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The signal control system for multi-intersection traffic management is an extensive complex nonlinear and non-equilibrium system and usually leads to a weak control strategy. Existing studies of traffic dynamics mainly focus on the applications to the single network, whereas how the structure of multiple intersections affects the dynamical behaviors is unclear. Connected vehicles in recent studies have shown the potential to eliminate traffic communication barriers and balance the traffic load. For this consideration, we propose a new multi-intersection model based on Vehicle-to-Everything (V2X) network to capture the features of traffic flow, which employs vehicular communication to obtain real-time traffic information and share it among the adjacent intersections. Focus on smoothing traffic flow without stop-and-go driving and improving the coordination of multiple traffic lights, we develop a multi-intersection coordination algorithm based on V2X (MICA-V for short) to maximize the green waveband in the arterial road. Due to the establishment of registration list yielding the average saturated headway time, our method is of high efficiency&#x2014;the distributed process of data makes the convergence to be very fast with nearly linear time. Simulation results via MATLAB with Simulation of Urban Mobility (SUMO) showed the effectiveness of the proposed MICA-V in improving traffic capacity, reducing the number of stop behaviors, and improve the average speed of vehicles moving on the arterial road.

A Coordination Algorithm for Signalized Multi-Intersection to Maximize Green Wave Band in V2X Network