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 …

Misunderstanding of driver correction behaviors is the primary reason for false warnings of
lane-departure-prediction systems. We proposed a learning-based approach to predict …

We present a literature review to analyze the state of the art in the area of road detection
based upon frontal images. For this purpose, a systematic literature review (SLR) was …

This article presents a machine learning-based technique to build a predictive model and
generate rules of action to allow autonomous vehicles to perform roundabout maneuvers …

Most traffic accidents are caused by driver-related factors such as poor perception,
aggressive decision-making, or improper maneuvering. Therefore, it is critical to evaluate …

Safe driving and minimizing the number of casualties are the main motivations of
researchers and car companies for decades. They also care very much on saving fuel …

In autonomous driving systems a strong relation to highly accurate maps is taken to be
inevitable, although street scenes change frequently. However, a preferable system would …

A large number of studies have shown that most vehicle collisions are caused by drivers'
abnormal operations. To ensure the safety of all people on the road network as much as …

Understanding traffic scene images taken from vehicle mounted cameras is important for
high-level tasks, such as advanced driver assistance systems and autonomous driving. It is …

Depth completion is the task of reconstructing dense depth images from sparse LiDAR data.
LiDAR depth completion, for which LiDAR data is the only input, is an ill-posed and …