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

Due to the stochasticity of human behaviors, predicting the future trajectories of road agents
is challenging for autonomous driving. Recently, goal-based multi-trajectory prediction …

Forecasting the future behaviors of dynamic actors is an important task in many robotics
applications such as self-driving. It is extremely challenging as actors have latent intentions …

Pedestrian trajectory prediction is an essential task in robotic applications such as
autonomous driving and robot navigation. State-of-the-art trajectory predictors use a …

Trajectory computing is a pivotal domain encompassing trajectory data management and
mining, garnering widespread attention due to its crucial role in various practical …

We consider the problem of predicting the future trajectory of scene agents from egocentric
views obtained from a moving platform. This problem is important in a variety of domains …

Video anomaly detection (VAD) has been extensively studied for static cameras but is much
more challenging in egocentric driving videos where the scenes are extremely dynamic …

Pedestrians and drivers are expected to safely navigate complex urban environments along
with several non cooperating agents. Autonomous vehicles will soon replicate this …

This paper presents a real-time lane change control framework of autonomous driving in
dense Traffic, which exploits cooperative behaviors of other drivers. This paper focuses on …

Autonomous vehicles are expected to drive in complex scenarios with several independent
non cooperating agents. Path planning for safely navigating in such environments can not …