Probabilistic delay model at stop-controlled intersection

Operating conditions at stop-controlled approaches to highway intersections depend, to a large extent, on the gap-acceptance behavior of motorists. Several researchers have previously proposed and demonstrated the application of discrete-choice modeling techniques for predicting gap-acceptance probabilities. The work described in this paper has used logit modeling to predict the probability that a randomly chosen motorist will accept a given gap in the conflicting traffic stream based upon characteristics of the gap. This gap-acceptance function is then used in a stochastic queuing model to predict vehicle delay. The specific methodology presented in this paper is applicable to right-turning traffic at a T-intersection. Evaluation of the methodology using an empirical data set suggests that the proposed analysis approach offers significant potential. Issues related to extending the applicability and generality of the proposed methodology are briefly discussed in the conclusions of this paper.