Print Email Facebook Twitter A hybrid scheme for real-time prediction of bus trajectories Title A hybrid scheme for real-time prediction of bus trajectories Author Fadaei, Masoud (KTH Royal Institute of Technology) Cats, O. (TU Delft Transport and Planning; KTH Royal Institute of Technology) Bhaskar, Ashish (Queensland University of Technology) Date 2016 Abstract The uncertainty associated with public transport services can be partially counteracted by developing real-time models to predict downstream service conditions. In this study, a hybrid approach for predicting bus trajectories by integrating multiple predictors is proposed. The prediction model combines schedule, instantaneous and historical data. The contribution of each predictor as well as values of respective parameters is estimated by minimizing the prediction error using a linear regression heuristic. The hybrid method was applied to five bus routes in Stockholm, Sweden, and Brisbane, Australia. The results indicate that the hybrid method consistently outperforms the timetable and delay conservation prediction method for different route layouts, passenger demands and operation practices. Model validation confirms model transferability and real-time applicability. Generating more accurate predictions can help service users adjust their travel plans and service providers to deploy proactive management and control strategies to mitigate the negative effects of service disturbances. Subject bus reliabilityhybrid modellinear regression heuristicreal-time informationtravel time predictionvehicle trajectory To reference this document use: http://resolver.tudelft.nl/uuid:f30cd496-d1a8-4f0e-bd14-d24c8e21cb78 DOI https://doi.org/10.1002/atr.1450 ISSN 0197-6729 Source Journal of Advanced Transportation, 50 (8), 2130-2149 Part of collection Institutional Repository Document type journal article Rights © 2016 Masoud Fadaei, O. Cats, Ashish Bhaskar Files PDF atr1450.pdf 642.03 KB Close viewer /islandora/object/uuid:f30cd496-d1a8-4f0e-bd14-d24c8e21cb78/datastream/OBJ/view