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

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

Wang, Z. (TU Delft Transport and Planning)
Krishnakumari, P.K. (TU Delft Transport and Planning)
Anupam, K. (TU Delft Pavement Engineering)
van Lint, J.W.C. (TU Delft Transport and Planning)
Erkens, S. (TU Delft Pavement Engineering)

2024

The 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.

http://resolver.tudelft.nl/uuid:b8379edc-ea14-41f9-82c5-9a8440c691a5

https://doi.org/10.1111/mice.13222

1093-9687

Computer-Aided Civil and Infrastructure Engineering

Institutional Repository

journal article

© 2024 Z. Wang, P.K. Krishnakumari, K. Anupam, J.W.C. van Lint, S. Erkens