Progression optimization in large scale urban traffic networks: A heuristic decomposition approach

Progression methods are widely used for optimization of traffic signal system operation in arterials and in grid networks. The methods provide robust solutions for traffic control as well as a multitude of design alternatives that are not readily available in other models. Solution procedures were developed in recent years using mixed-integer linear programming methods. While these methods can produce optimal solutions, they are computationally demanding and inefficient for traffic control applications. This paper describes a heuristic decomposition procedure for the optimization of the variable bandwidth network progression problem. The procedure does not merely exploit the mathematical formulation of the mixed-integer linear program, but is primarily based on the traffic characteristics of the network. The network is decomposed into priority sub-networks which facilitates the accelerated determination of the optimal values for the integer variables. The heuristic improves dramatically the efficiency of the computation, by at least a factor of 1/100. This enables to handle larger-scale networks, similar to the ones found in many metropolitan areas. Overall, more efficient computational procedures result in the ability to obtain improved solutions and, ultimately, lead to improved performance of the traffic network.