About

T. Donna Chen is an Associate Professor in the Department of Civil and Environmental Engineering at the University of Virginia, having joined the faculty in August 2015. Her research focuses on sustainable transportation systems, including modeling the impacts of new vehicle technologies on traveler behavior and the environment, travel demand modeling, transportation economics, and crash safety. She is involved in various professional organizations such as the Transportation Research Board, the American Society of Civil Engineers Transportation & Development Institute, the Intelligent Transportation Society of America, the Institute of Transportation Engineers, and Women’s Transportation Seminar. Dr. Chen holds a Ph.D. in Civil Engineering from the University of Texas at Austin, earned in 2015, along with a Master’s degree from the University of Texas at Arlington and a Bachelor’s degree from Texas A&M University. Her work emphasizes the importance of access to reliable transportation as a key determinant of quality of life. She has contributed to research on electric vehicle adoption, shared autonomous vehicle operations, and crash safety, and teaches courses in transportation infrastructure design and transportation economics and finance.

Research topics

• Engineering
• Economics
• Environmental science
• Demographic economics
• Business
• Microeconomics
• Statistics
• Geography
• Meteorology
• Transport engineering
• Econometrics

Selected publications

• Hydraulic and Thermal Characteristics Analysis of Large-Scale Clustered Ground Heat Exchangers with Non-Identical Circuits

  Buildings · 2026-02-01

  articleOpen access

  In the global wave of energy transition, ground-source heat pump (GSHP) systems are widely adopted for their ability to efficiently provide space heating and cooling. By utilizing stable shallow geothermal energy, these systems significantly reduce operational energy consumption in buildings, playing a crucial role in enhancing building energy efficiency and achieving low-carbon strategies. However, large-scale ground heat exchanger (GHE) clusters with non-identical circuits often face hydraulic and thermal imbalances, leading to degraded system performance. This study investigates the hydraulic and thermal behavior of a large-scale GHE system in Shandong Province, China. Hydraulic and thermal models are first developed based on Kirchhoff’s laws and the principle of energy conservation, and then used to simulate and analyze the influence of the number and depth of boreholes on hydraulic and thermal conditions. The results indicate that the flow imbalance rate and pipe length ratio follows a power-law relationship, δf = a (Lv/h)^b + d, with fitted coefficients, a = 0.0677–0.1294, b = −0.7086 to −1.0805, d = 0.0036–0.0921, while the heat exchange imbalance rate follows a linear relationship, δq = kδf + o, with k = 0.0906–0.265 and o = 0.0028–0.0039. Increasing the number of boreholes or decreasing depth exacerbates flow imbalance (10–58%), but soil thermal resistance dominates, limiting the increase in the heat exchange imbalance rate (2.2–9%). The formula and the quantitative relationship proposed in this paper aim to provide guidance for the engineering design of large-scale non-identical circuit GHE clusters.

  PublisherDOI

• Assessing the spatially heterogeneous transportation impacts of recurrent flooding in the Hampton roads region on auto accessibility

  Transportation Research Interdisciplinary Perspectives · 2025-11-01 · 1 citations

  articleOpen access

  • Verified crowdsourced flood data reveals TAZ-level accessibility impacts. • Morning peak shows greatest losses: 1.7 % mean, up to 49.6 % for work access. • Lower education zones experience disproportionate flood accessibility reductions. • Event-day methodology captures spatial and temporal flooding heterogeneity. • Observed flood events replace simulations for measuring transport performance. Recurrent flooding has increased rapidly in coastal regions due to sea level rise and climate change. A key metric for evaluating transportation system degradation is accessibility, yet the lack of temporally and spatially disaggregate data means that the impact of recurrent flooding on accessibility—and hence transportation system performance—is not well understood. Using crowdsourced WAZE flood incident data from the Hampton Roads region in Virginia, this study examines changes in the roadway network accessibility for travelers residing in 1,113 traffic analysis zones (TAZs) across five time-of-day periods. Additionally, a social vulnerability index framework is developed to understand the socioeconomic characteristics of TAZs that experience high accessibility reduction under recurrent flooding. Results show that TAZs experience the most accessibility reduction under recurrent flooding during the morning peak period (6 to 9am) with large differences across different zones, ranging from 0 % to 49.6 % for work trips (with population-weighted mean reduction of 1.71 %) and 0 % to 87.9 % for non-work trips (with population-weighted mean reduction of 0.81 %). Furthermore, the social vulnerability analysis showed that zones with higher percentages of lower socio-economic status, unemployed, less educated, and limited English proficiency residents experience greater accessibility reduction for work trips. In contrast to previous studies that aggregate the effects of recurrent flooding across a city, these results demonstrate that there exists large spatial and temporal variation in recurrent flooding’s impacts on accessibility. This study also highlights the need to include social vulnerability analysis in assessing impacts of climate events, to ensure equitable outcomes as investments are made to create resilient transportation infrastructure.

  PublisherDOI

• What Affects Pedestrian Street Crossing Decisions in Day and Night Scenarios? A Case Study in Charlottesville, Virginia

  SSRN Electronic Journal · 2025-01-01

  preprintOpen accessSenior author
  PublisherDOI

• A deep reinforcement learning based metro train operation control optimization considering energy conservation and passenger comfort

  Engineering Research Express · 2025-01-29 · 1 citations

  articleSenior author

  Abstract As an efficient mode of public transportation, urban rail transit promotes sustainable development by reducing energy consumption and improving service quality. Numerous studies have been conducted on this subject. However, many existing methods struggle to adapt to environmental changes due to the complexity of actual line conditions. Therefore, based on deep deterministic policy gradient (DDPG) and genetic algorithm (GA), a new optimization algorithm GA-DDPG is proposed in this paper. This algorithm utilizes DDPG for continuous action control of trains and employs GA to optimize the noise generation hyperparameter of DDPG, thereby enhancing the learning and adaptive capabilities of the algorithm. Firstly, a reference system is established based on expert knowledge to ensure safe train operation and guide the training of the algorithm model. Then, under the intervention of reference system, the GA-DDPG is used to optimize and adjust the train operation control strategy to achieve a balance in punctuality, energy efficiency, and comfort. Finally, simulation experiment shows that GA-DDPG achieves at least 5.2% energy savings and 51.2% passenger comfort compared to DDPG. More experiments further demonstrate that GA-DDPG possesses better adaptability and robustness than DDPG when the environment changes.

  PublisherDOI

• A Sequential and Dynamic Analysis of Pedestrian Street Crossing Decisions in Day and Night Scenarios: A Case Study in Charlottesville, Virginia

  SSRN Electronic Journal · 2025-01-01

  preprintOpen accessSenior author
  PublisherDOI

• The Shifting Impact of Recurrent Flooding on Transportation Accessibility: A Case Study of Affected Populations in The Hampton Roads Region

  arXiv (Cornell University) · 2024-02-11

  preprintOpen access

  Accelerated sea level rise has resulted in recurrent flooding in coastal regions, increasingly impacting both transportation systems and local populations. Using the Hampton Roads region in Virginia as a case study, this study a. identifies hotspots with frequent, significant accessibility reduction for work and nonwork travel utilizing crowdsourced WAZE flood report data during the month of August over 5 years: 2018 to 2022; and b. examines the shifts in social vulnerability in populations residing in these hotspots over the 5 year period using 2016 and 2021 American Community Survey data. Results show that approximately 12 percent and 3 percent of the population of the region reside in hotspots experiencing significant recurrent flooding-induced accessibility reduction for work and nonwork trips. Social vulnerability analysis revealed that populations with greater socioeconomic and transportation vulnerabilities are more susceptible to recurrent flooding induced accessibility impacts in terms of both extent and frequency. Furthermore, a comparison of social vulnerability indices between 2016 and 2021 shows an increasing trend of social vulnerability for highly impacted zones, with low income, disabled, and households with young children having restricted ability to relocate from these zones. The findings reinforce the necessity for spatially and temporally disaggregated studies of climate event impacts. Furthermore, the longer term population trends highlight the importance of dynamic assessment of climate event impacts at different time scales.

  PublisherOA PDFDOI

• Tugboat electrification planning for container ports

  SSRN Electronic Journal · 2024-01-01 · 2 citations

  preprintOpen access1st authorCorresponding
  PublisherDOI

• Copula Theory-Based Typical Scenario Generation of Photovoltaic Joint Output for Power Systems

  Environmental science and engineering · 2024-01-01

  book-chapter
  PublisherDOI

• Assessing The Spatially Heterogeneous Transportation Impacts of Recurrent Flooding in The Hampton Roads Region: Part 1 Auto Accessibility

  arXiv (Cornell University) · 2024-01-12

  preprintOpen access

  Recurrent flooding has increased rapidly in coastal regions due to sea level rise and climate change. A key metric for evaluating transportation system degradation is accessibility, yet the lack of temporally and spatially disaggregate data means that the impact of recurrent flooding on accessibility, and hence transportation system performance: is not well understood. Using crowdsourced WAZE flood incident data from the Hampton Roads region in Virginia, this study (Part 1) examines changes in the roadway network accessibility for travelers residing in 1,113 traffic analysis zones (TAZs) across five time of day periods. Additionally, a social vulnerability index framework is developed to understand the socioeconomic characteristics of TAZs that experience high accessibility reduction under recurrent flooding. Results show that TAZs experience the most accessibility reduction under recurrent flooding during the morning peak period (6 to 9am) with large differences across different zones, ranging from 0 to 49.6 (percentage) for work trips (with population weighted mean reduction of 1.71 percent) and 0 to 87.9 (percentage) for nonwork trips (with population weighted mean reduction of 0.81 percent). Furthermore, the social vulnerability analysis showed that zones with higher percentages of lower socioeconomic status, unemployed, less educated, and limited English proficiency residents experience greater accessibility reduction for work trips. In contrast to previous studies that aggregate the effects of recurrent flooding across a city, these results demonstrate that there exists large spatial and temporal variation in recurrent floodings impacts on accessibility. This study also highlights the need to include social vulnerability analysis in assessing impacts of climate events, to ensure equitable outcomes as investments are made to create resilient transportation infrastructure.

  PublisherOA PDFDOI

• Evaluating Current and Future Pedestrian Mid-Block Crossing Safety Treatments Using Virtual Reality Simulation

  SSRN Electronic Journal · 2024-01-01

  preprintOpen access
  PublisherDOI

Frequent coauthors

• Jonathan L. Goodall

  25 shared

• Erin Robartes

  Virginia Transportation Research Council

  23 shared

• Xiang Guo

  University of Virginia

  21 shared

• Arsalan Heydarian

  Engineering Systems (United States)

  20 shared

• Faria Tuz Zahura

  Government of the United States of America

  16 shared

• Wenjian Jia

  Chang'an University

  14 shared

• Austin Angulo

  University at Buffalo, State University of New York

  14 shared

• Yawen Shen

  University of Virginia

  13 shared

Labs

• Link LabPI

Awards & honors

• American Society of Civil Engineers Excellence in Civil Engi…
• National Science Foundation IGERT Fellow 2013-2015
• Federal Highway Administration Eisenhower Transportation Fel…