Selecting the most promising areas to introduce pooled feeder services when the demand is unknown: case study of Krakow, Poland

Abstract

This study proposes a parameter-free method to assess the potential of pooled on-demand transit feeder services in urban areas with unknown demand. We introduce the ’fraction of demand’, reflecting the probability that a resident will use the service. Demand is generated on the distribution of residents’ address points at varying demand fraction levels. Through simulations, we match travellers into pooled rides and evaluate the service’s potential using three performance indicators (KPIs). We observe how these KPIs change with varying demand fractions and identify the most promising hub for each area. By setting KPI thresholds, we select the optimal combination of area and hub that meets these thresholds at the lowest demand fraction. This approach assists municipalities in selecting the best areas to launch new services despite the absence of exact demand data. We illustrate its application through a case study in Krakow, ranking 12 pre-selected areas for feeder service deployment.