智能车辆垂直停放路径规划与跟踪控制

Hu Guo
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引用次数: 0

摘要

提出了一种考虑智能车辆初始航向角的自动垂直泊车算法。根据车辆的最小转弯半径、车辆与停车位的相对位姿以及停车位右顶点坐标,确定可行的停车起点。在避碰约束的基础上确定停车类型(即单步或多步)。考虑到车辆转向执行机构的约束,采用四次样条曲线对单步停车路径和多步停车中最后一条进入车位的路径进行平滑处理,以改善路径特性。然后,引入车辆的期望航向角函数,当实际航向角接近期望航向角时,轨迹跟踪中的横向位移偏差趋于零;随后,提出了一种基于动态边界层的双曲正切函数作为切换函数的非线性积分滑模控制器(NISMC)来跟踪期望的航向角,从而完成路径跟踪过程。通过联合仿真和硬件在环(HIL)试验验证了所设计算法的有效性,仿真和试验结果表明,即使车辆具有初始航向角,所设计的停车路径也是可行的;同时,基于NISMC控制器的跟踪性能不仅跟踪误差小,控制输出平滑,而且具有较强的响应率和鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intelligent vehicle perpendicular parking path planning and tracking control
This paper presents a novel automatic perpendicular parking algorithm, taking into account the initial heading angle of the intelligent vehicle. The feasible parking starting point is located based on the vehicle’s minimum turning radius, the relative pose between the vehicle and the parking spot as well as the coordinates of right vertex of the parking space. The type of parking (i.e. single-step or multi-step) is determined on the basis of the collision avoidance constraint. Considering the constraint of the vehicle steering actuator, the quartic spline curve is used to smooth the single-step parking path and the last path into the parking space of multi-step parking, so as to improve the path characteristics. Then, a desired heading angle function of the vehicle is introduced, and the lateral displacement deviation in path tracking tends to zero when the actual heading angle approaches the desired heading angle. Subsequently, a nonlinear integral sliding mode controller (NISMC) with the hyperbolic tangent function based on dynamic boundary layer as the switching function is proposed to track the desired heading angle, so as to complete the path-tracking process. Co-simulations and Hardware-in-the-Loop (HIL) tests are carried out to verify the effectiveness of the designed algorithm, simulation and test results show that the desired parking path can be feasibly planned even when the vehicle has an initial heading angle; meanwhile, the tracking performance based on the proposed NISMC controller not only has small tracking error, smooth control output, but also strong response rate and robustness.
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