Autonomous vehicles are expected to become an inevitable reality in the coming years, as their uncovered benefits are increasingly proven to be positive, such as increased safety and traffic efficiency. However, their impacts on travel choices have often been represented with an assumed reduction in the travel time penalty, which oversimplified AVs' subsequent effects activity-travel scheduling choices. As such, models and assessment methods do not accurately represent travel behavior implications of autonomous vehicles. Thus, using survey data, this thesis identifies possible rearrangements in activity-travel schedules, classifies the respondents into classes with similar profiles of expected rearrangements, and identifies further classification on the basis of socio-economic, personal, and travel characteristics. The survey to be used is one in which respondents were asked to report a full, regular working day activity schedule using their currently preferred mode of transport, then report the schedule as they expect it to be if they could use an autonomous vehicle. The initial exploration of the data identified the occurrence of activities on-board (work, spare-time, meals, and getting ready), changes to the duration of activities outside travel, as well as travel (delay of work-bound trips, and advancement of home-bond trips). Next, we used latent class models to cluster the responses with respect to on-board activity duration changes, stationary activity duration changes, and travel departure time changes. The clustering uncovered types of classes: no change, single activity on-board (work and spare-time), multiple activities on-board. Interactions between stationary and on-board activities were identified, with some direct activity transfer to travel episodes being common (with work, meals, and getting ready), while other activities were generally not transferred (spare-time). Finally, the addition of personal characteristics and demographics highlighted the limited influence of socio-economic factors, with the exception of education, on activity changes. In contrast, the most significant factors were mostly associated with work (daily time pressure and the ability to do work in the car) and travel time duration. An important insight uncovered was that the travel changes were limited and not as dramatic as expected, highlighting that the value of time impacts alone are not as representative as expected.