Comparative Analysis of Random Utility Models and Fuzzy Logic Models for Representing Gap-Acceptance Behavior Using Data from Driving Simulator Experiments

The paper proposes a comparative analysis of random utility models and fuzzy logic models for representing gap-acceptance behavior at priority intersections, based on data collected from driving simulator tests. Explanatory variables not detectable from on site observations were observed in the experiments. The proposed models include driving styles variables in addition to variables commonly used in gap-acceptance studies. The driving tests have been conducted using STSoftware® fixed-base driving simulator. The comparison between the two kinds of models, performed using the Receiver Operating Characteristic (ROC) curve analysis, indicates that fuzzy models can be considered an alternative to the use of random utility models. Furthermore the ability of driving simulators to provide data not detectable from direct observations is highlighted.