Navigating Urban Traffic Patterns: Ensemble Stacking for Improved Travel Time Prediction

Efficient travel time prediction is crucial for effective transportation planning, traffic management, and urban mobility. In this study, we present a novel approach to enhance travel time prediction accuracy in urban environments using ensemble stacking techniques. Leveraging gradient boosting algorithms as base models, our methodology integrates diverse predictive models to capture complex traff...