A hybrid scheme for real‐time prediction of bus trajectories |
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| Authors: | Masoud Fadaei Oded Cats Ashish Bhaskar |
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| Affiliation: | 1. Department of Transport Science, Royal Institute of Technology (KTH), Stockholm, Sweden;2. Department of Transport and Planning, Delft University of Technology, Delft, The Netherlands;3. Smart Transport Research Centre, School of Civil Engineering and Built Environment, Queensland University of Technology (QUT), Brisbane, Queensland, Australia |
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| 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. Copyright © 2017 John Wiley & Sons, Ltd. |
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| Keywords: | travel time prediction hybrid model real‐time information vehicle trajectory bus reliability linear regression heuristic |
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