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A Bayesian Markov mesh regime-switching regression model for bus travel time forecasting
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DOI：10.1016/j.tre.2026.104872.png)
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Abstract
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• A Bayesian Markov Mesh regime-switching regression model is proposed for probabilistic bus travel time forecasting. • A two-dimensional Markov mesh state structure captures joint link-to-link propagation and bus-to-bus interactions. • Regime-switching Gaussian regressions yield multimodal and skewed predictive travel time distributions with interpretable parameters. • A tailored block Gibbs sampling MCMC algorithm enables efficient posterior inference and uncertainty quantification.
Keywords:
Bus travel time
Probabilistic forecasting
Dynamic propagation
Hidden Markov Mesh model
Regime-switching regression
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