Determining Appropriate Fare Levels for Distance-Based Fare Structure Considering Users' Behaviors in a Time-Expanded Network

This research investigated the potential of a distance-based fare structure with a case study of the Utah Transit Authority system in northern Utah. The metrics of evaluation were viewed through demand maximization within a modeling scheme for a distance-based fare structure for all fixed route transit modes. Transit users' route choices were explicitly modeled in the transit system on the time-expanded network. This modeling scheme was integrated into the lower level of the hi-level programming framework, where the upper level uncovered the optimized fare levels for the distance-based fare structure with a genetic algorithm. Through implementation of the methodology, the distance-based fare levels were evaluated for their effect on increasing transit demand. Using the market segmentation analysis, the study found that a distance-based fare with a no-base fare had the highest potential for increasing the transit demand. A $0.50 base fare was examined and was shown to be feasible in the case that a base fare was not necessary because of agency policy.