Vehicle reidentification with self-adaptive time windows for real-time travel time estimation

Jiankai Wang, Nakorn Indra-Payoong, Agachai Sumalee, Sakda Panwai

Research output: Journal article publicationJournal articleAcademic researchpeer-review

15 Citations (Scopus)

Abstract

This paper proposes a vehicle reidentification (VRI) system with self-adaptive time windows to estimate the mean travel time for each time period on the freeway under traffic demand and supply uncertainty. To capture the traffic dynamics in real-time application, interperiod adjusting based on the exponential smoothing technique is introduced to define an appropriate time-window constraint for the VRI system. In addition, an intraperiod adjusting technique is also employed to handle the nonpredictable traffic congestion. To further reduce the negative effect caused by the mismatches, a postprocessing technique, including thresholding and stratified sampling, is performed on the travel time data derived from the VRI system. Several representative tests are carried out to evaluate the performance of the proposed VRI against potential changes in traffic conditions, e.g., recurrent traffic congestion, freeway bottlenecks, and traffic incidents. The results show that this method can perform well under traffic demand and supply uncertainty.
Original languageEnglish
Article number6648450
Pages (from-to)540-552
Number of pages13
JournalIEEE Transactions on Intelligent Transportation Systems
Volume15
Issue number2
DOIs
Publication statusPublished - 1 Jan 2014

Keywords

  • Stratified sampling
  • time window
  • travel time estimation
  • vehicle reidentification (VRI)
  • video image processing (VIP) systems

ASJC Scopus subject areas

  • Automotive Engineering
  • Computer Science Applications
  • Mechanical Engineering

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