kaist-dmlab/MG-TAR
[IEEE T-ITS] MG-TAR: Multi-view Graph Convolutional Networks for Traffic Accident Risk Prediction
This project helps urban planners, traffic safety analysts, and transportation agencies predict traffic accident risk in specific districts. It takes in local dangerous driving statistics and environmental data, then outputs a forecast of future accident risk and identifies the most dangerous areas. The goal is to inform proactive safety measures and resource allocation.
No commits in the last 6 months.
Use this if you need to accurately forecast traffic accident risk across different geographical districts using a combination of driving behavior and environmental factors.
Not ideal if you lack access to detailed dangerous driving statistics or contextual environmental data for your target regions.
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60
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23
Language
Python
License
MIT
Category
Last pushed
Nov 10, 2023
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