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首页> 外文期刊>Mechanical systems and signal processing >Development of a new integrated local trajectory planning and tracking control framework for autonomous ground vehicles
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Development of a new integrated local trajectory planning and tracking control framework for autonomous ground vehicles

机译：为自动地面车辆开发新的集成的局部轨迹规划和跟踪控制框架

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This study proposes a novel integrated local trajectory planning and tracking control (ILTPTC) framework for autonomous vehicles driving along a reference path with obstacles avoidance. For this ILTPTC framework, an efficient state-space sampling-based trajectory planning scheme is employed to smoothly follow the reference path. A model-based predictive path generation algorithm is applied to produce a set of smooth and kinematically-feasible paths connecting the initial state with the sampling terminal states. A velocity control law is then designed to assign a speed value at each of the points along the generated paths. An objective function considering both safety and comfort performance is carefully formulated for assessing the generated trajectories and selecting the optimal one. For accurately tracking the optimal trajectory while overcoming external disturbances and model uncertainties, a combined feedforward and feedback controller is developed. Both simulation analyses and vehicle testing are performed to verify the effectiveness of the proposed ILTPTC framework, and future research is also briefly discussed.
机译：这项研究提出了一种新颖的集成局部轨迹规划和跟踪控制（ILTPTC）框架，用于自动驾驶汽车沿参考路径行驶并避开障碍物。对于此ILTPTC框架，采用了一种有效的基于状态空间采样的轨迹规划方案来平稳地遵循参考路径。应用基于模型的预测路径生成算法来生成将初始状态与采样终端状态连接起来的一组平滑且在运动学上可行的路径。然后设计速度控制律，以沿着生成的路径在每个点上分配速度值。精心制定了既考虑安全性又考虑舒适性的目标函数，以评估生成的轨迹并选择最佳轨迹。为了在克服外部干扰和模型不确定性的同时准确跟踪最佳轨迹，开发了一种组合式前馈和反馈控制器。进行了仿真分析和车辆测试，以验证所提出的ILTPTC框架的有效性，并且还将简要讨论未来的研究。

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