Designing Integrated Fare Systems: A Pareto-Based Evaluation of Structural Complexity and Price-Distance Fairness

Abstract

This paper presents a decision-support framework for designing integrated fare systems across fixed-route and on-demand public transport. Using one year of operational and ridership data from Ingolstadt (Germany), we generate a set of ring- and cell-based zoning schemes and calibrate fares to preserve current single-ticket revenue. For the evaluation, we focus on the trade-off between an easy-to-understand tariff system, captured by structural complexity, and price-distance fairness (Gini index). Fare-system performance is first assessed separately for fixed-route and on-demand services. In a second step, Pareto-efficient joint fare systems are identified and ranked by their weighted Euclidean distance to an ideal point representing minimum complexity and maximum fairness. Findings show that moderate zoning granularity can improve both simplicity and price-distance fairness. Overall, the framework provides transport authorities a decision-support tool for selecting user-oriented integrated fare systems.