Dynamic gradient-based calibration reformulates static estimation as a control problem and achieves 48% better predictive accuracy than static methods on I-24 MOTION data.
Perfor- mance of continuum models for realworld traffic flows: Comprehensive benchmarking
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Dynamic Gradient-Based Calibration for Robust and Accurate Traffic Macrosimulation
Dynamic gradient-based calibration reformulates static estimation as a control problem and achieves 48% better predictive accuracy than static methods on I-24 MOTION data.