Estimating Preliminary Occupant Injury Risk Distributions for Highly Automated Vehicles With Respect to Future Seat Configurations and Load Directions

While highly automated vehicles (HAVs) will be able to reduce the number of accidents significantly by removing human error, some accidents may remain unavoidable – particularly during the transition period. HAVs also promise increased freedom in seat positioning for all passengers, including the driver. A growing amount of literature deals with individual issues of occupant safety in these new positions, but there is currently no comprehensive overview on the effects of combinations of possible future seat positions and vehicle load directions. Addressing this, the aim of this research is to develop a method to quickly highlight key combinations of seat position/inclination and crash load direction with respect to occupant safety for any given interior layout and set of restraint systems. Also, the method should facilitate the evaluation of restraint systems’ active principles. Inspired by common safety engineering methods, the proposed approach defines risk as combination of severity, exposure and controllability. To estimate the severity, each restraint system’s ability to restrain the occupant – referred to as restraining potential – is defined as mathematical function of relevant parameters, e.g. various seat adjustments and as function of the load direction relative to the occupant. These individual restraining potential functions which can be plotted as 2D-graphs, can then be combined into a total restraining potential for any specific combination of parameters (seat, load direction...). The required interpolation points for these functions are estimated theoretically and checked for plausibility based on finite element (FE) simulations with a human body model (HBM) and compared to literature. Additionally, the space available for occupant displacement (and thus available for dissipation of kinetic energy) is considered and combined with the restraining potential to a measure which is inversely proportional to the severity. The exposure is estimated with a distribution of the main accident types (front/side/rear). While the relevant future distribution is not yet known, estimates from recent literature or current accident data can be used as starting points. With a modular approach, effects of different distributions can easily be analysed by changing this input. Controllability (with respect to the risk definition) is not taken into account in this first implementation, since the approach only considers scenarios where crashes occur and all systems are expected to work faultlessly. Based on the calculated severity and exposure the occupant injury risk is automatically computed for a specific interior and then plotted for all reasonable combinations of seat adjustments. This enables an immediate overview for finding key combinations which should be the focus of in-depth analyses, e.g. detailed FE simulations. The proposed approach should not be seen as a replacement for detailed FEA but as a useful supplement for time and resource efficient preparation of simulation studies concerning the occupant safety of future HAVs. Estimating preliminary occupant injury risks for future HAVs provides an insight to their expected performance which highlights key parameter combinations and can aid the development of relevant regulations and test procedures.

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Appendices; Figures; References; Tables;
  • Pagination: 17p
  • Monograph Title: 26th International Technical Conference on the Enhanced Safety of Vehicles (ESV): Enabling a Safer Tomorrow

Subject/Index Terms

Filing Info

  • Accession Number: 01762194
  • Record Type: Publication
  • Report/Paper Numbers: 19-0175
  • Files: TRIS, ATRI, USDOT
  • Created Date: Dec 14 2020 3:41PM