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Publications
Publications (19)
This paper quantitatively investigates the crash severity of Autonomous Vehicles (AVs) with spatially localized machine learning and macroscopic measures of the urban built environment. We address spatial heterogeneity and spatial autocorrelation, while focusing on land use patterns and human behavior. Our Geographical Random Forest (GRF) model, ac...
This study explores the integration of AI in transportation electrification planning in Austin, TX, focusing on the use of Geospatial AI (GeoAI), Generative AI (GenAI), and Large Language Models (LLMs). GeoAI enhances site selection, localized GenAI models support meta-level estimations, and LLMs enable scenario simulations. These AI applications r...
Public electric vehicle charging stations (EVCSs) are vital for boosting EV adoption. This study investigates Seoul’s public EV charging patterns, taking into account the surrounding urban built environment. We collected built-environment data from land-use maps, Point of Interest (POI) data, and panorama images near public EVCS. The computer-visio...
This study investigates disparities in Electric Vehicle (EV) adoption among different socio-economic groups and geographic areas within Texas. We focused on the Texas Triangle, which includes Austin, Houston, San Antonio, and the Dallas-Fort Worth metropolitan area. Using EV registration data, our study applied unsupervised machine learning techniq...
The deployment of public electric vehicle charging stations (EVCS) is a critical component of transportation electrification. Recent studies have highlighted growing concerns about disparities in accessibility to public chargers between different demographic groups. This research expands ongoing equity concerns by contextualizing existing transport...
Transit deserts refer to regions with a gap in transit services, with the demand for transit exceeding the supply. This study goes beyond merely identifying transit deserts to suggest actionable solutions. Using a multi-class supervised machine learning framework, we analyzed factors leading to transit deserts, distinguishing demand by gender. Our...
Transportation electrification is promoted for its environmental and energy efficiency benefits. However, recent studies examining electric vehicle (EV) adoption have revealed complex patterns influenced by race and income disparities. These studies, primarily based on surveys, often overlook regional ownership variations and built environment meas...
COVID-19 drastically changed human mobility, including bike-sharing usage. Existing studies found positive impacts of COVID-19 on bike-sharing use. However, their analysis focused on the first year of the COVID-19 pandemic. This study traces the effects of COVID-19 by including the bike-sharing data of the second and third years of the pandemic to...
The safety of urban populations sensitive to extreme heat is under increasing threat. Few studies examine the potential benefits of deploying IoT environmental sensors in the urban context and their integration with large-scale human activity data. This paper examines the deployment of IoT sensors in high-resolution extreme heat risk assessment in...
This study explores the socioeconomic disparities observed in the early adoption of Electric Vehicles (EVs) in the United States. A multiagent deep reinforcement learning-based policy simulator was developed to address the disparities. The model, tested using data from Austin, Texas, indicates that neighborhoods with higher incomes and a predominan...
The deployment of public electric vehicle charging stations (EVCS) is a critical component of transportation electrification. Recent studies have highlighted growing concerns of disparities in accessibility to public chargers between different demographic groups. This research expands ongoing equity concerns by contextualizing existing transportati...
Bike-sharing is rapidly gaining popularity due to health, transportation, and recreational benefits. As more people use bike-sharing, the burden of reallocating bikes will increase because of the mismatch between outgoing and incoming bikes. Optimizing truck routes, incentivizing users, and crowdsourcing are common suggestions to mitigate rebalanci...
Cities worldwide have initiated the installation of urban climate sensors to monitor air quality in real time and take proactive measures against the growing threat of climate change. This study focuses on the city of Chicago and utilizes Microsoft’s recently launched Project Eclipse sensors to evaluate air quality status. We extracted surrounding...
The COVID-19 pandemic and social distancing restrictions have had a significant impact on urban mobility. As micro mobility offers less contact with other people, docked or dockless e-scooters and bike-sharing have emerged as alternative urban mobility solutions. However, little empirical research has been conducted to investigate how COVID-19 migh...
The application of IoT in cities is a critical component in constructing a smart city. Seoul Metropolitan Government began installing IoT sensors known collectively as S-DoT in 2019. S-DoT
collects real-time climate and floating population data. This study aims to introduce a smart city planning application in Seoul, to validate the S-DoT applicati...
Dockless electric scooter (E-scooters) services have emerged in the United States as an alternative form of micro transit in the past few years. With the increasing popularity of E-scooters, it is important for cities to manage their usage to create and maintain safe urban environments. However, E-scooter safety in U.S. urban environments remains u...
Transit deserts can result from the inequitable distribution of resources and services, and people living in transit deserts have limited access to transportation system. The aim of this study was to perform spatiotemporal data analysis to identify transit desert areas in Seoul in three steps. First, the transit gap between peak and off-peak hours...
