## 5 Conclusions  
Understanding the characteristics of mixed car-following situations is of high importance for preparing for emerging automated driving systems because it is unlikely that the AV market will grow rapidly and soon. A variety of simulation experiments have been conducted to evaluate the impact of AVs on traffic stream performance and to identify the characteristics of AV maneuvering. However, we are not aware of any study that addresses the driving safety of the mixed car-following pair consisting of an AV and MV using different road-alignment conditions. The purpose of this study is to propose a methodology to identify what kind of geometric conditions would have a negative impact on the driving safety of mixed car-following situations on freeways. A notable feature of this study is to adopt an MADS method to simulate the maneuvering of AVs and to evaluate the responsive behavior of MVs following AVs. Three safety indicators, including the acceleration noise, the standard deviation of the lane position, and the headway, were used to characterize the maneuvering behavior of the mixed car-following pairs in terms of driving safety. Then, the rate of change in the safety indicator compared to the baseline case, which is a flat tangent road section resulting in stable maneuvering, was applied to identify road-alignment conditions where mixed car-following pairs would experience relatively more hazardous situations. The evaluation results showed that a set of road sections with combined alignments led to higher risks to driving safety. The outcome of this study can be used to identify the road-alignment conditions in which mixed car-following pairs would experience hazardous situations. In addition, the outcome is expected to be used as a fundamental for the development of novel V2X-based traffic information content that enables ODD expansion of AVs and supports the more effective decision-making of MV drivers. Although valuable insights were obtainable using systematic simulation experiments, several further studies should be conducted to draw more generalized results and create practice-ready outcomes. First, more efforts need to be made to develop maneuvering \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Evaluation Target** & **Safety Indicator** & **Evaluation Index** & **Mixed Pair** \\ \hline Longitudinal safety & Acceleration noise & \(\Delta\)AN & 1000 m left curve 3\% downhill \\  & & & 1000 m right curve 3\% uphill \\ \hline Lateral safety & Standard deviation of lane position & \(\Delta\)Std.LP & 500 m right curve 1\% downhill \\ \hline Inter-vehicle safety & Average of headway & \(\Delta\)Avg.HW & 1000 m right curve 3\% downhill \\  & & & 1000 m left curve 1\% downhill \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Identified hazardous road sections for mixed vehicle pairs. control logic for AVs. This study adopted publicly released general control schemes for following preceding vehicles. However, there are valuable opportunities to improve the control logic used in driving simulation experiments. To do this, real-world AV-maneuvering data will make our simulation experiment more realistic. Additionally, more extensive simulation experiments with a larger participant group need to be conducted. Connection and synchronization of more than two driving simulation environments would allow for more valuable results, which are fundamental to developing effective traffic management strategies to address mixed traffic conditions. Rather than simply comparing the evaluation index with the baseline case, a more sophisticated method could be devised. Lastly, in addition to the three safety indicators used in this study, continuous efforts are needed to find more salient indicators. Although there are various safety indicators, there is a need to consider the method for prioritizing safety indicators that can well represent the safety concerns of mixed traffic flow.