Abstract: This research examines the spatial patterns of transit systems and commuter flows in the Wuhan Metropolitan Area, China, using Baidu users’ location data. It identifies transit deserts that particularly affect low-income commuters. The study reveals several key findings: Firstly, most transit demand originates from trips between neighboring communities, while… read more 

Abstract: This paper examines the travel patterns of 1.7 million shared E-scooter trips in Austin, TX, spanning from April 2018 to February 2019. With over 6,000 active E-scooters monthly, these trips covered approximately 117,000 miles. During this period, the average trip distance was 0.77 miles, lasting 7.55 minutes. Two primary… read more 

Abstract: This study investigates transit deserts in major Chinese cities, inspired by the concept of food deserts. Using open-source data, transit desert areas in Beijing, Shanghai, Wuhan, and Chengdu are identified. Key findings include: (1) Transit deserts are primarily found in city centers, unlike in developed countries such as the… read more 

Abstract: This study examines how neighborhood built environments influence pedestrians’ shopping travel activities in Shanghai, China, a high-density urban setting where walking is a common mode of transportation. Using data from a survey conducted in 2011 across 21 randomly selected neighborhoods, including shopping travel patterns, perceived environmental characteristics, and individual… read more 

Abstract: This study explores how various built environments impact bike-share usage in emerging dock-based systems across three Texas cities. Previous research lacks clarity on whether factors that drive high bicycle usage in large cities also apply to smaller, developing bike-share markets in less densely populated American cities. In Austin and… read more 

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 

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 

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 

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 

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