基于改进三元素避障模型的轨迹规划研究

Trajectory Planning Based on an Improved Three-Element Obstacle Avoidance Model

针对有动态障碍物干扰的交通环境,提出一种能描述车辆自身与障碍物运动关系的几何避障模型。通过将自车与障碍物空间距离分解为两个方向的距离,并结合自车与障碍物的相对速度得到三元素,建立基于三元素的改进避障模型。以模型预测控制原理(MPC)为基础,将离散化的车辆运动学模型作为预测模型,结合Frenet坐标系综合考虑道路边界、车辆自身机械结构、车辆行驶安全与舒适性等因素构建目标函数以及约束,最终建立非线性规划问题并求解。以金康赛力斯SF5作为试验车辆,加装硬件及传感器,搭建自动驾驶软件平台。在ROS+Matlab/Simulink软件平台上,部署轨迹规划算法进行实车试验。结果表明,该方法不仅能顺利避开障碍物,且可获得合理、舒适的行驶轨迹。

A geometric obstacle avoidance model is proposed for traffic environments with dynamic obstacles,which can describe the relationship between vehicle and obstacle movements.By decomposing the spatial distance between the vehicle and the obstacle into two directional components and incorporating their relative speed,three key elements are obtained.Based on these elements,an improved obstacle avoidance model is developed.Using the Model Predictive Control(MPC)principle,the discrete vehicle kinematics model is employed as the predictive model.The objective function and constraints are constructed by adopting the Frenet coordinate system and considering factors such as road boundaries,the vehicle's mechanical structure,driving safety and comfort.Finally,a nonlinear programming problem is established and solved.In this paper,the SF5 is used as the experimental vehicle,with hardware and sensors installed to build an autonomous driving platform.A trajectory planning algorithm was deployed on a ROS and Matlab/Simulink-based software platform for real-world vehicle testing.The results show that this method not only ensures smooth obstacle avoidance,but also produces a reasonable and comfortable driving path.