Trust miscalibration issues, represented by undertrust and overtrust, hinder the interaction
between drivers and self-driving vehicles. A modern challenge for automotive engineers is …

Driver state monitoring (DSM) systems aim to measure driver/occupant state, considering
factors such as fatigue, workload, attentiveness, and wellbeing. They are influential for some …

There is a growing use of intelligent systems to support human decision-making across
several domains. Trust in intelligent systems, however, is pivotal in shaping their widespread …

Stakeholders in the field of automated vehicles (AVs)—from developers to the general public—
seek confidence in the safety of these machines. In summer 2019, the Uber Advanced …

Level 3 automated vehicles (L3 AVs) enable the driver to perform non-driving tasks, taking
over in an emergency. In recent years, studies have extensively discussed the influencing …

Automated vehicles (AVs) that intelligently interact with drivers must build a trustworthy
relationship with them. A calibrated level of trust is fundamental for the AV and the driver to …

Human-robot teams have the ability to perform better across various tasks than human-only
and robot-only teams. However, such improvements cannot be realized without proper task …

Unmanned ground vehicles (UGVs) are autonomous robots capable of performing tasks
through self-navigation and decision-making. They have the potential to replace humans in …

Human-robot teams can leverage a human's expertise and a robot's computational power to
meaningfully improve mission outcomes. In command and control domains, the robot …

The human-robot interaction (HRI) community is interested in a range of research questions,
many of which are investigated through user experiments. Robots that occasionally require …