Abstract: This study aimed to identify areas in the US needing both transit improvements and anti-displacement protection. Instead of solely focusing on transit-dependent populations, a new method was developed to consider overall transportation demand among independent residents compared to public transit supply. Transit deserts in metro areas were analyzed using… read more
Projects
Exploring the factors affecting travel behaviors during the second phase of the COVID-19 pandemic in the United States
Abstract: This paper examines the impact of socio-demographic and health factors on changes in travel behavior during the second phase of the COVID-19 outbreak. Two measures were proposed: reduction in trips to stores and reduction in trips by public transport. Using survey data from the United States Census Bureau, binary… read more
Measuring travel behavior in Houston, Texas with mobility data during the 2020 COVID-19 outbreak
Abstract: The study analyzes travel patterns in Houston, Texas during COVID-19 using an autoregressive distributed lag model. Findings reveal that visit patterns and changes in COVID-19 cases from the previous week heavily influence behaviors in the following week. Factors such as unemployment claims, median minimum dwell time, and workplace visit… read more
An Open-Source Framework for Last Mile Delivery with Heterogeneous Robots
Abstract: The SMADS project at the University of Texas at Austin develops software for autonomous robot deliveries on campus. It integrates various subsystems like autonomy, scheduling, interface, and a customer app. The study reports on delivering lemonade outdoors to campus buildings and highlights advancements in integrating end-users and robot autonomy… read more
Estimating E-Scooter Traffic Flow Using Big Data to Support Planning for Micromobility
Abstract: The paper introduces a practical method for estimating e-scooter flow patterns using open datasets that track trip origins and destinations. By leveraging this data, the authors demonstrate how their models can assist cities in optimizing support for shared micromobility services. Additionally, the generated information can enhance the analysis of… read more
The impact of street characteristics on older pedestrians’ perceived safety in Shanghai, China
Abstract: This study explores how street characteristics affect perceived safety among older pedestrians in Shanghai, China, considering the influence of land-use patterns and urban sprawl. Using a mix of quantitative and qualitative methods, 68 elderly urban residents participated in a survey using simulated streetscape images. Findings from ordinal logit regression… read more
From shared micro-mobility to shared responsibility: Using crowdsourcing to understand dockless vehicle violations in Austin, Texas
Abstract: In recent years, dockless small vehicles have surged in progressive U.S. cities as a car-free travel alternative for short distances. However, little is known about the social impact of this influx on public space. This study examined 4,100 parking violation reports in Austin, Texas, sourced from the Austin 311… read more
Dockless E-scooter usage patterns and urban built Environments: A comparison study of Austin, TX, and Minneapolis, MN
Abstract: Recent years have witnessed a rise in dockless shared electric scooters (e-scooters) in American cities, offering a solution for short-distance car trips. However, research on e-scooter usage patterns and their urban connection is lacking. This study addressed this gap by analyzing e-scooter ridership in Austin and Minneapolis. Results revealed… read more
Longitudinal Social Impacts of HRI over Long-Term Deployments
Abstract: The Longitudinal Social Impacts of HRI over Long-Term Deployments Workshop aims to unite researchers focusing on comprehensively understanding such deployments. This includes those studying longitudinal human-robot interaction, long-term autonomy, and real-world deployments. The workshop aims to advance the study of how deployed robot systems influence both individuals interacting with… read more
Socio-economic Factors and Telework Status in the US during the COVID-19 Pandemic
Abstract: This study explores the impact of COVID-19 preventive measures, like telework, on individuals in the United States. Using mixed logit models, it analyzes the relationship between socio-economic factors and telework status. Results suggest a significant association between telework and various variables, including age, gender, education, marital status, financial strain,… read more