Protection Challenges in Seat Positions with Large Rearward Adjustment in Frontal Collisions: An Approach Using Stochastic Human Body Model Simulations

Felix Tobias Ressi*, Christoph Leo, Corina Klug, Wolfgang Sinz

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Novel seat positions enabled by self-driving cars have been investigated in various studies in recent years. However, there is little research on the effect of increased rearward seat adjustments. To predict challenges associated with the possibility to move the seat further backwards in the car than currently possible as driver, appropriate methods have to be defined. A detailed human body model, a THUMS v4.1 in particular, tissue-based injury risk evaluation methods, a generic vehicle interior and a Latin hypercube design of experiments taking the variability of real-world crashes into account was established.
In a first step, 200 simulations at current representative seat positions and a driving occupant posture were performed. The results were then compared to field data from an accident database to evaluate the accuracy of the method. The predictions exceeded the injury risks for the abdomen, head, and upper extremities, while underestimating the risk for thoracic and lower extremity injuries. A good match was observed for injuries of the neck and spine. In a second step, the 200 simulations were run again, but with the seat adjusted rearwards significantly. In this seat configuration, with the exception of the head and the upper extremities, increased injury risks were predicted for all body regions. The highest increases affected the lower extremities (+28%) – predominantly pelvic fractures – and the neck (+9%). In addition, (partial) submarining occurred in almost 50% of cases with the rearward adjusted seat – as opposed to none in the conventional seat position. The established method could be used in future studies to design safety measures addressing these identified potential safety risks.
Original languageEnglish
JournalFrontiers in Future Transportation
DOIs
Publication statusPublished - 22 Aug 2022

Keywords

  • occupant safety
  • novel seat configurations
  • accident data analysis
  • Human Body Models
  • stochastic analysis and modelling
  • injury prediction

Fields of Expertise

  • Mobility & Production

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