计算机科学

计算机科学 ›› 2019, Vol. 46 ›› Issue (10): 273-278.doi: 10.11896/jsjkx.190400147

• 人工智能 • 上一篇    下一篇

基于梯形规划曲线的智能车速度规划算法研究

曹波1, 李永乐2, 朱英杰1, 贾斌2, 徐友春2   

  1. (陆军军事交通学院学员五大队 天津300161)1
    (陆军军事交通学院军事交通运输研究所 天津300161)2
  • 收稿日期:2019-04-26 修回日期:2019-07-07 出版日期:2019-10-15 发布日期:2019-10-21
  • 通讯作者: 李永乐(1984-),男,工程师,主要研究方向为计算机视觉,E-mail:liyongle1984@163.com。
  • 作者简介:曹波(1994-),男,硕士生,主要研究方向为智能车运动规划,E-mail:1509968341@qq.com;朱英杰(1993-),男,硕士生,主要研究方向为智能车运动规划;贾斌(1962-),男,教授,主要研究方向为交通运输信息技术;徐友春(1972-),男,教授,主要研究方向为智能车环境感知。
  • 基金资助:
    本文受国家重点研发计划项目(2016YFB0100903)资助。

Research on Intelligent Vehicle Speed Planning Algorithms Based on Trapezoidal Planning Curve

CAO Bo1, LI Yong-le2, ZHU Ying-jie1, JIA Bin2, XU You-chun2   

  1. (Student Brigade 5,Army Military Transportation University,Tianjin 300161,China)1
    (Military Transportation Research Institute,Army Military Transportation University,Tianjin 300161,China)2
  • Received:2019-04-26 Revised:2019-07-07 Online:2019-10-15 Published:2019-10-21

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摘要： 针对QP(Quadratic Programming)算法应用于智能车速度规划时,存在停车过程减速较晚而导致减速距离短、平稳性差的问题,文中提出了基于梯形规划曲线的智能车速度规划算法。首先建立速度规划的QP模型并求解;然后分析不同初速度下基于梯形规划曲线的停车过程,将其结果作为非线性约束来实例化QP模型并再次求解;最后通过仿真实验和实车实验对比分析QP算法和所提算法的实验结果。仿真实验中,分别以39.8 km/h,31.5 km/h,20.6 km/h的初速度进入停车过程,速度变化曲线表明所提算法能够将减速开始时间提前,初步表明该算法具有优化效果;实车实验中,较QP算法而言,所提算法将3种初速度下的停车过程分别提前5.9 s,5.0 s,3.7 s,平均加速度绝对值分别减少0.5 m/s2,0.5 m/s2,0.4 m/s2,最大加速度绝对值分别减少0.16 m/s2,0.33m/s2,0.35 m/s2。仿真实验和实车实验表明,所提算法的改进效果明显,具有显著的优化作用。

关键词: QP算法, 速度规划, 梯形规划曲线, 智能车

Abstract: Aiming at the problem of short deceleration distance and poor stationarity caused by late deceleration in par-king process when QP (quadratic programming) algorithm is applied to speed planning of intelligent vehicles,there are some problems such as short deceleration distance and poor stationarity caused by late deceleration in the stopping process.This paper presented an intelligent vehicle speed planning algorithm based on the trapezoidal programming curve.Firstly,the QP model of speed planning is established and solved.Then,the stopping process based on trapezoidal programming curve at different initial speeds is analyzed,andits results are considered as nonlinear constraint to instantiate and solved QP model .Finally,the experimental results of QP algorithm and the algorithm were compared and analyzed through simulation experiment and real car experiment.In the simulation experiment,the initial speed of 39.8 km/h,31.5 km/h and 20.6 km/h was used to enter the parking process respectively.The speed curve shows that the proposed algorithm can advance the deceleration time,which preliminarily shows that the algorithm has the optimization effect.In the real vehicle experiment,compared with QP algorithm,the proposed algorithm advances the parking process of the three initial speed by 5.9 s,5.0 s and 3.7 s,the absolute value of the average acceleration decreases by 0.5 m/s2,0.5 m/s2and 0.4 m/s2,the absolute value of the maximum acceleration decreases respectively by 0.16 m/s2,0.33 m/s2 and 0.35 m/s2.The simulation and real vehicle experiments show that the improved method has obvious improvement effect and significant optimization effect.

Key words: Intelligent vehicle, QP algorithm, Speed planning, Trapezoidal planning curve

中图分类号: 

  • TP242
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