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Appending GPS traces with road grade data to estimate driver behaviour risk

Dissertation (MEng (Industrial Engineering))--University of Pretoria, 2021.

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Other Authors: Joubert, Johan W.
Format: Thesis
Language:English
Published: University of Pretoria 2021
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access_status_str Open Access
author2 Joubert, Johan W.
author_browse Joubert, Johan W.
author_facet Joubert, Johan W.
collection Thesis
dc_rights_str_mv © 2019 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria.
description Dissertation (MEng (Industrial Engineering))--University of Pretoria, 2021.
format Thesis
id oai:repository.up.ac.za:2263/81179
institution University of Pretoria (South Africa)
language English
last_indexed 2026-06-10T12:37:54.123Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository
publishDate 2021
publishDateRange 2021
publishDateSort 2021
publisher University of Pretoria
publisherStr University of Pretoria
record_format dspace
source_str UPSpace — University of Pretoria Institutional Repository
spelling oai:repository.up.ac.za:2263/81179 Appending GPS traces with road grade data to estimate driver behaviour risk Joubert, Johan W. jmariehugo@gmail.com Hugo, Jeanne-Marie UCTD BIR890 Dissertation (MEng (Industrial Engineering))--University of Pretoria, 2021. Road gradients have various impacts when it comes to the performance of a vehicle and its driver. Literature shows how steep grades can cause an increase in emission rates and accident rates, but the actual behaviour and risk of a driver on different road grades are neglected. To find reliable road grade values to use with a behavioural model, this dissertation proposes a smoothing method to be used on the elevation pro le of a freely available Digital Elevation Model, namely the 1 Arc second Shuttle Radar Topography Mission dataset. A behavioural model from literature is used to determine the risk of the drivers within an accelerometer dataset from 45 trucks for a day's travel, using all the records and not only those that fall within certain thresholds of harsh events. The model also allows for road grade to be added as a contextual variable, where records are filtered on fi ve different grade categories ranging from steep downhill to steep uphill roads. These categories each have their own risk space and ranking of driving performance. The majority of drivers have relative constant rankings, but the results show that some drivers behave differently with changes in gradient. Therefore, road grade can influence the behaviour of drivers and can be a useful addition to de fining and understanding the risk of a driver. Industrial and Systems Engineering MEng (Industrial Engineering) Unrestricted 2021-08-05T13:55:08Z 2021-08-05T13:55:08Z 2021 2021 Dissertation * S2021 http://hdl.handle.net/2263/81179 en © 2019 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. application/pdf University of Pretoria
spellingShingle UCTD
BIR890
Appending GPS traces with road grade data to estimate driver behaviour risk
title Appending GPS traces with road grade data to estimate driver behaviour risk
title_full Appending GPS traces with road grade data to estimate driver behaviour risk
title_fullStr Appending GPS traces with road grade data to estimate driver behaviour risk
title_full_unstemmed Appending GPS traces with road grade data to estimate driver behaviour risk
title_short Appending GPS traces with road grade data to estimate driver behaviour risk
title_sort appending gps traces with road grade data to estimate driver behaviour risk
topic UCTD
BIR890
url http://hdl.handle.net/2263/81179