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摘要: 无人车辆的轨迹规划与跟踪控制是实现自动驾驶的关键.轨迹规划与跟踪控制一般分为两个部分，即先根据车辆周边环境信息以及自车运动状态信息规划出参考轨迹，再依此轨迹来调节车辆纵横向输出以实现跟随控制.本文通过对无人车辆的轨迹规划与跟踪进行统一建模，基于行车环境势场建模与车辆动力学建模，利用模型预测控制中的优化算法来选择人工势场定义下的局部轨迹，生成最优的参考轨迹，并在实现轨迹规划的同时进行跟踪控制.通过CarSim与MATLAB/Simulink的联合仿真实验表明，该方法可在多种场景下实现无人车辆的动态避障.Abstract: Trajectory planning and tracking control of unmanned vehicles are the keys to autonomy. Generally, trajectory planning and tracking control are two functions in charge of generating reference trajectory according to the vehicle surrounding information and vehicle state information, and controlling vehicle motions according to the reference trajectory, respectively. In this paper, a unified modeling method to integrate trajectory planning and tracking control is presented. Based on the artificial potential field approach and vehicle dynamics modeling, the optimization algorithm of model predictive control is used to select the optimal local trajectory defined by the artificial potential field as the reference trajectory, which can be then tracked through vehicle motion control. A joint simulation of CarSim and MATLAB/Simulink shows that this method can effectively accomplish obstacle avoidance for the unmanned vehicle in several traffic scenarios.1) 本文责任编委 李力
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图 3 环境车的纵向势场值随距离变化图
Fig. 3 Longitudinal potential of the environment vehicle with respect to the relative distance
图 7 各场景的被控车速度变化图
Fig. 7 Speed variation diagram of the subject vehicle in several scenarios
图 8 各场景的控制增量以及控制量变化图
Fig. 8 Responses of the control increment and the control quantity variation in several scenarios
图 9 仿真场景中被控车的轨迹、侧向加速度、横摆角、横摆角速度的响应图
Fig. 9 Responses of the trajectory, lateral acceleration, yaw angle and yaw rate of the controlled vehicle in the simulation scenarios
图 10 场景4的行车轨迹和轮胎侧偏角响应图
Fig. 10 Responses of the trajectory and the slip angle in Scenario 4
表 1 控制器参数
Table 1 Controller parameters
参数 值 单位 参数 值 单位 $\sigma_{\rm lane}$, $A_{\rm lane}$ 0.8 $-$ $I_{z}$ 2 031 ${\rm kg}\cdot {\rm m}^{2}$ $\sigma_{\rm car}$ 0.53 $-$ $m$ 1 231 ${\rm kg}$ $A_{\rm road}$ 1 $-$ $a$, $b$ 1.04, 1.56 $\rm m$ $A_{\rm car}$ 15 $-$ $\varepsilon$, $\kappa$ 2, 0.01 $-$ $S_{\rm min}$ 3 ${\rm m}$ $C_{f}$ 61 224 $\rm N/rad$ $\rho$ 0.3 $-$ $C_{r}$ 42 500 ${\rm N/rad}$ $\lambda$ 0.5 $-$ $N_{p}$ 25 $-$ $A_{\rm car, long}$ 10 $-$ $N_{c}$ 2 $-$ 
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