Where and when does demand-responsive transport work best? A parametric analysis using agent-based modelling

Demand-Responsive Transport (DRT) presents significant potential to address the inefficiencies of conventional public transport, particularly in low-demand areas where conventional fixed-route services struggle with poor cost-efficiency and coverage. This study develops a unified agent-based modelling (ABM) framework to evaluate DRT performance across different urban contexts, addressing the lack of systematic evaluation tools for context-specific service design. The research introduces a novel parametric ABM integrating a comprehensive real-time matching algorithm that balances passenger utility and operator costs through a composite cost function. Unlike existing approaches, the model incorporates passenger walking behaviour, automatically adjusting service flexibility based on demand intensity whilst enabling systematic comparison across diverse operational scenarios. Three representative contexts are evaluated: small cities (many-to-many demand), large cities during off-peak periods (lower spatial demand density due to expanded service areas), and suburban feeder services (directional many-to-one patterns). Each scenario is analysed across fleet sizes (2–40 vehicles) and demand rates (10–200 requests/hour), with performance assessed through integrated passenger, operator, and economic indicators. Results demonstrate that DRT performance is fundamentally context-dependent. Suburban feeder services emerge as the optimal application, achieving total unit costs of 4–6 € per passenger and requiring minimal fleet investments (4–6 vehicles), representing 40–60 % cost advantages over urban scenarios. Small city operations achieve viable performance with moderate resources (8–12 vehicles, 6–8 €/pax), whilst large city deployments require substantial commitments (16–28 vehicles, 10–18 €/pax). The analysis reveals critical minimum viable fleet thresholds scaling proportionally with urban complexity, with capital investment ratios of 1:2:4 across scenarios, and confirming that spatial density fundamentally determines DRT viability. The findings provide evidence-based guidance for transport authorities, positioning suburban feeder applications as optimal entry points for DRT implementation.