Computing and Informatics

Traffic flow at urban intersections varies randomly during the day. It depends on several dynamic factors and requires efficient regulation and flexible control strategies in particular for traffic light regulation. The proposed strategy allows managing the green light time autonomously. The dynamic behavior of traffic signals at intersections can be seen as a discrete event system. Through this paper, a modular Timed Synchronized Petri Net (TSPN) model is developed and a real-time adaptive control strategy of urban signalized intersections is proposed. The control is shared between two communicant actors. The master-slaves approach is adopted in this control strategy. The master (controller) decides the next phase to be served with green light and its duration. While, the slaves (TSPN modules) control the traffic signals displays, phases transitions, and model traffic flow fluctuations. Thanks to the used modularity approach, the developed models reduce the system complexity in terms of combinatorial explosion, and they could be adapted easily for any real intersection. Using the developed models, some interesting properties of the system are checked, and some simulations are performed and analyzed in order to validate the proposed control approach.