An experimental comparison of conservative versus optimal collision avoidance warning system thresholds

Abstract

In the distributed signal detection theoretic (DSDT) model, the human operator and the warning mechanism are independent decision makers who work together as a team. The DSDT demonstrates that the optimal warning threshold, in general, differs from the signal detection theoretic (SDT) threshold, which assumes a single decision maker. This prediction was tested in an experiment where drivers received monetary rewards for making safe passing decisions on a driving simulator. The experiment focused on evaluating the quality of the decision making of the drivers, and not on perceptual issues. A collision avoidance system provided a warning when the probability of an inadequate overtaking gap exceeded a threshold. Three thresholds were tested. The control threshold resulted in no detections or false alarms. The DSDT threshold resulted in some misses but no false alarms. The SDT threshold resulted in no misses but frequent false alarms. As predicted, (1) drivers performed the best when the warning system used the DSDT threshold, and (2) use of the SDT threshold improved performance over the control threshold, even though four of the 10 drivers occasionally ignored the warning and made risky passing attempts in the SDT conditions, possibly because of earlier false alarms. These findings support the conclusion that the DSDT model is a useful, quantitative tool that should be used by warning designers.