Predicting trajectories of multiple agents in interactive driving scenarios such as
intersections, and roundabouts are challenging due to the high density of agents, varying …

Traffic flow prediction plays an instrumental role in modern intelligent transportation systems.
Numerous existing studies utilize inter-embedded fusion routes to extract the intrinsic …

In the context of the booming Internet of Vehicles, predicting vehicle trajectories is crucial for
intelligent transportation systems. Existing methods, reliant on sensor data and behavior …

Trajectory prediction is a critical aspect of understanding and estimating the motion of
dynamic systems, including robotics and autonomous vehicles (AVs). For safe and efficient …

Vehicle trajectory prediction plays a vital role in intelligent driving modules and helps
intelligent vehicles travel safely and efficiently in complex traffic environments. Several …

In order to navigate through complex traffic scenarios safely and efficiently, the autonomous
vehicle (AV) predicts its own behavior and future trajectory based on the predicted …

Path prediction is an essential task for many real-world Cyber-Physical Systems (CPS)
applications, from autonomous driving and traffic monitoring/management to …

Accurate prediction of vehicle trajectories is crucial to the safety and comfort of autonomous
vehicles. Although several graph-based models have exhibited substantial progress in …

Multi-channel learning has gained significant attention in recent applications, where neural
networks with t-product layers (t-NNs) have shown promising performance through novel …

Active safety systems on vehicles often face problems with false alarms. Most active safety
systems predict the driver's trajectory with the assumption that the driver is always in a …