CETOC Research

Year 1 Research In Progress:

CETOC-23-R-01: Longitudinal Analysis of Transit's Land Use Multiplier in Three Regions

CETOC-23-R-02: Quantifying the Influences of Telecommuting on VMT and Transit Usage

CETOC-23-R-03: Examining the Role of Transit Investments on Opportunity Outcomes

CETOC-23-R-04: Understanding Transit User Experience and Expectations in Underserved Communities

CETOC-23-R-05: Using Machine Learning to Understand the Built Environment's Influence on 15-Minute Transit-Oriented Communities

CETOC-23-R-06: 50 Years of Trends in Station Areas Across the United States

CETOC-23-R-07: Shared Micromobility as a Last-Mile Complement to Public Transit

CETOC-23-R-08: Analyzing Transit-Based Evacuation Demand in Hurricanes

CETOC-23-R-09: Gentrification, Displacement, and GHG Emissions at Transit-Oriented Communities

CETOC-23-R-10: Is Transit-Oriented Development Affordable for Low- and Moderate-Income Households
(In Terms of Housing & Transportation)?

Year 2 Research In Progress:

CETOC-24-R-01: Mobility Hub Usage in West Palm Beach

CETOC-24-R-02: Re-examining TODs through the Lens of Disability and Care Responsibilities: How Street and Network Structure Perpetuate Inequity of Access and Opportunity

CETOC-24-R-03: Identifying TOD-Capable Locations Using D Variables: Flipping the Recipe on Making the TOD Cake

CETOC-24-R-04: Useful Transit: Bridging the Gap Between the Vision and Reality of Transit-Oriented Communities

CETOC-24-R-05: High-Resolution Measurement of Transit Riders’ Extreme Heat Exposure Across U.S. Cities

CETOC-24-R-06: Inventorying Bus Stop Amenities Across the United States Using Google Street View Images and Computer Vision

CETOC-24-R-07: A Deep Learning Approach for Detecting Built Environment in Transit-Oriented Developments

CETOC-24-R-08: Mobility and Accessibility of Transit-Dependent and Transportation-Disadvantaged (TD2) Population During Hurricanes

CETOC-24-R-09: Updating and Expanding the Nation’s Most Comprehensive Database of Household Travel Survey Data and Related Built Environmental Data

CETOC-24-R-10: Developing a Scalable Evaluation Framework and Dashboard for Implementing and Monitoring Equitable Transit-Oriented Communities

CETOC-24-R-11: New Transit, Bike Infrastructure, and Green Space: Do They Have a Multiplying Effect on Gentrification and Displacement?

CETOC-24-R-12: Transit-Oriented Development (TOD) Formation along Bus Rapid Transit (BRT) Lines: Database Development, Analysis, and Identification of High-Impact Policy, Design, and Service Characteristics

CETOC-24-R-13: What Makes Affordable Housing Affordable: Mechanisms Used to Produce Affordable Housing Near Transit in the US

See "Education & Outreach" for our Year 2 Funded Education Projects

CETOC-Funded Peer-Reviewed Papers:

Huang, E., Yin, Z., Broaddus, A., Yan, X. (2024). Transit and shared e-scooter integration: Travel behavior insights from Los Angeles and Washington D.C. Travel Behavior and Society, 34, 100663.

Su, L., Yan, X., & Zhao, X. (2024). Spatial equity of micromobility systems: A comparison of shared E-scooters and docked bikeshare in Washington DC. Transport Policy, 145, 25-36.

Tian, G., & Danton, B. (2024). Studying Understudied Populations’ Travel Behaviors with a Machine Learning Approach: A Focus on Hispanic and Latinx Households. Journal of Planning Education and Research.

Tian, G., Danton, B. Ewing, R. & Li, B. (2024). Varying influences of the built environment on household travel in the United States – An update with 36 diverse regions and machine learning. Cities, 155, 105490.

Xu, Y., Ke, Q., Zhang, X., & Zhao, X. (2024). ICN: Interactive Convolutional Network for Forecasting Travel Demand of Shared Micromobility. GeoInformatica, 1-16.

Yin, Z., Rybarczyk, G., Zheng, A., Su, L., Sun, B. Yan, X. (2024). Shared micromobility as a first- and last-mile transit solution? Spatiotemporal insights from a novel dataset. Journal of Transport Geography, 114, 103778.

Zhang, X., Ke, Q., & Zhao, X. (2024). Travel Demand Forecasting: A Fair AI Approach. IEEE Transactions on Intelligent Transportation Systems, 25(10), 14611-14627.

Zhang, X., Zhou, Z., Xu, Y., & Zhao, X. (2024). Analyzing spatial heterogeneity of ridesourcing demand determinants using explainable machine learning. Journal of Transport Geography, 114, 103782.

Resources for PIs:

CETOC Data Management Plan