Haul truck drivers are at a high risk of developing fatigue due to the monotonous nature of the work and demanding shift rosters. In the mining industry, fatigue is identified as a major contributing factor in several fatal accidents a year. A number of fatigue detection devices are now available, that can contribute to improved fatigue risk management in the mining industry. This paper describes the technology and algorithms behind one particular product which is both predictive and un-obtrusive to the operator. The Advisory System for Tired Drivers (ASTiD), was developed by Fatigue Management International (FMI) in collaboration with the Loughborough Sleep Research Centre (LSRC), both in the United Kingdom. While this system includes a model of the human circadian rhythm as a bias for predicting expected fatigue risk by time of day, it also uses yaw data generated by a solid-state gyroscope in the horizontal plane. Algorithms analyse this data to determine the level of monotony of actual driving conditions and to detect changes in steering control caused by driver fatigue. During normal levels of attention, a haul truck driver applies continuous, small adjustments to the steering wheel. As the level of fatigue increases, steering adjustments become less frequent and more erratic. Differentiating between these modes of control in the highly variable mining environment is accomplished by chromatic processing of the gyroscope data. This paper will go into some detail explaining the principles behind chromatic processing and the specific application of these in detecting fatigue in haul truck operators.Technology in itself is not the solution to addressing operator fatigue, but it plays an important role in ongoing monitoring and maintaining awareness with mining personnel. Furthermore, the specific principles behind ASTiD technology support a risk-based approach to fatigue management, allowing optimisation of the mining operation for productivity as well as safety.