Python package to process NGSIM data and traffic sensing with autonomous vehicles
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Updated
Jun 15, 2020 - Jupyter Notebook
Python package to process NGSIM data and traffic sensing with autonomous vehicles
Official GE-GAN implementation for road traffic state estimation using graph embedding and WGAN; includes PeMS/Seattle data and a reproducible PeMS download workflow.
Calibration-free traffic state estimation method using detectors and connected vehicles data
Research-ready Caltrans PeMS downloader with uv, speed/flow/occupancy exports, detector GeoJSON, official SHN road geometry, maps, and GE-GAN profile.
Features injected recurrent neural networks for short-term traffic speed prediction
Using traffic flow and travel preference data to generate individual travel chain on the Highway
Traffic density and velocity reconstruction from sparse SUMO probes using Data-driven, LWR, and ARZ models.
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