Objective: This article provides a review of empirical studies of automated vehicle takeovers
and driver modeling to identify influential factors and their impacts on takeover performance …

Lane changes are complex driving behaviors and frequently involve safety–critical
situations. This study aims to develop a lane-change-related evasive behavior model, which …

Current advanced driver assistance systems (ADASs) do not consider drivers' preferences of
evasive behavior types and risk levels under rear-end near-crash scenarios, which …

This study aimed at modeling the Response Time (RT) and Total Braking Time (TBT) of
drivers under Partial Sleep Deprivation (PSD). Fifty male participants drove the driving …

Objective This paper aims to describe and test novel computational driver models, predicting
drivers' brake reaction times (BRTs) to different levels of lead vehicle braking, during driving …

Objective The paper presents a systematic analysis of drivers' crash avoidance response
during crashes and near-crashes and developed a machine learning-based predictive …

Predicting driver rear‐end risk‐avoidance maneuvers in cut‐in scenarios, especially
dangerous precrash scenarios, benefits the customization of automatic driving, particularly …

Cooperative adaptive cruise control is recognised as an effective means to reduce the rear‐
end collision caused by the delayed reaction and improper driving behaviours of manually …

Abstract Autonomous capabilities, including Autonomous Vehicle (AV) technology, aim to
reduce human effort, extend capabilities, and enhance safety. While AVs offer societal …

The influence of (cooperative) adaptive cruise control (CACC/ACC) on rear-end crashes
have been conducted by some previous studies. However, they usually did not consider the …