UNDERSTANDING BEHAVIORAL INTENTION AND ADOPTION OF AUTOMATED VEHICLES IN CANADIAN CENSUS METROPOLITAN AREAS

Abstract

Sharing automated vehicles (AVs) is a possible future, where shared automated vehicles (SAVs) and pooled automated vehicles (PooledAVs) are prospective on-demand AV configurations. While SAVs and PooledAVs can contribute to the sustainability of transport systems, the success of on-demand AVs depends on whether and how the public adopts them as regular travel modes. As such, this dissertation investigates five objectives: (1) to scrutinize the essential steps of designing a future mobility survey , while the primary focus of the survey is on respondents’ intentions to adopt various AV configurations (2) to propose and validate a theoretical model for on-demand AV adoption by extending the Theory of Planned Behavior (TPB), (3) to identify the prospective use cases of SAVs as the potential precursor of on-demand AVs, (4) to identify individual characteristics that may trigger different behavioral intentions among the on-demand AV service types, and finally (5) to investigate Canadians’ intentions to adopt on-demand AVs. A nationwide Canadian survey was designed and administered in fall 2021 (n = 5002) among adults (18 to 75 years old) residing in six major Canadian metropolitan areas: Toronto, Vancouver, Ottawa-Gatineau, Montréal, Calgary, and Hamilton. The findings of this dissertation paint a complex picture of on-demand AV adoption in the Canadian context with respect to the application of constructs from common technology adoption models and will help researchers investigating the characteristics of prospective consumers of on-demand AVs to identify the importance of affective motivations regarding adopting such emerging travel modes. The results reveal that many Canadians are yet either uncertain or reluctant to adopt AV technology in shared mobility services. In this light, policymakers and planners should adjust and moderate their expectations regarding the future market for on-demand AVs and be prepared for potential changes in travel behavior by examining incremental changes in existing on-demand ride-hailing services.