Vehicle Re-identification for Lane-level Travel Time Estimations on Congested Urban Road Networks Using Video Images

Cheng Zhang, Bi Yu Chen, William H.K. Lam, H. W. Ho, Xiaomeng Shi, Xiaoguang Yang, Wei Ma, S. C. Wong, Andy H.F. Chow

Research output: Journal article publicationJournal articleAcademic researchpeer-review

20 Citations (Scopus)


The provision of lane-level travel time information can enable accurate traffic control and route guidance in urban roads with distinctive traffic conditions among lanes. However, few studies in the literature have been conducted to estimate lane-level travel time distributions. This study proposes a new vehicle re-identification (V-ReID) method for estimating lane-level travel time distributions using video images from widely deployed surveillance cameras. In the proposed method, a lane-based bipartite graph matching is introduced to obtain optimal matches between upstream and downstream vehicles by considering lane-level traffic conditions and vehicles' lane changing behaviors and visual features. A lane-based travel time estimation technique is introduced to real-time estimate full spectrum of lane-level distribution parameters, including not only the mean but also the standard deviation and the distribution type. A comprehensive case study is carried out on a congested urban road in Hong Kong. Results of case study show that the proposed method outperforms the state-of-the-art link-based V-ReID method and is capable for providing accurate lane-level travel time distribution information on congested urban roads.

Original languageEnglish
JournalIEEE Transactions on Intelligent Transportation Systems
Publication statusAccepted/In press - 2021


  • Cameras
  • Detectors
  • Estimation
  • Feature extraction
  • lane-changing behaviors
  • lane-level travel time distributions
  • Roads
  • Standards
  • Vehicle re-identification
  • video images
  • Visualization

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications


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