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 risk-taking behavior. In 3 experiments, the authors examined the influence of a skill-based training program (hazard perception) on the risk-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. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The development, validation, and application of a video-based technique for measuring an everyday risk-taking behavior: Drivers' speed choice.

Drivers' choice of speed is an important aspect of everyday risk-taking behavior because it has been shown to be one of the most important predictors of road accident involvement. This research developed, validated, and applied a measure of drivers' speed choice that combined a high degree of experimental control with external and ecological validity. In Study 1, a video-simulation measure of drivers' speed choice was developed and found to relate specifically to speed-related accident involvement among, implying a degree of external validity. In Study 2, the measure was used to investigate the effect of auditory feedback on drivers' speed choice. It was found that increasing the level of internal car noise decreased drivers' preferred speeds. Further analyses indicated that this was likely due to perceptual effects on speed estimation. Results are discussed in terms of road safety and the ability of video-based measures to facilitate experimental control over tasks involving complex ecological stimuli. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Older drivers' insight into their hazard perception ability

Even though the driving ability of older adults may decline with age, there is evidence that some individuals attempt to compensate for these declines using strategies such as restricting their driving exposure. Such compensatory mechanisms rely on drivers’ ability to evaluate their own driving performance. This paper focuses on one key aspect of driver ability that is associated with crash risk and has been found to decline with age: hazard perception. Three hundred and seven drivers, aged 65–96, completed a validated video-based hazard perception test. There was no significant relationship between hazard perception test response latencies and drivers’ ratings of their hazard perception test performance, suggesting that their ability to assess their own test performance was poor. Also, age-related declines in hazard perception latency were not reflected in drivers’ self-ratings. Nonetheless, ratings of test performance were associated with self-reported regulation of driving, as was self-rated driving ability. These findings are consistent with the proposal that, whileself-assessments of driving ability may be used by drivers to determine the degree to which they restrict their driving, the problem is that drivershave little insight into their own driving ability. This may impact on the potential road safety benefits of self-restriction of driving because drivers may not have the information needed to optimally self-restrict. Strategies for addressing this problem are discussed.     

The development and validation of a hazard perception test for use in driver licensing

Drivers’ hazard perception is the ability to identify dangerous situations on the road ahead. We detail the development and validation of a new computer-based hazard perception test to be used for driver licensing purposes in Queensland, Australia. We proposed five principles of effective hazard perception test creation, which we used to guide development of the test. In Study 1, the video-based instructions for the test were found to be intelligible to non-native English-speakers with an effective English reading age of 10 years. In Study 2, experienced drivers were found to be faster at responding to hazards in the test than learner drivers (independent of simple reaction time or ability to use the response device), providing evidence for test validity. We found no evidence of gender, income, or educational differences in hazard perception scores. The results of both experiments confirm the efficacy of the five principles, and provide support for the validity of the QT-HPT and its suitability for use in the graduated driver licensing system.     

A hazard perception test for novice drivers

We developed a hazard perception test, modeled on that used currently in several Australian states, that presents short video scenes to observers and requires them to indicate the presence of a traffic conflict that would lead to a collision between the “camera” vehicle and another road user. After eliminating those scenes that were problematic (e.g., many observers did not recognize the hazard), we predicted driver group (novice vs. experienced drivers of similar age) on the basis of individual differences in reaction time, miss rate and false alarm rate. Novices were significantly slower in responding to hazards, even after controlling for age and simple reaction time. After selecting those scenes with the larger group differences, an 18-scene test that would be useful for mass testing exhibited even larger experience effects. There was good reliability in the resulting scale. Results suggest that this brief test of hazard perception can discriminate groups that differ in driving experience. Implications for driver licensing, evaluation and training are discussed.     

Using fuzzy signal detection theory to determine why experienced and trained drivers respond faster than novices in a hazard perception test

Drivers’ hazard perception ability, as measured in video-based simulations, correlates with crash involvement, improves with experience and can be trained. We propose two alternative signal detection models that could describe individual differences in this skill. The first model states that novice drivers are poorer at discriminating more hazardous from less hazardous situations than experienced drivers. The second model proposes that novice drivers require a higher threshold of danger to be present before they notice a situation is hazardous or before they are willing to classify a situation as hazardous. We applied a technique involving fuzzy signal detection analysis to differentiate between these two models when comparing novice and experienced drivers, and trained and untrained drivers, in various video-based hazard perception measures. The data favored the second model.     

Visual architecture and cognitive architecture

Traditional architectures have fundamental epistemological problems. Perception is inherently resource limited so controlling perception involves all the same AI-complete problems of reasoning about time and resources as the full-scale planning problem. Allowing a planner to transparently assume that the information it needs will automatically be present and up-to-date in the model thus presupposes a solution to a problem at least as difficult as planning itself. Although one can imagine many possible solutions to this problem, such as allowing the planner to recurse on its own epistemological problems, there have been no convincing attempts at this. In this paper, I compare behaviour-based and traditional systems in terms of their representational power and the strengths of their implicit epistemological theories. I argue that both have serious limitations and that those limitations are not addressed simply by joining the two into a hybrid. I discuss my work with using vision to support real-time activity and give an example of an interesting intermediate point between reactive and classical architectures that preserves the simplicity and parallelism of behaviour-based systems while supporting ‘symbolic’ representations. Traditionally, AI theories have assumed, either implicitly or explicitly, an architecture in which modules of the mind (perception, reasoning, motor control, etc.) are linked by way of some centralized database like structure, often referred to as a world model. Recently, a number of alternative architectures have been proposed which, to greater or lesser degrees, claim to do away with world models or with representations entirely. Many of the criticisms of traditional architectures revolve around speed and timescale. Planning, so the story goes, is slow but flexible, while feedback loops are fast but stupid. A common approach, both in this special issue and in the literature in general, is to adopt a hybrid which fuses a slow planner running on a long time-scale and a set of fast feedback loops running on a short time-scale. The problem with this argument is that planning is not slow, it is combinatorially explosive. Running an O(2 ⁿ ) algorithm on a time-scale ten times slower is the same as running it on a computer ten times faster : it simply lets one increase n by three. If time-scale were the true problem, faster CPUs would make tiered architectures obsolete in a few years. I believe the true issues are not speed, in the sense of time-scale, but combinatorics and epistemology. The former has been extensively discussed, so I will focus on epistemology. Clearly, if an agent architecture is to be successful it must take into account the capacities and limitations of perception. In this paper I discuss the influence of perceptual architecture on agent architecture, argue that the recent wave of tiered architectures do not adequately address these problems, and discuss my work on using vision to support real-time activity.     

The development and validation of two complementary measures of drivers’ hazard perception ability

Hazard perception in driving involves a number of different processes. This paper reports the development of two measures designed to separate these processes. A Hazard Perception Test was developed to measure how quickly drivers could anticipate hazards overall, incorporating detection, trajectory prediction, and hazard classification judgements. A Hazard Change Detection Task was developed to measure how quickly drivers can detect a hazard in a static image regardless of whether they consider it hazardous or not. For the Hazard Perception Test, young novices were slower than mid-age experienced drivers, consistent with differences in crash risk, and test performance correlated with scores in pre-existing Hazard Perception Tests. For drivers aged 65 and over, scores on the Hazard Perception Test declined with age and correlated with both contrast sensitivity and a Useful Field of View measure. For the Hazard Change Detection Task, novices responded quicker than the experienced drivers, contrary to crash risk trends, and test performance did not correlate with measures of overall hazard perception. However for drivers aged 65 and over, test performance declined with age and correlated with both hazard perception and Useful Field of View. Overall we concluded that there was support for the validity of the Hazard Perception Test for all ages but the Hazard Change Detection Task might only be appropriate for use with older drivers.