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    Applying Clustered KNN Algorithm for Short-Term Travel Speed Prediction and Reduced Speed Detection on Urban Arterial Road Work Zones by Hyun Su Park, Yong Woo Park, Oh Hoon Kwon, Shin Hyoung Park

    Published 2022-01-01
    “…This study developed and verified a travel speed prediction model based on the travel speed and work zone statistics collected from the advanced traffic management system (ATMS) real-time data in Daegu, South Korea. A clustered K-nearest neighbors (CKNN) algorithm was used to predict travel speed, resulting in a 6.9% average mean absolute percentage error (MAPE) using the data from 1,815 work zones. …”
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