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An automated driving system (ADS) shall provide safer conditions for highly automated vehicle (HAV) users compared to standard vehicles since human error is excluded. In the following decades, however, one can expect a mixed fleet of both standard and automated vehicles on roads. Therefore, collisions between manually driven cars and HAVs are to be expected. On the other hand, HAVs’ occupants access more room in the vehicle which allows them to rotate their seats to have a comfortable position. This work aims to address the issue of HAV’s occupant safety using tools of numerical simulations. We consider an FE model of a seat with the standard three-point belt at two initial orientations 45° and 90°. The occupant (50th percentile male) is represented with the Virthuman model. We test the idea of employing the active seat rotation system. By detecting a crash well in time an initially rotated seat is reoriented into a standard seating orientation in a rear-end crash.

Human-driven vehicles are going to be replaced by highly automated vehicles as one of the future mobility trends. Even though highly automated vehicles’ active safety systems can protect against vehicle-to-vehicle accidents, the traffic mix between human-driven vehicles and highly automated vehicles is still a potential source of vehicle collisions. Additionally, occupants in highly automated vehicles will be passengers not necessarily dealing with driving anymore, so there will be a considerable number of non-standard seating configurations. Those configurations are not able to be assessed for safety by hardware testing due to their number, variability and complexity. The objective of the paper is the development of a fast virtual approach to identify the passengers’ injury risk in non-standard seating configurations under multi-directional impact scenarios and severity.