## 6 Conclusions and Prospects  
A new method is proposed in this paper for path planning and tracking control of an automatic parking system for intelligent vehicles, which involves the optimization of the parking path planning method, verification of the path tracking control algorithm, and the simulation experiments and real vehicle testing of the proposed parking path planning and tracking control model. The results obtained from the automatic parking system developed based on the proposed parking path planning and tracking control model indicates that it is not only highly intelligent, but also available to lead to a higher parking success rate and a better parking efficiency, and offer a higher parking reliability and stability to drivers.  
The main objectives and conclusions of this paper are summarized as follows:  
1. Established the vehicle kinematic model of parking and analyzed the parking movement constraints. A reasonable and feasible parallel parking path planning program was proposed,  
Figure 25: Photos of Automatic Parking Test.  
and the simulation analysis was carried out. In addition, an optimization method for the curvature outliers in the path was studied based on the preview theory. Thus, the parking path was ultimately optimized.
2. To reflect the vehicle movement correctly and accurately, the simplified path tracking model for parking was developed. To improve the path tracking accuracy, an automatic parking path tracking controller was designed based on the dual closed-loop sliding mode variable structure control algorithm.
3. The testing vehicle model was built in CarSim, and the input and output variables of the control were predefined. The co-simulation platform was built with CarSim and MATLAB/Simulink. The parking path planning and tracking control model was designed and optimized in the platform. Besides, the effectiveness of the control model was verified by the co-simulation experiment.
4. An automatic parking system was developed based on the control model designed in this paper, and the real vehicle parking testing was carried out. The effectiveness of the control mode was further verified, and the high reliability and stability of the control mode were justified.  
In the follow-up research, we will further optimize the driver and threshold configuration of ultrasonic radar, and improve the parking slot searching algorithm thus improving improve the accuracy of boundary detection, and laying the foundation for further optimizing of the parking path. In addition, we will improve the vehicle control model to eliminate vehicle positioning and attitude errors caused by accumulated errors, thereby improving tracking control accuracy and further increasing the parking success rate.  
[PERSON] and [PERSON] designed the scheme. [PERSON], [PERSON], and [PERSON] checked the feasibility of the scheme. [PERSON] designed the control model and performed the software simulation experiments. [PERSON], [PERSON], and [PERSON] cooperate designed and developed the controller hardware. [PERSON] and [PERSON] provided the resources. [PERSON] and [PERSON] assisted [PERSON] conducted the real vehicle test. [PERSON] wrote the paper with help of [PERSON] and [PERSON]. All authors have read and agreed to the published version of the manuscript.  
This research was supported by the Natural Science Fund for Colleges and Universities in Jiangsu Province under Grant 16 KJA580001 and the National Natural Science Foundation of China under Grant 51675235.  
The authors declare no conflict of interest.