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1.
Front Public Health ; 11: 1199949, 2023.
Article in English | MEDLINE | ID: mdl-37670838

ABSTRACT

Objective: An 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. Methods: The 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. Results: In 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. Conclusions: A 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.


Subject(s)
Brain Injuries , Pedestrians , Proximal Femoral Fractures , Humans , Female , Male , Databases, Factual , Probability
2.
Accid Anal Prev ; 148: 105831, 2020 Dec.
Article in English | MEDLINE | ID: mdl-33125925

ABSTRACT

This study introduces a method that allows the generation and safety evaluation of a scenario catalog derived from potential car-pedestrian conflict situations. It is based on open-source software components and uses the road layout standard OpenDRIVE to derive participants' motion profiles with the support of available accident data. The method was implemented upon the open-source framework openPASS and can simulate results for different active safety system setups and facilitates the prediction of system capabilities to decrease the relative impact velocities and collision configurations such as the point of impact. A demonstration case was performed where the scenario catalog was derived and used to evaluate pedestrian collisions with and without a generic autonomous emergency braking (AEB) system. The AEB system aims to intervene in the event of an impending collision and might affect the outcome of a baseline scenario. The study indicated a change in the collision configuration and identified conflict situations less affected by the system. A particularly interesting finding was that some scenarios even led to a higher number of collisions (at lower impact) for the AEB intervention in comparison to the baseline cases.


Subject(s)
Accidents, Traffic/prevention & control , Accidents, Traffic/statistics & numerical data , Computer Simulation , Deceleration , Pedestrians , Protective Devices/statistics & numerical data , Safety Management/methods , Humans
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