为铰接式卡车设计可自适应权重的轨迹规划方法，避免急转弯和失控。
Trajectory Planning for an Articulated Commercial Vehicle using Model Predictive Contouring Control
- 基于模型预测轮廓控制，动态调整牵引车与挂车的关键点权重。
- 在正向与反向行驶中均能保持所有车轮在可行驶区域内。
- 适用于物流场景中的停靠、充电等复杂操作，适合自动驾驶卡车研发者。
本文提出一种基于模型预测轮廓控制（MPCC）的铰接式商用卡车（如牵引车-半挂车）轨迹规划方法。尽管MPCC在乘用车上表现良好，但对大型半挂车不适用：其挂车路径与牵引车不同，倒车时易发生折弯（jackknifing）且稳定性差。此外，实际驾驶中需根据场景优先考虑不同锚点位置，如停靠时关注挂车位置，充电时关注牵引车位置。为此，本文扩展了MPCC，实现锚点的场景依赖加权，并引入前后牵引车轴及挂车轴的显式道路边界约束，确保所有车轮始终在可行驶区域内。仿真结果表明，该方法成功完成典型物流场景下的正向与反向行驶。同时分析了优化参数对轨迹的影响，为车辆行为调控提供依据。最后，基于全尺寸原型车的初步测试验证了该方法的实际可行性。
原文摘要 · Abstract (English)
This paper presents a trajectory planning method for articulated commercial vehicles, specifically tractor-semitrailers, based on Model Predictive Contouring Control (MPCC). Although MPCC has proven effective for passenger cars, it is generally ill-suited for tractor-semitrailers. These vehicles are significantly larger, the semitrailer follows a different path than the tractor, and reversing maneuvers are unstable and prone to jackknifing. Furthermore, practical driving scenarios often require scenario-dependent prioritization of different vehicle `anchor points', e.g., prioritizing the semitrailer position during docking or the tractor position when parking to charge. Therefore, we extend MPCC to enable scenario-dependent weighting of these anchor points and incorporate explicit road-boundary constraints for the front and rear tractor axles and the semitrailer axle, thereby ensuring that all considered wheels remain within the drivable area. The simulation results demonstrate the successful navigation of a representative logistic scenario in both forward and reverse direction. Furthermore, the influence of the optimization parameters on the trajectories is analyzed, providing insights into controlling the vehicle behavior. Finally, first tests using a full-scale prototype vehicle show the practical applicability of the approach.
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