Large-scale congestion analysis using compressed measurements

Maryam Haghighat, Manoj Panda, Hai L. Vu, Hans Van Lint

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review


Traffic congestion is a major concern in metropolitan areas and a quick congestion assessment of large-scale network is required for modern traffic management referred to as Intelligent Transport Systems (ITS). However, ITSs are facing the challenge of real-Time storage, retrieval and processing of a vast amount of collected data over a large-scale network. Compressed sensing (CS) is an efficient technique of sampling high-dimensional data and is successfully used to reconstruct signals via a small set of non-Adaptive, linear measurements. Whilst CS has mainly been applied for data reconstruction, we propose in this paper the use of CS for classification and estimation of some meaningful parameters in the traffic problem. To this end, we develop a novel sensing matrix for congestion analysis and show that for traffic data collected in Melbourne urban network, our CS provides an opportunity to extract the desired information from a small number of random projections. In addition, our method could improve the efficiency of database query and has the ability to deal with missing or defective data.

Original languageEnglish
Title of host publication2016 IEEE 19th International Conference on Intelligent Transportation Systems, ITSC 2016
EditorsDenis Wolf
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages8
ISBN (Electronic)9781509018895
ISBN (Print)9781509018901
Publication statusPublished - 22 Dec 2016
Externally publishedYes
EventIEEE Conference on Intelligent Transportation Systems 2016 - Sheraton Rio Hotel & Resort, Rio de Janeiro, Brazil
Duration: 1 Nov 20164 Nov 2016
Conference number: 19th (Proceedings) (Website)


ConferenceIEEE Conference on Intelligent Transportation Systems 2016
Abbreviated titleITSC 2016
CityRio de Janeiro
Internet address


  • Compressed sensing (CS)
  • Intelligent transport systems (ITSS)
  • Traffic congestion

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