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Highly automated vehicles are one of the future mobility trends. Passengers will not deal with driving the car anymore as a result of the automated driving systems, so many non-standard seating configurations are expected. Even automated vehicles will be connected to avoid crashes, vehicle collisions will be still possible as many cars will still be driven manually. The work accommodates an existing virtual biomechanical human body model, which is scalable and easily adjustable to any seating configuration. Reference 50-percentile passengers are seated in the expected non-standard seating scenarios. A rear-end impact corresponding to two velocity levels is applied and the injury risk for each passenger is assessed through the abbreviated injury scale. The work is a base for a future artificial intelligence-based predictive system to assess injury risk for passengers in non-standard seating configurations of highly automated vehicles.



University of West Bohemia: Luděk Hynčík, Abbas Talimian, Jan Vychytil

Automated Safety Assessment of Passengers in Vehicles with Non-Standard Seating Configuration in Rear Impact

APAC-21-152 • Paper

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