A Hybrid Scheme for Real-Time Prediction of Bus Trajectories
(English)Manuscript (preprint) (Other academic)
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 based heuristic. The hybrid method was applied to five bus lines in Stockholm, Sweden and Brisbane, Australia. The results indicate that the hybrid method consistently outperforms the timetable and delay conservation prediction method for different line 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.
Transport Systems and Logistics
IdentifiersURN: urn:nbn:se:kth:diva-177486OAI: oai:DiVA.org:kth-177486DiVA: diva2:872972
QS 20152015-11-202015-11-202016-02-21Bibliographically approved