An Improved Macroscopic Modeling for Highway Traffic Density Estimation

Zeroual Abdelhafid, Fouzi Harrou, Ying Sun

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

3 Scopus citations


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 languageEnglish (US)
Title of host publication2018 4th International Conference on Frontiers of Signal Processing (ICFSP)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages5
ISBN (Print)9781538678534
StatePublished - 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.


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