Transport Lab

Transportation Engineering and Data Science

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Models and data to inform transportation decisions.

Our goal is to provide the information necessary to make smart decisions about transportation infrastructure investments and about how to best incorporate new technology into the existing transportation system. We do this by developing more sophisticated modeling tools to forecast the effects of proposed projects, analyzing new and emerging data sources to understand the effects of past projects, and combining both to advance the science of transportation forecasting in support of evidence-based policy decisions.

The challenges we face as civil engineers combine technical, social and systemic issues. To address these challenges, we aim to actively recruit and promote diverse voices in engineering, and welcome your's.

Our lab is a part of an active and growing transportation group in the Department of Civil Engineering at the University of Kentucky, Kentucky's flagship university. We work in close collaboration with the Kentucky Transportation Center, which serves as the research arm of the state Transportation Cabinet. We are located in beautiful Lexington, Kentucky, a vibrant small city with the nation's first urban growth boundary. Lexington is famous for bourbon, bluegrass and basketball, and offers easy access to hiking, rock climbing and other recreational opportunities.


Travel Demand Forecasting

Big Data

Planning and Policy

News

Transport Lab Part of New Tier 1 University Transportation Center

The University of Kentucky is part of a new Tier 1 University Transportation Center that will advance research and education programs that address critical transportation challenges facing the United States. Its center, The Transit – Serving Communities Optimally, Responsively, and Efficiently (T-SCORE) Center, aims to define a set of strategic visions that will guide public transportation into a sustainable and resilient future, and to equip local planners with the tools needed to translate their chosen vision into their own community.


Forecasting Through COVID-19 Will Be Crucial for the Future of Transportation

What will transportation in the United States look like as precautions designed to prevent the spread of coronavirus disease (COVID-19) are lifted? Forecasting and ensuring that money is being wisely spent is going to be particularly important in light of COVID-19. The National Cooperative Highway Research Program’s (NCHRP) report, Traffic Forecasting Accuracy Assessment Research, is designed to help improve the accuracy, reliability, and utility of project-level traffic forecasts. The Transportation Research Board recently highlighted the importance of this research by Greg Erhardt and Jawad Hoque.


Ride-Hail Research Featured in The Wall Street Journal and The Boston Globe

Eliot Brown wrote an article for The Wall Street Journal article titled "The Ride-Hail Utopia that Got Stuck in Traffic" telling the story of how Uber and Lyft said they would ease congestion, but instead they made it worse. Separately, The Boston Globe Spotlight Team (as featured in the movie Spotlight) wrote a three-part series, "Seeing Red", on the science and causes of traffic in Boston. Both feature recent research by Sneha Roy and Greg Erhardt. You can browse a dynamic map of the results created by our partners at the San Francisco County Transportation Authority.


Ride-Hailing and Transit Riderhip Decline

Recent research by Michael Graehler, Greg Erhardt and Alex Mucci found that the introduction of ride-hailing in is US cities is correlated with declining public transit ridership. Streetsblog, CityLab and others covered this research and its implications for sustainability.


Teaching

Research

Optimal, Responsive and Efficient Transit

Transit-Serving Communities Optimally, Responsively and Efficiently (T-SCORE), a Tier 1 University Transportation Center.

Causes of Transit Ridership Decline

Analyzing the causes of the recent transit ridership decline and evaluating the effectiveness of potential responses.

Traffic Forecast Accuracy

Measuring the historic accuracy of project-level traffic forecasts.

Ride-Hailing in San Francisco

Measuring the effect of ride-hailing on congestion, transit ridership and traffic safety in San Francisco.

Data Fusion

Developing a Big Data fusion tool to understand travel demand trends and measure transport project impacts.

Open Science

Launching a non-profit foundation to advance the science of travel demand forecasting.

People

Greg Erhardt

Assistant Professor

CV Google Scholar Twitter GitHub

I've spent 20 years working in transportation modeling and data analysis, spanning both research and practice in the US and Europe. As a practicing engineer, I led the final development and early applications of some of the nation’s most sophisticated transportation modeling systems, including activity-based travel models, a dynamic traffic assignment model, and long-distance travel models. My PhD is from the Centre for Advanced Spatial Analysis (CASA), a highly inter-disciplinary program focused on building a new “science of cities”. I have worked in government, and for RAND Europe, a leading public-policy think tank. My recent research investigates the application of continuously collected transportation data to the systematic retrospective evaluation of transportation projects. This research provides a platform from which to better evaluate the accuracy of travel models in forecasting the effects of real-world transportation projects.

Outside of work I enjoy playing with sticks and telling bad jokes with my two boys. This summer, we built a treehouse. On Fridays (and almost every day during quarantine), I have lunch with the director of the Kentucky Stable Isotope Geochemistry Lab.

Alex Mucci

PhD Student, MS 2017
Resume LinkedIn GitHub

My current research is looking into what drives transit ridership and how ride-hailing affects a city and its transit system. In my MS research I studied the effect that Uber and Lyft on transit ridership in San Francisco, CA. For my PhD, I am building models of ride-hail ridership that can be applied nationwide using open data.

When I am not saving the world one model at a time, I am usually helping my family on our farm, golfing, listening to the Talking Headways and Freakonomics Radio podcasts, or watching the Reds and Bengals post mediocre seasons.

Jawad Hoque

PhD Candidate, MS 2018

I did my B.Sc. in Civil Engineering from Bangladesh University of Engineering and Technology. I majored in Structural Engineering back home; magnificent bridges attracted me so. A year at the World Bank working for the Transportation Unit GT106 made me realize that I can contribute more for my country with advanced knowledge in Transportation Engineering so I decided to switch. I am currently working on assessing traffic forecast accuracy: the magnitude and the sources of error.

I am a quiet man, but you should come to the CATSlab and ask me about high-fantasy books.

Vedant Goyal

PhD Candidate

I am currently investigating the effect of ride-hailing on traffic safety in San Francisco. In parallel, I am running MatSIM scenarios to understand how to increase public transit ridership. Prior to joining UK, I was a Road Design and Transportation Coordinator at Bloomberg Philanthropies Initiative for Global Road Safety.

I keep very busy chasing around a two-year old.

Brandon Ivanchak

MS Student

Increasing roadway capacity encourages more people to drive and may therefore releive congestion less than might be expected. I am working to identify the factors leading to the variation in the magnitude of induced demand reported in the literature. I previously worked as a roadway design engineer at Stantec.

My dog and cats often join me during Zoom meetings.

Ian Zhang

Research Intern

I am enrolled in the Math, Science and Technology Center (MSTC) at Dunbar High School. For my capstone research project, I am working with the Transport Lab to estimate the uncertainty inherent in public transit forecasts.

Right now, I'm mostly stuck in the house.

Alumni

Dr. Sneha Roy

PhD 2019

My PhD dissertation used a unique data set scraped from the Uber and Lyft APIs to measure the ride-hailing's contribution to growing traffic congestion in San Francisco. I found it to be the biggest contributor to the 60% increase in vehicle hours of delay between 2010 and 2016. The resulting research was featured in publications including the San Francisco Chronicle, the Wall Street Journal, and NPR.

After graduating, I worked for Cambridge Systematics on Big Data applications in transport, and am now developing travel demand models for AECOM in San Jose, CA.

Michael Graehler

BS 2018

I completed a summer research project with the Transport Lab measuring the determinants of public transit ridership trends in 22 US cities. I found that ride-hailing's entry into a market led to net transit ridership loss. The resulting research was covered worldwide in publications including Streetsblog, Citylab and Expansión.

After graduating from UK, I completed an MS in Finance at Vanderbilt University and and went on to work for a healthcare investment bank in Charlotte, NC. I am also involved with Engineers Without Borders and started a non-profit organization, Developing Nepal.

Emily Greenway

BS 2020

As an undergraduate researcher in the Transport Lab, I completed a pilot study of climate migration models. As people are displaced by climate-related events, where they move to may drive growth in some cities, so we aimed to understand how people make those relocation decisions.

I am currently a senior in Civil Engineering at UK and look forward to graduating soon!