• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2020, Vol. 56 ›› Issue (4): 125-134.doi: 10.3901/JME.2020.04.125

• 运载工程 • 上一篇    下一篇

基于hp自适应伪谱法的自主泊车路径规划

钱立军, 吴冰, 仇多洋, 胡伟龙   

  1. 合肥工业大学汽车与交通工程学院 合肥 230009
  • 收稿日期:2019-05-29 修回日期:2019-09-16 出版日期:2020-02-20 发布日期:2020-04-23
  • 通讯作者: 吴冰(通信作者),男,1986年出生,博士研究生。主要研究方向为智能辅助驾驶技术。E-mail:hfutwubing@126.com
  • 作者简介:钱立军,男,1962年出生,博士,教授,博士研究生导师。主要研究方向为新能源汽车,智能网联汽车技术。E-mail:qianlijun66@163.com
  • 基金资助:
    国家自然科学基金(51875149,71431003)和安徽省高校自然科学研究(KJ2018A0782)资助项目。

Path Planning of Autonomous Parking Based on hp-adaptive Pseudospectral Method

QIAN Lijun, WU Bing, QIU Duoyang, HU Weilong   

  1. School of Automotive and Transportation Engineering, Hefei University of Technoloy, Hefei 230009
  • Received:2019-05-29 Revised:2019-09-16 Online:2020-02-20 Published:2020-04-23

摘要: 针对自主泊车路径规划最优控制问题求解收敛速率慢的问题,提出基于hp自适应高斯伪谱法的自主泊车路径规划方法。首先建立车辆运动学模型,并考虑自主泊车过程中避障约束和边界约束,再以泊车时间最短为性能目标函数,将自主泊车路径规划问题转化为最优控制问题。采用高斯伪谱法对最优控制问题进行离散化处理并采用序列二次规划进行求解,在求解过程中通过动态调整网格区间个数和多项式阶数实现提高求解收敛速率。根据实际场景选取4种工况并进行路径规划仿真,并将3种伪谱法进行对比分析,仿真结果表明hp自适应高斯伪谱法能够提升自主泊车路径规划最优控制问题求解收敛速率,同时该算法可以实现在狭窄泊车位内的泊车路径规划,通过实车试验验证提出的方法获得的自主泊车路径的有效性。

关键词: 自主泊车, 路径规划, hp自适应伪谱法, 最优控制

Abstract: Aiming at the problem that the convergence rate is slow when solving the optimal control problem of autonomous parking path planning, a method of autonomous parking path planning based on hp-adaptive Gauss pseudospectral method is proposed. First, the vehicle kinematical model is established, then the collision avoidance constraints and the boundary constraints in autonomous parking processes are further considered, finally the problem of autonomous parking path planning is converted into the optimal control problem which takes the shortest parking time as the cost function. The optimal control problem is discretized by Gauss pseudospectral method, and solved by sequential quadratic programming, in which the number of mesh intervals and degree of the polynomial are adjusted dynamically improving the convergence rate. According to the actual scenario, four autonomous parking conditions are designed and path planning is simulated, and three pseudospectral methods are compared and analyzed. The simulation results show that the convergence rate of the optimal control problem of autonomous parking path planning is improved by the hp-adaptive Gauss pseudospectral method, and the proposed mothed can obtain the parking path in a narrow parking lot, the effectiveness of the proposed method for autonomous parking path planning is verified by real vehicle tests.

Key words: autonomous parking, path planning, hp-adaptive pseudospectral method, optimal control

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