CN116523345B - Urban road topology network connectivity evaluation method - Google Patents
Urban road topology network connectivity evaluation method Download PDFInfo
- Publication number
- CN116523345B CN116523345B CN202310509930.9A CN202310509930A CN116523345B CN 116523345 B CN116523345 B CN 116523345B CN 202310509930 A CN202310509930 A CN 202310509930A CN 116523345 B CN116523345 B CN 116523345B
- Authority
- CN
- China
- Prior art keywords
- node
- nodes
- connectivity
- road network
- network
- 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
- 238000011156 evaluation Methods 0.000 title abstract description 6
- 238000000034 method Methods 0.000 claims abstract description 30
- 239000011159 matrix material Substances 0.000 claims abstract description 22
- 238000005457 optimization Methods 0.000 description 9
- 230000004075 alteration Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 230000001133 acceleration Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/07—Controlling traffic signals
- G08G1/081—Plural intersections under common control
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/901—Indexing; Data structures therefor; Storage structures
- G06F16/9024—Graphs; Linked lists
-
- 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"
- G06Q10/047—Optimisation of routes or paths, e.g. travelling salesman 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
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0637—Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
-
- 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—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/40—Business processes related to the transportation industry
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A30/00—Adapting or protecting infrastructure or their operation
- Y02A30/60—Planning or developing urban green infrastructure
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- General Business, Economics & Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Tourism & Hospitality (AREA)
- Marketing (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Game Theory and Decision Science (AREA)
- Development Economics (AREA)
- Educational Administration (AREA)
- Databases & Information Systems (AREA)
- Software Systems (AREA)
- Data Mining & Analysis (AREA)
- General Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention discloses an urban road topology network connectivity evaluation method, which comprises the following steps: s1: abstracting the urban road network into a directed graph G; s2: computing node v i And v j The number of communication paths between the nodes and the reachability a between any nodes are determined ij The method comprises the steps of carrying out a first treatment on the surface of the S3: according to the reachability a in step S2 ij Constructing a reachability matrix A of the directed graph G; s4: calculating two nodes v i And v j The total length of each communication path between the two paths is introduced with a steering coefficient q ikj Describing the steering condition of the intersection, and determining the shortest path l between two nodes when the steering of the intersection is limited ij The method comprises the steps of carrying out a first treatment on the surface of the S5: according to the number of the road sections passing by the shortest path, calculating a node v i And v j Shortest distance d between ij The method comprises the steps of carrying out a first treatment on the surface of the S6: by each ofInter-node reachability a ij And shortest distance d ij Computing node v i Degree of connectivity k i The method comprises the steps of carrying out a first treatment on the surface of the S7: through the connectivity k to each node i Accumulating to calculate the connectivity Con of the urban road network A . The method is suitable for evaluating the lane-level connectivity of the road networks in different forms, and reflects the actual reachable degree of the urban road network more in a fitting way.
Description
Technical Field
The invention relates to the technical field of urban traffic management and control, in particular to an urban road topology network connectivity evaluation method.
Background
Along with the acceleration of the urban process in China, the cities are continuously expanded, the urban road network becomes larger and more complex, the problem of urban traffic jam is also more serious, and the problem of traffic jam is more prominent in large-scale cities in China. Traffic jam characteristics vary from city to city, but one of the important reasons is that the road network connectivity is inadequate. The phenomena of 'dislocation intersection', 'right in and right out intersection', 'forbidden left turn and right turn', and the like cause the reduction of the connectivity of a road network, so that the traffic problems of 'concentrated traffic of a few trunk roads, insufficient utilization of other roads', and the like are highlighted, and the traffic jam of main trunk roads and nodes is aggravated.
The road network connectivity is used for evaluating the connection strength between road sections, and the road network connectivity is used as a road network operation evaluation index, so that the connection condition of the road network can be intuitively reflected, and the operation current situation of the whole road network can be evaluated. At present, related researches on urban road network connectivity in China are few, and the related researches are generally reflected by a connectivity index, namely the ratio of the sum of the line segments connected by each network node to the number of the whole network node. Although the connectivity index may reflect the connectivity of the urban road network to some extent, lane-level road network connectivity cannot be described, such as road left-hand prohibition, head-drop prohibition, etc. The road network connectivity is evaluated by establishing road network connectivity indexes, which mainly can be classified into alpha indexes, beta indexes, gamma indexes and the like, but the indexes describe the road network connectivity from the connection number of nodes and road sections, only the condition that four entrance roads of a road network intersection are fully communicated can be evaluated, and the road network connectivity condition when the lane direction in the intersection is limited (such as the left turn and right turn of a road is forbidden) can not be described. At present, more methods for evaluating the connectivity of the road network exist, but the connectivity of the road network is basically evaluated from the condition of full connectivity of an intersection, and the condition of the road network connectivity when the lane direction is limited is not considered.
Disclosure of Invention
Aiming at the defects of the prior art, the technical problem to be solved by the application is how to provide an urban road topology network connectivity evaluation method which is applicable to various crossing conditions and is fit with the actual road conditions of the city.
In order to solve the technical problems, the invention adopts the following technical scheme:
a method for evaluating the connectivity of an urban road topology network comprises the following steps: s1: abstracting the urban road network into a directed graph G; s2: calculating v of any two intersections as nodes i And v j Degree of accessibility a between ij The method comprises the steps of carrying out a first treatment on the surface of the S3: according to the reachability a in step S2 ij Constructing a reachability matrix A; s4: calculating two nodes v i And v j The total length of each path between them, introducing steering coefficient q ikj Describing the steering condition of the intersection, and obtaining the shortest path l between two nodes when the steering of the intersection is limited ij The method comprises the steps of carrying out a first treatment on the surface of the S5: according to the number of the road sections passing by the shortest path, calculating a node v i And v j Shortest distance d between ij The method comprises the steps of carrying out a first treatment on the surface of the S6: computing node v i Degree of connectivity k i : through the accessibility a among all nodes ij Shortest distance d between nodes ij Constructing single node connectivity k i Is calculated according to the formula; s7: the connectivity of each node is calculated through the steps, and the connectivity of each node is accumulated, so that the connectivity Con of the urban road network is calculated A 。
As an optimization, when the urban road network is abstracted into the directed graph in step S1, the intersections in the urban road network are regarded as nodes, the road sections are regarded as edges, and the urban road network can be abstracted into a simplified network graph, and the network graph is formed byA limited number of "node" sets V and "edge" sets E, denoted G, i.e., the network may be denoted G (V, E); in the network, the intersection is regarded as a node, v= { V 1 ,v 2 ,v 3 ,v 4 ,...,v n -is a set of intersection nodes; the road sections between adjacent intersections in the road network are edges connecting all nodes. E= { E 1 ,e 2 ,e 3 ,...,e n And is a collection of edges.
As an optimization, in step S2, the reachability a between nodes ij Representing node v i And v j The degree of connectivity, i.e., the number of paths connecting between two nodes; node v is considered to be a network node when there is at least 1 path connection between two nodes i To node v j Is communicated with, wherein the number of the communicating paths is a ij ，a ij 1 or more; if there is no path connection between two nodes, node v i To node v j Is not communicated with, a ij ＝0。
As an optimization, when the reachability matrix a is constructed in step S3, the method includes the following steps:
a1: the reachability adjacency matrix comprises reachability among all nodes of the whole road network;
a2: reachability adjacency matrix a is an n x n two-dimensional matrix. In the matrix, a ij Is an element of row i and column j in the matrix, representing node v i To node v j Is the degree of reachability of (a);
as optimization, in step S4, a distance weight coefficient Z is introduced into the initial road network directed graphTo express between two adjacent nodesThe length of the edge is G (V, E) →G (V, E, Z); when z ij ＝z ji If > 0, the edge is in a clear state and represents node v i And node v j Communicating; when z ij ＞0,z ji = infinity, representing a slave node v i Leading to node v j But not from node v j Leading to node v i The method comprises the steps of carrying out a first treatment on the surface of the When z ji ＞0,z ij = infinity, representing a slave node v j Leading to node v i Cannot be from node v i Leading to node v j The method comprises the steps of carrying out a first treatment on the surface of the When z ij ＝z ji = infinity, representing node v i To node v j Edges not directly connected;
as an optimization, the steering coefficient q is in step S4 ikj To describe steering behaviour between intersections, to describe the direction of travel v i →v k →v j Is a steering lane condition; q ik ＝q kj =1 to describe the steering of the first two nodes and the last two nodes; when q ikj =1, then the lane direction can pass normally; when q ikj And = ≡, the traffic is prohibited for that direction lane.
As an optimization, in step S4, l ij Is node v i To node v j The operation process of the shortest path of the path is as follows: at node v i To node v j And (3) respectively adding the lengths of edges between adjacent nodes communicated in each path, comparing the total length of each path between two nodes, and selecting the path with the shortest total length as the shortest path. Calculation of l ij Is calculated by the following formula:
wherein l ij For node v i To node v j Is the shortest path in (a); q ikj For node v i Through node v k Reach node v j Steering coefficient of (2); z ikj For node v i And node v j The length of the edges, i.e. node v i Through node v k Reach node v j The length of the edge.
As an optimization, in step S5, the node v is determined i To node v j After the shortest path of (2), calculating the number of the sections passed by the shortest path to obtain a node v i To node v j D of the shortest distance of (2) ij . When l ij Not equal to infinity, d ij 1 or more, representing the shortest path l ij Distance d of (2) ij 。
As an optimization, in step S6, the connectivity k i For node v i Reachability a with other nodes ij And node v i Shortest distance d to other nodes ij The index can reflect the self connectivity condition of each node in the road network; is calculated by the following calculation formula:
as an optimization, in step S7, the road network connectivity Con A Calculating the independent connectivity of each node in the road network, and accumulating the connectivity of each node in the road network to obtain the connectivity of the road network; the calculation formula is as follows:
in summary, the invention has the beneficial effects of being applicable to various intersection conditions and fitting with the actual road conditions of cities.
Drawings
Fig. 1 is a flow chart of a method for evaluating the connectivity of an urban road topology network according to the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings. In the description of the present invention, it should be understood that the azimuth or positional relationship indicated by the azimuth words such as "upper, lower" and "top, bottom", etc. are generally based on the azimuth or positional relationship shown in the drawings, and are merely for convenience of description and simplification of the description, and these azimuth words do not indicate or imply that the apparatus or element to be referred to must have a specific azimuth or be constructed and operated in a specific azimuth, without limiting the scope of protection of the present invention; the orientation word "inner and outer" refers to inner and outer relative to the contour of the respective component itself.
As shown in fig. 1, a method for evaluating the connectivity of an urban road topology network comprises the following steps: s1: abstracting the urban road network into a directed graph G; s2: calculating v of any two intersections as nodes i And v j Degree of accessibility a between ij The method comprises the steps of carrying out a first treatment on the surface of the S3: according to the reachability a in step S2 ij Constructing a reachability matrix A; s4: calculating two nodes v i And v j The total length of each path between them, introducing steering coefficient q ikj Describing the steering condition of the intersection, and obtaining the shortest path l between two nodes when the steering of the intersection is limited ij The method comprises the steps of carrying out a first treatment on the surface of the S5: according to the number of the road sections passing by the shortest path, calculating a node v i And v j Shortest distance d between ij The method comprises the steps of carrying out a first treatment on the surface of the S6: computing node v i Degree of connectivity k i : through the accessibility a among all nodes ij Shortest distance d between nodes ij Constructing single node connectivity k i Is calculated according to the formula; s7: the connectivity of each node is calculated through the steps, and the connectivity of each node is accumulated, so that the connectivity Con of the urban road network is calculated A 。
In this embodiment, when the urban road network is abstracted into the directed graph in step S1, the intersections in the urban road network are regarded as nodes, and the road segments are regarded as edges, so that the urban road network can be abstracted into a simplified network graph, and the network graph is composed of a limited set V of "nodes" and a set E of "edges", denoted by G, i.e., the network can be denoted as G (V, E); in the network, the intersection is regarded as a node, v= { V 1 ,v 2 ,v 3 ,v 4 ,...,v n -is a set of intersection nodes; the road sections between adjacent intersections in the road network are edges connecting all nodes. E= { E 1 ,e 2 ,e 3 ,...,e n And is a collection of edges.
In this embodiment, in step S2, the reachability a between nodes ij Representing node v i And v j The degree of connectivity, i.e., the number of paths connecting between two nodes; node v is considered to be a network node when there is at least 1 path connection between two nodes i To node v j Is communicated with, wherein the number of the communicating paths is a ij ，a ij 1 or more; if there is no path connection between two nodes, node v i To node v j Is not communicated with, a ij ＝0。
In this embodiment, when the reachability matrix a is constructed in step S3, the method includes the following steps:
a1: the reachability adjacency matrix comprises reachability among all nodes of the whole road network;
a2: reachability adjacency matrix a is an n x n two-dimensional matrix. In the matrix, a ij Is an element of row i and column j in the matrix, representing node v i To node v j Is the degree of reachability of (a);
in this embodiment, in step S4, a distance weight coefficient Z is introduced into the initial road network directed graphTo express the length of the edge between two adjacent nodes, then G (V, E) to G (V, E, Z); when z ij ＝z ji If > 0, the edge is in a clear state and represents node v i And node v j Communicating; when z ij ＞0,z ji = infinity, representing a slave node v i Leading to node v j But not from node v j Leading to node v i The method comprises the steps of carrying out a first treatment on the surface of the When z ji ＞0,z ij = infinity, representingSlave node v j Leading to node v i Cannot be from node v i Leading to node v j The method comprises the steps of carrying out a first treatment on the surface of the When z ij ＝z ji = infinity, representing node v i To node v j Edges not directly connected;
in this embodiment, the steering coefficient q is in step S4 ikj To describe steering behaviour between intersections, to describe the direction of travel v i →v k →v j Is a steering lane condition; q ik ＝q kj =1 to describe the steering of the first two nodes and the last two nodes; when q ikj =1, then the lane direction can pass normally; when q ikj And = ≡, the traffic is prohibited for that direction lane.
In this embodiment, the shortest path l in step S4 ij The operation process of (1) is as follows: at node v i To node v j And (3) respectively adding the lengths of edges between adjacent nodes communicated in each path, comparing the total length of each path between two nodes, and selecting the path with the shortest total length as the shortest path. The shortest path calculation formula is as follows:
wherein l ij For node v i To node v j Is the shortest path of (a); q ikj For node v i Through node v k Reach node v j Steering coefficient of (2); z ikj For node v i And node v j The length of the edges, i.e. node v i Through node v k Reaching the length of the node edge.
In this example, in step S5, node v is determined i To node v j Is the shortest path l of (1) ij Calculating the number of road segments passing through the shortest path to obtain a node v i To node v j D of the shortest distance of (2) ij . When l ij Not equal to infinity, d ij 1 or more, representing the shortest path l ij Distance d of (2) ij 。
In this embodiment, in step S6, the connectivity k i For node v i Reachability a with other nodes ij And node v i Shortest distance d to other nodes ij The index can reflect the self connectivity condition of each node in the road network; is calculated by the following calculation formula:
in the embodiment, in step S7, the road network connectivity Con A Calculating the independent connectivity of each node in the road network, and accumulating the connectivity of each node in the road network to obtain the connectivity of the road network; the calculation formula is as follows:
the beneficial effects are that:
the road network connectivity is one of important indexes for evaluating whether an urban road network is reasonable, the existing urban connectivity index describes whether road segments are connected or not, the influence of intersection steering limitation on road network connectivity cannot be reflected, and the road network connectivity is influenced by the steering limitation (left turning prohibition, right turning prohibition and the like) of different lanes of an urban intersection.
Finally, it should be noted that: various modifications and alterations of this invention may be made by those skilled in the art without departing from the spirit and scope of this invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (2)
1. A method for evaluating the connectivity of an urban road topology network comprises the following steps:
s1: abstracting the urban road network into a directed graph G;
s2: calculating v of any two intersections as nodes i And v j Degree of accessibility a between ij ；
S3: according to the reachability a in step S2 ij Constructing a reachability matrix A;
s4: find node v i And v j Shortest path between the two ij : comparison node v i And v j The total length of all the communication paths between the two paths is selected as the shortest path l ij ；
S5: computing node v i And v j Shortest distance d between ij : calculating the shortest distance by calculating the number of road sections passed by the shortest path;
s6: computing node v i Degree of connectivity k i : through the accessibility a among all nodes ij Shortest distance d between nodes ij Constructing single node connectivity k i Is calculated according to the formula;
s7: the connectivity of each node is calculated through the steps, and the connectivity of each node is accumulated, so that the connectivity Con of the urban road network is calculated A ；
In step S4, a distance weight coefficient Z is introduced to the initial road network directed graphTo express the length of the edge between two adjacent nodes, then G (V, E) to G (V, E, Z); when z ij ＝z ji If > 0, the edge is in a clear state and represents node v i And node v j Communicating; when z ij ＞0,z ji = infinity, representing a slave node v i Leading to node v j But not from node v j Leading to node v i The method comprises the steps of carrying out a first treatment on the surface of the When z ji ＞0,z ij = infinity, representing a slave node v j Leading to node v i Cannot be from node v i Leading to node v j The method comprises the steps of carrying out a first treatment on the surface of the When z ij ＝z ji = infinity, representing node v i To node v j Edges not directly connected;
steering coefficient q ikj To describe steering behaviour between intersections, to describe the direction of travel v i →v k →v j Is a steering lane condition; q ik ＝q kj =1 to describe the steering of the first two nodes and the last two nodes; when q ikj =1, then the lane direction can pass normally; when q ikj The lane in the direction is forbidden to pass if the number of the lanes is = ≡;
l ij is node v i To node v j The operation process of the shortest path of the (a) is as follows: at node v i To node v j Respectively adding the lengths of edges between adjacent nodes communicated in each path, comparing the total length of each path between two nodes, and selecting the path with the shortest total length as the shortest path; the formula is as follows:
wherein l ij For node v i To node v j Is the shortest path in (a); q ikj For node v i Through node v k Reach node v j Steering coefficient of (2); z ikj For node v i And node v j The length of the edges, i.e. node v i Through node v k Reach node v j The length of the edge;
in step S2, reachability a between nodes ij Representing node v i And v j The degree of connectivity, i.e., the number of paths connecting between two nodes; node v is considered to be a network node when there is at least 1 path connection between two nodes i To node v j Is communicated with, wherein the number of the communicating paths is a ij ，a ij 1 or more; if there is no path connection between two nodes, node v i To node v j Is not communicated with, a ij ＝0；
When the reachability matrix a is constructed in step S3, the method includes the following steps:
a1: the reachability adjacency matrix comprises reachability among all nodes of the whole road network;
a2: reachability adjacency matrix a is an n×n two-dimensional matrix; in the matrix, a ij Is an element of row i and column j in the matrix, representing node v i To node v j Is the degree of reachability of (a);
in step S5, d ij For node v i To node v j The shortest distance is calculated by the number of road sections passed by the shortest path; when l ij Not equal to infinity, d ij 1 or more, representing the shortest path l ij Distance d of (2) ij ；
In step S6, connectivity k i For node v i Reachability a with other nodes ij And node v i Shortest distance d to other nodes ij The index can reflect the self connectivity condition of each node in the road network; is calculated by the following calculation formula:
in step S7, the road network connectivity Con A Calculating the independent connectivity of each node in the road network, and accumulating the connectivity of each node in the road network to obtain the connectivity of the road network;the calculation formula is as follows:
2. the method for evaluating the network connectivity of the urban road topology according to claim 1, wherein when the urban road network is abstracted into a directed graph in the step S1, intersections in the urban road network are regarded as nodes, road sections are regarded as edges, the urban road network can be abstracted into a simplified network graph, and the network graph is composed of a limited set of nodes V and a set of edges E, denoted by G, i.e., the network can be denoted by G (V, E); in the network, the intersection is regarded as a node, v= { V 1 ,v 2 ,v 3 ,v 4 ,...,v n -is a set of intersection nodes; the road sections between adjacent intersections in the road network are edges for connecting all nodes, and E= { E 1 ,e 2 ,e 3 ,...,e n And is a collection of edges.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310509930.9A CN116523345B (en) | 2023-05-08 | 2023-05-08 | Urban road topology network connectivity evaluation method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310509930.9A CN116523345B (en) | 2023-05-08 | 2023-05-08 | Urban road topology network connectivity evaluation method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116523345A CN116523345A (en) | 2023-08-01 |
| CN116523345B true CN116523345B (en) | 2024-01-26 |
Family
ID=87391850
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310509930.9A Active CN116523345B (en) | 2023-05-08 | 2023-05-08 | Urban road topology network connectivity evaluation method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116523345B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117292547B (en) * | 2023-10-27 | 2024-05-07 | 重庆交通大学 | Method for evaluating connectivity of large-scale movable multistage influence area road network |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104392094A (en) * | 2014-10-17 | 2015-03-04 | 北京航空航天大学 | Reliability evaluation method of urban road network based on data of floating vehicles |
| CN106789744A (en) * | 2017-01-13 | 2017-05-31 | 重庆邮电大学 | Handled up resource regulating method with the height that time delay is perceived based on UNE virtualization |
| CN107181640A (en) * | 2017-05-03 | 2017-09-19 | 同济大学 | The acquisition methods of car networking connectedness index under a kind of urban road scene |
| CN107958094A (en) * | 2016-10-18 | 2018-04-24 | 武汉理工大学 | A kind of waters air route fragility research method based on Complex Networks Theory |
| CN108629974A (en) * | 2018-05-17 | 2018-10-09 | 电子科技大学 | Take the traffic circulation index method for building up of urban road traffic network feature into account |
| CN108752945A (en) * | 2018-05-23 | 2018-11-06 | 重庆交通大学 | High performance modified bitumen based on graphene and production method |
| CN108804593A (en) * | 2018-05-28 | 2018-11-13 | 西安理工大学 | The subgraph query method of undirected weighted graph based on collection of illustrative plates and reachable path number |
| CN109086910A (en) * | 2018-06-11 | 2018-12-25 | 北京工商大学 | Road network topology structure modelling method is runed in urban track traffic |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10277468B2 (en) * | 2015-04-10 | 2019-04-30 | Conduent Business Service, Llc | Method and system for determining reachability between one or more nodes in a graph |
-
2023
- 2023-05-08 CN CN202310509930.9A patent/CN116523345B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104392094A (en) * | 2014-10-17 | 2015-03-04 | 北京航空航天大学 | Reliability evaluation method of urban road network based on data of floating vehicles |
| CN107958094A (en) * | 2016-10-18 | 2018-04-24 | 武汉理工大学 | A kind of waters air route fragility research method based on Complex Networks Theory |
| CN106789744A (en) * | 2017-01-13 | 2017-05-31 | 重庆邮电大学 | Handled up resource regulating method with the height that time delay is perceived based on UNE virtualization |
| CN107181640A (en) * | 2017-05-03 | 2017-09-19 | 同济大学 | The acquisition methods of car networking connectedness index under a kind of urban road scene |
| CN108629974A (en) * | 2018-05-17 | 2018-10-09 | 电子科技大学 | Take the traffic circulation index method for building up of urban road traffic network feature into account |
| CN108752945A (en) * | 2018-05-23 | 2018-11-06 | 重庆交通大学 | High performance modified bitumen based on graphene and production method |
| CN108804593A (en) * | 2018-05-28 | 2018-11-13 | 西安理工大学 | The subgraph query method of undirected weighted graph based on collection of illustrative plates and reachable path number |
| CN109086910A (en) * | 2018-06-11 | 2018-12-25 | 北京工商大学 | Road network topology structure modelling method is runed in urban track traffic |
Non-Patent Citations (19)
| Title |
|---|
| Connectivity and Accessibility of the Railway Network in China: Guidance for Spatial Balanced Development;Jing Fan;Sustainability;全文 * |
| Research on Equilibrium Allocation Method of Urban Traffic Network based on Complex Network;Jianhua Liu;2022 IEEE International Conference on Advances in Electrical Engineering and Computer Applications (AEECA);全文 * |
| Roles of accessibility, connectivity and spatial interdependence in realizing the economic impact of high-speed rail: Evidence from China;Jingjuan Jiao;Transport Policy;全文 * |
| Vehicle-Trajectory Prediction Method for an Extra-Long Tunnel Based on Section Traffic Data;Ruru Xing;Sustainability;全文 * |
| 交通基础设施对区域经济增长的空间溢出效应研究——基于"长三角"区域数据分析;张阳阳;中国优秀硕士学位论文全文数据库经济与管理科学辑;全文 * |
| 可达性度量方法及应用研究进展评述;陈洁;陆锋;程昌秀;;地理科学进展(第05期);全文 * |
| 城市区域路网级联失效主动防控理论及方法研究;邢茹茹;中国博士学位论文全文数据库工程科技Ⅱ辑;全文 * |
| 城市的网络优势――中国互联网骨干网络结构与节点可达性分析;汪明峰;宁越敏;;地理研究(第02期);全文 * |
| 基于GIS的徐州市主城区交通道路网络可达性研究;王晓薇;奚砚涛;陶季奇;武金;;山西建筑(第14期);全文 * |
| 基于一种交通状态系数的城市路网交通状态评价研究;孙超;王波;张云龙;徐建闽;;公路交通科技(第05期);全文 * |
| 基于出行阻抗的公交网络连通性度量与优化;王成;中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑;全文 * |
| 基于通行能力的公路网连通度研究;邸振;查伟雄;宋晖颖;;华东交通大学学报(第04期);全文 * |
| 大城市中心区交通系统可靠性评价;周礼节;中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑;全文 * |
| 智能网联车环境下考虑反应时间影响的基本图模型;徐桃让;姚志洪;蒋阳升;杨涛;;公路交通科技(第08期);全文 * |
| 浙江省临安市山地型乡村绿道规划设计研究;张小凡;中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑;全文 * |
| 节点间有转向限制的网络最优路径算法;范昌胜;郭强;岳爱峰;;计算机工程与应用(第23期);全文 * |
| 车辆实时调度中的城市路网及交通描述模型;石建军, 宋延, 程世东;公路交通科技(第05期);全文 * |
| 面向城市路网级联失效的限流防控模型研究;邢茹茹;第十四届中国智能交通年会论文集;全文 * |
| 面向轨道交通站域协同发展的交通可达与空间使用绩效关系评价――以上海中心城区为例;张灵珠;庄宇;叶宇;;新建筑(第02期);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116523345A (en) | 2023-08-01 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN116523345B (en) | Urban road topology network connectivity evaluation method | |
| CN101308555A (en) | Multi-mode optimal path selection method for public transport | |
| CN110111574B (en) | Urban traffic imbalance evaluation method based on flow tree analysis | |
| CN105841709B (en) | A kind of running car paths planning method | |
| CN101149268A (en) | Road topology data model for navigation and calculation method | |
| CN109918819B (en) | Bayesian network-based large-scale bridge network evaluation method | |
| CN102436466A (en) | Bus transfer inquiry method based on geographic information system (GIS) classification | |
| CN110619426B (en) | Road network model construction method, device, equipment and storage medium | |
| CN102880641B (en) | Parametric bus transfer method in consideration of short-distance walking station pair | |
| CN104391907A (en) | Variable resolution rapid path searching method | |
| CN104617985A (en) | Method and device for route optimization of power communication network based on ant colony algorithm | |
| CN114815802A (en) | Unmanned overhead traveling crane path planning method and system based on improved ant colony algorithm | |
| CN102436481A (en) | Automatic identification method for road network structure mode | |
| CN105471749A (en) | Order-flexible low diameter large scale interconnection network topological structure and routing method thereof | |
| CN115100867B (en) | Urban intelligent traffic simulation method based on digital twins | |
| CN114117700A (en) | Urban public transport network optimization research method based on complex network theory | |
| CN105225004A (en) | The construction method of group of cities inter-city passenger rail gauze | |
| CN105577539A (en) | Routing method and system for non-regular three-dimensional integrated circuit network-on-chip | |
| CN110807931A (en) | Traffic network directed graph path model construction and solving method based on steering relation | |
| CN104239965A (en) | Large-scale road network double-layer routing method based on overlap community partitioning | |
| CN116611586A (en) | Newly built road network flow prediction method and system based on double-layer heterogeneous network | |
| CN109887280B (en) | Traffic network node criticality assessment method | |
| CN104915731A (en) | Vehicle travel path reconstruction macro/micro integrated new method based on automatic vehicle identification data | |
| CN111337047A (en) | Unstructured road macroscopic path planning method based on multi-task point constraint | |
| CN114353816A (en) | Multi-vehicle path planning method under 5G networking in Jobshop |
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 |