Traffic signal timing optimization in connected vehicles environment

We study the traffic signal control problem under the connected vehicle (CV) environment by assuming a fixed cycle length so that the proposed model can be extended readily for the coordination of multiple signals. The signal control problem is to minimize the weighted sum of total system fuel consumption and travel times. Due to the large dimension of the problem and the complexity of the nonlinear car-following model, we propose a Dynamic programming (DP) formulation by dividing the timing decisions into stages (one stage for a phase) and approximating the fuel consumption and travel time of a stage as functions of the state and decision variables of the stage. We also propose a two-step method, the end stage cost, and a branch and bound algorithm, to make sure that the obtained optimal solution can lead to the fixed cycle length. Numerical experiments are provided to test the performance of the proposed model using data generated by traffic simulation.