Signal Traffic Optimization Using Control Algorithm in Urban Traffic Framework

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.