%0 Journal Article
%T 基于小偏差模型预测的车道保持辅助控制<br>Predictive control for lane control systems using a small deviation model
%A 柳长春
%A 都东
%A 潘际銮
%J 清华大学学报（自然科学版）
%D 2015
%R 10.16511/j.cnki.qhdxxb.2015.22.011
%X 车道保持辅助系统需要在保证安全性的同时适应驾驶员习惯, 避免不必要的干预。该文通过在线构建人-车系统的小偏差模型, 基于模型预测控制理论, 设计了车道保持辅助控制策略。控制器通过在线求解二次规划问题, 获得矫正转向角, 帮助驾驶员避免无意的车道偏离。根据车辆当前状态, 计算名义预测轨迹。通过将非线性人-车模型围绕名义轨迹逐次线性化, 在线获取人-车系统小偏差模型。通过对系统安全性和驾驶员适应性指标的量化设计, 得到相应的目标函数和I/O约束, 建立了滚动时域优化问题。仿真实验演示了该控制器探测车道偏离危险和转向矫正的过程。真实场景下的实车实验表明: 该系统具有避免车道偏离、适应驾驶员习惯、避免不必要干预的能力。<br>Abstract：Lane control systems automatically keep a vehicle in its lane to improve driving safety. Such systems need to adapt to the driver's characteristics and should reduce unnecessary intervention. A small deviation model of the human-vehicle system is formulated for on-line prediction of the future vehicle trajectory with an assistance control strategy based on model predictive control (MPC). A corrective steering angle is computed by solving a quadratic programming problem. The nominal trajectory is predicted using the current vehicle information. Then, a deviation model is obtained by successively linearizing the human-vehicle system around the nominal prediction trajectory. A cost function and I/O constraints are designed according to a performance index. Simulations and real world tests show that this approach is able to avoid unintended lane departures while adapting to the driver's driving patterns and avoiding unnecessary intervention.
%K 车道保持
%K 模型预测控制
%K 小偏差模型
%K 驾驶员辅助系统
%K &lt
%K br&gt
%K lane keeping
%K model predictive control
%K small deviation model
%K driver assistance system
%U http://jst.tsinghuajournals.com/CN/Y2015/V55/I10/1087