Abstract
Automated vehicles (AVs) may transform not only our travel experience but our complete daily schedules. This study analyses the data from an interactive stated activity-travel survey using latent class cluster analysis to uncover the types and prevalence of schedule changes with AVs. The analysis reveals that the majority of respondents expected little to no changes in their schedules. Importantly however, these responses are correlated with low commitment to the survey, evident in unrealistically short response times to non-central survey parts and simpler representations of their current schedules. The remaining responses reveal significant and varied changes in activities on board and outside travel, and in commute departure times. We conclude that the prevalence of schedule changes may be underestimated in our and possibly other AV studies due to low survey commitment. Our findings also highlight diverse potential motivations behind schedule changes with AVs: while some travellers may desire to free up time for other activities during the day (time saving), others may satisfy an unmet activity need by engaging in on-board activities (time spending). Considering this heterogeneity is crucial in endeavours to quantify the total benefits and costs that automated vehicles will bring to their users.
Original language | English |
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Article number | 104006 |
Pages (from-to) | 1-22 |
Journal | Transportation Research Part A: Policy and Practice |
Volume | 182 |
DOIs | |
Publication status | Published - 2024 |
Bibliographical note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Keywords
- Automated vehicles
- Time use
- Activity schedules
- On-board activities
- Latent class clustering