Holistic pedestrian safety assessment for average males and females

Abstract

ObjectiveAn integrated assessment framework that enables holistic safety evaluations addressing vulnerable road users (VRU) is introduced and applied in the current study. The developed method enables consideration of both active and passive safety measures and distributions of real-world crash scenario parameters.MethodsThe likelihood of a specific virtual testing scenario occurring in real life has been derived from accident databases scaled to European level. Based on pre-crash simulations, it is determined how likely it is that scenarios could be avoided by a specific Autonomous Emergency Braking (AEB) system. For the unavoidable cases, probabilities for specific collision scenarios are determined, and the injury risk for these is determined, subsequently, from in-crash simulations with the VIVA+ Human Body Models combined with the created metamodel for an average male and female model. The integrated assessment framework was applied for the holistic assessment of car-related pedestrian protection using a generic car model to assess the safety benefits of a generic AEB system combined with current passive safety structures.ResultsIn total, 61,914 virtual testing scenarios have been derived from the different car-pedestrian cases based on real-world crash scenario parameters. Considering the occurrence probability of the virtual testing scenarios, by implementing an AEB, a total crash risk reduction of 81.70% was achieved based on pre-crash simulations. It was shown that 50 in-crash simulations per load case are sufficient to create a metamodel for injury prediction. For the in-crash simulations with the generic vehicle, it was also shown that the injury risk can be reduced by implementing an AEB, as compared to the baseline scenarios. Moreover, as seen in the unavoidable cases, the injury risk for the average male and female is the same for brain injuries and femoral shaft fractures. The average male has a higher risk of skull fractures and fractures of more than three ribs compared to the average female. The average female has a higher risk of proximal femoral fractures than the average male.ConclusionsA novel methodology was developed which allows for movement away from the exclusive use of standard-load case assessments, thus helping to bridge the gap between active and passive safety evaluations.

A Hierarchical Prediction Method for Pedestrian Head Injury in Intelligent Vehicle with Combined Active and Passive Safety System

“…The emergence of intelligent driving technology can reduce collision accidents caused by improper driver operation to a certain extent; however, for pedestrians, a strong uncertainty factor in the transportation system with respect to pedestrian–vehicle collision is hard to completely avoid, and the mortality rate of pedestrians remains very high. Therefore, the mechanisms of pedestrian injury and collision prevention measures remain research hotspots in the field of automobile safety [ 1 , 2 , 3 ].…”