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As Mobility as a Service (MaaS) systems become increasingly popular, travelis changing from unimodal trips to personalized services offered by a platformof mobility operators. Evaluation of MaaS platforms depends on modeling bothuser route decisions as well as operator service and pricing decisions. Weadopt a new paradigm for traffic assignment in a MaaS network of multipleoperators using the concept of stable matching to allocate costs and determineprices offered by operators corresponding to user route choices and operatorservice choices without resorting to nonconvex bilevel programmingformulations. Unlike our prior work, the proposed model allows travelers tomake multimodal, multi-operator trips, resulting in stable cost allocationsbetween competing network operators to provide MaaS for users. An algorithm isproposed to efficiently generate stability conditions for the stable outcomemodel. Extensive computational experiments demonstrate the use of the model tohandling pricing responses of MaaS operators in technological and capacitychanges, government acquisition, consolidation, and firm entry, using theclassic Sioux Falls network. The proposed algorithm replicates the samestability conditions as explicit path enumeration while taking only 17 secondscompared to explicit path enumeration timing out over 2 hours.

A many-to-many assignment game and stable outcome algorithm to evaluate collaborative Mobility-as-a-Service platforms