## 5 Automatic Parking Test of Real Vehicle  
To verify the effectiveness of the research in this paper, the automatic parking system developed is based on a control model and a real vehicle test. Figure 20 shows the architecture of the automatic parking system developed in this paper. The automatic parking system uses 12 ultrasonic radar sensors to reduce the detection blind area around the vehicle. Among them, the eight radar sensors installed both in front of and at the rear of the vehicle are short-range ultrasonic radar with a detection range of more than 2.5 m, which are mainly used to detect obstacles in the parking path, while the four radar sensors installed on the sides of the vehicle are long-distance ultrasonic radar with the detection distance of more than 4.5 m, which are mainly used for parking space detection. Meanwhile, the four radar sensors on the vehicle sides can detect obstacles around the vehicle during parking operation. Figure 19: Parking Path Tracking Results of Reference [22]. Figure 20: Framework of Automatic Parking System. Note: In the above framework diagram, radar refers to ultrasonic radar sensor, EMS/VCU represents the power control unit, GSM denotes the shift control unit, EPS is steering control unit, EPB refers to the parking control unit, HMI represents the human-machine interaction unit, and ABS/ESU is brake control unit. Besides, Controller means the automatic parking controller designed in this paper, and CAN refers to the vehicle controller area network. The equipment required for real vehicle test included the following: Test Vehicle, Automatic Parking System, CANoe, Laptop (Equipped with the software CodeWarrior 10.6.4, FreeMaster and MATLAB), PE Downloader, Oscilloscope, etc., as shown in Figure 21. Among them, the automatic parking system is installed on the test vehicle for parking test, CANOE is used to collect vehicle operating data, and the laptop is used for data recording and parameter debugging (CodeWarrior 10.6.4 provides the editing environment of the single-chip microcomputer used in this system, while FreeMaster and MATLAB Software is used for data recording and analysis). The PE downloader is available to download the program to the controller ECU, and the oscilloscope is used for signal acquisition and signal monitoring. To verify the effectiveness of the path planning and path tracking, control model is designed in this paper through real vehicle automatic parking. First of all, an open space was used to build a parking slot with sufficient length. The requirements in terms of parking slot size can be satisfied by only one reverse gear, thus completing the parking. The parameters of the parking slot used in the test are: length \(\times\) width = 7 m \(\times\) 2.5 m. After that, FreeMaster software is used to record the driving trajectory data during the whole parking process. Finally, the coordinates of the rear axle midpoint of the vehicle are selected and imported into MATLAB for conversion and processing. The trajectory of the rear axle midpoint of the test vehicle during the parking is plotted, as shown in Figure 22.  
The optimized parking path is compared with the actual trajectory of the test vehicle in Matlab. As per Figure 23, the results show that the deviation between the actual trajectory and the planned path is small, and the test vehicle is able to track the planned path to complete the parking well. Since the above parking slot is large and relatively rare in parking lots, in order to verify the effectiveness of the design control model in the real parking scenario, parking slots were built based on a real parking scenario, and several automatic parking tests were conducted. There are two kinds of parking slots for the automatic parking test. One is the standard parking slot on the right side with a length of 5.9 m (i.e., vehicle length + 1.2 m), which is composed of the front and rear obstacles with the curbstone.