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

dc.contributor.authorMuronga, K.
dc.contributor.authorVenter, K.
dc.contributor.coadvisor
dc.contributor.otherSouthern African Transport Conference (33rd : 2014 : Pretoria, South Africa)
dc.contributor.otherMinister of Transport, South Africa
dc.date.accessioned2015-06-18T07:51:58Z
dc.date.available2015-06-18T07:51:58Z
dc.date.created2014
dc.date.issued2014
dc.descriptionThis 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.zaen_ZA
dc.description.abstractPaper 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.abstractNaturalistic 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.extent8 pagesen_ZA
dc.identifier.citationMuronga, 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.isbn978-1-920017-61-3
dc.identifier.urihttp://hdl.handle.net/2263/45534
dc.language.isoenen_ZA
dc.rightsUniversity of Pretoriaen_ZA
dc.subjectNaturalistic drivingen_ZA
dc.subjectTraffic managementen_ZA
dc.subjectData collectionen_ZA
dc.titleNaturalistic driving data : managing and working with large databases for road and traffic management researchen_ZA
dc.typePresentationen_ZA

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