There are many reasons that the measurement of drivers' mental workload has great interest these days and will increasingly enjoy this status in the near future. Accidents are numerous, seemingly ineradicable, very costly, and in fact largely attributable to the victims themselves, human beings. Human errors in the sense of imperfect perception, insufficient attention, and inadequate information processing are the major causes of the bulk of the accidents on the road (Smiley & Brookhuis, 1987; Treat et al., 1977). Although both low and high mental workloads are undoubtedly basic conditions for these errors, an exact relation between mental workload and accident causation is not easily established, let alone measured in practice. Brookhuis, Van Winsum, Heijer, and Duynstee (1999) discriminated between underload and overload, the former leading to reduced alertness and lowered attention, the latter to distraction, diverted attention, and insufficient time for adequate information processing. Both factors have been studied in relation to driver impairment; however, the coupling to accident causation is not via a direct link (see also Brookhuis et al., 1999). Criteria for when impairment is below a certain threshold, leading to accidents, have to be established. Only then can accidents and mental workload (high or low) be related, in conjunction with the origins, such as information overload, boredom, fatigue, or factors such as alcohol and drugs. The traffic environment and traffic itself will only gain in complexity, at least for the present, with the rapid growth in numbers of automobiles and telematics applications. Aging plays a role in the interest in the measurement of drivers' mental workload these days and will increasingly do so in the near future.