In order to drive safely in a dynamic environment, autonomous vehicles should be able to
predict the future states of traffic participants nearby, especially surrounding vehicles, similar …

Vehicle trajectory prediction is a keystone for the application of the internet of vehicles (IoV).
With the help of deep learning and big data, it is possible to understand the between-vehicle …

As a core function of autonomous driving (AD) and the Internet of Vehicles (IoV), accurately
predicting the trajectory of vehicles can significantly improve traffic safety and reduce crash …

The significant contribution of human errors, accounting for approximately 94%(with a
margin of±2.2%), to road crashes leading to casualties, vehicle damages, and safety …

We present a new method for multi-modal, long-term vehicle trajectory prediction. Our
approach relies on using lane centerlines captured in rich maps of the environment to …

Vehicle trajectory prediction is a challenging problem in the field of autonomous driving,
which is of great significance to the safety of autonomous driving and traffic roads. In view of …

Vehicle Trajectory Prediction (VTP) is one of the key issues in the field of autonomous
driving. In recent years, more researchers have tried applying Deep Learning methods and …

This work presents a novel method for predicting vehicle trajectories in highway scenarios
using efficient bird's eye view representations and convolutional neural networks. Vehicle …

Snow and ice films obscure lane lines during the winter, leading to inaccurate trajectory
predictions and reducing a driver's ability to guide the vehicle. The full use of observable …

Trajectory prediction is one of the core functions of autonomous driving. Modeling spatial-
aware interactions and temporal motion patterns for observed vehicles are critical for …