Sleepiness, sleep-disordered breathing, and accident risk factors in commercial vehicle drivers

Sleep-disordered breathing and excessive sleepiness may be more common in commercial vehicle drivers than in the general population. The relative importance of factors causing excessive sleepiness and accidents in this population remains unclear. We measured the prevalence of excessive sleepiness and sleep-disordered breathing and assessed accident risk factors in 2,342 respondents to a questionnaire distributed to a random sample of 3,268 Australian commercial vehicle drivers and another 161 drivers among 244 invited to undergo polysomnography. More than half (59.6%) of drivers had sleep-disordered breathing and 15.8% had obstructive sleep apnea syndrome. Twenty-four percent of drivers had excessive sleepiness. Increasing sleepiness was related to an increased accident risk. The sleepiest 5% of drivers on the Epworth Sleepiness Scale and Functional Outcomes of Sleep Questionnaire had an in-creased risk of an accident (odds ratio [OR] 1.91, p = 0.02 and OR 2.23, p < 0.01, respectively) and multiple accidents (OR 2.67, p < 0.01 and OR 2.39, p = 0.01), adjusted for established risk factors. There was an increased accident risk with narcotic analgesic use (OR 2.40, p < 0.01) and antihistamine use (OR 3.44, p = 0.04). Chronic excessive sleepiness and sleep-disordered breathing are common in Australian commercial vehicle drivers. Accident risk was related to increasing chronic sleepiness and antihistamine and narcotic analgesic use.

Tyre-force estimation by Kalman inverse filtering: applications to off-highway mining trucks

Kalman inverse filtering is used to develop a methodology for real-time estimation of forces acting at the interface between tyre and road on large off-highway mining trucks. The system model formulated is capable of estimating the three components of tyre-force at each wheel of the truck using a practical set of measurements and inputs. Good tracking is obtained by the estimated tyre-forces when compared with those simulated by an ADAMS virtual-truck model. A sensitivity analysis determines the susceptibility of the tyre-force estimates to uncertainties in the truck's parameters.