Commuter ride-sharing using topology-based vehicle trajectory clustering: Methodology, application and impact evaluation

Zihan Hong, Ying Chen, Hani S. Mahmassani*, Shuang Xu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

22 Scopus citations


This paper illustrates a ride matching method for commuting trips based on clustering trajectories, and a modeling and simulation framework with ride-sharing behaviors to illustrate its potential impact. It proposes data mining solutions to reduce traffic demand and encourage more environment-friendly behaviors. The main contribution is a new data-driven ride-matching method, which tracks personal preferences of road choices and travel patterns to identify potential ride-sharing routes for carpool commuters. Compared with prevalent carpooling algorithms, which allow users to enter departure and destination information for on-demand trips, the proposed method focuses more on regular commuting trips. The potential effectiveness of the approach is evaluated using a traffic simulation-assignment framework with ride-sharing participation using the routes suggested by our algorithm. Two types of ride-sharing participation scenarios, with and without carpooling information, are considered. A case study with the Chicago tested is conducted to demonstrate the proposed framework's ability to support better decision-making for carpool commuters. The results indicate that with ride-matching recommendations using shared vehicle trajectory data, carpool programs for commuters contribute to a less congested traffic state and environment-friendly travel patterns.

Original languageEnglish (US)
Pages (from-to)573-590
Number of pages18
JournalTransportation Research Part C: Emerging Technologies
StatePublished - Dec 2017


  • Data mining
  • Ride-sharing
  • Trajectory clustering
  • Travel demand management

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Automotive Engineering
  • Transportation
  • Computer Science Applications


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