Assessing a Perceptual Model of Risky Real-Time Decision Making

A new model of real-time risky decision making is introduced that predicts tradeoffs between processing and risk taking during driving. This model, called Decision-Making under Risk in a Vehicle, or DRIVE, was fitted to data from a task in which subjects decided when to cross an intersection as a car approached from the cross street. Results showed that subjects attempted to cross less often before the oncoming car when it started closer to the intersection, even though objective risk was the same regardless of starting distance. Also, when the car started closer, subjects who reported having more real-life automobile accidents were less likely to take advantage of a longer opportunity to cross first. These results, along with results from fitting DRIVE to the data, suggest that risk-taking effects can be accounted for by a model of risk perception, and not by a model of risk acceptance.