Driver education classes were once seen as a remedy for young drivers' overinvolvement in crashes, but research results from the early 1970s were disappointing. Few changes in the content or methods of instruction occurred until recently, but this could change rapidly. Personal computers (PCs) can now present videos or photorealistic simulations of risky, cognitively demanding traffic scenarios that require quick responses without putting the participant at risk. As such programs proliferate, evaluating their effectiveness poses a major challenge. We report the use of a fixed-base driving simulator to study the effects of both experience on the road and PC-based risk awareness training on younger drivers' part-task simulator driving performance in risky traffic scenarios. We ran three groups of drivers on the simulator: one group first trained on the PC (younger, inexperienced drivers) and two groups who received no PC training (younger, inexperienced and experienced drivers). Overall, the younger, inexperienced drivers who were trained on a PC operated their vehicles in risky scenarios in ways that differed measurably from those of the untrained younger, inexperienced drivers and, more important, in ways that we believe would decrease their exposure to risk considering that, on average, their behavior was more similar to the behavior of the untrained, experienced drivers. More research is needed to demonstrate whether these findings apply on the open road to the larger population of younger drivers. However, at least initially, the research suggests that PC-based risk awareness training programs have the potential to reduce the high crash rate among younger, inexperienced drivers.

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Younger adults are overinvolved in accidents. Model high school driver education programs were developed in the 1970s in an attempt to reduce this overinvolvement. An evaluation of these programs suggested that they were largely ineffective. Recently, the AAA Foundation for Traffic Safety has developed the first PC-based driver education program (Zero Errors Driving or Driver ZED) using real footage of risky scenarios. The hope is that younger drivers seeing these scenarios will learn to recognize risky situations in the real world before they develop. In an attempt to evaluate the Driver ZED program, the performance of 20 younger drivers is being tested on the University of Massachusetts' driving simulator. Ten of these drivers have been trained with ZED (the trained group) and ten have not seen the program (the untrained group). All 20 drivers must navigate a total of 24 scenarios that have been programmed on the driving simulator. Measures of driving performance were developed which can be used to discriminate between risky and nonrisky drivers. A preliminary evaluation of the performance of the trained and untrained subjects indicates that the trained subjects are performing more cautiously than the untrained subjects in some, but not all, scenarios (e.g., the trained subjects brake sooner when approaching a pedestrian crossing).

Commercially available voice-activated dialing systems (VADS) are promoted as providing users with a safer car phone method, hands-free dialing. Despite the safety benefits, errors (such as call flow and user interface design issues) can cause users to reject the technology. The purpose of this study was to investigate the call flow structures of a commercially available voice activated dialing system under simulated driving conditions and provide recommendations for its improvement. Results demonstrated that users were most frustrated with voice recognition errors. Additionally, we found that menu navigation was intuitive for the most part but that more practice in the tutorial could be used as a stopgap measure to help solidify the voice directory concept. The HELP call flow presented the majority of problems to users due to its cumbersome design. Finally, the user interface design could be improved by following the principles of conversational speech especially with the call by NAME option and avoiding repetitive prompts which contribute no additional information to the user.

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