A Cell‐Based Distributed‐Coordinated Approach for Network‐Level Signal Timing Optimization

This article develops an efficient methodology to optimize the timing of signalized intersections in urban street networks. Our approach distributes a network-level mixed-integer linear program (MILP) to intersection level. This distribution significantly reduces the complexity of the MILP and makes it real-time and scalable. We create coordination between MILPs to reduce the probability of finding locally optimal solutions. The formulation accounts for oversaturated conditions by using an appropriate objective function and explicit constraints on queue length. We develop a rolling-horizon solution algorithm and apply it to several case-study networks under various demand patterns. The objective function of the optimization program is to maximize intersection throughput. The comparison of the obtained solutions to an optimal solution found by a central optimization approach (whenever possible) shows a maximum of 1% gap on a number of performance measures over different conditions.