Investigation of head injuries suffered by pedestrians in traffic accidents via videos

Abstract

Head injury is the leading cause of fatality and disability suffered by pedestrians, which were the extremely vulnerable population of road users. The purpose of this study is to investigate the risk factors determining the head injury severity of pedestrians involved in traffic accidents. A team was established to collect pedestrian–vehicle accident cases occurring between 2011 and 2015 in Chongqing, China. Person-, vehicle- and environment-related variables were analysed using multivariate logistic regression method to determine the relative likelihood of pedestrian head injury. Pedestrian head injuries were coded according to the Abbreviated Injury Scale (AIS) and 111 collisions were analysed. It was found that higher proportions of severe head injuries (AIS4+) were associated with age of over 44 years old and impact speed of over 40 km/h. Comparison of the pedestrian head injury risk from the different contact site demonstrated that the collision with the windshield frame generally leads to more severe injury. In addition, the risks of severe head injury of pedestrians aged 45 years were 10%, 25%, 50%, 75% and 90% at impact speeds of 23.7, 33.9, 44.2, 54.5 and 64.7 km/h, respectively. The first three determinant variables on head injury severity and fatality risk were impact speed, head contact site and pedestrian age. The risks of severe head injury suffered by pedestrian increased radically when the impact speed exceeds 30 km/h. We believe that these findings may play an important role in understanding the vehicle–pedestrian collisions, which can serve as a guide in designing targeted interventions.

Keywords:

• Head injury risk
• fatality risk
• pedestrian collision
• traffic accident
• surveillance video

Disclosure statement

The authors declare no conflict of interest.

Additional information

Funding

The research presented in this article was supported by National Natural Science Foundation of China (No. 31800788) and National Key Research and Development Plan (No. 2016YFC0800702). We acknowledge the police department of Chongqing for their help in pedestrian–vehicle crash data sampling.