Application of ACN data to improve vehicle safety and occupant care

Augenstein, Jeffery; Digges, Kennerly; Perdeck, Elana; Stratton, James; Bahouth, George; Baur, Peter; Messner, George

Affiliations

¹William Lehman Injury Research Center, University of Miami, United States

²Pacific Institute for Research and Evaluation, United States

Abstract

In MY 2007 nearly all of the BMW's sold in the US will be equipped with an Automatic Crash Notification System (ACN) called "BMW Assist". The service is provided to the customer for a period of 4 years free of charge. This fleet of BMW's will notify the Telematics Service Provider (TSP) when they have been in moderate or severe crashes. This service will continue to be provided for a period of 4 years. The resulting body of information will be of unprecedented value for research purposes. For example, researchers will be able to determine the time between the initiation of the emergency call and the arrival of rescue. For cases with long rescue times research can focus on ways to shorten the time and improve the service. In addition, cases with injuries can be identified as candidates for in-depth investigation. This capability will resolve one of the greatest impediments to crash investigation research — how to find crashes of interest. Finally, by having a complete census of all crashes involving ACN equipped vehicles less than four years old, the crash exposure can be determined and crash involvement risks can be accurately calculated. When combined with sales exposure data, the crash involvement rates will permit the benefits of accident avoidance countermeasures to be assessed. There is no other data system that will provide the resolution or accuracy of this system — particularly for the assessment of crash avoidance countermeasures.

Links

URL: http://www-nrd.nhtsa.dot.gov/pdf/esv/esv20/07-0512-W.pdf

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Cited By (3)

Year	Entry
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.
2011	Kononen DW, Flannagan CAC, Wang SC. Identification and validation of a logistic regression model for predicting serious injuries associated with motor vehicle crashes. Accid Anal Prev. January 2011;43(1):112-122.