In order to predict the behavior of human drivers accurately, the autonomous vehicle should
be able to understand the reasoning and decision process of motion generation of human …

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 …

Forecasting the future behavior of all traffic agents in the vicinity is a key task to achieve safe
and reliable autonomous driving systems. It is a challenging problem as agents adjust their …

Anticipating the future trajectories of surrounding vehicles is a crucial and challenging task
in path planning for autonomy. We propose a novel Convolutional Long Short Term Memory …

The trajectory prediction is a critical and challenging problem in the design of an
autonomous driving system. Many AI-oriented companies, such as Google Waymo, Uber …

Trajectory prediction of surrounding objects plays a pivotal role in the field of autonomous
driving vehicles. In the current rollout process, it suffers from an accumulation of errors …

Scene understanding and future motion prediction of surrounding vehicles are crucial to
achieve safe and reliable decision-making and motion planning for autonomous driving in a …

For the path planning of autonomous vehicles, it is important to predict the future trajectory of
the surrounding vehicles. However, predicting future trajectory is difficult because it needs to …

This paper presents online-capable deep learning model for probabilistic vehicle trajectory
prediction. We propose a simple encoder-decoder architecture based on multihead …

Accurate prediction of the future motion of surrounding vehicles is crucial for ensuring the
safety of motion planning in autonomous vehicles. However, it is challenging to perform …