Ride-pooling is widely recognized as a sustainable way to ease congestion, reduce costs and cut emissions, yet adoption remains limited. When operators act independently, efficiency is low because requests cannot be matched across platforms. Aggregation platforms seek to improve this by forcing all operators into a permanent coalition, but differences in size, cost and market position make such arrangements unstable. To address this, researchers from Beihang University and Delft University of Technology developed a multi-level coalition formation game framework that enables coalitions to form dynamically in response to trip requests, allowing flexible cooperation without requiring all operators to remain in a single group at all times.
The team published their study in Communications in Transportation Research on November 15, 2025.
Despite its many advantages, ride-pooling accounts for less than 30 percent of taxi trips in many Chinese cities. The main barrier is low matching efficiency: many requests cannot be combined into feasible passenger groups, and successful matches often involve long detours and suboptimal routes, reducing cost savings and discouraging passengers.
"A natural and dramatic solution," says Yaotian Tan, the principal investigator, "is that aggregation platforms such as Amap have begun to enable cross-operator ride-pooling by forming city-wide coalitions." Although this improves overall efficiency, it raises long-term stability concerns: heterogeneous fleet sizes, market shares and cost structures make it difficult to guarantee sustained benefits for all participants.
A multi-level coalition framework
The new framework tackles this dilemma by modeling the decision processes of both operators and passengers. It shows how coalitions can form dynamically, how orders and revenues can be allocated, and how stable outcomes can be sustained even in competitive and fragmented markets.
"To verify the applicability of this method in different contexts, we selected three representative Chinese cities—Ningxia, Chengdu and Haikou," Tan explains. "They reflect diverse regional and demand characteristics, especially in trip distance distributions." The results show that the framework consistently improves vehicle utilization, reduces travel costs and fosters cooperation that participants are willing to maintain.
Looking ahead
"This balance between efficiency and stability is crucial if ride-pooling is to deliver its social and environmental benefits," Tan says. Aoyong Li, associate professor at Beihang University, adds: "We hope this research can lay the groundwork for the next generation of aggregation platforms, helping them design flexible cooperation models that are both effective and sustainable."
The above research is published in Communications in Transportation Research (COMMTR), which is a fully open access journal co-published by Tsinghua University Press and Elsevier. COMMTR publishes peer-reviewed high-quality research representing important advances of significance to emerging transport systems. COMMTR is also among the first transportation journals to make the Replication Package mandatory to facilitate researchers, practitioners, and the general public in understanding and advancing existing knowledge. At its discretion, Tsinghua University Press will pay the open access fee for all published papers in 2025.
About Communications in Transportation Research
Communications in Transportation Research was launched in 2021, with academic support provided by Tsinghua University and China Intelligent Transportation Systems Association. The Editors-in-Chief are Professor Xiaobo Qu, a member of the Academia Europaea from Tsinghua University and Professor Shuai'an Wang from Hong Kong Polytechnic University. The journal mainly publishes high-quality, original research and review articles that are of significant importance to emerging transportation systems, aiming to serve as an international platform for showcasing and exchanging innovative achievements in transportation and related fields, fostering academic exchange and development between China and the global community.
It has been indexed in SCIE, SSCI, Ei Compendex, Scopus, CSTPCD, CSCD, OAJ, DOAJ, TRID and other databases. It was selected as Q1 Top Journal in the Engineering and Technology category of the Chinese Academy of Sciences (CAS) Journal Ranking List. In 2022, it was selected as a High-Starting-Point new journal project of the "China Science and Technology Journal Excellence Action Plan". In 2024, it was selected as the Support the Development Project of "High-Level International Scientific and Technological Journals". The same year, it was also chosen as an English Journal Tier Project of the "China Science and Technology Journal Excellence Action Plan Phase Ⅱ". In 2024, it received the first impact factor (2023 IF) of 12.5, ranking Top1 (1/58, Q1) among all journals in "TRANSPORTATION" category. In 2025, its 2024 IF was announced as 14.5, maintaining the Top 1 position (1/61, Q1) in the same category. Tsinghua University Press will cover the open access fee for all published papers in 2025.
