Behavior-related research areas such as motion prediction/planning, representation/
imitation learning, behavior modeling/generation, and algorithm testing, require support from …

Motion planning is a core technique for autonomous driving. Nowadays, there still exists a
lot of challenges in motion planning for autonomous driving in complicated environments …

This paper presents a decoupled trajectory planning framework based on the integration of
lattice searching and convex optimization for autonomous driving in structured …

Self-driving vehicles are expected to be at the core of future transportation systems. Over
time, these vehicles might enhance traffic efficiency and safety, especially at road …

While lane change behavior of human drivers has already been widely investigated,
concepts and algorithms to plan lane changes for automated vehicles become necessary …

In the background of autonomous driving at level 3 to level 4, an automated vehicle should
own smarter driving brain to face complicated transportation situations. In order to construct …

Research in the areas related to driving behavior, eg, behavior modeling and prediction,
requires datasets with highly interactive vehicle motions. Existing public vehicle motion …

Human drivers navigate by continuously predicting the intent of road users and interacting
with them. For safe autonomous driving, research about predicting future trajectory of …