Autonomous driving has achieved significant milestones in research and development over
the last two decades. There is increasing interest in the field as the deployment of …

The inevitable impact of autonomous vehicles (AV) on traffic safety is becoming a reality with
the progressive deployment of these vehicles in different parts of the world. Still, many …

Predicting the future trajectories of dynamic traffic actors is a cornerstone task in
autonomous driving. Though existing notable efforts have resulted in impressive …

Automated driving has the potential to revolutionize personal, public, and freight mobility.
Beside accurately perceiving the environment, automated vehicles must plan a safe …

Predicting the future trajectories of traffic agents is a pivotal aspect in achieving collision-free
driving for autonomous vehicles. Although the overall accuracy of existing prediction …

Accurately predicting the trajectories of vehicles in a driving environment composed of
various traffic participants is very significant for the driving safety of intelligent vehicles. The …

Artificial intelligence (AI) plays a critical role in the prediction, planning, and control of
autonomous vehicle. The original motion control methods are increasing in accuracy, but …

Point cloud registration is a classic and fundamental problem. Existing point cloud
registration methods obtain correspondence point pairs by calculating the correlation …

Pedestrian trajectory prediction is essential for self-driving vehicles, social robots, and
intelligent monitoring applications. Diverse trajectory data is critical for high-accuracy …

Data-driven methods have great advantages in modeling complicated human behavioral
dynamics and dealing with many human-robot interaction applications. However, collecting …