Neural Computing and Applications

, Volume 31, Supplement 1, pp 247–258 | Cite as

A novel algorithm for peer-to-peer ridesharing match problem

  • Ruimin Ma
  • Lifei Yao
  • Lijun Song
  • Maozhu JinEmail author
S.I. : Machine Learning Applications for Self-Organized Wireless Networks


Peer-to-peer (P2P) ridesharing is a promising mode of transportation that has gained popularity during the recent years. The widespread use of smart phones, mobile application development platforms and online payment systems provide new opportunities to enable P2P ridesharing. In this paper, we introduce a notion of two-sided matching to build a single-driver multiple-rider stable matching ridesharing model and propose a heuristic algorithm to establish stable or nearly stable matches. We conduct extensive numerical experiments to demonstrate the computational efficiency of the proposed algorithm and show its practical applicability to reasonably sized P2P ridesharing contexts. The results show that we can significantly increase the stability of ridesharing matching solutions at the cost of only a small degradation in system-wide performance.


Peer-to-peer ridesharing Single-driver multiple-rider Stable matches Heuristic algorithm 



The authors acknowledge the Scientific Research Foundation of Guangzhou University (Grant No. 69-18ZX10183), Key Research Project of Sichuan Science and Technology Department (Grant No. 18ZDYF1707).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


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Copyright information

© The Natural Computing Applications Forum 2018

Authors and Affiliations

  1. 1.School of ManagementGuangzhou UniversityGuangzhouChina
  2. 2.Business SchoolSichuan UniversityChengduChina
  3. 3.College of Communication EngineeringChengdu University of Information TechnologyChengduChina

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