![]() The best model for predicting passing or failing the on-road assessment included the Hazard Perception Test, color vision, and, a measure of walking speed from the Roadwise Review, which yielded a sensitivity of 82% and a specificity of 69% (AROC =. The Hazard Perception Test approached significance when predicting accumulated points and was a significant predictor of automatic disqualifications, as well as pass/fail outcomes. The number of serious problems (excluding head and neck flexibility) that were identified by the Roadwise Review was a significant predictor of automatic disqualifications, and a significant predictor of passing or failing the on-road assessment. Raw scores on the Roadwise Review did not predict accumulated points, or automatic disqualifications, but could predict who would pass or fail the on-road evaluation. approximately 18 km, along a mixed residential and commercial route. They also participated in a standardized driving assessment of. The Roadwise Review, a brief Hazard Perception Test and several tests of vision were given to 65 cognitively healthy, licensed older drivers (M = 74 years, SD = 9 years). This study evaluated the ability to predict the on-road driving of older drivers using a battery of laboratory-based instruments. The findings lend support to the need to create a safety culture in which driver assessment and improvement is the norm, as well as reducing exposure to risk wherever possible through better ways of working and travelling. Both attitude and behaviour scores exhibit a statistically significant association with collision involvement, along with other variables such as mileage driven, driver age and personality. The influence of these variables on collision involvement was assessed using a Poisson regression model. ![]() Analysis of the data revealed that attitude, behaviour, knowledge and hazard perception are highly correlated with self-reported collisions. Data was also collected on driver demographics and their driving and collision history. A large and unique data set collected from online assessment of drivers employed in a UK telecommunications organisation is analyzed. The aim of this paper is to review the practical application of an online fleet driver assessment program to help identify, target and reduce occupational road safety risks. Knowledge of the Rules of the Road and the perception of hazards are also associated with collision involvement. Many studies have shown that driver attitude and behaviour are important determinants of the likelihood of collision involvement. ![]()
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