A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Impact of pavement condition on passenger car traffic
The present paper explores the influence of pavement condition, roughness, and longitudinal grade on the operating speed (V85) of passenger car traffic at multi-lane roads. The pavement condition is described as a pavement condition index, while pavement roughness is expressed as an international roughness index. The necessary data are collected at 67 tangent sections and the following three modelling approaches are adopted for analysis: linear regression, multiple regression analysis, and artificial neural network. The obtained results show that the artificial neural network modelling approach is the best one for estimating the operating speed V85 in terms of main statistical parameters.
Impact of pavement condition on passenger car traffic
The present paper explores the influence of pavement condition, roughness, and longitudinal grade on the operating speed (V85) of passenger car traffic at multi-lane roads. The pavement condition is described as a pavement condition index, while pavement roughness is expressed as an international roughness index. The necessary data are collected at 67 tangent sections and the following three modelling approaches are adopted for analysis: linear regression, multiple regression analysis, and artificial neural network. The obtained results show that the artificial neural network modelling approach is the best one for estimating the operating speed V85 in terms of main statistical parameters.
Impact of pavement condition on passenger car traffic
Ahmed Mohamed Semeida (author) / Mohamed El-Shabrawy (author)
2016
Article (Journal)
Electronic Resource
Unknown
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