As Mobility as a Service (MaaS) systems become increasingly popular, travel is changing from unimodal trips to personalized services offered by a platform of mobility operators. Evaluation of MaaS platforms depends on modeling both user route decisions as well as operator service and pricing decisions. We adopt a new paradigm for traffic assignment in a MaaS network of multiple operators using the concept of stable matching to allocate costs and determine prices offered by operators corresponding to user route choices and operator service choices without resorting to nonconvex bilevel programming formulations. Unlike our prior work, the proposed model allows travelers to make multimodal, multi-operator trips, resulting in stable cost allocations between competing network operators to provide MaaS for users. An algorithm is proposed to efficiently generate stability conditions for the stable outcome model. Extensive computational experiments demonstrate the use of the model to handling pricing responses of MaaS operators in technological and capacity changes, government acquisition, consolidation, and firm entry, using the classic Sioux Falls network. The proposed algorithm replicates the same stability conditions as explicit path enumeration while taking only 17 seconds compared to explicit path enumeration timing out over 2 hours.

随着移动即服务（MaaS）系统变得越来越流行，旅行正从单峰旅行变为由移动运营商平台提供的个性化服务。对MaaS平台的评估取决于对用户路线决策以及运营商服务和定价决策建模。我们采用稳定匹配的概念，在由多个运营商组成的MaaS网络中采用一种新的流量分配范式，以分配成本并确定与用户路线选择和运营商服务选择相对应的运营商提供的价格，而无需采用非凸双层编程公式。与我们之前的工作不同，提出的模型允许旅行者进行多模式，多运营商旅行，从而在竞争网络运营商之间进行稳定的成本分配，为用户提供MaaS。提出了一种有效生成稳定结果模型的稳定条件的算法。大量的计算实验表明，使用经典的苏福尔斯网络，该模型可用于处理MaaS运营商在技术和产能变更，政府收购，合并和公司进入方面的价格响应。该算法复制了与显式路径枚举相同的稳定性条件，而与显式路径枚举在2小时内超时相比仅花费了17秒。