Disruptions in Transportation: Understanding Attitudinal and Behavioral Implications

The past two decades have been marked by disruptions in the way transportation is provided to society. Examples are carsharing, ridehailing services, and electric scooters. Understanding how sensitive travel behavior is during transportation disruptions is a key part of planning for the future of transportation. While the effects of people's attitudes and perceptions on travel behavior and choices have been studied in the past, their role in response to disruptions remains under explored. This dissertation explores the effect of attitudes on travel behavior and perceptions for two distinct disruptions: the advent of autonomous vehicles (AVs) and the COVID-19 pandemic. Before diving into such elaborate relationships, it is important to understand how attitudinal data is collected and measured. Thus, a study of the effects of different survey methods on the collection of attitudes towards transportation disruptions is performed. This dissertation finds that having a favorable perception of AVs is the most important factor in defining one’s willingness to use them. More importantly, those who only heard about AVs without knowing much about them were actually less likely to have a favorable perception when compared to those who never heard of AVs prior to the survey, reinforcing the need for thoughtful education and awareness initiatives. Additionally, gender also played an important role in expectations about the AV Future: not only are women less interested in using AVs as a pooled ride service, but also that the effect of attitudes on defining that choice was different for men and women. Regarding the COVID-19 pandemic, two different attitudes towards COVID were identified: concern about the effects of the COVID-19 response, and concern about the health effects of the coronavirus. Both shaped the ways people traveled, and how often they did so. These findings reinforce the need for the broad collection of attitudinal data and the incorporation of such parameters on future travel forecasting.