沥青
推论
因果推理
沥青路面
环境科学
计算机科学
工程类
土木工程
可靠性工程
计量经济学
运输工程
法律工程学
数学
人工智能
材料科学
复合材料
作者
Lingyun You,Nanning Guo,Zhengwu Long,Fusong Wang,Chundi Si,Aboelkasim Diab
标识
DOI:10.1080/10298436.2024.2381060
摘要
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 favourable options need to be chosen 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 annual post-maintenance performance of four preventive preservation treatments of pavements for longitudinal cracking over a 5-year period of upkeep. Three fundamental issues were brought to our attention: detection of causal relationships prior to variables under environmental loading (identification of causal structure); obtaining direct causal effects of treatment on outcomes excluding covariates (identification of causal effects) and sensitivity analysis of causal relationships. The results show that the method can accurately evaluate the effect of preventive maintenance treatments, assess the maintenance time to cater well for the functional performance of different preventive maintenance approaches and develop appropriate maintenance strategies for pavements.
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