发表机构
TORC Robotics LLC; Daimler Truck AG; MassRobotics（TORC机器人有限责任公司; 戴姆勒卡车股份公司; 大众机器人协会）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
研究自动驾驶中安全等冲突的解决，提出W-SQP加权分层松弛非线性MPC，将九个规则家族编译求解，能实时重新规划并记录残差，经评估在安全法规方面无系统性缺陷，是可审核、有优先级偏差且随时可用的NMPC原型。
AI 中文摘要
自动驾驶车辆运动规划器必须实时解决安全、法规、舒适性和效率之间的冲突，并公开这些决策以供审核。我们提出了W-SQP，一种加权分层松弛非线性模型预测控制器（NMPC），它将九个驾驶规则家族编译成一个四层共享松弛非线性规划，使用CasADi和IPOPT在线求解；该名称表示加权二次松弛惩罚，而非序列二次规划求解器。强分离的分层惩罚使剩余违规偏向低优先级规则，同时保持驱动界限严格。控制器从其执行状态以10Hz重新规划，并在每个周期记录每个规则的残差。90ms的求解器时间限制返回一个随时迭代，在执行前通过车辆动力学进行投影；观察到的中位数和最大挂钟求解时间分别为28ms和104ms。我们在Waymax中针对反应式和提议-选择基线在150个Waymo开放运动数据集场景中对W-SQP进行闭环评估，并引入了一种与日志无关的协议，该协议将安全和法规合规性与与记录的人类轨迹的相似性分开。在此协议下，W-SQP在与日志无关的安全和法规规则方面相对于专家回放没有系统性的组级缺陷，在最困难、差异最大的场景中有一些局部回归。结果表明W-SQP是一个可审核、具有优先级偏差、随时可用的NMPC原型，而非硬实时或形式上安全的控制器。
英文摘要
Autonomous-vehicle motion planners must resolve conflicts among safety, regulation, comfort, and efficiency in real time while exposing those decisions for audit. We present W-SQP, a weighted tiered-slack nonlinear model predictive controller (NMPC) that compiles nine driving-rule families into a four-tier shared-slack nonlinear program solved online with CasADi and IPOPT; the name denotes the weighted quadratic slack penalty, not a sequential-quadratic-programming solver. Strongly separated tier penalties bias residual violations toward lower-priority rules while leaving actuation bounds hard. The controller replans from its executed state at $10$\,Hz and records per-rule residuals on every cycle. A $90$\,ms solver-time limit returns an anytime iterate that is projected through the vehicle dynamics before execution; median and maximum observed wall-clock solve times were $28$ and $104$\,ms. We evaluate W-SQP in closed loop on 150 Waymo Open Motion Dataset scenarios in Waymax against reactive and proposal-and-select baselines, and introduce a log-independent protocol that separates safety and regulatory compliance from resemblance to the recorded human trajectory. Under this protocol, W-SQP shows no systematic group-level deficit relative to expert replay on the log-independent safety and regulatory rules, with several localized regressions in the hardest, highest-divergence scenarios. The results characterize W-SQP as an auditable, priority-biased, anytime-capable NMPC prototype rather than a hard-real-time or formally safe controller.
CommentsThe manuscript is submitted to the Journal of Control Engineering Practice, A journal of The International Federation of Automatic Control (IFAC)
