汽车工程 ›› 2021, Vol. 43 ›› Issue (7): 978-986.doi: 10.19562/j.chinasae.qcgc.2021.07.004

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基于双五次多项式的智能汽车换道轨迹规划

牛国臣(),李文帅,魏洪旭   

  1. 中国民航大学机器人研究所,天津 300300
  • 收稿日期:2020-09-02 修回日期:2021-01-27 出版日期:2021-07-25 发布日期:2021-07-20
  • 通讯作者: 牛国臣 E-mail:niu_guochen@139.com
  • 基金资助:
    天津市科技计划项目(17ZXHLGX00120)

Intelligent Vehicle Lane Changing Trajectory Planning Based on Double Quintic Polynomials

Guochen Niu(),Wenshuai Li,Hongxu Wei   

  1. Robotics Institute,Civil Aviation University of China,Tianjin 300300
  • Received:2020-09-02 Revised:2021-01-27 Online:2021-07-25 Published:2021-07-20
  • Contact: Guochen Niu E-mail:niu_guochen@139.com

摘要:

为满足智能汽车换道过程中安全性和舒适性的要求,提出了一种基于双五次多项式的智能汽车换道轨迹规划算法。以动态规划换道时间和增加舒适性约束条件来改进五次多项式规划算法,在该基础上结合当前环境和换道始末状态计算出中转状态,并采用两次改进的五次多项式算法避免与前方车辆碰撞。轨迹规划与轨迹跟踪的仿真和试验结果表明,对于不同的工况,本文中提出的双五次换道轨迹规划算法在横向速度、加速度、加速度变化率以及算法运行时间等方面都具有优势,得到的轨迹也满足实际状况下的车辆换道要求,安全性得到提升且操纵稳定性良好,证明该算法具有一定的实际应用价值。

关键词: 智能汽车, 换道, 轨迹规划, 双五次多项式, 轨迹跟踪

Abstract:

In order to meet the requirements of safety and comfort during lane changing of the intelligent vehicle, an intelligent vehicle lane changing trajectory planning algorithm based on double quintic polynomials is proposed. The quintic polynomial programming algorithm is improved with the condition of dynamic programming of lane changing time and increased comfort constraints. On this basis, the transit state is calculated by combining the current environment and the beginning and end states of the lane changing, and the twice improved quintic polynomial algorithm is used to avoid collision with the vehicle in front. The simulation and experiment results of trajectory planning and trajectory tracking show that the proposed double quintic polynomials lane changing trajectory planning algorithm has advantages in lateral velocity, acceleration, acceleration rate of change and running time of the algorithm under different working conditions. In addition, the trajectory obtained can also meet the requirements of vehicle lane changing under the actual situation, with improved safety and good handling stability, which proves that the algorithm has certain practical application value.

Key words: intelligent vehicle, lane changing, trajectory planning, double quintic polynomials, trajectory tracking