Low-Cost Road Traffic State Estimation System Using Time-Spatial Image Processing

Ekalux Ua-Areemitr, Agachai Sumalee, William H.K. Lam

Research output: Journal article publicationJournal articleAcademic researchpeer-review

3 Citations (Scopus)

Abstract

Road traffic mobility can be described by its Level of Services (LoS). A major challenge in traffic state and LoS estimation is the limitation of observed traffic data. To derive the traffic state of a road network, a sensor network needs to be installed. Most stationary sensing techniques involve high investment in terms of the sensor installation, data communication and computational resources. This paper proposes a low-cost image processing system for road traffic state estimation using time-spatial image (TSI) processing. The TSI is an image processing technique for transforming a series of video images into a single image. Therefore, the TSI can reduce memory resources compared with the traditional methods. A camera can be exploited for traffic-state estimation through integration with TSI generating and processing modules. In addition, traffic state variables such as space-mean-speed, flow and density can be estimated. Empirical results are provided based on several experiments to show that TSI processing is a viable lowcost approach to traffic state estimation.

Original languageEnglish
Article number8742556
Pages (from-to)69-79
Number of pages11
JournalIEEE Intelligent Transportation Systems Magazine
Volume11
Issue number3
DOIs
Publication statusPublished - 1 Sep 2019

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

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