RiccardoSpolaor/Verbal-Explanations-of-Spatio-Temporal-Graph-Neural-Networks-for-Traffic-Forecasting
An eXplainable AI system to elucidate short-term speed forecasts in traffic networks obtained by Spatio-Temporal Graph Neural Networks.
This tool helps traffic managers and urban planners understand why a traffic forecasting system predicts congestion or free flow on specific road segments. It takes existing traffic network data and short-term speed forecasts, then explains the reasons behind the predictions in easy-to-understand verbal descriptions and visual subgraphs. This is designed for non-technical users who need to trust and act on AI-driven traffic predictions.
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Use this if you need clear, verbal explanations for why your traffic forecasting system is predicting specific congestion or free flow patterns.
Not ideal if you are looking for a system to generate raw traffic speed forecasts rather than explain existing ones.
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Jupyter Notebook
License
MIT
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Last pushed
Feb 23, 2024
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