A review of intelligent driving style analysis systems and related artificial intelligence algorithms

dc.contributor.authorMeiring, Gys Albertus Marthinus
dc.contributor.authorMyburgh, Hermanus Carel
dc.contributor.emailherman.myburgh@up.ac.zaen_ZA
dc.date.accessioned2016-02-16T10:32:12Z
dc.date.available2016-02-16T10:32:12Z
dc.date.issued2015-12-04
dc.descriptionG.A.M. Meiring performed this work as part of his Master’s degree in Computer Engineering, under the supervision of H.C. Myburgh. This work is the combination of three research assignments in the form of an exam assignment. Each assignment was thoroughly reviewed and graded by H.C. Myburgh, who also provided detailed feedback, which G.A.M. Meiring incorporated in the final draft. H.C. Myburgh also prepared this manuscript from the exam assignment submitted by G.A.M. Meiring.en_ZA
dc.description.abstractIn this paper the various driving style analysis solutions are investigated. An in-depth investigation is performed to identify the relevant machine learning and artificial intelligence algorithms utilised in current driver behaviour and driving style analysis systems. This review therefore serves as a trove of information, and will inform the specialist and the student regarding the current state of the art in driver style analysis systems, the application of these systems and the underlying artificial intelligence algorithms applied to these applications. The aim of the investigation is to evaluate the possibilities for unique driver identification utilizing the approaches identified in other driver behaviour studies. It was found that Fuzzy Logic inference systems, Hidden Markov Models and Support Vector Machines consist of promising capabilities to address unique driver identification algorithms if model complexity can be reduced.en_ZA
dc.description.librarianam2015en_ZA
dc.description.urihttp://www.mdpi.com/journal/sensorsen_ZA
dc.identifier.citationMeiring, GAM & Myburgh, HC 2015, 'A review of intelligent driving style analysis systems and related artificial intelligence algorithms', Sensors, vol. 15, no. 12, pp. 30653-30682.en_ZA
dc.identifier.issn1424-8220
dc.identifier.other10.3390/s151229822
dc.identifier.urihttp://hdl.handle.net/2263/51413
dc.language.isoenen_ZA
dc.publisherMDPI Publishingen_ZA
dc.rights© 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons by Attribution.en_ZA
dc.subjectDriving styleen_ZA
dc.subjectDriver behaviouren_ZA
dc.subjectArtificial intelligenceen_ZA
dc.subjectMachine learningen_ZA
dc.subjectDriver safetyen_ZA
dc.subjectRoad accidenten_ZA
dc.subjectDriver identificationen_ZA
dc.titleA review of intelligent driving style analysis systems and related artificial intelligence algorithmsen_ZA
dc.typeArticleen_ZA

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