## 5 Simulation and Experimental Results
### Experimental Result 1: Anti-Collision via V2V  
In this scenario, we perform experiments of the proposed anti-collision system with real-world data. As shown in Figure 10a-c, V1 cannot recognize the pedestrian who suddenly appears from an uncertainty area caused by parking cars in a narrow street. However, V2, which comes from the opposite site, is able to detect the pedestrian. The actual images of vehicles' front view are presented in Figure 10a,b including detection results. A top-view illustration is depicted in Figure 10c. V1 with 36 km/h and V2 with 47 km/h speed drive and a distance between them is about 20 m. A pedestrian walks westwards as 5.5 km/h in 15 m away from V1. In Figure 11, we plot the measured and estimated values of position, velocity, and calculated acceleration of the pedestrian. In Figure 11b, it is shown that the cosine effect compensation can have a high impact on measurements. As pedestrian and V2 come closer, the angle between them increases, which causes the measured velocities to be smaller than actual values. It can be seen that the estimated values are quite close to ground truth values. The precise estimations in Figure 11a,b result in correct acceleration values (direction) as in Figure 11c. \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Video(Image) size [pixels] & 1280 \(\times\) 720, 1920 \(\times\) 1080 \\ \hline Frame per second & 30 FPS \\ \hline Object detection (ML) & YOLOv3 \\ \hline Number of classifications & 16 \\ \hline Basic message size & 500 bytes/msg \\ \hline Message transmission period & 10 Hz \\ \hline Frequency & 5.9 GHz \\ \hline Bandwidth & 10 MHz \\ \hline Modulation and coding scheme & 16 QAM \\ \hline Data rate & 18 Mbps \\ \hline Safety area (Car, Human) & 4.8 m, 0.5 m \\ \hline Deceleration rate & 5 m/s\({}^{2}\) \\ \hline Distance accuracy & 0.1 m \\ \hline Velocity accuracy & 0.1 m/s \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Experimental parameters. Figure 10: Collision scenario: (**a**) Front image of V1 which cannot detect a pedestrian. (**b**) Front image of V2 which can detect a pedestrian. (**c**) Top-view illustration of this scenario. Next, we explore how confidences of V1 change over time. We assume that the current frame of V1 and V2 starts at \(t=0\). In this frame, V2 detects seven objects including the pedestrian, which takes 22.46 ms. The detection outcome is encapsulated as the proposed format with 1053 bytes. The delay is only 4.68 ms. As soon as V1 receives data from V2 at \(t=27.1\) ms, the data fusion is performed. As the pedestrian is located in the uncertainty area of V1, we set confidences to \(\{0.0,0.0,1.0\}\). V1 takes 0.88 ms of processing time in the decision-making, prediction, and the decision to issue warning. In addition, the data fusion system returns the highest confidence on the detection of a person. The whole decision process takes only about 27.9 ms. During the process, the confidence on existence changes from 0.0 to 0.66. We impose 0.5 threshold to determine existence of object. The detailed changes in confidences are illustrated in Figure 12; it shows that V1 can start to decelerate after moving by the distance of only 0.27 m even if V1 cannot directly recognize the pedestrian. The detailed results are addressed in Table 3.  
Figure 11: The received measurement and estimated trajectory about pedestrian at V1: (**a**) Position comparison. (**b**) Measured and estimated velocities about x and y axes with and without cosine effect compensation. (**c**) Comparisons of the calculated acceleration (direction). Figure 12: Changes of confidences about \(\{\text{E},\text{N},\text{U}\}\) for V1. Finally, we investigate a collision scenario through the environment modeling as shown in Figure 13. Each object has own safety area, e.g., car has 4.8 m and human is set to 0.5 m. Prediction line indicates future trace until 7 s later, and star dots imply that the accident is expected to happen when moving objects reach those locations.