适用于车头泊入的路径规划和跟踪控制新方法

doi:10.3778/j.issn.1002-8331.2108-0423

摘要/Abstract

摘要： 自动泊车作为智能汽车自动驾驶技术的一个关键组成部分，已成为业界关注和研究的热点。现有的自动泊车系统都是基于倒车实现，而大多数新型电动汽车充电口安装在车头，因此设计了车头泊入的泊车新方法。该方法首先对车辆进行运动学建模，然后根据汽车与车库的相对位置基于几何推导进行路径规划，最后利用PID对泊车过程进行跟踪控制。采用PID路径跟踪控制算法与现有泊车跟踪控制算法相比较，有效简化了算法结构，克服了“计算爆炸”的问题，具有较强的鲁棒性，符合现有新型电动汽车车头泊入的需求。使用Matlab和CarSim联合仿真实车参数模型车的运动学模型，完善了传统泊车过程模型的运动仿真分析，仿真结果验证了所设计的跟踪控制方法的有效性。

关键词: 电动汽车, 车头泊入, 路径规划, PID跟踪控制, 联合仿真

Abstract: As a key component of smart car autonomous driving technology, automatic parking has become a focus of attention and research in the industry. Since the existing automatic parking systems are based on reversing, and most new electric vehicle charging ports are installed in the front of the car, this paper designs a parking method for the head of the car. The process of this method mainly includes the kinematics modeling of the vehicle, then the path planning is based on geometric derivation according to the relative position of the car and the garage, finally the PID is used to track and control the parking process. In addition, compared with the existing parking tracking control algorithm, this paper adopts the PID path tracking control algorithm, which effectively simplifies the algorithm structure and overcomes the problem of “computational explosion”. It has strong robustness, and conforms to the existing new models and the demand for the parking of electric cars. Finally, by building a test model car in CarSim, and using the Matlab platform to conduct a joint simulation experiment, this paper effectively solves that the traditional model can not comprehensively analyze the motion simulation of the automatic parking process, the simulation results verify the effectiveness of the tracking control method designed in this paper.

Key words: electric vehicles, head parking, path planning, PID tracking control, co-simulation

詹瑞典, 黄经伟, 张学习, 肖淳, 侯帅, 蔡述庭. 适用于车头泊入的路径规划和跟踪控制新方法[J]. 计算机工程与应用, 2023, 59(4): 297-302.

ZHAN Ruidian, HUANG Jingwei, ZHANG Xuexi, XIAO Chun, HOU Shuai, CAI Shuting. New Method of Path Planning and Tracking Control for Head Parking[J]. Computer Engineering and Applications, 2023, 59(4): 297-302.

参考文献

[1] 唐维军，徐琨，柳有权，等.自动驾驶汽车虚拟测试中的树木点云生成法[J].计算机工程与应用，2021，57（11）：185-192.
TANG W J，XU K，LIU Y Q，et al.Method for generating three-dimensional point cloud of trees in autonomous vehicle virtual testing[J].Computer Engineering and Applications，2021，57（11）：185-192.
[2] 石贞洪，江洪，于文浩.适用于路径跟踪控制的自适应MPC算法研究[J].计算机工程应用，2020，56（21）：266-271.
SHI Z H，JIANG H，YU W H，et al.Research on adaptive MPC algorithm for path tracking control[J].Computer Engineering and Applications，2020，56（21）：266-271.
[3] HUANG Y，DING H，ZHANG Y，et al.A motion planning and tracking framework for autonomous vehicles based on artificial potential field elaborated resistance network（APFE-RN） approach[J].IEEE Transactions on Industrial Electronics，2020，67（2）：1376-1386.
[4] XIONG Z，LI W，HAN Q，et al.Privacy-preserving auto-driving：a GAN-based approach to protect vehicular camera data[C]//2019 IEEE International Conference on Data Mining，2019：668-677.
[5] 张公凯，陈才学，郑拓.改进鲸鱼算法在电动汽车有序充电中的应用[J].计算机工程与应用，2021，57（4）：272-278.
ZHANG G K，CHEN C X，ZHENG T.Application of improved whale optimization algorithm in ordered charging of electric vehicle[J].Computer Engineering and Applications，2021，57（4）：272-278.
[6] 韩爱青.全球新能源汽车推广势在必行[J].高科技与产业化，2021，27（1）：35-37.
HAN A Q.Global promotion of new energy vehicles is imperative[J].High-Tech and Industrialization，2021，27（1）：35-37.
[7] JUNG K，PARK J，SON S，et al.Position prediction of wireless charging electric vehicle for auto parking using extreme gradient boost algorithm[C]//2020 IEEE Wireless Power Transfer Conference，2020：439-442.
[8] 李红，郭孔辉.基于Matlab的多约束自动平行泊车轨迹规划[J].中南大学学报（自然科学版），2013，44（1）：101-107.
LI H，GUO K H.Trajectory planning of automatic parallel parking with multi-constraints based on Matlab[J].Journal of Central South University（Science and Technology），2013，44（1）：101-107.
[9] 宋若旸，阙海霞，马宗钰，等.基于改进RRT*算法的自动驾驶车辆路径规划研究[J].汽车实用技术，2021，46（1）：20-22.
SONG R Y，QUE H X，MA Z Y，et al.Path planning of autonomous vehicles at intersections based on improved RRT*[J].Automobile Applied Technology，2021，46（1）：20-22.
[10] 徐立平.基于阿克曼理论的转向梯形设计分析[J].机械工程师，2017（5）：69-70.
XU L P.Analysis of steering trapezoid design based on Ackerman’s theory[J].Mechanical Engineer，2017（5）：69-70.
[11] 高琳琳，唐风敏，郭蓬，等.自动驾驶横向运动控制的改进LQR方法研究[J].机械科学与技术，2021，40（3）：435-441.
GAO L L，TANG F M，GUO P，et al.Research on improved LQR method for self-driving vehicle lateral control[J].Mechanical Science and Technology for Aerospace Engineering，2021，40（3）：435-441.
[12] 张海亮，张娟萍，池荣虎.汽车智能自动驾驶的PID控制方法研究[J].时代汽车，2020（21）：33-34.
ZHANG H L，ZHANG J P，CHI R H.Research on PID control method of automobile intelligent autopilot[J].Auto Time，2020（21）：33-34.
[13] PIAO C，LIU X，LU C.Lateral control using parameter self-tuning LQR on autonomous vehicle[C]//2019 International Conference on Intelligent Computing，Automation and Systems，2019：913-917.
[14] FARAG W，SALEH Z.MPC track follower for self-driving cars[C]//2nd Smart Cities Symposium，2019：1-6.
[15] DANI S，SONAWANE D，INGOLE D，et al.Performance evaluation of PID，LQR and MPC for DC motor speed control[C]//2017 2nd International Conference for Convergence in Technology，2017：348-354.