CN103913165B - A kind of indoor emergency response context aware navigationsystem and navigation method - Google Patents
A kind of indoor emergency response context aware navigationsystem and navigation method Download PDFInfo
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Abstract
The present invention relates to a kind of indoor emergency response context aware navigationsystem and navigation method. Described navigationsystem at least comprises positioned sensor network, server and early warning sensor, and described positioned sensor network is by the locating base station of the wired or wireless connection of same server, form with the mobile terminal of locating base station wireless connections and/or positioning label and the LED screen with locating base station wired connection; Described early warning sensor is with server wireless connections. The multiple context of described navigation methods combining indoor environment calculates guidance path, and sight residing for user presents guidance path to user in several ways adaptively, it is provided that real-time, accurate, personalized navigation Service. The present invention can be used for large complicated indoor venue personnel positioning, emergency evacuation, Post disaster relief, the security control such as hospital, market, office building, station etc., it is possible to the science of raising public place emergency response disposal, promptness, validity.
Description
Technical field
The present invention relates to a kind of indoor positioning navigationsystem, belong to indoor positioning navigation and location-based service field, in particular to a kind of indoor emergency response context aware navigationsystem and navigation method.
Background technology
Along with the fast development of the technology such as geographical information system(GIS) (GIS), location Based service (LBS) and thing networking, Spatial Information Technology and application expand to the interior space gradually. It is estimated that have 80% all relevant to position in the information that obtains of people, and people reach the time of 87% average every day in the interior space, and people are more and more urgent to Indoor Location Information demand. Especially the large-scale indoor site surrounding such as hospital, market, office building, station is complicated, personnel's high concentration, and when there is emergency situation, the real time position how obtaining personnel in time carries out evacuating navigation, the key being rapid evacuation He suing and labouring.
Indoor navigation system of the prior art generally includes server, positioned sensor, positioned sensor base station and navigation and receives terminal, the foundation of its navigation is mainly static map information, by arranging Origin And Destination and utilize path algorithm to provide navigation way. Also there is comparatively advanced indoor navigation system, consider dynamic personnel positions and density when calculating navigation way, make navigation way comparatively accurate.
But, indoor navigation system of the prior art, does not arrange fire alarm sensor or smoke transducer usually, therefore when there is fire alarm or toxic gas diffusion event, cannot provide escape route safely and effectively. Simultaneously, also there is multiple influence factor in actual indoor environment, the such as translational speed of dissimilar personnel, road type, road safety, fire service, illumination situation etc., play keying action for evacuating navigation when realizing efficient real with aid decision making service, and there is no these influence factors at present as the indoor navigation system inputting data. In addition, be there is larger difference by the dissimilar like this user of the general population and the disabled in navigation demand, and existing indoor navigation system only provides two or three maps or voice navigate mode usually, guidance path and the guide information of applicable different crowd feature can not be provided, user individual navigation Service demand cannot be met.
Summary of the invention
In order to solve the deficiencies in the prior art, the present invention provides a kind of indoor emergency response context aware navigationsystem, is provided with locating device and early warning sensor, it is possible to real-time collecting personnel positions also responds to fire or poison gas disaster; Present invention also offers a kind of navigation method based on this system, it is contemplated that multiple static state that navigation is had an impact by indoor environment, dynamic effects factor, it may be possible to provide in real time, accurately, navigation way efficiently. Meanwhile, the present invention can arrange user preference for dissimilar user, provides navigation way by the mode of indoor two three-dimensional maps, voice, note or LED screen so that navigate mode more personalized, hommization.
The present invention is the technical scheme that its technical problem of solution adopts:
The present invention provides a kind of indoor emergency response context aware navigationsystem, and this system at least comprises positioned sensor network, server and early warning sensor; Described positioned sensor network is by the locating base station of the wired or wireless connection of same server, form with the mobile terminal of locating base station wireless connections and/or positioning label, LED screen with locating base station wired connection, wherein locating base station receives the positional parameter of each mobile terminal and the transmission of each positioning label and sends it to server, sends the location navigation result calculated by server to mobile terminal and/or LED screen; Positioning label sends positional parameter to locating base station; Mobile terminal sends positional parameter to locating base station and receives the navigation results of locating base station transmission; LED screen receives and shows the navigation results that locating base station sends; Described server receives data, the store management data of locating base station and early warning sensor transmission, and utilizes optimum path planning algorithms to calculate guidance path, and guidance path data are sent to locating base station; Described early warning sensor with server wireless connections, for respond to disaster and occur disaster time send early warning signal to server. Described positioned sensor base station can be Wi-Fi base station; Described mobile terminal can be have the mobile equipments such as the mobile phone of location with wireless transmission function or panel computer;Described positioning label can be Wi-Fi positioning label; Described server is have wired and computer that is wireless transmission function.
Described early warning sensor is fire alarm sensor and/or smoke transducer, for responding to fire and/or toxic gas and send early warning signal to server.
This system also comprises the monitoring terminal of same server wired connection.
Present invention also offers a kind of navigation method, specifically comprise the following steps:
(1) indoor emergency response context aware navigationsystem is built: dispose positioned sensor network, server, early warning sensor and LED screen at indoor scene, early warning sensor is fire alarm sensor and/or smoke transducer, the type of each early warning sensor and distributing position information is stored in the server; Mobile terminal and positioning label are carried with by personnel, and everyone carries a mobile terminal or a positioning label; LED screen is placed at the obvious place of metope;
(2) for each mobile terminal and positioning label define personnel's type respectively, and personnel's type data are stored in server; Described personnel's type comprises the general population and the disabled;
(3) by mobile terminal editing navigation requested data send to server, described navigation requests data comprise navigation preference, start position and terminal position, described navigation preference receives the foundation of navigation information mode as mobile terminal, and navigate mode comprises digital map navigation, voice navigation, note navigation and LED screen navigation;
(4) set up indoor emergency response navigation position model and store in the server; Described indoor emergency response navigation position model comprises spatial context and non-spatial context, and wherein spatial context comprises indoor scene two-dimension vector map, grating map, two dimensional navigation network model and three-dimensional space model, three-dimensional navigation network model; Non-spatial context comprises static context and dynamic context, wherein static context comprises the personnel's type in emergency response environment, road type, road distance, road safety, fire service and illumination situation, and dynamic context comprises disaster type, disaster position and impact scope, personnel's real time position, density of personnel, the average evacuation speed of personnel; Wherein, the static context data in described spatial context data and non-spatial context utilize GIS software modeling to obtain according to actual indoor environment, and the dynamic context data in non-spatial context is obtained by following step:
(4a) disaster type, disaster position and impact scope:
When presence of fire or toxic gas diffusion disaster, early warning sensor sends early warning signal to server, according to the early warning sensor type sending signal, server determines that disaster type is fire or toxic gas diffusion disaster, and adopt the disaster spreading model based on cellular automata, using the distributing position of early warning sensor as input, dynamic calculation Hazard processes and spread situation, to obtain disaster impact scope;
(4b) personnel's real time position:
Positional parameter is sent to locating base station by mobile terminal and positioning label in real time, positional parameter is sent to server by locating base station again, server receives positional parameter and it can be used as input, locates blending algorithm computing staff's real time position by the Wi-Fi/DR based on particle filter;
(4c) density of personnel:
Utilize stream of people's density calculation model that Predtechenski and Milinskii proposes by following formulae discovery:
D=Nf/WL ... ..(1)
Wherein, D is people's flow density, and N represents number, draws by everyone's real time position statistics;F represents individual's horizontally-projected area, for directly presetting empirical value in the server; W represents stream of people's width, and namely the most Zuoren person of the stream of people and the real-time ultimate range of the rightest personnel, calculate according to everyone's real time position; L represents stream of people's length, and namely the most front personnel of the stream of people and the real-time ultimate range of last personnel, calculate according to everyone's real time position;
(4d) the average evacuation speed of personnel:
Judge personnel's type: if personnel's type is as the disabled, then the average evacuation speed V of the personnel that arrange0For 1.20-1.40m/s; If personnel's type is the general population, then calculate evacuation speed according to following sight:
When the general population is without, when passing through road under disaster scenarios it, personnel average evacuation speed V is by following formulae discovery:
V=112D4-38D3+434D2-217D+57 ... ... ..(2)
Wherein, V is the average evacuation speeds of personnel, and unit is m/min, D is people's flow density, calculates according to formula (1);
When the general population is without the average evacuation speed V of personnel when passing through door under disaster scenarios it1By following formulae discovery:
V1=V [1.17+0.13sin (6.03D-0.12)] ... .(3)
Wherein, D is people's flow density, calculates according to formula (1);
As the personnel average evacuation speed V of the general population under disaster scenarios it2By following formulae discovery:
V2=V·μ1..(4)
Wherein, μ1Be experience factor, calculate according to following two kinds of scenes: by horizontal channel or by open wide door time, μ1By following formulae discovery:
μ1=1.49-0.36D ... ..(5)
Wherein, D is people's flow density, calculates according to formula (1);
Time downstairs, μ1It is set to empirical value 1.21;
(5) building navigation network data and be stored in server, described navigation network data are band power digraph G, G=<V ', E, W>, and wherein V ' is the set on summit in figure, and E is the set on limit, and W is the set of the power on each limit; The set V ' on summit and the set E on limit, according to the definition of indoor scene two-dimension vector map in spatial context, represents the road of indoor scene, with the joint of each road of vertex representation with limit; For each the limit of G, there is the power that a real number is called limit, the power on each limit is more than or equal to zero, and the more big expression of weights is crowded more serious, represents that the road from a node to another node direction does not exist or target node can not reach when weights are just infinite; The set W of the power on each limit is determined by following step:
(5a) utilizing analysis expert method, by two or more, expert defines weights respectively for each decision attribute, and described decision attribute is expressed by non-spatial context, and the weights of each decision attribute adopt exponential scale method scale;
(5b) for each decision attribute, the expert decision-making weights each expert provided are averaged, and get the comprehensive weights that the immediate scale with mean value is this decision attribute; If upper and lower two adjacent scales are identical with the difference of the mean value tried to achieve, then get the comprehensive weights that the less scale of variance is this decision attribute;
(5c) the every bar limit in digraph G is weighed for band, each decision attribute is set to the importance per-cent of this edge, respectively the importance per-cent of this edge is multiplied by the comprehensive weights of each decision attribute with it, the result i.e. weights on this limit that each product is added, the weights calculating every bar limit respectively finally obtain set W;
(6) server is by the Point matching of the navigation start position of step (3) and terminal position and band power digraph G, using band power digraph G, starting point S and terminal T as input, Dijkastra algorithm or A* algorithm is utilized to export the optimum path data between starting point S and terminal T;
(7) user preference that server receives according to step (3) determines navigate mode, with the form of map, voice or note, optimum path data is sent to locating base station, then is sent to mobile terminal and/or LED screen by locating base station;
(8) mobile terminal and/or LED screen show the optimum path data received and guide target to navigate;
(9) repeating step (4) is to step (8), until the positional information that mobile terminal sends is the terminal position that step (3) is arranged, navigation terminates.
The useful effect that the present invention produces based on its technical scheme is:
(1) the present invention utilizes early warning sensor real-time collecting disaster data, and using this disaster data as input so that navigation way safety and reliability;
(2) the multiple context of indoor scene stored in collection in real time and/or server is participated in the calculating of optimum navigation way by the present invention as parameter so that navigation procedure has concurrently in real time, feature accurate, efficient;
(3) the present invention is directed to dissimilar user's feature and calculate the density of population so that navigation is more accurately reliable;
(4) the present invention is directed to different user preferences, it is possible to send navigation information with map, note, voice mode to mobile terminal and/or LED screen, guide target, make navigation guide mode more personalized, hommization.
Accompanying drawing explanation
Fig. 1 is navigationsystem block diagram.
Fig. 2 is navigation method flow diagram.
Embodiment
Below in conjunction with drawings and Examples, the invention will be further described.
The present invention provides a kind of indoor emergency response context aware navigationsystem, and this system at least comprises positioned sensor network, server and early warning sensor; Described positioned sensor network is by the locating base station of the wired or wireless connection of same server, form with the mobile terminal of locating base station wireless connections and/or positioning label, LED screen with locating base station wired connection, wherein locating base station receives the positional parameter of each mobile terminal and the transmission of each positioning label and sends it to server, sends the location navigation result calculated by server to mobile terminal and/or LED screen; Positioning label sends positional parameter to locating base station; Mobile terminal sends positional parameter to locating base station and receives the navigation results of locating base station transmission; LED screen receives and shows the navigation results that locating base station sends; Described server receives data, the store management data of locating base station and early warning sensor transmission, and utilizes optimum path planning algorithms to calculate guidance path, and guidance path data are sent to locating base station; Described early warning sensor with server wireless connections, for respond to disaster and occur disaster time send early warning signal to server. Described positioned sensor base station can be-Wi-Fi base station; Described mobile terminal can be have the mobile equipments such as the mobile phone of location with wireless transmission function or panel computer; Described positioning label can be-Wi-Fi positioning label; Described server is have wired and computer that is wireless transmission function.
Described early warning sensor is fire alarm sensor and/or smoke transducer, for responding to fire and/or toxic gas and send signal to server.
This system also comprises the monitoring terminal of same server wired connection.
Present invention also offers a kind of navigation method, specifically comprise the following steps:
(1) indoor emergency response context aware navigationsystem is built: dispose positioned sensor network, server, early warning sensor and LED screen at indoor scene, early warning sensor is fire alarm sensor and/or smoke transducer, the type of each early warning sensor and distributing position information is stored in the server;Mobile terminal and positioning label are carried with by personnel, and everyone carries a mobile terminal or a positioning label; LED screen is placed at the obvious place of metope;
(2) for each mobile terminal and positioning label define personnel's type respectively, and personnel's type data are stored in server; Described personnel's type comprises the general population and the disabled;
(3) by mobile terminal editing navigation requested data send to server, described navigation requests data comprise navigation preference, start position and terminal position, described navigation preference receives the foundation of navigation information mode as mobile terminal, and navigate mode comprises digital map navigation, voice navigation, note navigation and LED screen navigation;
(4) set up indoor emergency response navigation position model and store in the server; Described indoor emergency response navigation position model comprises spatial context and non-spatial context, and wherein spatial context comprises indoor scene two-dimension vector map, grating map, two dimensional navigation network model and three-dimensional space model, three-dimensional navigation network model; Non-spatial context comprises static context and dynamic context, wherein static context comprises the personnel's type in emergency response environment, road type, road distance, road safety, fire service and illumination situation, and dynamic context comprises disaster type, disaster position and impact scope, personnel's real time position, density of personnel, the average evacuation speed of personnel; Wherein, the static context data in described spatial context data and non-spatial context utilize GIS software modeling to obtain according to actual indoor environment, and the dynamic context data in non-spatial context is obtained by following step:
(4a) disaster type, disaster position and impact scope:
When presence of fire or toxic gas diffusion disaster, early warning sensor sends signal to server, according to the early warning sensor type sending signal, server determines that disaster type is fire or toxic gas diffusion disaster, and adopt the disaster spreading model based on cellular automata, based on cellular automata, in conjunction with the distributing position of early warning sensor, dynamic calculation Hazard processes, with spreading situation, obtains disaster impact scope;
(4b) personnel's real time position:
Office's territory coordinate data are sent to positioned sensor base station by mobile terminal and positioning label in real time, and Zai Jiangju territory, positioned sensor base station coordinate data are sent to server, server office of acceptance territory coordinate data, thus obtain personnel's real time position;
(4c) density of personnel:
Utilize stream of people's density calculation model that Predtechenski and Milinskii proposes by following formulae discovery:
D=Nf/WL ... ..(1)
Wherein, D is people's flow density, and N represents number, draws by everyone's real time position statistics; F represents individual's horizontally-projected area, for directly presetting empirical value in the server; W represents stream of people's width, and namely the most Zuoren person of the stream of people and the real-time ultimate range of the rightest personnel, calculate according to everyone's real time position; L represents stream of people's length, and namely the most front personnel of the stream of people and the real-time ultimate range of last personnel, calculate according to everyone's real time position;
(4d) the average evacuation speed of personnel:
Judge personnel's type: if personnel's type is as the disabled, then the average evacuation speed V of the personnel that arrange0For 1.20-1.40m/s; If personnel's type is the general population, then calculate evacuation speed according to following sight:
When the general population is without, when passing through road under disaster scenarios it, personnel average evacuation speed V is by following formulae discovery:
V=112D4-38D3+434D2-217D+57 ... ... ..(2)
Wherein, V is the average evacuation speeds of personnel, and unit is m/min, D is people's flow density, calculates according to formula (1);
When the general population is without the average evacuation speed V of personnel when passing through door under disaster scenarios it1By following formulae discovery:
V1=V [1.17+0.13sin (6.03D-0.12)] ... .(3)
Wherein, D is people's flow density, calculates according to formula (1);
As the average evacuation speed V of the personnel under disaster scenarios it2By following formulae discovery:
V2=V·μ1..(4)
Wherein, μ1Be experience factor, calculate according to following two kinds of scenes: by horizontal channel or by open wide door time, μ1By following formulae discovery:
μ1=1.49-0.36D ... ..(5)
Wherein, D is people's flow density, calculates according to formula (1);
Time downstairs, μ1It is set to empirical value 1.21;
(5) building navigation network data and be stored in server, described navigation network data are band power digraph G, G=<V ', E, W>, and wherein V ' is the set on summit in figure, and E is the set on limit, and W is the set of the power on each limit; The set V ' on summit and the set E on limit, according to the definition of indoor scene two-dimension vector map in spatial context, represents the road of indoor scene, with the joint of each road of vertex representation with limit; For each the limit of G, there is the power that a real number is called limit, the power on each limit is more than or equal to zero, and the more big expression of weights is crowded more serious, represents that the road from a node to another node direction does not exist or target node can not reach when weights are just infinite; The set W of the power on each limit is determined by following step:
(5a) utilizing analysis expert method, make more than 2 experts define weights respectively for each decision attribute, described decision attribute is expressed by non-spatial context, and the weights of each decision attribute adopt exponential scale method scale;
(5b) for each decision attribute, the expert decision-making weights each expert provided are averaged, and get the comprehensive weights that the immediate scale with mean value is this decision attribute; If upper and lower two adjacent scales are identical with the difference of the mean value tried to achieve, then get the comprehensive weights that the less scale of variance is this decision attribute;
(5c) the every bar limit in digraph G is weighed for band, each decision attribute is set to the importance per-cent of this edge, respectively the importance per-cent of this edge is multiplied by the comprehensive weights of each decision attribute with it, the result i.e. weights on this limit that each product is added, the weights calculating every bar limit respectively finally obtain set W;
(6) server is by the Point matching of the navigation start position of step (3) and terminal position and band power digraph G, using band power digraph G, starting point S and terminal T as input, Dijkastra algorithm or A* algorithm is utilized to export the optimum path data between starting point S and terminal T;
(7) user preference that server receives according to step (3) determines navigate mode, with the form of map, voice or note, optimum path data is sent to locating base station, then is sent to mobile terminal and/or LED screen by locating base station;
(8) mobile terminal and/or LED screen show the optimum path data received and guide target to navigate;
(9) repeating step (4) is to step (8), until the positional information that mobile terminal sends is the terminal position that step (3) is arranged, navigation terminates.
Claims (1)
1. respond a navigation method for context aware navigationsystem based on indoor emergency, described system at least comprises positioned sensor network, server and early warning sensor;Described positioned sensor network is by the locating base station of the wired or wireless connection of same server, form with the mobile terminal of locating base station wireless connections and/or positioning label, LED screen with locating base station wired connection, wherein locating base station receives the positional parameter of each mobile terminal and the transmission of each positioning label and sends it to server, sends the location navigation result calculated by server to mobile terminal and/or LED screen; Positioning label sends positional parameter to locating base station; Mobile terminal sends positional parameter to locating base station and receives the navigation results of locating base station transmission; LED screen receives and shows the navigation results that locating base station sends; Described server receives data, the store management data of locating base station and early warning sensor transmission, and utilizes optimum path planning algorithms to calculate guidance path, and guidance path data are sent to locating base station; Described early warning sensor with server wireless connections, for respond to disaster and occur disaster time send early warning signal to server, it is characterised in that specifically comprise the following steps:
(1) indoor emergency response context aware navigationsystem is built: dispose positioned sensor network, server, early warning sensor and LED screen at indoor scene, early warning sensor is fire alarm sensor and/or smoke transducer, the type of each early warning sensor and distributing position information is stored in the server; Mobile terminal and positioning label are carried with by personnel, and everyone carries a mobile terminal or a positioning label; LED screen is placed at the obvious place of metope;
(2) for each mobile terminal and positioning label define personnel's type respectively, and personnel's type data are stored in server; Described personnel's type comprises the general population and the disabled;
(3) by mobile terminal editing navigation requested data send to server, described navigation requests data comprise navigation preference, start position and terminal position, described navigation preference receives the foundation of navigation information mode as mobile terminal, and navigate mode comprises digital map navigation, voice navigation, note navigation and LED screen navigation;
(4) set up indoor emergency response navigation position model and store in the server; Described indoor emergency response navigation position model comprises spatial context and non-spatial context, and wherein spatial context comprises indoor scene two-dimension vector map, grating map, two dimensional navigation network model and three-dimensional space model, three-dimensional navigation network model; Non-spatial context comprises static context and dynamic context, wherein static context comprises the personnel's type in emergency response environment, road type, road distance, road safety, fire service and illumination situation, and dynamic context comprises disaster type, disaster position and impact scope, personnel's real time position, density of personnel, the average evacuation speed of personnel; Wherein, the static context data in described spatial context data and non-spatial context utilize GIS software modeling to obtain according to actual indoor environment, and the dynamic context data in non-spatial context is obtained by following step:
(4a) disaster type, disaster position and impact scope:
When presence of fire or toxic gas diffusion disaster, early warning sensor sends early warning signal to server, according to the early warning sensor type sending signal, server determines that disaster type is fire or toxic gas diffusion disaster, and adopt the disaster spreading model based on cellular automata, using the distributing position of early warning sensor as input, dynamic calculation Hazard processes and spread situation, to obtain disaster impact scope;
(4b) personnel's real time position:
Positional parameter is sent to locating base station by mobile terminal and positioning label in real time, positional parameter is sent to server by locating base station again, server receives positional parameter and it can be used as input, locates blending algorithm computing staff's real time position by the Wi-Fi/DR based on particle filter;
(4c) density of personnel:
Utilize stream of people's density calculation model that Predtechenski and Milinskii proposes by following formulae discovery:
D=Nf/WL............................. (1)
Wherein, D is people's flow density, and N represents number, draws by everyone's real time position statistics; F represents individual's horizontally-projected area, for directly presetting empirical value in the server; W represents stream of people's width, and namely the most Zuoren person of the stream of people and the real-time ultimate range of the rightest personnel, calculate according to everyone's real time position; L represents stream of people's length, and namely the most front personnel of the stream of people and the real-time ultimate range of last personnel, calculate according to everyone's real time position;
(4d) the average evacuation speed of personnel:
Judge personnel's type: if personnel's type is as the disabled, then the average evacuation speed V of the personnel that arrange0For 1.20-1.40m/s; If personnel's type is the general population, then calculate evacuation speed according to following sight:
When the general population is without, when passing through road under disaster scenarios it, personnel average evacuation speed V is by following formulae discovery:
V=112D4-38D3+434D2-217D+57………(2)
Wherein, V is the average evacuation speeds of personnel, and unit is m/min, D is people's flow density, calculates according to formula (1);
When the general population is without the average evacuation speed V of personnel when passing through door under disaster scenarios it1By following formulae discovery:
V1=V [1.17+0.13sin (6.03D-0.12)] ... ... .... (3)
Wherein, D is people's flow density, calculates according to formula (1);
As the personnel average evacuation speed V of the general population under disaster scenarios it2By following formulae discovery:
V2=V μ1..............................................(4)
Wherein, μ1Be experience factor, calculate according to following two kinds of scenes: by horizontal channel or by open wide door time, μ1By following formulae discovery:
μ1=1.49-0.36D...................................... (5)
Wherein, D is people's flow density, calculates according to formula (1);
Time downstairs, μ1It is set to empirical value 1.21;
(5) building navigation network data and be stored in server, described navigation network data are band power digraph G, G=<V ', E, W>, and wherein V ' is the set on summit in figure, and E is the set on limit, and W is the set of the power on each limit; The set V ' on summit and the set E on limit, according to the definition of indoor scene two-dimension vector map in spatial context, represents the road of indoor scene, with the joint of each road of vertex representation with limit; For each the limit of G, there is the power that a real number is called limit, the power on each limit is more than or equal to zero, and the more big expression of weights is crowded more serious, represents that the road from a node to another node direction does not exist or target node can not reach when weights are just infinite; The set W of the power on each limit is determined by following step:
(5a) utilizing analysis expert method, by two or more, expert defines weights respectively for each decision attribute, and described decision attribute is expressed by non-spatial context, and the weights of each decision attribute adopt exponential scale method scale;
(5b) for each decision attribute, the expert decision-making weights each expert provided are averaged, and get the comprehensive weights that the immediate scale with mean value is this decision attribute;If upper and lower two adjacent scales are identical with the difference of the mean value tried to achieve, then get the comprehensive weights that the less scale of variance is this decision attribute;
(5c) the every bar limit in digraph G is weighed for band, each decision attribute is set to the importance per-cent of this edge, respectively the importance per-cent of this edge is multiplied by the comprehensive weights of each decision attribute with it, the result i.e. weights on this limit that each product is added, the weights calculating every bar limit respectively finally obtain set W;
(6) server is by the Point matching of the navigation start position of step (3) and terminal position and band power digraph G, using band power digraph G, starting point S and terminal T as input, Dijkastra algorithm or A* algorithm is utilized to export the optimum path data between starting point S and terminal T;
(7) user preference that server receives according to step (3) determines navigate mode, with the form of map, voice or note, optimum path data is sent to locating base station, then is sent to mobile terminal and/or LED screen by locating base station;
(8) mobile terminal and/or LED screen show the optimum path data received and guide target to navigate;
(9) repeating step (4) is to step (8), until the positional information that mobile terminal sends is the terminal position that step (3) is arranged, navigation terminates.
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