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General conclusions on short term forecasting 1/2

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General conclusions on short term forecasting 1/2

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  1. Session: Short Term Forecasting1. Hubert Rehborn, DaimlerChrysler Research Institute, DE Best practice in short term forecasting of congested traffic patterns in Hessen2. Jan Holm, Danish Road Directorate, DK Model for short term forecast on M33. Klaus Kaae Andersen, Technical University of Denmark Short term forecast of travel times on the Danish motorway network based on TRIM data4. Satu Innamaa, VTT, Technical Research Centre of FinlandSelf-adapting flow status forecast

  2. General conclusions on short term forecasting 1/2 • Increased demand for short term forecasts • Several successful models available/developedrecently with very different approaches • Models presented are globally applicable depending on the type of raw data available • Self-adapting/self-learning methodsseem to be a suitable way forward because only a small amount of data is saved • Measurement of true travel times between inductive loops seem to be possible (recognition of sequencies of vehicles)

  3. General conclusions on short term forecasting 2/2 • Models already in on-line use • Forecasts could be a business case

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