Elucidation of user autonomous driving system preference mechanisms under the extension of internal and external factors.

This study is based on the extended Technology Acceptance Model, integrating Habit Theory and Regret Theory to construct a model of users' continuous usage intentions. It conducts a comparative analysis of users' continuous usage intentions for both assisted driving systems and driverless systems. Data was collected through an online questionnaire survey and analyzed using Structural Equation Modeling. The results indicate that, within assisted driving systems, perceived importance and driving habits significantly influence continuous usage intentions; conversely, in driverless systems, driving habits are paramount. In both systems, users' perceived importance and experience of regret have a significant impact on driving habits, with experience of regret indirectly affecting continuous usage intentions through driving habits. User scale exerts direct or indirect effects through various variables. Regarding control variables, significant differences exist between the two systems; users of assisted driving systems prioritize economic benefits, while users of driverless systems focus on after-sales service. This research theoretically establishes a new framework, enriching and refining relevant theories; practically, it provides references for system improvement and promotion; and it suggests avenues for future research into control variables and segmented user groups. The study reveals the driving factors behind users' continuous usage of different driving systems, constructing a universally applicable theoretical model with significant academic and practical implications.