The DVA model has applications to several traffic safety issues, including automated driving systems and traffic flow models.

No abstract

Previous research has indicated that observers use differences between velocities and ratios of velocities to judge the depth within a moving object, although depth cannot in general be determined from these quantities. In four experiments we examined the relative effects of velocity difference and velocity ratio on judged depth within a transparent object that was rotating about a vertical axis and translating horizontally, examined the effects of the velocity difference for pure rotations and pure translations, and examined the effect of the velocity difference for objects that varied in simulated internal depth. Both the velocity difference and the velocity ratio affected judged depth, with difference having the larger effect. The effect of velocity difference was greater for pure rotations than for pure translations. Simulated depth did not affect judged depth unless there was a corresponding change in the projected width of the object. Observers appear to use the velocity difference, the velocity ratio, and the projected width of the object heuristically to judge internal object depth, rather than using image information from which relative depth could potentially be recovered.

An important task during driving is the maintenance of headway during car following. The visual information available to a driver for successful car following was examined. A model of car following that used the visual angle and change in visual angle of a lead vehicle was developed. The study examined whether information from the surrounding scene (e.g., the roadway and buildings) influenced car-following performance. Licensed drivers were presented with a car-following task in a driving simulator. The simulator display consisted of a roadway scene with a lead vehicle that varied speed according to a sine wave. To evaluate the role of scene information, car-following performance was examined when the surrounding scene was present or absent. Two frequencies and three amplitudes of speed variation were also examined. The results indicated that control gain was greater when the scene was absent, with near unity gain when the scene was present. These findings indicated more accurate control during car following when the surrounding scene information was present. These results suggest that drivers also use other sources of information (e.g., absolute distance information from height in the visual field relative to the horizon and edge rate information specifying observer speed) to maintain headway. The implications of this research to nighttime accident rates and intelligent highway systems are discussed.

Effects of information specifying the position of an object in a 3-D scene were investigated in two experiments with twelve observers. To separate the effects of the change in scene position from the changes in the projection that occur with increased distance from the observer, the same projections were produced by simulating (a) a constant object at different scene positions and (b) different objects at the same scene position. The simulated scene consisted of a ground plane, a ceiling plane, and a cylinder on a pole attached to both planes. Motion-parallax scenes were studied in one experiment; texture-gradient scenes were studied in the other. Observers adjusted a line to match the perceived internal depth of the cylinder. Judged depth for objects matched in simulated size decreased as simulated distance from the observer increased. Judged depth decreased at a faster rate for the same projections shown at a constant scene position. Adding object-centered depth information (object rotation) increased judged depth for the motion-parallax displays. These results demonstrate that the judged internal depth of an object is reduced by the change in projection that occurs with increased distance, but this effect is diminished if information for change in scene position accompanies the change in projection.