Header menu link for other important links
X
Performance comparison of data driven and less data demanding techniques for bus travel time prediction
Published in Institute for Transport Studies in the European Economic Integration
2017
   
Issue: 65
Abstract
Accurate travel time information of public transport will help operators to effectively manage and implement their operating strategies and help passengers by reducing the uncertainty about arrival time of buses at bus stops. The reliability of such information provided to passengers greatly depends on the prediction technique used, which in turn, depends on the quality of the input used in the prediction technique. In other words, identifying and using the correct input in the appropriate prediction technique is important. Prediction techniques can be data driven or less data intensive. The first part of this paper presents a systematic statistical approach for identifying the significant inputs for travel time prediction. The second part compares the performance of two popular prediction methods, one being the data driven Artificial Neural Network (ANN) method and the other being a model based approach using the Kalman Filter Technique (KFT) that is less data intensive, to predict bus travel time. The performances of both methods were evaluated using the data obtained from the field. It was found that ANN outperformed KFT in terms of prediction error, if a good database is available, and in case of limited data availability, KFT will be more advantag eous.
About the journal
JournalEuropean Transport - Trasporti Europei
PublisherInstitute for Transport Studies in the European Economic Integration
ISSN18253997
Open AccessNo
Concepts (17)
  •  related image
    Bus transportation
  •  related image
    Buses
  •  related image
    Forecasting
  •  related image
    Kalman filters
  •  related image
    Neural networks
  •  related image
    Statistical methods
  •  related image
    Time varying control systems
  •  related image
    Transportation
  •  related image
    BUS TRAVEL TIME PREDICTIONS
  •  related image
    KALMAN FILTER TECHNIQUE
  •  related image
    KALMAN FILTERING TECHNIQUES
  •  related image
    Performance comparison
  •  related image
    PREDICTION TECHNIQUES
  •  related image
    SIGNIFICANT INPUTS
  •  related image
    TRAVEL TIME INFORMATION
  •  related image
    Travel time prediction
  •  related image
    Travel time