Use of travel time in a shared automated vehicle for work and leisure: Results from a field experiment with a Wizard-of-Oz simulator-on-wheels vehicle
Abstract
Shared automated vehicles (SAVs) have the potential to transform travel by enabling users to engage in a wide range of non-driving-related tasks (NDRTs), enhancing productivity and travel satisfaction. To explore this potential, we conducted a field experiment using a Wizard-of-Oz simulator-on-wheels vehicle replicating SAV services in urban areas. The study examined how engaging in work and leisure NDRTs influenced attitudes and preferences for SAVs versus conventional transport modes (public transport (PT), conventional cars, and bicycles) and associated values of travel time (VoTTs). A total of 104 participants completed two test rides while engaging in work and leisure activities, with engagement levels captured via video. Field study results showed that participants preferring work over leisure inside SAVs had a more positive perception of travel time in them post-test. Whilst, high levels of NDRT engagement during test rides increased the dissatisfaction with travel time in traditional PT, highlighting SAVs’ potential to shift preferences. Experience with NDRTs also reduced the negative perception of car travel costs, aligning this perception with that of SAVs post-test. This adjustment caused a shift in VoTTs: while SAVs initially held the highest values, test rides elevated VoTTs for conventional cars – previously lower and on par with PT – to match those of SAVs for leisure-oriented participants. However, for work-oriented participants, SAVs had significantly lower VoTTs than cars, underscoring their advantage for productivity-focused travel. Finally, the experiment demonstrated the relevance of the Wizard-of-Oz approach for simulating realistic SAV experiences, with 74% of participants believing the setup was genuine.
Fields of Study & Subjects
Transportation and Mobility Innovations
Human-Automation Interaction and Safety
Transportation Planning and Optimization
Publication details
- Journal / source
- Transportation Research Part C Emerging Technologies
- Volume
- 188
- Pages
- 105646–105646
- Publication date
- 21 April 2026
- Language
- EN