A Study On Head-brain Injury Risk Analysis In Real World Vehicle-pedestrian Traffic Accidents

Pedestrians are the most vulnerable road users, and frequently involved in vehicle traffic accidences. In China, nearly 100 000 people dead in road vehicle traffic accidents in which pedestrians accounted for about one-quarter. The head-brain injuries in vehicle-pedestrian collisions accounted for 30% of all reported injuries on different body regions, which often resulted in a fatal consequence. Such injuries can result in disabilities and long-term sequence, which lead to significant social costs. Consequently, improving traffic safety for pedestrians would be significant and valuable for society. It is therefore important for studying the characteristics of pedestrian accidents and understanding the head-brain injury mechanism of the pedestrian, which forms background knowledge to improve vehicle design for pedestrian protection.This study introduced the anatomical structures of human head. The injury patterns and mechanism of head-brain, as well as the main head-brain injury criteria were summarized from a literature study. Vehicle-pedestrian accidents data, registered by traffic police, were collected in Changsha city from 2001 to 2006. Statistic method was used to analysis the epidemiology of pedestrian traffic injuries. On site investigation was carried out for in-depth pedestrian accident study. The critical data and investigation methods were summarized in present study. 12 detailed cases from on-site investigation were selected and reconstructed using validated multi-body vehicle-pedestrian models by the software MADYMO in order to study the dynamic responses and head-brain injuries in car-to-pedestrian collisions. Regression method was used for analysis the correlation between dynamic parameters and injury parameters. The results from MADYMO accident reconstructions were used as the input conditions of FE injury reconstructions. 7 reconstructed cases were selected for injury reconstruction using validated FE head-brain and vehicle models by using the software LS-DYNA in order to investigate the biomechanical responses of head-brain in pedestrian accidents. Logistic regression models between physic parameters and AIS 3+ head-brain injuries were developed via MATLAB code. The probability of exist head-brain injury criteria were analyzed including HIC, HIP, GAMBIT, threshold corridors criteria and SIMon criteria. Logistic regression models of HIC, HIP, GAMBIT and AIS 3+ head-brain injuries were also developed. Parameter study was conducted using factorial test method in order to study the influences of passenger car front structures and stiffness on pedestrian head-brain injuries. Large family car, small family car, SUV and MPV were selected as the major styles of passenger cars for analyze the influences on pedestrian head-brain injuries with different impact speeds varies from 20km/h to 50km/h. Head-brain injury prevention and protection methods were discussed based on the analysis of influence of designed parameters on pedestrian head-brain injuries.The in-depth vehicle-pedestrian accidents study results show that the passenger cars are most frequently involved in pedestrian accidents. The lateral impact is the most common scenario, head and lower extremity injuries are the most frequent injury patterns while head injuries is the major cause of death.The accidents reconstruction results show that the relationships are statistically significant between vehicle-pedestrian impact speed and such parameters including head impact time, head impact related velocity, throw out distance and HIC.It is found from injury reconstructions that when coup/contrecoup pressure, von Mises and shear stress exceeds 195.5kPa, -196.8kPa, 20.1kPa and 11.4kPa respectively, AIS 3+ head-brain injuries are likely to happen with 50% probability.The probability of head-brain injury criteria analysis results show that the head-brain prediction probability of HIC, HIP and GAMIT is in descending order while physic parameters exhibit strongest correlation with AIS3+ brain injuries. The threshold corridors criteria have good probability for predicting slight brain injuries without level. SIMon criteria show bad probability that may due to different FE head-brain models.The results from parameter study indicate that when the impact speed exceeds 40km/h, serious head-brain injuries will be generated. The stiffness of car front parts also affects the level of head-brain injury, and properly reducing the stiffness has the benefits of improving head-brain protection. The height of bonnet leading edge is also important to pedestrian head-brain injuries, and other dimension parameters, more or less, had relationships to the outputs.It can be predicted that improving traffic control and strengthening the safety awareness of pedestrian would reduce the pedestrian accidents. The regression models from accident reconstruction results would be used as empirical equations for pedestrian accidents reconstructions. The Logistic regression models from injury reconstruction results would be used to predict AIS 3+ head-brain injuries. The findings from this study have a contribution to the understanding of head-brain injury biomechanics and developing background knowledge for pedestrian protection.