Projects

This three-chapter dissertation will study the reasons behind the decisions of local jurisdictions, including cities and counties, about VMT reduction levels in their environmental reviews and how local planners view equity in the process of implementing VMT-reducing strategies in the CEQA process.

This research will study the challenges of installation and operation of a reliable network of public DC fast charging stations. While existing studies show costs ranging from $20,000 - $150,000, the researchers find costs range anywhere between $122,000 and $440,000.

The goal of this research is to understand vehicle interactions in mixed traffic and leverage the understanding to shape AV behaviors, simultaneously benefiting all road users (i.e., ensuring equity) and achieving emission reduction, even with a limited proportion of AVs.

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.

The study will utilize mathematical modeling, including artificial intelligence, to design a policy for the optimal use of plug-in hybrid electric vehicles and identify charging locations for future battery electric vehicle drivers

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 dissertation will present an evaluation framework, using material from California as a case study, to prioritize the adoption of SCM by concurrently considering (1) material performance, (2) resource availability, and (3) environmental impact reduction.

This research proposes to use bootstrap analysis to derive confidence intervals for each item in the AASHTOWare database.

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.

The project focuses on smart charging of electric vehicles (EVs) – specifically the optimization-based charging of EVs over time.

This project will extend Georgia Tech’s previous effort in designing its family of mode and path-specific multi-modal transportation simulator elements, in parallel support of the Atlanta Regional Commission’s ITS4US project.

This research responds to identified gaps within the field of life cycle analysis while contributing a more nuanced, accurate understanding of the lithium-ion batteries value chain.

The goal of this project is to develop a connected automation-enabled cooperative management framework for mixed traffic.

The objectives of the research project are to: 1) Combine cooperativity and the EAD to reduce the negative effect of the increasing penetration rate and 2) conduct field tests in existing connected vehicle testbeds and extend the scope to corridors or networks and study the energy optimization approach for multiple intersections.

This project studies the application of wireless charging to enhance performance of battery electric truck fleets through range extension.

The goal of this project is to design and evaluate a Dynamic Mobility Management System (DyMMS) to address traffic congestion, which leads to more fuel consumption, significant greenhouse gas (GHG) emissions, and poor air quality.