Highway safety has attracted significant research interest in recent years, especially as
innovative technologies such as connected and autonomous vehicles (CAVs) are fast …

In this article, we present an efficient planning system for automated vehicles in highly
interactive environments (EPSILON). EPSILON is an efficient interaction-aware planning …

Safe motion planning for autonomous vehicles is a challenging task, since the exact future
motion of other traffic participant is usually unknown. In this article, we present a verification …

Trajectory planning for automated parking has been widely known as more challenging than
that for on-road driving due to the nonconvex kinematics, high-dimensional collision …

Autonomous vehicle (AV) stacks are typically built in a modular fashion, with explicit
components performing detection, tracking, prediction, planning, control, etc. While …

Path planning is a critical part for improving the driving safety and driver comfort of
autonomous vehicles (AVs), especially in complex maneuvering conditions. In addition …

In modern autonomy stacks, prediction modules are paramount to planning motions in the
presence of other mobile agents. However, failures in prediction modules can mislead the …

Planning safe trajectories for autonomous vehicles in complex urban environments is
challenging since there are numerous semantic elements (such as dynamic agents, traffic …

The motion planners used in self-driving vehicles need to generate trajectories that are safe,
comfortable, and obey the traffic rules. This is usually achieved by two modules: behavior …

In this paper, we introduce a novel and efficient hybrid trajectory planning method for
autonomous driving in highly constrained environments. The contributions of this paper are …