LANE-BASED TRAVEL TIME ESTIMATION FOR MULTIPLE VEHICLE TYPES: A VEHICLE REIDENTIFICATION APPROACH

Cheng Zhang, H. W. Ho, William H.K. Lam, Wei Ma, S. C. Wong, Andy H.F. Chow

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

Travel time are crucial information for route guidance and traffic management. On urban roads with many lane-changing movements, different types of vehicles will have different traveling speeds and the traffic conditions of different lanes are not the same. However, little attention has been given to estimate travel times for different types of vehicles traveling on different lanes. This paper proposed a lane-based travel time estimation for multiple vehicle types through the matching of low-resolution vehicle images from surveillance cameras. Vehicle size and high-dimensional deep-learning features are extracted from vehicle images for vehicle classification. Lane-based bipartite graph matching technique, which based on matching probabilities estimated from vehicle features, are adopted to reidentify vehicles. Case study is conducted on a congested four-lane urban road in Hong Kong, and the results shows that the proposed model generally give an accurate estimation of travel times for different types of vehicles traveling on different lanes.

Original languageEnglish
Title of host publicationProceedings of the 25th International Conference of Hong Kong Society for Transportation Studies, HKSTS 2021
Subtitle of host publicationSustainable Mobility
EditorsRyan C.P. Wong, Jiangping Zhou, W.Y. Szeto
PublisherHong Kong Society for Transportation Studies Limited
Pages2-10
Number of pages9
ISBN (Electronic)9789881581495
Publication statusPublished - Dec 2021
Event25th International Conference of Hong Kong Society for Transportation Studies: Sustainable Mobility, HKSTS 2021 - Hong Kong, Hong Kong
Duration: 9 Dec 202110 Dec 2021

Publication series

NameProceedings of the 25th International Conference of Hong Kong Society for Transportation Studies, HKSTS 2021: Sustainable Mobility

Conference

Conference25th International Conference of Hong Kong Society for Transportation Studies: Sustainable Mobility, HKSTS 2021
Country/TerritoryHong Kong
CityHong Kong
Period9/12/2110/12/21

Keywords

  • Lane-based travel time
  • Vehicle re-identification
  • Vehicle type
  • Video images

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Civil and Structural Engineering
  • Building and Construction
  • Transportation

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