UT Shield

, Filed Under: News & Events

The latest EV research by UIL has been published in PLOS ONE

This research examines disparities in access to public electric vehicle charging stations (EVCS) in Austin, Texas, highlighting transportation equity concerns. Using threshold equity toolkits and regression analysis, the study explores how race and income impact public charger access. The findings show that most EVCSs are located in areas where the… read more 

, Filed Under: News & Events

Smart Mobility & AI Symposium

About the event: The Smart Mobility and AI Symposium will be a day-long gathering of UT students and interdisciplinary professionals across academia and industry to inform, examine, and discuss how Autonomous Vehicles (AV), Electric Vehicles (EV), and Artificial Intelligence (AI) impact transportation system and urban climate. This symposium aims to… read more 

, Filed Under: News & Events

Welcome to join UIL, Ahyoung!

We are excited to introduce Ahyoung Chang, the newest Ph.D. student in the Community and Regional Planning (CRP) program at the University of Texas at Austin. We are pleased to welcome her to our lab! Ahyoung specializes in urban informatics, urban form, the built environment, walkability, and livability. Her research… read more 

, Filed Under: News & Events

AI Tackles Transit Deserts: New Interactive Dashboard Featured in PLOS ONE

UIL’s latest research project, “Developing a Transit Desert Interactive Dashboard: Supervised Modeling for Forecasting Transit Deserts,” was recently published in the journal PLOS ONE. In an exciting development, the Urban Info Lab (UIL) has published a groundbreaking study in the prestigious journal PLOS ONE. Titled “Developing a Transit Desert Interactive… read more 

, Filed Under: Projects

Developing a transit desert interactive dashboard: Supervised modeling for forecasting transit deserts

Abstract: Transit deserts are areas where transit demand exceeds supply. This study not only identifies these regions but also proposes actionable solutions using a multi-class supervised machine learning framework. Focusing on peak times and gender differences in demand, the study evaluated several models and selected the Random Forest method. Key… read more 

, Filed Under: Projects

Uncovering electric vehicle ownership disparities using K‑means clustering analysis: A case study of Austin, Texas

Abstract: Transportation electrification is promoted for its environmental benefits, but EV adoption shows complex patterns influenced by race and income disparities. Recent studies often overlook regional ownership variations and urban form measures. This study uses actual EV registration data with spatial analyses, revealing an East–West divide in Austin. West Austin… read more 

, Filed Under: Projects

Spatio-temporal patterns of heat index and heat-related Emergency Medical Services (EMS)

Abstract: This study investigates the patterns of extreme heat during summers and their link to heat-related Emergency Medical Services (EMS) incidents in Austin-Travis County, Texas, focusing on 2020 and 2021. Analyzing 47,838 heat-related EMS cases, the research identifies significant correlations between high heat index (HI) frequency/intensity and increased EMS incidents,… read more 

, Filed Under: Projects

Evaluating urban fire vulnerability and accessibility to fire stations and hospitals in Austin, Texas

Abstract:  This study identifies fire vulnerability patterns, maps high-risk areas with limited access to fire stations and hospitals, and determines factors contributing to increased fire incidents. A fire vulnerability index was developed using health and socio-environmental factors, while accessibility to resources was assessed through E2SFCA analysis. OLS and GWR regression… read more