Autonomous driving requires efficient and safe decision making and motion planning in
dynamic and uncertain environments. Future movement of surrounding vehicles is often …

In automated driving, predicting and accommodating the uncertain future motion of other
traffic participants is challenging, especially in unstructured environments in which the high …

This thesis presents a behavior planning algorithm for automated driving in urban
environments with an uncertain and dynamic nature. The uncertainty in the environment …

The autonomous vehicle is widely applied in various ground operations, in which motion
planning and tracking control are becoming the key technologies to achieve autonomous …

This paper proposes a two-stage trajectory planning method for self-driving vehicles (SDVs)
in intersection scenarios with uncertain social circumstances while considering other traffic …

In the literature, the intensive research effort has been made on the trajectory planning for
autonomous vehicles, while the integration of the trajectory planner with the trajectory …

Traditional decoupling trajectory planning strategy deals with complex urban road scenes
with many shortcomings, such as stereotyped behavior and poor trajectory quality. Aiming at …

Trajectory planning is one of the most important modules of the Autonomous Driving
Systems (ADSs), which aims to achieve a safe and comfortable interaction between the …

Path planning is discussed in this article for an autonomous vehicle given a route to follow.
Route data is considered to be available for a distance ahead of the vehicle in a receding …

Decision-making and motion planning are two core functionalities of intelligent vehicles. A
novel integrated decision-making and planning framework is presented for real-time and …