Intelligent traffic flow prediction using time- series models

Abstract

Traffic congestion leads to wasted time, increased fuel consumption, and environmental damage. To mitigate these effects, predicting traffic flow with high accuracy is crucial. Traditional statistical models offer limited capabilities in handling nonlinear and complex patterns in traffic data. In contrast, intelligent methods based on time-series analysis and machine learning provide better flexibility and adaptability.