@article{ref1,
title="Efficiency of Vehicle-Based Data to Predict Lane Departure Arising From Loss of Alertness Due to Fatigue",
journal="Annual proceedings of the Association for the Advancement of Automotive Medicine",
year="1996",
author="Wong, PKH and Siegmund, Gunter P. and King, D. J. and Cooper, P. J. and Filiatrault, DD",
volume="40",
number="",
pages="363-376",
abstract="Seventeen long-haul truck drivers were recruited to participate in a driver fatigue study. The study was conducted to determine if a degradation in driver performance could be detected from controlled inputs of drowsy drivers. A test protocol was developed to replicate the kind of driving environment generally regarded (and often associated) with single-vehicle, run-off-the-road-type crashes. Physiological measures of drowsiness were recorded while a fully instrumented 3-axle truck-tractor was driven on a closed-circuit track. Driving sessions were conducted when test subjects were both alert and sleep deprived. Analysis and refinement of experimental data were used to develop a preliminary steering-based algorithm. The results of the study indicate that lane departure, arising from a loss of alertness due to fatigue, may be predicted by monitoring movements of the steering wheel.<p />",
language="",
issn="1540-0360",
doi="",
url="http://dx.doi.org/"
}