Analysis of demand–supply gaps in public transit systems based on census and GTFS data: a case study of Calgary, Canada

Abstract

Abstract Bridging the gap between demand and supply in transit service is crucial for public transportation management, as planning actions can be implemented to generate supply in high demand areas or to improve upon inefficient deployment of transit service in low transit demand areas. This study aims to introduce feasible approaches for measuring gap types 1 and 2. Gap type 1 measures the gap between public transit capacity and the number of public transit riders per area, while gap type 2 measures the gap between demand and supply as a normalized index. Gap type 1 provides a value that is more realistic than gap type 2, but it requires detailed passenger data that is not always readily available. Gap type 2 is a practical alternative when the detailed passenger data is unavailable because it uses a weighting scheme to estimate demand values. It also uses a newly proposed normalization method called M-score, which allows for a longitudinal gap analysis where yearly gap patterns and trends can be observed and compared. A 5-year gap analysis of Calgary transit is used as a case study. This work presents a new perspective of hourly gaps and proposes a gap measurement approach that contributes to public transit system planning and service improvement.