A hierarchical Bayesian formulation of the Intelligent Driver Model, implemented with TensorFlow Probability and Edward2, calibrates per-driver parameters and outperforms pooled, individual, and genetic-algorithm baselines on in-sample error metrics.
A case for online traffic simulation: Systematic procedure to calibrate car-following models using vehicle data,
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Strengthening the Case for a Bayesian Approach to Car-following Model Calibration and Validation using Probabilistic Programming
A hierarchical Bayesian formulation of the Intelligent Driver Model, implemented with TensorFlow Probability and Edward2, calibrates per-driver parameters and outperforms pooled, individual, and genetic-algorithm baselines on in-sample error metrics.