In recent years, autonomous vehicles (AVs), which observe the driving environment and
lead a few or all of the driving tasks, have garnered tremendous success. The field of AVs …

Automated vehicles (AVs) must be thoroughly evaluated before their release and
deployment. A widely used evaluation approach is the Naturalistic-Field Operational Test (N …

This article reviews data-centric approaches for statistical modeling of driver behavior.
Modeling driver behavior is challenging due to its stochastic nature and the high degree of …

Intelligence in vehicles has developed through the years as self-driving expectations and
capabilities have increased. To date, the majority of the literature has focused on …

Lane changes are stressful maneuvers for drivers, particularly during high-speed traffic
flows. Advanced driver-assistance systems (ADASs) aim to assist drivers during lane …

Proactive lane-changing (LC) risk prediction can assist driver's LC decision-making to
ensure driving safety. However, most previous studies on LC risk prediction did not consider …

Autonomous vehicles must be comprehensively evaluated before deployed in cities and
highways. However, most existing evaluation approaches for autonomous vehicles are static …

This study aims to investigate the contributing factors affecting the occurrence of crashes
while lane-changing maneuvers of drivers. Two different data sets were used from the same …

Lane change has been recognized as a challenging driving maneuver and a significant
component of traffic safety research. Develo** a real-time continuous lane change …

Estimating a driver's lane-change (LC) intent is very important so as to avoid traffic accidents
caused by improper LC maneuvers. This paper proposes a lane-change Bayesian network …