## 5 Conclusions  
This paper first proposed an enhanced berth mapping model for underground parking scenes. The generated lightweight map was distributed in block form around key parking berths, and each map block consisted of a certain number of discrete nodes. Furthermore, a high-precision multimodal localization method was proposed that integrated the lightweight map and the Clothoid trajectory prediction. This method used trajectory prediction to determine the position range of the vehicle and employed an adaptive localization strategy that matched the prediction result. The experiments were conducted in two typical underground parking scenes, leading to the following conclusions:  
1. The proposed representation method constructed a lightweight map based on the scene data associated with the key berths, effectively compressing the memory requirements of the map while assisting the intelligent vehicles in achieving high-precision positioning. Additionally, it offered the advantages of a low mapping cost, a low maintenance cost, and high practicality. 2. The proposed localization method achieved a trajectory prediction accuracy of 40 cm on multiple datasets from two typical underground parking scenes. Meanwhile, the accuracy of the nearest map node retrieval exceeded 92%, and the metric localization accuracy met the 30 cm standard. This demonstrated that the proposed localization method possessed high precision, robustness, and applicability to diverse scenes. Si \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Scene**} & \multirow{2}{*}{**Loop**} & \multirow{2}{*}{**Method**} & \multicolumn{4}{c}{**Average Time Consumption (ms)**} \\ \cline{4-7}  & & & **Group 1** & **Group 2** & **Group 3** & **Group 4** \\ \hline \multirow{4}{*}{Industrial park} & \multirow{2}{*}{2 nd} & Ours & 132 & 114 & 145 & 119 \\  & & Tao’s & 1765 & 1540 & 1947 & 1490 \\  & & PAN-SLAM & 116 & 101 & 116 & 101 \\  & & Ours & 144 & 102 & 155 & 107 \\  & & Tao’s & 1798 & 1510 & 1993 & 1469 \\  & & PAN-SLAM & 121 & 98 & 121 & 98 \\ \hline \multirow{4}{*}{Mall} & \multirow{2}{*}{2 nd} & Ours & 131 & 125 & 149 & 122 \\  & & Tao’s & 1906 & 1731 & 1945 & 1763 \\ \cline{1-1}  & & PAN-SLAM & 118 & 105 & 118 & 105 \\ \cline{1-1}  & & Ours & 161 & 146 & 165 & 149 \\ \cline{1-1}  & & Tao’s & 1947 & 1861 & 1965 & 1883 \\ \cline{1-1}  & & PAN-SLAM & 125 & 113 & 125 & 113 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: The comparison of the results for different methods in terms of the localization time. multaneously, under varying lighting conditions for the same source data, the method controlled the differences in various indicators within a narrow range, showcasing its strong resistance to light interference. 3. The proposed localization method, based on a lightweight enhanced berth map, utilized the distance between the holistic features to represent the similarity between the nodes, effectively reducing the localization time and achieving a localization frequency of approximately 10 Hz, thus meeting the real-time requirements. This demonstrated the low spatial and temporal complexity and low operational cost of the localization system. In our future research plans, we will continue to focus on around-view images of underground parking lot scenes and develop semantic feature extraction and matching methods to replace the role of traditional features in the localization system. This will improve the real-time performance, accuracy, and robustness of the system. Conceptualization, F.L. and Z.H. ; methodology, F.L. ; software, F.L. ; validation, F.L. and Y.Y. ; formal analysis, F.L. ; investigation, F.L. and Y.Y. ; writing--original draft preparation, F.L. and J.C.; writing--review and editing, F.L. and X.L. ; visualization, J.C.; supervision, F.L. and Z.H. ; project administration, Z.H. and X.L. ; funding acquisition, X.L. All authors have read and agreed to the published version of the manuscript. This research was funded by the National Natural Science Foundation of China, grant number U20A20198. Not applicable.