  To address the challenge of conflicting traffic flows that complete on
opposing cycle times in a specific phase of the traffic light, we proposed a
novel decentralized traffic light control methodology based on the
identification of the congestion's bottleneck and its influence. By computing
the cost of each congested tree, this methodology, called the Tree Method,
prioritizes bottlenecks based on global influence, i.e., their impact on the
entire road network. To test this methodology, we used SUMO (Simulation of
Urban Mobility) as a traffic simulator to run various simulations with both
realistic and abstract Origin-Destination (OD) matrices under different traffic
loads. By prioritizing traffic flows based on their global cost, rather than
merely local ones, the Tree Method accurately identified the root cause of
traffic-tree congestion and its effect along the traffic upstream. It exhibited
major improvements in both the throughput and the average travel time
measurements. Further in-depth analyses of individual simulation runs and
time-based performance demonstrated that the Tree Method is superior compared
to other methods, not only in terms of average performance but also for the
majority of drivers and throughout most of the time. Another significant
advantage of this method is its simplicity of analysis, facilitating real-time
adjustments in each cycle and aligning with the inherent feedback dynamics of
traffic flows. This feature makes the Tree Method highly suitable for
integration into actual traffic control systems.
