Large-scale field test of forward collision alert and lane departure warning systems
In: Office of Advanced Safety Research, Washington, D.C.
Authors: Carol A. C. Flannagan, David J. LeBlanc, Scott Bogard, Kazutoshi Nobukawa, Prabha Narayanaswamy, Andrew Leslie, Raymond Kiefer, Michael Marchione, Christopher Beck, Kyle Lobes
This report covers a field study on an innovative large-scale data collection technique used to gather information about how crash avoidance systems operate in the field and how drivers respond to them. Although the specific systems studied were the General Motors (GM) camera-based forward collision alert (FCA) and lane departure warning (LDW) systems, this technique could be readily applied to other emerging active safety (crash avoidance) systems and used to better inform emerging active safety consumer metrics. It should be noted that both the FCA and LDW systems evaluated have consistently met the National Highway Traffic Safety Administration’s Crash Avoidance New Car Assessment Program (CA NCAP) performance criteria since this program was initiated. The study team found that this data collection technique has several distinct strengths, including cost, sample size, drivers using their own vehicles where they can turn systems off, ability to look at long-term effects, data efficiency, and the ability to acquire “rapid-turnaround” large-scale results, and that this new data collection technique is ideally suited for understanding the safety impacts of crash avoidance systems.