Simulation Optimization of Urban Arterial Signals via Simultaneous Perturbation Stochastic Approximation (SPSA)

In this paper, we develop a simulation optimization procedure for optimizing the urban arterial traffic signal timings including a bunch of sequential intersections. The system performance is estimated via a stochastic discrete-event meso-scopic traffic simulator, and a gradient-based search algorithm on stochastic approximation is applied to give the optimal signal timings. Simultaneous perturbation analysis is used to derive both left-hand and right-hand gradient estimators of the system performance with respect to the cycle lengths, green splits, and green offsets for those intersections within the arterial. Numerical experiments show that the meso-scopic traffic simulator provides reasonable system performance in much less running time if properly calibrated, compared with a widely-used commercial traffic microscopic simulation program CORSIM. In particular, for all scenarios designed, the optimizer converges to optimal signal timing plans which significantly increase the system performance