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 …

Trajectory planning has generally been framed as finding the lowest cost one from a set of
trajectory candidates, where the cost function has been hand-crafted with carefully tuned …

In this work we put forward a predictive trajectory planning framework to help autonomous
vehicles plan future trajectories. We develop a partially observable Markov decision process …

Emergency avoidance is an aggressive maneuver with high collision risk. This paper
presents an integrated decision making and motion control framework to achieve …

A reliable prediction of traffic participants' trajectories is challenging for automated driving.
We attempt to integrate human trajectory's temporal and spatial reciprocal consistency into …

Driving in a human-like manner is important for an autonomous vehicle to be a smart and
predictable traffic participant. To achieve this goal, parameters of the motion planning …

Autonomous driving, including intelligent decision-making and path planning, in dynamic
environments (like highway) is significantly more difficult than the navigation in static …

Lane-changing trajectory planning (LTP) is an effective concept to control automated
vehicles (AVs) in mixed traffic, which can reduce traffic conflicts and improve overall traffic …

In this paper, under unforeseen circumstances, a dynamics-constrained global-local (DGL)
hybrid path planning scheme incorporating global path planning and local hierarchical …

Making safe and human-like decisions is an essential capability of autonomous driving
systems, and learning-based behavior planning presents a promising pathway toward …