Researchers Bingqing Liu, David Watling, and Joseph Y. J. Chow from the University of California, Davis, and the University of Leeds have delved into the complexities of Mobility-as-a-Service (MaaS) markets, offering a novel approach to model and optimize these systems. Their work, published in the journal Transportation Research Part B: Methodological, introduces a stochastic assignment game framework that could significantly impact the energy industry, particularly in urban mobility and transportation sectors.
The researchers first present general forms of one-to-one and many-to-many stochastic assignment games, discussing optimality conditions and defining the core of these games. They then extend the general stochastic many-to-many assignment game into a stochastic Stackelberg game to model MaaS systems. In this model, the MaaS platform acts as the leader, setting fares to maximize revenue, while users and operators react to these fare settings, forming a stochastic many-to-many assignment game that considers both fixed-route services and Mobility-on-Demand (MOD).
The Stackelberg game is formulated as a bilevel problem, with the lower level being the stochastic many-to-many assignment game between users and operators. This lower level is shown to yield a coalitional logit model. The upper-level problem involves fare adjustment to maximize revenue. To solve these problems, the researchers propose an iterative balancing algorithm for the lower-level problem and an iterative fare adjusting heuristic for the bilevel problem. They demonstrate that the solution of the heuristic is equivalent to the bilevel problem with an additional condition when it converges.
The practical applications of this research for the energy sector are significant. The model can be used to design MaaS fares that maximize the platform’s income while anticipating the selfish behavior and heterogeneity of users and operators. Public agencies can also leverage this model to manage multimodal transportation systems more effectively. By optimizing mobility services, the energy industry can reduce congestion, improve efficiency, and lower emissions, contributing to a more sustainable urban environment.
The researchers conducted two case studies to validate their model, showcasing its potential to revolutionize the way we approach urban mobility and transportation management. This work not only advances the theoretical understanding of stochastic assignment games but also provides a powerful tool for the energy industry to enhance mobility services and achieve broader sustainability goals.
This article is based on research available at arXiv.