With growing numbers of intelligent autonomous systems in human environments, the ability
of such systems to perceive, understand, and anticipate human behavior becomes …

In this review, we provide an overview of emerging trends and challenges in the field of
intelligent and autonomous, or self-driving, vehicles. Recent advances in the field of …

In order to drive safely in a dynamic environment, autonomous vehicles should be able to
predict the future states of traffic participants nearby, especially surrounding vehicles, similar …

Motion prediction for the leading vehicle is a critical task for connected autonomous
vehicles. It provides a method to model the leading-following vehicle behavior and analysis …

Lane changing is a critical task for autonomous driving, especially in heavy traffic. Numerous
automatic lane-changing algorithms have been proposed. However, surrounding vehicles …

Intelligent vehicles and advanced driver assistance systems (ADAS) need to have proper
awareness of the traffic context, as well as the driver status since ADAS share the vehicle …

Shared control schemes allow a human driver to work with an automated driving agent in
driver-vehicle systems while retaining the driverʼ s abilities to control. The human driver, as …

Scenario understanding and motion prediction are essential components for completely
replacing human drivers and for enabling highly and fully automated driving (SAE-Level …

In this article, we propose a nonlinear receding horizon game-theoretic planner for
autonomous cars in competitive scenarios with other cars. The online planner is specifically …

This study develops a Complete LAne-Changing Decision (CLACD) modeling framework
that explains both the mandatory and discretionary lane-changing behaviors, incorporates …