通过图划分限制计算层级，实现高效安全的车辆轨迹规划。
Limiting Computation Levels in Prioritized Trajectory Planning with Safety Guarantees
- 用可达性分析保障并行规划的安全性，再对部分车辆串行规划以减少保守性。
- 仿真显示计算层级降低约64%，同时保持解的质量。
- 适合需要高效且安全的多车协同规划场景。
在车辆优先级规划中，车辆可并行或串行规划轨迹。并行规划计算时间稳定但难以保证无碰撞；串行规划虽能保证无碰撞，但随着串行计算车辆数量（即计算层级）增加，计算时间显著上升。该层级由车辆耦合与优先级构成的有向耦合图决定。本文通过可达性分析保障并行规划的轨迹安全，尽管结果偏保守。为缓解此问题，提出仅对部分车辆进行串行规划，并将子集选择建模为图划分问题，从而独立设定计算层级。仿真表明，相比串行规划，计算层级降低约64%，同时维持解的质量。
原文摘要 · Abstract (English)
In prioritized planning for vehicles, vehicles plan trajectories in parallel or in sequence. Parallel prioritized planning offers approximately consistent computation time regardless of the number of vehicles but struggles to guarantee collision-free trajectories. Conversely, sequential prioritized planning can guarantee collision-freeness but results in increased computation time as the number of sequentially computing vehicles, which we term computation levels, grows. This number is determined by the directed coupling graph resulted from the coupling and prioritization of vehicles. In this work, we guarantee safe trajectories in parallel planning through reachability analysis. Although these trajectories are collision-free, they tend to be conservative. We address this by planning with a subset of vehicles in sequence. We formulate the problem of selecting this subset as a graph partitioning problem that allows us to independently set computation levels. Our simulations demonstrate a reduction in computation levels by approximately 64% compared to sequential prioritized planning while maintaining the solution quality.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。