# Priority of Emergency Vehicle Dynamic Right-Of-Way Control Method in Networked Environment
## 3 Experimental Verification
### Simulation Experiments and Data Analysis
#### 3.2.2 Analysis of Experimental Results
In addition, the mutual influence is reflected by comparing the trend of EV and CV running times under the same control method. It is worth mentioning that \(L_{1}\) is not discussed in this study, because it is closely related to the vehicle's driving state ahead, and the variation law is complex. To simplify the test process and obtain a relatively objective trend of the influence of the buffer interval length on the running time, \(L_{1}\) was fixed at 15 m during the simulation, and the flow rate was fixed at 1300 pcu/h. In addition, \(L_{2}\) varied from 30 m to 150 m to derive the variation rule [20]. Figure 11a,b reveal that the ER and PSR had a flat trend. Under PDR conditions, the EV's running time curve presented a downward trend, and the CV's running time showed an upward trend. The two aligned with the mutual influence mechanism on operating efficiency. Since EVs do not have physical functional areas under the ER and PSR conditions, which are unaffected by the  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{ \begin{tabular}{c} **CV’s** \\ **Input** \\ **Flow** \\ **(pcu/h)** \\ **Time (s)** \\ \end{tabular}  } & \multicolumn{2}{c}{**ER**} & \multicolumn{2}{c}{**PSR**} & \multicolumn{2}{c}{**PDR**} \\ \cline{2-7}  & **EV** & **CV** & **EV** & **CV** & **EV** & **CV** \\  & **Average** & **Average** & **Average** & **Average** & **Average** & **Average** \\  & **Running** & **Running** & **Running** & **Running** & **Running** & **Running** \\  & **Time (s)** & **Time (s)** & **Time (s)** & **Time (s)** & **Time (s)** & **Time (s)** & **Time (s)** \\ \hline
600 & 70.9 & 84.9 & 57.5 & 85.6 & 59.5 & 85.215 \\
700 & 72.5 & 85 & 57.5 & 85.8 & 59.8 & 85.36 \\
800 & 74.3 & 85.1 & 57.5 & 86.1 & 60.3 & 85.5 inter-buffer length, the corresponding curves did not change with the inter-buffer length. In Figure 11a, when the length between the buffer zones exceeded 120 m, the PDR curve gradually tended to be flat and approached the PSR curve. When CVs cannot be imported, the operation effect is similar to PSR. The change in the PDR curve in Figure 11b was exactly opposite to that in Figure 11a, which reveals the result of CVs and EVs preempting limited road space resources. Therefore, when the CV's flow rate is high, the buffer length should be reduced, and the efficiency of the CV's operation can be enhanced. Since the ER and PDR methods compress the running space of CVs to different degrees, the saturation will increase. Figure 12a shows the relationship between the running time and the saturation of different organization methods, where the length of the non-invasive interval was \(L_{1}=15\) m, and the length of the buffer zone was \(L_{2}=90\) m. The flow input changed from 600 pcu/h to 2000 pcu/h. The saturation degree is the flow-to-traffic capacity ratio, with capacity set at 1200 pcu/h per lane. According to the traffic flow theory, the higher the saturation and speed, the greater the corresponding traffic capacity. Visibly, when the saturation is less than 0.8, the traffic capacity of the PSR method is the largest, followed by the PDR method, and the ER method is the smallest, but the traffic capacity  
Figure 11: Curve of the influence of the length of EVs buffer area on the running time: (**a**) EVs and (**b**) CVs. corresponding to the PSR method is close to the PDR method. Although the PSR method has excellent advantages concerning traffic capacity, it requires many space resources. The plotted results in Figure 10b reveal that the space resources of the EVs compressed the CVs, declined the CVs' operation efficiencies, and the PSR method had the most substantial impact on the other vehicles. Therefore, from the system point of view, the PSR method is not a method with better comprehensive performance.