The present study developed and tested a driving by visual angle (DVA) model of car following, which is based on visual information (visual angle and rate of change of visual angle) available to the driver. Two experiments in a driving simulator examined car-following performance in response to speed variations of a lead vehicle defined by a sum of sine wave oscillations and ramp acceleration functions. The model also was applied to six driving events using real world driving data. Findings indicate that the model provided a good fit to car-following performance in the driving simulation studies as well as in real-world driving performance. A comparison with a model based on three-dimensional parameters suggests that the DVA was more predictive of driver behavior in matching lead vehicle speed and distance headway.
Abstract