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Model predictive driver model considering the steering characteristics of the skilled drivers:

机译:考虑到熟练驾驶员的转向特性,对预测驾驶员模型进行建模:

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First, the experienced drivers with good driving skills are used as objects of learning and road steering test data of skilled drivers are collected in this article. To better simulate human drivers, skilled drivers’ steering characteristics are analyzed under different steering conditions. Vehicle trajectories of skilled drivers are fitted by general regression neural network, and the ideal path trajectory is obtained. Second, the model predictive control algorithm is used to build the driver model. According to the requirements of quickly and steadily tracking the track of skilled drivers, vehicle kinematics model is established. The objective function and the corresponding constraint conditions of the driver model based on model predictive control were determined. Finally, numerical simulations results demonstrate that the driver model based on model predictive control can accurately track the reference trajectory of skilled drivers under the four typical steering conditions, and the tracking effect is...
机译:首先,将具有良好驾驶技能的有经验的驾驶员用作学习的对象,并在本文中收集熟练驾驶员的道路转向测试数据。为了更好地模拟人类驾驶员,需要分析熟练的驾驶员在不同转向条件下的转向特性。通过通用回归神经网络拟合熟练驾驶员的车辆轨迹,并获得理想的路径轨迹。其次,模型预测控制算法用于构建驾驶员模型。根据快速,稳定地跟踪熟练驾驶员轨迹的要求,建立了车辆运动学模型。确定了基于模型预测控制的驾驶员模型的目标函数和相应的约束条件。最后,数值仿真结果表明,基于模型预测控制的驾驶员模型能够在四种典型转向条件下准确跟踪熟练驾驶员的参考轨迹,且跟踪效果良好。

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