Path tracking of automatic parking based on nonlinear model predictive control

In megacities, the number of vehicles has rapidly grown. Automatic parking, a special type of unmanned driving, has become an important technology to ease parking difficulties. Path tracking is also a core part of automatic parking. However, during automatic parking, the curvature of the reference p...

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Main Authors: GU Qing, BAI Guo-xing, MENG Yu, LIU Li, LUO Wei-dong, GAN Xin
Format: Article
Language:zho
Published: Science Press 2019-07-01
Series:工程科学学报
Subjects:
Online Access:http://cje.ustb.edu.cn/article/doi/10.13374/j.issn2095-9389.2019.07.014
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author GU Qing
BAI Guo-xing
MENG Yu
LIU Li
LUO Wei-dong
GAN Xin
author_facet GU Qing
BAI Guo-xing
MENG Yu
LIU Li
LUO Wei-dong
GAN Xin
author_sort GU Qing
collection DOAJ
description In megacities, the number of vehicles has rapidly grown. Automatic parking, a special type of unmanned driving, has become an important technology to ease parking difficulties. Path tracking is also a core part of automatic parking. However, during automatic parking, the curvature of the reference path is very large. This poses a challenge in automatic parking and is different from that in high-speed unmanned driving. When the curvature of the reference path is large, the constraints of the system severely restrain the path tracking performance. These constraints include the limit of the steering wheel angle speed. Applying model predictive control is a good way to handle multiple constraints. Recently, a path tracking controller for automatic parking based on linear time-varying model predictive control has been reported. However, for automatic parking, the accuracy of the linearized prediction model is still insufficient. To solve this problem, a path tracking controller based on nonlinear model predictive control was proposed in this paper. This controller was compared with the controller based on linear time-varying model predictive control. The simulation environment is a combination of MATLAB/Simulink and PreScan. The simulation results show that the proposed controller could complete automatic parking with multiple constraints. After the parking was completed, the angle between the vehicle heading and the center line of the parking space was 0.0189 rad. The distance between the midpoint of the rear axle of the vehicle and the center line of the parking space was 0.1045 m. This distance was only 5.56% of the width of the vehicle body. Compared with the controller based on linear time-varying model predictive control, the proposed controller for automatic parking exhibited a higher parking precision, larger safety margin, and less parking time. In terms of real-time performance, the proposed controller could also meet the requirements for automatic parking.
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spelling doaj-art-4c066df8f1a04bf08f7f3112d3f3f7db2025-08-20T02:16:56ZzhoScience Press工程科学学报2095-93892019-07-0141794795410.13374/j.issn2095-9389.2019.07.014Path tracking of automatic parking based on nonlinear model predictive controlGU Qing0BAI Guo-xing1MENG YuLIU Li2LUO Wei-dong3GAN Xin4School of Mechanical Engineering, University of Science and Technology Beijing, Beijing 100083, ChinaSchool of Mechanical Engineering, University of Science and Technology Beijing, Beijing 100083, ChinaSchool of Mechanical Engineering, University of Science and Technology Beijing, Beijing 100083, ChinaSchool of Mechanical Engineering, University of Science and Technology Beijing, Beijing 100083, ChinaSchool of Mechanical Engineering, University of Science and Technology Beijing, Beijing 100083, ChinaIn megacities, the number of vehicles has rapidly grown. Automatic parking, a special type of unmanned driving, has become an important technology to ease parking difficulties. Path tracking is also a core part of automatic parking. However, during automatic parking, the curvature of the reference path is very large. This poses a challenge in automatic parking and is different from that in high-speed unmanned driving. When the curvature of the reference path is large, the constraints of the system severely restrain the path tracking performance. These constraints include the limit of the steering wheel angle speed. Applying model predictive control is a good way to handle multiple constraints. Recently, a path tracking controller for automatic parking based on linear time-varying model predictive control has been reported. However, for automatic parking, the accuracy of the linearized prediction model is still insufficient. To solve this problem, a path tracking controller based on nonlinear model predictive control was proposed in this paper. This controller was compared with the controller based on linear time-varying model predictive control. The simulation environment is a combination of MATLAB/Simulink and PreScan. The simulation results show that the proposed controller could complete automatic parking with multiple constraints. After the parking was completed, the angle between the vehicle heading and the center line of the parking space was 0.0189 rad. The distance between the midpoint of the rear axle of the vehicle and the center line of the parking space was 0.1045 m. This distance was only 5.56% of the width of the vehicle body. Compared with the controller based on linear time-varying model predictive control, the proposed controller for automatic parking exhibited a higher parking precision, larger safety margin, and less parking time. In terms of real-time performance, the proposed controller could also meet the requirements for automatic parking.http://cje.ustb.edu.cn/article/doi/10.13374/j.issn2095-9389.2019.07.014vehicleautomatic parkingpath trackingmotion controlnonlinear model predictive control
spellingShingle GU Qing
BAI Guo-xing
MENG Yu
LIU Li
LUO Wei-dong
GAN Xin
Path tracking of automatic parking based on nonlinear model predictive control
工程科学学报
vehicle
automatic parking
path tracking
motion control
nonlinear model predictive control
title Path tracking of automatic parking based on nonlinear model predictive control
title_full Path tracking of automatic parking based on nonlinear model predictive control
title_fullStr Path tracking of automatic parking based on nonlinear model predictive control
title_full_unstemmed Path tracking of automatic parking based on nonlinear model predictive control
title_short Path tracking of automatic parking based on nonlinear model predictive control
title_sort path tracking of automatic parking based on nonlinear model predictive control
topic vehicle
automatic parking
path tracking
motion control
nonlinear model predictive control
url http://cje.ustb.edu.cn/article/doi/10.13374/j.issn2095-9389.2019.07.014
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AT liuli pathtrackingofautomaticparkingbasedonnonlinearmodelpredictivecontrol
AT luoweidong pathtrackingofautomaticparkingbasedonnonlinearmodelpredictivecontrol
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