Abstract

Abstract Traffic flow at urban intersections fluctuates randomly throughout the day. It depends on several dynamic factors and requires adequate regulation and adaptable control strategies in particular for traffic signals regulation. This paper deals with this problem, and our proposal focuses on the adaptive management of traffic lights within urban intersections. To do so, Timed Synchronized Petri Nets (TSPNs) models are first developed to model and study the system behaviour. Then a real-time adaptive control strategy is proposed for traffic regulation within urban signalized intersections. The control logic is shared between two communicating components of the system. The slaves (TSPNs sub-models) control the traffic signals displays, phases transitions, and traffic flow fluctuations. The master (controller) decides and selects the next phase that should be serviced and determines its green light duration. Due to the used modularity approach, the developed models decrease the modelling complexity, and more importantly, they can be adapted easily to a cluster of intersections. Furthermore, various traffic signal control strategies could be implemented using these models. Moreover, some simulations are performed, and the obtained results are analysed and discussed. Our control strategy is validated through these simulation results.

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