随着交通基础设施建设规模持续扩张，传统公路养护决策模式面临数据孤岛、决策滞后、资源配置不均等困境。本文深入分析大数据技术在公路养护决策中的价值内涵，剖析当前融合应用中存在的数据质量参差不齐、技术标准缺失、人才队伍不足、投入产出评估困难等关键问题。在此基础上，构建基于感知层数据采集优化、平台层智能分析增强、应用层决策支持完善、保障层制度机制健全的精准决策实现路径，为提升公路养护决策科学性和有效性提供理论指导和实践参考。

With the continuous expansion of transportation infrastructure construction, traditional highway maintenance decision making models face challenges such as data silos, decision-making lag, and uneven resource allocation. This paper deeply analyzes the value connotation of big data technology in highway maintenance decision-making, and examines key issues in current integration applications, including uneven data quality, lack of technical standards, insufficient talent teams, and difficulties in input output evaluation. On this basis, the paper constructs a precision decision-making implementation path based on optimization of data collection at the perception layer, enhancement of intelligent analysis at the platform layer, improvement of decision support at the application layer, and establishment of sound institutional mechanisms at the guarantee layer. This research provides theoretical guidance and practical references for enhancing the scientific nature and effectiveness of highway maintenance decision-making.