Adaptive and coordinated traffic signal control based on Q-learning and Multiband model

Adaptive and coordinated signal setting has been research emphasis. Cycle, split, and offset are three important parameters. Lessons and experiments about adaptive signal control have shown that cycle and phase sequence renewal interval should be less than 20 minutes. So frequently optimized parameters are split and offset. For Webster signal setting theory, the ratio between flow rate to saturation flow rate is the determining parameter. But this ratio is not sensitive to small flow rate change. Therefore, the paper integrates Q-learning with multiband model to realize adaptive and coordinated signal setting, in which the former optimizes split, the latter optimizes offset. Based on this integrated model, adaptive and coordinated signal setting for the three-intersections artery is done.