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http://hdl.handle.net/1942/43594
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DC Field | Value | Language |
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dc.contributor.author | Arshi, Abubeker Nemo | - |
dc.contributor.author | Alhajyaseen, Wael | - |
dc.contributor.author | MAMO, Wondwesen | - |
dc.date.accessioned | 2024-08-28T08:07:40Z | - |
dc.date.available | 2024-08-28T08:07:40Z | - |
dc.date.issued | 2024 | - |
dc.date.submitted | 2024-08-09T17:32:57Z | - |
dc.identifier.citation | Procedia Computer Science, 238, p. 159 -166 | - |
dc.identifier.issn | 1877-0509 | - |
dc.identifier.uri | http://hdl.handle.net/1942/43594 | - |
dc.description.abstract | Having accurate road traffic crashes (RTCs) and violations data is essential for establishing more realistic crash and casualty reduction programs. Although crash data commonly suffer from issues of accuracy and comprehensiveness, these factors are often disregarded in crash analyses. This research aims to evaluate the trustworthiness of self-reported RTCs and violations data in relation to actual record data among professional taxi and bus drivers in the state of Qatar. The analysis will account for divergences across socio-demographic features and driver types. A statistical analysis i.e. Wilcoxon signed-rank test was used on the collected data (one year self-reported and two years actual data) of 566 participants, comprising 361 taxi drivers and 206 bus drivers who were employed by Karwa driving school. The results revealed significant differences between self-reported RTCs and traffic violation data and actual records. The accuracy of self-reporting also varies depending on the type of driver and across various socio-demographic categories. The variations observed in the data have significant inferences for the overall reliability of the data and their influence on crash analysis. | - |
dc.description.sponsorship | This conference paper was made possible by the internal grant award [QUST-1-CENG-2024-1779] from Qatar University. The statements made herein are solely the responsibility of the authors. The authors would like to thank Mr. Robert Makondo from Karwa Driving Academy of Mowasalat, and his team for supporting the data collection. | - |
dc.language.iso | en | - |
dc.publisher | - | |
dc.rights | 2024 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the Conference Program Chairs 10.1016/j.procs.2024.06.011 | - |
dc.subject.other | Traffic safety | - |
dc.subject.other | Crash data | - |
dc.subject.other | Reliability | - |
dc.subject.other | Professional drivers | - |
dc.subject.other | Public health | - |
dc.title | Reliability of Self-Reported Road Crash and Violation Data of Professional Drivers: The Case of Qatar | - |
dc.type | Proceedings Paper | - |
local.bibliographicCitation.conferencedate | 2024, April 23 - 24 | - |
local.bibliographicCitation.conferencename | The 15th International Conference on Ambient Systems, Networks and Technologies (ANT) | - |
local.bibliographicCitation.conferenceplace | Hasselt, Belgium | - |
dc.identifier.epage | 166 | - |
dc.identifier.spage | 159 | - |
dc.identifier.volume | 238 | - |
local.bibliographicCitation.jcat | C1 | - |
local.type.refereed | Refereed | - |
local.type.specified | Proceedings Paper | - |
dc.identifier.doi | 10.1016/j.procs.2024.06.011 | - |
dc.identifier.eissn | - | |
local.provider.type | CrossRef | - |
local.uhasselt.international | yes | - |
item.fulltext | With Fulltext | - |
item.accessRights | Open Access | - |
item.contributor | Arshi, Abubeker Nemo | - |
item.contributor | Alhajyaseen, Wael | - |
item.contributor | MAMO, Wondwesen | - |
item.fullcitation | Arshi, Abubeker Nemo; Alhajyaseen, Wael & MAMO, Wondwesen (2024) Reliability of Self-Reported Road Crash and Violation Data of Professional Drivers: The Case of Qatar. In: Procedia Computer Science, 238, p. 159 -166. | - |
crisitem.journal.issn | 1877-0509 | - |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
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Conference proceeding paper.pdf | Published version | 708.79 kB | Adobe PDF | View/Open |
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