复杂交通环境下的智能汽车局部轨迹规划方法的研究

Research on the local trajectory planning method for intelligent vehicles in a complex traffic environment

对于复杂交通环境下智能汽车的实时轨迹动态规划的问题,提出了一种基于Frenet坐标的智能车辆局部轨迹规划的算法。利用三次样条曲线拟合道路中心线,得到道路参考线。通过初始状态和目标状态,采样得到四次多项式和五次多项式候选轨迹的集合。综合考虑智能车辆行驶安全性、候选轨迹的横向与纵向加速度变化及全局轨迹追踪能力,设计了安全性代价函数、轨迹舒适性代价函数和轨迹偏移量代价函数,评价轨迹成本。最后通过仿真结果可知,该算法可以实时性得到既舒适又安全的轨迹。且设计了多种类型的道路,其中包括具有单个匀速和变速障碍物的双车道连续弯道,具有多个匀速和变速障碍物的三车道弯道,来测试该方法。测试结果表明:该算法能有效改善复杂动态环境下的避障能力。

To cope with the problem of real-time trajectory dynamic planning for intelligent vehicles in complex traffic settings,this paper proposes a local trajectory planning algorithm based on Frenet coordinates.Firstly,the road center line is fitted to obtain the road reference line by utilizing a cubic spline curve.Then,according to the initial and target configuration,the sets of quartic and quintic polynomial candidate trajectories are generated by sampling.Additionally,multi-objective cost functions containing safety,trajectory comfortability and trajectory offset are designed to evaluate the trajectory cost by considering the effects of vehicle safety,the lateral and longitudinal acceleration changes of candidate trajectories and the global trajectory tracking ability.Ultimately,the simulation results reveal that the proposed method can obtain a real-time comfortable and safe trajectory.Furthermore,various types of roads are designed to test the approach,including a two-lane continuous curve with a single constant-speed or variable-speed obstacle,and a three-lane curve with multiple constant-speed obstacles or variable-speed obstacles.The test results show that the algorithm can effectively improve obstacle avoidance in complex dynamic environments.