Safety-guaranteed motion planning is critical for self-driving cars to generate collision-free
trajectories. A layered motion planning approach with decoupled path and speed planning …

Multi-vehicle coordinated motion planning has always been challenged to safely and
efficiently resolve conflicts under non-holonomic dynamic constraints. Constructing spatial …

This work considers the problem of optimal lane changing in a structured multi-agent road
environment. A novel motion planning algorithm that can capture long-horizon …

Mixed-integer quadratic programs (MIQPs) are a versatile way of formulating vehicle
decision making (DM) and motion planning problems, where the prediction model is a …

Considerable research efforts have been devoted to the development of motion planning
algorithms, which form a cornerstone of the autonomous driving system (ADS). Nonetheless …

Scenarios are a crucial element for developing, testing, and verifying autonomous driving
systems. However, open-source scenarios are often formulated using different …

Validating motion planning algorithms for autonomous vehicles on a real system is essential
to improve their safety in the real world. Open-source initiatives, such as Autoware, provide a …

In this paper, a planning method based on the spatiotemporal variable-step-size A*
algorithm is proposed to address the problem of safe trajectory planning for incremental …