Subjective and predicted sleepiness while driving in young adults

Sleepiness is a significant contributor to car crashes and sleepiness related crashes have higher mortality and morbidity than other crashes. Young adult drivers are at particular risk for sleepiness related car crashes. It has been suggested that this is because young adults are typically sleepier than older adults because of chronic sleep loss, and more often drive at times of increased risk of acute sleepiness. This prospective study aimed to determine the relationship between predicted and perceived sleepiness while driving in 47 young-adult drivers over a 4-week period. Sleepiness levels were predicted by a model incorporating known circadian and sleep factors influencing alertness, and compared to subjective ratings of sleepiness during 25 18 driving episodes. Results suggested that young drivers frequently drive while at risk of crashing, at times of predicted sleepiness (>7% of episodes) and at times they felt themselves to be sleepy (>23% of episodes). A significant relationship was found between perceived and predicted estimates of sleepiness. However, the participants nonetheless drove at these times. The results of this study may help preventative programs to specifically target factors leading to increased sleepiness when driving (particularly time of day), and to focus interventions to stop young adults from driving when they feel sleepy. (c) 2005 Elsevier Ltd. All rights reserved.

Does anticipation training affect drivers' risk taking?

Skill and risk taking are argued to be independent and to require different remedial programs. However, it is possible to contend that skill-based training could be associated with an increase, a decrease, or no change in fisk-taking behavior. In 3 experiments, the authors examined the influence of a skill-based training program (hazard perception) on the fisk-taking behavior of car drivers (using video-based driving simulations). Experiment 1 demonstrated a decrease in risk taking for novice drivers. In Experiment 2, the authors examined the possibilities that the skills training might operate through either a nonspecific reduction in risk taking or a specific improvement in hazard perception. Evidence supported the latter. These findings were replicated in a more ecological context in Experiment 3, which compared advanced and nonadvanced police drivers.

Signal detection theory in applied tasks: The case of hazard perception in driving

Fuzzy signal detection analysis can be a useful complementary technique to traditional signal detection theory analysis methods, particularly in applied settings. For example, traffic situations are better conceived as being on a continuum from no potential for hazard to high potential, rather than either having potential or not having potential. This study examined the relative contribution of sensitivity and response bias to explaining differences in the hazard perception performance of novices and experienced drivers, and the effect of a training manipulation. Novice drivers and experienced drivers were compared (N = 64). Half the novices received training, while the experienced drivers and half the novices remained untrained. Participants completed a hazard perception test and rated potential for hazard in occluded scenes. The response latency of participants to the hazard perception test replicated previous findings of experienced/novice differences and trained/untrained differences. Fuzzy signal detection analysis of both the hazard perception task and the occluded rating task suggested that response bias may be more central to hazard perception test performance than sensitivity, with trained and experienced drivers responding faster and with a more liberal bias than untrained novices. Implications for driver training and the hazard perception test are discussed.

Do expert drivers have a reduced illusion of superiority?

It is well established that people tend to rate themselves as better than average across many domains. To maintain these illusions, it is suggested that people distort feedback about their own and others' performance. This study examined expert/novice differences in self-ratings when people compared themselves with others of the same level of expertise and background as themselves. Given that a key expert characteristic is increased self-monitoring, we predicted that experts in a domain may have a reduced illusion of superiority because they are more aware of their actual ability. We compared expert police drivers with novice police drivers and found that this prediction was not supported. Expert police drivers rated themselves as superior to equally qualified drivers, to the same degree as novices, Cohen's d = .03 ns. Despite their extensive additional training and experience, experts still appear to be as susceptible to illusions of superiority Lis everyone else. (C) 2004 Elsevier Ltd. All rights reserved.