A Bayesian approach to traffic estimation in stochastic user equilibrium networks.

Highlights: [•] This study proposes a statistical model to estimate route traffic flows in congested networks. [•] We formulate the problem as a conditional distribution of route flows. [•] The Bayesian theorem is applied to derive the conditional distribution. [•] A hierarchical form is designed to integrate prior knowledge. [•] Characteristics of route/link traffic flows are estimated using a blocked Metropolis–Hastings (M–H) algorithm. [ABSTRACT FROM AUTHOR]