In order to protect extra retort teams, building labours, and the common community, road needs managing vehicle and pedestrian to manage traffic flows and offer guidance regarding traffic congestion, municipal or state roadway authorities may also utilize CCTV and other methods of traffic surveillance. One optimization framework is used to provide prompt and dependable decision-making by combining the dependable Whale Optimization Algorithms (WOA) and the quick-running Machine Learning (ML) algorithms. First, a standard WOA algorithm is used as a decision variable, with the network's total journey time serving as the unbiased role. In order to select the good performing model for additional hyper-tuning, multiple regression models are trained to estimate the overall journey interval in the traffic network under study. Finally, a good performance regression model, the extreme-gradient decision tree (XGBT), and WOA algorithm are clustered into a lone optimization outline.