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Adjusting vehicle secondary safety ratings to account for crash-avoidance technology fitment using real-world crash and injury data.

Michael D KeallStuart Newstead
Published in: Traffic injury prevention (2024)
Different market groups have different crash patterns, so the safety attributable to safety technology fitment differs at the market group level. This study presents an approach for providing a summary measure of crash avoidance according to the fitment of safety technologies. If this measure is combined with an estimate of secondary safety (whether derived from existing crash and injury data or from new car crash assessment programs), the combined estimate then represents the important elements of safety provided by the vehicle. The methods presented here form a rational basis for assigning safety ratings to represent the benefits of swiftly developing safety technologies.
Keyphrases
  • public health
  • machine learning
  • big data
  • electronic health record
  • artificial intelligence
  • deep learning