“Sustainable Transportation Planning During an Era of Technological Evolution” provides an in-depth analysis spanning three pivotal chapters, each focusing on the nexus of climate change, transportation, and metropolitan planning. Chapter 2 delves into climate change's role in transportation plans. The literature reviews transportation’s effects on climate change and the significance of Metropolitan Planning Organization (MPO) transportation planning. After identifying research gaps and ethical considerations, the chapter outlines a methodology employing Latent Dirichlet Allocation (LDA) model construction, text preprocessing, and evaluation metrics. Python’s Natural Language Processing (NLP) toolbox is utilized to analyze the contents of 42 long-range transportation plans. Semantic interpretations emphasize word frequencies, climate keywords, transportation plan similarities, and data visualizations, culminating in a discussion of the findings and research conclusions. Chapter 3 shifts to the modeling of autonomous vehicles (AV) concerning sustainable development. It reviews the implications of technological advancements on mobility, long-term planning, and urban expansion. The methodology presents land use forecasts, transportation modeling, and AV simulation parameters. Various scenarios, such as increased auto availability and decreased parking costs, are explored. A detailed discussion synthesizes these findings, leading to a research conclusion. Chapter 4 targets current MPO transportation planning activities, accentuating climate action. Data is collected via a PDF survey completed and returned by 13 of Wisconsin’s 14 MPOs. A description of the survey methodology is followed by an examination of the findings, offering key insights and latent thematic comparisons to the findings documented in Chapter 2 concerning climate action currently being taken by Wisconsin’s MPOs via their long-range transportation planning activities.