Modeling the endogeneity of lane-mean speeds and lane-speed deviations using a Bayesian structural equations approach with spatial correlation

Wen Cheng, Gurdiljot Singh Gill, Taha Sakrani, Dennis Ralls and Xudong Jia

Transportation Research Part A: Policy and Practice, 2018, vol. 116, issue C, 220-231

Abstract: 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.

Keywords: Random effects; Spatial correlation; Multivariate; Multilane; Endogeneity; Speed prediction (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (2)

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DOI: 10.1016/j.tra.2018.06.014

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