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.

翻译：随着新型服务的出现，城市交通正经历快速变革。移动枢纽（MHs）被提出作为物理-数字融合点，在邻近范围内提供一系列公共和私人出行选择。通过支持出行即服务，这些枢纽可作为出行决策与运营商策略交汇的焦点。我们开发了一个双层移动枢纽平台设计模型，将移动枢纽视为控制杠杆。上层（平台）通过设定补贴激励最后一公里运营商，以实现收入或流量的最大化；下层通过基于路段的扰动效用路径选择（PURC）分配模型捕捉出行者与运营商的联合决策，该模型可转化为严格凸二次规划。我们利用下层的KKT条件将双层问题重构为单层规划，并采用间隙惩罚法及利用下层问题计算成本低廉特性的迭代热启动方案进行求解。在玩具网络和长岛铁路（LIRR）案例（244个节点、469条路段、78个OD对）上的数值实验表明，该方法可在数分钟内获得低于1%的最优性间隙。在基础LIRR案例中，该模型使政策制定者能够量化移动枢纽的社会剩余价值，或实施补贴、监管微出行运营商定价的价值。比较基于路段的补贴与基于枢纽的补贴，后者计算成本更高，但提供了更便于比较与控制的机制。