2022•International Journal of Pavement EngineeringRequires access

A simplified skid resistance predicting model for a freeway network to be used in a pavement management system

Heriberto Pérez-Acebo, Mikel Montes-Redondo, Andreas Appelt, Daniel J. Findley

Open publisher page 31 citations

Abstract

The available skid resistance, or friction, in a pavement surface is a vital parameter for functional evaluations of roads due to its relation with crashes. Therefore, highway administrations must collect friction data on their road network to provide safe roads to users. Additionally, a prediction model that can forecast the available skid resistance in each road segment is necessary for an efficient pavement management system (PMS). The aim of this paper is to develop a skid resistance prediction model for the bituminous pavements of the motorway network of federal state of Bavaria, in Germany, with information that is typically available in a PMS: the Annual Average Daily Traffic , the Annual Average Daily Heavy Traffic , and the number of lanes in each segment. Despite its simplicity, with 6410 road segments of 2 and 3 lanes of the Bavarian motorway network, the model achieves a determination coefficient (R2) of 0.405. If information about the surface layer material is added, R2 increases to 0.480. Consequently, apart from predicting the minimum available friction in each lane in a motorway, the study underlines the necessity that a PMS should contain the recommended elements and additional surface layer material, because the quality of the prediction improves.

About this research paper

What this paper is about

The available skid resistance, or friction, in a pavement surface is a vital parameter for functional evaluations of roads due to its relation with crashes. Therefore, highway administrations must collect friction data on their road network to provide safe roads to users. Additionally, a prediction model that can forecast the available skid resistance in each road segment is necessary for an efficient pavement management system (PMS). The aim of this paper is to develop a skid resistance prediction model for the bituminous pavements of the motorway network of federal state of Bavaria, in Germany, with information that is typically available in a PMS: the Annual Average Daily Traffic , the Annual Average Daily Heavy Traffic , and the number of lanes in each segment. Despite its simplicity, with 6410 road segments of 2 and 3 lanes of the Bavarian motorway network, the model achieves a determination coefficient (R2) of 0.405. If information about the surface layer material is added, R2 increases to 0.480. Consequently, apart from predicting the minimum available friction in each lane in a motorway, the study underlines the necessity that a PMS should contain the recommended elements and additional surface layer material, because the quality of the prediction improves.

Why it matters

OpenAlex reports 31 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

The available skid resistance, or friction, in a pavement surface is a vital parameter for functional evaluations of roads due to its relation with crashes. Therefore, highway administrations must collect friction data on their road network to provide safe roads to users. Additionally, a prediction model that can forecast the available skid resistance in each road segment is necessary for an efficient pavement management system (PMS). The aim of this paper is to develop a skid resistance prediction model for the bituminous pavements of the motorway network of federal state of Bavaria, in Germany, with information that is typically available in a PMS: the Annual Average Daily Traffic , the Annual Average Daily Heavy Traffic , and the number of lanes in each segment. Despite its simplicity, with 6410 road segments of 2 and 3 lanes of the Bavarian motorway network, the model achieves a determination coefficient (R2) of 0.405. If information about the surface layer material is added, R2 increases to 0.480. Consequently, apart from predicting the minimum available friction in each lane in a motorway, the study underlines the necessity that a PMS should contain the recommended elements and additional surface layer material, because the quality of the prediction improves.

Key concepts: Skid (aerodynamics), Pavement management, Road surface, Transport engineering, Environmental science, Friction coefficient, Engineering, Civil engineering

Related papers

Back to paper searchBrowse research topicsOriginal source
A simplified skid resistance predicting model for a freeway network to be used in a pavement management system — Research Paper | ScholarLens