Roundabouts promise potential safety and efficiency benefits in the homogenous environment of conventional vehicles. However, their performance can deteriorate if high and/or imbalanced traffic exists. The advent of connected and automated vehicles (CAVs) has provided great opportunities to make transportation infrastructures more efficient. The purpose of this study is to develop a model to optimally control CAVs at roundabouts under a fully CAV environment. A two-stage optimization model is proposed to optimize vehicle trajectories. At the first stage, a mixed-integer linear programming model is formulated that optimizes vehicle arrival time at the roundabout. Then the optimal arrival time is fed to the second stage model to optimize vehicle trajectories, which is a non-linear programming model. CAVs are guaranteed to pass the roundabout safely without stops. Simulation tests are carried out with different demand levels and turning ratios. To evaluate the performance of the proposed model, delay and throughput are compared with a conventional strategy in which the roundabout is controlled by the yielding rules. Sensitivity analysis is conducted to investigate the impact of control zone length and roundabout diameters. The results show the advantages of the proposed model in terms of delay and throughput in both high and imbalanced traffic.This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

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In urban road networks, intersections are the main bottlenecks. Selecting an appropriate intersection control type can significantly improve the performance of an isolated intersection. Therefore, this paper offers recommendations for selecting the most efficient control type among two-way stop control, signalized intersection (SIG), roundabout (RB), and signalized roundabout (SIGRB) based on capacity and delay. The procedure to calculate delay and capacity is taken from the Highway Capacity Manual 6th edition (2016), or developed separately if needed. Two flow patterns are assumed: fixed and time-varying demand. For fixed demand, the results show that SIGRB outperforms other control types both in capacity and delay at higher demand levels. It was also observed that increase in left-turn ratio increases the delay and decreases the capacity of all control types while its impact on SIGRB was the least. Considering time-varying demand, traffic volume fluctuates over the 5-h period of the analysis. It was found that using both RB and SIGRB together creates significantly less delay compared with the other options. Additionally, using RB provides less variability in delay when there is fluctuation in demand. The major finding of this research is that RB and SIGRB have potential benefits for delay in conditions of (i) high traffic volume, (ii) high left-turn ratio, and (iii) demand fluctuation. Furthermore, it is suggested that SIG should be used if the left-turn ratio is relatively low. The results of this study could help decision-makers to choose the best control type for an isolated intersection under various traffic conditions.