An Algorithm for Detecting Heavy-Truck Driver Fatigue from Steering Wheel Motion

This paper is the culmination of previous work to determine if steering behavior could be used to unobtrusively detect driver fatigue. The driving performance of 17 sleep-deprived heavy-truck drivers was monitored on a closed track. Functions in the time, frequency, and phase domains were developed to quantify changes in steering wheel input. The steering-based weighting functions which correlated most strongly with independent measures of driver fatigue and drowsiness were used to develop a simple algorithm. The algorithm predicted fatigue for all 17 volunteer drivers before the end of their test. The algorithm identified 12 drivers before a lane breach occurred, and only two drivers were not captured until a lane breach greater than 15 cm occurred. These data and the algorithm demonstrate the potential for a steering-based fatigue detection algorithm.