The highway alignment optimization problem is modeled to identify the preferred alignment alternatives which minimize total cost and satisfy the highway design standards. Several mathematical models have been developed during the past decades, among which the Highway Alignment Optimization (HAO) model has been used in several practical highway design projects with satisfactory results. However, several major cost components, such as vehicle operating cost and environmental cost are estimated roughly, and should be improved to yield more precise cost estimates and to allow optimization of lane widths. These are the HAO model features which this thesis seeks to improve.

Lane width is an important factor in highway design, which is related to the travel speed, safety, as well as earthwork cost. This thesis employs Newton's method and Finite Difference method to search for the appropriate lane width. The preferred lane width found in the case study is 10.6 feet, for which the total cost is $233 million, and 12.5% less than the total cost at 12 feet lane width. In addition, this thesis improves the vehicle operating cost prediction by calculating the vehicle resistance force and horsepower, and estimating the fuel consumption based on the fuel consumption rate (g/hp-hr). Moreover, the environmental cost, particularly the vehicle emissions cost is incorporated in the newly improved HAO model. It is found that the vehicle emission cost decreases by 9% after including the environmental cost component in the model objective function.

The results of the case study and sensitivity analyses indicate that the improved HAO model can find good highway alignments efficiently in tough topographic environmental. Moreover, the model can jointly consider the social, economic and environmental consequences, and result in less fuel consumption and pollutant emissions.