To investigate the links between mental workload, age and risky driving, a cross-sectional study was conducted on a driving simulator using several established and some novel measures of driving ability and scenarios of varying complexity. A sample of 115 drivers was divided into three age and experience groups: young inexperienced (18–21 years old), adult experienced (25–55 years old) and older adult (70–86 years old). Participants were tested on three different scenarios varying in mental workload from low to high. Additionally, to gain a better understanding of individuals’ ability to capture and integrate relevant information in a highly complex visual environment, the participants’ perceptual-cognitive capacity was evaluated using 3-dimensional multiple object tracking (3D-MOT). Results indicate moderate scenario complexity as the best suited to highlight well-documented differences in driving ability between age groups and to elicit naturalistic driving behavior. Furthermore, several of the novel driving measures were shown to provide useful, non-redundant information about driving behavior, complementing more established measures. Finally, 3D-MOT was demonstrated to be an effective predictor of elevated crash risk as well as decreased naturally-adopted mean driving speed, particularly among older adults. In sum, the present experiment demonstrates that in cases of either extreme high or low task demands, drivers can become overloaded or under aroused and thus task measures may lose sensitivity. Moreover, insights from the present study should inform methodological considerations for future driving simulator research. Importantly, future research should continue to investigate the predictive utility of perceptual-cognitive tests in the domain of driving risk assessment.

Simulator-based training platforms have the potential for facilitating learning in a safe and controlled environment. Trainers can provide students with simulated scenarios representing a large number of challenging situations to help the student gauge their own performance, learn from their mistakes, and gain experience with complex skills through repeated practice. Often, novel ideas for new simulator-based training systems are initially developed and tested in a laboratory setting. However, understanding how best to implement simulators for use in practice is not a trivial undertaking. A concurrent engineering process that involves the researchers, practitioners, engineers, trainers and other end users is required. Designers must understand the requirements and the barriers to implementation, and the only way to accomplish this is to understand the end users and include them in design process. The current paper discusses a novel model describing the implementation cycle for the development and deployment of advanced driving simulator-based training systems and provides a real-world case example of one such successful deployment.

A long-term, naturalistic, prospective-cohort transfer of training study was conducted in commercial driving schools in Quebec, Canada, to test the effects on driver performance and behavior of integrating driving simulator–based training (DSBT) into the driver education program. For the study, 1 h of DSBT could be substituted for 1 h of on-road training for up to six of the mandatory 15 h. Four driving schools provided a convenience sample of 1,120 learner drivers (average age 17.7 and 52.7% female) between January 2010 and December 2014. Of the study sample, 95% received 1 to 4 h of DSBT. Those in the comparison group were all new, young Quebec drivers who had completed the mandatory driver education program in the same period. This paper reports on the association between DSBT and government driving records for 2 years after licensing. The DSBT group recorded lower infraction rates and, controlling for vehicle ownership and age, comparable crash rates. The lower infraction rates for males, despite the higher vehicle ownership normally associated with greater and riskier driving exposure, are a positive and unexpected finding. Crashes are multifactorial events less obviously related to drivers’ skills or intentions, and the comparable crash rates potentially indicate absence of overconfidence attributable to a form of advanced driver training. Overall, these results show that the substitution of relatively few hours of DSBT for on-road training is associated with reduced infractions and has no apparent influence on crashes in the first 2 years of unsupervised driving after licensing.

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DE evaluations need to identify and control for potential confounding factors. Research is needed to understand the associations between increased crash risk and potential confounding factors like motivation to attend DE and hours of supervised driving practice.