With rapid advances in technology development and public adoption, it is crucial to understand how these services will shape the future of travel depending on the extent to which people will use these services; impact the transportation and infrastructure systems such as changes in the use of transit and active modes of travel; and influence how technology developers create and update these transportation technologies to better serve people’s mobility needs. This dissertation explores how two major emerging services, namely ridehailing services and autonomous vehicles (AVs), will be used in the future when they are widely available and vastly used, and how they may impact the transportation infrastructure and societal travel patterns. The four proposed chapters use comprehensive quantitative and qualitative methods to explore the status of these technologies from theory, through robust modeling frameworks, to practice, by investigating the recent AV pilot deployments in real-world settings. In the second chapter, it was found that increased frequency of ridehailing use is significantly associated with a decrease in bus usage, suggesting that ridehailing functions more as a substitute for buses than as a complement and implying that transit agencies should explore ways to incorporate ridehailing services in their plans to enhance transit usage. Next, the third chapter showed that interest in using AVs for running errands had a positive and significant effect on AV ownership intent, even after accounting for a host of variables. The fourth chapter depicted how ridehailing experiences have a considerable effect on the willingness to ride AV-based services in both private and shared modes, suggesting that experience is crucial for future adoption of these services. Then, two recent real-world AV experiences are explored in the fifth chapter. Lessons learned from these experiments reinforced the importance of first-hand experiences in promoting AV awareness and trustworthiness, potentially leading to greater degrees of adoption. Finally, the results and discussions presented in this dissertation strengthen the body of literature on key emerging transportation technologies and inform policymakers and stakeholders to properly prepare cities and the public to welcome these technologies into our transportation system in an efficient, equitable, and complementary way.

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.