论文标题
连续散置在自动驾驶和控制中的应用
Applications of Successive Convexification in Autonomous VehiclePlanning and Control
论文作者
论文摘要
在本文中，我们介绍了连续的凸化方法在最近的航空航天文献中借用的自动驾驶问题。我们在连续的凸框架内提出了两个优化问题。使用车辆运动学模型中的ARC长度参数化，我们通过一系列约束和障碍物配置解决了速度计划和模型预测控制问题。本文是从航空航天文献到自动驾驶问题的连续散装方法的第一个系统应用。此外，我们通过在模拟部分中包括逃避操纵来显示逻辑状态触发约束的简单应用。我们提供了问题制定和实施的详细信息，并呈现并讨论结果。
In this paper, we present the application of successive convexification methods to autonomous driving problems borrowed from recent aerospace literature. We formulate two optimization problems within the successive convexification framework. Using arc-length parametrization in the vehicle kinematic model, we solve the speed planning and model predictive control problems with a range of constraints and obstacle configurations. This paper is the first systematic application of successive convexification methods from the aerospace literature to the autonomous driving problems. In addition, we show a simple application of logical state-trigger constraints in a continuous formulation of the optimization by including an evasion maneuver in the simulations section. We give details of the problem formulation and implementation and present and discuss the results.
