Abstract: This study explores disparities in Electric Vehicle (EV) adoption across different socio-economic groups and geographic areas in Texas, focusing on the Texas Triangle (Austin, Houston, San Antonio, and Dallas-Fort Worth). Using EV registration data and hierarchical clustering, the research identified distinct adoption patterns. Tesla emerged as the dominant brand,… read more
Projects
AI-FEED: Prototyping an AI-Powered Platform for the Food Charity Ecosystem
Abstract: This paper introduces AI-FEED, a web-based platform (ai-feed.ai) designed to tackle food and nutrition insecurity within the food charity ecosystem. Using AI and blockchain technology, AI-FEED improves access to nutritious food and optimizes resource allocation, aiming to reduce food waste and enhance community health. It was developed through stakeholder… read more
Toward an equitable transportation electrification plan: Measuring public electric vehicle charging station access disparities in Austin, Texas
Abstract: 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… read more
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
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
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
Evaluating urban fire vulnerability and accessibility to fire stations and hospitals in Austin, Texas
Abstract: Anthropogenic climate change has increased fire frequency and intensity, yet urban fire vulnerability is under-researched. 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… read more
Spatio-temporal patterns of heat index and heat-related Emergency Medical Services (EMS)
Abstract: Research on summertime extreme heat patterns and their link to heat-related Emergency Medical Services (EMS) incidents remains limited, despite rising concerns about heat waves and their health impacts. This study explores spatiotemporal patterns of the heat index (HI) and its relationship to heat-related EMS incidents in Austin-Travis County, Texas,… read more
Exploring Urban Space through AI: Comparative Insights from OpenAI ChatGPT and Google Bard
Abstract: This study compares the abilities of two AI chatbots, OpenAI ChatGPT and Google Bard, to understand urban environments, inspired by Kevin Lynch’s “Image of the City.” We examined their grasp of city landmarks, navigation, and spatial perception. ChatGPT offered factual, generalized responses, while Google Bard provided detailed, immersive answers… read more
Towards AI-Generated Sustainable Cities: An Investigation of GPT-4 and DALL-E in Urban Design
Abstract: This study investigates the potential of AI tools, GPT-4 and DALL-E, in generating sustainable urban design concepts addressing key issues like urban heat islands, walkability, and green spaces. Through a systematic methodology, the study demonstrates the ability of these tools to generate novel ideas, while also revealing limitations in… read more