Abstract

Hazard perception skill has been found to be associated with drivers’ crash risk. This skill has typically been measured using computer-based response-time hazard perception tests, in which drivers indicate the earliest point that they detect a potential hazard in video clips of traffic filmed from a driver’s perspective. In recent years, researchers have suggested an alternative type of measure, known as a “hazard prediction test”, in which each test item is a traffic clip that stops (typically cutting to black) just before a hazardous incident unfolds. Drivers taking the test have to predict what happens next in the clip. Measures of this kind have been found to distinguish between high risk (novice) and lower risk (experienced) driver groups, and have been argued to offer several advantages over traditional response-time hazard perception tests. However, a key strength of the response-time hazard perception test is that assessments using this format have been found to predict crash involvement. The same has not yet been demonstrated for hazard prediction tests, raising questions about their validity. In the present research, we created a new hazard prediction test using Australian traffic scenes. In our version of the test, drivers’ scores were based on how many plausible predictions they were able to generate for each traffic clip. We established validity evidence for the test scores in two studies with separate samples, using two different versions of the test (long vs. short) with different response modes (verbal vs. written). As well as distinguishing between novice and experienced driver groups, test scores were also associated with self-reported crash involvement in both studies. We also found a significant correlation between hazard prediction test scores and scores in an established response-time hazard perception test. These findings support the proposal that scores on the hazard prediction test are a valid measure of hazard perception skill.

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