地球信息科学学报 ›› 2021, Vol. 23 ›› Issue (9): 1586-1597.doi: 10.12082/dqxxkx.2021.200700

• 地球信息科学理论与方法 • 上一篇    下一篇

面向室内导航的分层认知路网优化方法

王行风1,*(), 刘俊生2   

  1. 1. 中国矿业大学环境测绘学院,徐州 221116
    2. 南京市测绘勘察研究院股份有限公司,南京 210019
  • 收稿日期:2020-11-19 出版日期:2021-09-25 发布日期:2021-11-25
  • 作者简介:王行风(1972— ),男,江苏徐州人,副教授,主要从事室内GIS与移动GIS研究。E-mail: xzwind@cumt.edu.cn
  • 基金资助:
    国家重点研发计划项目(2016YFB0502104)

Optimized Method of Indoor Road Network based on Spatial Hierarchical Cognition

WANG Xingfeng1,*(), LIU Junsheng2   

  1. 1. School of Environment and Spatial Informatics, China University of Mining Technology, Xuzhou 221116, China
    2. Nanjing Institute of Survey, Mapping & Geotechnical Investigation, Company Limited, Nanjing 210019, China
  • Received:2020-11-19 Online:2021-09-25 Published:2021-11-25
  • Contact: *WANG Xingfeng, E-mail: xzwind@cumt.edu.cn
  • Supported by:
    National Key Research and Development Program of China(2016YFB0502104)

摘要:

随着室内空间应用规模的增加以及室内定位技术的发展,面向大型场馆等室内空间的应急救援与导航成为室内GIS应用的研究热点,而室内路网构建是室内应急导航服务得以实现的关键技术。本文面向室内导航寻径的这一现实问题,以室内路网动态构建与优化作为研究对象,基于室内空间感知规律以及分层认知的方式,提出和构建了室内单元认知分层编码方法:① 将建筑物室内路网分为街道-建筑物、建筑物-楼层、楼层-区块、区块-房间等4个层次;② 为了满足语义分析的需求,在分析室内单元功能的基础上,引入“虚拟房间单元”,将室内封闭性空间和联系性空间统一剖分为房间单元;③ 依据室内建筑认知分层模型以及室内单元剖分结果,按照建筑物-楼层-分区-房间单元的顺序,从高级到低级的顺序进行连续分层编码。以国内某商业中心为例构建了室内分层认知路网,每一个层次都可以减少参与运算的结点和弧段数,简化了计算网络,从而提高了运算的效率,同楼层寻径时间约为55 ms,跨楼层的寻径时间约为100 ms左右。结果表明,该分层认知编码模型符合人们对室内路网的经验性层次认知,能够很好地刻画路网层次特征,能满足寻径计算的精度和效率的要求,为面向导航的室内应用奠定了基础。

关键词: 室内地理信息系统, 空间认知, 分层认知, 拓扑关系, 路网模型, 寻径, 位置服务, 室内导航

Abstract:

With the increase of indoor space application and the development of indoor positioning technology, the integration and application of indoor location information has become one of the hot spots in indoor GIS research. Emergency rescue and navigation for indoor space, such as large venues, has become a research hotspot of indoor GIS application. The construction of indoor network is the key technology to realize the indoor emergency navigation service. In this paper, aiming at the problem of indoor navigation routing, we proposed and constructed Indoor Cognitive Hierarchical Coding Method (ICHCM) based on indoor space perception and hierarchical cognition. The main contents are as follows: (1) Based on the law of indoor space perception and the way of hierarchical cognition, the indoor road network was simplified into four levels: street-building level, building-floor level, floor-block level, and block-room level. Thus a tree network of multi-level expression was formed; (2) In order to meet the needs of semantic analysis and path finding, the "virtual room" unit was introduced to divide the indoor closed unit and associated unit into room unit based on the analysis of the indoor unit function. The partition strategy of horizontal and vertical connection space was also provided; (3) Based on the cognitive hierarchical model of interior architecture and the results of indoor unit division, the indoor units were coded successively from high level to low level. This indoor unit encoding method is of great significance to semantic relations, spatial queries, topological relations, and path finding in indoor space. In order to verify the feasibility and effectiveness of the proposed road network construction and coding method, a commercial center was selected as study area, four levels of indoor road network were constructed. The number of nodes and arcs of every level of the network was reduced by layered and partitioned processing while the ICHCM network was effectively simplified and the efficiency of calculation was improved. The time used in path-finding was less than those of traditional network models. The same floor routing time was -55 millisecond while the cross floor routing time was -100 millisecond. The results showed that ICHCM model fits the way of the cognition of science for people. ICHCM can describe the characteristics of the network of different levels, enable the integrated path-finding of indoor space, and meet the demand of the precision and efficiency of path-finding. Results from this study provide important basis for indoor navigation.

Key words: indoor GIS, spatial cognition, layered cognitive, topological relationship, route network model, way-finding, location based service, indoor navigation