论文标题
基于风险的自动驾驶汽车计划
Risk-based path planning for autonomous vehicles
论文作者
论文摘要
在本文中，为自动驾驶汽车引入了基于风险图的路径计划算法。实施多元B-Spline来生成风险图，该映射衡量与不同对象碰撞的风险。在接下来的步骤中，设计了两级最佳控制问题。在第一级，发现总体最低风险轨迹。然后在第二层中，在其风险值最低的路径中，确定了最小转向工作的路径。最后，使用最佳控制软件OCPID-DAE1进行数值模拟。结果表明，此方法对于找到自动驾驶汽车的最小风险路径是有用且有意义的。
In this paper, a risk map-based path planning algorithm is introduced for autonomous vehicles. Multivariate B-splines are implemented to generate a risk map, which measures the risk of colliding with different objects. In the following step, a two-level optimal control problem is designed. At the first level, an overall lowest risk trajectory is found. Then in the second level, among the paths whose risk value is the lowest, the one with the minimum steering effort is determined. Finally, numerical simulations are carried out with the optimal control software OCPID-DAE1. Results show that this method is useful and meaningful to find a path of minimum risk for an autonomous vehicle.
