Predicting operating speed: comparison of linear regression and structural equation models
(2021) Institution of Civil Engineers. Proceedings. Transport — p. 1-13 (2021)
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- Authors
Bamdad Mehrabani, Behzad 
Abdi Kordani, Ali
- Abstract
- The aim of this research was to predict operating speed by considering geometric and roadside factors. Although most previous studies have employed linear regression modelling (LRM) to predict operating speed, this study recommends structural equation modelling (SEM) for the prediction of operating speed on rural multi-lane highways. In addition to geometric variables, LRM takes roadside variables into account. When employing SEM in this work, two latent variables were defined, namely ‘roadside effects’ and ‘geometric effects’. The first latent variable was the combination of land-use type, land-use density and number of accesses per segment, while the second was extracted from the segment length, highway grade, curvature, the presence of a guardrail and flat roadside slope, and the posted speed limits. The residual analysis and R2 values for LRM and SEM suggest that SEM demonstrates superior modelling performance compared with LRM. These results show the significant role of latent variables in predicting speed, which cannot be achieved through ordinary LRM.
- Affiliations
Citations
Bamdad Mehrabani, B., Mirbaha, B., Sgambi, L., & Abdi Kordani, A. (2021). Predicting operating speed: comparison of linear regression and structural equation models. Institution of Civil Engineers. Proceedings. Transport, 1-13. https://doi.org/10.1680/jtran.20.00065 (Original work published 2021)