CERTH presentation of a model for accurate traffic prediction under both normal and abnormal conditions

Posted November 3rd, 2016 | Categories: Movesmart

CERTH presented in the 19th EURO Working Group on Transportation Meeting, held during 5-7 of September in Istanbul, their work on a new model for accurate traffic prediction under both normal and abnormal conditions. The model is based on the identification of the traffic patterns shown under both normal and abnormal conditions using a clustering algorithm and the use of different prediction models from the fields of machine learning and time series analysis for each separate cluster that represents a traffic pattern. Experimental results indicated that the proposed model outperforms typical traffic prediction models from the relevant literature in terms of prediction accuracy under both normal and abnormal conditions.

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