Existing environment modeling approaches and trajectory planning approaches for
intelligent vehicles are difficult to adapt to multiple scenarios, as scenarios are diverse and …

Autonomous vehicle requires a general planner for all possible scenarios. Existing
researches design such a planner by a unified scenario description. However, it may …

Trajectory planning plays a crucial role in autonomous driving. It generates feasible
geometric paths within a certain time horizon to guide autonomous vehicles. However …

Conventional layered planning architecture temporally partitions the spatiotemporal motion
planning by the path and speed, which is not suitable for lane change and overtaking …

This paper presents a hierarchical trajectory planning based on the integration of a sampling
and an optimization method for urban autonomous driving. To manage a complex driving …

To enable autonomous vehicles to respond quickly to changes in the surrounding
environment and to generate safe and stable trajectory, we propose a safety-based …

Effective trajectory prediction is of great significance for the design of intelligent driving
systems. To overcome the problems of low algorithm efficiency and insufficient scenario …

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

Efficient trajectory planning for intelligent vehicles in dynamic environments is a non-trivial
task due to the diversity and complexity of driving scenarios. It requires the planner to be …

Providing safe, smooth, and efficient trajectories for autonomous vehicles has long been a
question of great interest in the field of autopiloting. In dynamic and ever-changing urban …