Traffic congestion in urban areas represents a significant challenge that affects mobility and quality of life. This study explores how the modification of traffic rules at intersections, such as managing turns, speed control, and vehicular access, can improve traffic flow more efficiently than traditional approaches based solely on traffic signal adjustments. Through the analysis of different traffic algorithms and simulation models in SUMO, the impact of these modifications is evaluated in key indicators such as wait time, queue length, and CO \(_2\) emissions. The results suggest that a hybrid strategy combining adaptive traffic signal control with dynamic modification of traffic rules can significantly optimize urban mobility and reduce congestion. Additionally, it is evident that the implementation of these strategies allows for a more efficient use of existing road infrastructure.