CN106652440A - Method and apparatus for determining frequent activity area of vehicle - Google Patents
Method and apparatus for determining frequent activity area of vehicle Download PDFInfo
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- CN106652440A CN106652440A CN201510730921.8A CN201510730921A CN106652440A CN 106652440 A CN106652440 A CN 106652440A CN 201510730921 A CN201510730921 A CN 201510730921A CN 106652440 A CN106652440 A CN 106652440A
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- G—PHYSICS
- G08—SIGNALLING
- 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
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Abstract
The embodiment of the invention discloses a method and apparatus for determining the frequent activity area of a vehicle. The method is applied to an electronic device and comprises: acquiring each piece of position data of each vehicle, establishing a relation between each piece of position data and each node, establishing a complex network of the vehicle according to the distance between every two nodes, and determining each frequent activity area of the vehicle according to the degree of each node in the complex network. The method acquires the position data of each vehicle, establishes the complex network of the vehicle, accurately obtains the correlation between the nodes by means of the complex network so as to accurately determine the frequent activity area of each vehicle, thereby facilitating traffic flow forecast and control and effectively solving traffic congestion problems.
Description
Technical field
The present invention relates to technical field of data processing, the determination in the frequent activities region of more particularly to a kind of vehicle
Method and device.
Background technology
With the quickening of Urbanization in China, each big and medium-sized cities enter the period of motor vehicle high-speed growth,
Urban congestion situation becomes increasingly conspicuous, and how to alleviate congestion becomes the problem of a primary study.Gather around to alleviate
It is stifled the contact situation of vehicle to be predicted, taken appropriate measures prevention congestion according to the result of prediction.
In prior art when the contact situation to vehicle is predicted, it is proposed that one kind is based on public transport GPS numbers
According to public transport arrive at a station Forecasting Methodology, read the topological data of bus station in the method first, set up bus station
The topological relation of point；The real-time GPS data of public transit vehicle is received afterwards, and is obtained at set time intervals
Take and export in topological relation in the station of each circuit buses postpone, stand between delay and postpone to the next stop.
It can be seen from foregoing description, be in prior art for bus station GPS addresses in the case of
The topological relation of foundation, so as to the prediction for carrying out, but for other do not use the vehicle of fixed station, for example
Personal car etc., the place due to obtaining its Jing often activities, and the information in frequent activities region, cause nothing
Method realizes the prediction of vehicle contact situation, so as to solve the problems, such as traffic congestion.
The content of the invention
The embodiment of the invention discloses a kind of determination method and device in the frequent activities region of vehicle, to true
Determine the information in the frequent activities region of vehicle, realize the prediction of vehicle contact situation, solve asking for traffic congestion
Topic.
To reach above-mentioned purpose, the embodiment of the invention discloses a kind of determination side in the frequent activities region of vehicle
Method, is applied to electronic equipment, and the method includes：
For each vehicle, every position data of the vehicle is obtained；
The corresponding relation between every position data and each node is set up, according to the distance between each two node,
Set up the complex network of the vehicle；
According to the degree of each node in the complex network, each frequent activities region of the vehicle is determined.
Further, it is described according to the distance between each two node, set up the complex network bag of the vehicle
Include：
For the corresponding position data of each node, judge whether the node is little with the distance between other nodes
In the first distance threshold of setting；
If it is, connecting the node and described other nodes.
Further, the information of the acquisition time in the position data also comprising the position data, described
According to the distance between each two node, setting up the complex network of the vehicle includes：
For the acquisition time of the corresponding position data of each node, each node is carried out sequentially in time
Sequence；
Connect two neighboring node.
Further, the degree according to each node in the complex network, determine the vehicle each
Frequent activities region includes：
For each node, judge the degree of the node whether more than the amount threshold for setting；
If it is, using the node as the corresponding node in the position in frequent activities region；
In the corresponding node in position in frequent activities region, according to the corresponding every positional number of each node
According to judging that whether the distance between each two node is not more than the second distance threshold value of setting；
If it is, the corresponding position of two nodes is located in same frequent activities region, and otherwise, this two
The corresponding position of node is located in different frequent activities regions.
Further, it is described during the information of the acquisition time in the position data also comprising the position data
Method also includes：
For each frequent activities region, according to should frequent activities region the corresponding position of each node
The acquisition time of data, determine the property in the frequent activities region.
Further, the information of the acquisition time in the position data also comprising the position data, described
According to the distance between each two node, before setting up the complex network of the vehicle, methods described also includes：
For the acquisition time of the corresponding position data of each node, each node is carried out sequentially in time
Sequence；
For two neighboring node, judge whether the corresponding position data of two neighboring node is identical；
If it is, judging the difference of the acquisition time of the position data of the two neighboring node whether more than setting
Time threshold；
If not, one of node and its corresponding position data are deleted.
Further, obtaining every position data of the vehicle includes：
At set time intervals, the nothing on the vehicle that will be obtained by global position system GPS
The position data of line fidelity WiFi terminal, as the position data of the vehicle for obtaining.
A kind of determining device in the frequent activities region of vehicle is embodiments provided, electronics is applied to and is set
Standby, the device includes：
Acquisition module, for for each vehicle, obtaining every position data of the vehicle；
Module is set up, for setting up the corresponding relation between every position data and each node, according to each two
The distance between node, sets up the complex network of the vehicle；
Determining module, for according to the degree of each node in the complex network, determine the vehicle each
Frequent activities region.
Further, it is described to set up module, specifically for for the corresponding position data of each node, judging
Whether the distance between the node and other nodes are less than the first distance threshold for setting；If it is, connection
The node and described other nodes.
Further, the information of the acquisition time in the position data also comprising the position data, described to build
Formwork erection block, it is right sequentially in time specifically for for the acquisition time of the corresponding position data of each node
Each node is ranked up；Connect two neighboring node.
Further, the determining module, specifically for for each node, judge the node degree whether
More than the amount threshold of setting；If it is, the node is corresponding as the position in frequent activities region
Node；In the corresponding node in position in frequent activities region, according to the corresponding every position of each node
Data, judge whether the distance between each two node is not more than the second distance threshold value of setting；If it is,
Then the corresponding position of two nodes is located in same frequent activities region, otherwise, the corresponding position of two nodes
Setting in different frequent activities regions.
Further, when the information of the acquisition time in the position data also comprising the position data, institute
State determining module, be additionally operable to for each frequent activities region, according to should frequent activities region each
The acquisition time of the corresponding position data of node, determine the property in the frequent activities region.
Further, it is described during the information of the acquisition time in the position data also comprising the position data
Device also includes：
Filtering module, for being directed to the acquisition time of the corresponding position data of each node, sequentially in time
Each node is ranked up；For two neighboring node, the corresponding position data of two neighboring node is judged
It is whether identical；If it is, judging whether the difference of the acquisition time of the position data of the two neighboring node is big
In the time threshold of setting；If not, one of node and its corresponding position data are deleted.
Further, the acquisition module, specifically at set time intervals, being determined by the whole world
The position data of the Wireless Fidelity WiFi terminal on the vehicle that position system GPS is obtained, as acquisition
The vehicle position data.
Embodiments provide a kind of determination method and device in the frequent activities region of vehicle, the method
Electronic equipment is applied to, including：For each vehicle, every position data of the vehicle is obtained, set up every
Corresponding relation between bar position data and each node, according to the distance between each two node, sets up described
The complex network of vehicle, according to the degree of each node in the complex network, determines each frequency of the vehicle
Numerous zone of action.Due to for each vehicle obtaining its position data in embodiments of the present invention, and set up should
The complex network of vehicle, accurately obtains the incidence relation between node, such that it is able to standard by complex network
The frequent activities region of true determination each car, conveniently carries out the prediction and control of traffic flow, so as to have
The solution traffic jam issue of effect.
Description of the drawings
In order to be illustrated more clearly that the embodiment of the present invention or technical scheme of the prior art, below will be to implementing
Example or the accompanying drawing to be used needed for description of the prior art are briefly described, it should be apparent that, describe below
In accompanying drawing be only some embodiments of the present invention, for those of ordinary skill in the art, do not paying
On the premise of going out creative work, can be with according to these other accompanying drawings of accompanying drawings acquisition.
Fig. 1 is a kind of determination process in the frequent activities region of vehicle provided in an embodiment of the present invention；
Fig. 2 is the position data according to vehicle provided in an embodiment of the present invention, it is determined that vehicle complex network；
Fig. 3 is adjacency matrix schematic diagram provided in an embodiment of the present invention；
A kind of determination process in the frequent activities region of the vehicle in above-described embodiment that Fig. 4 is provided for the present invention；
Fig. 5 is the determination process in the frequent activities region of another vehicle provided in an embodiment of the present invention；
Fig. 6 is that a kind of determination apparatus structure in the frequent activities region of vehicle provided in an embodiment of the present invention is illustrated
Figure.
Specific embodiment
In order to accurately determine the frequent activities region of each vehicle, the prediction and control of traffic flow is conveniently carried out
System, effectively solves traffic jam issue, embodiments provides a kind of frequent activities region of vehicle
Determination method and device.
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clearly
Chu, it is fully described by, it is clear that described embodiment is only a part of embodiment of the invention, rather than
Whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art are not making creation
Property work under the premise of the every other embodiment that obtained, belong to the scope of protection of the invention.
If using each element of internal system as node, the relation between element is considered as connection, then be
System just constitutes a network, and such as nervous system can regard a large amount of neurocytes as and mutually be interconnected by nerve fiber
Connect the network to be formed, computer network can regard as computer by communication media for example optical cable, twisted-pair feeder,
The network that coaxial cable etc. is interconnected to form, similar also has electric power networks, social relation network, traffic
Network etc..Emphasize the structure of system and the research of the function exactly complex network from structural point analysis system
Thinking, except that the topological structure property research different from the past of these live networks for abstracting
Network, and node is numerous, therefore it is called complex network (Complex Network)
Complex network be one kind for describing nature and social sciences and engineering technology in close between respective nodes
The theory of connection relation.People unanimously think that complex network should include the implication of three aspects：First, it is complicated
Network is the true reflection of the topological structure of real complex system；Second, in complexity, complex network should
This is more higher than regular network and random network；3rd, complex network enables people to " complexity system easy to understand
Why complicated system is " this problem.Generally will with attractor, self similarity, worldlet, from group
Knit and be referred to as complex network with the network of some properties in uncalibrated visual servo or all properties.
The concept of complex network moderate is portray and weigh individual node characteristic most simple while being also most important
Concept, degree represents that the definition of the quantity on the side that node possesses, the i.e. degree of node is node connection
The number of other nodes.
The embodiment of the present invention is carried out based on complex network, determines the frequent activities region of vehicle.
Fig. 1 is a kind of determination process in the frequent activities region of vehicle provided in an embodiment of the present invention, the process
Comprise the following steps：
S101：For each vehicle, every position data of the vehicle is obtained.
Specifically, the position data of vehicle is obtained by global positioning system (GPS).Can ensure that really
The accuracy in fixed frequent activities region, can obtain at set time intervals in embodiments of the present invention
Every position data of each vehicle is taken, the corresponding time interval of each vehicle can be with identical, it is also possible to different.
In order to realize the acquisition of vehicle position data, the GPS location mould for being positioned can be installed on vehicle
Block, by the d GPS locating module every position data of vehicle is obtained.The position data can be specific Jing
Latitude information.
It is preferred that in one embodiment of the invention, in order to reduce the change to vehicle, the vehicle is obtained
Every position data include：
At set time intervals, the nothing on the vehicle that will be obtained by global position system GPS
The position data of line fidelity WiFi terminal, as the position data of the vehicle for obtaining.
Wireless Fidelity WiFi terminal on vehicle can be that WiFi terminal is arranged on vehicle.On vehicle
It can place WiFi terminal on certain position of vehicle to arrange WiFi terminal, or, on vehicle
The WiFi terminal that user carries with, the WiFi terminal can be mobile terminal, for example mobile phone, panel computer,
Net book, Ipad etc..
S102：The corresponding relation between every position data and each node is set up, according between each two node
Distance, set up the complex network of the vehicle.
Complex network is made up of the annexation between multiple nodes and node, in order to build the complexity of vehicle
Network, initially sets up the corresponding relation between every position data and each node, using every position data as
A node in the complex network.Then according to the distance between node, determine that the connection between node is closed
System, so as to set up the complex network of vehicle.
When complex network is set up, the maximum of a diameter of any two euclidean distance between node pair of the complex network,
The length on the side of two nodes of connection is referred to as the average path length of network, and the average path length is all sections
The meansigma methodss of point distance between, the average path length describes the separation degree between Node Contraction in Complex Networks.
In embodiments of the present invention according to the distance between two nodes, judge whether carried out between two nodes
Connection, so that it is determined that the complex network of vehicle.Due to the corresponding relation between node and position data, therefore
It is determined that between any two node apart from when, according to the corresponding position data of the node, determine two sections
The distance between point.
The diameter of known complex network, the average path length of complex network, and determine between each node
The method of degree, the process for setting up complex network belongs to prior art, in embodiments of the present invention to the complex web
The process of specifically setting up of network is not repeated.
S103：According to the degree of each node in the complex network, each frequent activities of the vehicle are determined
Region.
After complex network is set up, the degree of each node is it was determined that according to each node in the complex network
Degree, you can determine each frequent activities region of vehicle.
Fig. 2 is the position data according to vehicle provided in an embodiment of the present invention, it is determined that vehicle complex network,
It can be seen that the degree of some nodes is very big in the complex network, such as Fig. 2 interior joints 1 and and node 3 between
The line of connection is referred to as the degree of node, in Fig. 2 with node 1, node 2 ..., the line that is connected of node 6 it is unusual
It is many, therefore above-mentioned each node is unusual big, and spend larger node in the intensive region of lines,
There is interconnected relationship between node in lines close quarters, can be determined according to the lines close quarters
The frequent activities region of vehicle.By node 1, node 2 and the area encompassed of node 3 in specific such as Fig. 2,
And node 4, node 5 and the area encompassed of node 6, multiple nodes are included in the two regions, each section
The degree of point is all very big, and the lines in two regions are intensive, therefore two regions are defined as into vehicle
Frequent activities region.
Due to for each vehicle obtaining its position data in embodiments of the present invention, and set up answering for the vehicle
Miscellaneous network, by complex network the incidence relation between node is accurately obtained, such that it is able to accurately determination
The frequent activities region of each vehicle, conveniently carries out the prediction and control of traffic flow, so as to effectively solve
Traffic jam issue.
In one embodiment of the invention, it is described according to the distance between each two node, set up the car
Complex network include：
For the corresponding position data of each node, judge whether the node is little with the distance between other nodes
In the first distance threshold of setting；
If it is, connecting the node and described other nodes.
In the above-described embodiments, because position data can be specifically latitude and longitude information, therefore according to node
With the corresponding relation of position data, each two section can be determined according to the corresponding latitude and longitude information of each node
The distance between point.According to latitude and longitude information, determine that distance belongs to prior art, in embodiments of the present invention
The process is not repeated.
Latitude and longitude information is corresponding with physical location, therefore each physical location is relative with the node of complex network
Should, using latitude and longitude information and spherical distance computational methods, it may be determined that the distance in N number of node between any two,
Obtain distance matrix.By taking N number of node as an example, the building process of matrix of adjusting the distance is illustrated, by each node
Be numbered respectively node 1, node 2 ... node N, build node 1 to the row matrix of node N,
With the column matrix of a node 1 to node N, then the Distance matrix D of a N*N can be obtained, in distance matrix
The numerical value of each position D (i, j) is the distance between corresponding two node is and node j.
According to each distance value in the distance matrix and the relation of the first distance threshold of setting, it may be determined that right
The adjacency matrix answered, is also illustrated with above-mentioned example, by the way can be by the distance of a N*N
Matrix D, is converted to the adjacency matrix A of a N*N.Numerical value in the adjacency matrix is 0 or 1,0 expression correspondence
The distance between two nodes more than the first distance threshold of setting, then there is no company between two nodes
Relation is connect, 1 represents first distance threshold of the distance between corresponding two nodes less than setting, this two sections
There is annexation between point.In embodiments of the present invention first distance threshold can be set according to demand
It is fixed, for example first distance threshold can be set to 0.05 km, or other numerical value.
On the basis of above-described embodiment, in an alternative embodiment of the invention, the positional number of the vehicle of acquisition
According in can also include the position data acquisition the time information, when in the position data include the positional number
According to the acquisition time information when, to obtain and there may be company between the temporally adjacent corresponding node of position data
Relation is connect, shows the relation of the corresponding position of the node.Therefore, when in the position data also include the position
The information of the acquisition time of data is put, it is described according to the distance between each two node, set up the vehicle
Complex network includes：
For the acquisition time of the corresponding position data of each node, each node is carried out sequentially in time
Sequence；
Connect two neighboring node.
Following table for above-described embodiment provide each node is ranked up sequentially in time after result.
The acquisition time includes specific date and time, according to the acquisition temporal information, can be to positional number
According to being ranked up, there is corresponding relation between each position data and node.
Therefore it is determined that during distance matrix, the acquisition time of the corresponding position data of each node can be directed to,
Each node is ranked up sequentially in time, according to the result of sequence, determines the sequence number of each node,
According to the sequence number, distance matrix and the corresponding adjacency matrix of the distance matrix are determined.In embodiments of the invention
In, according to the mode in above-described embodiment according to, it is determined that in adjacency matrix after the numerical value of each position, also
The data of the corresponding position of adjacent company node can be set to 1, i.e., for adjacency matrix A, will abut against square
The numerical value of the position A (i, i+1) in battle array is set to 1, and Jia one by its corresponding degree for corresponding node.
Determined after adjacency matrix according to aforesaid way, for each node, it may be determined that each node correspondence
Degree, adjacency matrix schematic diagram as shown in Figure 3 occurs 1 according in the corresponding string of the node or a line
Quantity, it may be determined that the corresponding degree of the node.According to the corresponding degree of each node, vehicle can be set up
Complex network.
A kind of determination process in the frequent activities region of the vehicle in above-described embodiment that Fig. 4 is provided for the present invention,
The process is comprised the following steps：
S401：For each vehicle, every position data of the vehicle is obtained.
S402：The corresponding relation between every position data and each node is set up, it is corresponding for each node
The acquisition time of position data, each node is ranked up sequentially in time.
S403：Connect two neighboring node, and for each node, judge between the node and other nodes
Distance whether less than the first distance threshold of setting；If it is, carrying out step S404, otherwise, walked
Rapid S405.
S404：Connect the node and described other nodes.Step S406 is carried out afterwards.
S405：It is not connected to the node and described other nodes.
S406：According to the degree of each node in the complex network, each frequent activities of the vehicle are determined
Region.
It is described according to institute in an embodiment of the invention on the basis of the above embodiment of the present invention
The degree of each node in complex network is stated, determining each frequent activities region of the vehicle includes：
For each node, judge the degree of the node whether more than the amount threshold for setting；
If it is, using the node as the corresponding node in the position in frequent activities region；
In the corresponding node in position in frequent activities region, according to the corresponding every positional number of each node
According to judging that whether the distance between each two node is not more than the second distance threshold value of setting；
If it is, the corresponding position of two nodes is located in same frequent activities region, and otherwise, this two
The corresponding position of node is located in different frequent activities regions.
In order to judge whether node as the corresponding section in the position in frequent activities region in the embodiment of the present invention
Whether point, the amount threshold for arranging can be more than according to the degree of node and be judged that the amount threshold can be with root
It is configured according to demand, for example, can is 10 or 20 etc..
After being ranked up to node sequentially in time, there is annexation between adjacent node, i.e., such as
Really two nodes are adjacent, then the corresponding degree of two nodes Jia 1, if the distance between two nodes are less than setting
The first distance threshold, then the corresponding degree of two nodes Jia 1.Therefore each section can determine according to said process
The corresponding degree of point, such that it is able to judge whether can be corresponding as the position in frequent activities region using node
Node.
In position in determining frequent activities region during corresponding node, same frequent work is could also belong to
Node in dynamic region, because there is corresponding relation with position data in each node, therefore according between node
Distance, distance less than second distance threshold value the corresponding position of two nodes be located at same frequent activities region
In, otherwise, the corresponding position of two nodes is located in different frequent activities regions.
Further, in embodiments of the present invention, after each frequent activities region is determined, can be with root
According to the acquisition time of the corresponding position data of each node in the frequent activities region, the frequent activities are determined
The property in region.
If the acquisition time of the corresponding position data of most of node in the frequent activities region is working day
Daytime, then can determine the frequent activities region be working region；If big in the frequent activities region
The acquisition time of the corresponding position data of part of nodes is at 11 points in evening to morning 7, then can determine the frequent work
Dynamic region is house region；If the corresponding position data of most of node in the frequent activities region is obtained
The time is taken for weekend, then can determine the frequent activities region for public place of entertainment etc..
In order to ensure the accuracy in the frequent activities region for determining, it is ensured that the accuracy of follow-up traffic control,
In one embodiment of the present of invention, when the letter of the acquisition time in the position data also comprising the position data
Breath, it is described according to the distance between each two node, before setting up the complex network of the vehicle, the side
Method also includes：
For the acquisition time of the corresponding position data of each node, each node is carried out sequentially in time
Sequence；
For two neighboring node, judge whether the corresponding position data of two neighboring node is identical；
If it is, judging the difference of the acquisition time of the position data of the two neighboring node whether more than setting
Time threshold；
If not, one of node and its corresponding position data are deleted.
Because the position data of vehicle is obtained at set time intervals, when vehicle long-time is parked in together
During one position, such as in company, downstairs parking lot parks cars after going to work, or in community parking field after going home
Park cars, then the position data of the vehicle for obtaining all is identical, therefore after being ranked up to node,
May determine that whether the corresponding position data of two neighboring node is identical.Therefore the problem of acquisition precision, judges
Whether the corresponding position data of two neighboring node is identical, can judge that the distance between two nodes are
It is no to be less than a smaller given threshold, such as 10 meters etc., if the distance between two nodes are less than one
Individual smaller given threshold, then it is considered that the corresponding position data of two nodes is identical.
If whether the difference of the acquisition time of the further position data according to the two neighboring node is more than
The time threshold of setting, it is determined whether delete one of node and the corresponding position data of the node.Should
Time threshold can be set according to demand, for example, the time threshold is set to into the time interval, or slightly
Micro- and big numerical value of the time interval etc., such as time interval are 5 minutes, then can be by the time threshold
Value is set to 5 point half.After one of node and the node corresponding position data is deleted, by its it
The sequence number of node afterwards re-starts adjustment, using the continuous node of sequence number as adjacent node.
Fig. 5 is the determination process in the frequent activities region of another vehicle provided in an embodiment of the present invention, the mistake
Journey is comprised the following steps：
S501：For each vehicle, every position data of the vehicle is obtained, wherein in the position data also
The information of the acquisition time comprising the position data.
S502：The corresponding relation between every position data and each node is set up, it is corresponding for each node
The acquisition time of position data, each node is ranked up sequentially in time.
S503：For two neighboring node, judge whether the corresponding position data of two neighboring node is identical,
If it is, carrying out step S504, otherwise, S506 is carried out.
S504：Judge the difference of acquisition time of the position data of the two neighboring node whether more than setting
Time threshold, if it is, carrying out step S506, otherwise, carries out step S505.
S505：One of node and its corresponding position data are deleted, and by the node after it
Sequence number re-starts adjustment, using the continuous node of sequence number as adjacent node.
S506：Connect two neighboring node, and for each node, judge between the node and other nodes
Distance whether less than the first distance threshold of setting；If it is, carrying out step S507, otherwise, walked
Rapid S508.
S507：Connect the node and described other nodes.Afterwards, step S509 is carried out.
S508：It is not connected to the node and described other nodes.
S509：According to the degree of each node in the complex network, each frequent activities of the vehicle are determined
Region.
Due to for each vehicle obtaining its position data in embodiments of the present invention, and set up answering for the vehicle
Miscellaneous network, by complex network the incidence relation between node is accurately obtained, such that it is able to accurately determination
The frequent activities region of each vehicle, conveniently carries out the prediction and control of traffic flow, so as to effectively solve
Traffic jam issue.
Fig. 6 is that a kind of determination apparatus structure in the frequent activities region of vehicle provided in an embodiment of the present invention is illustrated
Figure, the device is applied to electronic equipment, and the device includes：
Acquisition module 61, for for each vehicle, obtaining every position data of the vehicle；
Module 62 is set up, for setting up the corresponding relation between every position data and each node, according to per two
The distance between individual node, sets up the complex network of the vehicle；
Determining module 63, for according to the degree of each node in the complex network, determining the every of the vehicle
Individual frequent activities region.
It is described to set up module 62, specifically for for the corresponding position data of each node, judge the node with
Whether the distance between other nodes are less than the first distance threshold for setting；If it is, connect the node and
Described other nodes.
The information of the acquisition time in the position data also comprising the position data, it is described to set up module 62,
Specifically for for the acquisition time of the corresponding position data of each node, sequentially in time to each node
It is ranked up；Connect two neighboring node.
The determining module 63, specifically for for each node, judging the degree of the node whether more than setting
Amount threshold；If it is, using the node as the corresponding node in the position in frequent activities region；
In the corresponding node in position in frequent activities region, according to the corresponding every position data of each node, sentence
Whether the distance between disconnected each two node is not more than the second distance threshold value of setting；If it is, two sections
The corresponding position of point is located in same frequent activities region, and otherwise, the corresponding position of two nodes is located at not
In same frequent activities region.
When the information of the acquisition time in the position data also comprising the position data, the determining module
63, be additionally operable to for each frequent activities region, according to should frequent activities region each node correspondence
Position data the acquisition time, determine the property in the frequent activities region.
During the information of the acquisition time in the position data also comprising the position data, described device also includes：
Filtering module 64, it is suitable according to the time for for the acquisition time of the corresponding position data of each node
Ordered pair each node is ranked up；For two neighboring node, the corresponding positional number of two neighboring node is judged
According to whether identical；If it is, whether judging the difference of the acquisition time of the position data of the two neighboring node
More than the time threshold of setting；If not, one of node and its corresponding position data are deleted.
The acquisition module 61, specifically at set time intervals, will be by global position system GPS
The position data of the Wireless Fidelity WiFi terminal on the vehicle for obtaining, as the vehicle for obtaining
Position data.
Embodiments provide a kind of determination method and device in the frequent activities region of vehicle, the method
Electronic equipment is applied to, including：For each vehicle, every position data of the vehicle is obtained, set up every
Corresponding relation between bar position data and each node, according to the distance between each two node, sets up described
The complex network of vehicle, according to the degree of each node in the complex network, determines each frequency of the vehicle
Numerous zone of action.Due to for each vehicle obtaining its position data in embodiments of the present invention, and set up should
The complex network of vehicle, accurately obtains the incidence relation between node, such that it is able to standard by complex network
The frequent activities region of true determination each car, conveniently carries out the prediction and control of traffic flow, so as to have
The solution traffic jam issue of effect.
For systems/devices embodiment, because it is substantially similar to embodiment of the method, so the ratio of description
Relatively simple, related part is illustrated referring to the part of embodiment of the method.
It should be noted that herein, such as first and second or the like relational terms be used merely to by
One entity or operation make a distinction with another entity or operation, and not necessarily require or imply these
There is any this actual relation or order between entity or operation.And, term " including ", "comprising"
Or its any other variant is intended to including for nonexcludability, so that including a series of mistake of key elements
Journey, method, article or equipment not only include those key elements, but also including be not expressly set out other
Key element, or also include the key element intrinsic for this process, method, article or equipment.Do not having
In the case of more restrictions, the key element limited by sentence "including a ...", it is not excluded that wanting including described
Also there is other identical element in process, method, article or the equipment of element.
One of ordinary skill in the art will appreciate that realizing all or part of step in said method embodiment
Program be can be by instruct the hardware of correlation to complete, described program can be stored in computer-readable
In taking storage medium, the storage medium for obtaining designated herein, such as：ROM/RAM, magnetic disc, CD etc..
Presently preferred embodiments of the present invention is the foregoing is only, protection scope of the present invention is not intended to limit.
All any modification, equivalent substitution and improvements made within the spirit and principles in the present invention etc., are all contained in
In protection scope of the present invention.
Claims (14)
1. the determination method in the frequent activities region of a kind of vehicle, it is characterised in that be applied to electronic equipment,
The method includes：
For each vehicle, every position data of the vehicle is obtained；
The corresponding relation between every position data and each node is set up, according to the distance between each two node,
Set up the complex network of the vehicle；
According to the degree of each node in the complex network, each frequent activities region of the vehicle is determined.
2. method according to claim 1, it is characterised in that between the node according to each two
Distance, setting up the complex network of the vehicle includes：
For the corresponding position data of each node, judge whether the node is little with the distance between other nodes
In the first distance threshold of setting；
If it is, connecting the node and described other nodes.
3. method according to claim 2, it is characterised in that the position is also included in the position data
The information of the acquisition time of data is put, it is described according to the distance between each two node, set up the vehicle
Complex network includes：
For the acquisition time of the corresponding position data of each node, each node is carried out sequentially in time
Sequence；
Connect two neighboring node.
4. the method according to any one of claim 1-3, it is characterised in that described according to the complex web
The degree of each node in network, determining each frequent activities region of the vehicle includes：
For each node, judge the degree of the node whether more than the amount threshold for setting；
If it is, using the node as the corresponding node in the position in frequent activities region；
In the corresponding node in position in frequent activities region, according to the corresponding every positional number of each node
According to judging that whether the distance between each two node is not more than the second distance threshold value of setting；
If it is, the corresponding position of two nodes is located in same frequent activities region, and otherwise, this two
The corresponding position of node is located in different frequent activities regions.
5. method according to claim 4, it is characterised in that the position is also included in the position data
When putting the information of acquisition time of data, methods described also includes：
For each frequent activities region, according to should frequent activities region the corresponding position of each node
The acquisition time of data, determine the property in the frequent activities region.
6. the method according to any one of claim 1-3, it is characterised in that also wrap in the position data
The information of the acquisition time containing the position data, it is described according to the distance between each two node, set up described
Before the complex network of vehicle, methods described also includes：
For the acquisition time of the corresponding position data of each node, each node is carried out sequentially in time
Sequence；
For two neighboring node, judge whether the corresponding position data of two neighboring node is identical；
If it is, judging the difference of the acquisition time of the position data of the two neighboring node whether more than setting
Time threshold；
If not, one of node and its corresponding position data are deleted.
7. method according to claim 1, it is characterised in that obtain every position data of the vehicle
Including：
At set time intervals, the nothing on the vehicle that will be obtained by global position system GPS
The position data of line fidelity WiFi terminal, as the position data of the vehicle for obtaining.
8. the determining device in the frequent activities region of a kind of vehicle, it is characterised in that be applied to electronic equipment,
The device includes：
Acquisition module, for for each vehicle, obtaining every position data of the vehicle；
Module is set up, for setting up the corresponding relation between every position data and each node, according to each two
The distance between node, sets up the complex network of the vehicle；
Determining module, for according to the degree of each node in the complex network, determine the vehicle each
Frequent activities region.
9. device according to claim 8, it is characterised in that described to set up module, specifically for pin
To the corresponding position data of each node, judge the distance between the node and other nodes whether less than setting
The first distance threshold；If it is, connecting the node and described other nodes.
10. device according to claim 9, it is characterised in that the position is also included in the position data
The information of the acquisition time of data is put, it is described to set up module, specifically for for the corresponding position of each node
The acquisition time of data, each node is ranked up sequentially in time；Connect two neighboring node.
11. devices according to any one of claim 8-10, it is characterised in that the determining module, tool
Whether body is used to be directed to each node, judge the degree of the node more than the amount threshold for setting；If it is,
Using the node as the corresponding node in the position in frequent activities region；Position pair in frequent activities region
In the node answered, according to the corresponding every position data of each node, the distance between each two node is judged
Whether the second distance threshold value of setting is not more than；If it is, the corresponding position of two nodes is located at same frequency
In numerous zone of action, otherwise, the corresponding position of two nodes is located in different frequent activities regions.
12. devices according to claim 11, it is characterised in that when also including in the position data
During the information of the acquisition time of the position data, the determining module is additionally operable to for each frequent activities area
Domain, according to should frequent activities region the corresponding position data of each node the acquisition time, it is determined that should
The property in frequent activities region.
13. devices according to any one of claim 8-10, it is characterised in that in the position data also
During the information of the acquisition time comprising the position data, described device also includes：
Filtering module, for being directed to the acquisition time of the corresponding position data of each node, sequentially in time
Each node is ranked up；For two neighboring node, the corresponding position data of two neighboring node is judged
It is whether identical；If it is, judging whether the difference of the acquisition time of the position data of the two neighboring node is big
In the time threshold of setting；If not, one of node and its corresponding position data are deleted.
14. devices according to claim 8, it is characterised in that the acquisition module, specifically for pressing
According to the time interval of setting, the Wireless Fidelity on the vehicle that will be obtained by global position system GPS
The position data of WiFi terminal, as the position data of the vehicle for obtaining.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109783597A (en) * | 2019-01-29 | 2019-05-21 | 江苏满运软件科技有限公司 | Determine method, apparatus, the electronic equipment, storage medium of the fixed position of driver |
| CN110021161A (en) * | 2018-01-09 | 2019-07-16 | 株式会社日立制作所 | A kind of prediction technique and system of traffic direction |
| CN110969275A (en) * | 2018-09-30 | 2020-04-07 | 杭州海康威视数字技术股份有限公司 | Traffic flow prediction method and device, readable storage medium and electronic device |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH1173591A (en) * | 1997-08-29 | 1999-03-16 | Matsushita Electric Ind Co Ltd | Route information calculating device |
| CN104217579A (en) * | 2013-07-23 | 2014-12-17 | 同济大学 | Method for searching critical road sections of traffic networks on basis of redundancy of road section sub-networks |
| CN104330089A (en) * | 2014-11-17 | 2015-02-04 | 东北大学 | Map matching method by use of historical GPS data |
| CN104464344A (en) * | 2014-11-07 | 2015-03-25 | 湖北大学 | Vehicle driving path prediction method and system |
| CN104850604A (en) * | 2015-05-04 | 2015-08-19 | 华中科技大学 | Tensor-based user track mining method |
| CN104952248A (en) * | 2015-06-08 | 2015-09-30 | 浙江大学 | Automobile convergence predicting method based on Euclidean space |
| CN104966129A (en) * | 2015-06-08 | 2015-10-07 | 浙江大学 | Method for separating vehicle running track |
-
2015
- 2015-10-30 CN CN201510730921.8A patent/CN106652440B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH1173591A (en) * | 1997-08-29 | 1999-03-16 | Matsushita Electric Ind Co Ltd | Route information calculating device |
| CN104217579A (en) * | 2013-07-23 | 2014-12-17 | 同济大学 | Method for searching critical road sections of traffic networks on basis of redundancy of road section sub-networks |
| CN104464344A (en) * | 2014-11-07 | 2015-03-25 | 湖北大学 | Vehicle driving path prediction method and system |
| CN104330089A (en) * | 2014-11-17 | 2015-02-04 | 东北大学 | Map matching method by use of historical GPS data |
| CN104850604A (en) * | 2015-05-04 | 2015-08-19 | 华中科技大学 | Tensor-based user track mining method |
| CN104952248A (en) * | 2015-06-08 | 2015-09-30 | 浙江大学 | Automobile convergence predicting method based on Euclidean space |
| CN104966129A (en) * | 2015-06-08 | 2015-10-07 | 浙江大学 | Method for separating vehicle running track |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110021161A (en) * | 2018-01-09 | 2019-07-16 | 株式会社日立制作所 | A kind of prediction technique and system of traffic direction |
| CN110969275A (en) * | 2018-09-30 | 2020-04-07 | 杭州海康威视数字技术股份有限公司 | Traffic flow prediction method and device, readable storage medium and electronic device |
| CN110969275B (en) * | 2018-09-30 | 2024-01-23 | 杭州海康威视数字技术股份有限公司 | Traffic flow prediction method and device, readable storage medium and electronic equipment |
| CN109783597A (en) * | 2019-01-29 | 2019-05-21 | 江苏满运软件科技有限公司 | Determine method, apparatus, the electronic equipment, storage medium of the fixed position of driver |
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| Publication number | Publication date |
|---|---|
| CN106652440B (en) | 2019-05-21 |
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