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Driver drowsiness/fatigue is an important cause of combination-unit truck crashes. Recent analyses of the problem estimates that 15% - 36% of all crashes fatal to combination-unit-truck drivers are drowsiness related. The cost of these crashes is estimated to be $2,060 per vehicle over the lifetime of a combination-unit truck. Drowsy driver detection methods can form the basis of a system to potentially reduce the number of crashes related to drowsy driving. Recently, significant strides have been made in the development and application of a real-time drowsiness monitor. The monitor employs a novel dual image video processing technique to measure PERCLOS, a scientifically validated measure of drowsiness. Uses for the PERCLOS monitor include: providing real-time drowsiness feedback to the driver, providing performance feedback to a fatigue management program, and/or providing regulatory compliance information to enforcement officials.

Carnegie Mellon Driving Research Center, together with ISIM, is presently involved in the design and development of an Advanced Human Factors Research and Driving Training Research Facility. The facility has been designed to address human factors issues and driver training issues. Human factors interests include developing countermeasures for fatigue and driver/vehicle interface issues. Driver training issues include validating the usefulness of simulators for driver training, developing effective curricula and investigating simulator fidelity needed for effective training. A key component of the facility is the Carnegie Mellon TruckSim that will be capable of simulating a variety of commercial and emergency vehicles using interchangeable cabs mounted to a common motion platform. TruckSim's modular configuration will allow for rapid and cost effective design of experiments and training scenarios. A first research program to evaluate fatigue countermeasures is presented as an example.