A review of intelligent driving style analysis systems and related artificial intelligence algorithms
| dc.contributor.author | Meiring, Gys Albertus Marthinus | |
| dc.contributor.author | Myburgh, Hermanus Carel | |
| dc.contributor.email | herman.myburgh@up.ac.za | en_ZA |
| dc.date.accessioned | 2016-02-16T10:32:12Z | |
| dc.date.available | 2016-02-16T10:32:12Z | |
| dc.date.issued | 2015-12-04 | |
| dc.description | G.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.abstract | In 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.librarian | am2015 | en_ZA |
| dc.description.uri | http://www.mdpi.com/journal/sensors | en_ZA |
| dc.identifier.citation | Meiring, 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.issn | 1424-8220 | |
| dc.identifier.other | 10.3390/s151229822 | |
| dc.identifier.uri | http://hdl.handle.net/2263/51413 | |
| dc.language.iso | en | en_ZA |
| dc.publisher | MDPI Publishing | en_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.subject | Driving style | en_ZA |
| dc.subject | Driver behaviour | en_ZA |
| dc.subject | Artificial intelligence | en_ZA |
| dc.subject | Machine learning | en_ZA |
| dc.subject | Driver safety | en_ZA |
| dc.subject | Road accident | en_ZA |
| dc.subject | Driver identification | en_ZA |
| dc.title | A review of intelligent driving style analysis systems and related artificial intelligence algorithms | en_ZA |
| dc.type | Article | en_ZA |