Use of longitudinal roughness data as a tool for effective maintenance management of gravel roads

dc.contributor.authorMwaipungu, Richard R.
dc.contributor.authorAllopi, D.R. (Dhiren)
dc.contributor.otherSouthern African Transport Conference (30th : 2011 : Pretoria, South Africa)
dc.contributor.otherTransportation Research Board of the National Academies (TRB)
dc.contributor.otherMinister of Transport, South Africa
dc.date.accessioned2011-09-26T12:22:25Z
dc.date.available2011-09-26T12:22:25Z
dc.date.issued2011-07
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 Document Transformation Technologies Postal Address: PO Box 560 Irene 0062 South Africa. Tel.: +27 12 667 2074 Fax: +27 12 667 2766 E-mail: nigel@doctech URL: http://www.doctech.co.zaen_US
dc.description.abstractPaper presented at the 30th Annual Southern African Transport Conference 11-14 July 2011 "Africa on the Move", CSIR International Convention Centre, Pretoria, South Africa.en_US
dc.description.abstractThis paper attempt to define the use of gravel road longitudinal roughness data as a significant input in Gravel Road Management System (GRMS). The data were collected from three gravel roads constructed using marginal materials in Tanzania. Two of them are in the Kilimanjaro Region and one in the Coastal Region. The rates of longitudinal roughness progression of these gravel roads were recorded using vehicle mounted bump rntegrator (VMBI) at 100 metre intervals. These data were later used to locate road sections w~th roughness at or above IRI 14 mlkm for distress survey. Roughness at or above IRI 14 mlkm is specified by the literature as the min~mum above which the gravel roads will begin to show deep depressions and erosion gulley. The correlation between longitudinal roughness and traffic volume for each road was good, and the minimum and maximum threshold at which maintenance should be triggered was set. Recommendations are made to use classified traffic volume data together with longitudinal roughness data in prioritising gravel road maintenance.en_US
dc.description.sponsorshipCD sponsored by TRANSNETen_US
dc.format.extent10 pagesen_US
dc.format.mediumPDFen_US
dc.identifier.citationMwaipungu, RR & Allopi, D 2011, 'The use of longitudinal roughness data as a tool for effective maintenance management of gravel roads.', Paper presented to the 30th Annual Southern African Transport Conference, South Africa, 11-14 July. pp. 55-64en_US
dc.identifier.isbn9781920017514
dc.identifier.urihttp://hdl.handle.net/2263/17296
dc.language.isoenen_US
dc.publisherDocument Transformation Technologiesen_US
dc.relation.ispartofSATC 2011
dc.rightsUniversity of Pretoriaen_US
dc.subjectLongitudinalen_US
dc.subjectGravel roaden_US
dc.subjectKilimanjaro Regionen_US
dc.subjectCoastal Regionen_US
dc.subjectVehicle mounted bump integratoren_US
dc.subject.lcshTransportation
dc.subject.lcshTransportation -- Africaen
dc.subject.lcshTransportation -- Southern Africa
dc.titleUse of longitudinal roughness data as a tool for effective maintenance management of gravel roadsen_US
dc.typePresentationen_US

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