# Selecting Non-Line of Sight Critical Scenarios for Connected Autonomous Vehicle Testing
## 5 Discussion
Looking into the results of Table 3 under column 1 more minutely, in scenario number 4 the ego vehicle was only 1.39 m away from the collision point when it came to a stop on braking initiation. Similarly, several other scenarios have less than 3 m distance from the collision point. This distance is the distance where the ego vehicle comes to a complete halt upon initiating braking from the point the sensors detect the oncoming CAV. This is in the most optimistic road and weather condition, or in other words the best-case scenario, and hence if any of these parameters were to change slightly, Category 3 scenarios would move to Category 2 and Category 2 scenarios would likewise be in Category 1. These results show the GA was successfully able to search the scenario space for critical scenarios. Figure 9 illustrates the results from Table 3 and the corresponding scenario categories of the simulation without communication. Figure 9 shows the scenario categories; the red dots indicate scenarios in Category 2 and the orange dots indicate scenarios in Category 3. From Figure 9 it can be observed that a large number of scenarios have a stopping distance from collision point of less than 5 m (Category 2) with many coming under 3 m. From the results it can be seen that the scenarios outputted from the GA fit within the definition of critical scenarios as discussed in Section 3.1. A scenario is considered critical if TTC < TST (Category 1) or within a threshold safety value (Category 2). The safety value is when the stopping distance is within a small distance from the collision point, which has been assumed to be 5 m. If there was a change in weather condition which would lead to the need for a much larger braking distance, this could result in a collision and the Category 2 scenarios would very likely be Category 1 scenarios. Furthermore, if system performance or reaction time was to change as suggested by [PERSON] et al. [84], an autonomous vehicle could have a reaction time of up to 0.5 s and, with these parameters, all the scenarios from Category 2 would be within Category 1 and all scenarios within Category 3 would be either within Category 1 or within \begin{table}
\begin{tabular}{c c c} \hline \hline \multirow{2}{*}{**Scenario Number**} & **Distance to Collision** & **Distance to Collision with** \\  & **without Communication (m)** & **Communication (m)** \\ \hline  
\hline \hline \end{tabular}
\end{table} 
Table 3: Results for Experiments 2 and 3.  
the upper limits of Category 2. Figure 10 compares these results with communication to determine the braking distance if communication was received beforehand. Figure 10 shows the comparison of the results of distance to collision point with and without communication. From Figure 10 it can be observed that most of the critical scenarios acquired from the GA have a stopping distance of less than 5 m, with a few a little over 5 m and an outlier at just under 10 m. These scenarios are critical scenarios, as discussed earlier, where any change in parameters leads to a collision. These scenarios can be used as test scenarios to test algorithms, for example, obstacle detection, trajectory planning or collision avoidance. Comparing this to results acquired with a communication network, it can be observed that the stopping distance from the collision point for most of the scenarios was over 15 m. This confirms the need for communication beforehand in order to avoid a collision. From this it is clearly seen that the scenarios are also capable of being used as test scenarios for any new development within the V2X communication area and not just for autonomous vehicle navigation algorithms.