RESUMO
COVID-19 has upended travel across the world, disrupting commute patterns, mode choices, and public transit systems. In the United States, changes to transit service and reductions in passenger volume due to COVID-19 are lasting longer than originally anticipated. In this paper we examine the impacts of the COVID-19 pandemic on individual travel behavior across the United States. We analyze mobility data from Janurary to December 2020 from a sample drawn from a nationwide smartphone-based panel curated by a private firm, Embee Mobile. We combine this with a survey that we administered to that sample in August 2020. Our analysis provides insight into travel patterns and the immediate impacts of the COVID-19 pandemic on transit riders. We investigate three questions. First, how do transit riders differ socio-demographically from non-riders? Second, how has the travel behavior of transit riders changed due to the pandemic in comparison to non-riders, controlling for other factors? And third, how has this travel behavior varied across different types of transit riders? The travel patterns of transit riders were more significantly disrupted by the pandemic than the travel of non-riders, as measured by the average weekly number of trips and distance traveled before and after the onset of the pandemic. This was calculated using GPS traces from panel member smartphones. Our survey of the panel revealed that of transit riders, 75% reported taking transit less since the pandemic, likely due to a combination of being affected by transit service changes, concerns about infection risk on transit, and trip reductions due to shelter-in-place rules. Less than 10 percent of transit riders in our sample reported that they were comfortable using transit despite COVID-19 infection risk, and were not affected by transit service reductions. Transit riders were also more likely to have changed their travel behavior in other ways, including reporting an increase in walking. However, lower-income transit riders were different from higher-income riders in that they had a significantly smaller reduction in the number of trips and distance traveled, suggesting that these lower-income households had less discretion over the amount of travel they carried out during the pandemic. These results have significant implications for understanding the way welfare has been affected for transportation-disadvantaged populations during the course of the pandemic, and insight into the recovery of U.S. transit systems. The evidence from this unique dataset helps us understand the future effects of the pandemic on transit riders in the United States, either in further recovery from the pandemic with the anticipated effects of mass vaccination, or in response to additional waves of COVID-19 and other pandemics.
RESUMO
This paper presents the design, analysis and results of a driving simulator experiment conducted to study the interaction between drivers and pedestrians in a mixed-street environment. Ninety-six students of the American University of Beirut (AUB) participated in the experiment that took place in the Transportation and Infrastructure Laboratory of AUB. The study looked at the driver-pedestrian interaction from the driver's perspective, by quantifying the effects of different scenario variables on the driving behavior of the participants. Kruskall-Wallis test shows that drivers' behavior in proximity of pedestrians tends to be statistically significantly less aggressive when their approach velocity is lower, curb-side parking is not allowed, a crosswalk exists, and the number of pedestrians crossing the street is higher. A discrete choice model for the yielding behavior of the drivers was also developed as a function of different predictor variables. Five out of the six predictors considered (except for gender) had a statistically significant effect on the yielding behavior, particularly the effects of curb-side parking, number of pedestrians crossing, and approach velocity. The model was then used to evaluate the effect of policy variables on the yielding probabilities of the drivers. The results of this study enrich current knowledge and understanding of drivers' behavior and their interaction with pedestrians, especially with studying the effects of scenario variables that were not addressed before; this would help planners propose and evaluate safety measures and traffic calming techniques to reduce the risks on pedestrians. The study also confirms the effectiveness of driving simulators in studying driver-pedestrian interactions.