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Title: Geographical information systems coupled prediction modelling of road traffic accidents in Brunei
Author: Ladi, Hj Supry Hj Ag
ISNI:       0000 0004 2699 1105
Awarding Body: University of East London
Current Institution: University of East London
Date of Award: 2006
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The analysis of road accident data has led to the development of a number of prediction models to allow testing of road improvement schemes. However, the advances in Information Technology and particularly within the field of Geographical Information Systems (GIS) has enabled it to be linked with applied sciences such as Fluid Mechanics, Highway Design and Traffic Engineering to create a "loosely" to "tightly coupled" GISbased system. Such a system allows correction and simulation tasks to be performed whenever necessary. This approach has been applied to the problem in Brunei where they are at the initial stage towards realising the importance of road-safety research. This work has been proved to contribute tangible benefits for the Brunei road safety authorities. ArcGIS software was used to produce clusters of road accidents along a road and create a road accident database linked with the Brunei road network which form the initial stage of this research. The research develops a new 'Modified Voronoi Process' (MVP) for the identification of accident hotspots along a road. This technique uses a combination of GIS functionalities with Microsoft Excel software. The establishment of a Hotspot Zone dimension (HZD) within the MVP is creative and is very beneficial for Brunei road safety authorities and other researchers. The technique incorporates Brunei road accident hotspot definition established by the author. The final outcome of this research is the development of a GIS-based Road Accident Prediction System and is an innovation and enhancement to the world of road accident prediction system and particularly in Brunei. The system incorporates an external prediction model, which is "tightly coupled" or integrated with a GIS. The coupling enables the prediction to be carried out on a single platform for easy input and computation. The system was tested using accident data acquired from manually recorded 24-hour police reports and statistical software used to analyse the sensitivity of accident locations. The system was also used for a sensitivity analysis of the application of the United States Federal Highway Agency (USFHA) prediction model on a segment of road in Brunei.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available