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dc.contributor.authorUglanov, A.
dc.contributor.authorKartashev, K.
dc.contributor.authorCampean, I. Felician
dc.contributor.authorDoikin, Aleksandr
dc.contributor.authorAbdullatif, Amr R.A.
dc.contributor.authorAngiolini, E.
dc.contributor.authorLin, C.
dc.contributor.authorZhang, Q.
dc.date.accessioned2021-12-10T17:22:41Z
dc.date.accessioned2021-12-21T14:39:22Z
dc.date.available2021-12-10T17:22:41Z
dc.date.available2021-12-21T14:39:22Z
dc.date.issued2022
dc.identifier.citationUglanov A, Kartashev K, Campean IF et al (2022) Driver Behaviour Modelling: Travel Prediction Using Probability Density Function. In: Jansen T, Jensen R, Mac Parthaláin N et al (eds) Advances in Computational Intelligence Systems. UKCI 2021. Advances in Intelligent Systems and Computing. Springer, Cham. 1409: 545-556.en_US
dc.identifier.urihttp://hdl.handle.net/10454/18692
dc.descriptionNoen_US
dc.description.abstractThis paper outlines the current challenges of driver behaviour modelling for real-world applications and presents the novel method to identify the pattern of usage to predict upcoming journeys in probability sense. The primary aim is to establish similarity between observed behaviour of drivers resulting in the ability to cluster them and deploy control strategies based on contextual intelligence and datadriven approach. The proposed approach uses the probability density function (PDF) driven by kernel density estimation (KDE) as a probabilistic approach to predict the type of the upcoming journey, expressed as duration and distance. Using the proposed method, the mathematical formulation and programming algorithm procedure have been indicated in detail, while the case study examples with the data visualisation are given for algorithm validation in simulation.en_US
dc.language.isoenen_US
dc.relation.isreferencedbyhttps://doi.org/10.1007/978-3-030-87094-2_48en_US
dc.subjectDriver behaviour modellingen_US
dc.subjectProbability density functionen_US
dc.subjectKernel density estimationen_US
dc.subjectProbabilistic predictionsen_US
dc.titleDriver Behaviour Modelling: Travel Prediction Using Probability Density Functionen_US
dc.status.refereedYesen_US
dc.date.Accepted2021-09-10
dc.contributor.sponsoraiR-FORCE project, funded as Proof of Concept by the Institute of Digital Engineering
dc.date.application2021-11-18
dc.typeConference paperen_US
dc.type.versionNo full-text in the repositoryen_US
dc.date.updated2021-12-10T17:22:43Z
refterms.dateFOA2021-12-21T14:39:49Z
dc.openaccess.statusclosedAccessen_US


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