Autonomous driving (AD) has developed tremendously in parallel with the ongoing
development and improvement of deep learning (DL) technology. However, the uptake of …

Traffic congestion is more likely to lead to aggressive driving behavior that is associated with
increased crash risks. Previous studies mainly focus on driving behavior during congestion …

In recent decades, driving assistance systems have been evolving towards personalization
for adapting to different drivers. With the consideration of driving preferences and driver …

Predicting lane change maneuvers is critical for autonomous vehicles and traffic
management as lane change may cause conflict in traffic flow. Most existing studies do not …

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 propose a new detection method to predict a vehicle's trajectory and use it for detecting
lane changes of surrounding vehicles. According to the previous research, more than 90 …

Due to the complexity of experiments to test driving behaviors and the high cost of data
collection for some types of vehicles, eg, heavy-duty freight vehicles, it is normally hard to …

Prediction of lane changes (LCs) provides critical information to enhance traffic safety and
efficiency in a connected and automated driving environment. It is essential to precisely …

Car-following is the most general behavior in highway driving. It is crucial to recognize the
cut-in intention of vehicles from an adjacent lane for safe and cooperative driving. In this …

Due to the growing interest in automated driving, a deep understanding on the
characteristics of human driving behavior is critical for human-like autonomous vehicles …