Comparison of Models for the Prediction of Travel Time for Public Transport Prioritization

Public transportation plays an important role in enhancing the environmental sustainability of urban traffic system. Since the 1980s, public transport prioritization at signalized intersections has been instrumental in reducing travel time and improving passenger comfort. The development of V2X (Vehicle-to-Everything) technology presents new opportunities to further enhance the prioritization. Accurate travel time prediction is crucial for optimizing public transport prioritization at intersections. In this study, we introduce a set of models for the prediction of travel time and apply them to a real-world dataset. Then the applicability of our models is compared by analyzing the temporal and spatial characteristics of the accuracy and their temporal consistency of predictions.