# Queue Spillover Management in a Connected Vehicle Environment
## 4 Simulation Analysis  
To verify the feasibility of the design method, this paper selected an adjacent intersection of Huangdao District, Qingdao City, Shandong province as the research object. The intersection is two-way four lanes where left turn and straight are separated, and it is easy to cause queuing overflow phenomenon in the peak time. The real scene and simulation scene, are shown in Figure 5. The simulation settings of VISSIM, are shown in Table 3. The distribution of the phases at the intersection, is shown in Figure 6.  
Figure 5: Real scene and simulation scene. The survey showed that the length of the west approach section is 350 m and the traffic flow in the west straight section was large, which easily causes queuing overflow. The proposed method was used to simulate with VISSIM. The maximum queuing length of each section was taken as the target amount. The simulation results are shown in Figure 7. As it can be seen from Figure 7, the west approach spills over in the 500 s and will continue to overflow under uncontrolled conditions, eventually resulting in spillovers. The traffic volume of other roads was in a normal trend, indicating the same at the time of the signal allocation. The volume of traffic on the south and north sections can be self-regulated to ensure normal traffic operation. In view of the problem of spillover of the west approach at this intersection, it was necessary to determine the position of its overflow limit point. The simulation compared the positions at 60%, 70% and 80% respectively. After setting the detection point on the overflow section, the maximum queue length was still taken as the target detection amount. The simulation results are shown in Figure 8.  
The simulation results of Figure 8 can be analyzed: \begin{table}
\begin{tabular}{c c} \hline
**Direction** & **Vehicle Flowrate (V/h)** \\ \hline West & 600 \\ East & 400 \\ North & 400 \\ South & 400 \\ \hline \end{tabular}
\end{table} 
Table 3: Simulation Setting Table. Figure 6: Intersection phase. Figure 7: Simulation results. When the detector position was at 60% of the road, the blue line in the graph represents the change in the maximum queue length of the road. The initial moment of vehicle queuing was detected to be 320 s, and the arrival time of overflow was detected to be 500 s. The interval time was 180 s, that is, when the detecting point detects the vehicle, overflow will arrive after 1.5 cycles; so, the signal control needs to be implemented in 1.5 cycles. 2. When the detector position was at 70% of the road, the red line in the graph represents the change in the maximum queue length of the road. The initial moment of vehicle queuing was detected to be 440 s, and the arrival time of overflow was detected to be 500 s. The interval time was 60 s, that is, when the detecting point detects the vehicle, overflow will arrive after 0.5 cycles; so the signal control needs to be implemented in 0.5 cycles. 3. Similarly, when the detection point was located at 80% of the road, the signal control needs to be completed within 0.25 cycles. In order to achieve effective control of the intersection, one cycle interval must be ensured. Therefore, based on the simulation results analysis, the detector should be placed at 60% of the length of the intersection. Accordingly, when the detector detects a queued vehicle, the control phase time is adjusted, and the next cycle begins. The intersection road is two-way four lanes, and the standard width of a single lane is 3.75 m, so the available crosswalk width is 15 m. The shortest time for the pedestrian to pass the crosswalk is as follows:  
\[t=\frac{l_{w}}{1.292}=12s \tag{18}\]  
That is, the maximum straight-through phase of the southbound approach time is 40\(-\)12 = 28 s. The distribution of the maximum available phase of the southbound approach, is divided into two cases.