The continuous evolution of automotive and communication technologies can result in more efficient traffic management. At roundabouts, Autonomous and Connected Vehicles (CAVs) have the potential to enhance traffic operations, minimizing lost time and providing higher capacities by improving the gap acceptance process.

This research aims to take advantage of those evolving technologies in order to design a more efficient traffic management system for single-lane roundabouts. Such a system would provide optimal coordination of CAVs to negotiate the roundabout, maximizing throughput and minimizing average control delay.

The expert system developed and tested (Roundabout Manager) acts as a central controller and manages conflicts within the roundabout. It prioritizes incoming vehicles based on demand-dependent strategies and adjusts their trajectories accounting for the geometry of the roundabout. Seven strategies are proposed to coordinate CAV trajectories. The first strategy prioritizes incoming vehicles based on their Shortest-Remaining-Time-First (SRTF, i.e., the shortest time till the vehicle reaches the first conflict section it will encounter) to the conflict sections within the circular roadway, while the other strategies add to the SRTF rules to accommodate highly unbalanced traffic flows, with heavy right- or left-turning maneuvers.

To illustrate the operation of the algorithm and assess its effectiveness as a function of the demand distribution, a total of 15 oversaturated demand scenarios with 10 replications per scenario were simulated for each of the seven strategies examined. It was concluded that, under any of the strategies proposed, the system guarantees higher throughput with lower average control delay compared to conventional vehicles’ operation. The capacity of the roundabout under fully CAVs traffic flow is increased by 58 to 73% (from low to high conflicting flow, respectively). The strategy that prioritizes vehicles that have to travel through more conflict points and those that leave the system first outperforms the other strategies at all demand scenarios, becoming the optimal coordination of CAVs at roundabouts. This strategy reduces the average control delay between 80 and 97% compared to traffic with conventional vehicles, as assessed using the Highway Capacity Manual procedures.

汽车和通讯技术的不断发展可以提高交通管理的效率。在回旋处，无人驾驶和互联车辆（CAV）可以通过改善差距接受流程来增强交通运营，减少损失的时间并提供更高的容量。

这项研究旨在利用那些不断发展的技术，以便为单车道回旋处设计更有效的交通管理系统。这样的系统将提供CAV的最佳协调，以协商回旋处，最大化吞吐量并最小化平均控制延迟。

开发和测试的专家系统（Roundabout Manager）充当中央控制器，管理回旋处的冲突。它根据需求相关策略对进来的车辆进行优先排序，并根据回旋处的几何形状调整其轨迹。提出了七种策略来协调CAV轨迹。第一种策略根据传入的车辆的最短保留时间优先（SRTF，即，直到车辆到达它将遇到的第一个冲突段的最短时间），将优先级分配给圆形车道内的冲突段，而其他策略则添加SRTF规则，以适应高度不平衡的交通流，并采用向右或向左转弯的沉重动作。

为了说明该算法的操作并根据需求分布评估其有效性，针对所检查的七个策略中的每一个，总共模拟了15个过饱和的需求场景，每个场景有10个重复。结论是，与传统车辆的运行相比，在任何建议的策略下，该系统均可以保证更高的吞吐量和更低的平均控制延迟。在完全CAV的交通流量下，回旋处的通行能力增加了58％至73％（分别从低到高冲突流量）。在所有需求场景下，优先考虑必须经过更多冲突点的车辆和那些首先离开系统的车辆的策略都优于其他策略，从而成为在回旋处CAV的最佳协调。