Cycle-level vs. Second-by-Second Adaptive Traffic Signal Control using Deep Reinforcement Learning

With unrelenting growth in population and urbanization, cities face escalating challenges in providing fast and reliable mobility. A significant source of delay for urban commuters is related to signalized intersections. optimizing traffic signals to maximize the capacity of intersections is of critical importance for cities. Although this topic has been around for decades, recently, Deep Reinforcement Learning (DRL) approaches have begun to be …