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Users’ Trust Evolvement in Fully Driverless Robotaxis During First Ride: An On-Road Study

Zhenyu Wang et al.

Human Factors2026https://doi.org/10.1177/00187208261420147article
AJG 3
Weight
0.50

What the paper says

ObjectiveThis study investigates how users' trust evolves during their first ride in a fully driverless robotaxi and how it can be affected by user characteristics, system design, and traffic scenarios.BackgroundAs driving automation technology matures, driverless robotaxis have become available. Despite its immense economic and social potential, public acceptance can be strongly influenced by user trust. Previous research on trust in autonomous vehicles often relied on surveys, driving simulators, or "Wizard of Oz" methods, potentially introducing biases.MethodAn on-road experiment was conducted in commercially operating fully driverless robotaxis on public urban roads. In total, 30 participants with no prior experience riding fully driverless robotaxis were recruited, comprising nondrivers (n = 10), and drivers with (n = 10) and without (n = 10) driving automation experience. Dynamic trust was collected at a 2-min interval during the ride, along with participants' think-aloud for changes in trust. A cumulative link mixed model was used to assess the impact of past driving experience, demographics, and riding time on trust development.ResultsOur findings revealed that dynamic trust increased gradually and stabilized over time, with user heterogeneity playing a moderating role in this process. Further think-aloud data analysis identified key factors in trust formation, including driving style, riding safety and comfort, and user interface design.ConclusionTrust in driverless robotaxis builds progressively with real-world exposure, shaped by user characteristics, vehicle control, and interface design.ApplicationOur findings underscore the importance of considering user heterogeneity in fostering trust and acceptance of robotaxis.

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https://doi.org/https://doi.org/10.1177/00187208261420147

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@article{zhenyu2026,
  title        = {{Users’ Trust Evolvement in Fully Driverless Robotaxis During First Ride: An On-Road Study}},
  author       = {Zhenyu Wang et al.},
  journal      = {Human Factors},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1177/00187208261420147},
}

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Users’ Trust Evolvement in Fully Driverless Robotaxis During First Ride: An On-Road Study

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.