CN110111567B - Traffic control subarea division method and system based on modularity evaluation - Google Patents
Traffic control subarea division method and system based on modularity evaluation Download PDFInfo
- Publication number
- CN110111567B CN110111567B CN201910330745.7A CN201910330745A CN110111567B CN 110111567 B CN110111567 B CN 110111567B CN 201910330745 A CN201910330745 A CN 201910330745A CN 110111567 B CN110111567 B CN 110111567B
- Authority
- CN
- China
- Prior art keywords
- network
- sub
- modularity
- nodes
- area
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
-
- 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
- G08G1/0125—Traffic data processing
-
- 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
- G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
Abstract
A traffic control subarea division method and a system based on modularity evaluation relate to the field of traffic control, and the method comprises the following steps: an initial dividing step; calculating; judging a subregion; and (5) a step of repartitioning. The invention provides a traffic control subarea division system and method based on modularity evaluation based on overall efficiency of an urban road network after comprehensively analyzing the influence of various division principles on the division result of the traffic control subarea. Simulation experiments prove that the modularity is used as an index for measuring the strength of the network subareas after the subareas are divided, and if the strength of the subarea structure divided by the network is stronger, the dividing quality is better. Thus, optimal network subdivision may be obtained by maximizing modularity. The sub-area division evaluation index, namely the modularity, is used as a control parameter in the traffic control sub-area division process, so that the global optimization of the traffic control sub-area division can be ensured, and the calculation speed of a traffic control sub-area division algorithm is improved.
Description
Technical Field
The invention relates to a traffic control subarea division method for traffic control, and relates to the field of traffic control.
Background
Due to the correlation characteristic of traffic flow, a certain linkage mechanism is often shown among intersections of the regional road network, and the change of the traffic state of one intersection can be spread out like ripples, so that the whole road network is influenced. However, the coordination control of the whole area is often too complex, which cannot meet the requirements of traffic real-time performance and reliability, and cannot achieve a better coordination control effect. Therefore, when signal control is performed on a road network containing hundreds or even thousands of intersections, the road network is often divided into a plurality of mutually independent areas, each area contains 1 or a plurality of adjacent signal intersections, and such an area is called a "traffic control sub-area".
The control of the current urban large-scale road network is usually realized by dividing the road network, so that a complex large-scale control problem can be converted into a plurality of independent sub-road network control problems, and then the control can be coordinated and controlled by adopting a corresponding algorithm. Therefore, the general steps of the coordination control are usually to divide the sub-area first and then to perform the coordination control on the sub-area.
The subdivision is an important technology of the whole large road network area adaptive traffic signal control system, the subdivision quality of the whole large road network area adaptive traffic signal control system must be evaluated through the whole efficiency of an area road network, however, the subdivision cannot be evaluated before the control system is subdivided (the system and the implementation, the quality of the subdivision evaluation is afterwards oryzanol), and the evaluation must be carried out by searching for proper simplified theoretical parameters through a model method.
At present, the more popular signal lamp control system in the market generally adopts two modes for sub-zone division: one is a preset fixed type, such as the SCOOT system of siemens corporation, and traffic engineers conduct field investigation on intersections in a networking area for about 3 weeks, collect network information and traffic data, judge the relevance between intersections according to the economic benefits and traffic flow brought by coordinating intersections, and determine which intersections are in a sub-area. The other is based on dynamic partitioning of real-time traffic flow, such as a SCATS system. The system combines and sets a threshold merging or splitting subarea according to the correlation or the periodic similarity between intersections.
The common partitioning method is mainly based on the principles of similar periods, similar traffic flows, similar distances and the like, and the principles are mainly divided according to whether intersections in adjacent or small ranges can be combined or not, so that whether actual control is convenient or not and whether algorithm flow is simple or not are considered more. Therefore, the currently commonly used sub-area division evaluation indexes are limited to the evaluation of the local optimization effect after the sub-area division.
And the urban road network is an open and uncertain complex system, and the small-range coordination is difficult to make the global coordination optimal. Therefore, the method for dividing the traffic control subareas needs to start from the overall transportation efficiency and the stability of the strategy effect of the road network so as to ensure the control effect of the whole road network, and unfortunately, no related technology or research results appear.
Disclosure of Invention
The invention aims to solve the problem that the existing road network division cannot be started from the global transportation efficiency and the stability of the strategy effect, but only has poor local optimization effect, and provides a system and a method for dividing a traffic control subarea based on modularity evaluation.
A traffic control subregion partition method based on modularity evaluation is used for partitioning subregions in a traffic network, and is characterized by comprising the following steps:
an initial dividing step, namely acquiring the number M of intersections of the road network, and recording n nodes in the network structure as a set C: { C1,C2,...,CnAnd dividing sub-areas corresponding to the road network one by one according to the fact that each sub-area comprises a node to obtain a set S: { S1,S2,...,SN}，n＝M，C1∈S1,C2∈S2,...,Cn∈SNAnd calculating to obtain the network modularity Q under the subregion divisionInitial；
A calculation step of calculating all the nodes C in the set CiAnd adjacent sub-area { Sj,Sk,Sm,., corresponding to the increment of the network modularity (delta Q) after combination one by onej,ΔQk,ΔQm,.., and from { S }j,Sk,Sm,.. find the adjacent sub-area S with the largest incrementmaxAnd dividing the sub-area SmaxAs node CiThe new subregion Si' to which it belongs;
a sub-area judgment step of judging for all the nodes CiI ∈ {1, 2., n }, which is the new subzone Si' whether or not to the sub-region S to which the original belongsiAre the same subarea;
a merging step, namely generating a new network structure when the nodes are judged to be in the same subarea, merging all the nodes with the same subarea mark number to form a new node set { C1,C2,...,CnN is equal to the updated number of network nodes H;
a re-division step of calculating the updated structure modularity Q of the networkUpdatingAnd comparing whether the value is greater than the modularity before updating the network structure, and ending when the result is negative, andthe network division result at this time is used as the final division result.
The invention provides a traffic control subarea dividing method based on modularity evaluation, which is characterized by comprising the following steps of:
the network modularity is calculated by the following formula:
where n is the number of network sub-regions, lv is the number of edges inside the sub-region v, dv is the sum of degrees of all nodes in the sub-region v, and M is the total number of edges of the network.
The invention provides a traffic control subarea dividing method based on modularity evaluation, which is characterized by comprising the following steps of:
the network modularity is calculated by the following formula:
wherein Aij represents the weight value between the nodes i and j, ki represents the sum of the weight values of the nodes i in the network, ci represents the subarea to which the node i belongs, m is the number of edges of the whole network,
if node i and node j are in the same sub-area, δ (ci, cj) ═ 1, otherwise, it equals 0.
The invention provides a traffic control subarea dividing method based on modularity evaluation, which is characterized by comprising the following steps of:
when nodes i and j in the network form an undirected graph edge, the weight is directly 1.
The invention provides a traffic control subarea dividing method based on modularity evaluation, which is characterized by comprising the following steps of:
and when the judgment result shows that the data are not in the same sub-area, skipping to enter the calculation step.
The invention provides a traffic control subarea dividing method based on modularity evaluation, which is characterized by comprising the following steps of:
wherein the structure modularity Q of the network after updatingUpdatingAnd when the value is greater than the modularity before updating the network structure, skipping to enter the calculation step.
The invention also provides a traffic control subarea division system based on modularity evaluation, which is characterized by comprising the following steps:
an initial dividing unit for: acquiring the number M of intersections of a road network, and recording n nodes in a network structure as a set C: { C1,C2,...,CnAnd dividing sub-areas corresponding to the road network one by one according to the fact that each sub-area comprises a node to obtain a set S: { S1,S2,...,SN}，n＝M，C1∈S1,C2∈S2,...,Cn∈SNAnd calculating to obtain the network modularity Q under the subregion divisionInitial；
A computing unit to: computing all nodes C in the set CiAnd adjacent sub-area { Sj,Sk,Sm,., corresponding to the increment of the network modularity (delta Q) after combination one by onej,ΔQk,ΔQm,.., and from { S }j,Sk,Sm,.. find the adjacent sub-area S with the largest incrementmaxAnd dividing the sub-area SmaxAs node CiThe new subregion Si' to which it belongs;
a sub-area judgment unit for: determine for all nodes CiI ∈ {1, 2., n }, which is the new subzone Si' whether or not to the sub-region S to which the original belongsiAre the same subarea;
a merging unit to: when the nodes are judged to be in the same subarea, a new network structure is generated, all the nodes with the same subarea mark number are merged to form a new node set { C1,C2,...,CnN is equal to the updated number of network nodes H;
a repartitioning unit to: calculating the updated fabric modularity Q of the networkUpdatingAnd comparing whether the current modularity is larger than the modularity before updating the network structure, ending the process in the negative result, and taking the network partitioning result at the moment as the final partitioning result.
The traffic control subarea division system based on modularity evaluation provided by the invention can also have the following characteristics:
the network modularity is calculated by the following formula:
where n is the number of network sub-regions, lv is the number of edges inside the sub-region v, dv is the sum of degrees of all nodes in the sub-region v, and M is the total number of edges of the network.
The traffic control subarea division system based on modularity evaluation provided by the invention can also have the following characteristics:
the network modularity is calculated by the following formula:
wherein Aij represents the weight value between the nodes i and j, ki represents the sum of the weight values of the nodes i in the network, ci represents the subarea to which the node i belongs, m is the number of edges of the whole network,
if node i and node j are in the same sub-area, δ (ci, cj) ═ 1, otherwise, it equals 0.
The traffic control subarea division system based on modularity evaluation provided by the invention can also have the following characteristics:
when nodes i and j in the network form an undirected graph edge, the weight is directly 1.
Action and Effect of the invention
The invention provides a traffic control subarea division system and method based on modularity evaluation based on overall efficiency of an urban road network after comprehensively analyzing the influence of various division principles on the division result of the traffic control subarea. Simulation experiments prove that the modularity is used as an index for measuring the strength of the network subareas after the subareas are divided, and if the strength of the subarea structure divided by the network is stronger, the dividing quality is better. Thus, optimal network subdivision may be obtained by maximizing modularity. The sub-area division evaluation index, namely the modularity, is used as a control parameter in the traffic control sub-area division process, so that the global optimization of the traffic control sub-area division can be ensured, and the calculation speed of a traffic control sub-area division algorithm is improved.
Drawings
Fig. 1 is a schematic diagram of a simple network.
FIG. 2 is a schematic flow chart of a traffic control sub-area division method based on modularity evaluation according to an embodiment of the present invention;
FIG. 3 is a flow chart of a traffic control sub-area division method based on modularity evaluation in an optimized embodiment of the invention;
FIG. 4 is a schematic structural diagram of a traffic control sub-area division system based on modularity evaluation according to an embodiment of the present invention;
fig. 5 is a network modularity variation curve after the invention and the SCATS partition.
Detailed Description
In order to make the technical means, the creation features, the achievement purposes and the effects of the invention easy to understand, the following embodiments specifically describe the system and the method for dividing the traffic control sub-area based on the modularity evaluation in combination with the accompanying drawings.
With the rapid development of traffic networks, the complexity of the traffic networks is also rapidly increasing, and in order to reduce the complexity of the research on the traffic networks, it is necessary to divide urban traffic networks into reasonable traffic control sub-areas. In order to obtain a better traffic control subarea division effect, the invention provides that a subarea division evaluation index, namely modularity, is introduced in the subarea division process, the effect of the evaluation index is mainly embodied in a traffic control subarea division algorithm, and the specific flow of the algorithm is shown in figure 1.
The modularity is also called as a modularization metric value, is a commonly used index for measuring the structural strength of a network subregion at present, and the definition of the modularity is provided by Mark NewMan at first as follows:
wherein, Aij represents the weight value between the nodes i (the undirected graph edge weight value is 1), ki represents the sum of the weight values of the nodes i in the network, ci represents the subarea to which the node i belongs, if i and j are in the same subarea, δ (ci, cj) is 1, otherwise, δ is equal to 0, and m is the edge number of the whole network.
For example, a simple network as shown in fig. 1, with 4 nodes, 3 edges, divided into 3 sub-regions (where nodes 1 and 2 are in sub-region 1, node 3 is in sub-region 2, and node 4 is in sub-region 3):
generating the adjacency matrix according to the definition is:
the sub-area matrix to which the node belongs is as follows:
[1 1 2 3]
the network modularity is then:
the modularity calculation formula of the simplified network becomes:
where n is the number of network sub-regions, lv is the number of edges inside the sub-region v, dv is the sum of degrees of all nodes in the sub-region v, and M is the total number of edges of the network. Degree < Degree >: is one of the simplest and most important concepts that characterize the properties of a single node. In a undirected network, the degree ki of a node i is defined as the number of edges connected to the node i.
Or taking the above network as an example, the network modularity is as follows:
it can be seen that the two formula definitions are equivalent.
The simplified formula is the sum of the modularity of each sub-area, which lets us know the modularity algorithm of each sub-area. The size of the modularity value mainly depends on the sub-area allocation C of the nodes in the network, namely the sub-area dividing condition of the network, and can be used for quantitatively measuring the sub-area dividing quality of the network, wherein the closer the value is to 1, the stronger the strength of the sub-area structure divided by the network is, namely the better the dividing quality is. An optimal network subdivision can thus be obtained by maximizing the modularity Q.
As can be seen from the flow diagram of the traffic control sub-area division method based on modularity evaluation shown in fig. 2, the combination between intersections and the change of the network logic structure are both measured by the modularity index. A large number of tests show that the evaluation method can obtain a better traffic control subarea, and the algorithm has a higher convergence speed.
The following describes a traffic control sub-area division system and method based on modularity evaluation with reference to embodiments.
Example 1
As shown in fig. 2, the present embodiment provides a traffic control sub-area division method based on modularity evaluation, which is used for dividing sub-areas in a traffic network, and includes the following steps:
an initial dividing step S1, obtaining the intersection number M of the road network, and recording n nodes in the network structure as a set C: { C1,C2,...,CnAnd dividing sub-areas corresponding to the road network one by one according to the fact that each sub-area comprises a node to obtain a set S: { S1,S2,...,SN}，n＝M，C1∈S1,C2∈S2,...,Cn∈SNAnd calculating to obtain the network modularity Q under the subregion divisionInitial；
A calculation step S2 of calculating all the nodes C in the set CiAnd adjacent sub-area { Sj,Sk,Sm,., corresponding to the increment of the network modularity (delta Q) after combination one by onej,ΔQk,ΔQm,.., and from { S }j,Sk,Sm,.. } inFinding the most incremental neighboring sub-region SmaxAnd dividing the sub-area SmaxAs node CiThe new subregion Si' to which it belongs;
a sub-area judgment step S3 of judging whether all the nodes C are presentiI ∈ {1, 2., n }, which is the new subzone Si' whether or not to the sub-region S to which the original belongsiAre the same subarea;
a merging step S4, generating a new network structure when the nodes are judged to be in the same sub-area, merging all the nodes with the same sub-area label to form a new node set { C1,C2,...,CnN is equal to the updated number of network nodes H;
a re-division step S5 for calculating the updated structure modularity Q of the networkUpdatingAnd comparing whether the current modularity is larger than the modularity before updating the network structure, ending the process in the negative result, and taking the network partitioning result at the moment as the final partitioning result.
Wherein, the network modularity can be calculated by the following formula:
wherein n is the number of network subareas, lv is the number of edges inside the subarea v, dv is the sum of degrees of all nodes in the subarea v, M is the total number of edges of the network, and when the nodes i and j in the network form an undirected graph edge, the weight is directly 1.
Or
The network modularity is calculated by the following formula:
wherein Aij represents the weight value between the nodes i and j, ki represents the sum of the weight values of the nodes i in the network, ci represents the subarea to which the node i belongs, m is the number of edges of the whole network,
if node i and node j are in the same sub-area, δ (ci, cj) ═ 1, otherwise, it equals 0.
Obviously, the derivation from the above formula yields the same results for formula one and formula two.
Example 2
On the basis of example 1, as a supplement:
in the sub-area judgment step S3, when it is judged that the sub-areas are not in the same sub-area, the flow proceeds to the calculation step S2.
In the re-dividing step S5, the structure modularity Q of the network after updatingUpdatingIf it is greater than the modularity before updating the network structure, the process proceeds to the calculation step S2.
Example 3
As shown in fig. 3, this embodiment further optimizes the calculation step S2 based on embodiment 1 or 2, and is implemented by performing traversal calculation from sub-area to sub-area.
An initial dividing step S1, obtaining the intersection number M of the road network, and recording n nodes in the network structure as a set C: { C1,C2,...,CnAnd dividing sub-areas corresponding to the road network one by one according to the fact that each sub-area comprises a node to obtain a set S: { S1,S2,...,SN}，n＝M，C1∈S1,C2∈S2,...,Cn∈SNAnd calculating to obtain the network modularity Q under the subregion divisionInitial；
A calculation step S2 of calculating all the nodes C in the set CiAnd adjacent sub-area { Sj,Sk,Sm,., corresponding to the increment of the network modularity (delta Q) after combination one by onej,ΔQk,ΔQm,., updating the modularity before the network structure.
The programmed algorithm implementation of this step is shown in figure 3,
firstly, setting an initialization loop variable i to be 0;
second, determine whether the current sub-area is the last sub-area, i < n? If the judgment result is yes, the next step is carried out, otherwise, the traversal is finished, and the step S3 is directly jumped to;
third, compute node { Sj,Sk,Sm,.. } increment of network modularity after combination with neighboring subregions { Δ Q }j,ΔQk,ΔQm,...}；
Fourthly, finding out the adjacent subarea S with the largest incrementmaxIn which S ismax∈{Sj,Sk,Sm,...}；
The fifth step, the node CiTo the sub-zone SmaxAnd record the label, i.e. Ci∈Smax,Si'＝Smax；
And sixthly, entering the next subarea to perform the operations from the first step to the fifth step, namely i + +.
A sub-area judgment step S3 of judging whether all the nodes C are presentiI ∈ {1, 2., n }, which is the new subzone Si' whether or not to the sub-region S to which the original belongsiAre the same sub-region.
The programmed algorithm implementation of this step is shown in FIG. 3, with the decision being made for all nodes CiI ∈ {1, 2., n }, whether its subzone is the same as the previous round, i.e., Si'？＝Si,i∈{1,2,...,n}
A merging step S4, generating a new network structure, merging all nodes with the same sub-area label to form a new node set { C }1,C2,...,CnAt this point n equals the updated number of network nodes H.
The program algorithm implementation of this step is as shown in fig. 3, when it is determined to be in the same sub-area, a new network structure is generated, and all nodes with the same sub-area label are merged to form a new node label { C1,C2,...,CnWhen n is equal to the updated number of network nodes H, i.e. n ═ H.
A re-division step S5 for calculating the updated structure modularity Q of the networkUpdatingAnd comparing whether the current modularity is larger than the modularity before updating the network structure, ending the process in the negative result, and taking the network partitioning result at the moment as the final partitioning result.
The algorithm implementation of the procedure of this step is as shown in fig. 3, and determines whether the new network structure modularity (Q) is increased compared to the previous one, and if not, takes the network partitioning result at this time as the final partitioning result.
Wherein, the network modularity can be calculated by the following formula:
wherein n is the number of network subareas, lv is the number of edges inside the subarea v, dv is the sum of degrees of all nodes in the subarea v, M is the total number of edges of the network, and when the nodes i and j in the network form an undirected graph edge, the weight is directly 1.
Or
The network modularity is calculated by the following formula:
wherein Aij represents the weight value between the nodes i and j, ki represents the sum of the weight values of the nodes i in the network, ci represents the subarea to which the node i belongs, m is the number of edges of the whole network,
if node i and node j are in the same sub-area, δ (ci, cj) ═ 1, otherwise, it equals 0.
Obviously, the derivation from the above formula yields the same results for formula one and formula two.
Example 4
The embodiment provides a traffic control subregion partitioning system based on modularity evaluation, which comprises an initial partitioning unit 100, a calculating unit 200, a subregion judging unit 300, a merging unit 400 and a re-partitioning unit 500.
An initial dividing unit 100 for: acquiring the number M of intersections of a road network, and recording n nodes in a network structure as a set C: { C1,C2,...,CnAnd dividing sub-areas corresponding to the road network one by one according to the fact that each sub-area comprises a node to obtain a set S: { S1,S2,...,SN}，n＝M，C1∈S1,C2∈S2,...,Cn∈SNAnd calculating to obtain the network modularity Q under the subregion divisionInitial。
A computing unit 200 for: computing all nodes C in the set CiAnd adjacent sub-area { Sj,Sk,Sm,., corresponding to the increment of the network modularity (delta Q) after combination one by onej,ΔQk,ΔQm,.., and from { S }j,Sk,Sm,.. find the adjacent sub-area S with the largest incrementmaxAnd dividing the sub-area SmaxAs node CiThe new subregion Si' to which it belongs.
A sub-area judgment unit 300 for: determine for all nodes CiI ∈ {1, 2., n }, which is the new subzone Si' whether or not to the sub-region S to which the original belongsiAre the same sub-region.
A merging unit 400 for: when the nodes are judged to be in the same subarea, a new network structure is generated, all the nodes with the same subarea mark number are merged to form a new node set { C1,C2,...,CnAt this point n equals the updated number of network nodes H.
A repartitioning unit 500 for calculating a fabric modularity Q of the updated networkUpdatingAnd comparing whether the current modularity is larger than the modularity before updating the network structure, ending the process in the negative result, and taking the network partitioning result at the moment as the final partitioning result.
Wherein, the network modularity can be calculated by the following formula:
wherein n is the number of network subareas, lv is the number of edges inside the subarea v, dv is the sum of degrees of all nodes in the subarea v, M is the total number of edges of the network, and when the nodes i and j in the network form an undirected graph edge, the weight is directly 1.
Or
The network modularity is calculated by the following formula:
wherein Aij represents the weight value between the nodes i and j, ki represents the sum of the weight values of the nodes i in the network, ci represents the subarea to which the node i belongs, m is the number of edges of the whole network,
if node i and node j are in the same sub-area, δ (ci, cj) ═ 1, otherwise, it equals 0.
Obviously, the derivation from the above formula yields the same results for formula one and formula two.
Example 5
On the basis of example 4, as a supplement:
in the sub-area judgment unit 300, when it is judged that the sub-areas are not in the same sub-area, the jump-entry calculation unit 200 executes the jump-entry.
In the repartitioning unit 500, the degree of structural modularity Q of the network after updatingUpdatingAnd when the value is greater than the modularity before updating the network structure, jumping to the computing unit 200 for execution.
In order to illustrate the technical effects of the traffic control sub-area division system and method based on modularity evaluation provided in the embodiments, the following is verified through simulation experiments.
The experimental procedure was as follows:
1. and (5) information acquisition. And data required by the traffic control subarea division comprise dynamic traffic flow and scene information which continuously change along with time and static/semi-static road information. In order to ensure the stability and accuracy of the method, special software or application program needs to be developed to interface with a third-party system or an existing information integration platform so as to automatically or even real-timely collect parameters of various influence subarea division results, including: road network topology, road section and intersection attributes, traffic flow information, traffic flow average speed, lane occupancy, weather conditions, construction conditions and the like.
2. And (6) data arrangement. The data acquired in step 1 may have missing or abnormal data, and the acquired data needs to be preprocessed by methods such as data screening and prediction, so that the integrity and rationality of the data are ensured.
3. And (4) algorithm implementation. Referring to the flow chart of the traffic control subregion division method shown in fig. 2 or fig. 3, the subregion division algorithm program based on the modularity evaluation is implemented by writing an application program or software.
4. And (6) testing. And (3) testing an algorithm result by adopting data acquired in real time, comparing the algorithm result with the partitioning results of the SCOOT and SCATS of the main stream signal control system, and verifying the rationality of the traffic control sub-area partitioning method based on modularity evaluation.
101 intersections in a certain city are taken as test objects.
Since the partition method of SCOOT is static partition, i.e. the partition scheme does not change with time, the effect is certainly not better than that of the method adopted by the present invention if the partition scheme is evaluated in real-time modularity.
For comparison with the real-time partition of the SCATS, as shown in fig. 5, a black curve represents the change of the network modularity after the sub-partitions are divided at different times, and a gray curve represents the change of the network modularity after the sub-partitions are divided at different times. Compared with the calculation results, the average modularity of the sub-area division of the invention is 0.8074, and the average modularity of the SCATS sub-area division is 0.7569, so that the experiment can verify that the sub-area division effect of the invention is better. Effects and effects of the embodiments
The invention provides a traffic control subarea division system and method based on modularity evaluation based on overall efficiency of an urban road network after comprehensively analyzing the influence of various division principles on the division result of the traffic control subarea. Simulation experiments prove that the modularity is used as an index for measuring the strength of the network subareas after the subareas are divided, and if the strength of the subarea structure divided by the network is stronger, the dividing quality is better. Thus, optimal network subdivision may be obtained by maximizing modularity. The sub-area division evaluation index, namely the modularity, is used as a control parameter in the traffic control sub-area division process, so that the global optimization of the traffic control sub-area division can be ensured, and the calculation speed of a traffic control sub-area division algorithm is improved.
Through example verification, the sub-area division method provided by the invention enables the combination between intersections and the change of a network logic structure to be measured through a modularity index, and a large number of tests show that the evaluation method can obtain a better traffic control sub-area, and the algorithm convergence speed is higher.
The present invention is not limited to the above-described embodiments, and it will be apparent to those skilled in the art that various modifications and improvements can be made without departing from the principle of the present invention, and such modifications and improvements are also considered to be within the scope of the present invention. Those not described in detail in this specification are within the skill of the art.
Claims (6)
1. A traffic control subregion partition method based on modularity evaluation is used for partitioning subregions in a traffic signal lamp control network, and is characterized by comprising the following steps:
an initial dividing step, namely acquiring the number M of intersections of the road network, and recording n nodes in the network structure as a set C: { C1,C2,...,CnAnd dividing sub-areas corresponding to the road network one by one according to the fact that each sub-area comprises a node to obtain a set S: { S1,S2,...,SN}，n＝M，C1∈S1,C2∈S2,...,Cn∈SNAnd calculating to obtain the network modularity Q under the subregion divisionInitial；
A calculation step of calculating all the nodes C in the set CiAnd adjacent sub-area { Sj,Sk,Sm,., corresponding to the increment of the network modularity (delta Q) after combination one by onej,ΔQk,ΔQm,.., and from { S }j,Sk,Sm,.. find the adjacent sub-area S with the largest incrementmaxAnd dividing the sub-area SmaxAs node CiThe new subregion Si' to which it belongs;
a sub-area judgment step of judging for all the nodes CiI ∈ {1, 2., n }, to which it belongs newlySubregion Si' whether or not to the sub-region S to which the original belongsiAre the same subarea;
a merging step, namely generating a new network structure when the nodes are judged to be in the same subarea, merging all the nodes with the same subarea mark number to form a new node set { C1,C2,...,CnN is equal to the updated number of network nodes H;
a re-division step of calculating the updated structure modularity Q of the networkUpdatingComparing whether the degree of modularity is larger than that before updating the network structure, ending the process in the negative result, and taking the network division result as the final division result;
the network modularity is calculated by the following formula:
wherein Aij represents the weight value between the nodes i and j, ki represents the sum of the weight values of the nodes i in the network, ci represents the subarea to which the node i belongs, m is the number of edges of the whole network,
if node i and node j are in the same sub-area, δ (ci, cj) ═ 1, otherwise, it equals 0.
2. The method of claim 1, wherein the method comprises the following steps:
when nodes i and j in the network form an undirected graph edge, the weight is directly 1.
3. The method of claim 1, wherein the method comprises the following steps:
and when the judgment result shows that the data are not in the same sub-area, skipping to enter the calculation step.
4. The method of claim 3, wherein the sub-area of the traffic control is divided according to the modularity evaluation, and the method comprises:
wherein the structure modularity Q of the network after updatingUpdatingAnd when the value is greater than the modularity before updating the network structure, skipping to enter the calculation step.
5. A traffic control subregion division system based on modularity evaluation is used for dividing subregions in a traffic signal lamp control network, and is characterized by comprising:
an initial dividing unit for: acquiring the number M of intersections of a road network, and recording n nodes in a network structure as a set C: { C1,C2,...,CnAnd dividing sub-areas corresponding to the road network one by one according to the fact that each sub-area comprises a node to obtain a set S: { S1,S2,...,SN}，n＝M，C1∈S1,C2∈S2,...,Cn∈SNAnd calculating to obtain the network modularity Q under the subregion divisionInitial；
A computing unit to: computing all nodes C in the set CiAnd adjacent sub-area { Sj,Sk,Sm,., corresponding to the increment of the network modularity (delta Q) after combination one by onej,ΔQk,ΔQm,.., and from { S }j,Sk,Sm,.. find the adjacent sub-area S with the largest incrementmaxAnd dividing the sub-area SmaxAs node CiThe new subregion Si' to which it belongs;
a sub-area judgment unit for: determine for all nodes CiI ∈ {1, 2., n }, which is the new subzone Si' whether or not to the sub-region S to which the original belongsiAre the same subarea;
a merging unit to: when the nodes are judged to be in the same subarea, a new network structure is generated, all the nodes with the same subarea mark number are merged to form a new node set { C1,C2,...,CnN is equal to the updated number of network nodes H;
a repartitioning unit to: calculating the updated fabric modularity Q of the networkUpdatingAnd comparing whether the comparison result is larger than that before updating the network structureThe modularity is finished when the result is negative, and the network division result at the moment is taken as the final division result;
the network modularity is calculated by the following formula:
wherein Aij represents the weight value between the nodes i and j, ki represents the sum of the weight values of the nodes i in the network, ci represents the subarea to which the node i belongs, m is the number of edges of the whole network,
if node i and node j are in the same sub-area, δ (ci, cj) ═ 1, otherwise, it equals 0.
6. The system for partitioning a traffic control sub-area based on modularity evaluation recited in claim 5, wherein:
when nodes i and j in the network form an undirected graph edge, the weight is directly 1.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910330745.7A CN110111567B (en) | 2019-04-23 | 2019-04-23 | Traffic control subarea division method and system based on modularity evaluation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910330745.7A CN110111567B (en) | 2019-04-23 | 2019-04-23 | Traffic control subarea division method and system based on modularity evaluation |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110111567A CN110111567A (en) | 2019-08-09 |
| CN110111567B true CN110111567B (en) | 2021-05-18 |
Family
ID=67486385
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910330745.7A Active CN110111567B (en) | 2019-04-23 | 2019-04-23 | Traffic control subarea division method and system based on modularity evaluation |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110111567B (en) |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111210625B (en) * | 2020-01-10 | 2022-06-07 | 阿里巴巴集团控股有限公司 | Traffic control method and device and electronic equipment |
| CN113129614B (en) * | 2020-01-10 | 2023-01-24 | 阿里巴巴集团控股有限公司 | Traffic control method and device and electronic equipment |
| CN111768618B (en) * | 2020-06-04 | 2021-07-20 | 北京航空航天大学 | Traffic jam state propagation prediction and early warning system and method based on city portrait |
| CN113362205B (en) * | 2021-06-18 | 2023-01-17 | 广州工商学院 | Teaching team cultivation management system |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| ES2234195T3 (en) * | 1999-10-08 | 2005-06-16 | Eidgenossische Technische Hochschule Zurich | DEVICE FOR CONTROLLING A PHYSICAL SYSTEM. |
| CN101751777A (en) * | 2008-12-02 | 2010-06-23 | 同济大学 | Dynamic urban road network traffic zone partitioning method based on space cluster analysis |
| CN102800200A (en) * | 2012-06-28 | 2012-11-28 | 吉林大学 | Method for analyzing relevance of adjacent signalized intersections |
| CN105869401A (en) * | 2016-05-12 | 2016-08-17 | 华南理工大学 | Road network dynamic partitioning method based on different crowdedness degrees |
| CN108364465A (en) * | 2018-02-09 | 2018-08-03 | 太原理工大学 | The method for dynamically partitioning of city road network control work zone based on macroscopical parent map |
| CA3071498A1 (en) * | 2017-01-31 | 2018-08-09 | Keyvan T. Diba | Electronic traffic alert system |
| CN108648454A (en) * | 2018-05-18 | 2018-10-12 | 中山大学 | A kind of traffic zone method for dynamically partitioning based on trip data |
| CN109410577A (en) * | 2018-11-09 | 2019-03-01 | 东北林业大学 | Adaptive traffic control sub-area division method based on Spatial Data Mining |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102722986B (en) * | 2012-06-28 | 2014-04-30 | 吉林大学 | Urban road network traffic control subarea dynamic partitioning method |
| CN102890860B (en) * | 2012-09-28 | 2014-10-22 | 北京世纪高通科技有限公司 | Method and device for classifying traffic zone |
| CN109272170B (en) * | 2018-10-11 | 2019-08-30 | 北京市交通信息中心 | A kind of traffic zone dividing system based on Louvain algorithm |
-
2019
- 2019-04-23 CN CN201910330745.7A patent/CN110111567B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| ES2234195T3 (en) * | 1999-10-08 | 2005-06-16 | Eidgenossische Technische Hochschule Zurich | DEVICE FOR CONTROLLING A PHYSICAL SYSTEM. |
| CN101751777A (en) * | 2008-12-02 | 2010-06-23 | 同济大学 | Dynamic urban road network traffic zone partitioning method based on space cluster analysis |
| CN102800200A (en) * | 2012-06-28 | 2012-11-28 | 吉林大学 | Method for analyzing relevance of adjacent signalized intersections |
| CN105869401A (en) * | 2016-05-12 | 2016-08-17 | 华南理工大学 | Road network dynamic partitioning method based on different crowdedness degrees |
| CA3071498A1 (en) * | 2017-01-31 | 2018-08-09 | Keyvan T. Diba | Electronic traffic alert system |
| CN108364465A (en) * | 2018-02-09 | 2018-08-03 | 太原理工大学 | The method for dynamically partitioning of city road network control work zone based on macroscopical parent map |
| CN108648454A (en) * | 2018-05-18 | 2018-10-12 | 中山大学 | A kind of traffic zone method for dynamically partitioning based on trip data |
| CN109410577A (en) * | 2018-11-09 | 2019-03-01 | 东北林业大学 | Adaptive traffic control sub-area division method based on Spatial Data Mining |
Non-Patent Citations (2)
| Title |
|---|
| Study on urban road network traffic district division based on clustering analysis;Luhua Zhao et al.;《IEEE》;20181231;全文 * |
| 城市路网交通控制子区动态划分策略;马有苗;《城乡规划》;20181231;全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110111567A (en) | 2019-08-09 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110111567B (en) | Traffic control subarea division method and system based on modularity evaluation | |
| CN110111335B (en) | Urban traffic scene semantic segmentation method and system for adaptive countermeasure learning | |
| CN108981739B (en) | Path planning method, device, server and storage medium | |
| CN108364465B (en) | Dynamic division method of urban road network control subarea based on macroscopic basic graph | |
| CN109635748B (en) | Method for extracting road characteristics in high-resolution image | |
| CN108712287B (en) | VANET community discovery method based on node similarity | |
| CN113989305B (en) | Target semantic segmentation method and street target abnormity detection method applying same | |
| CN110276966B (en) | Intersection signal control time interval dividing method | |
| CN110502447B (en) | Regression test case priority ordering method based on graph | |
| CN113257016B (en) | Traffic signal control method and device and readable storage medium | |
| CN112215427A (en) | Vehicle driving track reconstruction method and system under condition of bayonet data loss | |
| CN110738132A (en) | target detection quality blind evaluation method with discriminant perception capability | |
| CN113609240B (en) | Vehicle travel track reconstruction method based on massive bayonet data | |
| CN114969234A (en) | Vector characterization method for full-quantity city road network | |
| CN113505261B (en) | Data labeling method and device and data labeling model training method and device | |
| CN111311907A (en) | Identification method for uncertain basic graph parameter identification based on cellular transmission model | |
| CN114723037A (en) | Heterogeneous graph neural network computing method for aggregating high-order neighbor nodes | |
| CN117114220A (en) | Vehicle scheduling algorithm based on graph neural network | |
| US20230161688A1 (en) | Intelligent test method for dynamically generating test case according to test performance of tested system | |
| CN116362120A (en) | Traffic flow prediction method and device based on MGCN-GRU model | |
| CN114070438B (en) | Detection method and system for electromagnetic signals of 5G base station | |
| CN113284030B (en) | Urban traffic network community division method | |
| CN111985526B (en) | Similar scene clustering-based trailing interval management strategy generation method and system | |
| CN114663606A (en) | Three-dimensional road model system and generation mode | |
| Werth et al. | Surrogate-assisted microscopic traffic simulation-based optimisation of routing parameters |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |