基于改进驾驶风险场和A*算法的自动驾驶汽车动态避障路径规划

Ye Tian, Huaxin Pei, Yi Zhang
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引用次数: 3

摘要

在车辆路径规划中,安全性是最重要的考虑因素。驾驶风险场作为交通风险评估的主要、常用指标,能够描述复杂交通场景的综合驾驶风险,具有较强的实时性。针对现有驾驶风险场模型的缺陷,提出了一种采用椭圆修正公式的改进驾驶风险场模型。与已有研究相比,改进后的模型能够考虑到道路不同方向的安全差异。然后,提出了一种基于改进的驾驶风险场和a *算法的自动驾驶汽车路径规划算法,并考虑了动态避障。仿真结果表明,该算法准确可行,能够保证车辆在路径规划过程中的行驶安全,提高算法效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Path Planning for CAVs Considering Dynamic Obstacle Avoidance Based on Improved Driving Risk Field and A* Algorithm
In vehicle path planning, safety is the most important consideration. As a main and popular index of traffic risk assessment, driving risk field can describe the comprehensive driving risk of complex traffic scenes, and has strong real-time performance. In view of the defects of the existing driving risk field model, this paper proposes an improved driving risk field with ellipse modification formula. Compared with the existing research, the improved model can take into account the safety differences in different directions of the road. Then, a path planning algorithm based on improved driving risk field and A * algorithm is proposed for CA V s, which considers dynamic obstacle avoidance. The simulation result shows that the algorithm is accurate and feasible, which can ensure the driving safety of vehicle in the process of path planning and improve the efficiency of the algorithm.
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