Automated vehicles (AVs) have the potential to change the way we travel within our cities. However, the conditions under which consumers will adopt AVs are poorly understood. An internet-based survey was conducted in the Greater Toronto and Hamilton Area to understand how consumers will respond to automated vehicles. This study estimates the effect of demographic characteristics, travel characteristics, and built-environment variables on respondent’s willingness to pay for private autonomous vehicles and frequency of use for shared autonomous vehicles under different pricing levels. The results indicate that having a higher household income and owning a more expensive vehicle are good predictors of interest in PAVs, whereas individuals who experienced more car accidents as a passenger and individuals who commute using public transit or walk/cycle are more interested in SAVs. Regional rail users, Uber users, and younger respondents were interested in both ownership models. This provides insight to help policymakers advance transportation policies and collective social goals.