# Service-Oriented Cooperation Policies for Intelligent Ground Vehicles Approaching Intersections
## 5 Verification Experiments and Analysis
### Experiments and Analysis  
Considering the key constraints to guarantee cooperation safety, QoS of vehicles (H) (or vehicles (M) when there is no vehicle (H)), and the traffic throughput of one intersection, a series of experiments have been designed and carried out, and further, corresponding scheduling effects are analyzed as below. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Parameter** & **Value (Scope)** & **Parameter** & **Value (Scope)** & **Parameter** & **Value (Scope)** \\ \hline \(|\xi_{\gamma l}^{\mathrm{\bar{\bar{\bar{\bar{\bar{\bar{\bar{\bar{\bar{\bar{\bar{\bar{ \bar{     \bar{\bar{       }}}}}}}}}}}}|\) & 4 & \(|\xi_{\ell}^{\mathrm{\bar{\bar{\bar{\bar{  
(1) Promotion of Passing-Through Orders  
These designed policies are firstly verified under a same traffic situation, totally covering 200 vehicles in each experiment. Figures 9 and 10 shows the experimental results, where exist four vehicles (H): 20031 and 20046 on lane \(\ell_{2}\), 10201 and 10211 on lane \(\ell_{1}\). It can be observed that authorization orders of these four vehicles (H) are promoted by these eight policies to be \(<-2,6,-9,-8>,<1,3,0,0>\), \(<-1,2,3,6>\), \(<0,2,0,2>\), \(<6,12,12,12>\), \(<10,11,14,14>\), \(<9,8,12,13>\), and \(<9,8,11,10>\), respectively. It is clear that all four QoS-oriented policies authorize all vehicles (H) to pass through preferentially, and those platoon-based policies also performed better. This experiment is carried out with a bigger \(P_{H}\) value 0.2, which means more vehicles (H) will exist in traffic flows. However as is well known, such scenes are very scarcely in reality. The relevant experimental results are shown in Figures 11 and 12, from which we can find these four QoS-oriented policies still perform better to guarantee the QoS of vehicles (H). Significantly, HQEP-SV has exhibited the outstanding capability to authorize vehicles (H) preferentially because the single-vehicle authorization and the GPI mechanism make it more flexible. It needs to be noted that the number of promoted places is not the unique factor to measure these policies. As aforementioned, there are still other important indicators need to be concerned, typically the average delay time of all vehicles (H) and the throughput of any intersection. (2) Delay Time of Vehicles{H,M,L}  
Delay time is the real indicator that reflects how long one vehicle has been blocked. Although we have devoted to finding novel policies to authorize vehicles (H) preferentially, a few vehicles (H) are still delayed when there simultaneously exist vehicles (H) on different lanes. This is a normal phenomenon in real transportation procedures. Thereout, we have drew up a statistics-based evaluation indicator, the average delay time, to appraise the effect of these policies. Concretely, for each experimental variable, a series of experiments have been conducted, and each time the traffic flows are composed of 200 vehicles. * Reservation Distance: \(d_{r}\)  
The influence of reservation distance \(d_{r}\), corresponding to the position \(P_{r}\), is the first experimental indicator. In our model, the value of \(d_{r}\) will mainly affect the length of \(Q_{\ell}\). The bigger the value of \(d_{r}\) is appointed, the more vehicles are allowed to be buffered in \(Q_{\ell}\). It implicitly means that one vehicle (H) is able to be perceived earlier by I-Agent, thereby, can be authorized earlier. Figures 13 and 14 shows experimental results when changing \(d_{r}\) from 10 m to 70 m. It can be observed that along with the increase of \(d_{r}\) the average delay time of all vehicles rises, especially for FAFP-SV policy. That is mainly because that there are more vehicles buffered in these \(Q_{\ell}\), and furthermore, leading to more vehicles delayed. However, it can be also observed that, all QoS-oriented policies can obviously decrease the average delay time of vehicles with higher priorities,  
meanwhile, be influenced very little by \(d_{r}\).