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This study focused on the development of speed prediction models for a multilane highway which incorporate the potential endogenous relationship between adjacent lane speeds and speed deviations while considering geometric design, traffic flow, and other variables in the model specification and accounting for the correlation structures due to multilevel nature of data. The Full Bayesian framework was employed to build the hierarchical models which accounted for three correlation structures at multiple levels: the correlation between speeds of adjoining lanes due to multivariate nature; spatially structured correlations between the adjacent segments, and spatially unstructured correlations among segments.

The model estimates which influence the lane-mean speed indicated the directional variation of exogenous factors. For the westbound traffic, the afternoon and night hours were observed to be influential …