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

By the year 2045, it is projected that Autonomous Vehicles (AVs) will make up half of the
new vehicle market. Successful adoption of AVs can reduce drivers' stress and fatigue, curb …

Automated vehicles alleviate the need for driver attention and control. However, a takeover
request (TOR) to the driver remains essential for emergencies and safety–critical scenarios …

Objective This study develops a computational model to predict drivers' response time and
understand the underlying cognitive mechanism for freeway exiting takeovers in …

Construction noise is a pervasive and influential source of stress for urban residents and can
lead to various health problems, including hormonal dysfunction and cardiovascular …

The modeling of distracted driving behavior has been studied for many years, however,
there remain many distraction phenomena that can not be fully modeled. This study …

Partially automated systems are expected to reduce road crashes related to human error,
even amongst professional drivers. Consequently, the applications of these systems into the …

The driver's takeover time is crucial to ensure a safe takeover transition in conditional
automated driving. The study aimed to construct a prediction model of driver's takeover time …

Humans' internal states play a key role in human-machine interaction, leading to the rise of
human state estimation as a prominent field. Compared to swift state changes such as …

Take-over performance plays a significant role in evaluating drivers' state, and serves as a
crucial reference for enhancing control transitions in the context of conditionally automated …