Injury identification: priorities for data transmitted

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Augenstein, Jeffrey¹; Perdeck, Elana¹; Bahouth, George T.²; Digges, Kennerly H.³; Borchers, Nils⁴; Baur, Peter⁴

Injury identification: priorities for data transmitted

Proceedings of the 19th International Technical Conference on the Enhanced Safety of Vehicles (ESV)

Affiliations

¹William Lehman Injury Research Center, USA

²Pacific Institute for Research and Evaluation, USA

³The George Washington University, USA

⁴BMW, Germany
Abstract

The objective of this study was to prioritize the variables that could be transmitted with an ACN (Automatic Crash Notification) signal. The main purpose of transmitting these variables is to assist in early identification of those occupants with time critical injuries. For the purposes of this study, all MAIS 3+ injuries were classified as time critical. The basis for prioritizing crash variables was based on their ability to identify MAIS 3+ injured occupants in the National Automotive Sampling System- Crashworthiness Data System (NASS/CDS) dataset.

In this study, multivariate models to represent crash events were developed based on historical crash data from the years 1997-2003. The analysis established a relationship between crash attributes and crash outcomes for all passenger vehicles in the database.

The resulting analysis provided a ranking of crash variables in order of importance. Crash severity (Delta-V) was found to be the most important variable for all planar crash directions. The addition of other crash variables improved the accuracy of the injury prediction algorithm.

For frontal crashes important secondary crash variables include: 3-point belt usage, multi-impact crashes, occupant age and the presence of more than 6” of intrusion. For near-side crashes, the most important secondary variables were occupant age, narrow object crashes, and the presence of intrusion. For far side crashes, the most important secondary crash variables were 3-point belt usage and the occurrence of a narrow object crash. Rollover was found to be a high risk event that predicted high injury risk independent of Delta-V if 3-point belts were unused.

The paper will show the relative importance of the crash and occupant variables by crash direction.
Links

URL: http://www-nrd.nhtsa.dot.gov/pdf/esv/esv19/05-0416-O.pdf

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2015	Gabler HC, Weaver AA, Stitzel JD. Automotive field data in injury biomechanics. In: Yoganandan N, Nahum AM, Melvin JW, eds. Accidental Injury: Biomechanics and Prevention. 3rd ed. New York: Springer; 2015:33-49.
2009	Craig M, Scarboro M, Flannagan C. Combining CIREN and NASS-CDS data to predict occupant outcomes in frontal crashes. In: Proceedings of the 21st International Technical Conference on the Enhanced Safety of Vehicles (ESV). June 15-18, 2009; Stuttgart, Germany.
2011	Craig MJ, Scarboro M, Ridella SA. Predicting occupant outcomes with EDR data. In: Proceedings of the 22nd International Technical Conference on the Enhanced Safety of Vehicles (ESV). June 13-16, 2011; Washington, DC.
2015	Stitzel J, Weaver A, Schoell S, Barnard R, Talton J, Martin RS, Meredith JW. Occupant transportation decision algorithm: an advanced automatic crash notification algorithm developed and evaluated for motor vehicle crash occupant triage. In: Proceedings of the 24th International Technical Conference on the Enhanced Safety of Vehicles (ESV). June 8-11, 2015; Gothenburg, Sweden.
2015	Kiuchi T, Motomura Y, Matsumoto H, Mashiko K. Pilot study on advanced automatic collision notification and helicopter emergency medical service system in Japan. In: Proceedings of the 24th International Technical Conference on the Enhanced Safety of Vehicles (ESV). June 8-11, 2015; Gothenburg, Sweden.