Freight transportation is a key element in economic growth and the development of countries. Linking freight lines between Gulf Cooperation Council (GCC) countries (specifically Kuwait, Saudi Arabia, Bahrain, United Arab Emirates and Oman) will increase revenues, improve infrastructure asset efficiency and generate employment. Shipping and transport industries endure continuous changes and transformations in response to technological developments and changes in world trade. Significant amounts of documentation, research papers as well as technical and economic reports are available in literature that details ways in which these industries respond to and meet the needs of shippers and consumers. Information and data are valuable assets in providing a basic understanding and base knowledge of the different types and methods of shipping options, as well as the impacts of different transportation modes. In this paper, possible environmental impacts will be discussed, including air quality, noise levels and vibration. In addition, safety factors such as fatalities and accidents will be incorporated into discussions on mode selection. A GIS model was implemented and a case study was created to assess these impacts, estimate damage costs as well as discuss concerns with logistics and mode selection. Finally, possible mitigation measures to manage environmental and safety concerns will be proposed. Based on the analysis and results, more work on environmentally sustainable models and designs need to be implemented to mitigate impacts and to ensure that the environment and quality of life can be preserved. Incentivizing shifts from truck to rail or to intermodal systems is key for shippers’ participation in reducing environmental and societal impacts. Encouraging shippers to change their mode selection can relieve congestion and lower accident rates.
Rehabilitation and maintenance of pavement are well established and costly operations. One of the major challenges of these operations is determining the optimum maintenance and repair schedule. In any given city, there are hundreds of miles of pavement constructed at different times and are in different states of deterioration. It is the job of municipal engineers to establish a cost effective schedule that prioritizes the repair or even the reconstruction of different segments of the roads. The schedule is usually based on an overall Pavement Condition Index (PCI). Typically, inspectors are sent out to observe the pavement conditions and conduct accurate measurements to be used in computing the PCI; however the cost associated with such inspection missions is often high.This thesis proposes a novel approach to estimate a cost effective Pavement Indicator (PI) for the entire city (or any area of interest). The proposed approach exploits newly available miniature cameras, GPS, wireless networking and Digital Signal Processing to automatically and continually collect visual information about different segments of the road, and combines these images to establish a live map of the city roads where different colours correspond to an approximate estimate of a pavement indicator (PI). The proposed technique is not a replacement of the traditional inspection, but rather it is a tool to identify the sections that are in greater need of repair. The technique involves taking pictures of various sections of the road network using cameras mounted on public vehicles and transmitting these images to a processing centre. Each image is processed using image filtering techniques to produce an initial estimate of PI. The cumulative effect of these estimates produces regional estimates that become more ii statistically accurate as time goes by, and the overall PI map is continually updated to maintain a global visual map of PI. The proposed pavement indicator (PI) map can then be linked to an optimization software package to determine the most cost effective road rehabilitation schedule.iii This dissertation is dedicated to the memory of my father, Bakheet Ghaith Bakheet Al-Falahi iv ACKNOWLEDGEMENTS First of all, I would like to profusely thank Allah for enabling me to achieve this research work.
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