Meeting Professional Service Needs: Integration of Specialized Mathematics and the Application of Mathematical Algorithms in Urban Traffic Management

In response to the traffic congestion around tourist areas during holidays, this paper conducts an in-depth analysis of vehicle traffic data and proposes several models and solutions. First, the K-means clustering algorithm is used to divide the day into three main time periods based on traffic flow differences, providing scientific insights for traffic management. Second, a genetic algorithm is employed to optimize the signal light configuration of main roads, improving traffic efficiency. Third, by identifying cruising vehicles during the May Day holiday, the required number of temporary parking spaces in the tourist area is estimated, alleviating parking pressure. Finally, the T-test model is applied to evaluate the effectiveness of temporary traffic control measures, and the results show that these measures effectively reduced traffic flow and improved operational efficiency. This study is based on the 2024 National College Student Mathematical Modeling Contest, E Problem – Traffic Flow Control, and the results are highly consistent with the findings from actual reference materials.