Asphalt pavements as the most prevalent transportation infrastructure, are prone to serious traffic safety problems due to functional or structural damage caused by stresses or strains imposed through repeated traffic loads and continuous climatic cycles. The good quality or high serviceability of infrastructure networks is vital to the urbanization and industrial development of nations. In order to maintain good functional pavement performance and extend the service life of asphalt pavements, the long-term performance of pavements under maintenance policies needs to be evaluated and favorable options selected based on the condition of the pavement. A major challenge in evaluating maintenance policies is to produce valid treatments for the outcome assessment under the control of uncertainty of vehicle loads and the disturbance of freeze-thaw cycles in the climatic environment. In this study, a novel causal inference approach combining a classical causal structural model and a potential outcome model framework is proposed to appraise the long-term effects of four preventive maintenance treatments for longitudinal cracking over a 5-year period of upkeep. Three fundamental issues were brought to our attention: 1) detection of causal relationships prior to variables under environmental loading (identification of causal structure); 2) obtaining direct causal effects of treatment on outcomes excluding covariates (identification of causal effects); and 3) sensitivity analysis of causal relationships. The results show that the method can accurately evaluate the effect of preventive maintenance treatments and assess the maintenance time to cater well for the functional performance of different preventive maintenance approaches. This framework could help policymakers to develop appropriate maintenance strategies for pavements.

结合经典因果结构模型和潜在结果模型框架，提出了一种新的因果推断方法，评估了五年维护期间四种预防性维护措施对纵向龟裂的长期效果，结果显示该方法能准确评估维护措施的效果并评估维护时间以保证不同的预防性维护方法的功能性能。该框架可帮助政策制定者制定适当的道路维护策略。

评估养护政策对沥青路面功能性能的长期影响的因果推断方法