Publications (Pre-2025)

This study employs a novel approach combining spatial analysis and Factor Analysis of Mixed Data (FAMD) to delve into bikeshare users’ perceptions and expectations based on bikeshare systems' online platforms for user feedback.

This project evaluates a broad range of factors influencing microtransit adoption and travel behavior among underserved populations using original revealed choice survey data collected from February – May 2024 with online and intercept surveys.

This work is the first to examine households’ decision to maintain at least two plug-in electric vehicles (PEVs) in their household fleets.

The goal of this project was to assess the capabilities of the travel demand forecasting models (TDMs) used by California’s metropolitan planning organizations (MPOs) with respect to forecasting the increase in vehicle miles of travel induced by highway capacity expansion.

This dissertation examines clean energy supply chains in the context of the just transition and circular economy frameworks, focusing on a central technology for zero-emissions transportation: lithium-ion batteries (LIBs) for electric vehicles (EVs). The author focuses on three phases of the LIB life cycle: mineral extraction, component and cell manufacturing, and end-of-life management.

In this project, the team developed MOVES-Matrix 3.0 based on the existing MOVES Matrix framework, and modified the code to perform the iterative processes with MOVES 3, handle new data formats, and join distributed computing outputs into new matrices.

A team at the University of California, Davis, conducted a case study in Sacramento, California, to explore bikesharing as an option for connecting affordable housing residents with transit services. This brief summarizes the findings from that research and provides implications for the field.

Using the 2017 National Household Travel Survey, this study quantifies and compares travel burdens in rural versus nonrural communities in the United States.

This research examines the factors that can help explain the differences between users and non-users of online shopping in the U.S.A. during April and May 2020 to help understand the barriers to home-based shopping accessibility.

The research presented in this paper explores the impacts of noise barrier characteristics on AERMOD-predicted concentrations.

This dissertation consists of six studies that explore the environmental sustainability and social equity implications of micromobility services, separately and together. The studies compiled in this dissertation examine the implications of travel behavior for environmental sustainability through the lens of equity.

In this paper, the authors present a new sensor location model that aims to maximize observability of link densities in a dynamic traffic network described using a piecewise linear system of ordinary differential equations.

Traffic sensors serve as one of the most important sources for such data by providing an accurate and reliable general picture of the traffic system. In this dissertation, a new sensor location model is developed to maximize the observability of link densities in a dynamic traffic network described using a piecewise linear ordinary differential equation system.

In this study, a modeling framework for population exposure to traffic-related PM2.5 with high spatiotemporal resolution is proposed and applied to the I-575/I-75 Northwest Corridor (NWC) in Atlanta, GA, for environmental equity analysis.

The purpose of this literature review is to assess what is currently known about the ability of travel demand forecasting models (TDMs) to provide accurate forecasts for different types of transportation plans and projects with respect to different outcome measures of interest.

This dissertation sets out to 1) explore the feasibility of implementing a per-mile road-usage charge (RUC) in replacement of the motor fuel taxes, 2) estimate the changes in vehicles-miles travelled (VMT) and the revenues generated from motor fuel taxes under the backdrop of vehicle electrification, and 3) quantify the effects of vehicle class and fuel type portfolios in ZEV-adopting households’ vehicle replacement decisions.

This study delves into the energy and emissions impacts of Shared Autonomous and Electric Vehicles (SAEVs) on disadvantaged communities in California.

In this study, a modeling framework was developed to generate high-resolution synthetic fleets, for use with synthetic household modeling in activity-based travel models, by integrating various data sources.

Research performed in this supplemental NCST study improved model algorithms to increase analytical efficiency and to integrate ridership demographics, so that energy use impacts could be assessed across demographic groups for use in social sustainability analysis.

The 2023-24 survey collected data from 4,774 people affiliated with UC Davis about their travel to campus.