## 4 Experiment and Evaluation
### Actual Car Experiment  
The experimental vehicle is the ROEWE Marvel X electric vehicle; the experimental environment is shown in Figure 15; and the hardware architecture of the actual vehicle is shown in Figure 16; Table 4 shows the configuration of the vehicle. The vehicle is equipped with an Around View Monitor (AVM) system around the body, twelve ultrasonic radars around the body, four fisheye cameras, and an RTK-GPS system, which exchanges data with other ECU nodes inside the vehicle via CAN bus and sends control commands to the execution unit. The data are processed using the algorithm proposed in this paper, and the parking control is output to the intelligent parking control unit via the CAN bus. Figure 14: CNN-LSTM network mean square error loss function curve. Figure 15: Actual parallel parking slot: (**a**) Vehicle obstacle, columnar obstacle, and curbstone obstacles; (**b**) columnar obstacle and curbstone obstacles; (**c**) vehicle obstacle and curbstone obstacles; (**d**) vehicle obstacle and fuzzy parking slot line; (**e**) vehicle obstacle and columnar obstacle and fuzzy parking slot line; and (**f**) vehicle obstacle and covered parking slot lines. Because the detection algorithm is beyond the scope of this paper, it is assumed in the experiments that the parked parking position has been detected by AVM or radar. The vehicle position during parking is obtained from RTK-GPS, and the positioning error is only 1-2 cm in the open environment. The actual car experiments consist of the following two groups:  
Group 1: Frame-by-frame analysis of the parking trajectory of the actual car test, Figure 17, shows the experimental environment of this experiment and the end-to-end intelligent parking model controlling the experimental vehicle for parking. The deviation is the mean square error between the car's predicted and actual path coordinates on the \(x\) and \(y\) axis. Figure 18 shows the comparison trajectory between the actual car and the test for the complete parking process with \(MSE\) of 0.048 for the \(x\)-axis trajectory coordinates and 0.012 for the y-axis trajectory coordinates. Figure 19 compares the control decision between the actual car and the test for the actual car for this parking process. The results show that the computational model provides a smooth driving experience that is consistent with a skilled driver. Group 2: Design of end-to-end intelligent parking and existing path-tracking intelligent parking of parking accuracy and actual time comparison experiments: There are six types of experimental environments, such as bilateral car obstacle, bilateral column obstacle, unilateral column obstacle, unilateral car obstacle, fuzzy or obscured slot line, and the arrow points to three different angles (\(0^{\circ}\), \(-4^{\circ}\), \(4^{\circ}\)) of parking starting; there are three relative positions of 1 m, 1.5 m, and 2 m. A total of 54 working conditions and 20 sets of end-to-end intelligent parking model and existing path-tracking intelligent parking model with the standard parking position were conducted under each working condition to compare the parking test, where the distance between the standard parking position and the boundary on both sides was 0.3 m, the distance between the rear end and the rear side boundary was 0.2 m (the standard parking position is shown in Figure 20), and 1080 sets of parking data were finally obtained. \begin{table}
\begin{tabular}{c c} \hline \hline
**Name** & **Data** \\ \hline Length/m & 4.67 \\ Width/m & 1.90 \\ Wheelbase/m & 2.80 \\ Front suspension/m & 0.94 \\ Rear suspension/m & 0.93 \\ Minimum turn radius of car/m & 6.00 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Configuration of vehicle. Figure 16: (**a**) The hardware architecture of the intelligent parking experimental system; (**b**) path data collection platform. Figure 17: Parallel parking trajectory comparison experiment: **(a)** Start parking; **(b)** Car turning; **(c)** Continuous turning; **(d)** Second turning; **(e)** Enter the parking space; **(f)** Complete parking.