## 4 Results
### The Validation of PCRI's Effectiveness Using the inD Dataset
Through the examination of acceleration magnitudes, the proactive collision avoidance actions of the vehicle can be assessed at various time points, allowing for the identification of the critical moment of increased conflict risk. A larger value of deceleration indicates more intense braking actions by the driver at that moment, suggesting more aggressive evasive maneuvers, which in turn implies a greater risk of conflicts. Table 2 illustrates the deceleration of the subject vehicle in this event. The bolded rows in the table represent the frame number and deceleration information at the moments of maximum deceleration. In Table 2, the absolute acceleration exceeds 1m/s\({}^{2}\) starting at frame #5959 and 2m/s\({}^{2}\) from frame #5978, reaching a peak at frame #5992. The alignment of PCRI's conflict risk identification with these acceleration trends demonstrates its superior performance over TTC in conflict identification. Therefore, in rear-end conflict, PCRI can more accurately identify the moment of highest conflict risk. \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & **Rear-End** & **Lane-Changing** & **Crossing** & **All** \\ \hline TTC & 2.7 & 0.3 & 1.6 & 4.6 \\ PCRI & 0 & 0.4 & 1.2 & 1.6 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: The average number of conflict missing rate (conflict times/ video). To validate the necessity of integrating three variables within PCRI, the variations in each variate during conflicts are plotted and compared against TTC individually. From Figure 12(a), the trends of TTC and TTR are essentially consistent, and the lowest trough of TTR occurs near frame #5992, indicating that TTR effectively represents different conflict risks. In Figure 12(b), the change in EDR does not completely align with that of TTC, indicating that EDR alone cannot summarize the risk in conflicts. It merely reflects the risk associated with the subject vehicle's trajectory moving through the risk region. As the relative motion of the vehicles shifts away from the risk region, the value of EDR decreases. And if the subject vehicle does not cross the risk region again, its value will approach 0. According to Figure 12(c), the overall trend of TRSD is similar to that of TTC, but the variation in TRSD between frames #5940 and #5960 differs from that of TTC. In Figure 12(d), the trend of CRF changes is essentially consistent with that of TTC because CRF is the pre-normalization version of PCRI. However, the key shortcoming is that CRF can exhibit extreme values, leading to significant spikes in the trend. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Frame**} & **Deceleration** & \multirow{2}{*}{**Frame**} & **Deceleration** & \multirow{2}{*}{**Frame**} & **Deceleration** & \multirow{2}{*}{**Frame**} & **Deceleration** \\  & **(m/s2)** & & **(m/s2)** & & **(m/s2)** & & **(m/s2)** \\ \hline
5931 & 0.86662 & 5951 & 0.74541 & 5971 & 1.68923 & 59  
Another event selected is taken from video No.21, featuring a crossing conflict between vehicle #527 and vehicle #528. In this scenario, the minimum value of PCRI is 0.162, which can identify the conflict, whereas the minimum value of TTC is 3.324 s, failing to identify the conflict. Figure 14 shows the changes in PCRI and TTC. In this event, PCRI and TTC exhibit differing trends. TTC reaches its lowest value from frames #30066 to #30085, with the most critical moment at frame #30075, and the lowest point of PCRI is between frames #29996 and #30015, with the peak risk at frame #30007. Table 3 presents the deceleration at key frames. The bolded row in the table represents the frame number and deceleration information at the moments of maximum deceleration. It shows that the subject vehicle maintains a high acceleration value between frames #29996 and #30008, and after frame #30066, the vehicle begins to accelerate rather than decelerate. Thus, the moments of highest risk in this scenario are near frames #29996 to #30008. Therefore, PCRI can effectively and accurately identify the crossing conflicts.