Traffic congestion detection based on hybrid observer and GLR test

Fouzi Harrou, Abdelhafid Zeroual, Ying Sun

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations


This paper introduces an effective approach for detecting road traffic congestion. This approach uses a hybrid observer (HO) that exploits both the flexibility and simplicity of the piecewise switched linear model to estimate the traffic density parameter and employs a generalized likelihood ratio (GLR) test to detect traffic congestion. We evaluated the HO-GLR with real data from a segment of the four-lane State Route 60 (SR-60) highway in southern California. Results show that the HO-GLR approach is suitable for traffic congestion monitoring.
Original languageEnglish (US)
Title of host publication2018 Annual American Control Conference (ACC)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages6
ISBN (Print)9781538654286
StatePublished - Aug 17 2018

Bibliographical note

KAUST Repository Item: Exported on 2020-12-16
Acknowledged KAUST grant number(s): OSR-2015-CRG4-2582
Acknowledgements: The research reported in this publication was supported by funding from King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award No: OSR-2015-CRG4-2582.


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