Trajectory prediction of the ego vehicle is necessary for the cooperation driving of intelligent
vehicles and drivers. Methods based on deep learning can fit complex functions, but they …

Predicting vehicle trajectories using deep learning has seen substantial progress in recent
years. However, making autonomous vehicles pay attention to their surrounding vehicles …

Predicting the trajectory of neighboring vehicles is closely related to the driving safety of
intelligent vehicles and supports driving assistance. This article proposes a dual-attention …

This paper presents a literature review on Intention-aware and Interaction-aware Trajectory
Prediction for Autonomous Vehicle, which covers primary studies since 2008. The research …

Trajectory prediction aims to estimate the future location of the vehicle based on its historical
motion state, which is essential for driving decision-making and local motion planning of …

Integrating trajectory prediction to the decision-making and planning modules of modular
autonomous driving systems is expected to improve the safety and efficiency of self-driving …

Precise trajectory prediction is pivotal for autonomous vehicles operating in real-world traffic
conditions, and can help them make the right decisions to ensure safety on the road …

Despite the advancements in the technologies of autonomous driving, it is still challenging to
study the safety of a self-driving vehicle. Trajectory prediction is one core function of an …

Accurate and reliable trajectory prediction is crucial for autonomous vehicles to achieve safe
and efficient operation. Vehicles perceive the historical trajectories of moving objects and …

To drive safely in complex traffic environments, autonomous vehicles need to make an
accurate prediction of the future trajectories of nearby heterogeneous traffic agents (ie …