多工况下自动泊车系统停车位识别方法研究  

Research on parking space identification method of automaticparking system under multiple working conditions

作　　者：汪永旺 汪石农 姜灏[2] 周倪青[2] 李志晋 Wang Yongwang;Wang Shinong;Jiang Hao;Zhou Niqing;Li Zhijin(Anhui Polytechnic University,School of Electrical Engineering,Wuhu 241000,China;Chery Automobile Co.,Ltd.,Wuhu 241000,China)

机构地区：[1]安徽工程大学电气工程学院,芜湖241000 [2]奇瑞汽车股份有限公司,芜湖241000

出　　处：《电子测量与仪器学报》2022年第9期174-182,共9页Journal of Electronic Measurement and Instrumentation

基　　金：安徽省高校自然科学重点项目(KJ2021A0508);安徽工程大学国家基金预研项目(Xjky2020019);电气传动与控制安徽省重点实验室开放基金项目(DQKJ202207)资助。

摘　　要：针对自动泊车系统需要对多工况下的停车位进行正确识别的问题,提出了一种基于摄像头和超声波传感器进行距离和视觉信息融合的停车位识别方法。该方法首先通过摄像头和超声波传感器对停车位进行识别,识别成功则输出停车位类型,否则融合摄像头、超声波传感器和车轮速传感器的信息得出车辆的车身姿态特征参数,通过模糊推理方法输出相应的停车位类型。然后,多工况下停车位识别仿真模型在MATLAB上被搭建,并针对不同的停车位场景进行了仿真分析,仿真结果表明了该方法的合理性和可靠性。最后,在多工况下对该方法进行了实车实验,停车位识别正确率超过了90%,表明了该方法具有实际应用的可行性。Aiming at the problem that automatic parking system needs to correctly identify the parking space under multiple working conditions, this paper proposes a parking space recognition method based on distance and visual information fusion of cameras and ultrasonic sensors. This method first identifies the parking space through cameras and ultrasonic sensors, and the parking space type is output if the identification is successful. Otherwise, the information of cameras, ultrasonic sensors and wheel speed sensors is fused to obtain the vehicle parking position characteristic parameters, and the corresponding parking space type is output through fuzzy reasoning. Then, the simulation model of parking space identification under multiple working conditions is built on MATLAB, and the simulation analysis is carried out for different parking space scenarios. The simulation results show that the method is reasonable and reliable. Finally, the real vehicle experiment is carried out under multiple working conditions, and the parking space recognition accuracy is more than 90%, indicating that the method is feasible for practical application.

关 键 词：信息融合 模糊推理 停车位识别 

分 类 号：TP274[自动化与计算机技术—检测技术与自动化装置]