Pre-crash Repositioning of  Rearward Shifted Seats in Automated Vehicles

Becker, Julian; Zeuß, Daniel; Thirunavukkarasu, Dinesh

doi:10.1007/s38311-022-1414-6

Cited by 1 publication

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“…The occupant simulation is used to determine how pre‐crash movements affect the risk of injury during the later in‐crash simulation. The occupant simulation makes it possible to include a realistic model of the vehicle interior [1] (Figure 20) including the control panel, steering panel, and driver seat. By using multibody models for the simulation, it makes possible to simulate long pre‐crash phases (Figure 20 shows the occupant response to the

740 ms

long pre‐crash phase illustrated in Figure 19) that would be prohibitively expensive to evaluate using an FE model.…”

Section: Applicationsmentioning

confidence: 99%

Dynamic human body models in vehicle safety: An overview

et al. 2023

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Significant trends in the vehicle industry are autonomous driving, micromobility, electrification and the increased use of shared mobility solutions. These new vehicle automation and mobility classes lead to a larger number of occupant positions, interiors and load directions. As safety systems interact with and protect occupants, it is essential to place the human, with its variability and vulnerability, at the center of the design and operation of these systems. Digital human body models (HBMs) can help meet these requirements and are therefore increasingly being integrated into the development of new vehicle models. This contribution provides an overview of current HBMs and their applications in vehicle safety in different driving modes. The authors briefly introduce the underlying mathematical methods and present a selection of HBMs to the reader. An overview table with guideline values for simulation times, common applications and available variants of the models is provided. To provide insight into the broad application of HBMs, the authors present three case studies in the field of vehicle safety: (i) in‐crash finite element simulations and injuries of riders on a motorcycle; (ii) scenario‐based assessment of the active pre‐crash behavior of occupants with the Madymo multibody HBM; (iii) prediction of human behavior in a take‐over scenario using the EMMA model.

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