People’s Preferences in the Adoption of New Mobility Technologies: A Case Study of Puget Sound Region

This is a study where U.S cities are classified according to their demographics, transportation modes and the number of shared bikes and vehicles using hierarchical clustering and principle component analysis. An MNL model is developed using the Puget Sound Regional Council Household Travel Survey in addition to other land use and trip characteristics. After that, several Probit models were developed to test the factors affecting people’s interests and concerns regarding AV technology using the same survey. It was found that US cities fall into four clusters with the majority of US cities fell into one cluster because of their suburban planning and their auto-centric transportation systems. The Multinomial Logit model explores the mode choice in Seattle, an outstanding city and is known for its multimodality. It was found what previous literature points out to the factors affecting the mode choice, which are personal, household, trip, and land use variable. In the end, an order probit model was developed to model the factors affecting the level of interests and concerns towards Autonomous vehicles.