A causal discovery approach to study key mixed traffic‐related factors and age of highway affecting raveling

Author:

Wang Zili1,Krishnakumari Panchamy1,Anupam Kumar1,van Lint Hans1,Erkens Sandra1

Affiliation:

1. Faculty of Civil Engineering and Geosciences Delft University of Technology South Holland The Netherlands

Abstract

AbstractThe relationship between real‐world traffic and pavement raveling is unclear and subject to ongoing debates. This research proposes a novel approach that extends beyond traditional correlation analyses to explore causal mechanisms between mixed traffic and raveling. This approach incorporates the causal discovery method, and is applied to five Dutch porous asphalt (PA) highway sites that have substantial data sets. Findings indicate a nonlinear relationship between traffic volume and raveling, with road age emerging as a shared contributor. The results also suggest that the degree to which different vehicle types contribute as a causal factor for raveling varies with carriageway configurations and lane characteristics. This underlines the need for targeted maintenance strategies. Challenges remain due to confounding correlations among traffic variables, necessitating further development of causal discovery models. This study may not conclusively resolve the debate on to what extent traffic contributes to raveling, but we argue we provide sufficient evidence against rejecting this hypothesis.

Funder

Ministry of Infrastructure and Water Management

Rijkswaterstaat

Publisher

Wiley

Reference65 articles.

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