📝 SummarXiv

Abstract

Urban mobility is undergoing rapid transformation with the emergence of new services. Mobility hubs (MHs) have been proposed as physical-digital convergence points, offering a range of public and private mobility options in close proximity. By supporting Mobility-as-a-Service, these hubs can serve as focal points where travel decisions intersect with operator strategies. We develop a bilevel MH platform design model that treats MHs as control levers. The upper level (platform) maximizes revenue or flow by setting subsidies to incentivize last-mile operators; the lower level captures joint traveler-operator decisions with a link-based Perturbed Utility Route Choice (PURC) assignment, yielding a strictly convex quadratic program. We reformulate the bilevel problem to a single-level program via the KKT conditions of the lower level and solve it with a gap-penalty method and an iterative warm-start scheme that exploits the computationally cheap lower-level problem. Numerical experiments on a toy network and a Long Island Rail Road (LIRR) case (244 nodes, 469 links, 78 ODs) show that the method attains sub-1% optimality gaps in minutes. In the base LIRR case, the model allows policymakers to quantify the social surplus value of a MH, or the value of enabling subsidy or regulating the microtransit operator's pricing. Comparing link-based subsidies to hub-based subsidies, the latter is computationally more expensive but offers an easier mechanism for comparison and control.