Safe and human‐like trajectory planning is crucial for self‐driving cars. While model‐based
planning has demonstrated reliability, it is beneficial to incorporate human demonstrations …

Human‐like automated driving strategies could have advantages in traffic safety and
comfort. However, the primary features of human‐like driving behaviors are not clear yet. To …

Human-like driving is of great significance for safety and comfort of autonomous vehicles,
but existing trajectory planning methods for on-road vehicles rarely take the similarity with …

Humanlike driving is significant in improving the safety and comfort of automated vehicles.
This paper proposes a personalized motion planning method with driver characteristics in …

Due to the uncertainty of traffic participants' intentions, generating safe but not overly
cautious behavior in interactive driving scenarios remains a formidable challenge for …

As autonomous driving technology continues to advance and gradually become a reality,
ensuring the safety of autonomous driving in complex traffic scenarios has become a key …

Learning-based approaches have achieved remarkable performance in the domain of
autonomous driving. Leveraging the impressive ability of neural networks and large …

This article advances state-of-the-art automated driving systems with a comprehensive
framework that encompasses decision making, maneuver planning, and trajectory tracking …

We propose a new scheme to learn motion planning constraints from human driving
trajectories. Behavioral and motion planning are the key components in an autonomous …

The ultimate goal of self-driving technologies is to offer a safe and human-like driving
experience. As one of the most important enabling functionalities, trajectory planning has …