In the passing decades, the monitoring of pavements and passing vehicles was developed vigorously with the growth of information and sensing technology. Pavement monitoring is an essential part of pavement research and plays an important role in transportation system. At the same time, the monitoring system about the traffic, such as Weigh-in-Motion (WIM) system and traffic classification system, also attracted lots of attention because of their importance in traffic statistics and management. The monitoring system in this dissertation combines the monitoring for pavements and traffic together with the same sensing network. For pavement health monitoring purpose, the modulus of the asphalt layer can be back-calculated based on the collected mechanical responses under corresponding environmental conditions. At the same time, the actually strain and stress in pavements induced by each passing vehicle are also used for pavement distress prediction. For traffic monitoring purpose, the horizontal strain traces are analyzed with a Gaussian model to estimate the speed, wandering position, weight and classification of each passing vehicle. The whole system, including the sensing network and corresponding analysis method, can monitor the pavement and the traffic simultaneously, and is called transportation monitoring system. This system has a high efficiency because of its low cost and easy installation; multi-functionality to provide many important information of transportation system. Many related studies were made to improve the prototyped transportation monitoring system. With the assistance of numerical simulation software ABAQUS and 3D-Move, the effect of many loading and environmental conditions, including temperature, vehicle speed, tire configuration and inflation pressure, are taken into consideration. A method was set up to integrate data points from many tests of similar environmental and loading conditions based on Gaussian model. Another method for consistent comparison of variable field sensor data was developed. It was demonstrated that variation in field measurement was due to uncontrollable environmental and loading factors, which may be accounted for by using laboratory test and numerical simulation based corrections. / Ph. D.

In the past, transportation related economic analysis has considered agency related costs only. However, transportation managers are moving towards more holistic economic analysis including road user and environmental costs and benefits. In particular, transportation air pollution is causing increasing harm to health and the environment. Transport managers are now considering related emissions in transport economical analyses, and have established strategies to help meet Kyoto Protocol targets, which specified a fifteen percent reduction in Canada's emissions related to 1990 levels within 2008-2012.<p>The objectives of this research are to model heavy vehicle emissions using a emissions computer model which is able to assess various transport applications, and help improve holistic economic transport modeling. Two case studies were evaluated with the model developed.<p>Firstly, the environmental benefits of deploying weigh-in-motion systems at weigh stations to pre-sort heavy vehicles and reduce delays were assessed. The second case study evaluates alternative truck sizes and road upgrades within short heavy oilfield haul in Western Canada. <p>The model developed herein employed a deterministic framework from a sensitivity analysis across independent variables, which identified the most sensitive variables to primary field state conditions. The variables found to be significant included idling time for the weigh-in-motion case study, road stiffness and road grades for the short heavy haul oilfield case study.<p>According to this research, employing WIM at weigh stations would reduce annual Canadian transportation CO₂ emissions by nearly 228 kilo tonnes, or 1.04 percent of the Canadian Kyoto Protocol targets. Regarding direct fuel savings, WIM would save from 90 to 190 million litres of fuel annually, or between $59 and $190 million of direct operating costs.<p>Regarding the short heavy oil haul case study, increasing allowable heavy vehicle sizes while upgrading roads could decrease the annual emissions, the fuel consumption, and their associated costs by an average of 68 percent. Therefore, this could reduce each rural Saskatchewan municipality's annual CO₂ emissions from 13 to 26.7-kilo tonnes, which translates to 0.06 and 0.12 percent of the Canadian Kyoto Protocol targets or between $544,000 and $ 1.1 million annually. <p>Based on these results, the model demonstrates its functionality, and was successfully applied to two typical transportation field state applications. The model generated emissions savings results that appear to be realistic, in terms of potential Kyoto targets, as well as users cost reductions and fuel savings.

In the past, transportation related economic analysis has considered agency related costs only. However, transportation managers are moving towards more holistic economic analysis including road user and environmental costs and benefits. In particular, transportation air pollution is causing increasing harm to health and the environment. Transport managers are now considering related emissions in transport economical analyses, and have established strategies to help meet Kyoto Protocol targets, which specified a fifteen percent reduction in Canada's emissions related to 1990 levels within 2008-2012.<p>The objectives of this research are to model heavy vehicle emissions using a emissions computer model which is able to assess various transport applications, and help improve holistic economic transport modeling. Two case studies were evaluated with the model developed.<p>Firstly, the environmental benefits of deploying weigh-in-motion systems at weigh stations to pre-sort heavy vehicles and reduce delays were assessed. The second case study evaluates alternative truck sizes and road upgrades within short heavy oilfield haul in Western Canada. <p>The model developed herein employed a deterministic framework from a sensitivity analysis across independent variables, which identified the most sensitive variables to primary field state conditions. The variables found to be significant included idling time for the weigh-in-motion case study, road stiffness and road grades for the short heavy haul oilfield case study.<p>According to this research, employing WIM at weigh stations would reduce annual Canadian transportation CO₂ emissions by nearly 228 kilo tonnes, or 1.04 percent of the Canadian Kyoto Protocol targets. Regarding direct fuel savings, WIM would save from 90 to 190 million litres of fuel annually, or between $59 and $190 million of direct operating costs.<p>Regarding the short heavy oil haul case study, increasing allowable heavy vehicle sizes while upgrading roads could decrease the annual emissions, the fuel consumption, and their associated costs by an average of 68 percent. Therefore, this could reduce each rural Saskatchewan municipality's annual CO₂ emissions from 13 to 26.7-kilo tonnes, which translates to 0.06 and 0.12 percent of the Canadian Kyoto Protocol targets or between $544,000 and $ 1.1 million annually. <p>Based on these results, the model demonstrates its functionality, and was successfully applied to two typical transportation field state applications. The model generated emissions savings results that appear to be realistic, in terms of potential Kyoto targets, as well as users cost reductions and fuel savings.