This paper investigates the application of Artificial Intelligence (AI) in forecasting vehicle traffic risk during road connection and construction activities. It focuses on how AI models, including machine learning and predictive analytics, can analyze historical traffic data, environmental conditions, and real-time inputs to predict potential congestion, accidents, and disruptions. The study emphasizes AI’s role in proactive traffic management, helping authorities plan safer and more efficient road connections. By identifying high-risk zones and periods, AI-driven forecasting supports strategic decision-making, minimizes delays, and enhances road user safety. The research underlines AI’s capacity to revolutionize traffic risk prediction and infrastructure planning.

Artificial Intelligence, Traffic Risk Forecasting, Road Construction, Predictive Analytics, Traffic Management, Machine Learning.

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