Traffic crashes, heavy congestion, and discomfort often occur on rough pavements due to
human drivers' imperfect decision-making for vehicle control. Autonomous vehicles (AVs) …

Autonomous lane changing is a critical feature for advanced autonomous driving systems,
that involves several challenges such as uncertainty in other driver's behaviors and the trade …

Urban settings are challenging environments to implement eco-driving strategies for
automated vehicles. It is often assumed that sufficient information on the preceding vehicle …

Lane change is a common-yet-challenging driving behavior for automated vehicles. To
improve the safety and efficiency of automated vehicles, researchers have proposed various …

Road intersection is one of the most complex and accident-prone traffic scenarios, so it's
challenging for autonomous vehicles (AVs) to make safe and efficient decisions at the …

Performing safe and efficient lane changes is a crucial feature for creating fully autonomous
vehicles. Recent advances have demonstrated successful lane following behavior using …

An accurate vehicle trajectory prediction promotes understanding of the traffic environment
and enables task criticality assessment in advanced driver assistance systems (ADASs) in …

Through shared real-time traffic information and perception of complex environments,
connected and automated vehicles (CAVs) are endowed with global decision-making …

High-level driving behavior decision-making is an open-challenging problem for connected
vehicle technology, especially in heterogeneous traffic scenarios. In this paper, a deep …

Intersections are considered one of the most complex scenarios in a self-driving framework
due to the uncertainty in the behaviors of surrounding vehicles and the different types of …