Valuation of Travel Time and Autonomous Vehicle Features: The Role of Acceptance and Trust in Mode Choice

Abstract

The widespread adoption of autonomous vehicles (AVs) is expected to fundamentally reshape how individuals perceive and value their travel time. However, the psychological constructs that interpret this relationship have not been sufficiently studied. This study examines the influence of attitudinal factors, specifically non-shared autonomous vehicle (NSAV) acceptance and technology trust, on travel time preferences and the Value of Time (VOT) for AVs. Using stated preference (SP) survey data from Oxfordshire and the West Midlands, England, we developed a hybrid choice model (HCM). This model analyzes user choices among four transportation modes: private vehicle (PV), public transit (PT), private autonomous vehicle (PAV), and shared autonomous vehicle (SAV) while including latent psychological constructs derived from attitudinal indicators. The modeling results show that NSAV acceptance is a strong and significant predictor of both PAV and SAV adoption, while trust indicates a significant negative effect on SAV choice, suggesting that concerns about privacy and shared riding reduce willingness to use shared automated services. VOT estimates exhibit meaningful heterogeneity across income, age, and gender, consistent with the model’s socio-demographic interaction structure. In terms of AV features, safety perception emerged as a marginally significant positive attribute, while connectivity and dynamic routing features were found to be statistically insignificant. These findings highlight the importance of including psychological factors alongside conventional travel characteristics when modeling the adoption of AVs and planning for such services, providing practical implications for service providers and policymakers in the design of future autonomous transportation.