A TGNN selects road segments and predicts road-measurement uncertainty inside a Kalman filter, reducing urban GNSS horizontal error at the 95th percentile by 29% relative to GNSS-only.
Osmnx: A python package to work with graph-theoretic openstreetmap street networks
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Neural Augmented Kalman Filters for Road Network assisted GNSS positioning
A TGNN selects road segments and predicts road-measurement uncertainty inside a Kalman filter, reducing urban GNSS horizontal error at the 95th percentile by 29% relative to GNSS-only.