CN104281709A - Method and system for generating traffic information tiled map - Google Patents

Abstract

The invention discloses a method and a system for generating a traffic information tiled map. The method comprises the following steps: acquiring road network information data and traffic information data; determining a relation between a sensing device and a road section; reading a base map of a target area map; normalizing the current traffic information data; dividing the map with the zoom level of n into a plurality of rectangular blocks, calculating the updating complexity of the current traffic information data in each rectangular block, and adjusting the updating complexity of the current traffic information data in each rectangular block to be identical to obtain a self-adaptive rectangular block division result; allocating different self-adaptive rectangular blocks onto different computer nodes to calculate the current traffic information data, generating a map block coating, rendering the map block coating to the corresponding base map, and generating a map block including the current traffic information data; merging all map blocks to generate the tiled map. By adopting the technical scheme, the time for generating the tiled map can be reduced, and the efficiency can be improved.

Description

The generation method and system of transport information tile map

Technical field

The present invention relates to areas of information technology, particularly relate to a kind of generation method and system of transport information tile map.

Background technology

Current, contacting of network map and people's Working Life is more and more tightr, and the function application in daily life of its circuit query, vehicle mounted guidance etc. is especially extensive.ITS (Intelligent Transportation System, intelligent transportation system) is the traffic control system that newly-developed gets up.GIS (Geographic Information System, Geographic Information System), GPS (Global Positioning System, GPS) theory and technology will incorporate in this system, together for ITS provides digital Platform.Based on the ITS of GIS, GPS, real-time dynamic information service can be provided for road users, improve trip mode, also can provide control reference information for road management person, effectively improve the traffic capacity and the security of existing road.

At present, dynamic traffic service information is generated, mainly through GIS server and the traffic information server cooperating providing traffic information tile map, basis GIS server receives user's request, and to the traffic information tile figure (transport information tile figure) of traffic information server application certain proportion chi, longitude and latitude scope, each tile figure equal and opposite in direction of transport information, after obtaining feedback, traffic information tile figure is superposed with the basic GIS map in this locality (i.e. the base map of map), obtains transport information map and feed back to user's display; The up-to-date real-time road data of traffic information server timing acquisition, carry out road conditions and play up, and generate traffic information tile figure and store.

But, in current technology, due to each tile figure equal and opposite in direction divided, and amount of traffic information in each tile figure is not all the same, amount of traffic information in some tile figure is very large, need longer Time Calculation to determine, the amount of traffic information in some tile figure is less, and the calculative time is also less, and after the amount of traffic information in each tile figure calculated, could superpose with the basic GIS map in this locality reoffers to user, and expend time in longer, efficiency comparison is low.

Summary of the invention

In view of this, the invention provides a kind of generation method and system of transport information tile map, in order to reduce the time generating tile map, raise the efficiency.

For achieving the above object, the invention provides following technical scheme:

A generation method for transport information tile map, comprising:

Obtain road network information data, create the road network information table corresponding with described road network information data; Described road network information data comprise the geographical location information in each section;

Obtain traffic information data, sensing equipment information and described traffic information data are stored into sensing equipment information table; Described sensing equipment information comprises the geographical location information of sensing equipment;

The geographical location information in the geographical location information of described sensing equipment and section is carried out matching primitives, determines the incidence relation in described sensing equipment and section;

The base map of target area map is read from Distribution GIS service platform server;

Calculate the current traffic information data in the current collection period of described sensing equipment, normalized is done to described current traffic information data;

Be that the map of n level is divided into multiple rectangle block by level of zoom, calculate the update complexity of described current traffic information data in each rectangle block, between described rectangle block, when the update complexity of described current traffic information data is different, adjust the size of described rectangle block, make the update complexity of described current traffic information data in each rectangle block equal, obtain self-adaptation rectangle block division result;

The base map of described target area map is divided into the base map block corresponding with described self-adaptation rectangle block division result, different described self-adaptation rectangle blocks is dispensed to the calculating different computer nodes carrying out described current traffic information data in described self-adaptation rectangle block, generates the map block coating comprising described current traffic information data;

Described map block coating is played up the map base map to correspondence, generates the map block comprising described current traffic information data;

The map block that all computer nodes generate is reconsolidated, generates the tile map comprising described current traffic information data.

Preferably, described road network information data are obtained from described Distribution GIS service platform, in the HBASE database of Hadoop platform, create the road network information table corresponding with described road network information data, described Hadoop platform is built on the server of described Distribution GIS service platform.

Preferably, obtain described traffic information data by described sensing equipment, described sensing equipment comprises: ground induction coil, radar, camera and video camera.

Preferably, described sensing equipment information comprises:

The numbering of described sensing equipment, type, title, geographic position, collection direction and gather the type of described traffic information data.

Preferably, described sensing equipment information and described traffic information data are stored into sensing equipment information table before, also comprise:

Described sensing equipment information table is created in the HBASE database of Hadoop platform.

Preferably, the described geographical location information by the geographical location information of described sensing equipment and section carries out matching primitives, determines the incidence relation in described sensing equipment and section, comprising:

Obtain the geographical location information of described sensing equipment;

The alternative section be associated with described sensing equipment is searched from described road network information table;

In alternative section, determine and the section that described sensing equipment is associated.

Preferably, also comprise:

Described tile map is divided into the rectangular tile map of formed objects, is kept in HBASE database, described rectangular tile map comprises described current traffic information data.

A generation system for transport information tile map, comprising:

First acquisition module, for obtaining road network information data, creates the road network information table corresponding with described road network information data; Described road network information data comprise the geographical location information in each section;

Second acquisition module, for obtaining traffic information data, is stored into sensing equipment information table by sensing equipment information and described traffic information data; Described sensing equipment information comprises the geographical location information of sensing equipment;

First computing module, for the geographical location information of the geographical location information of described sensing equipment and section is carried out matching primitives, determines the incidence relation in described sensing equipment and section;

3rd acquisition module, for reading the base map of target area map from Distribution GIS service platform server;

Second computing module, for calculating the current traffic information data in the current collection period of described sensing equipment, makes normalized to described current traffic information data;

Self-adaptation rectangle block generation module, for being that the map of n level is divided into multiple rectangle block by level of zoom, calculate the update complexity of described current traffic information data in each rectangle block, between described rectangle block, when the update complexity of described current traffic information data is different, adjust the size of described rectangle block, make the update complexity of described current traffic information data in each rectangle block equal, obtain self-adaptation rectangle block division result;

Map block coating generation module, for the base map of described target area map being divided into the base map block corresponding with described self-adaptation rectangle block division result, different described self-adaptation rectangle blocks is dispensed to the calculating different computer nodes carrying out described current traffic information data in described self-adaptation rectangle block, generates the map block coating comprising described current traffic information data;

Map block generation module, for described map block coating being played up the map base map to correspondence, generates the map block comprising described current traffic information data;

Tile map generation module, for being reconsolidated by the map block that all computer nodes generate, generates the tile map comprising described current traffic information data.

Preferably, also comprise:

Sensing equipment information table creation module, for creating described sensing equipment information table in the HBASE database of Hadoop platform.

Preferably, also comprise:

Rule tile map generation module, for described tile map being divided into the rectangular tile map of formed objects, be kept in HBASE database, described rectangular tile map comprises described current traffic information data.

Known via above-mentioned technical scheme, compared with prior art, the invention provides a kind of generation method and system of transport information tile map.Adopt technical scheme provided by the invention, be that the map of N level is divided into multiple rectangle block by level of zoom, calculate the update complexity of described current traffic information data in each rectangle block, between described rectangle block, when the update complexity of described current traffic information data is different, adjust the size of described rectangle block, make the update complexity of described current traffic information data in each rectangle block equal, obtain self-adaptation rectangle block division result, now, the complexity of the current traffic information Data Update in each self-adaptation rectangle block is equal, can computing time of current traffic information data in each rectangle block of efficient balance, the overall time of the current traffic information data calculating that all rectangle blocks are completed in respective block reduces, in addition, different described self-adaptation rectangle blocks is dispensed to the calculating different computer nodes carrying out current traffic information data in described self-adaptation rectangle block, generate the map block coating comprising described current traffic information data, due to separate computations, the efficiency of calculating can be improved, reduce computing time, then, described map block coating is played up the map base map to correspondence, generate the map block comprising described current traffic information data, the map block that all computer nodes generate is reconsolidated, generate the tile map comprising described current traffic information data.Therefore, adopt technical scheme provided by the invention, effectively can reduce the time generating tile map, raise the efficiency.

Accompanying drawing explanation

In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, be briefly described to the accompanying drawing used required in embodiment or description of the prior art below, apparently, accompanying drawing in the following describes is only embodiments of the invention, for those of ordinary skill in the art, under the prerequisite not paying creative work, other accompanying drawing can also be obtained according to the accompanying drawing provided.

The process flow diagram of the generation method of a kind of transport information tile map that Fig. 1 provides for the embodiment of the present invention;

The structural drawing of the generation system of a kind of transport information tile map that Fig. 2 provides for the embodiment of the present invention.

Embodiment

Below in conjunction with the accompanying drawing in the embodiment of the present invention, be clearly and completely described the technical scheme in the embodiment of the present invention, obviously, described embodiment is only the present invention's part embodiment, instead of whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art, not making the every other embodiment obtained under creative work prerequisite, belong to the scope of protection of the invention.

For enabling above-mentioned purpose of the present invention, feature and advantage become apparent more, and below in conjunction with the drawings and specific embodiments, the present invention is further detailed explanation.

Embodiment

Refer to Fig. 1, the process flow diagram of the generation method of a kind of transport information tile map that Fig. 1 provides for the embodiment of the present invention.As shown in Figure 1, the method comprises:

Step S101, obtains road network information data, creates the road network information table corresponding with described road network information data;

Concrete, obtain described road network information data from GIS (Geographic Information System, Geographic Information System) service platform, described road network information data comprise the geographical location information in each section; In the HBASE database of Hadoop platform, create the road network information table corresponding with described road network information data, described Hadoop platform is built on the server of described Distribution GIS service platform.Described road network information table comprises: section is numbered, section title, section the beginning and the end longitude and latitude, road section length and section industrial grade.The whole road network of appointed area (such as Xihu District of Hangzhou City) is converted into road network information table, and each section in region has unique section numbering.

Step S102, obtains traffic information data, sensing equipment information and described traffic information data is stored into sensing equipment information table; Described sensing equipment information comprises the geographical location information of sensing equipment;

Concrete, described sensing equipment information and described traffic information data are stored into sensing equipment information table before, also comprise: in the HBASE database of Hadoop platform, create described sensing equipment information table.Described sensing equipment information table comprises: device numbering, device type, device name, device location (longitude and latitude), equipment gathers direction and (comprises 1: from the east to the west, 2: from west to east, 3: from south to north, 4: from north to south), traffic parameter type is gathered.Each equipment has unique device numbering.

Concrete, obtain described traffic information data by described sensing equipment, described sensing equipment comprises: ground induction coil, radar, camera and video camera.Described sensing equipment information comprises: the numbering of described sensing equipment, type, title, geographic position, collection direction and gather the type of described traffic information data.

Further, set forth with the traffic flow information data instance in traffic information data.Traffic flow information data are obtained by the flow analysis algorithms of each sensing equipment self.The sensing equipment type that the present invention relates to and traffic flow data account form as follows:

Ground induction coil: when vehicle passing detection region, under the effect of electromagnetic induction, in traffic detector, electric current can rise by great-jump-forward, the trigger recording instrument when this electric current exceedes the threshold values of specifying, realize vehicle and the detection by the time, the traffic flow parameter of acquisition is set to: wherein FVN represents that sensor type is ground induction coil, P represents GPS (the Global Positioning System of sensor, GPS) position < longitude l, latitude g>, V represents the current road segment traffic parameter collected, the present embodiment is traffic flow parameter, and D represents wagon flow direction, sensor collection point, and t represents the time of parameter acquisition; Ground induction coil calculates the time complexity upgrading the magnitude of traffic flow and is designated as OFVN;

Radar gathers: utilize radar linear frequency modulation know-why, road pavement launched microwave, by carrying out the real-time digitized processing analysis of high speed, inspection vehicle flow to echoed signal, the contactless traffic detector of the traffic essential informations such as occupation rate, speed and vehicle, obtains traffic parameter and is set to: wherein RAD represents that sensor type is radar, P represents the GPS location < longitude l of sensor, latitude g>, V represents the current road segment traffic parameter collected, the present embodiment is traffic flow parameter, D represents wagon flow direction, sensor collection point, and t represents the time of parameter acquisition; Radar collection calculates the time complexity upgrading the magnitude of traffic flow and is designated as ORAD;

Bayonet socket gathers: carry out video capture to each vehicle of current road segment of passing through, by technological means such as Car license recognition according to the statistical vehicle flowrate such as track, period, vehicle, average speed and space headway etc., the traffic parameter of acquisition is set to: wherein EAY represents that sensor type is video card jaws equipment, P represents the GPS location < longitude l of sensor, latitude g>, V represents the current road segment traffic parameter collected, the present embodiment is traffic flow parameter, D represents wagon flow direction, sensor collection point, and t represents the time of parameter acquisition; Bayonet socket collection calculates the time complexity upgrading the magnitude of traffic flow and is designated as OEAY;

Video acquisition: gather the video data on road section by video capture device, obtained the data on flows of road by intelligent means such as pattern-recognitions, the traffic parameter of acquisition is set to: wherein Video representative sensor type is video capture device, P represents the GPS location < longitude l of sensor, latitude g>, V represents the current road segment traffic parameter collected, the present embodiment is traffic flow parameter, D represents wagon flow direction, sensor collection point, and t represents the time of parameter acquisition.Video acquisition calculates the time complexity upgrading the magnitude of traffic flow and is designated as OVIDEO.

Step S103, carries out matching primitives by the geographical location information in the geographical location information of described sensing equipment and section, determines the incidence relation in described sensing equipment and section;

Concrete, described step S103 comprises:

A, obtain the geographical location information of described sensing equipment;

B, from described road network information table, search the alternative section be associated with described sensing equipment;

Concrete, first calculate the error radius of described sensing equipment.Such as, the variance of system is met for the stochastic error of video camera (video acquisition), covariance matrix model is:

$P=\left[\begin{array}{cc}{\text{\&sigma;}}_x^2& {\mathrm{\&sigma;}}_{\mathrm{xy}}\\ {\mathrm{\&sigma;}}_{\mathrm{yx}}& {\mathrm{\&sigma;}}_y^2\end{array}\right]$

Wherein σ _x, σ _ythe standard deviation of sensor measurement errors, the variance of sensor measurement errors, the covariance of sensor measurement errors, then error ellipse ε _eformula is as follows:

$\mathrm{\&alpha;}=\sqrt{\frac{({\mathrm{\&sigma;}}_x^2+{\mathrm{\&sigma;}}_y^2+\sqrt{{({\mathrm{\&sigma;}}_x^2-{\mathrm{\&sigma;}}_y^2)}^2+4{\mathrm{\&sigma;}}_{\mathrm{xy}}^2})}{2}}$

$b=\sqrt{\frac{({\mathrm{\&sigma;}}_x^2+{\mathrm{\&sigma;}}_y^2-\sqrt{{({\mathrm{\&sigma;}}_x^2-{\mathrm{\&sigma;}}_y^2)}^2+4{\mathrm{\&sigma;}}_{\mathrm{xy}}^2})}{2}}$

$\mathrm{\&phi;}=\frac{\mathrm{\&pi;}}{2}-\frac{1}{2}\mathrm{\&theta;}\arctan \left(\frac{2{\mathrm{\&sigma;}}_{\mathrm{xy}}^2}{{\mathrm{\&sigma;}}_x^2-{\mathrm{\&sigma;}}_y^2}\right)$

Wherein α is oval major semi-axis, and b is oval minor semi-axis, and φ is transverse orientation and direct north angle.

Then, centered by camera position, error ellipse ε will be dropped on _esection in region is all labeled as alternative section.

C, in alternative section, to determine and the section that described sensing equipment is associated.

Concrete, suppose error ellipse ε _ebe respectively with the intersection point in alternative section: (x ₁, y ₁), (x ₂, y ₂), then with the straight-line equation by intersection point be:

$\left\{\begin{array}{c}\mathrm{ax}+\mathrm{by}+c=0\\ k=\frac{y_2-y_1}{x_2-x_1}\end{array}\right.$ Wherein a=1, $b=\frac{1}{k},c=-x_1+\frac{1}{k}\&times;y_1$ Calculate the air line distance of video camera to each alternative section:

$d_{i,l}\text{=}\frac{a\&times;\mathrm{dev}\_{\mathrm{lon}}_i+b\&times;\mathrm{dev}\_{\mathrm{lat}}_i+c}{\sqrt{a^{+}+b^2}}$ Obtain the section blk_idi be associated with video camera:

blk_id _i＝argmin{d _j,l}。

Step S104, reads the base map of target area map from GIS service Platform Server;

Step S105, calculates the current traffic information data in the current collection period of described sensing equipment, makes normalized to described current traffic information data;

Concrete, set forth with the traffic flow information data instance in traffic information data.

Described sensing equipment is at current collection period, and a namely current collection period acquires n traffic flow data, then the section flow in a collection period is designated as: Q _s, the traffic parameter of other type can also be calculated, as section average velocity is designated as: V _s, section average occupancy is designated as: O _s:

Section flow Q _s:

Section average velocity V _s:

Section average occupancy O _s:

The data unit gathered due to different sensors is different with the order of magnitude, adopts mean difference method to be normalized data:

$y_v=|\frac{\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{V}_{\mathrm{si}}}{n}-V_{\mathrm{si}}|/\frac{1}{n}\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}|\frac{\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{V}_{\mathrm{si}}}{n}-V_{\mathrm{si}}|$

$y_Q=|\frac{\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{Q}_{\mathrm{si}}}{n}-Q_{\mathrm{si}}|/\frac{1}{n}\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}|\frac{\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{Q}_{\mathrm{si}}}{n}-Q_{\mathrm{si}}|$

$y_O=|\frac{\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{O}_{\mathrm{si}}}{n}-O_{\mathrm{si}}|/\frac{1}{n}\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}|\frac{\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{O}_{\mathrm{si}}}{n}-O_{\mathrm{si}}|$

Wherein y _v, y _q, y _orepresent the section average velocity after normalization respectively, section flow, section average occupancy.In the present embodiment, traffic flow data is uploaded in the sensing equipment information table in HBase, comprising: sensor name, sensor number, and the positional information of sensor (GPS), normalization traffic parameter.

Step S106, be that the map of n level is divided into multiple rectangle block by level of zoom, calculate the update complexity of described current traffic information data in each rectangle block, between described rectangle block, when the update complexity of described current traffic information data is different, adjust the size of described rectangle block, make the update complexity of described current traffic information data in each rectangle block equal, obtain self-adaptation rectangle block division result;

Concrete, still set forth with the traffic flow information data instance in traffic information data.

Calculate the update complexity O (Bi) of traffic flow information data in each rectangle block Bi:

(1) the map point level of n-th (n ∈ [1, N], the quantity of the level of zoom that N will provide for GIS service platform) rank is divided into y block, is vertically divided into x block, then whole region is divided into xy rectangle block, shown in following form 1:

Table 1:

Rectangle block B _ibe designated as <B_ _idi, (V _i, H _i), (V _i+1, H _i+1) >;

(2) rectangle block B is added up _ithe kind of interior sensor and quantity, be designated as wherein, m is sensor type: 1 represents ground induction coil, and 2 represent radar, and 3 represent bayonet socket, and 4 represent video acquisition, and i represents rectangle region block number;

Calculate B _iinterior all section { blk_id _i, determination methods is section blk_id _imid point (x _mi, y _mi) whether be positioned at rectangle block B _iin;

$x_{\mathrm{mi}}=\frac{1}{2}(\mathrm{sblk}\_{\mathrm{lon}}_i+\mathrm{eblk}\_{\mathrm{lon}}_i)$

$y_{\mathrm{mi}}=\frac{1}{2}(\mathrm{sblk}\_{\mathrm{lat}}_i+\mathrm{eblk}\_{\mathrm{lat}}_i)$

V _i≤x _mi≤V _i+1,H _i≤y _mi≤H _i+1

Determine allly to be distributed in rectangle block B _iinterior all corresponding device { dev_id _j;

The kind of the sensor in statistics rectangle block Bi and quantity

$N_i^m=\underset{\{\mathrm{dev}\_{\mathrm{id}}_j\}}{\mathrm{\&Sigma;}}\mathrm{\&delta;}(\mathrm{dev}\_{\mathrm{type}}_j=m)$

Wherein, $\mathrm{\&delta;}(x=x_0)=\left\{\begin{array}{c}1,x=x_0\\ 0,x\&NotEqual;x_0\end{array}\right..$

(3) time complexity calculating the magnitude of traffic flow of Bi is designated as

$O_i^n\left(B_i\right)=\mathrm{\&Sigma;}(N_i^1{O}_{\mathrm{FVN}}+N_i^2{O}_{\mathrm{RAD}}+N_i^3{O}_{\mathrm{BAY}}+N_i^4{O}_{\mathrm{VIDO}})$

(4) time complexity average and the variance of the map magnitude of traffic flow of renewal n-th grade is calculated:

${\mathrm{\&mu;}}_{\mathrm{xy}}^n=\frac{\underset{i=1}{\overset{\mathrm{xy}}{\mathrm{\&Sigma;}}}{O}_i^n\left(B_i\right)}{\mathrm{xy}},$

${\mathrm{\&sigma;}}_{\mathrm{xy}}^n=\frac{1}{\mathrm{xy}}\sqrt{\underset{i=1}{\overset{\mathrm{xy}}{\mathrm{\&Sigma;}}}{(O_i^n\left(B_i\right)-{\mathrm{\&mu;}}_{\mathrm{xy}}^n)}^2}$

(5) Vi and Hi is adjusted in the following manner:

$V_i\&LeftArrow;\mathrm{Vi}+\mathrm{\&alpha;}\frac{\&PartialD;}{\&PartialD;V_i}{\mathrm{\&mu;}}_{\mathrm{xy}}^n+\mathrm{\&beta;}\frac{\&PartialD;}{\&PartialD;V_i}{O}_{\mathrm{xy}}^n,$

$H_i\&LeftArrow;\mathrm{Hi}+\mathrm{\&alpha;}\frac{\&PartialD;}{\&PartialD;H_i}{\mathrm{\&mu;}}_{\mathrm{xy}}^n+\mathrm{\&beta;}\frac{\&PartialD;}{\&PartialD;H_i}{O}_{\mathrm{xy}}^n,$

Wherein α and β is respectively the study intensity of n-th grade of map magnitude of traffic flow time complexity average and variance;

(6) (1), (2), (3) step is repeated, until Vi and Hi convergence:

|V _i-V _i+1|≤ε _target

|H _i-H _i+1|≤ε _target

Wherein ε _targetfor the convergence threshold preset, optionally, be generally 1.0e ^-3.

Finally, make the update complexity of described current traffic information data in each rectangle block equal, obtain self-adaptation rectangle block division result.

Step S107, the base map of described target area map is divided into the base map block corresponding with described self-adaptation rectangle block division result, different described self-adaptation rectangle blocks is dispensed to the calculating different computer nodes carrying out described current traffic information data in described self-adaptation rectangle block, generates the map block coating comprising described current traffic information data;

Concrete, still set forth with the traffic flow information data instance in traffic information data.According to the self-adaptation rectangle block division result of step S106, map base map is divided into the base map block corresponding with self-adaptation rectangle block according to level, and base map block is designated as: <bMap_ _idi, bMap _i>; Adopt the Map-Reduce mechanism of Hadoop platform by the B_id of self-adaptation rectangle block Bi _ikey-value pair is divided into the self-adaptation rectangle block Bi comprising corresponding traffic parameter n=1,2,3,4, N; By base map block bMap _ibMap_id _iwith base map block bMap _ibe divided into key-value pair n=1,2,3,4, N.The Map mechanism of Hadoop is according to bMap_id _iand B_id _ithe different computer nodes different self-adaptation rectangle blocks being dispensed to Hadoop platform complete the calculating to traffic flow information data, generate the map block layer comprising traffic flow information data.

Step S108, plays up the map base map to correspondence by described map block coating, generates the map block comprising described current traffic information data;

Concrete, described map block coating is played up to the map base map corresponding with described map block coating, generate the map block comprising described current traffic information data.

Step S109, reconsolidates the map block that all computer nodes generate, and generates the tile map comprising described current traffic information data.

Adopt the technical scheme that above-described embodiment provides, be that the map of N level is divided into multiple rectangle block by level of zoom, calculate the update complexity of described current traffic information data in each rectangle block, between described rectangle block, when the update complexity of described current traffic information data is different, adjust the size of described rectangle block, make the update complexity of described current traffic information data in each rectangle block equal, obtain self-adaptation rectangle block division result, now, the complexity of the current traffic information Data Update in each self-adaptation rectangle block is equal, can computing time of current traffic information data in each rectangle block of efficient balance, the overall time of the current traffic information data calculating that all rectangle blocks are completed in respective block reduces, in addition, different described self-adaptation rectangle blocks is dispensed to the calculating different computer nodes carrying out current traffic information data in described self-adaptation rectangle block, generate the map block coating comprising described current traffic information data, due to separate computations, the efficiency of calculating can be improved, reduce computing time, then, described map block coating is played up the map base map to correspondence, generate the map block comprising described current traffic information data, the map block that all computer nodes generate is reconsolidated, generate the tile map comprising described current traffic information data.Therefore, adopt technical scheme provided by the invention, effectively can reduce the time generating tile map, raise the efficiency.

In addition, (optional owing to different described self-adaptation rectangle blocks to be dispensed to the calculating different computer nodes carrying out current traffic information data in described self-adaptation rectangle block, the present invention adopts the Distributed Computing Platform based on Hadoop), namely height concurrency ground calculates the transport information on each tile figure, under computing time restrictive condition, multiple traffic information data can be calculated simultaneously.

Further, the technical scheme that above-described embodiment provides, also comprises:

Described tile map is divided into the rectangular tile map of formed objects, is kept in HBASE database, described rectangular tile map comprises described current traffic information data.

Further, the technical scheme that above-described embodiment provides, also comprises:

Described rectangular tile map is upgraded every Preset Time.

In order to more comprehensively set forth technical scheme provided by the invention, the invention provides a kind of generation system of transport information tile map.

Refer to Fig. 2, the structural drawing of the generation system of a kind of transport information tile map that Fig. 2 provides for the embodiment of the present invention.As shown in Figure 2, this system comprises:

First acquisition module 201, for obtaining road network information data, creates the road network information table corresponding with described road network information data; Described road network information data comprise the geographical location information in each section;

Second acquisition module 202, for obtaining traffic information data, is stored into sensing equipment information table by sensing equipment information and described traffic information data; Described sensing equipment information comprises the geographical location information of sensing equipment;

First computing module 203, for the geographical location information of the geographical location information of described sensing equipment and section is carried out matching primitives, determines the incidence relation in described sensing equipment and section;

3rd acquisition module 204, for reading the base map of target area map from Distribution GIS service platform server;

Second computing module 205, for calculating the current traffic information data in the current collection period of described sensing equipment, makes normalized to described current traffic information data;

Self-adaptation rectangle block generation module 206, for being that the map of n level is divided into multiple rectangle block by level of zoom, calculate the update complexity of described current traffic information data in each rectangle block, between described rectangle block, when the update complexity of described current traffic information data is different, adjust the size of described rectangle block, make the update complexity of described current traffic information data in each rectangle block equal, obtain self-adaptation rectangle block division result;

Map block coating generation module 207, for the base map of described target area map being divided into the base map block corresponding with described self-adaptation rectangle block division result, different described self-adaptation rectangle blocks is dispensed to the calculating different computer nodes carrying out described current traffic information data in described self-adaptation rectangle block, generates the map block coating comprising described current traffic information data;

Map block generation module 208, for described map block coating being played up the map base map to correspondence, generates the map block comprising described current traffic information data;

Tile map generation module 209, for being reconsolidated by the map block that all computer nodes generate, generates the tile map comprising described current traffic information data.

In order to optimize technical scheme provided by the invention further, the generation system of the transport information tile map that the embodiment of the present invention provides, also comprises:

Sensing equipment information table creation module, for creating described sensing equipment information table in the HBASE database of Hadoop platform;

Rule tile map generation module, for described tile map being divided into the rectangular tile map of formed objects, be kept in HBASE database, described rectangular tile map comprises described current traffic information data.

Known via above-mentioned technical scheme, compared with prior art, the invention provides a kind of generation method and system of transport information tile map.Adopt technical scheme provided by the invention, be that the map of N level is divided into multiple rectangle block by level of zoom, calculate the update complexity of described current traffic information data in each rectangle block, between described rectangle block, when the update complexity of described current traffic information data is different, adjust the size of described rectangle block, make the update complexity of described current traffic information data in each rectangle block equal, obtain self-adaptation rectangle block division result, now, the complexity of the current traffic information Data Update in each self-adaptation rectangle block is equal, can computing time of current traffic information data in each rectangle block of efficient balance, the overall time of the current traffic information data calculating that all rectangle blocks are completed in respective block reduces, in addition, different described self-adaptation rectangle blocks is dispensed to the calculating different computer nodes carrying out current traffic information data in described self-adaptation rectangle block, generate the map block coating comprising described current traffic information data, due to separate computations, the efficiency of calculating can be improved, reduce computing time, then, described map block coating is played up the map base map to correspondence, generate the map block comprising described current traffic information data, the map block that all computer nodes generate is reconsolidated, generate the tile map comprising described current traffic information data.Therefore, adopt technical scheme provided by the invention, effectively can reduce the time generating tile map, raise the efficiency.

Finally, also it should be noted that, in this article, the such as relational terms of first and second grades and so on is only used for an entity or operation to separate with another entity or operational zone, and not necessarily requires or imply the relation that there is any this reality between these entities or operation or sequentially.And, term " comprises ", " comprising " or its any other variant are intended to contain comprising of nonexcludability, thus make to comprise the process of a series of key element, method, article or equipment and not only comprise those key elements, but also comprise other key elements clearly do not listed, or also comprise by the intrinsic key element of this process, method, article or equipment.When not more restrictions, the key element limited by statement " comprising ... ", and be not precluded within process, method, article or the equipment comprising described key element and also there is other identical element.

In this instructions, each embodiment adopts the mode of going forward one by one to describe, and what each embodiment stressed is the difference with other embodiments, between each embodiment identical similar portion mutually see.For system disclosed in embodiment, because it corresponds to the method disclosed in Example, so description is fairly simple, relevant part illustrates see method part.

The software module that the method described in conjunction with embodiment disclosed herein or the step of algorithm can directly use hardware, processor to perform, or the combination of the two is implemented.Software module can be placed in the storage medium of other form any known in random access memory (RAM), internal memory, ROM (read-only memory) (ROM), electrically programmable ROM, electrically erasable ROM, register, hard disk, moveable magnetic disc, CD-ROM or technical field.

To the above-mentioned explanation of the disclosed embodiments, professional and technical personnel in the field are realized or uses the present invention.To be apparent for those skilled in the art to the multiple amendment of these embodiments, General Principle as defined herein can without departing from the spirit or scope of the present invention, realize in other embodiments.Therefore, the present invention can not be restricted to these embodiments shown in this article, but will meet the widest scope consistent with principle disclosed herein and features of novelty.

Claims (10)

1. a generation method for transport information tile map, is characterized in that, comprising:

Obtain road network information data, create the road network information table corresponding with described road network information data; Described road network information data comprise the geographical location information in each section;

Obtain traffic information data, sensing equipment information and described traffic information data are stored into sensing equipment information table; Described sensing equipment information comprises the geographical location information of sensing equipment;

The geographical location information in the geographical location information of described sensing equipment and section is carried out matching primitives, determines the incidence relation in described sensing equipment and section;

The base map of target area map is read from Distribution GIS service platform server;

Calculate the current traffic information data in the current collection period of described sensing equipment, normalized is done to described current traffic information data;

Be that the map of n level is divided into multiple rectangle block by level of zoom, calculate the update complexity of described current traffic information data in each rectangle block, between described rectangle block, when the update complexity of described current traffic information data is different, adjust the size of described rectangle block, make the update complexity of described current traffic information data in each rectangle block equal, obtain self-adaptation rectangle block division result;

The base map of described target area map is divided into the base map block corresponding with described self-adaptation rectangle block division result, different described self-adaptation rectangle blocks is dispensed to the calculating different computer nodes carrying out described current traffic information data in described self-adaptation rectangle block, generates the map block coating comprising described current traffic information data;

Described map block coating is played up the map base map to correspondence, generates the map block comprising described current traffic information data;

The map block that all computer nodes generate is reconsolidated, generates the tile map comprising described current traffic information data.

2. method according to claim 1, it is characterized in that, described road network information data are obtained from described Distribution GIS service platform, in the HBASE database of Hadoop platform, create the road network information table corresponding with described road network information data, described Hadoop platform is built on the server of described Distribution GIS service platform.

3. method according to claim 1, is characterized in that, obtains described traffic information data by described sensing equipment, and described sensing equipment comprises: ground induction coil, radar, camera and video camera.

4. method according to claim 1, is characterized in that, described sensing equipment information comprises:

The numbering of described sensing equipment, type, title, geographic position, collection direction and gather the type of described traffic information data.

5. method according to claim 1, is characterized in that, described sensing equipment information and described traffic information data are stored into sensing equipment information table before, also comprise:

Described sensing equipment information table is created in the HBASE database of Hadoop platform.

6. method according to claim 1, is characterized in that, the described geographical location information by the geographical location information of described sensing equipment and section carries out matching primitives, determines the incidence relation in described sensing equipment and section, comprising:

Obtain the geographical location information of described sensing equipment;

The alternative section be associated with described sensing equipment is searched from described road network information table;

In alternative section, determine and the section that described sensing equipment is associated.

7. method according to claim 1, is characterized in that, also comprises:

Described tile map is divided into the rectangular tile map of formed objects, is kept in HBASE database, described rectangular tile map comprises described current traffic information data.

8. a generation system for transport information tile map, is characterized in that, comprising:

First acquisition module, for obtaining road network information data, creates the road network information table corresponding with described road network information data; Described road network information data comprise the geographical location information in each section;

Second acquisition module, for obtaining traffic information data, is stored into sensing equipment information table by sensing equipment information and described traffic information data; Described sensing equipment information comprises the geographical location information of sensing equipment;

First computing module, for the geographical location information of the geographical location information of described sensing equipment and section is carried out matching primitives, determines the incidence relation in described sensing equipment and section;

3rd acquisition module, for reading the base map of target area map from Distribution GIS service platform server;

Second computing module, for calculating the current traffic information data in the current collection period of described sensing equipment, makes normalized to described current traffic information data;

Self-adaptation rectangle block generation module, for being that the map of n level is divided into multiple rectangle block by level of zoom, calculate the update complexity of described current traffic information data in each rectangle block, between described rectangle block, when the update complexity of described current traffic information data is different, adjust the size of described rectangle block, make the update complexity of described current traffic information data in each rectangle block equal, obtain self-adaptation rectangle block division result;

Map block coating generation module, for the base map of described target area map being divided into the base map block corresponding with described self-adaptation rectangle block division result, different described self-adaptation rectangle blocks is dispensed to the calculating different computer nodes carrying out described current traffic information data in described self-adaptation rectangle block, generates the map block coating comprising described current traffic information data;

Map block generation module, for described map block coating being played up the map base map to correspondence, generates the map block comprising described current traffic information data;

Tile map generation module, for being reconsolidated by the map block that all computer nodes generate, generates the tile map comprising described current traffic information data.

9. system according to claim 8, is characterized in that, also comprises:

Sensing equipment information table creation module, for creating described sensing equipment information table in the HBASE database of Hadoop platform.

10. system according to claim 8, is characterized in that, also comprises:

Rule tile map generation module, for described tile map being divided into the rectangular tile map of formed objects, be kept in HBASE database, described rectangular tile map comprises described current traffic information data.