No abstract

Uncoordinated traffic flows at the traditional roundabouts, especially with a small circumference and fewer lanes, are often heavily affected by congestion, which escalates fuel consumption, CO2 emissions, idling, and travel delay. An intriguing way to mitigate such uncoordinated flows at junctions would be facilitated through optimal traffic signalization. For this purpose, this paper presents a novel holistic Three-Leg Signalized Roundabout (TLSR) model based on two signalized stop lines (2SL). The first stop line is placed at each entry curve of a roundabout with effectual lane markings as usual. Hereafter, the second stop line is set exclusively in the circulatory roadway to improve left-turning mobility with an additional “short-lane model” to deal with heavy traffic, following specific patterns for smooth vehicle merging. The capacity and optimal signal cycle relationships are derived to evaluate the performance of the proposed TLSR-2SL, considering the internal space constraints of the roundabout. Under the various scenarios, the parameters’ sensitivity tests demonstrate that signal cycle and central radius play a significant role in enhancing the roundabout’s operational performance. From the executed simulation, the proposed framework improves the traffic flow by 15% and controls the relative error within 10% compared to benchmark methods.

This paper presents a novel holistic T-shape roundabout coordination system (TCS) that addresses the connected and automated vehicles (CAVs) flow in a typically isolated T-shape roundabout. The TCS optimizes the states of each approaching vehicle in a receding horizon control framework that aims to minimize the total crossing time, considering the vehicles' dynamic states. The control method ensures the comfortable crossing of each vehicle by retaining the basic features of a traditional traffic control management system. The optimal states are broadcasted ahead by TCS, which enables the CAVs to form a cluster and tune their speed in order to cross the roundabout with minimum stop-delay. We evaluate the effectiveness of the proposed TCS method under the various traffic flow demand. From the executed simulation, it is observed that the optimization process usually improves the average velocity, and reduces both the traffic density and vehicles' idling situation. As a consequence, the fuel consumption of each vehicle around the roundabout is also decreased. These outputs are compared with the traditional method, showing that the overall flow performance significantly improves in the case of the proposed scheme, and vehicles have rapid optimization for a smooth crossing.INDEX TERMS bi-level coordination, CAVs clustering, connected and automated vehicles, optimization, receding horizon control, T-roundabout,

In order to improve the Quality of service (QoS) and the Quantity of user Experience, overlay network visualized the network application and underlay structure. An algorithm named MOO-GSON is proposed uses Multi-Objective Optimization (MOO) to construct the General Service overlay network (GSON) topology. With the MOO model, this algorithm has taken into account the reusing of nodes and links and matched the physical network. Visual topology decreases the cost of signal links and the overall network. A series of experimental simulation is designed to analyze the Algorithm performance. The results show that the algorithm has a better tradeoff in running time and performance than similar algorithms.