CN113780674A - Method and device for researching travel path and readable storage medium - Google Patents
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Abstract
The embodiment of the application provides a method and a device for researching a travel path and a readable storage medium, and belongs to the technical field of traffic big data analysis. The method comprises the following steps: dividing a plurality of traffic cells according to the trunk network; acquiring a traffic start and stop point OD data set; according to the traffic cells passed by the OD connecting lines, the expected traffic travel is distributed to travel paths of adjacent traffic cells; and generating a traffic spider-web graph according to the travel path and the assigned weight of the travel path. By adopting the scheme, the drawing by using a special tool can be avoided, and the cost is saved; meanwhile, the scheme does not need to collect a large amount of traffic impedance data and survey data, and is particularly practical when the traffic impedance data and the detailed travel survey data are lacked and the urban travel main channel is urgently needed to be researched; the method has reference significance for the traffic planning research of the urban rail transit with the low traffic impedance coefficient.
Description
Technical Field
The embodiment of the application relates to the technical field of traffic big data analysis, in particular to a method and a device for researching a travel path and a readable storage medium.
Background
The travel expectation line is a straight line connecting the centers of gravity of all the cells of the city, and the width of the travel expectation line shows the expected amount of the row quantity, and can reflect the traffic demand, so the travel expectation line has a more important role in traffic line network planning. However, the expected number of lines for traveling is huge, and the lines are disorganized and unintuitive, which brings difficulties to analysis.
Aiming at the problems, a spider-web diagram can be adopted, the spider-web diagram is used for distributing the expected traffic travel of each cell to the travel paths of adjacent cells, the passenger flow trend demand of the city can be reflected more visually, and a traffic planner can study the main travel channel of the city and assist the traffic line network planning. However, the construction of existing spider-web maps is complex, time consuming, costly, and requires a large volume of traffic impedance data and survey data.
Disclosure of Invention
The embodiment of the application aims to provide a method, a device and a readable storage medium for researching a travel path, and solves the problems of complex construction, time consumption and high cost of the existing spider-web graph.
In order to solve the technical problem, the present application is implemented as follows:
in a first aspect, an embodiment of the present application provides a method for researching a travel path, where the method includes:
dividing a plurality of traffic cells according to the trunk network;
acquiring a traffic start and stop point OD data set;
according to the traffic cells passed by the OD connecting lines, distributing the expected traffic travel to travel paths of adjacent traffic cells;
and generating a traffic spider-web map according to the travel path and the distribution weight of the travel path.
In some embodiments, assigning the travel expectation to a travel path of an adjacent traffic cell according to the traffic cell passed by the OD link comprises:
intersecting the OD connecting line with the plurality of traffic zones to obtain a plurality of target line segments;
acquiring the midpoint of each target line segment;
sorting the midpoints according to longitude and latitude coordinates to obtain an ordered cell list;
filtering non-adjacent traffic cells from the ordered cell list to obtain a plurality of adjacent traffic cells;
and sequentially counting the weights of the adjacent traffic districts to obtain the travel path of the adjacent traffic districts.
In some embodiments, intersecting the OD connection with the plurality of traffic zones to obtain a plurality of target line segments includes:
acquiring geometric topologies of the plurality of traffic cells and a first cell list corresponding to the plurality of traffic cells, wherein the first cell list comprises a correspondence between traffic cell IDs and the geometric topologies of the traffic cells;
and intersecting the OD connecting line with the geometric topology of the plurality of traffic cells to obtain the plurality of target line segments and a second cell list of the cell list corresponding to the plurality of target line segments.
In some embodiments, filtering out non-neighboring traffic cells from the ordered list of cells results in a plurality of neighboring traffic cells, comprising:
acquiring an adjacency list of the plurality of traffic cells;
performing weight counting on cells in the ordered cell list;
and filtering non-adjacent traffic cells from the ordered cell list according to the adjacency list to obtain the plurality of adjacent traffic cells.
In a second aspect, an embodiment of the present application provides an apparatus for studying a travel path, where the apparatus includes:
the dividing module is used for dividing a plurality of traffic cells according to the trunk network;
the acquisition module is used for acquiring an OD data set;
the distribution module is used for distributing the expected traffic travel to travel paths of adjacent traffic cells according to the traffic cells passed by OD connecting lines;
and the generating module is used for generating a traffic spider-web map according to the travel path and the assigned weight of the travel path.
In some embodiments, the assignment module is further configured to:
intersecting the OD connecting line with the plurality of traffic cells to obtain a plurality of target line segments;
acquiring the midpoint of each target line segment;
sorting the midpoints according to longitude and latitude coordinates to obtain an ordered cell list;
filtering non-adjacent traffic cells from the ordered cell list to obtain a plurality of adjacent traffic cells;
and sequentially counting the weights of the adjacent traffic districts to obtain the travel path of the adjacent traffic districts.
In some embodiments, the assignment module is further configured to:
acquiring geometric topologies of the plurality of traffic cells and a first cell list corresponding to the plurality of traffic cells, wherein the first cell list comprises a correspondence between traffic cell IDs and the geometric topologies of the traffic cells;
and intersecting the OD connecting line with the geometric topology of the plurality of traffic cells to obtain the plurality of target line segments and a second cell list of the cell list corresponding to the plurality of target line segments.
In some embodiments, the intersection module is further configured to:
acquiring an adjacency list of the plurality of traffic cells;
performing weight counting on cells in the ordered cell list;
and filtering non-adjacent cells from the ordered cell list according to the adjacency list to obtain the plurality of adjacent cells.
In a third aspect, an embodiment of the present application provides an apparatus for studying a travel path, including a processor, a memory, and a program or instructions stored on the memory and executable on the processor, where the program or instructions, when executed by the processor, implement the steps of the method for studying a travel path according to the first aspect.
In a fourth aspect, the present application provides a readable storage medium, on which a program or instructions are stored, which when executed by a processor implement the steps of the method for studying a travel path according to the first aspect.
In the embodiment of the application, an OD connecting line is determined through an OD data set, a travel path is obtained by using the intersection of the OD connecting line and a traffic cell, and then a traffic spider-web map is drawn through the travel path. By adopting the scheme, the drawing by using a special tool can be avoided, and the cost is saved; in addition, the scheme can be executed by compiling scripts, so that the drawing of the spider-web graph can be rapidly completed when a large amount of OD data are faced, and the efficiency is improved; meanwhile, the scheme does not need to collect a large amount of traffic impedance data and survey data, and is particularly practical when the traffic impedance data and the detailed travel survey data are lacked and the urban travel main channel is urgently needed to be researched; the method has reference significance for the traffic planning research of the urban rail transit with the low traffic impedance coefficient.
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Fig. 1 is a schematic flowchart of a method for researching a travel path according to an embodiment of the present application;
fig. 2 is a second schematic flowchart of a method for researching a travel route according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of an apparatus for studying a travel path according to an embodiment of the present application;
fig. 4 is a second schematic structural diagram of an apparatus for studying a travel path according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some, but not all, embodiments of the present application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terms first, second and the like in the description and in the claims of the present application are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that embodiments of the application may be practiced in sequences other than those illustrated or described herein, and that the terms "first," "second," and the like are generally used herein in a generic sense and do not limit the number of terms, e.g., the first term can be one or more than one. In addition, "and/or" in the specification and claims means at least one of connected objects, a character "/" generally means that a preceding and succeeding related objects are in an "or" relationship.
To better understand the solution of the present application, the following is first described:
the existing creation of spider-web images often requires the use of specialized expensive tools, such as TransCAD, whose rough steps are as follows:
1. and dividing the cells according to the main road network.
2. The cell travel matrix is constructed according to the gravity model, and the traffic impedance data and detailed travel survey data (such as travel distance, travel time, travel cost, travel behaviors and the like) need to be considered, and the cell travel matrix is simplified into the distance between the weight/center of each cell in the absence of the data.
3. An OD data set is obtained.
4. And for each OD data, solving the shortest path between the ODs by utilizing Dijkstra and other algorithms according to the cell travel matrix to obtain the travel path of the primary adjacent cell.
5. And obtaining and rendering spider-web graph data.
Therefore, the existing scheme is complex, time-consuming and high in cost, needs a large amount of traffic impedance data and detailed survey data, cannot completely reflect the travel demand even if the data are generated, and only provides reference for a traffic planner to research city travel main channels. Therefore, a simple, rapid and low-cost cobweb map construction system and method are needed to provide reference for traffic planners to research city travel main channels.
The method for studying a travel route provided by the embodiment of the present application is described in detail below with reference to the accompanying drawings through specific embodiments and application scenarios thereof.
Referring to fig. 1, an embodiment of the present application provides a method for researching a travel path, where the method includes:
step 101: dividing a plurality of traffic cells according to the trunk network;
step 102: obtaining an OD data set;
in the embodiment of the present application, an Origin-Destination (OD) data set refers to a travel data set with a longitude and latitude of a start point, and the OD data set includes a plurality of OD data.
Step 103: according to the traffic cells passed by the OD connecting lines, the expected traffic travel is distributed to travel paths of adjacent traffic cells;
in the present embodiment, an OD link refers to a link between a start point and an end point in one OD data.
Compared with the prior art that the shortest path of the gravity model is taken as a basis for distribution, in the embodiment of the application, for each piece of OD data, the expected travel of traffic is distributed to the travel path of the adjacent traffic cell by taking the cell through which the OD connecting line passes as a basis.
In some embodiments, allocating the travel expectation to the travel path of the adjacent traffic cell according to the traffic cell passed by the OD connection line comprises:
(1) intersecting the plurality of OD connecting lines with the plurality of traffic cells to obtain a plurality of target line segments;
in the embodiment of the application, the intersection of the OD connecting lines and the traffic cells of the approaches can obtain the target line segments, so that a plurality of target line segments can be obtained after the intersection of all the OD connecting lines and the corresponding traffic cells.
Further, in some embodiments, intersecting a plurality of OD links with a plurality of traffic cells to obtain a plurality of target line segments includes:
(1.1) acquiring geometric topologies of a plurality of traffic cells and a first cell list corresponding to the plurality of traffic cells, wherein the first cell list comprises a corresponding relation between traffic cell IDs and geometric topologies (graphs) of the traffic cells, and specifically, the cell ID list and the geometric topologies (including longitude and latitude coordinates) of the cells are in one-to-one correspondence;
and (1.2) intersecting the OD connecting line with the geometric topology of the plurality of traffic cells to obtain a plurality of target line segments and a second cell list of the cell list corresponding to the plurality of target line segments.
(2) Acquiring the midpoint of each target line segment;
(3) sorting the intermediate points according to longitude and latitude coordinates to obtain an ordered cell list;
in the embodiment of the application, the midpoints of all the line segments are obtained and sorted according to the longitude and latitude coordinates, and a corresponding ordered cell list is obtained.
(4) Filtering non-adjacent traffic cells from the ordered cell list to obtain a plurality of adjacent traffic cells;
(5) and sequentially counting the weights of the adjacent traffic districts to obtain the travel path of the adjacent traffic districts.
In the embodiment of the application, non-adjacent traffic cells are filtered, only adjacent traffic cells are reserved, and the travel path is determined based on the target line segments in the adjacent cells.
Further, in some embodiments, filtering out non-neighboring cells from the ordered list of cells to obtain a plurality of neighboring cells comprises:
(5.1) obtaining an adjacency list of a plurality of traffic cells, wherein the adjacency list can be a traffic cell adjacency list or a matrix;
(5.2) carrying out weight counting on the cells in the ordered cell list, for example, for a trip accumulation 1, the thickness of lines rendered by the spider-web graph is different according to different accumulated values of trips for each path;
and (5.3) filtering non-adjacent cells from the ordered cell list according to the adjacent list to obtain a plurality of adjacent cells.
Step 104: and generating a traffic spider-web graph according to the travel path and the assigned weight of the travel path.
In the embodiment of the application, a traffic spider-web map is rendered and drawn according to the obtained multiple travel paths.
In the embodiment of the application, an OD connecting line is determined through an OD data set, a travel path is obtained by using the intersection of the OD connecting line and a traffic cell, and then a traffic spider-web map is drawn through the travel path. By adopting the scheme, the drawing by using a special tool can be avoided, and the cost is saved; in addition, the scheme can be executed by compiling scripts, so that the drawing of the spider-web graph can be rapidly completed when a large amount of OD data are faced, and the efficiency is improved; meanwhile, the scheme does not need to collect a large amount of traffic impedance data and survey data, and is particularly practical when the traffic impedance data and the detailed travel survey data are lacked and the urban travel main channel is urgently needed to be researched; the method has reference significance for the traffic planning research of the urban rail transit with the low traffic impedance coefficient.
The method of the present application is described below with reference to specific examples:
referring to fig. 2, which shows a flow of the method of the present application, in this embodiment, Python may be used to develop a calculation script, and data is 1 million OD data sets for a certain city as an analysis object, and the specific steps are as follows:
1. and dividing traffic cells according to the existing trunk network.
2. A traffic cell geometric topology (graph) and a corresponding cell ID List1 are obtained.
3. And acquiring a traffic cell adjacency list/matrix.
4. The OD dataset is input.
5. And obtaining a straight line L according to the longitude and latitude of the starting point and the stopping point of each OD data.
6. Using the Pandas library, intersecting the straight line L with the whole geometric topology (graph) of the traffic cell to obtain a series of line segments and a List of corresponding cell IDs 2 (obtained through the corresponding relationship in step 2).
7. And acquiring midpoints of the line segments and sequencing the line segments to obtain a corresponding ordered cell ID List 3.
And sequentially counting the weight of the List3 cell, and filtering non-adjacent cells by using a traffic cell adjacency List to obtain the travel path of the primary adjacent cell.
8. And processing all OD data sets to obtain spider-web graph data and rendering.
Referring to fig. 3, an embodiment of the present application further provides an apparatus 300 for studying a travel path, where the apparatus includes:
a dividing module 301, configured to divide a plurality of traffic cells according to a trunk network;
an obtaining module 302, configured to obtain an OD data set;
the allocating module 303 is configured to allocate the expected travel route to a travel path of an adjacent traffic cell according to the traffic cell through which an OD connection line passes;
a generating module 304, configured to generate a traffic spider-web map according to the travel path and the assigned weight of the travel path.
In some embodiments, the allocation module is further configured to:
intersecting the OD connecting line with the plurality of traffic cells to obtain a plurality of target line segments;
acquiring the midpoint of each target line segment;
sorting the midpoints according to longitude and latitude coordinates to obtain an ordered cell list;
filtering non-adjacent traffic cells from the ordered cell list to obtain a plurality of adjacent traffic cells;
and sequentially counting the weights of the adjacent traffic districts to obtain the travel path of the adjacent traffic districts.
In some embodiments, the assignment module is further configured to:
acquiring geometric topologies of the plurality of traffic cells and a first cell list corresponding to the plurality of traffic cells, wherein the first cell list comprises a correspondence between traffic cell IDs and the geometric topologies of the traffic cells;
and intersecting the OD connecting line with the geometric topology of the plurality of traffic cells to obtain the plurality of target line segments and a second cell list of the cell list corresponding to the plurality of target line segments.
In some embodiments, the intersection module is further configured to:
acquiring an adjacency list of the plurality of traffic cells;
performing weight counting on cells in the ordered cell list;
and filtering non-adjacent cells from the ordered cell list according to the adjacency list to obtain the plurality of adjacent cells.
The apparatus for studying a travel path in the embodiment of the present application may be an apparatus, or may be a component, an integrated circuit, or a chip in a terminal. The device can be mobile electronic equipment or non-mobile electronic equipment. By way of example, the mobile electronic device may be a mobile phone, a tablet computer, a notebook computer, a palm top computer, a vehicle-mounted electronic device, a wearable device, an ultra-mobile personal computer (UMPC), a netbook or a Personal Digital Assistant (PDA), and the like, and the non-mobile electronic device may be a server, a Network Attached Storage (NAS), a Personal Computer (PC), a Television (TV), a teller machine or a self-service machine, and the like, and the embodiments of the present application are not particularly limited.
The device for researching the travel path in the embodiment of the present application may be a device having an operating system. The operating system may be an Android (Android) operating system, an ios operating system, or other possible operating systems, and embodiments of the present application are not limited specifically.
The device for researching a travel path provided in the embodiment of the present application can implement each process implemented by the method embodiments of fig. 1 to 2, and is not described herein again in order to avoid repetition.
Optionally, as shown in fig. 4, an apparatus 400 for researching a travel path is further provided in an embodiment of the present application, and includes a memory 401, a processor 402, and a program or an instruction stored in the memory 401 and executable on the processor 402, where the program or the instruction is executed by the processor 402 to implement each process of the above method for researching a travel path, and can achieve the same technical effect, and is not described herein again to avoid repetition.
It should be noted that the electronic devices in the embodiments of the present application include mobile electronic devices and non-mobile electronic devices.
The embodiment of the present application further provides a readable storage medium, where a program or an instruction is stored on the readable storage medium, and when the program or the instruction is executed by a processor, the program or the instruction implements each process of the above method for researching a travel path, and can achieve the same technical effect, and in order to avoid repetition, details are not repeated here.
The processor is the processor in the electronic device described in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and so on. It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element. Further, it should be noted that the scope of the methods and apparatus of the embodiments of the present application is not limited to performing the functions in the order illustrated or discussed, but may include performing the functions in a substantially simultaneous manner or in a reverse order based on the functions involved, e.g., the methods described may be performed in an order different than that described, and various steps may be added, omitted, or combined. In addition, features described with reference to certain examples may be combined in other examples.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present application.
While the present embodiments have been described with reference to the accompanying drawings, it is to be understood that the invention is not limited to the precise embodiments described above, which are meant to be illustrative and not restrictive, and that various changes may be made therein by those skilled in the art without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. A method of studying a travel path, the method comprising:
dividing a plurality of traffic cells according to the trunk network;
acquiring a traffic start and stop point OD data set;
according to the traffic cells passed by the OD connecting lines, distributing the expected traffic travel to travel paths of adjacent traffic cells;
and generating a traffic spider-web graph according to the travel path and the distribution weight of the expected traffic travel of the travel path.
2. The method of claim 1, wherein assigning the travel expectation to a travel path of an adjacent traffic cell according to the traffic cell traversed by the OD link comprises:
intersecting the OD connecting line with the plurality of traffic cells to obtain a plurality of target line segments;
acquiring the midpoint of each target line segment;
sorting the midpoints according to longitude and latitude coordinates to obtain an ordered cell list;
filtering non-adjacent traffic cells from the ordered cell list to obtain a plurality of adjacent traffic cells;
and sequentially counting the weights of the adjacent traffic districts to obtain the travel path of the adjacent traffic districts.
3. The method of claim 2, wherein intersecting the OD connection with the plurality of traffic cells to obtain a plurality of target line segments comprises:
acquiring geometric topologies of the plurality of traffic cells and a first cell list corresponding to the plurality of traffic cells, wherein the first cell list comprises a correspondence between traffic cell IDs and the geometric topologies of the traffic cells;
and intersecting the OD connecting line with the geometric topology of the plurality of traffic cells to obtain the plurality of target line segments and a second cell list of the cell list corresponding to the plurality of target line segments.
4. The method of claim 2, wherein filtering out non-neighboring traffic cells from the ordered list of cells to obtain a plurality of neighboring traffic cells comprises:
acquiring an adjacency list of the plurality of traffic cells;
performing weight counting on cells in the ordered cell list;
and filtering non-adjacent traffic cells from the ordered cell list according to the adjacency list to obtain the plurality of adjacent traffic cells.
5. An apparatus for studying a travel path, the apparatus comprising:
the dividing module is used for dividing a plurality of traffic cells according to the trunk network;
the acquisition module is used for acquiring an OD data set;
the distribution module is used for distributing the expected traffic travel to travel paths of adjacent traffic cells according to the traffic cells passed by OD connecting lines;
and the generating module is used for generating a traffic spider-web map according to the travel path and the distribution weight of the expected traffic travel of the travel path.
6. The apparatus of claim 5, wherein the assignment module is further configured to:
intersecting the OD connecting line with the plurality of traffic cells to obtain a plurality of target line segments;
acquiring the midpoint of each target line segment;
sorting the midpoints according to longitude and latitude coordinates to obtain an ordered cell list;
filtering non-adjacent traffic cells from the ordered cell list to obtain a plurality of adjacent traffic cells;
and sequentially counting the weights of the adjacent traffic districts to obtain the travel path of the adjacent traffic districts.
7. The apparatus of claim 6, wherein the assignment module is further configured to:
acquiring geometric topologies of the plurality of traffic cells and a first cell list corresponding to the plurality of traffic cells, wherein the first cell list comprises a correspondence between traffic cell IDs and the geometric topologies of the traffic cells;
and intersecting the OD connecting line with the geometric topology of the plurality of traffic cells to obtain the plurality of target line segments and a second cell list of the cell list corresponding to the plurality of target line segments.
8. The apparatus of claim 6, wherein the intersection module is further configured to:
acquiring an adjacency list of the plurality of traffic cells;
performing weight counting on cells in the ordered cell list;
and filtering non-adjacent cells from the ordered cell list according to the adjacency list to obtain the plurality of adjacent cells.
9. An apparatus for studying a travel path, comprising a processor, a memory, and a program or instructions stored on the memory and executable on the processor, the program or instructions, when executed by the processor, implementing the steps of the method for studying a travel path according to any one of claims 1 to 4.
10. A readable storage medium, on which a program or instructions are stored, which when executed by a processor, implement the steps of the method of studying a travel path according to any one of claims 1 to 4.
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| Publication number | Priority date | Publication date | Assignee | Title |
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