The authors present several versions of a general model, titled the E-Z Reader model, of eye movement control in reading. The major goal of the modeling is to relate cognitive processing (specifically aspects of lexical access) to eye movements in reading. The earliest and simplest versions of the model (E-Z Readers 1 and 2) merely attempt to explain the total time spent on a word before moving forward (the gaze duration) and the probability of fixating a word; later versions (E-Z Readers 3-5) also attempt to explain the durations of individual fixations on individual words and the number of fixations on individual words. The final version (E-Z Reader 5) appears to be psychologically plausible and gives a good account of many phenomena in reading. It is also a good tool for analyzing eye movement data in reading. Limitations of the model and directions for future research are also discussed.

Novice drivers (16-year-olds with < or = 6 months' driving experience) have the highest crash involvement rates per 100 million vehicle miles (161 million vehicle km). In the past, this was attributed to greater risk taking or poorly developed psychomotor skills. More recently, however, their high crash involvement rate has been hypothesized to be attributable largely to their relative inability to acquire and assess information in inherently risky situations. The current study seeks to evaluate this hypothesis by recording eye movements while 72 participants (24 novice drivers, 24 younger drivers, and 24 older drivers) drove through 16 risky scenarios in an advanced driving simulator. There were significant age-related differences in driver scanning behavior, consistent with the hypothesis that novice drivers' scanning patterns reflect their failure to acquire information about potential risks and their consequent failure to deal with these risks. Actual or potential applications of this research include modification of these scenarios for display on a PC as a basis for a training module that would enable novice drivers to recognize risky scenarios before they encounter them on the road, in the hope of reducing their high fatality rate.

Objective This study aimed (a) to determine whether older drivers looked less often for potential threats while turning than younger drivers and (b) to compare the effectiveness of active and passive training on older drivers’ performance and evaluation of their driving skills in intersections. Background Age-related declines in vision, physical abilities, psychomotor coordination, and cognition combine to make it less likely that older drivers will look for potential threats during a turn. Research suggests that active training should be an effective means of improving older drivers’ performance and self-awareness. Method In Experiment 1, younger and older participants drove a series of virtual intersection scenarios, were shown video replays, and were provided feedback. In Experiment 2, older drivers were assigned to one of three cohorts: active simulator training, passive classroom training, or no training. Pre- and posttraining simulator and field drives assessed training effectiveness. Results In Experiment 1, older drivers looked less often during turns than younger drivers. Customized feedback was successful in altering drivers’ perception of their abilities. In Experiment 2, active training increased a driver’s probability of looking for a threat during a turn by nearly 100% in both posttraining simulator and field drives. Those receiving passive training or no training showed no improvement. Conclusion Compared with passive training, active training is a more effective strategy for increasing older drivers’ likelihood of looking for threats during a turn. Application The results of this research can guide the development of programs that could reduce intersection crashes among older drivers.

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Younger drivers (18–21 years) are over-involved in crashes. Research suggests that one of the reasons for this over-involvement is their failure to scan areas of the roadway for information about potential risks in situations that are hazardous, but not obviously so. The primary objective of the present study is to develop and evaluate a training program that addresses this failure. It was hypothesised that PC-based hazard anticipation training would increase the likelihood that younger drivers would scan for potential hazards on the open road. In order to test this hypothesis, 12 trained and 12 untrained drivers' eye movements were measured as they drove a vehicle on local residential, feeder and arterial roads. Overall, the trained drivers were significantly more likely to gaze at areas of the roadway that contained information relevant to the reduction of risks (64.4%) than were the untrained drivers (37.4%). Significant training effects were observed even in situations on the road that were quite different from those shown in training. These findings have clear implications for the type of training of teen drivers that is necessary in order to increase their anticipation of hazards.

The PC training program developed, which is portable and can be widely used, has great promise in improving risk perception for novice drivers on the road.

Sixteen year old drivers are involved in 10.3 fatal crashes per 100 million vehicle miles, a rate almost double that of 18 year olds and almost eight times that of 45–64 year olds, who are the safest group of drivers. Crash rates are particularly higher during the first month of licensure and decline rapidly for about six months and 1000 miles and then much more slowly for at least two years, consistent with a typical learning curve. Research indicates that drivers who have their learner’s permit or are just newly licensed have particular difficulties identifying areas of a scenario from which hidden risks could emerge. Standard driver education programs do not appear to address these difficulties adequately. This suggests that some alternative form of driver training could reduce the crashes, either in the classroom or on the road. A PC based program designed to teach drivers to recognize risks early on is shown to improve their awareness of hazards, both on an advanced driving simulator and on the road.

Novice drivers (teen drivers with their solo license for six months or less) are at a greatly inflated risk of crashing. Post hoc analyses of police accident reports indicate that novice drivers fail to anticipate hazards, manage their speed, and maintain attention. These skills are much too broadly defined to be of much help in training. Recently, however, driving simulators have been used to identify those skills which differentiate the novice drivers from older, more experienced drivers in the areas of hazard anticipation and speed management. Below, we report an experiment on a driving simulator which compares novice and experienced drivers’ performance in the third area believed to contribute especially heavily to crashes among novice drivers: attention to the forward roadway. The results indicate that novice drivers are much more willing to glance for long periods of time inside the vehicle than are experienced drivers. Interestingly, the results also indicate that both novice and experienced drivers spend equal amounts of time glancing at tasks external to the vehicle and in the periphery. Moreover, just as a program has been designed to train the scanning skills that clearly differentiate novice from experienced drivers, one might hope that a training program could be designed to improve the attention maintenance skills of novice drivers. We report on the initial piloting of just such a training program. Finally, we address a question that has long been debated in the literature: Do the results from driving simulators generalize to the real world? We argue that in the case of hazard anticipation, speed management, and attention maintenance the answer is yes.