Perceptual Countermeasures Against Tailgating:
A Virtual Reality Experiment


Bernhard F. Frey

Massey University School of Aviation, Auckland, New Zealand

 

This paper reports the results of a simulator study investigating the utility of three different display systems aimed at reducing the incidence of tailgating in highway traffic. The performance of 45 participants is evaluated against two control conditions (normal driving conditions, and normal driving conditions plus instructions to maintain a 2-second gap). The relative strengths and weaknesses of each system are assessed under three different road conditions (i.e., straight and level, winding, and undulating).

The first display system consists of a light mounted on the rear bumper of the (computer controlled) leading car. The light is linked to equipment measuring the distance to a following car, and changes color with time-to-contact (t ; Lee, 1976). The second display system draws on technology that is used in aviation to guide the approach path of an aircraft to an airfield (visual approach slope indicators). The adapted system consists of a light enclosed in a small box that is affixed to the rear bumper of the leading car. The system serves to delineate the projected light beam. The exact configuration of the delineation mechanism is linked to the speed of that car. The perceptual experience of the driver of the following car is such that a light appears to wink on when the eye traverses the edge of the beam (i.e., when t reaches a pre-determined magnitude).

The third display system is based more firmly on the concept of natural display and control systems . It makes the crucial variable (t ) more directly available to the driver of the following car, in the form of a predictive display that indicates the location on the road that that car will pass in a specified amount of time.

Performance is recorded in real-time to allow quantitative evaluation. The arguably most important measures extracted from the raw data (x, y, z -position) are t , and variability in t , but a range of other measures are also evaluated (e.g., number, variability, and magnitude of control inputs). The primary analysis technique is repeated measures multi-variate analysis of variance, but other techniques (e.g., regression) may be utilized as and when appropriate. Results are discussed with respect to both theoretical and practical considerations.