Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.766796
Title: Quantifying the patterns of road traffic crashes in the Sultanate of Oman : statistical evaluation of aggregate data from police records
Author: Al Aamri, Amira Khamis
ISNI:       0000 0004 7656 3723
Awarding Body: University of Southampton
Current Institution: University of Southampton
Date of Award: 2018
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Abstract:
The alarming growth of Road Traffic Crashes (RTCs) and related outcomes remain an unresolved global public health emergency in low- and middle-income countries. The risks of RTCs are considerably high in the Gulf Cooperation Council (GCC) countries, where the oil-driven economy has overtime sparked rapid economic growth accompanied by large influx of expatriates, rapid urbanisation and unprecedented growth in motor vehicles. Oman has the second highest death rate from RTCs within GCC countries. Although, there is a growing body of peer-reviewed literature on the trends and behavioural characteristics associated with RTCs in Oman, the interactive effects of associated demographic, environmental and spatial factors are not well understood. The higher representation of expatriate population and rapid urbanisation level adds further complexity in understanding and quantifying these risks. The overarching aim of this research is to apply robust statistical techniques to identify and evaluate the social, demographic, spatial and technological factors associated with the likelihood of RTCs and associated outcomes in Oman. Data for the research are drawn from the Royal Oman Police (ROP) National Road Traffic Crashes (NRTC) database which recorded 35,851 cases in aggregate format for the period 2010-2014. In addition, the researcher independently generated the geographical coordinates (latitude and longitude) for the Muscat governorate based on transcripts recorded within the NRTC database and using Google maps, which was then linked to the Muscat road network and statistically validated using the pilot data from iMAAP network based crash analysis system developed by the UK Transport Research Laboratory.
Supervisor: Zhang, Li-Chun Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.766796  DOI: Not available
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