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Researchers are using Bluetooth traffic data to predict travel times by employing a data-driven approach. The methodology involves filtering, cleaning, and fusing the data to create advanced models and tools for forecasting congestion effects in urban areas. One promising model is an ARIMA-based one that showed good results in predicting travel times.
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Researchers are using Bluetooth traffic data to predict travel times by employing a data-driven approach. The methodology involves filtering, cleaning, and fusing the data to cre…
The article highlights several limitations of using Bluetooth traffic data for travel time prediction, including:1. Computational efforts: Processing Bluetooth data requires sign…
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