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Arrival flow profile estimation and prediction for urban arterials using license plate recognition data

  • Hao Wu
  • , Jiarong Yao
  • , Peizhe Kang
  • , Chaopeng Tan
  • , Yang Cai
  • , Junjie Zhou
  • , Edward Chung
  • , Keshuang Tang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

Arrival flow profiles enable precise assessment of urban arterial dynamics and support signal control optimization. License plate recognition (LPR) data, with comprehensive coverage and event-based detection, are promising for reconstructing arrival flow profiles. This paper presents an arrival flow profile estimation and prediction method for urban arterials using LPR data. Unlike conventional methods assuming traffic homogeneity and ignoring wave features and signal timing impacts, our approach employs a time partition algorithm and platoon dispersion model to compute arrival flow using only boundary data. Shockwave theory defines the piecewise relation between arrival flow and profile. We further derive the link between arrival flow profiles and traffic dissipation at downstream intersections, enabling recursive estimation across all intersections. The method also predicts arrival flow profiles under various signal timing schemes. Validation through simulation and empirical cases demonstrates its robustness and reliable performance.

Original languageEnglish
Article number2585060
JournalTransportmetrica B
Volume13
Issue number1
DOIs
Publication statusPublished - Nov 2025

Keywords

  • arrival flow profile
  • license plate recognition (LPR) data
  • platoon dispersion
  • shockwave reconstruction
  • Signalized arterials

ASJC Scopus subject areas

  • Software
  • Modelling and Simulation
  • Transportation

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