2022
DOI: 10.1177/03611981221088197
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Analyzing the Difference Between Operating Speed and Target Speed Using Mixed-Effect Ordered Logit Model

Abstract: Desired operating speed (target speed) plays an important role in enhancing traffic operations and providing safe mobility to road users. Understanding the difference between vehicles’ operating speed and target speed on arterial roads is important for achieving safer speed that is consistent with the activity generated in the context classified roadways. This paper proposes a mixed-effect ordered logit model to examine the significant exogenous factors that affect the difference between the two speeds. To the… Show more

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Cited by 4 publications
(2 citation statements)
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References 38 publications
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“…As delineated by Mahmoud et al [35] and Palardy [36], estimations for nested data, alternatively known as hierarchical regression models, mixed regression models, nested data models, and random coefficient models, are categorized within the realm of Generalized Linear Latent and Mixed Models (GLLAMM). This approach enables the concurrent examination of both fixed and random effects associated with the observed phenomenon.…”
Section: A Multilevel Proportional Odds Approachmentioning
confidence: 99%
“…As delineated by Mahmoud et al [35] and Palardy [36], estimations for nested data, alternatively known as hierarchical regression models, mixed regression models, nested data models, and random coefficient models, are categorized within the realm of Generalized Linear Latent and Mixed Models (GLLAMM). This approach enables the concurrent examination of both fixed and random effects associated with the observed phenomenon.…”
Section: A Multilevel Proportional Odds Approachmentioning
confidence: 99%
“…Liu et al ( 21 ) revealed that slope direction, the absolute value of the elevation difference, the standard deviation of elevation, curve radius, and transition curve ratio help define highway alignment characteristics. Mahmoud et al ( 22 ) found that speed limit, traffic volume, shoulder width, block length, number of signals, pavement conditions, land use type, and population density significantly affect the GDC. Theofilatos and Yannis ( 23 ) found that the traffic volume significantly affects the crash rate.…”
mentioning
confidence: 99%