Accurate trajectory prediction of surrounding road users is the fundamental input for motion
planning, which enables safe autonomous driving on public roads. In this paper, a safe …

In the burgeoning field of autonomous vehicles (AVs), trajectory prediction remains a
formidable challenge, especially in mixed autonomy environments. Traditional approaches …

Predicting the future behavior of traffic participants in the scene surrounding the ego vehicle
is essential for the autonomous vehicle to plan a safe, comfortable, and legal route. The …

Reliable trajectory planning like human drivers in real-world dynamic urban environments is
a critical capability for autonomous driving. To this end, we develop a vision and imitation …

How to make precise multi-agent trajectory prediction is a crucial problem in the context of
autonomous driving. It is significant to have the ability to predict surrounding road …

Decision-making and motion planning are extremely important in autonomous driving to
ensure safe driving in a real-world environment. This study proposes an online evolutionary …

General-purpose trajectory planning algorithms for automated driving utilize complex reward
functions to perform a combined optimization of strategic, behavioral, and kinematic …

As autonomous driving technology progresses, the need for precise trajectory prediction
models becomes paramount. This paper introduces an innovative model that infuses …

Trajectory prediction has always been a challenging problem for autonomous driving, since
it needs to infer the latent intention from the behaviors and interactions from traffic …

Generating safe and non-conservative behaviors in dense, dynamic environments remains
challenging for automated vehicles due to the stochastic nature of traffic participants' …