Dissertation Grant

This research will address policy-relevant questions by investigating cost-efficient ways to implement a RUC, evaluating the equity impacts of RUC, and quantifying factors that influence household’s PEV adoption decisions.

This project synthesizes various energy models into one model that estimates transit vehicle energy consumption using real-world data.

This dissertation presents an econometric model to measure supply and demand within the Chinese vehicle market. The model will be significant for industry, particularly car manufacturers interested in better targeting cars, including alternative vehicles, for the Chinese market.

This study aims to conduct a time-series to explore how electric vehicle (EV) adoption has increased over time and to predict how future EV adoption will continue to expand in the future.

This study systematically reviews the policy landscape for sustainable freight transportation using text mining and natural language processing techniques and aggregates them into seven distinct policy types: prohibitions, rebates, sales mandates, technological mandates, material infrastructure, and immaterial infrastructure.

This research will apply climate vulnerability assessments and the TBL approach to sustainability to rail infrastructure planning and resource allocation decision making. The results will be validated by rail operators and administrators to support improved investments in rail that are resilient to extreme events, protect the natural environment, enhance economic competitiveness, and improve societal quality of life, equitably.

This project aims to develop a comprehensive knowledge of the capabilities of different last-mile strategies and policies for varied markets and delivery environments.

This research investigates these two crucial components of climate mitigation that have proven to be politically obstinate. Three studies will focus on the context in which land use and transportation policies are created – the "who, what, and why" of political influence – in order to better understand the barriers to and opportunities for policy change.

This project bridges the gap between predicted and measured near-road PM2.5 from vehicle emissions, by creating and evaluating the effectiveness of two correction modules.