Distraction, misjudgement and driving mistakes can significantly affect a driver, resulting in
an increased risk of accidents. There are diverse factors that can cause mistakes in driving …

The impacts of climate change, especially sea-level rise, are an increasing threat to the
world's coastal regions. Following recommendations made by the United Nations about the …

Trust calibration poses a significant challenge in the interaction between drivers and
automated vehicles (AVs) in the context of human-automation collaboration. To effectively …

This report aims to advance the discussion on those fundamental aspects to be considered
in order to have trustworthy Artificial Intelligence (AI) systems in the Automated/Autonomous …

The present online study surveyed drivers of SAE Level 2 partially automated cars on
automation use and attitudes towards automation. Respondents reported high levels of trust …

We introduce a novel capabilities-based bi-directional multi-task trust model that can be
used for trust prediction from either a human or a robotic trustor agent. Tasks are …

As vehicle driving evolves from human-controlled to autonomous, human–machine
interaction ensures intuitive usage as well as the feedback from vehicle occupants to the …

The performance of a driving automation system (DAS) can influence the human drivers'
trust in the system. This driving-simulator study examined how different types of DAS failures …

Recent advances in AI technologies are dramatically changing the world and impacting our
daily life. However, human users still essentially need to cooperate with AI systems to …

Objective This paper proposes an objective method to measure and identify trust-change
directions during takeover transitions (TTs) in conditionally automated vehicles (AVs) …