Using judgment analysis to identify at-risk drivers and to evaluate the effectiveness of training for changing drivers' perceptions of crash risk
Date of Completion
Automobile crashes are associated with considerable economic costs for organizations that rely on the operation of motor vehicles as a part of everyday business activities. As such, being able to identify drivers who are more likely to be involved in crashes is something that would greatly benefit a large number of organizations. Little research, however, has focused on finding low-cost ways to identify potential problem drivers in the selection process or already within an organization. ^ The primary goal of the research presented here was to assess whether judgment analysis and individual difference measures can be useful tools for the identification of at-risk drivers, and whether computer-based training can have an impact on how drivers use various cues when making judgments of crash risk. ^ In one study, a judgment task focusing on perceptions of crash risk in various driving scenarios was developed and administered to younger (under 21 years of age) and older drivers (over 25 years of age). Analysis of participants' responses to the judgment task showed that differences among younger and older drivers existed for the weight assigned to the presence of passengers, road type being driven on, and time with eyes off of the roadway. Results of a second study showed some indications that the weight assigned to driver distraction in the judgment task could be potentially useful for predicting extended glances away from the forward roadway. Finally, a third study did not find any changes in crash risk factor weights after exposure to a training program, but a number of relationships were found among individual difference measures and baseline performance on a computer-based attention maintenance assessment program. ^ The practical implications of the findings of each study are discussed and directions for future research proposed. ^
Thomas, Franklin Dennis, "Using judgment analysis to identify at-risk drivers and to evaluate the effectiveness of training for changing drivers' perceptions of crash risk" (2009). Doctoral Dissertations. AAI3383930.