Dynamic gradient-based calibration for METANET-style traffic models yields 48% higher predictive accuracy and better robustness than static calibration on I-24 MOTION data.
The role of macroscopic modeling in the simulation, surveillance and control of motorway network traffic,
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Dynamic Gradient-Based Calibration for Robust and Accurate Traffic Macrosimulation
Dynamic gradient-based calibration for METANET-style traffic models yields 48% higher predictive accuracy and better robustness than static calibration on I-24 MOTION data.