Naturalistic driving data : managing and working with large databases for road and traffic management research

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dc.contributor.author Muronga, K.
dc.contributor.author Venter, K.
dc.contributor.coadvisor
dc.contributor.other Southern African Transport Conference (33rd : 2014 : Pretoria, South Africa)
dc.contributor.other Minister of Transport, South Africa
dc.date.accessioned 2015-06-18T07:51:58Z
dc.date.available 2015-06-18T07:51:58Z
dc.date.created 2014
dc.date.issued 2014
dc.description This paper was transferred from the original CD ROM created for this conference. The material was published using Adobe Acrobat 10.1.0 Technology. The original CD ROM was produced by CE Projects cc. Postal Address: PO Box 560 Irene 0062 South Africa. Tel.: +27 12 667 2074 Fax: +27 12 667 2766 E-mail: proceedings@ceprojects.co.za en_ZA
dc.description.abstract Paper presented at the 33rd Annual Southern African Transport Conference 7-10 July 2014 "Leading Transport into the Future", CSIR International Convention Centre, Pretoria, South Africa. en_ZA
dc.description.abstract Naturalistic driving and field operational tests are used worldwide to collect data from drivers in order to better understand the human, vehicle and environment interactions. The fairly new methodology has already provided great insight into numerous driver behaviours that could previously not be observed directly. The data is collected with a data acquisition system which is installed in the vehicle. This system consists of cameras facing the driver (and passengers) as well as cameras facing outward. An on-board computer is installed in the vehicle and collects information about the vehicle. This information includes satellite positions, data and time as well as speed and acceleration and deceleration data. The system collects large volumes of data and the challenge is to manage this data efficiently as currently the datasets take-up much storage space, are in different formats necessitating that different software programs be used to download, transcribe and analyse the data. This paper provides an overview of the challenges experienced while working with these large data sets as well as some of the possible solutions identified. The findings and recommendations from this study should prove useful to other researchers and practitioners interested in working with naturalistic data. en_ZA
dc.format.extent 8 pages en_ZA
dc.identifier.citation Muronga, K & Venter, K 2014, "Naturalistic driving data : managing and working with large databases for road and traffic management research", Paper presented at the 33rd Annual Southern African Transport Conference 7-10 July 2014 "Leading Transport into the Future", CSIR International Convention Centre, Pretoria, South Africa. en_ZA
dc.identifier.isbn 978-1-920017-61-3
dc.identifier.uri http://hdl.handle.net/2263/45534
dc.language.iso en en_ZA
dc.rights University of Pretoria en_ZA
dc.subject Naturalistic driving en_ZA
dc.subject Traffic management en_ZA
dc.subject Data collection en_ZA
dc.title Naturalistic driving data : managing and working with large databases for road and traffic management research en_ZA
dc.type Presentation en_ZA


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