面向室内导航的分层认知路网优化方法

doi:10.12082/dqxxkx.2021.200700

摘要/Abstract

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

王行风, 刘俊生. 面向室内导航的分层认知路网优化方法[J]. 地球信息科学学报, 2021, 23(9): 1586-1597.DOI:10.12082/dqxxkx.2021.200700

WANG Xingfeng, LIU Junsheng. Optimized Method of Indoor Road Network based on Spatial Hierarchical Cognition[J]. Journal of Geo-information Science, 2021, 23(9): 1586-1597.DOI:10.12082/dqxxkx.2021.200700

图/表 12

图1

图2

图3

图4

图5

图6

图7

图8

表1

表2

表3

图9

参考文献 26

[1]	李清泉, 周宝定, 马威, 等. GIS辅助的室内定位技术研究进展[J]. 测绘学报, 2019, 48(12):1498-1506.
	[ Li Q Q, Zhou B D, Ma W, et al. Research process of GIS-aided indoor localization[J]. Acta Geodaetica et Cartographica Sinica, 2019, 48(12):1498-1506. ]
[2]	Liu L, Li B F, Zlatanova S, et al. Indoor navigation supported by the Industry Foundation Classes (IFC): A survey[J]. Automation in Construction, 2021, 121:103436. doi: 10.1016/j.autcon.2020.103436
[3]	Fu M Q, Liu R. An approach of checking an exit sign system based on navigation graph networks[J]. Advanced Engineering Informatics, 2020, 46:101168. doi: 10.1016/j.aei.2020.101168
[4]	赵江洪, 董岩, 危双丰, 等. 室内导航路网提取研究进展[J]. 测绘科学, 2020, 45(12):45-54,76.
	[ Zhao J H, Dong Y, Wei S F, et al. Review of the research progresses on extraction of indoor navigation network[J]. Science of Surveying and Mapping, 2020, 45(12):45-54,76. ]
[5]	Fu M Q, Liu R, Qi B, et al. Generating straight skeleton-based navigation networks with Industry Foundation Classes for indoor way-finding[J]. Automation in Construction, 2020, 112:103057. doi: 10.1016/j.autcon.2019.103057
[6]	Han T, Almeida J S, da Silva S P P, et al. An effective approach to unmanned aerial vehicle navigation using visual topological map in outdoor and indoor environments[J]. Computer Communications, 2020, 150:696-702. doi: 10.1016/j.comcom.2019.12.026
[7]	Lin J, Zhu R H, Li N, et al. Do people follow the crowd in building emergency evacuation? A cross-cultural immersive virtual reality-based study[J]. Advanced Engineering Informatics, 2020, 43:101040. doi: 10.1016/j.aei.2020.101040
[8]	Lee J. A spatial access-oriented implementation of a 3-D GIS topological data model for urban entities[J]. GeoInformatica, 2004, 8(3):237-264. doi: 10.1023/B:GEIN.0000034820.93914.d0
[9]	Chen L C, Wu C H, Shen T S, et al. The application of geometric network models and building information models in geospatial environments for fire-fighting simulations[J]. Computers, Environment and Urban Systems, 2014, 45:1-12. doi: 10.1016/j.compenvurbsys.2014.01.003
[10]	de Thill J C, Dao T H D, Zhou Y H. Traveling in the three-dimensional city: Applications in route planning, accessibility assessment, location analysis and beyond[J]. Journal of Transport Geography, 2011, 19(3):405-421. doi: 10.1016/j.jtrangeo.2010.11.007
[11]	Gupta S, R S, Mishra R S, et al. Corridor segmentation for automatic robot navigation in indoor environment using edge devices[J]. Computer Networks, 2020, 178:107374. doi: 10.1016/j.comnet.2020.107374
[12]	Lin W Y, Lin P H. Intelligent generation of indoor topology (i-GIT) for human indoor pathfinding based on IFC models and 3D GIS technology[J]. Automation in Construction, 2018, 94:340-359. doi: 10.1016/j.autcon.2018.07.016
[13]	赵彬彬, 王安, 汤鑫, 等. 基于廊道空间几何特性的室内导航路网模型构建[J]. 长沙理工大学学报(自然科学版), 2019, 16(4):8-15.
	[ Zhao B B, Wang A, Tang X, et al. Construction of indoor navigation network model based on spatial geometrical characteristics of corridor space[J]. Journal of Changsha University of Science & Technology (Natural Science), 2019, 16(4):8-15. ]
[14]	Ma G F, Wu Z J. BIM-based building fire emergency management: Combining building users' behavior decisions[J]. Automation in Construction, 2020, 109:102975. doi: 10.1016/j.autcon.2019.102975
[15]	尤承增, 彭玲, 王建辉, 等. 高精度室内地图辅助VLC与PDR融合定位[J]. 地球信息科学学报, 2019, 21(9):1402-1410. doi: 10.12082/dqxxkx.2019.190061
	[ You C Z, Peng L, Wang J H, et al. VLC and PDR fusion positioning by incorporating high-precision indoor map[J]. Journal of Geo-information Science, 2019, 21(9):1402-1410. ]
[16]	Tu S S, Waqas M, Lin Q Q, et al. Tracking area list allocation scheme based on overlapping community algorithm[J]. Computer Networks, 2020, 173:107182. doi: 10.1016/j.comnet.2020.107182
[17]	Lee K, Lee J, Kwan M P. Location-based service using ontology-based semantic queries: A study with a focus on indoor activities in a university context[J]. Computers, Environment and Urban Systems, 2017, 62:41-52. doi: 10.1016/j.compenvurbsys.2016.10.009
[18]	熊维茜, 高平, 呙维, 等. 面向多层建筑的室内外一体化路径规划算法[J]. 测绘地理信息, 2020, 45(1):44-46,61.
	[ Xiong W Q, Gao P, Guo W, et al. Indoor and outdoor integrated path planning algorithm for multi-story buildings[J]. Journal of Geomatics, 2020, 45(1):44-46,61. ]
[19]	傅梦颖, 张恒才, 王培晓, 等. 基于移动对象轨迹的室内导航网络构建方法[J]. 地球信息科学学报, 2019, 21(5):631-640. doi: 10.12082/dqxxkx.2019.190024
	[ Fu M Y, Zhang H C, Wang P X, et al. A method for constructing indoor navigation networks based on moving object trajectory[J]. Journal of Geo-information Science, 2019, 21(5):631-640. ]
[20]	Hajibabai L, Delavar M R, Malek M R, et al. Agent-Based Simulation of Spatial Cognition and Wayfinding in Building Fire Emergency EvacuationGeomatics Solutions for Disaster Management[J]. Geomatics Solutions for Disaster Managenment, 2007, 6752(4):255-270.
[21]	王行风. 面向室内外一体化寻径的道路网络空间感知层次建模方法[J]. 测绘科学技术, 2018, 6(2):141-150.
	[ Wang X F. Hierarchical Modeling of Indoor and Outdoor Road Network Based on Spatial Cognition[J]. Geomatics Science and Technology, 2018, 6(2):141-150. ] doi: 10.12677/GST.2018.62016
[22]	王行风, 汪云甲. 一种顾及拓扑关系的室内三维模型组织和调度方法[J]. 武汉大学学报·信息科学版, 2017, 42(1):35-42.
	[ Wang X F, Wang Y J. Organization and scheduling of indoor three-dimensional geometric model based on spatial topological relation[J]. Geomatics and Information Science of Wuhan University, 2017, 42(1):35-42. ]
[23]	唐炉亮, 刘章, 杨雪, 等. 符合认知规律的时空轨迹融合与路网生成方法[J]. 测绘学报, 2015, 44(11):1271-1276,1284.
	[ Tang L L, Liu Z, Yang X E, et al. A method of spatio-temporal trajectory fusion and road network generation based on cognitive law[J]. Acta Geodaetica et Cartographica Sinica, 2015, 44(11):1271-1276,1284. ]
[24]	Fletcher Dunn, Ian Parberry. 史银雪,陈洪,王荣静译. 3D数学基础:图形与游戏开发[M]. 北京: 清华大学出版社, 2005.
	[ 3D Math Primer for Graphics and Game Development[M]. Beijing: Tsinghua University Press, 2005. ]
[25]	朱金龙. 室内场景下人群疏散的若干关键技术研究[D]. 长春:吉林大学, 2016.
	[ Zhu J L. Research on several key technologies of the crowd evacuation in indoor scene[D]. Changchun: Jilin University, 2016. ]
[26]	张海荣, 王行风, 闫志刚. 地理信息系统原理[M]. 徐州: 中国矿业大学出版社, 2017.
	[ Zhang H R, Wang X F, Yan Z G. Principles of geographical information system[M]. Xuzhou: China University of Mining and Technology Press, 2017. ]

楼层	节点数/个		弧段数/段
楼层	分层网络模型	ICHCM	分层网络模型	ICHCM
1层	170	144	176	150
2层	172	138	183	145
3层	184	156	195	145
4层	128	113	136	127
5层	102	87	112	91
垂直弧段	-	-	68	68
总计	756	638	870	726

	寻径方式	参与寻径的结点/个	参与寻径的弧段/段	寻径时间/ms
分层网络模型	同层	136	145	102
分层网络模型	跨楼层	263	272	216
ICHCM	同层	82	62	55
ICHCM	跨楼层	205	176	102

路网层次	节点数/个	弧段数/段	说明
Street-building	0	0	和室外街道路网相连的出入口
Building-floor	85	68	电梯弧段、楼梯弧段、扶梯弧段
Floor-block	113	108	建筑物的第一、五层的联系空间弧段信息
Block-room	5	4	第四层A区各个房间节点、弧段起止点、交叉点等
小计	203	180