The COVID-19 outbreak significantly disrupted urban mobility across the world and affected people’s travel behaviors. This paper aims to explore the relationship between socio-demographic and health factors and changes in travel behavior during the second phase of this outbreak. We proposed two measures to assess these changes: (i) whether an individual reduced the number of trips to stores during the second phase of the pandemic and (ii) whether an individual reduced the number of trips by public transport during this period. Two binary logit models were estimated based on survey data from the United States Census Bureau. The results indicate that all variables, including age, gender, educational status, marital status, work loss, difficulty with expenses, household size, work type, income, health status, and anxiousness were significantly associated with changes in travel behavior.

Although studies have previously investigated the spatial factors of COVID-19, most of them were conducted at a low resolution and chose to limit their study areas to high-density urbanized regions. Hence, this study aims to investigate the economic-demographic disparities in COVID-19 infections and their spatial-temporal patterns in areas with different population densities in the United States. In particular, we examined the relationships between demographic and economic factors and COVID-19 density using ordinary least squares, geographically weighted regression analyses, and random forest based on zip code-level data of four regions in the United States. Our results indicated that the demographic and economic disparities are significant. Moreover, several areas with disadvantaged groups were found to be at high risk of COVID19 infection, and their infection risk changed at different pandemic periods. The findings of this study can contribute to the planning of public health services, such as the adoption of smarter and comprehensive policies for allocating economic recovery resources and vaccines during a public health crisis.

Over the past few years, increased e-scooter ridership has raised concerns about the growing number of injury accidents involving e-scooters. Additionally, given the lack of appropriate e-scooter a...

Roundabouts are considered as one of the most efficient forms of intersection that substantially reduce the types of crashes that result in injury or loss of life. Nevertheless, they do not eliminate collision risks, especially when human error plays such a large role in traffic crashes. In this study, we used a driving simulator and an eye tracker to investigate drivers’ eye movements under cell phone-induced distraction. A total of 45 drivers participated in two experiments conducted under distracted and non-distracted conditions. The results indicated that, under distracting conditions, the drivers’ fixation duration decreased significantly on roundabouts, and pupil size increased significantly.

The COVID-19 outbreak posed a considerable risk to the health of people in the US and across the world. To reduce its spread, various companies in America adopted a range of preventive measures, such as telework, for the majority of their workforces. Considering that these measures have disproportionate effects on individuals, this study examined the potential relationship between socio-economic characteristics and telework status in the United States through mixed logit models developed in this research. Results indicated that telework status was significantly associated with the majority of the variables used in the models, namely, age, gender, educational status, marital status, difficulty with expenses, household size, work type, and anxiety.

The pandemic arising from the 2019 coronavirus disease has significantly affected all facets of human life across the world, including economies and transportation systems, thereby changing people’s travel behaviors. This research was aimed at exploring the relationship between socio-economic factors and e-scooter trip durations before and during the pandemic. We developed a hazard-based duration approach and estimated multiple spatial and non-spatial models on the basis of 2019 and 2020 dockless e-scooter data collected from the City of Austin’s Open Data Portal. The results indicated an overall increase in e-scooter trip durations after the pandemic. Moreover, analysis of variables revealed potential changes in users’ behavior before and during the pandemic. In particular, whereas e-scooter trip durations were found to be positively associated with aggregate travel time to work before the pandemic, this trend was reversed during the pandemic. In addition, during the pandemic, e-scooter travel time was positively correlated with the ratio of individuals with bachelor’s degrees or greater to those with associate degrees or lower. However, no specific pattern was observed before the pandemic. Lastly, the results showed the presence of disparities within the study area; therefore, it is vital to extend e-scooter service areas to cover underserved communities.