多粒度时空对象的Geo-AI建模及公交线路规划应用

doi:10.13474/j.cnki.11-2246.2025.1004

测绘通报 ›› 2025, Vol. 0 ›› Issue (10): 20-25.doi: 10.13474/j.cnki.11-2246.2025.1004

• 智慧交通建设与实践 • 上一篇

多粒度时空对象的Geo-AI建模及公交线路规划应用

杜莹¹, 邓国臣², 韦原原¹

1. 郑州师范学院地理与旅游学院, 河南郑州 450044;
2. 中国测绘科学研究院, 北京 100036

收稿日期:2025-05-09 发布日期:2025-10-31
通讯作者: 邓国臣。E-mail:105319275@qq.com
作者简介:杜莹(1977-),女,博士,副教授,主要研究方向为地理信息系统与地理环境仿真。E-mail:zzdy2003@sina.com
基金资助:
国家重点研发计划(2021YFB3900900)

Spatio-temporal object-based Geo-AI modeling and application to bus route planning

DU Ying¹, DENG Guochen², WEI Yuanyuan¹

1. School of Geography and Tourism, Zhengzhou Normal University, Zhengzhou 450044, China;
2. Chinese Academy of Surveying and Mapping, Beijing 100036, China

Received:2025-05-09 Published:2025-10-31

摘要/Abstract

摘要： 多粒度时空对象作为全空间信息系统的基本数据模型,在空间数据实体化建模方面具有独特优势。本文结合时空对象模型的认知与行为能力特征,构建一种面向群体智能的Geo-AI模型。在Geo-AI与多粒度时空对象模型理论分析的基础上,引入蚁群优化算法,依托多粒度时空对象的数据组织方式,实现智能体与GIS数据的直接交互。通过实际公交线路规划案例,验证该模型在空间计算、仿真与交互方面的可行性和优势。试验结果表明,基于时空对象模型的Geo-AI群体智能建模方法,能够有效支持公交线路优化问题的求解;相较于传统方法,该模型在空间计算、动态仿真和实时交互方面表现出更强的适应性,为智能空间信息系统的进一步发展提供了新的技术思路。

关键词: 多粒度时空对象, 地理空间人工智能, 蚁群算法, 线路规划

Abstract: Multi-granularity spatio-temporal objects, as the basic data model of the pan-spatial information system, have special advantages in performing spatial data materialization modeling.Based on the cognitive and behavioral ability characteristics of the spatio-temporal object model, the construction and application of Geo-AI has become a research direction that urgently needs to be broken through in the field.On the basis of completing the basic theoretical analysis of Geo-AI and multi-granularity spatio-temporal object model, combining with the basic principle of ant colony algorithm, a Geo-AI group intelligence model based on spatio-temporal object data and applied to bus route planning is constructed, and experiments and applications are carried out in conjunction with practical cases.The results show that combining spatio-temporal object models with artificial intelligence algorithms enables Geo-AI modeling and applications directly based on GIS, and provides advantages in computation, simulation and real-time interaction for spatial planning problems.

Key words: multi-granularity spatio-temporal objects, Geo-AI, ant colony algorithm, route planning

中图分类号:

P208

杜莹, 邓国臣, 韦原原. 多粒度时空对象的Geo-AI建模及公交线路规划应用[J]. 测绘通报, 2025, 0(10): 20-25.

DU Ying, DENG Guochen, WEI Yuanyuan. Spatio-temporal object-based Geo-AI modeling and application to bus route planning[J]. Bulletin of Surveying and Mapping, 2025, 0(10): 20-25.

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多粒度时空对象的Geo-AI建模及公交线路规划应用

Spatio-temporal object-based Geo-AI modeling and application to bus route planning

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