Multi-condition Parking Space Recognition Based on Information Fusion and Decision Planning of Automatic Parking System

doi:10.3901/JME.2021.06.131

Abstract

Abstract: Aiming at the lack of recognition of inclined parking spaces in automatic parking system, a method of intelligent recognition of inclined parking spaces in daily life is proposed, and multi-condition parking spaces recognition and parking are achieved. Based on the recognition of existing parallel and vertical parking spaces, the method is combined with distance and visual information. In this method, the information of ultrasonic sensor, camera and wheel speed sensor are used to obtain the pose feature parameters of a vehicle, the Sugeno fuzzy inference method is used to to determine three different types of parking spaces: horizontal, vertical and inclined. subsequently, the multi- condition parking space identification model and the corresponding path planning model are built in Matlab/Simulink soft, and the simulation is carried out for six different types of inclined parking spaces, parallel parking spaces and vertical parking spaces. finally, the real vehicle test is carried out. The simulation and real vehicle test results show the effectiveness and rationality of the above parking space identification method and path planning strategy.

Key words: information fusion, inclined parking spaces, multi-condition parking spaces recognition, fuzzy reasoning, analysis of obstacle avoidance

CLC Number:

U461

JIANG Wuhua, XIN Xin, CHEN Wuwei, CUI Weiwei. Multi-condition Parking Space Recognition Based on Information Fusion and Decision Planning of Automatic Parking System[J]. Journal of Mechanical Engineering, 2021, 57(6): 131-141.

References

[1] 徐磊. 基于EPS的自动泊车路径规划及跟踪控制研究[D]. 合肥:合肥工业大学,2017. XU Lei. Research on path planning and tracking of automatic parking system based on EPS[D]. Hefei:Hefei University of Technology,2017.
[2] SCHWESINGER U,BÜRKI M,TIMPNER J,et al. Automated valet parking and charging for e-mobility[C]//Institute of Electrical and Electronics Engineers. Intelligent Vehicles Symposium. Gothenburg,Sweden:IEEE,2016:157-164.[3] VIJAY J,SWARN R. Vision and dead reckoning-based end-to-end parking for autonomous vehicles[C]//Institute of Electrical and Electronics Engineers. Intelligent Vehicles Symposium. Changshu,China:IEEE,2018:2182-2187.[4] JANG C,SUNWOO M. Semantic segmentation-based parking space detection with standalone around view monitoring system[J]. Machine Vision and Applications,2019,30(2):309-319.
[5] DAXWANGER W A,SCHMIDT G K. Skill-based visual parking control using neural and fuzzy networks[C]//Institute of Electrical and Electronics Engineers. Intelligent Systems for the 21st Century. Vancouver,BC,Canada:IEEE,1995:1659-1664.
[6] XU Jin,CHEN Guang. Vision-guided automatic parking for smart car[C]//Institute of Electrical and Electronics Engineers. Intelligent Vehicles Symposium. Dearborn,MI,USA:IEEE,2002:725-730.
[7] SUHR J K,JUNG H G,BAE K,et al. Automatic free parking space detection by using motion stereo-based 3D reconstruction[J]. Machine Vision and Applications,2010,21(2):163-176.
[8] 王文飞. 基于超声波与机器视觉的自动泊车系统设计[D]. 杭州:浙江大学,2011. WANG Wenfei. Automatic parking system design based on ultasonic and machine vision[D]. Hangzhou:Zhejiang University,2011.
[9] 白中浩,周培义,王飞虎. 基于视觉的车位线识别算法[J]. 中国机械工程,2014,25(20):2825-2829. BAI Zhonghao,ZHOU Peiyi,WANG Feihu. Parking space marking recognition based on vision[J]. China Mechanical Engineering,2014,25(20):2825-2829.
[10] 江浩斌,沈峥楠,马世典,等. 基于信息融合的自动泊车系统车位智能识别[J]. 机械工程学报,2017,53(22):125-122. JIANG Haobin,SHEN Zhengnan,MA Shidian,et al. Intelligent identification of automatic parking system based on information fusion[J]. Journal of Mechanical Engineering,2017,53(22):125-122.
[11] 张永瑞. 基于FPGA的自动斜式泊车系统研究与实现[D]. 大连:大连理工大学,2014. ZHANG Yongrui. Research and implementation of automatic inclined parking system based on FPGA[D]. Dalian:Dalian University of Technology,2014.
[12] SUHR J K,JUNG H G. A universal vacant parking slot recognition system using sensors mounted on off-the-shelf vehicles[J]. Sensors,2018,18(4):1213-1233.
[13] 王凌云. 基于Sugeno型模糊推理算法的模糊控制器及其应用[J]. 电子技术应用,2000,26(10):31-33. WANG Lingyun. Fuzzy controller based on sugeno fuzzy reasoning algorithm and its application[J]. Electronic and Applied Technology,2000,26(10):31-33.
[14] 孟繁微. 车辆垂直泊车转向控制算法研究[D]. 长春:吉林大学,2011. MENG Fanwei. Research on steering control algorithm for automatic vertical parking[D]. Changchun:Jilin University,2011.

[1]	QIAN Min, GENG Keke, YIN Guodong, LI Shangjie, WANG Ziwei, SUN Yuxiao. Re-identification Algorithm for Cooperative Vehicle-infrastructure System Based on Multi-information Fusion [J]. Journal of Mechanical Engineering, 2024, 60(16): 231-240.
[2]	XIAO Chunyu, LUO Xiangping, TIAN Shiqiao, GONG Dao. Research on Railway Track Curvature Detection System Based on Bogie Attitude Trajectory [J]. Journal of Mechanical Engineering, 2023, 59(6): 204-213.
[3]	TENG Hongzhao, DENG Zhaohui, Lü Lishu, GU Qianwei, LIU Tao, ZHUO Rongjin. Research of Process Condition Monitoring Based on Multi-sensor Information Fusion [J]. Journal of Mechanical Engineering, 2022, 58(6): 26-41.
[4]	ZHAO Jie, WU Rui, ZHANG He, ZHU Yanhe, ZANG Xizhe. Research on Operation Skill Transfer and Control Oriented to Complex Force Interaction Tasks [J]. Journal of Mechanical Engineering, 2022, 58(18): 116-132.
[5]	SHEN Huimin, GE Ruikang, GU Xiaowei, CAI Xiaotong, GAN Yi, YANG Geng. Method of Dexterous Finger Unit Full-pose Modeling Based on Magnetic-inertial Sensor Fusion [J]. Journal of Mechanical Engineering, 2022, 58(18): 133-140.
[6]	REN Yanjun, YIN Guodong, SHA Wenhan, SHEN Tong. Longitudinal Velocity Adaptive Estimation for Four-wheel-drive Vehicles Via Kinematic Information Fusion [J]. Journal of Mechanical Engineering, 2021, 57(8): 184-194.
[7]	YE Zhuang, YU Jianbo. Feature Extraction of Gearbox Vibration Signals Based on Multi-Channels Weighted Convolutional Neural Network [J]. Journal of Mechanical Engineering, 2021, 57(1): 110-120.
[8]	XIONG Lu, JIN Da, LENG Bo, YU Zhuoping, YANG Xing. Adaptive Tire-road Friction Estimation Method for Distributed Drive Electric Vehicles Considering Multiple Road Excitations [J]. Journal of Mechanical Engineering, 2020, 56(18): 123-133.
[9]	XUE Peilin, WU Yuan, YIN Guodong, LIU Shuaipeng, LIN Yiheng, HUANG Wenhan, ZHANG Yun. Real-time Target Recognition for Urban Autonomous Vehicles Based on Information Fusion [J]. Journal of Mechanical Engineering, 2020, 56(12): 165-173.
[10]	CHANG Shuhe, ZHANG Haoyu, XU Haiying, HONG Yuxiang, WANG Li, DU Dong. Online Path Recognition for Additive Manufacturing and Arc Welding with Filler Wire Based on Multi-vision Information Fusion [J]. Journal of Mechanical Engineering, 2019, 55(17): 1-7.
[11]	ZHANG Niaona, GUO Konghui, DING Haitao. Driving Cycle Recognition Algorithm Based on Multi-source Information Fusion and Application in Vehicle Torque Distribution [J]. Journal of Mechanical Engineering, 2017, 53(24): 135-143.
[12]	SUN Jian, LI Hongru. Method for Feature Extraction Based on Composite Spectrum and Relative Entropy Fusion [J]. Journal of Mechanical Engineering, 2017, 53(24): 96-103.
[13]	ZHANG Ming, JIANG Zhinong. Reciprocating Compressor Fault Diagnosis Technology Based on Multi-source Information Fusion [J]. Journal of Mechanical Engineering, 2017, 53(23): 46-52.
[14]	JIANG Haobin, SHEN Zhengnan, MA Shidian, CHEN Long. Intelligent Identification of Automatic Parking System Based on Information Fusion [J]. Journal of Mechanical Engineering, 2017, 53(22): 125-133.
[15]	GUO Qianjian, ZHAO Guoyong, CHENG Xiang, QI Xiaoni. Research on Volumetric Error Compensation of Two Turntable Five-axis Machine Tools [J]. Journal of Mechanical Engineering, 2016, 52(13): 189-194.