Distributed traffic control system based on model predictive control
The paper investigates a distributed control system scheme for urban road traffic management. The control algorithm is based on model predictive control (MPC) involving Jacobi iteration algorithm to solve constrained and nonlinear programming problem. The signal controllers of traffic network constitute a network of computers. They can distribute their computation realizing an efficient traffic control without any central management. However the optimal control inputs can be also calculated by a single traffic controller if the traffic network contains few intersections. The control aim is to relieve traffic congestion, reduce travel time and improve homogenous traffic flow in urban traffic area using distributed control architecture. The MPC based control strategy can be implemented in any urban transportation network but adequate measurement system and modern traffic controllers are needed. Theory, realization possibilities and simulation of the control method are also presented. The simulation results show that the system is able to ameliorate the network efficiency and reduce travel time. The distributed MPC based traffic control strategy proves the effectiveness by realizing a dependable control operation and creating optimal flow in the network subjected to control input constraints.