Advances in International Computer Science

Urban traffic congestion has become an urgent issue to be addressed in the development of modern cities. With the acceleration of urbanization, traffic pressure is increasing day by day. Large-scale traffic congestion not only affects the daily life of urban residents but also causes economic losses and environmental pollution. Big data-based traffic congestion prediction provides effective decision support for urban managers. Through the collection and analysis of real-time data, it can accurately predict the changing trends of traffic flow and timely adjust traffic control strategies, thereby alleviating congestion. Combining big data analysis to formulate scientific governance strategies helps improve traffic efficiency and enhance the quality of urban operation. This paper aims to explore the application of big data in urban traffic congestion prediction and governance, analyze its implementation paths, and propose specific governance strategies.

Urban traffic; Big data; Traffic congestion; Prediction; Governance strategies