An efficient statistical-based approach for road traffic congestion monitoring

Handle URI:
http://hdl.handle.net/10754/626958
Title:
An efficient statistical-based approach for road traffic congestion monitoring
Authors:
Abdelhafid, Zeroual; Harrou, Fouzi; Sun, Ying ( 0000-0001-6703-4270 )
Abstract:
In this paper, we propose an effective approach which has to detect traffic congestion. The detection strategy is based on the combinational use of piecewise switched linear traffic (PWSL) model with exponentially-weighted moving average (EWMA) chart. PWSL model describes traffic flow dynamics. Then, PWSL residuals are used as the input of EWMA chart to detect traffic congestions. The evaluation results of the developed approach using data from a portion of the I210-W highway in Califorina showed the efficiency of the PWSL-EWMA approach in in detecting traffic congestions.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Applied Mathematics and Computational Science Program
Citation:
Abdelhafid Z, Harrou F, Sun Y (2017) An efficient statistical-based approach for road traffic congestion monitoring. 2017 5th International Conference on Electrical Engineering - Boumerdes (ICEE-B). Available: http://dx.doi.org/10.1109/ICEE-B.2017.8192228.
Publisher:
IEEE
Journal:
2017 5th International Conference on Electrical Engineering - Boumerdes (ICEE-B)
KAUST Grant Number:
OSR-2015-CRG4-2582
Issue Date:
14-Dec-2017
DOI:
10.1109/ICEE-B.2017.8192228
Type:
Conference Paper
Sponsors:
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.
Additional Links:
http://ieeexplore.ieee.org/document/8192228/
Appears in Collections:
Conference Papers; Applied Mathematics and Computational Science Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorAbdelhafid, Zeroualen
dc.contributor.authorHarrou, Fouzien
dc.contributor.authorSun, Yingen
dc.date.accessioned2018-02-01T07:24:59Z-
dc.date.available2018-02-01T07:24:59Z-
dc.date.issued2017-12-14en
dc.identifier.citationAbdelhafid Z, Harrou F, Sun Y (2017) An efficient statistical-based approach for road traffic congestion monitoring. 2017 5th International Conference on Electrical Engineering - Boumerdes (ICEE-B). Available: http://dx.doi.org/10.1109/ICEE-B.2017.8192228.en
dc.identifier.doi10.1109/ICEE-B.2017.8192228en
dc.identifier.urihttp://hdl.handle.net/10754/626958-
dc.description.abstractIn this paper, we propose an effective approach which has to detect traffic congestion. The detection strategy is based on the combinational use of piecewise switched linear traffic (PWSL) model with exponentially-weighted moving average (EWMA) chart. PWSL model describes traffic flow dynamics. Then, PWSL residuals are used as the input of EWMA chart to detect traffic congestions. The evaluation results of the developed approach using data from a portion of the I210-W highway in Califorina showed the efficiency of the PWSL-EWMA approach in in detecting traffic congestions.en
dc.description.sponsorshipThe 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.en
dc.publisherIEEEen
dc.relation.urlhttp://ieeexplore.ieee.org/document/8192228/en
dc.subjectComputational modelingen
dc.subjectData modelsen
dc.subjectDensity measurementen
dc.subjectMonitoringen
dc.subjectRoadsen
dc.subjectVehicle dynamicsen
dc.titleAn efficient statistical-based approach for road traffic congestion monitoringen
dc.typeConference Paperen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.contributor.departmentApplied Mathematics and Computational Science Programen
dc.identifier.journal2017 5th International Conference on Electrical Engineering - Boumerdes (ICEE-B)en
dc.contributor.institutionLAIG Laboratory, University of 08 May 1945, Guelma 24000, Algeria CReSTIC, university of Reims Champagne-ardenne, Franceen
kaust.authorHarrou, Fouzien
kaust.authorSun, Yingen
kaust.grant.numberOSR-2015-CRG4-2582en
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