Sustainable Transportation Decision-Making: Spatial Decision Support Systems (SDSS) and Total Cost Analysis

Abstract

Building a new infrastructure facility requires a significant amount of time and expense. This is particularly true for investments in transportation for their longstanding and great degree of impact on society. The scope of time and money involved does not mean, however, we only focus on the economies of scale and may ignore other aspects of the built environment. To this extent, how can we achieve a more balanced perspective in infrastructure decision-making? In addition, what aspects should be considered when making more sustainable decisions about transportation investments? These two questions are the foundations of this study.

This dissertation shares its process in part with a previous research project – Texas Urban Triangle (TUT). Although the TUT research generated diverse variables and created possible implementations of spatial decision support system (SDSS), the methodology still demands improvement. The current method has been developed to create suitable routes but is not designed to rank or make comparisons. This is admittedly one of the biggest shortfalls in the general SDSS approach, but is also where I see as an opportunity to make alternative interpretation more comprehensive and effective. The main purpose of this dissertation is to develop a Spatial Decision Support System (SDSS) that will lead to more balanced decision-making in transportation investment and optimize the most sustainable high-speed rail (HSR) route.

The decision support system developed here explicitly elaborates the advantages and disadvantages of a transportation corridor in three particular perspectives: construction (fixed costs); operation (maintenance costs); and externalities (social and environmental costs), with a specific focus on environmental externalities. Considering more environmental features in rail routing will offset short-term economic losses and creates more sustainable environments in long-term infrastructure planning.