计算机应用 ›› 2017, Vol. 37 ›› Issue (3): 883-888.DOI: 10.11772/j.issn.1001-9081.2017.03.883

• 应用前沿、交叉与综合 • 上一篇    下一篇

面向自动驾驶的动态路径规划避障算法

周慧子1, 胡学敏1, 陈龙2, 田梅1, 熊豆1   

  1. 1. 湖北大学 计算机与信息工程学院, 武汉 430062;
    2. 中山大学 数据科学与计算机学院, 广州 510006
  • 收稿日期:2016-07-18 修回日期:2016-08-22 出版日期:2017-03-10 发布日期:2017-03-22
  • 通讯作者: 胡学敏
  • 作者简介:周慧子(1995-),女,辽宁沈阳人,主要研究方向:动态路径规划;胡学敏(1985-),男,湖南岳阳人,讲师,博士,主要研究方向:计算机视觉、动态路径规划;陈龙(1985-),男,湖北襄阳人,讲师,博士,主要研究方向:立体视觉、无人驾驶;田梅(1995-),女,湖北武汉人,主要研究方向:动态路径规划;熊豆(1995-),女,湖北武汉人,主要研究方向:自动控制。
  • 基金资助:
    国家自然科学基金青年基金资助项目(41401525);广东省自然科学基金资助项目(2014A030313209);湖北省大学生创新创业训练计划基金资助项目(201410512030)。

Dynamic path planning for autonomous driving with avoidance of obstacles

ZHOU Huizi1, HU Xuemin1, CHEN Long2, TIAN Mei1, XIONG Dou1   

  1. 1. School of Computer Science and Information Engineering, Hubei University, Wuhan Hubei 430062, China;
    2. School of Data and Computer Science, Sun Yat-sen University, Guangzhou Guangdong 510006, China
  • Received:2016-07-18 Revised:2016-08-22 Online:2017-03-10 Published:2017-03-22
  • Supported by:
    This work is partially supported by the National Natural Science Foundation of China (41401525), the Natural Science Foundation of Guangdong Province (2014A030313209), the Student's Platform for Innovation and Entrepreneurship Training Program of Hubei Province (201410512030).

摘要: 针对自动驾驶中避障的动态路径规划问题,提出一种在已知车辆的初始位置、速度、方向和障碍物位置情况下,实时避开障碍物的动态规划算法。首先,利用三次样条曲线的二阶连续性,结合已知的车道信息产生道路基准线;其次,以车辆的位置方向和道路的曲率构建s-q坐标系,并在s-q坐标系内产生从车辆当前位置到目的位置的一簇平滑曲线,作为候选路径;最后,综合考虑车辆行驶的安全性、平滑性和连贯性准则,设计一种新的代价函数,并且通过使代价函数最小化的方法从候选路径中选择最佳路径。在实验过程中,通过设计多种不同的模拟道路来检验算法的性能。实验结果表明,该方法在多种地形的单车道和多车道道路上都能够规划出安全、平滑的路径,有效避开障碍物,并且具有较好的实时性。

关键词: 自动驾驶, 动态路径规划, 候选路径, 路径选择, 代价函数

Abstract: To deal with the problem of dynamic path planning for autonomous driving with avoidance of obstacles, a real-time dynamic path planning approach was proposed to avoid obstacles in real-time under the condition of knowing initial vehicle position, speed, orientation and the obstacle positions. Firstly, a base frame of the road was constructed using the continuity of the second derivative for cubic spline curves combined with the information of the road edges and lanes. Secondly, the s-q coordinate system was established using the position and orientation of the vehicle and the curvature of the road. Then a set of smooth curves from the current position to the destination were generated as the path candidates in the s-q coordinate system. Finally, considering the factors of safety, smoothness and continuity, a novel cost function was designed, and the optimal path was selected by minimizing the cost function. Various simulative roads were designed to test the proposed method in the experiments. The experimental results show that the proposed approach has the ability of planning a safe and smooth path for avoiding the obstacles on both single-lane roads and multi-lane roads with good real-time performance.

Key words: autonomous driving, dynamic path planning, path candidate, path selection, cost function

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