Until recently, many studies have dealt separately with the problems of highway alignment optimization and network design. However, no models have been found that integrate these problems comprehensively and effectively. This dissertation seeks to find a realistic three-dimensional highway alignment that best improves an existing network, while considering its costs, geometric design, and environmental impacts on the study area. To fulfill this objective, an effective network model is developed that can simultaneously optimize (i) highway alignments and (ii) junction points with existing roads. In addition, the model’s optimization process considers traffic impacts due to the highway addition as well as factors associated with its construction.
This dissertation starts by investigating the major cost components and important constraints in the highway design processes. Next, existing models for optimizing highway alignments are reviewed by assessing their advantages and disadvantages. Effective solution search methods are then developed to help solve the complex optimization problem. Development of the search methods is essential since an equilibrium traffic assignment as well as alignment optimization is undertaken in the proposed network model. Precise formulations of various highway costs and constraints are also developed for evaluating the various candidate alternatives.
Cost functions for system improvements that can be obtained from the new highway addition are proposed. These are calculated based on the equilibrium traffic flows found from the assignment process. Complex geographical constraints including user preferences and environmentally sensitive areas are realistically represented, along with design standards required for highways. To represent highway alignments, sets of tangents, circular curves and transition spirals are used; in addition, three-leg structure models are also developed for representing the highway endpoints. Finally, several case studies are conducted to test the performance of the proposed models.
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