This paper describes a model, called Decision-Making under Risk In a Vehicular Environment (DRIVE), that simulates the trade-off between two strategies for achieving a goal in real time: 1) Responding quickly to meet a deadline and 2) delaying responses to better evaluate risks. DRIVE is used to predict the performance of an automobile driver waiting to cross an intersection as a car approaches from the cross street. In this task, the driver is punished for crashing into the oncoming car, but is also put under pressure to cross quickly. Results show a relationship between risk-taking on the intersection-crossing task and external measures of risk taking, including driving history and participation in risky activities. DRIVE model fits indicate that individual differences on this task can be accounted for by varying the decision-making parameters in the model, rather than the perceptual parameters.