## 3 Methodology
### Derivation of Promising Evaluation Indicators and Development of an Integrated Evaluation Index  
Eleven vehicle interaction indicators were selected for the analysis of this study. The indicators included the TTC-based conflict count, stopping distance index (SDI)-based crash count, average deceleration rate to avoid a crash (DRAC), DRAC-based conflict count, crash potential index (CPI), average spacing, standard deviation of spacing, time-varying volatility (VF) of spacing, average headway, standard deviation of headway, and time-varying volatility of headway. The TTC-based conflict count is defined as the number of conflicts with a TTC of less than 1.5 s [22]. The SDI is a safety evaluation indicator that judges safe/unsafe conditions based on the difference between the minimum stopping distance of the leading vehicle and that of the trailing vehicle. When the stopping distance of the trailing vehicle is greater than the stopping distance of the leading vehicle, the scenario is unsafe, as shown in Equation (2). A conflict is defined as an SDI of less than 0 [23]. DRAC is the collision avoidance deceleration when the trailing vehicle recognizes a hazard and starts to slow down. As the DRAC increases, the safety decreases; the formula for this is shown in Equation (3). Additionally, if the DRAC exceeds 3.35 m/s\({}^{2}\), it is defined as a conflict [24]. The CPI is the probability that the DRAC exceeds the maximum available deceleration rate (MADR) in a given time interval [25]. As the CPI increases, safety decreases; this computation is shown in Equation (4). The time-varying volatility is the variability of the indicator value over time [26]. As the time-varying volatility increases, the safety decreases, as shown in Equation (5). \[SDI_{t}=d_{LV,t}-d_{FV,t} \tag{2}\]  
where \(d_{FV,t}\) is the stopping distance of the trailing vehicle at time \(t\) (m) and \(d_{LV,t}\) is the stopping distance of the leading vehicle at time \(t\) (m). \[DRAC_{t}=\frac{(V_{FV,t}-V_{LV,t})^{2}}{2s_{t}} \tag{3}\]  
where \(V_{FV,t}\) is the velocity of the trailing vehicle at time \(t\) (m/s), \(V_{LV,t}\) is the velocity of the leading vehicle at time \(t\) (m/s), and \(s_{t}\) is the spacing at time \(t\) (m). \[CPI=\frac{\sum\Pr(MADR\leq DRAC_{t})}{T} \tag{4}\]  
where \(MADR\) is the maximum available deceleration rate (m/s\({}^{2}\)), \(DRAC_{t}\) is the maximum deceleration at time \(t\) (m/s\({}^{2}\)), and \(T\) is the analysis unit time. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Division** & **Parameter** & **MD Mode** & **AD Mode** \\ \hline \multirow{4}{*}{Lane change 1} & Waiting time before diffusion [s] & 60.0 & 60.0 \\  & Minimum headway (front/rear) [m] & 0.5 & 0.2 \\  & Safety distance reduction factor [m] & 0.6 & 0.3 \\  & Maximum deceleration for cooperative braking [m/s\({}^{2}\)] & \(-\)3.0 & \(-\)3.0 \\ \hline \hline \end{tabular} 1  
\end{table} 
Table 1: _Cont._\[VF=\sqrt{\frac{1}{n-1}\sum\limits_{t=1}^{T}(r_{t}-\overline{r})^{2}} \tag{5}\]  
where \(r_{t}\) is the relative change in the indicator value at time \(t\) (%), \(n\) is the number of data points, and \(t\) is the sampling interval. Both autonomous vehicle and manually driven vehicle driving data were utilized to derive the aforementioned evaluation indicators for the evaluation of mixed traffic conditions. For the simulation-based hazardous road sections, 186 sections were selected, which were the same as the sections defined as actual hazardous road sections. The evaluation indicators were calculated for each road section. The definitions and equations for obtaining the candidate evaluation indicators are presented in Table 2.  
The DT analysis technique was used to select promising evaluation indicators that can be used to effectively identify hazardous sections on actual roads. The 11 simulation-based vehicle interaction safety evaluation indicators were used as input variables in the DT analysis.