Date of Graduation
12-2024
Document Type
Dissertation
Degree Name
Doctor of Philosophy in Engineering (PhD)
Degree Level
Graduate
Department
Industrial Engineering
Advisor/Mentor
Pohl, Edward A.
Committee Member
Parnell, Gregory S.
Second Committee Member
Hernandez, Sarah V.
Third Committee Member
LaScola Needy, Kim L.
Keywords
Autonomous Vehicles; Connected Vehicles; Decision Analysis; MODA; Resilience; Transportation Planning
Abstract
Transportation planning involves complex decisions to provide high-quality transportation systems involving multiple stakeholders with numerous competing interests, on top of that they are trying to improve the quality and reliability of those systems on shrinking budgets. This decision is further complicated by the advent of new transportation methods e.g., ride-hailing and the promise of connected and autonomous vehicles (CAVs). While the actual short-term impact of these technologies is uncertain, they will most certainly have a significant impact within the 20-year planning horizon that transportation planners typically consider. These technologies are also blurring the lines between traditionally separate modes of transportation; private vehicles and public transit were distinctly separate modes of transportation, but micro-transit and ride-hailing services have made that distinction less clear. The interconnectedness and technological reliance that come along with these new options also increases the importance of resilience in our transportation system. This research takes a holistic approach to decision-making for transportation systems to accommodate new technology and mobility options. This research moves the state of transportation planning forward in multiple ways. It provides an understanding of the current state of planning for CAVs at the national level from a Metropolitan Planning Organization (MPO) perspective and breaks down the assumptions and uncertainty that have resulted in such a wide range of predictions for the impact of connected and autonomous vehicles to help transportation professionals and public agencies make more informed decisions. I provide a formal definition of resilience and have developed a resilience framework that addresses the all-hazards concept for resilience that is gaining prominence in transportation. The frameworks and definitions are then applied to CAVs and the transportation system using a MODA process and I consider how similar frameworks can be developed for equity and access based on their common structure. I created the universal transportation value hierarchy. This objective hierarchy defines all of the fundamental objectives of a transportation system and provides a framework that allows any combination of planning agencies to organize all of the subobjectives and performance measures that they want to include in their planning process throughout the entire life cycle of a transportation project. It can incorporate everything from federal requirements down to local goals and cover planning horizons from a long-range planning level down to a specific project’s alternative analysis. This fundamental objective-based structure allows planners to better make decisions between different transportation modes as well as changes in policy vs physical infrastructure vs digital infrastructure. This hierarchy is compatible with a Multiple Objective Decision Analysis (MODA) which this research will demonstrate to be an effective methodology for making transportation investment decisions. Finally I address the critiques in the literature of multi-criteria decision analysis and demonstrate how a multistage MODA process addresses these traditional areas of concern for transportation investment decisions and show how this process can create an effective decision support system for our transportation planning processes with increased efficiency and transparency.
Citation
Cottam, B. (2024). Establishing a Robust Decision Framework to Support Transportation Planning Decisions and Accommodate Connected and Autonomous Transportation Alternatives. Graduate Theses and Dissertations Retrieved from https://scholarworks.uark.edu/etd/5564
