测绘通报 ›› 2026, Vol. 0 ›› Issue (9): 123-130.doi: 10.13474/j.cnki.11-2246.2026.0918

• 学术研究 • 上一篇    下一篇

车路云一体化下高精地图数据价值形成与评价指标体系

应申1,2, 普贝吉1, 陶璐1, 贺风3, 孙国睿1   

  1. 1. 武汉大学资源与环境科学学院, 湖北武汉 430079;
    2. 亚热带建筑与城市科学全国重点实验室, 广东广州 510630;
    3. 中国地图出版社集团有限公司, 北京 100054
  • 收稿日期:2026-06-29 发布日期:2026-10-09
  • 作者简介:应申(1979—),男,博士,教授,研究方向为高精地图、3DGIS。E-mail:shy@whu.edu.cn
  • 基金资助:
    国家自然科学基金(42471479);亚热带建筑与城市科学全国重点实验室开放研究基金(2024KA05)

Value formation and evaluation indicator system of high-definition map under vehicle-road-cloud integration

Ying Shen1,2, Pu Beiji1, Tao Lu1, He Feng3, Sun Guorui1   

  1. 1. School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, China;
    2. State Key Laboratory of Subtropical Building and Urban Science, Guangzhou 510630, China;
    3. Sinomaps Press Group Co., Ltd., Beijing 100054, China
  • Received:2026-06-29 Published:2026-10-09

摘要: [目的]在车路云一体化环境下,高精地图数据的价值形成具有分阶段、多主体和动态累积特征,亟需建立适用于其场景特征的价值评价指标体系。[方法]本文基于马克思劳动价值论,从价值转移与价值增殖视角出发,结合高精地图数据流通的前置生产、正式生产和应用3个阶段,分析其在一次生产、多次生产与反馈优化生产中的价值形成逻辑及对应市场结构。[结果]构建了分阶段的高精地图数据资产价值评价指标体系,形成数据质量、合规治理、信息丰度、成本投入、感知协同、决策支撑、控制执行、公共治理增殖、数据赋能、平台协同和商业模式11个评价维度。[结论]该指标体系能够较系统地刻画高精地图数据资产的价值形成过程,为其价值评价及后续货币化估值提供基础支撑。

关键词: 车路云一体化, 高精地图, 数据资产, 价值评价指标体系, 价值转移, 价值增殖, 数据流通

Abstract: [Purposes] Under the vehicle-road-cloud integrated architecture,the value formation of high-definition map (HDMap)data is characterized by staged evolution,multi-stakeholder participation,and dynamic accumulation.It is therefore necessary to establish a value evaluation indicator system suited to its scenario-specific characteristics.[Methods] Based on Marx's labor theory of value and from the perspectives of value transfer and value valorization,this study examines the value formation logic of HDMap data in single production,multiple production,and feedback optimization,as well as the corresponding market structures,in relation to the three stages of data circulation: pre-production,production,and application.[Findings] A stage-specific value evaluation indicator system for HDMap data assets is constructed,including 11 evaluation dimensions: data quality,compliance governance,information richness,cost input,perception coordination,decision support,control execution,public governance value valorization,data empowerment,platform coordination,and business model.[Conclusions] The proposed indicator system can systematically characterize the value formation process of HDMap data assets and provide a foundation for their value evaluation and subsequent monetary valuation.

Key words: vehicle-road-cloud integration, HDMap, data assets, value evaluation indicator system, value transfer, value valorization, data circulation

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