CN109166308A - A kind of aggregation characteristic method for visualizing of the traffic flow based on space constraint distance - Google Patents
A kind of aggregation characteristic method for visualizing of the traffic flow based on space constraint distance Download PDFInfo
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- CN109166308A CN109166308A CN201810878022.6A CN201810878022A CN109166308A CN 109166308 A CN109166308 A CN 109166308A CN 201810878022 A CN201810878022 A CN 201810878022A CN 109166308 A CN109166308 A CN 109166308A
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- G—PHYSICS
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- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
- G08G1/0133—Traffic data processing for classifying traffic situation
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Abstract
The invention discloses a kind of aggregation characteristic method for visualizing of traffic flow based on space constraint distance, carry out statistics calculating to distance between all transport nodes two-by-two contacted there are traffic trip in research area first；Secondly, research intra zone traffic node is carried out complex network convergence factor value according to given space constraint distance range (being denoted as R) and is calculated；Different space constraint distance range R values is set again, calculates the convergence factor value of each node；Finally, carrying out spatial visualization displaying to transport node by ArcGIS cuclear density algorithm.The present invention provides decision-making foundation by the efficient visual presentation to traffic connection aggregation situation under the linking analysis realization different spaces scale between tool transport node for urban planning and traffic administration.
Description
Technical field
The present invention relates to urban planning and urban transportation technical field, especially a kind of traffic based on space constraint distance
The aggregation characteristic method for visualizing of stream.
Background technique
With the fast development of current big data technology, the acquisition and application of telecommunication flow information have obtained tremendous development, produce
Higher social economic value is given birth to.Wherein, traffic stream aggregation situation is in city and traffic programme in research and analysis region
Important content, and have very significant practical significance to resident living and social production.For example, which is judged in city
Between a little bus stations the aggregation situation of the volume of the flow of passengers can for urban public bus lines reappraise and design provide the most directly according to
According to the passenger flow aggregation situation visually dissolved between public bicycles website then can provide foundation for the scheduling of public bicycles.Always
For it, traffic flow space clustering situation analysis current social economic development and informationization technology research and development in have it is important
Theory and practice value.
In general, traffic flow is made of 2 fundamentals: being contacted between node and node.Specifically, node can
To be interpreted as bus station, high-speed rail website etc..Survey region is either divided into a certain size grid, then by each grid
Regard that node, such as city have been partitioned into the identical grid of size as, then counts the visitor that gets on the bus of taxi in each grid
It flows and passenger flow situation of getting off, to realize the connection signature analysis for hiring out passenger flow to city.In a sense, taxi does not have
One more specific node space facility, grid division can then construct the node of " opposite " and " virtual ".Node
Between connection be primarily referred to as the practical volume of the flow of passengers etc. that node and node generate, such as the volume of the flow of passengers between bus station.So, such as
What goes the aggregation situation of research traffic flow using connection between node and node.It is readily apparent that if between these nodes
Connection it is closer, then illustrate that traffic flow is about assembled between these nodes.So, if it is possible to those are associated with closely point and is looked for
Out, then by space density algorithm (common cuclear density algorithm in such as GIS-Geographic Information System) it shows, is then easy to allow
Researcher quickly develops the aggregation situation of traffic flow.
Currently, Complex Networks Theory is the most important theories and method for solving the problems, such as to contact between node and node.Its
In, convergence factor index in Complex Networks Theory is mainly used between the node for describing to be connected in network with same node also mutually
For the degree of adjacent node.Convergence factor describes the probability mutually recognized two-by-two between any three users or intensity, reflection
User recognizes the tightness degree of relationship in whole network.It is contacted tightly between egress it can be seen that convergence factor may determine that
Close degree.
However, there is problems in practical applications in the prior art: 1. existing convergence factor calculated result reflection
Be the also degree of adjacent node each other between the node being connected with same node.That is, if the node that A node is connected has
B, C and D, wherein the space length of A and B, C are close, and the space length of A and D is far.In the convergence factor for calculating A node
When, it can take into account the relationship between B, C and D.But in reality, it only can take into account and be closer between node (B and C) with A
Aggregation situation, for example, public bicycles ride most of situation be distance shorter trip, only have least a portion of people that can ride
Farther out, therefore when considering the whole incidence relation between node, should not consider when calculating each node and those distances
Farther away node.To sum up, problem 1 is primarily referred to as: if the space scale in research area is larger, conclusion and actual demand
There is some difference, does not meet the traffic trip analysis of smaller scale especially.2. current node rendezvous coefficient be difficult directly into
Row cuclear density spatial visualization.Because the height of convergence factor value reflects the association situation between interdependent node, and each section
The interdependent node of point may have very big difference on space scale, i.e. the interdependent node of some nodes is simply present in office
Portion, and the interdependent node of certain nodes is more than and is present in part, is also all distributed in the overall situation.This have that is, logic coker
The selected radius parameter value of density can not unite.However, we are it is seen that assemble data on earth by problem 1 and 2
Be calculated according to what scale be actually do not know.Finally, different scale space research is very heavy in reality
The proposition wanted.It then becomes necessary to which provide a kind of new method to solve that convergence factor under different scale scene calculates asks
Topic, so that user be allowed rapidly to distinguish that the aggregation characteristic of different spaces scale lower node is distributed.
Summary of the invention
There is provided the technical problem to be solved by the present invention is to overcome the deficiencies in the prior art it is a kind of based on space constraint away from
From traffic flow aggregation characteristic method for visualizing, the present invention can be different by realizing to the linking analysis between transport node
The efficient visual presentation of traffic connection aggregation situation, provides decision-making foundation for urban planning and traffic administration under space scale.
The present invention uses following technical scheme to solve above-mentioned technical problem:
A kind of aggregation characteristic method for visualizing of the traffic flow based on space constraint distance proposed according to the present invention, including it is following
Step:
Step 1 carries out statistics calculating to distance between all transport nodes two-by-two contacted there are traffic trip in research area；
Step 2 presets different space constraint distance range R, for different R, respectively to research intra zone traffic node
The convergence factor value for carrying out complex network node calculates；The convergence factor of complex network node is carried out to research intra zone traffic node
It is specific as follows to be worth the process calculated:
All transport nodes in step 2.1, traversal area to be studied, the node in traversal is denoted as V every time；
Step 2.2 filters out all transport nodes with V distance in range R, and acquired results are denoted as set P；
V and P are constructed to form a complex network data set W, and are calculated this point V's according to Complex Networks Theory by step 2.3
Convergence factor value；
Step 3, according to the convergence factor value of the calculated each transport node of step 2, by ArcGIS cuclear density algorithm to friendship
Logical node carries out spatial visualization displaying.
As a kind of aggregation characteristic method for visualizing of the traffic flow based on space constraint distance of the present invention into one
Prioritization scheme is walked, distance is that resulting space length is calculated using shortest path first in step 1, rather than air line distance.
As a kind of aggregation characteristic method for visualizing of the traffic flow based on space constraint distance of the present invention into one
Prioritization scheme is walked, the data format of W is the data format suitable for Pajek Complex Networks Analysis software.
As a kind of aggregation characteristic method for visualizing of the traffic flow based on space constraint distance of the present invention into one
Prioritization scheme is walked, it is every that each cuclear density, which calculates Population field used, in the ArcGIS cuclear density algorithm in step 3
The convergence factor value of a transport node.
As a kind of aggregation characteristic method for visualizing of the traffic flow based on space constraint distance of the present invention into one
Prioritization scheme is walked, it is to carry out aggregation system that each cuclear density, which calculates set radius r, in the ArcGIS cuclear density algorithm in step 3
Some value in number space constraint distance range R set when calculating.
The invention adopts the above technical scheme compared with prior art, has following technical effect that
(1) present invention is a kind of aggregation characteristic method for visualizing of traffic flow based on space constraint distance, can by this method
To find out the convergence factor index value of adaptable complex network node according to different spaces dimensional analysis requirement；Meanwhile it can be with
It analyzes and requires according to different spaces, adaptable space cuclear density is carried out to the convergence factor of complex network node and visualizes exhibition
Show；
(2) Visualization result meaning of the invention are as follows: under certain space dimensional constraints, the connection of complex network local nodes
Aggregation situation；If visually dissolving a series of result figure according to different spaces scale, acquired results can help people fast
The fast geographical complexity network node that solves assembles situation is how to change as space scale changes.
Detailed description of the invention
Fig. 1 is overall flow schematic diagram of the invention.
Fig. 2 is transport node and its connection distribution schematic diagram.
Fig. 3 is R value when being 0~700 meter, the corresponding set P interior joint composition schematic diagram of each node；Wherein, (a)
It is (d) time (c) to traverse set P when C node (b) to traverse set P when B node to traverse set P when A node
Set P when D node is gone through, set P when (e) being traversal E node.
Fig. 4 is R value when being 0~1500 meter, the corresponding set P interior joint composition schematic diagram of each node；Wherein,
(a) for traversal A node when set P, (b) for traversal B node when set P, (c) for traversal C node when set P, (d) be
Set P when D node is traversed, set P when (e) being traversal E node.
Fig. 5 is suitable for data format schematic diagram required for Complex Networks Analysis.
Fig. 6 is parameter selection schematic diagram when ArcGIS carries out cuclear density.
Fig. 7 be R value be 0~700 meter when, visualize achievement schematic diagram.
Fig. 8 be R value be 0~1500 meter when, visualize achievement schematic diagram.
Specific embodiment
Technical solution of the present invention is described in further detail with reference to the accompanying drawing:
Technical solution proposed by the invention mainly considers not only to want when existing Complex Networks Theory calculates convergence factor
In view of network topology structure, it is also contemplated that spatial relation constraint, and a kind of traffic flow based on space constraint distance proposed
Aggregation characteristic method for visualizing.It provides a kind of new multi-spatial scale analysis for the visualization of traffic flow space clustering feature
Method can substantially improve the deficiencies in the prior art.
Method of the invention is as follows:
Step 1, referring to attached drawing 1, first to research area in it is all there are traffic trip connection transport nodes two-by-two between distance
Carry out statistics calculating.Referring to attached drawing 2, trip stream of the telecommunication flow information between certain city public bicycle website in example,
5 transport nodes, respectively A, B, C, D, E are contained altogether.Wherein, there is the node pair of traffic connection are as follows:
A and B, A and C, A and D, B and C, B and D, C and D and D and E.
Therefore only need to count the distance between above-mentioned transport node, specific statistical value are as follows:
A and B is 600 meters, and A and C are 550 meters, and A and D are 1500 meters, and B and C are 570 meters, and B and D are 1200 meters, and C and D are 1300
Rice, D and E are 350 meters.
Wherein, distance statistics among the above are to calculate resulting space length according to shortest path first, and non-space is straight
Linear distance.
Step 2, to research intra zone traffic node, according to given space constraint distance range (being denoted as R) calculate complex network
The convergence factor value of node, the value of this case R are 0~700 meter；
All transport nodes in step 2.1, traversal area to be studied, the node in traversal is denoted as V every time；
Step 2.2 filters out all transport nodes with V distance in 0~700 meter, and acquired results are denoted as set P.Referring to attached
(b) in set P, Fig. 3 when (a) in Fig. 3, Fig. 3 is traversal A node is (c) in set P, Fig. 3 when traversing B node
It is when traversing E node to traverse (e) in the set P, Fig. 3 when (d) in the set P, Fig. 3 when C node is traversal D node
Set P.The node set P for needing to consider when traversing A node in this example is { B, C }, needs to consider when traversing B node
Node set P be { A, C }, it is { A, B } that the node set P that considers is needed when traversing C node, needs to examine when traversing D node
The node set P considered is { E }, and the node set P for needing to consider when traversing E node is { D }.
V and P are constructed to form a complex network data set W, and are calculated this according to Complex Networks Theory by step 2.3
The convergence factor index value of point.Wherein, the node set that W is included when traversing A node in this example is { A, B, C }, traverses B
The node set that W is included when node is { A, B, C }, and the node set that W includes when traversing C node is { A, B, C }, traversal D section
The node set that W includes when point is { D, E }, and the node set that W includes when traversing E node is { E, D }.It is this reality referring to attached drawing 5
The data format of example W, it is suitable for a kind of common data forms of the Complex Networks Analysis software such as Pajek.
The different space constraint distance range R value of step 3, setting, is respectively calculated according to step 2.R value in this example
Another value range be 0~1500 meter.According to this referring to attached drawing 4, (a) in Fig. 4 is set P when traversing A node, figure
(c) in set P, Fig. 4 when (b) in 4 is traversal B node is that (d) in set P, Fig. 4 when traversing C node is traversal D
(e) in set P, Fig. 4 when node is set P when traversing E node.It needs to consider when traversing A node in this example
Node set P be { B, C, D, E }, it is { A, C, D, E } that the node set P that considers is needed when traversing B node, traverses C node
When to need the node set P that considers be { A, B, D, E }, the node set P for needing to consider when traversing D node be A, B, C,
E }, the node set P for needing to consider when traversing E node is { A, B, C, D }.
The node set that W is included when traversing each node in this example is { A, B, C, D, E }.
Step 4 carries out spatial visualization displaying to transport node by ArcGIS cuclear density algorithm.Referring to attached drawing 6, specifically
Using ArcGIS carry out cuclear density calculating, Population field used be each transport node convergence factor value, for into
Some value in row convergence factor space constraint distance range R set when calculating.For this example, need to carry out 2 cores
Density calculates, and radius r takes 700 meters and 1500 meters respectively.
Referring to attached drawing 7, when to be R value be 0~700 meter, traffic flow cuclear density visualizes achievement schematic diagram.Referring to attached drawing 8,
When for R value being 0~1500 meter, traffic flow cuclear density visualizes achievement schematic diagram.
Comparison diagram 7 and Fig. 8, it can be found that: when R value is 0~700 meter, the traffic current density cutting in area will be studied
At two parts, i.e., A, B, C form a team forms a team with D, E.The reason is that the distance between A, B, C be less than 700 meters, between D, E away from
From again smaller than 700 meters, and the distance of A, B, C to D, E are more than 700 meters.Under the influence of this space constraint distance, necessarily to grind
Study carefully area and forms 2 traffic flow Nesting Zones obviously cut.When R value is 0~1500 meter, then make the cutting region in Fig. 7
It is coupled.Because the convergence factor calculating of individual node considers in research area under the influence of this space constraint distance
All node conditions, rather than local nodes.
The above content is a further detailed description of the present invention in conjunction with specific preferred embodiments, and it cannot be said that
Specific implementation of the invention is only limited to these instructions.For those of ordinary skill in the art to which the present invention belongs, exist
Under the premise of not departing from present inventive concept, several simple deductions or substitution can also be made, all shall be regarded as belonging to of the invention
Protection scope.
Claims (5)
1. a kind of aggregation characteristic method for visualizing of the traffic flow based on space constraint distance, which is characterized in that including following step
It is rapid:
Step 1 carries out statistics calculating to distance between all transport nodes two-by-two contacted there are traffic trip in research area；
Step 2 presets different space constraint distance range R, for different R, respectively to research intra zone traffic node
The convergence factor value for carrying out complex network node calculates；The convergence factor of complex network node is carried out to research intra zone traffic node
It is specific as follows to be worth the process calculated:
All transport nodes in step 2.1, traversal area to be studied, the node in traversal is denoted as V every time；
Step 2.2 filters out all transport nodes with V distance in range R, and acquired results are denoted as set P；
V and P are constructed to form a complex network data set W, and are calculated this point V's according to Complex Networks Theory by step 2.3
Convergence factor value；
Step 3, according to the convergence factor value of the calculated each transport node of step 2, by ArcGIS cuclear density algorithm to friendship
Logical node carries out spatial visualization displaying.
2. a kind of aggregation characteristic method for visualizing of traffic flow based on space constraint distance according to claim 1,
It is characterized in that, distance is that resulting space length is calculated using shortest path first in step 1, rather than air line distance.
3. a kind of aggregation characteristic method for visualizing of traffic flow based on space constraint distance according to claim 1,
It is characterized in that, the data format of W is the data format suitable for Pajek Complex Networks Analysis software.
4. a kind of aggregation characteristic method for visualizing of traffic flow based on space constraint distance according to claim 1,
It is characterized in that, it is each that each cuclear density, which calculates Population field used, in the ArcGIS cuclear density algorithm in step 3
The convergence factor value of transport node.
5. a kind of aggregation characteristic method for visualizing of traffic flow based on space constraint distance according to claim 1,
It is characterized in that, it is to carry out convergence factor that each cuclear density, which calculates set radius r, in the ArcGIS cuclear density algorithm in step 3
Some value in set space constraint distance range R when calculating.
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| CN101046919A (en) * | 2006-10-12 | 2007-10-03 | 华南理工大学 | Visual evaluating method for urban traffic system state based on traffic flow phase character istic and its application |
| CN107134141A (en) * | 2017-06-30 | 2017-09-05 | 北京航空航天大学 | Consider the expression of large-scale road network space-time traffic behavior and the analysis method of spatial structure characteristic |
| CN107423897A (en) * | 2017-07-20 | 2017-12-01 | 青岛大学 | A kind of method that public traffic network is evaluated using public transport archives |
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Address after: 210019 Building B3, No. 1, Yunlongshan Road, Jianye District, Nanjing, Jiangsu Patentee after: Jiangsu urban planning and Design Institute Co.,Ltd. Address before: 210036 Jiangsu Jianshe Building, No. 88, Caochangmen Street, Gulou District, Nanjing, Jiangsu Patentee before: JIANGSU INSTITUTE OF URBAN PLANNING AND DESIGN |