, a total of 92 crashes on expressways in Changsha and Zhuzhou areas from 2010 to 2016 were selected. The data was analyzed statistically regarding the corresponding driver, vehicle, roadway and environment characteristics. Firstly, descriptive statistics were conducted to understand the rear-end crash characteristics. Then, ordered logistic regression models were utilized to identify the contributing factors affecting the injury severity of drivers and copilots in rear trucks. Finally, the fatality risk models with respect to relative speed were developed through single logistic regression analyses. The results showed that the probability of driver being fatal decreased if only right fronts of rear trucks were involved in crashes. The probability of copilot being fatal increased if the drivers turned left before crash occurrences or a light truck rear-ended a heavy truck. The relative speed had the highest statistical significance for the truck impact severity. And the copilots were more vulnerable in truck rear-end crashes compared with drivers, with the relative speeds corresponding to 50% probability of being fatal were 32.49 and 35.18 km/h, respectively. The findings from this study provided the theory and data bases for the development of active and passive protection systems.

[1]  Cheol Oh,et al.  Risk Factors Related to Fatal Truck Crashes on Korean Freeways , 2014, Traffic injury prevention.

[2]  Andrew S. Fullerton.  A Conceptual Framework for Ordered Logistic Regression Models , 2009 .

[3]  Yong Peng,et al.  Development of head injury risk functions based on real-world accident reconstruction , 2014 .

[4]  Hongzhi Guan,et al.  A multinomial logit model-Bayesian network hybrid approach for driver injury severity analyses in rear-end crashes. , 2015, Accident; analysis and prevention.

[5]  F. Mannering,et al.  Differences in rural and urban driver-injury severities in accidents involving large-trucks: an exploratory analysis. , 2005, Accident; analysis and prevention.

[6]  Hsing-Chung Chu,et al.  Assessing factors causing severe injuries in crashes of high-deck buses in long-distance driving on freeways. , 2014, Accident; analysis and prevention.

[7]  Jikuang Yang,et al.  Logistic regression analysis of pedestrian casualty risk in passenger vehicle collisions in China. , 2010, Accident; analysis and prevention.

[8]  Niranga Amarasingha,et al.  Gender differences of young drivers on injury severity outcome of highway crashes. , 2014, Journal of safety research.

[9]  Xuedong Yan,et al.  Investigating the influence of curbs on single-vehicle crash injury severity utilizing zero-inflated ordered probit models. , 2013, Accident; analysis and prevention.

[10]  Guangnan Zhang,et al.  Risk factors associated with traffic violations and accident severity in China. , 2013, Accident; analysis and prevention.

[11]  F. Mannering,et al.  Driver aging and its effect on male and female single-vehicle accident injuries: some additional evidence. , 2006, Journal of safety research.

[12]  T L Bunn,et al.  Sleepiness/fatigue and distraction/inattention as factors for fatal versus nonfatal commercial motor vehicle driver injuries. , 2005, Accident; analysis and prevention.

[13]  Joel Liesman,et al.  Estimating the relationship between measured wind speed and overturning truck crashes using a binary logit model. , 2007, Accident; analysis and prevention.

[14]  Li-Yen Chang,et al.  Analysis of driver injury severity in truck-involved accidents using a non-parametric classification tree model , 2013 .

[15]  H. Chiou,et al.  Seatbelt Use and Traumatic Brain Injury in Taiwan: A 16-Year Study , 2015, Iranian journal of public health.

[16]  Athanasios Theofilatos,et al.  Investigation on occupant injury severity in rear-end crashes involving trucks as the front vehicle in Beijing area, China , 2016, Chinese journal of traumatology = Zhonghua chuang shang za zhi.

[17]  Shanshan Zhao,et al.  Weather impacts on single-vehicle truck crash injury severity. , 2016, Journal of safety research.

[18]  Guangquan Lu,et al.  Reconstruction model of vehicle impact speed in pedestrian–vehicle accident , 2009 .

[19]  Samantha Islam,et al.  Comprehensive analysis of single- and multi-vehicle large truck at-fault crashes on rural and urban roadways in Alabama. , 2014, Accident; analysis and prevention.

[20]  Fred L Mannering,et al.  Highway accident severities and the mixed logit model: an exploratory empirical analysis. , 2008, Accident; analysis and prevention.

[21]  Dietmar Otte,et al.  A Study of Adult Pedestrian Head Impact Conditions and Injury Risks in Passenger Car Collisions Based on Real-World Accident Data , 2013, Traffic injury prevention.

[22]  Xiaoyu Zhu,et al.  A comprehensive analysis of factors influencing the injury severity of large-truck crashes. , 2011, Accident; analysis and prevention.

[23]  Bengt Arne Sjöqvist,et al.  On scene injury severity prediction (OSISP) algorithm for car occupants. , 2015, Accident; analysis and prevention.

[24]  A T McCartt,et al.  Factors associated with falling asleep at the wheel among long-distance truck drivers. , 2000, Accident; analysis and prevention.

[25]  Abebayehu Assefa,et al.  Effects of excessive speeding and falling asleep while driving on crash injury severity in Ethiopia: a generalized ordered logit model analysis. , 2014, Accident; analysis and prevention.

[26]  Guizhen Yu,et al.  Are electric self-balancing scooters safe in vehicle crash accidents? , 2016, Accident; analysis and prevention.

[27]  Rafael Consunji,et al.  Underutilization of occupant restraint systems in motor vehicle injury crashes: A quantitative analysis from Qatar , 2016, Traffic injury prevention.

[28]  Sherif Ishak,et al.  Freeway Truck Lane Restriction and Differential Speed Limits , 2010 .

[29]  Don Scott,et al.  Car following decisions under three visibility conditions and two speeds tested with a driving simulator. , 2007, Accident; analysis and prevention.

[30]  Guizhen Yu,et al.  Simulative investigation on head injuries of electric self-balancing scooter riders subject to ground impact. , 2016, Accident; analysis and prevention.

[31]  Qing-yuan Yu.  Causes and Prevention Measures of Secondary Rear-End Accidents in the Rescue of Highway Traffic Accidents , 2013 .

[32]  David A. Hensher,et al.  A latent class model for discrete choice analysis: contrasts with mixed logit , 2003 .

[33]  Yingfeng Li,et al.  Comparison of characteristics between fatal and injury accidents in the highway construction zones , 2008 .

[34]  Brendan J. Russo,et al.  Comparison of factors affecting injury severity in angle collisions by fault status using a random parameters bivariate ordered probit model , 2014 .