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Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/29285
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dc.contributor.authorChetcuti Zammit, Luana-
dc.contributor.authorFabri, Simon G.-
dc.contributor.authorScerri, Kenneth-
dc.date.accessioned2018-04-18T06:41:13Z-
dc.date.available2018-04-18T06:41:13Z-
dc.date.issued2017-
dc.identifier.citationZammit, L. C., Fabri, S. G., & Scerri, K. (2017). Online state and multidimensional parameter estimation for a macroscopic model of a traffic junction. 20th International Conference on Intelligent Transportation Systems (ITSC), Yokohama. 1-6.en_GB
dc.identifier.urihttps://www.um.edu.mt/library/oar//handle/123456789/29285-
dc.description.abstractAn online multidimensional self-estimation algorithm is developed to jointly estimate the parameters of a macroscopic model describing the traffic dynamics in a signalized junction under different traffic conditions, together with the state variables characterising traffic flow. The proposed novel methodology is based on the Expectation-Maximization algorithm and multidimensional Robbins-Monro stochastic approximation. The algorithm is validated on the geometry of a signalized 3-arm junction within the traffic network of Malta resulting in a mean percentage error of -0.965% on the parameter estimates. This is aimed to form part of an adaptive control loop for traffic light systems that is able to autonomously adjust to changing traffic conditions.en_GB
dc.language.isoenen_GB
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_GB
dc.rightsinfo:eu-repo/semantics/restrictedAccessen_GB
dc.subjectExpectation-maximization algorithmsen_GB
dc.subjectTraffic engineering -- Data processingen_GB
dc.subjectIntelligent transportation systemsen_GB
dc.titleOnline state and multidimensional parameter estimation for a macroscopic model of a traffic junctionen_GB
dc.typeconferenceObjecten_GB
dc.rights.holderThe copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holderen_GB
dc.bibliographicCitation.conferencename20th International Conference on Intelligent Transportation Systems (ITSC)en_GB
dc.bibliographicCitation.conferenceplaceYokohama, Japan, 16-19/10/2017en_GB
dc.description.reviewedpeer-revieweden_GB
dc.identifier.doi10.1109/ITSC.2017.8317685-
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