## 5 Simulation  
### Simulation Example  
(1) The target parking lot which was selected as the simulation prototype is shown in Figure 4. As shown in Figure 5, We have redesigned the parking spaces and roads in the target parking lot according to the Engineering Construction Industry Standard JGJ 100-98. Figure 3: Route planning process. Based on the undirected graph with weights, the adjacency matrix composed of the weights between the nodes is shown in Equation (4). \[\left[ \begin{array}{cccccccccccccccc}0&13.375&\infty&\infty&\infty&\infty& \infty&11.465&\infty&\infty&\infty&\infty&\infty&\infty&\infty\\ 13.375&0&1.65&\infty&\infty&\infty&\infty&\infty&\infty&\infty&\infty&\infty& \infty&\infty\\ \infty&1.65&0&13.19&\infty&\infty&\infty&\infty&\infty&\infty&\infty&\infty& \infty\\ \infty&\infty&13.19&0&5.875&\infty&\infty&\infty&\infty&\infty&\infty&11&\infty &\infty\\ \infty&\infty&\infty&5.875&0&5&\infty&\infty&\infty&\infty&\infty&\infty&\infty \\ \infty&\infty&\infty&\infty&5&0&5.875&\infty&\infty&\infty&\infty&\infty&\infty \\ 11.465&\infty&\infty&\infty&\infty&5.875&0&11&\infty&\infty&\infty&\infty&\infty &\infty\\ \infty&\infty&\infty&\infty&\infty&\infty&\infty&11&0&3.375&\infty&\infty& \infty&14.058\\ \infty&\infty&\infty&\infty&\infty&\infty&\infty&3.375&0&5&\infty&\infty&\infty \\ \infty&\infty&\infty&\infty&\infty&\infty&\infty&\infty&5&0&8.375&\infty&\infty \\ \infty&\infty&\infty&11&\infty&\infty&\infty&\infty&\infty&8.375&0&12.656&\infty\\ \infty&\infty&\infty&\infty&\infty&\infty&\infty&\infty&\infty&\infty&12.686&0 &10.054\\ \infty&\infty&\infty&\infty&\infty&\infty&\infty&14.058&\infty&\infty&\infty&10. 054&0\end{array} \right] \tag{4}\]  
(4) Using this matrix as the data source of the Dijkstra algorithm, and calculating the shortest distance and the shortest route from the entrance to each parking space. The result is shown in Table 1.  
(5) Setting the dynamic influence factors in the parking lot (the remaining parking time of the vehicle during parking, the moving vehicles' current position, and their driving routes). The test vehicle speed is set to 5 km/h, which not only ensures the safety of driving in the parking lot, but also satisfies the vehicle's recognition ability for surrounding parking spaces [38]. Figure 8 means that there are two cars going on automatic parking, the remaining time is 45 s and 50 s, and there is a car in the parking lot, driving to follow the red line to the parking space pointed by the red arrow to start automatic parking. (6) Selecting the No. 6 node as the target parking space, and the driving route of the No. 6 parking space is 1\(\rightarrow\)7\(\rightarrow\)6. (7) There is a dynamic influence factor in the driving route of No. 6 parking space. It is a parking space being used for automatic parking, and the required time is 50 s. It means that the lane will \begin{table}
\begin{tabular}{c c c} \hline \hline
**Parking Space Number** & **Route** & **Distance/m** \\ \hline Parking Space 2 & 1\(\rightarrow\)2 & 13.375 \\ Parking Space 3 & 1\(\rightarrow\)2\(\rightarrow\)3 & 15.025 \\ Parking Space 5 & 1\(\rightarrow\)7\(\rightarrow\)6\(\rightarrow\)5 & 22.340 \\ Parking Space 6 & 1\(\rightarrow\)7\(\rightarrow\)6 & 17.340 \\ Parking Space 9 & 1\(\rightarrow\)7\(\rightarrow\)8\(\rightarrow\)9 & 25.840 \\ Parking Space 10 & 1\(\rightarrow\)7\(\rightarrow\)8\(\rightarrow\)9\(\rightarrow\)10 & 30.840 \\ Parking Space 12 & 1\(\rightarrow\)7\(\rightarrow\)8\(\rightarrow\)13\(\rightarrow\)12 & 47.027 \\ Parking Space 13 & 1\(\rightarrow\)7\(\rightarrow\)8\(\rightarrow\)13 & 36.523 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Shortest route and distance from the starting point to each parking space. Figure 8: Real-time condition of the parking lot. be occupied for 50 s, and the weight of the corresponding road in the matrix needs to be corrected. As shown in Equation (5). \[\left[