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.

中文翻译：

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研究影响松散的关键混合交通相关因素和高速公路年龄的因果发现方法

现实世界的交通和路面磨损之间的关系尚不清楚，并且一直存在争论。这项研究提出了一种新颖的方法，超越了传统的相关性分析，探索混合交通和拆散之间的因果机制。该方法结合了因果发现方法，并应用于拥有大量数据集的五个荷兰多孔沥青 (PA) 高速公路站点。研究结果表明，交通量与散车之间存在非线性关系，其中道路老化成为共同的影响因素。结果还表明，不同车辆类型作为散线因果因素的程度随车道配置和车道特征的不同而变化。这强调了有针对性的维护策略的必要性。由于交通变量之间的混杂相关性，挑战仍然存在，需要进一步开发因果发现模型。这项研究可能无法最终解决关于流量在多大程度上促进散乱的争论，但我们认为我们提供了足够的证据来反对拒绝这一假设。