动态环境感知的多目标室内路径规划方法
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摘要
为了满足复杂室内环境中用户的多目标导航需求,提出了动态环境感知的多目标室内路径规划方法.该方法顾及室内路径复杂度、拥挤程度与阻断事件等多维室内环境语义,扩展了节点-边表示的室内导航路网模型,通过量化表征多维室内环境语义,建立了能够综合感知室内环境语义变化的导航通行成本函数,然后,将顾及室内动态环境语义的导航通行成本函数值作为室内导航路网模型的边长,设计实现了基于Dijkstra的多目标室内路径规划算法.通过模拟实验分析比较室内路径规划结果,实验结果表明:由于扩展后的室内导航路网模型增加了具有方向性语义的垂直组件,考虑了阻断事件因素,导航路径规划能够避开不可用连接边;在路径拥挤程度分别为轻度、缓慢和堵塞情况下,由于考虑了路径复杂度和拥挤程度,节约的通行时间平均提升了17%.
A dynamic environment-aware multi-objective indoor path planning method is proposed, aimed at satisfying the multi-objective navigation requirements of users in complex indoor environments. Multidimensional indoor environment semantics such as indoor path complexity, the degree of congestion, and blocking events were take into account. The node-edge representation indoor navigation network model was also expanded,and a navigation traffic cost function was established by precisely quantifying the multi-dimensional indoor environment semantics. The value of the navigation traffic cost function was then taken as the side length of the model, and a multi-objective indoor path planning algorithm based on Dijkstra was designed and implemented. The results of the simulation show that navigation path planning can avoid unavailable connection edges by adding the vertical components with directional semantics and considering the blocking events factor in the extended indoor navigation network model. After the path complexity and traffic congestion were considered,the travel time is saved by an average of 17% in three traffic patterns, i.e., light,mild and heavy congestion.
A dynamic environment-aware multi-objective indoor path planning method is proposed, aimed at satisfying the multi-objective navigation requirements of users in complex indoor environments. Multidimensional indoor environment semantics such as indoor path complexity, the degree of congestion, and blocking events were take into account. The node-edge representation indoor navigation network model was also expanded,and a navigation traffic cost function was established by precisely quantifying the multi-dimensional indoor environment semantics. The value of the navigation traffic cost function was then taken as the side length of the model, and a multi-objective indoor path planning algorithm based on Dijkstra was designed and implemented. The results of the simulation show that navigation path planning can avoid unavailable connection edges by adding the vertical components with directional semantics and considering the blocking events factor in the extended indoor navigation network model. After the path complexity and traffic congestion were considered,the travel time is saved by an average of 17% in three traffic patterns, i.e., light,mild and heavy congestion.
引文
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[2]MAKRI A,ZLATANOVA S,VERBREE E.An approach for indoor wayfinding replicating main principles of an outdoor navigation system for cyclists[J].The International Archives of the Photogrammetry,Remote Sensing and Spatial Information Sciences,2015,40(4):29-35.
[3]XIONG Qing,ZHU Qing,ZLATANOVA S,et al.Multi-level indoor path planning method[C]//International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences.Tokyo:[s.n.],2015:19-23.
[4]VANCLOOSTER A,VIAENE P,VAN D W N,et al.Analyzing the applicability of the least risk path algorithm in indoor space[C]//Isprs Annals of the Photogrammetry Rotnote Sensing and Spatial Information Sciences.Cape Town:[s.n.],2013:19-26.
[5]迟光华,谢君,李强,等.一种用于制定多层多出口的室内应急疏散规划的方法[J].遥感信息,2013,28(6):116-120.CHI Guanghua,XIE Jun,LI Qiang,et al.A method for planning multilayer and multi-exit indoor emergency evacuation[J].Remote Sensing Information,2013,28(6):116-120.
[6]KHAN A A,YAO Z,KOLBE T H.3D geoinformation science[M].3D Geoinformation Science.Berlin Heidelberg:Springer,2015:175-192.
[7]LIN Y H,LIU Y S,GAO G,et al.The IFC-based path planning for 3D indoor spaces[J].Advanced Engineering Informatics,2013,27(2):189-205.
[8]TSETSOS V,ANAGNOSTOPOULOS C,KIKIRASP,et al.Semantically enriched navigation for indoor environments[J].International Journal of Web&Grid Services,2006,2(4):453-478.
[9]XU Y,WEN Z,ZHANG X.Indoor optimal path planning based on Dijkstra algorithm[C]//International Conference on Materials Engineering and Information Technology Applications.Paris:Atlantis Press,2015:309-313.
[10]LYARDET F,SZETO D W,AITENBICHLER E.Context-aware indoor navigation[C]//European Conference on Ambient Intelligence.Berlin Heidelberg:Springer,2008:290-307.
[11]林雕,宋国民,游雄,等.基于上下文感知的室内路径规划研究[J].地理与地理信息科学,2016,32(3):8-13.LIN Diao,SONG Guomin,YOU Xiong,et al.Study on the context-aware indoor path planning[J].Geography and Geo-Information Science,2016,32(3):8-13.
[12]KARAS I R,BATUK F,AKAY A E,et al.Innovations in 3D Geo information systems[M].Berlin Heidelberg:Springer,2006:395-404.
[13]LEE J.A three-dimensional navigable data model to support emergency response in microspatial builtenvironments[J].Annals of the Association of American Geographers,2008,97(3):512-529.
[14]YUAN W,SCHNEIDER M.Geospatial thinking[M].Berlin Heidelberg:Springer,2010:299-313.
[15]SRIKULWONG M.Tactile displays for pedestrian navigation[D].Bath:University of Bath,2012.
[16]BALAKRISHNAN B,SUNDAR S S.Where am I?How can I get there?Impact of navigability and narrative transportation on spatial presence[J].HumanComputer Interaction,2011,26(3):161-204.
[17]DUCKHAM M,KULIK L.“Simplest”paths:automated route selection for navigation[J].Lecture Notes in Computer Science,2003,2825(1):169-185.
[18]RICHTER K F,DUCKHAM M.Simplest instructions:finding easy-to-describe routes for navigation[C]//International Conference on Geographic Information Science.Berlin Heidelberg:Springer,2008:274-289.
[19]GOLLEDGE R G,GARLING T.Handbook of transport geography and spatial systems[M].Bingley:Emerald Group Publishing Limited,2004:501-512.
[20]TURNER A.Spatial information theory[M].Berlin Heidelberg:Springer,2009:489-504.
[21]LO S M,FANG Z,LIN P,et al.An evacuation model:the SGEM package[J].Fire Safety Journal,2004,39(3):169-190.