Fully automated services allow for greater flexibility in operations and lower marginal operational costs. In this study we examined the strategic planning implications of a novel service concept – an automated rail demand responsive transit (DRT) system that offers a direct non-stop service. The objective of this study was to determine the capacity requirements of the envisaged service and discuss its prospects and feasibility. A cost minimization approach for determining the optimal track and station platform capacities for a rail-DRT system so that passenger, infrastructure, and operational costs are minimized is described. The macroscopic model allows for studying the underlying relations between technological, operational and demand parameters, optimal capacity settings, and the obtained cost components. The model was applied to a series of numerical experiments to test its implications for different network structures and demand distributions. The results of the numerical experiments indicate that – unlike conventional rail systems in which stations often are capacity bottlenecks – link capacity properties are more critical for the performance of automated rail-DRT systems than station capacity. A series of sensitivity analyses was performed to test the consequences of various cost and capacity specifications, as well as the characteristics of future automated rail-DRT systems.