Simultaneous Realization of Decision, Planning and Control for Lane-Changing Behavior Using Nonlinear Model Predictive Control
Simultaneous Realization of Decision, Planning and Control for Lane-Changing Behavior Using Nonlinear Model Predictive Control
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DOI：
10.1587/transinf.2020edp7039
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发表时间：
2020-12
期刊：
影响因子：
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通讯作者：
H. Okuda;Nobuto Sugie;Tatsuya Suzuki;Kentaro Haraguchi;Z. Kang
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文献类型：
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作者：
H. Okuda;Nobuto Sugie;Tatsuya Suzuki;Kentaro Haraguchi;Z. Kang
总结 路径规划和运动控制是实现安全可靠自动驾驶的基础组成部分。然而，由于这两个组件之间存在很强的数学相互作用，因此对这两个组件的作用的区分有些模糊。这通常会导致实现中的冗余计算。克服这种冗余的一个吸引人的想法是基于模型预测控制框架的同步路径规划和运动控制（SPPMC）。 SPPMC不仅考虑车辆动力学，还考虑反映物理限制、安全约束等的各种约束来找到最佳控制输入，以实现给定行为的目标。在真实交通环境中的驾驶中，决策与规划和控制也有很强的交互作用。在某些上下文中切换多个任务以实现更高级别任务的情况下，这一点更加突出。本文提出了一种集成决策、路径规划和运动控制的基本思想，并且可以实时执行。特别是，选择变道行为及其启动决策作为目标任务。所提出的想法基于非线性模型预测控制和成本函数及其约束的适当切换。因此，在安全等多种约束下，通过求解单个优化问题来实现换道行为的启动、规划和控制决策。使用车辆模拟器测试了所提方法的有效性。
SUMMARY Path planning and motion control are fundamental components to realize safe and reliable autonomous driving. The discrimination of the role of these two components, however, is somewhat obscure because of strong mathematical interaction between these two components. This often results in a redundant computation in the implementation. One of attracting idea to overcome this redundancy is a simultaneous path planning and motion control (SPPMC) based on a model predictive control framework. SPPMC finds the optimal control input considering not only the vehicle dynamics but also the various constraints which reflect the physical limitations, safety constraints and so on to achieve the goal of a given behavior. In driving in the real tra ffi c environment, decision making has also strong interaction with planning and control. This is much more emphasized in the case that several tasks are switched in some context to realize higher-level tasks. This paper presents a basic idea to integrate decision making, path planning and motion control which is able to be executed in realtime. In particular, lane-changing behavior together with the decision of its initiation is selected as the target task. The proposed idea is based on the nonlinear model predictive control and appropriate switching of the cost function and constraints in it. As the result, the decision of the initiation, planning, and control of the lane-changing behavior are achieved by solving a single optimization problem under several constraints such as safety. The validity of the proposed method is tested by using a vehicle simulator.