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The COVID-19 pandemic has impacted billions of people around the world. To capture some of these impacts in the United States, we are conducting a nationwide longitudinal survey collecting information about activity and travel-related behaviors and attitudes before, during, and after the COVID-19 pandemic. The survey questions cover a wide range of topics including commuting, daily travel, air travel, working from home, online learning, shopping, and risk perception, along with attitudinal, socioeconomic, and demographic information. The survey is deployed over multiple waves to the same respondents to monitor how behaviors and attitudes evolve over time. Version 1.0 of the survey contains 8,723 responses that are publicly available. This article details the methodology adopted for the collection, cleaning, and processing of the data. In addition, the data are weighted to be representative of national and regional demographics. This survey dataset can aid researchers, policymakers, businesses, and government agencies in understanding both the extent of behavioral shifts and the likelihood that changes in behaviors will persist after COVID-19.

Understanding people's travel behavior is necessary for achieving goals such as increased bicycling and walking, decreased traffic congestion, and adoption of clean-fuel vehicles. To understand underlying motivations, researchers increasingly are adding subjective variables to models of travel behavior. This article presents a systematic review of 158 such studies. Nearly every reviewed article finds subjective variables to be predictive of transport outcomes. However, the 158 reviewed studies include 2864 distinct subjective survey questions. This heterogeneity makes it difficult to reach definitive conclusions about which subjective variables are most important for which transport outcomes. In addition to heterogeneity, challenges of this literature also include an unclear direction of causality and tautological relationships between some subjective variables and behavior. Within the constraints imposed by these challenges, we attempt to evaluate the explanatory power of subjective variables, which subjective variables matter most for which transport choices, and whether the answers to these questions vary between continents. To reduce heterogeneity in future studies, we introduce the Standardized Transport Attitude Measurement Protocol, which identifies a curated set of subjective questions. We have also developed an open-access database of the reviewed studies, including all subjective survey questions and models, with an interactive, searchable interface. Keywords Attitudes • Perceptions • Travel choice • Travel behavior • Factor analysisNathan Harness and Alexis Consalvo have contributed equally.

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The COVID-19 pandemic has brought about transformative changes in human activity-travel patterns. These lifestyle changes were naturally accompanied by and associated with changes in transportation mode use and work modalities. In the United States, most transit agencies are still grappling with lower ridership levels, thus signifying the onset of a new normal for the future of transit. This paper addresses this challenge using a novel panel survey data set collected from a representative sample of individuals across the United States. The study involved the estimation of a panel multinomial probit model of mode choice to capture both socio-economic effects and period (pre-, during-, and post-COVID) effects that contribute to changes in mode choice. This paper provides rich insights into the evolution of commute mode use as a result of the pandemic, with a particular focus on public transit. Through a rigorous modeling approach, this paper provides a deep understanding of how transit use has evolved, how it is likely to evolve into the future, and the socio-economic and demographic characteristics that affect the evolution (and expected future use) of public transit. Results suggest that transit patronage is likely to remain depressed by about 30% for the foreseeable future, in the absence of substantial changes in service configurations. This study also shows that minority groups and those living in higher density regions are more likely to exhibit a return to transit use in the post-pandemic period.

Urban roadways are used inefficiently, with capacity scaled to meet peak demands and underutilization at off-peak hours. The COVID-19 pandemic has significantly disrupted the transportation system, and one possible outcome is a spreading of rush hour. We use six years of highway sensor data from the California state highway system to evaluate that possibility, and find that peaks are spreading in the post-lockdown period, the spreading is statistically significant, and has been relatively stable since summer 2021. Spreading of peak travel periods calls into question highway expansion plans based on pre-pandemic travel forecasts.