The prediction of surrounding agent trajectories in heterogeneous traffic environments
remains a challenging task for autonomous driving due to several critical issues, such as …

Predicting the trajectories of surrounding heterogeneous traffic agents is critical for the
decision making of an autonomous vehicle. Recently, many existing prediction methods …

Accurate vehicle trajectory prediction can benefit a variety of intelligent transportation system
applications ranging from traffic simulations to driver assistance. The need for this ability is …

Accurate behavior prediction of other vehicles in the surroundings is critical for intelligent
transportation systems. Common practices to reason about the future trajectory are through …

In this paper, Vulnerable Road User (VRU) trajectory prediction for autonomous driving
based on the Intention-Attention-Gate Recurrent Unit (IA-GRU), Improved Social Force …

With the rapid development of machine learning, autonomous driving has become a hot
issue, making urgent demands for more intelligent perception and planning systems. Self …

Accurate and reliable prediction of vehicle trajectories is closely related to the path planning
of intelligent vehicles and contributes to intelligent transportation safety, especially in …

Predicting the trajectory of other road users, especially vulnerable road users (VRUs), is an
important aspect of safety and planning efficiency for autonomous vehicles. With recent …

In vehicle trajectory prediction, the difficulty in modeling the interaction relationship between
vehicles lies in constructing the interaction structure between the vehicles in the traffic …

Accurate and reliable prediction of future motions of the nearby agents and effective
environment understanding will contribute to high-quality and meticulous path planning for …