Mechanism design for Mobility-as-a-Service platform considering travelers’ strategic behavior and multidimensional requirements

Abstract

Mobility-as-a-Service (MaaS) is an emerging transport model which provides access to a combination of travel modes through a single platform. A MaaS operator sits between travelers and transport service providers (TSPs), acting as a broker who purchases mobility resources from individual TSPs, constructs seamless transport services, and then sells them to travelers in response to their demand. To ensure the sustainability of such platforms, the key challenge lies in matching travelers to TSPs so that travelers’ individual needs are satisfied, TSPs gain nonnegative profits and system efficiency is achieved. To solve this matching and pricing problem, travelers’ truthful valuations and travel requirements are needed, while such information is usually unknown to operators beforehand. In this study, we develop an auction-based online mobility resource allocation and pricing mechanism to solve this problem, taking into account travelers’ strategic behavior. We first propose an offline (static) mechanism using a Vickrey–Clarke–Groves (VCG) based pricing scheme to ensure incentive compatibility, individual rationality, and system efficiency. We then develop an online mechanism based on the dynamic learning algorithm to obtain the near-optimal solution and compare it to a customized greedy based algorithm. We compare both online mechanisms to the offline VCG based mechanism and theoretically prove the competitive ratios. The efficiency and performance of the proposed mechanisms are demonstrated through a numerical study.