Abstract:

Increasing urbanization, rapid urban population growth and economic development are signs of society's rapid development. There are increasing traffic problems in the city, which affect the city's normal function. This paper aims to create a computational model to study vehicle queues on urban roads to control vehicle crashes, traffic volumes and average vehicle delays. This model offers analysis at multiple intersections with traffic lights controlling vehicle queues based on fixed time intervals. We defined our objective function as minimizing the queue length. We used the Matlab program to simulate the proposed method. MPC-based traffic control can be implemented in any urban transportation network, but a modern traffic controller and a proper measurement system are needed for that goal. Furthermore, we address this issue explicitly by employing a sampled multi-agent system at the intersection. The intersections are considered independent agents, which share information, and their stability is established independently. The simulations show the model predictive control in the simulation results prove the effectiveness of the designed model predictive control based traffic control strategy and show that the system can improve the network efficiency and cause reduces the lengths of cars

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