# Cooperative Roundabout Control Strategy for Connected and Autonomous Vehicles
## 4 Concluding Comments  
This study aims to fill a gap in the current literature by illustrating the advantages of roundabouts in a CAV environment. The main contributions of this study are to: (i) develop a hierarchical roundabout control framework to decouple system performance measures and vehicle safety constraints, to relieve the computational burden by significantly decreasing the dimension of the optimal control problem; (ii) investigate the potential advantages of roundabout designs compared to traditional intersection designs to provide insights for future infrastructure design in urban networks in CAV environments; and (iii) extend existing linear CACC models to a circular CACC virtual platoon control model to address the safety and stability considerations for vehicles operating within a roundabout.  
This study suggests another potential venue for intersection infrastructure design for CAVs beyond signal-free intersections. This exploratory investigation has some limitations: (i) the proposed model assumes constant incoming flows; therefore real-world dynamics may not be fully captured; (ii) the roadways of the approaches and the roundabout are both assumed to be one-lane roads; so, multi-lane problems such as lane change are not addressed; and (iii) how to adapt human drivers in the proposed control strategy during the transition period is another unexplored issue. Therefore, the insights from this study can provide directions for further research, including: (i) leveraging closed-loop control strategies such as model predictive control to enhance the roundabout flow control performance (i.e., the flow control model in the proposed hierarchical framework can be replaced with more advanced ones to deal with changing incoming flows and measurement delays); (ii) extending the proposed control strategy to multilane roundabouts; and (iii) investigating roundabout control problem in a mixed traffic environment (e.g., enabling larger operational uncertainty for human driven vehicles in models and employing augmented reality or mixed reality technologies to project suggested vehicle movements in roundabouts to assist human drivers).  
Conceptualization, C.W. and S.P.; methodology, C.W.; software, Y.W.; validation, C.W. and Y.W.; formal analysis, C.W.; investigation, C.W.; resources, S.P.; data curation, Y.W.; writing--original draft preparation, C.W.; writing--review and editing, S.P. and Y.W.; visualization, C.W.; supervision, S.P.; project administration, S.P.; funding acquisition, S.P. All authors have read and agreed to the published version of the manuscript.  
This research was supported by the Center for Connected and Automated Transportation (CCAT) Region V University Transportation Center funded by the U.S. Department of Transportation under Award #69A3551747105.  
Not applicable.  
The authors declare no conflict of interest.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Intersection** & **Proposed** & **Proposed** & **Signal-Free** & \\
**Control** & **Roundabout** & **Roundabout** & **Intersection** & **Fully Actuated** \\
**Strategy** & **Flow Control** & **Control** & **Control** & **Signal Control** \\ \hline Throughput (trips/min) & 105 & 82.2 & 120.5 & 76.5 \\ \hline Lane capacity (veh/lane/min) & 60 & 60 & 80 & 80 \\ \hline Number of lanes & 4 & 4 & 8 & 8 \\ \hline Intersection & 0.438 & 0.343 & 0.188 & 0.119 \\ design efficiency & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 3: Performance comparison.