Road accident analysis factors

The problem of road accident is increasing in developing countries. A matter of research has been and is being committed to this topic, as a search of past and current research shows. Road accidents in developing countries have progressed over the last ten years. This could be because of increasing...

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Main Author:	Esmaeeli, Hamed
Format:	Thesis
Language:	English
Published:	2010
Subjects:	HE Transportation and Communications
Online Access:	http://eprints.utm.my/id/eprint/11157/4/HamedEsmaeeliMFKA2010.pdf
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id	my-utm-ep.11157
record_format	uketd_dc
spelling	my-utm-ep.111572017-09-27T04:05:40Z Road accident analysis factors 2010-04 Esmaeeli, Hamed HE Transportation and Communications TE Highway engineering. Roads and pavements The problem of road accident is increasing in developing countries. A matter of research has been and is being committed to this topic, as a search of past and current research shows. Road accidents in developing countries have progressed over the last ten years. This could be because of increasing vehicle occupancy over time or to the fact that a particular type of accident is much more common now than was the case ten years ago. For instance commercial vehicles are currently used to transport workers to and from their places of their work. When such a vehicle is involved in an accident, large numbers of mortalities often occur. This report investigates the modelling and implementation of a coordination system within a simulation environment to foresee future accident rate. The approach of analysis used must be correspondingly robust and objective to evaluate accident rate. To comparing changes in car ownership, we hope to use these data to investigate the factors behind these changes. Some examples are the effect of income, changes in employment, changing household structure and changes in residential and work location. They should not be too sensitive to departures from model assumptions or the presence of a substantial number of outliers. Given the polluted nature of the data, ordinary least squares regression is not suitable, therefore, robust regression techniques are recommended. 2010-04 Thesis http://eprints.utm.my/id/eprint/11157/ http://eprints.utm.my/id/eprint/11157/4/HamedEsmaeeliMFKA2010.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Civil Engineering Faculty of Civil Engineering [1] Arrowsmith, DK and Place, CM, (1992). “Dynamical Systems”, Chapman & Hall , 1992). [2] Banister D., Bayliss D. (1992), Structural changes in population and impact on passenger transport, ECMT Round table 88, Paris: OECD. [3] CURRIE, G. & SENBERGS, Z. (2007) Exploring Forced Car Ownership in Metropolitan Melbourne. 30th Australasian Transport Research Forum. Melbourne, ATRF. [4] Victoria Transport Policy Institute,( 2007) [5] WADHWA, L. C. (1986) Urban household car ownership in Australia. Australasian Transportation Research Forum. Darwin. [6] Yohai, V.J. (1987), “High Breakdown and High Efficiency Robust Estimates for Regression”, [7] Final Report on the Factors that Influence Owners? Decisions when they Scrap Cars and HGVs Report for Department of Environment, Transport and the Regions. Institute for Transport Studies University of Leeds and Hague Consulting Group (2002?) (unpublished) [8] Motor vehicle stocks, scrappage, and sales. Greenspan A.; Cohen D. The Review of Economics and Statistics, 1 August 1999, [9] Audit of Car Ownership Models, Gerard de Jong et al. prepared by RAND Report no. 01192 2002 for Transport Research Centre of the Netherlands Ministry of Transport. [10] Income Distribution, Australia, 1995-96 (cat. no. 6523.0) [11] S-Plus 2000 Guide to Statistics vol. 1” 1999 [12] Fan J. and Gijbels I.1996
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	HE Transportation and Communications HE Transportation and Communications
spellingShingle	HE Transportation and Communications HE Transportation and Communications Esmaeeli, Hamed Road accident analysis factors
description	The problem of road accident is increasing in developing countries. A matter of research has been and is being committed to this topic, as a search of past and current research shows. Road accidents in developing countries have progressed over the last ten years. This could be because of increasing vehicle occupancy over time or to the fact that a particular type of accident is much more common now than was the case ten years ago. For instance commercial vehicles are currently used to transport workers to and from their places of their work. When such a vehicle is involved in an accident, large numbers of mortalities often occur. This report investigates the modelling and implementation of a coordination system within a simulation environment to foresee future accident rate. The approach of analysis used must be correspondingly robust and objective to evaluate accident rate. To comparing changes in car ownership, we hope to use these data to investigate the factors behind these changes. Some examples are the effect of income, changes in employment, changing household structure and changes in residential and work location. They should not be too sensitive to departures from model assumptions or the presence of a substantial number of outliers. Given the polluted nature of the data, ordinary least squares regression is not suitable, therefore, robust regression techniques are recommended.
format	Thesis
qualification_level	Master's degree
author	Esmaeeli, Hamed
author_facet	Esmaeeli, Hamed
author_sort	Esmaeeli, Hamed
title	Road accident analysis factors
title_short	Road accident analysis factors
title_full	Road accident analysis factors
title_fullStr	Road accident analysis factors
title_full_unstemmed	Road accident analysis factors
title_sort	road accident analysis factors
granting_institution	Universiti Teknologi Malaysia, Faculty of Civil Engineering
granting_department	Faculty of Civil Engineering
publishDate	2010
url	http://eprints.utm.my/id/eprint/11157/4/HamedEsmaeeliMFKA2010.pdf
_version_	1747814820767334400

Road accident analysis factors

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