论文标题
通过结合模型预测控制和控制屏障功能，同时进行车道保存和避免障碍
Simultaneous Lane-Keeping and Obstacle Avoidance by Combining Model Predictive Control and Control Barrier Functions
论文作者
论文摘要
在这项工作中，我们将{模型预测控制}（MPC）和控制屏障函数（CBF）设计{Methods}结合起来，为同时泳道（LK）和避免障碍物（OA）创建层次控制法（OA）：在低水平上，MPC在主机操作期间通过轨迹跟踪执行LK。在高水平上，确保LK和OA都在某些实际情况下设计和比较的不同基于CBF的安全过滤器。特别是，我们表明，指数安全性（ESF）和规定的时间安全（PTSF）过滤器，必要时覆盖MPC控制，在适当优先级时会导致可行的二次程序。我们还通过使用输入约束的CBF来研究受输入约束的控制设计。最后，我们比较了ESF，PTSF的组合及其在LK和OA目标中，在两项模拟研究中针对早期和晚期发现的障碍场景中的LK和OA目标的表现。
In this work, we combine {Model Predictive Control} (MPC) and Control Barrier Function (CBF) design {methods} to create a hierarchical control law for simultaneous lane-keeping (LK) and obstacle avoidance (OA): at the low level, MPC performs LK via trajectory tracking during nominal operation; and at the high level, different CBF-based safety filters that ensure both LK and OA are designed and compared across some practical scenarios. In particular, we show that Exponential Safety (ESf) and Prescribed-Time Safety (PTSf) filters, which override the MPC control when necessary, result in feasible Quadratic Programs when safety is prioritized appropriately. We additionally investigate control designs subject to input constraints by using Input-Constrained-CBFs. Finally, we compare the performance of combinations of ESf, PTSf, and their input-constrained counterparts with respect to the LK and OA goals in two simulation studies for early- and late-detected obstacle scenarios.
