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Holistic pedestrian safety assessment for average males and females
Vehicle Safety Institute, Graz University of Technology, Austria.
Volvo Car Corporation, Torslanda HABVS-VAK, Sweden.
Swedish National Road and Transport Research Institute, Traffic and road users, Traffic Safety and Traffic System.ORCID iD: 0000-0001-5531-0274
Swedish National Road and Transport Research Institute, Traffic and road users, Traffic Safety and Traffic System. Mechanics and Maritime Science, Chalmers University, Sweden.ORCID iD: 0000-0001-6868-5673
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2023 (English)In: Frontiers In Public Health, ISSN 2296-2565, Vol. 11, article id 1199949Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Frontiers Media S.A., 2023. Vol. 11, article id 1199949
National Category
Vehicle Engineering
Identifiers
URN: urn:nbn:se:vti:diva-19893DOI: 10.3389/fpubh.2023.1199949ISI: 001057828400001PubMedID: 37670838Scopus ID: 2-s2.0-85169671177OAI: oai:DiVA.org:vti-19893DiVA, id: diva2:1796155
Available from: 2023-09-11 Created: 2023-09-11 Last updated: 2024-01-10Bibliographically approved

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Grumert, EllenLinder, Astrid

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