Bandwidth Synchronization Under Progression Time Uncertainty

Deterministic progression time is generally assumed in bandwidth optimization models. However, progression time is cycle-by-cycle time varying and generally longer than the deterministic value. Progression time uncertainty has a considerable impact on the bandwidth that is obtained with deterministic data. In addition, we prove that there exist infinite optimal solutions in the MAXBAND model if a known optimal solution holds some properties. Different optimal solutions may have different sensitivities to progression time uncertainty. In this paper, we develop a two-phase approach. In the first phase we solve the MAXBAND models with perturbation controlled by a parameter and generate a number of optimal or suboptimal plans, and in the second phase we apply the Monte Carlo method to simulate random progression time, evaluate the generated plans, and rank them by the reliability. We also conduct extensive microscopic traffic simulation using VISSIM to evaluate delays and stops for certain optimal plans. Some observations are made.