沥青路面养护决策技术研究进展

    Progress in Research on Asphalt Pavement Maintenance Decision-making Technology

    • 摘要: 随着道路基础设施的快速发展,沥青路面养护工作面临着越来越多的挑战,传统养护方法由于里程长、病害类型多样、空间分布广泛及信息收集困难、效率低下等问题,迫切需要发展智慧养护技术。通过系统地总结沥青路面养护决策技术的发展历程,从早期的人工巡查和经验判断,到基于路况检测装备辅助的初级养护决策技术、中级阶段的大数据分析驱动技术,以及高级阶段的人工智能应用,分析了各阶段的工作原理、研究进展和优势与局限性,针对沥青路面养护决策所面临的挑战与需求进行了探究与展望。结果表明:养护决策技术在路面病害识别和养护方法的准确性与效率方面取得了显著进展,但不同等级道路检测需求与有限养护经费的矛盾,多类型病害智能识别效果、数据管理问题、预测准确性与资金分配复杂性,以及当前管理模式的局限性等方面仍面临挑战。将来通过技术的创新升级,尤其是物联网、传感器技术、人工智能等技术的深度融合应用,可以有效提高养护决策的精确度和智能化水平,但在沥青路面养护数字化转型升级,构建一套模型、一套数据的全生命期智慧养护决策等方面仍需要开展大量研究。

       

      Abstract: With the rapid development of road infrastructure, the maintenance of asphalt pavements faces increasing challenges. Traditional maintenance methods, due to their long mileage, diverse types of damages, widespread spatial distribution, difficulty in information collection, and low efficiency, urgently require the development of intelligent maintenance technologies. By systematically summarizing the development history of asphalt pavement maintenance decision-making technologies, from the early manual inspections and empirical judgments to the primary maintenance decision-making technologies aided by road condition detection equipment, to the intermediate stage of big data analysis-driven technologies, and to the advanced stage of artificial intelligence applications, this paper analyzed the working principles, research progress, advantages, and limitations of each stage. It also explored and forecasted the challenges and needs faced by asphalt pavement maintenance decision-making. The analysis shows that maintenance decision-making technologies have made significant progress in the accuracy and efficiency of pavement disease identification and maintenance methods. However, challenges still exist in areas such as the contradiction between detection needs for different levels of roads and limited maintenance funds, the effectiveness of intelligent identification of multiple types of diseases, data management issues, prediction accuracy, the complexity of fund allocation, and the limitations of current management models. In the future, through innovative upgrades in technology, especially the deep integration and application of the Internet of Things, sensor technology, and artificial intelligence, the precision and intelligence level of maintenance decision-making can be effectively improved. However, in the digital transformation and upgrading of asphalt pavement maintenance, building a system of models and data for the entire life cycle of intelligent maintenance decision-making, a large amount of research still needs to be conducted.

       

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