Characterization of Lane Departure Crashes Using Event Data Recorders Extracted from Real-World Collisions

Event
SAE 2013 World Congress & Exhibition
Authors Abstract
Content
Lane Departure Warning (LDW) is a production active safety system that can warn drivers of an unintended departure. Critical in the design of LDW and other departure countermeasures is understanding pre-crash driver behavior in crashes. The objective of this study was to gain insight into pre-crash driver behavior in departure crashes using Event Data Recorders (EDRs). EDRs are units equipped on many passenger vehicles that are able to store vehicle data, including pre-crash data in many cases.
This study used 256 EDRs that were downloaded from GM vehicles involved in real-world lane departure collisions. The crashes were investigated as part of the NHTSA's NASS/CDS database years 2000 to 2011.
Nearly half of drivers (47%) made little or no change to their vehicle speed prior to the collision and slightly fewer decreased their speed (43%). Drivers who did not change speed were older (median age 41) compared to those who decreased speed (median age 27). Drivers in lane departure crashes were traveling above the posted speed limit in 65% of cases. Almost half (49%) of drivers did not apply the brakes during the pre-crash record, suggesting that drivers may be steering more often than braking to avoid crashes.
The newest advanced EDRs record steering wheel angle in addition to the data collected by older EDRs most common in the current fleet. We also present a case study using advanced EDR data to simulate the vehicle's trajectory. This method could be invaluable in benefits estimates of safety systems.
Meta TagsDetails
DOI
https://doi.org/10.4271/2013-01-0730
Pages
9
Citation
Kusano, K., and Gabler, H., "Characterization of Lane Departure Crashes Using Event Data Recorders Extracted from Real-World Collisions," SAE Int. J. Passeng. Cars - Mech. Syst. 6(2):705-713, 2013, https://doi.org/10.4271/2013-01-0730.
Additional Details
Publisher
Published
Apr 8, 2013
Product Code
2013-01-0730
Content Type
Journal Article
Language
English