Traffic congestion detection based on hybrid observer and GLR test

Fouzi Harrou; Abdelhafid Zeroual; Ying Sun

doi:10.23919/ACC.2018.8431387

Traffic congestion detection based on hybrid observer and GLR test

Fouzi Harrou, Abdelhafid Zeroual, Ying Sun

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

10 Scopus citations

Abstract

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 language	English (US)
Title of host publication	2018 Annual American Control Conference, ACC 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	604-609
Number of pages	6
ISBN (Print)	9781538654286
DOIs	https://doi.org/10.23919/ACC.2018.8431387
State	Published - Aug 9 2018
Event	2018 Annual American Control Conference, ACC 2018 - Milwauke, United States Duration: Jun 27 2018 → Jun 29 2018

Publication series

Name	Proceedings of the American Control Conference
Volume	2018-June
ISSN (Print)	0743-1619

Conference

Conference	2018 Annual American Control Conference, ACC 2018
Country/Territory	United States
City	Milwauke
Period	06/27/18 → 06/29/18

Bibliographical note

Publisher Copyright:
© 2018 AACC.

ASJC Scopus subject areas

Electrical and Electronic Engineering

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.23919/ACC.2018.8431387

Cite this

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title = "Traffic congestion detection based on hybrid observer and GLR test",

abstract = "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.",

author = "Fouzi Harrou and Abdelhafid Zeroual and Ying Sun",

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doi = "10.23919/ACC.2018.8431387",

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Harrou, F, Zeroual, A & Sun, Y 2018, Traffic congestion detection based on hybrid observer and GLR test. in 2018 Annual American Control Conference, ACC 2018., 8431387, Proceedings of the American Control Conference, vol. 2018-June, Institute of Electrical and Electronics Engineers Inc., pp. 604-609, 2018 Annual American Control Conference, ACC 2018, Milwauke, United States, 06/27/18. https://doi.org/10.23919/ACC.2018.8431387

Traffic congestion detection based on hybrid observer and GLR test. / Harrou, Fouzi; Zeroual, Abdelhafid; Sun, Ying.
2018 Annual American Control Conference, ACC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 604-609 8431387 (Proceedings of the American Control Conference; Vol. 2018-June).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - 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.

AB - 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.

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Traffic congestion detection based on hybrid observer and GLR test

Abstract

Publication series

Conference

Bibliographical note

ASJC Scopus subject areas

UN SDGs

Access to Document

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