Trajectory planning is essential for autonomous vehicles when operating in dynamic traffic
environments. A layered approach usually separates out into path planning and speed …

In the field of autonomous driving, velocity planning is of paramount importance for handling
dynamic obstacle scenarios. To avoid unnecessary acceleration and deceleration, self …

In this paper, we present a convex-optimization-based method to solve speed planning
problems over a fixed path for autonomous driving in both static and dynamic environments …

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 …

This paper proposed a deep reinforcement learning based reference speed planning
strategy to co-optimize the fuel economy, driving safety, and travel efficiency of connected …

To generate safe and real-time trajectories for an autonomous vehicle in dynamic
environments, path and speed decoupled planning methods are often considered. This …

In this paper, we present a complete, flexible and safe convex-optimization-based method to
solve speed planning problems over a fixed path for autonomous driving in both static and …

Connected and automated vehicles (CAVs) have real-time knowledge of the immediate
driving environment, actions to be taken in the near future and information from the cloud …

A speed planner uses available information to enable automated vehicles to “eco-drive,”
which includes eco-approach and departure at signalized intersections and leads to …

We present a framework for robust autonomous driving motion planning system in urban
environments which includes trajectory refinement, trajectory interpolation, avoidance of …