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Preliminary Estimates of Near Side Crash Injury Risk in Best Performing Passenger Vehicles
Technical Paper
2018-01-0548
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
The goal of this paper is to estimate near-side injury risk in vehicles with the best side impact performance in the U.S. New Car Assessment Program (NCAP). The longer-term goal is to predict the incidence of crashes and injury outcomes in the U.S. in a future fleet of the 2025-time frame after current active and passive safety countermeasures are fully implemented. Our assumption was that, by 2025, all new vehicles will have side impact passive safety performance equivalent to current U.S. NCAP five star ratings.
The analysis was based on real-world crashes extracted from case years 2010-2015 in the National Automotive Sampling System / Crashworthiness Data System (NASS/CDS) in which front-row occupants of late-model vehicles (Model Year 2011+) were exposed to a near-side crash. Vehicles in the dataset were assigned their probability of driver injury greater than AIS 3 (Abbreviated Injury Scale) across any body region (MAIS3+) from NCAP testing based on the VIN and associated identifiers recorded by the NASS/CDS investigator. Using logistic regression, injury risk curves were developed to characterize the performance of each vehicle model as a function of total delta-v and probability of MAIS3+ injury from NCAP testing. Other predictor variables in the model included belt status, age, and gender. The resulting injury risk curves were developed for MAIS2+ injured occupants as a function of crash severity and occupant characteristics. These injury risk curves will facilitate early prediction of residual crash injury risk after best performing passive safety countermeasures are fully implemented in a future fleet of the 2025-time frame.
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Citation
Bareiss, M., David, M., and Gabler, H., "Preliminary Estimates of Near Side Crash Injury Risk in Best Performing Passenger Vehicles," SAE Technical Paper 2018-01-0548, 2018, https://doi.org/10.4271/2018-01-0548.Data Sets - Support Documents
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