An Improved Macroscopic Modeling for Highway Traffic Density Estimation

Zeroual Abdelhafid; Fouzi Harrou; Ying Sun

doi:10.1109/ICFSP.2018.8552077

An Improved Macroscopic Modeling for Highway Traffic Density Estimation

Zeroual Abdelhafid, Fouzi Harrou, Ying Sun

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

3 Scopus citations

Abstract

Efficient and accurate estimation of traffic density plays an important role in the development of intelligent transportation systems by providing relevant information for rapid decision-making. The purpose of this study is to design a model-based procedure to estimate traffic density. Here, we design an innovative observer that combines the benefits of piecewise switched linear traffic model with Luenberger observer estimator for improving road traffic density estimation. We evaluated the proposed estimator by using traffic data from the four-lane SR-60 freeway in southern California.

Original language	English (US)
Title of host publication	2018 4th International Conference on Frontiers of Signal Processing (ICFSP)
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	135-139
Number of pages	5
ISBN (Print)	9781538678534
DOIs	https://doi.org/10.1109/ICFSP.2018.8552077
State	Published - Nov 30 2018

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): OSR-2015-CRG4-2582
Acknowledgements: This publication is based upon work supported by King Abdullah University of Science and Technology (KAUST), Office of Sponsored Research (OSR) under Award No: OSR-2015-CRG4-2582.

Access to Document

10.1109/ICFSP.2018.8552077

Cite this

@inproceedings{40a682626d00421ab6411f5da12b8801,

title = "An Improved Macroscopic Modeling for Highway Traffic Density Estimation",

abstract = "Efficient and accurate estimation of traffic density plays an important role in the development of intelligent transportation systems by providing relevant information for rapid decision-making. The purpose of this study is to design a model-based procedure to estimate traffic density. Here, we design an innovative observer that combines the benefits of piecewise switched linear traffic model with Luenberger observer estimator for improving road traffic density estimation. We evaluated the proposed estimator by using traffic data from the four-lane SR-60 freeway in southern California.",

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

note = "KAUST Repository Item: Exported on 2020-10-01 Acknowledged KAUST grant number(s): OSR-2015-CRG4-2582 Acknowledgements: This publication is based upon work supported by King Abdullah University of Science and Technology (KAUST), Office of Sponsored Research (OSR) under Award No: OSR-2015-CRG4-2582.",

year = "2018",

month = nov,

day = "30",

doi = "10.1109/ICFSP.2018.8552077",

language = "English (US)",

isbn = "9781538678534",

pages = "135--139",

booktitle = "2018 4th International Conference on Frontiers of Signal Processing (ICFSP)",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

}

TY - GEN

T1 - An Improved Macroscopic Modeling for Highway Traffic Density Estimation

AU - Abdelhafid, Zeroual

AU - Harrou, Fouzi

AU - Sun, Ying

N1 - KAUST Repository Item: Exported on 2020-10-01 Acknowledged KAUST grant number(s): OSR-2015-CRG4-2582 Acknowledgements: This publication is based upon work supported by King Abdullah University of Science and Technology (KAUST), Office of Sponsored Research (OSR) under Award No: OSR-2015-CRG4-2582.

PY - 2018/11/30

Y1 - 2018/11/30

N2 - Efficient and accurate estimation of traffic density plays an important role in the development of intelligent transportation systems by providing relevant information for rapid decision-making. The purpose of this study is to design a model-based procedure to estimate traffic density. Here, we design an innovative observer that combines the benefits of piecewise switched linear traffic model with Luenberger observer estimator for improving road traffic density estimation. We evaluated the proposed estimator by using traffic data from the four-lane SR-60 freeway in southern California.

AB - Efficient and accurate estimation of traffic density plays an important role in the development of intelligent transportation systems by providing relevant information for rapid decision-making. The purpose of this study is to design a model-based procedure to estimate traffic density. Here, we design an innovative observer that combines the benefits of piecewise switched linear traffic model with Luenberger observer estimator for improving road traffic density estimation. We evaluated the proposed estimator by using traffic data from the four-lane SR-60 freeway in southern California.

UR - http://hdl.handle.net/10754/631263

UR - https://ieeexplore.ieee.org/document/8552077

UR - http://www.scopus.com/inward/record.url?scp=85059977279&partnerID=8YFLogxK

U2 - 10.1109/ICFSP.2018.8552077

DO - 10.1109/ICFSP.2018.8552077

M3 - Conference contribution

SN - 9781538678534

SP - 135

EP - 139

BT - 2018 4th International Conference on Frontiers of Signal Processing (ICFSP)

PB - Institute of Electrical and Electronics Engineers (IEEE)

ER -

An Improved Macroscopic Modeling for Highway Traffic Density Estimation

Abstract

Bibliographical note

Access to Document

Other files and links

Fingerprint

Cite this