Using instrumented motorcycle data to study road factors influencing motorcycle crash risk
Adinegoro, Yusuf (2018) Using instrumented motorcycle data to study road factors influencing motorcycle crash risk. PhD thesis, Queensland University of Technology.
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Yusuf Adinegoro Thesis (PDF 9MB) |
Description
This thesis developed a new methodological framework for studying how road conditions contribute to motorcycle crash risk. Using specific engineering approaches, the data collected by an instrumented motorcycle were transformed into measures of road geometry and road surface quality. Their contributions to crash risk were then examined using an epidemiological case-crossover design. The method was tested using crash and road data from the Gillies Range Road in Northern Queensland.
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| ID Code: | 121454 |
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| Item Type: | QUT Thesis (PhD) |
| Supervisor: | Haworth, Narelle, Bunker, Jonathan, Debnath, Ashim, & Wishart, Darren |
| Keywords: | case-crossover, conditional logistic regression, crash risk, instrumented motorcycle, motorcycle, pavement distress, pavement roughness, single vehicle crashes, sensors, surface defects |
| DOI: | 10.5204/thesis.eprints.121454 |
| Divisions: | Current > Research Centres > Centre for Future Mobility/CARRSQ Past > QUT Faculties & Divisions > Faculty of Health |
| Institution: | Queensland University of Technology |
| Deposited On: | 08 Oct 2018 11:58 |
| Last Modified: | 22 Jan 2025 00:42 |
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