CN114898013A

CN114898013A - Traffic isochronal generation method, electronic device and storage medium

Info

Publication number: CN114898013A
Application number: CN202210829156.5A
Authority: CN
Inventors: 吕国林; 唐铠; 屈新明; 朱发玉; 吕锴超; 曹希雯
Original assignee: Shenzhen Urban Transport Planning Center Co Ltd
Current assignee: Shenzhen Urban Transport Planning Center Co Ltd
Priority date: 2022-07-15
Filing date: 2022-07-15
Publication date: 2022-08-12
Anticipated expiration: 2042-07-15
Also published as: CN114898013B

Abstract

The invention provides a traffic isochronous cycle generation method, electronic equipment and a storage medium, and belongs to the technical field of traffic simulation. The method comprises the following steps: s1, creating a road searching network according to a file transmitted by a user; s2, calculating shortest path and travel cost; s3, performing grid division according to a face area file transmitted by a user to obtain a grid center point coordinate; s4, predicting the travel overhead of each grid center; s5, carrying out level division on the stroke expenses corresponding to each grid; and S6, obtaining the surface area outline of the same expense grade, and rendering the surface area outline into a picture to obtain a traffic equal time circle. The method solves the technical problems of poor sensitivity, excessive dependence on a map API interface, lack of stability and more limitation on regional traffic analysis, urban work and residence separation, urban traffic convenience analysis, public service facility accessibility analysis and the like. The calculation efficiency is effectively improved; and has the characteristics of less required basic data, definite parameter meaning and high running speed.

Description

Traffic isochronous ring generation method, electronic device and storage medium

Technical Field

The present disclosure relates to an isochronous ring generating method, and more particularly, to a traffic isochronous ring generating method, an electronic device, and a storage medium, and belongs to the technical field of traffic simulation.

Background

With the development of times and industrial progress, the daily travel modes of people, such as automobiles, subways, conventional buses, bicycles, walking and the like, have more choices. Various vehicles further expand the travel range of residents, and the construction of conventional bus lines and rail networks is the main reason for the increase of the urban traffic passing radiation range. Therefore, the travel of the residents is the key point to be considered, and the travel distance is converted into the travel time length. In addition, due to the irregular arrangement of the lines and stations of the buses and the tracks and the difference of the running speeds of different bus lines and subway lines, the travel distance and the consumed travel time do not have a strong geometric growth relationship any more. In other words, it is not very clear from the length of the travel distance to determine which shorter the travel time from selecting different travel modes to a plurality of different destinations is, which causes a certain information obstruction to the travel decision of the residents.

The waiting time circle is an integrated expression of the travel duration on the time dimension and the space dimension, and the travel time spent in different travel modes reaching different destinations can be reflected intuitively. The isochronous ring is mostly composed of irregularly-shaped isochrones, the travel time cost of each point on the same isochrone is the same, and the time difference between two adjacent isochrones is the same. The larger the limit value of travel time of the equal hour circle is, the larger the equal hour circle range is. The time circles such as traffic and the like provide a more scientific and more intuitive method for the decision of resident travel.

The research and development personnel provide the following schemes aiming at the problems:

1. equal time circle generation method based on road network structure

The method for generating the equal time circle based on the road network structure constructs the road network structure according to the road information, wherein the road network structure comprises a plurality of roads and a plurality of road nodes. And then calculating the shortest time from the target position to each node of the road network, and calculating the travel overhead level corresponding to each road node according to the calculated shortest time. And finally, connecting time equivalence points, generating an isoline, smoothing the isoline, filling the isoline, and rendering to form an equal time circle. The method has the main defects that the main fitting object is a node on a road, the shortest time from the target position to a node on a non-road is roughly estimated only through the shortest time of the node, and a generated equal time circle has a large error with the actual time. Furthermore, the method does not specifically take into account differences in the topography of the terrain, such as: mountains or bodies of water beside some roads can be given inaccurate time, and even some inaccessible places without road networks can be given a value, so that the accuracy of circle construction during traffic and the like is further reduced.

2. Online map API-based isochronous ring generation method

The conventional map service mainly provides information such as point-to-point travel time. However, for the case of multiple destinations or uncertain destinations, and the pursuit of the shortest time within a limited time range, the conventional map service cannot provide a good travel decision. The method for generating the equal-time circles based on the online map API comprises the steps of firstly determining an equal-time circle analysis range, generating grid points based on the equal-time circle analysis range, then traversing the shortest time from a target position to each grid point position by relying on an API (application program interface) opened by a map, generating contour lines, and finally rendering to obtain the equal-time circles. The method can effectively generate the time circle which best accords with the actual traffic and the like, but has great defects: firstly, the calculation speed is influenced by the calling API speed, and when the calculation quantity is large, the calculation speed is obviously slow; secondly, the online map API interface has quota, and the access times of each account per day are limited, so that the large-scale equal-time-circle calculation cannot be performed.

The analysis and research of the scheme also has the following defects:

1. the equal-time circle generation method based on the road network structure is high in operability, but is poor in accuracy, and is poor in sensitivity on regional traffic analysis, urban work and stop separation, urban traffic convenience analysis, public service facility reachability analysis and the like.

2. The isochronous ring obtained by the online map API-based isochronous ring generation method is highly fit to the reality in theory, but in actual operation, the isochronous ring excessively depends on a map API interface, is lack of stability, has many limitations, and is difficult to solve at present.

In summary, the currently proposed isochronous ring generation method has the technical problems of poor sensitivity to regional traffic analysis, separation of urban work and residence, analysis of urban traffic convenience, analysis of accessibility of public service facilities and the like, excessive dependence on a map API interface, lack of stability and more limitations.

Disclosure of Invention

The following presents a simplified summary of the invention in order to provide a basic understanding of some aspects of the invention. It should be understood that this summary is not an exhaustive overview of the invention. It is not intended to determine the key or important part of the present invention, nor is it intended to limit the scope of the present invention. Its sole purpose is to present some concepts in a simplified form as a prelude to the more detailed description that is discussed later.

In view of the above, to solve the technical problems in the prior art, the present invention provides a traffic isochronal circle generation method, an electronic device, and a storage medium.

The first scheme is as follows: a traffic isochronal generation method comprises the following steps:

s1, creating a road searching network according to a file transmitted by a user;

s2, calculating shortest path and travel cost;

s3, performing grid division according to a face area file transmitted by a user to obtain a grid center point coordinate;

s4, predicting the travel cost of each grid center by using the kriging difference value;

s5, carrying out level division on the stroke expenses corresponding to each grid;

and S6, obtaining the surface area outline of the same overhead grade, and rendering the surface area outline into a picture to obtain a traffic equal time circle.

Preferably, the files transmitted by the user comprise a point layer file and a line layer file;

the method for creating the searched road network by the line level file comprises the steps of converting road networks in different directions into one-way road networks, reserving road topology starting point numbers, road topology key point numbers and weight fields specified by a user, and generating an edge list according to a column sequence transmitted by the user;

the method for creating the searched road network by the point layer file comprises the steps of obtaining longitude and latitude coordinates and a weight dictionary of each road topology number, and generating an edge node list;

and creating an undirected graph, namely the searched road network, according to the edge list and the edge node list.

Preferably, the method for calculating the shortest path includes searching a path by taking a designated node as a starting point, calculating shortest paths and distances from the starting point to all other nodes by using a Dijkstra algorithm, and obtaining a node id, a node longitude and latitude coordinate and a corresponding shortest path distance of each end point;

the method for calculating the travel cost comprises the steps that the created search road network is stored in the form of a directed graph, N nodes are arranged in the graph, and the travel cost from the node K to other N nodes or the travel cost from other N nodes to the node K can be obtained after the node K is calculated.

Preferably, the method for grid division according to the area files transmitted by the user is that the grid width input by the user is set to be L meters, the maximum longitude and latitude of the identified area are respectively max _ lon and max _ lat, the minimum longitude and latitude are respectively min _ lon and min _ lat, the central point of the area is Rcen, the coordinates are (center _ lon and center _ lat), the central transverse offset point Rcen- Δ x, the coordinates are (center _ lon + Δ lon and center _ lat), the central transverse offset point Rcen- Δ y and the coordinates are (center _ lon and center _ lat + Δ lat), and the step length of the longitude and latitude is determined as "step" and "lat _ step";

wherein, dis (R) ₁ ,R ₂ ) Representing the distance between two geographical coordinate points.

Preferably, the method for predicting the travel cost of each grid center by using the kriging difference value is to estimate the attribute value of an unknown point by using weighted summation of the attribute values of spatially known points, and the formula is expressed as:

wherein the content of the first and second substances,

is an unknown point

The estimated value of (c) is determined,

is a known point

The value of the attribute of (a) is,

are weight coefficients.

Preferably, the method for ranking the trip cost corresponding to each grid is to rank the grids according to the time interval set by the user and the trip cost value of the grid.

Preferably, the method for obtaining the face region contour of the same overhead level is,

s61, marking each grid with a Dx and Dy value, wherein the Dx and Dy represent the positions of the grids in a matrix;

s62, obtaining the maximum value max _ x of dx and the maximum value max _ y of dy according to the result of grid division, constructing a matrix of (max _ x + 3) × (max _ y + 3), initializing the matrix value to be 0, taking out grids with the same time _ level row for each time _ level value as the time _ level in the result of grid division is discrete and exhaustible, filling the corresponding position in the initialized matrix to be 1 according to the indexes of dx and dy, wherein all the filled grids belong to the same stroke overhead area;

s63, obtaining a binary image with a closed contour in a matrix construction result, traversing all grid points with a matrix value of 1, and adding the grid points into a boundary point disordered set Bdistorser if matrix values of the grid points in 8 neighborhoods of the grid points meet the following formula;

where N (i) represents the matrix values of the i neighborhood of the grid;

s64, arbitrarily selecting one B from the Bdissorders ₀ As search point, it is removed from Bdistor, added to Border in the ordered set of boundary points, and the grids whose matrix value is 1 in eight neighborhoods, in the set Bdistor and not in the set Border are searched in this way until returning to B ₀ And at the moment, judging whether the Bdissorder is empty or not, if so, indicating that only one face area exists, otherwise, indicating that a plurality of face areas exist, and executing the same searching step on the rest points in the set Bdissorder until the Bdissorder is empty, so that the boundary sequence point coordinates are obtained, and the face area outline can be directly generated.

Preferably, the method for converting the road network in different directions into the one-way road network comprises the following steps:

s11, determining a field for indicating the direction;

s12, link with the direction of topological forward, wherein the road topological starting point number and the road topological end point number are kept unchanged;

s13, a link with a topological reverse direction is used for interchanging the road topology starting point number and the road topology end point number;

s14, changing a link with a topological two-way direction into a link with a topological forward direction and a topological reverse direction, and changing the link into a link with a topological forward direction, wherein the field contents of the road topology starting point number and the road topology end point number are kept unchanged; and changing the topological reverse link into a topological reverse link, and interchanging the road topological starting point number and the road topological end point number.

Scheme II: an electronic device comprising a memory and a processor, the memory storing a computer program, the processor implementing the steps of a traffic isochronal circle generation method according to aspect one when executing the computer program.

The third scheme is as follows: a computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements a traffic isochron generation method according to one aspect.

The invention has the following beneficial effects: the invention provides a traffic isochronous ring generating method integrating road network construction, shortest path calculation, grid division, kriging interpolation and contour extraction algorithms and considering both accuracy and calculation efficiency; different road networks and surface area file generation equal time circles are supported, the shortest travel time between nodes is calculated based on the road network structure, and the calculation efficiency is effectively improved; according to the actual landform, the inaccessible area in the area file is processed, and then the equal-time circle is generated, so that the accuracy is greatly improved; the required basic data is less, the parameter meaning is clear, and the operation speed is high; the method solves the technical problems of poor sensitivity, excessive dependence on a map API interface, lack of stability and more limitation on regional traffic analysis, urban work and residence separation, urban traffic convenience analysis, public service facility accessibility analysis and the like.

Drawings

The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:

FIG. 1 is a schematic process flow diagram;

FIG. 2 is a schematic diagram of grid division;

FIG. 3 is a schematic diagram of matrix value filling;

FIG. 4 is a schematic diagram of a grid matrix within a neighborhood;

FIG. 5 is a schematic diagram of an unordered set of boundary points;

FIG. 6 is a schematic view of ordered boundary point acquisition;

FIG. 7 is a diagram illustrating rendering results after extracting contours;

FIG. 8 is a diagram illustrating rendering results after no contour extraction.

Detailed Description

In order to make the technical solutions and advantages of the embodiments of the present application more apparent, the following further detailed description of the exemplary embodiments of the present application with reference to the accompanying drawings makes it clear that the described embodiments are only a part of the embodiments of the present application, and are not exhaustive of all embodiments. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.

Example 1, the present embodiment is described with reference to fig. 1 to 8, and a traffic isochronal circle generation method includes the steps of: s1, creating a road searching network according to files transmitted by a user, wherein the files transmitted by the user comprise point layer files and line layer files;

and (3) creating a road searching network according to the point-level files and the line-level files transmitted by the user, wherein the field information of the transmitted road network is shown in the field information of the road network in the table 1.

TABLE 1 field information of road network

Name of field	Meaning of a field	Whether it is necessary or not
			link_id	Road segment numbering	Whether or not
from_node	Road topology starting point numbering	Is that
			to_node	Road topology end point numbering	Is that
dir	Road direction	Is that
			{weight_field}	Weight field	Is that

The method for creating the route searching network by the line level file comprises the steps of converting the road networks in different directions into one-way road networks, reserving from _ node, to _ node and a weight field specified by a user, and generating an edge list according to the sequence of columns transmitted by the user, wherein the edge list is used for creating a graph.

The method for converting the road networks in different directions into the one-way road network comprises the following steps:

s11, determining a field for indicating the direction; there are three cases of link directions, namely topology forward, topology reverse, and topology bidirectional.

S12, keeping the field contents of link, from _ node and to _ node with the direction of the topological forward unchanged;

s13, the link with the direction in the topological reverse direction exchanges the contents of the from _ node field and the to _ node field, namely the from _ node field is the content of the original to _ node field, and the to _ node field is the content of the original from _ node field;

s14, changing the link with the direction of topological bi-direction into two links of topological forward direction and topological reverse direction, and d) changing the link into two links of topological forward direction and topological reverse direction. Link, from node and to node fields that are instead topological forward remain unchanged; instead of a topologically reversed link, the from node and to node field contents are interchanged.

The method for creating the searched road network by the point layer file comprises the steps of obtaining longitude and latitude coordinates and a weight dictionary of each node, and generating an edge node list for creating a graph.

S2, calculating shortest path and travel cost;

the shortest path calculating method includes the steps that a specified node is used as a starting point to search paths, the Dijkstra algorithm is used for calculating the shortest paths and the distances from the starting point to all other nodes, and the node id, the node longitude and latitude coordinates and the corresponding shortest path distance of each end point are obtained;

the Dijkstra algorithm is a typical single-source shortest path algorithm, and uses breadth-first search for calculating the shortest path from one node to all other nodes in an assigned directed graph or undirected graph. The method is mainly characterized in that the expansion is carried out layer by layer outside by taking a starting point as a center until the expansion reaches a terminal point. The principle of the Dijkstra algorithm is: under the condition of an adjacency matrix (an undirected graph or a weighted graph) of a known graph, a set of all points is divided into two parts, one part is traversed, and the other part is not traversed and is respectively represented. Firstly, giving initial values (infinity) and unmarked), then independently giving path weights communicated by the source points (x), temporarily determining the path weights as communicated points as the shortest path to be marked, namely traversing; the method comprises the steps of continuously traversing all nodes, traversing all paths of a known graph, finding the path with the minimum weight in the communication paths (the points of the connected lines) which traverse to the points, marking the traversal points, continuously judging and replacing in circulation, correcting the shortest path, and obtaining the real minimum value, namely the shortest path, in continuous correction.

The data structure as follows is obtained:

name of field	Meaning of a field	Whether it is necessary or not
			node_id	Node numbering	Is that
travel_cost	Travel overhead	Is that

the grid division method according to the face domain file transmitted by the user comprises the steps of setting the grid width input by the user to be L meters, identifying the maximum longitude and latitude of the area to be max _ lon and max _ lat respectively, identifying the minimum longitude and latitude to be min _ lon and min _ lat respectively, setting the central point of the area to be Rcen, setting the coordinates to be (center _ lon and center _ lat), setting the central transverse offset point Rcen-delta x, setting the coordinates to be (center _ lon + delta lon and center _ lat), setting the central transverse offset point Rcen-delta y and setting the coordinates to be (center _ lon and center _ lat + delta lat), and determining the step length of the longitude and latitude to be in a length of lon _ step and lat _ step;

wherein, dis (R) ₁ ,R ₂ ) Representing the distance between two geographical coordinate points. To facilitate subsequent contour extraction, each grid is labeled with a dx and dy value, which, as shown in fig. 2, represent the position in the matrix where the grid is located.

The following data structure results:

name of field	Meaning of a field	Whether it is necessary or not
			grid_id	Grid numbering	Is that
cen_lon	Grid center point longitude	Is that
			cen_lat	Grid center point latitude	Is that
dx	Matrix index column number	Is that
			dy	Matrix index row number	Is that

Specifically, the longitude step and the latitude step can be uniquely determined according to the length and the width of the grid input by the user.

S4, predicting the travel cost of each grid center by using the Kerrin difference value, training a common Kerrin model by using shortest path cost data obtained by path searching as a training set, setting a variation function by a user through a variogram _ model, providing linear, power, gaussian, statistical, exponemental and hole-effect models for the user to select, defaulting to the linear model, and simultaneously supporting the user to change nlags parameters to set the lag distance of the variation function so as to adjust the variation function value, and defaulting to nlags = 6. And using the coordinates of the grid center points as input, and using the trained model to predict to obtain the shortest-circuit overhead data corresponding to each grid point.

The method specifically comprises that the kriging interpolation is to estimate the attribute value of an unknown point by using the weighted summation of the attribute values of the known points on the space, and the formula is expressed as follows:

wherein the content of the first and second substances,

is an unknown point

The estimated value of (c) is determined,

is a known point

The value of the attribute of (a) is,

are weight coefficients.

And the weight coefficients need to satisfy two conditions: firstly, satisfy unbiased estimation, secondly, estimate value

And true value

The error of (2) is minimal. Namely:

ordinary kriging applies to regionalized variables, assuming uniform spatial properties, any point in the space has the same expectation and variance, i.e. for any point:

in other words, the attribute value of an arbitrary point

From the area mean value

And random deviation from that point

The composition is as follows:

wherein the content of the first and second substances,

is constant

Namely:

for unbiased estimation constraints, the formula

And substituting, then:

and for any point have

Then:

namely obtain

One of the constraints of (1):

for estimation error

Comprises the following steps:

order to

Wherein

I.e. the deviation of the property value at an unknown point from the average value of the property of the region. The estimated bias can be simplified to:

for the variation function, let the half-variance function be

The equivalent forms are:

the procedure was demonstrated as follows:

by

Is provided with

Then equation (11) is modified as:

among them, there are:

thus, there are:

from the first law of geography, it can be known that spatially similar attributes are similar.

Can represent the similarity of the attributes; spatial similarity may be measured in distance

Expressed, its expression is:

kriging interpolation hypothesis

And

functional relationships exist, which may be linear, quadratic, exponential, logarithmic, and the like. Calculating the distance between any two points in the known data set

Sum half-variance

To obtain

An

And (4) data pairs. All will be

And

drawing a scatter diagram, searching an optimal curve capable of fitting the scatter point to obtain a functional relation

. I.e. for different lag distances

To find each

The variation function value of.

According to the half-variance function, the estimated deviation is:

substitution formula

The following can be obtained:

because of the estimated error

Minimum, while satisfying the formula

This is an optimization problem with constraints. Using a Lagrange multiplier method to solve, and setting a Lagrange objective function as:

wherein the content of the first and second substances,

is the lagrange multiplier. By the above-mentioned formula pair

And

and solving the partial derivative to obtain a Kriging equation set, wherein the partial derivative is equal to zero, namely:

will be a formula

And formula

Substituting, simplifying to obtain:

due to the fact that

Thus, therefore, it is

And then:

solving the above formula to obtain the weight coefficient

And lagrange constant

. Writing in a matrix form is:

solving the weight coefficient by inverting the matrix

。

Inputting the time overhead step cost _ step, the following data structure is obtained:

name of field	Meaning of a field	Whether it is necessary or not
			grid_id	Grid numbering	Is that
travel_cost	Travel overhead	Is that
			tim_level	Travel overhead level	Is that

And S5, carrying out grade division on the stroke expenses corresponding to each grid, and carrying out grade division on the grids according to the time interval set by the user and the stroke expense values of the grids. The time interval unit supports hour, minute and second, and the default time interval is 5 minutes. For example, the travel cost is 0-5 minutes corresponding to the level 1, 5-10 minutes corresponding to the level 2, and so on, the traffic 5-minute and other time circle data of the designated node can be obtained.

S6, obtaining the surface area outline of the same expense grade, and rendering the surface area outline into a picture to obtain a traffic equal time circle, wherein the method specifically comprises the following steps:

and S62, obtaining the maximum value max _ x of dx and the maximum value max _ y of dy according to the result of grid division, constructing a matrix of (max _ x + 3) × (max _ y + 3), initializing the matrix value to be 0, taking out grids with the same time _ level column for each time _ level value as the time _ level in the result of grid division is discrete and exhaustible, filling the corresponding positions in the initialized matrix to be 1 according to the indexes of dx and dy, wherein all the filled grids belong to the same stroke overhead area, and refer to FIG. 3.

S63, obtaining a binary image with a closed contour in a matrix construction result, traversing all grid points with a matrix value of 1, and adding the grid points into a boundary point disordered set (refer to FIG. 5) Bdistorser if grid point matrix values in eight neighborhoods (refer to FIG. 4) meet the following formula;

where N (i) represents the matrix values of the i neighborhood of the grid;

s64, arbitrarily selecting one B from the Bdissorders ₀ As a search point, the search point is simultaneously removed from the Bdistorser, added to the Border in the boundary point ordered set, and the grids which have the matrix value of 1 in the eight neighborhoods, are in the Bdistorser set and are not in the Border set are retrieved (if a plurality of alternative grids preferentially select the grid points in the 1, 3, 6 and 8 neighborhoods), and searched in this way until the search returns to the B ₀ At this time, judging whether the Bdissorder is empty or not is executed, if the Bdissorder is empty, the situation shows that only one face area is available, if the Bdissorder is not empty, the situation shows that a plurality of face areas exist, the same searching steps are executed on the rest points in the set Bdissorder until the Bdissorder is empty, at this time, the boundary sequence point coordinates are obtained, and the face areas can be directly generatedOutline, refer to fig. 6.

Rendering the images to obtain time rings of traffic and the like, and obtaining the time rings of traffic and the like which are directly rendered without extracting the outlines and the time rings of traffic and the like which are rendered after extracting the outlines by referring to fig. 7 and fig. 8, wherein the time rings of traffic and the like which are rendered after extracting the outlines have the characteristic of vectorization layers compared with the time rings of traffic and the like which are directly rendered without extracting the outlines, and lossless amplification and reduction can be performed.

Abbreviations and key terms

Waiting for time circle: the space range which can be reached in a certain time by taking a certain place as a stroke starting point and different travel modes. The time-consuming substitution of the distance by the traffic is carried out in the waiting time, the actual use habit is better met, the traffic convenience degree of one area can be visually reflected, and the method is greatly helpful for regional traffic analysis, reachability analysis of public transport service facilities, convenience degree analysis of urban traffic and the like.

Interpolation: on the basis of known limited discrete data point information, a mapping relation is established between a space domain and an attribute domain of the sample points by researching the attribute information of the sample points by using corresponding analytical research models, the mapping relation is quantified, and finally, the value of an unknown point is estimated on the basis of the established mapping relation. In short, interpolation is a method for predicting the point value of unknown data according to a plurality of known data. Interpolation is an important method of discrete function approximation.

Kriging interpolation (Kriging): the kriging interpolation is firstly proposed by south Africa mine engineers D.G.Krige, and then is optimized by French geography mathematician Matheron, so that the method is a practical space estimation technology. The method is based on the theory of a variation function and structural analysis and carries out unbiased optimal estimation on regional variables in a limited region. The kriging interpolation method can be carried out in two steps, and firstly, the known points around the point to be interpolated are determined to be selected for carrying out weighted interpolation calculation. And then carrying out variability analysis on the selected known points to obtain a variation function, further constructing a Krigin equation set, and obtaining the attribute value of the point to be interpolated by using the weight coefficient.

Regionalized variables: all things in nature have spatial characteristics such as air temperature, air pressure, temperature, humidity, and the like. The natural phenomena of different areas at the same time show certain structural characteristics and random characteristics in space. Therefore, when the observed value shows different characteristics with the change of the spatial position and shows a certain spatial distribution, such a variable is called a regionalized variable. In short, it is a variable related to spatial position. There is some spatial regularity between regionalized variables at different spatial locations, and these random variables are spatially correlated.

Function of variation: one half of the variance of the difference between the values of a geological variable at two locations in space is typically defined as the variogram. The variation function is a mathematical tool specific to geostatistics, and can describe the spatial structure variation of a regionalized variable and can also describe the random variation of the regionalized variable. Conventional variogram models include exponential, spherical, and gaussian models. The index model is suitable for the river channel type geological conditions, and the generated result is relatively high in randomness; the spherical model is suitable for large-scale river channels and relatively stable delta deposition environments, and has moderate relative randomness; the Gaussian model is suitable for stable deposition environments such as sea and lake and has the best continuity. The area variables used in the actual work are selected and combined from the above three models, wherein spherical models are more used.

In embodiment 2, the computer device of the present invention may be a device including a processor, a memory, and the like, for example, a single chip microcomputer including a central processing unit, and the like. And the processor is used for implementing the steps of the recommendation method capable of modifying the relationship-driven recommendation data based on the CREO software when executing the computer program stored in the memory.

The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.

Embodiment 3 computer-readable storage Medium embodiment

The computer readable storage medium of the present invention may be any form of storage medium that can be read by a processor of a computer device, including but not limited to non-volatile memory, ferroelectric memory, etc., and the computer readable storage medium has stored thereon a computer program that, when the computer program stored in the memory is read and executed by the processor of the computer device, can implement the above-mentioned steps of the CREO-based software that can modify the modeling method of the relationship-driven modeling data.

The computer program comprises computer program code which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.

While the invention has been described with respect to a limited number of embodiments, those skilled in the art, having benefit of this description, will appreciate that other embodiments can be devised which do not depart from the scope of the invention as described herein. Furthermore, it should be noted that the language used in the specification has been principally selected for readability and instructional purposes, and may not have been selected to delineate or circumscribe the inventive subject matter. Accordingly, many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the appended claims. The present invention has been disclosed in an illustrative rather than a restrictive sense, and the scope of the present invention is defined by the appended claims.

Claims

1. A traffic isochronal generation method is characterized by comprising the following steps:

s2, calculating shortest path and travel cost;

s3, performing raster division according to a face area file transmitted by a user to obtain a coordinate of a raster center point;

and S6, obtaining the surface area outline of the same expense grade, and rendering the surface area outline into a picture to obtain a traffic equal time circle.

2. The traffic isochronal circle generation method according to claim 1, wherein the files transmitted by the user comprise point layer files and line layer files;

3. The method for generating traffic isochronous circles according to claim 2, wherein the method for calculating shortest paths is to search for routes with a designated node as a starting point, calculate shortest paths and distances from the starting point to all other nodes by using Dijkstra algorithm, and obtain node id, node longitude and latitude coordinates and corresponding shortest path distances of each end point;

the method for calculating the travel cost comprises the steps of storing the created searched road network in the form of a directed graph, setting N nodes in the graph, and obtaining the travel cost from the node K to other N nodes or the travel cost from other N nodes to the node K after the node K is specified and calculated.

4. The method of claim 3, wherein the grid division is performed according to the area files inputted by the user, the grid width inputted by the user is set as L meters, the maximum longitude and latitude of the identified area are max _ lon and max _ lat, the minimum longitude and latitude are min _ lon and min _ lat, the central point of the area is Rcen, the coordinates are (center _ lon and center _ lat), the central lateral offset point Rcen- Δ x, the coordinates are (center _ lon + Δ lon and center _ lat), the central lateral offset point Rcen- Δ y and the coordinates are (center _ lon and center _ lat + Δ lat), the step sizes of the longitude and latitude are determined as lon _ step and lat _ step;

5. The method as claimed in claim 4, wherein the method for predicting the travel cost of each grid center by using the kriging difference is to estimate the attribute value of the unknown point by weighted summation of the attribute values of the spatially known points, and the formula is expressed as:

wherein the content of the first and second substances,

is an unknown point

The estimated value of (c) is determined,

is a known point

The value of the attribute of (a) is,

are weight coefficients.

6. The method of claim 5, wherein the step of ranking the travel cost corresponding to each grid is performed by ranking the grids according to the time interval set by the user and the travel cost value of the grid.

7. The method of claim 6, wherein the method of obtaining the area contour of the same cost level is,

where N (i) represents the matrix values of the i neighborhood of the grid;

s64, arbitrarily selecting one B from the Bdissorders ₀ As search points, they are simultaneously removed from the Bdissorder, added to Border in the ordered set of boundary points, and the grids whose matrix value is 1 in the eight neighborhoods, are in the set Bdissorder and are not in the set Border are searched in this way until returning to B ₀ And at the moment, judging whether the Bdissorder is empty or not, if so, indicating that only one face area exists, otherwise, indicating that a plurality of face areas exist, and executing the same searching step on the rest points in the set Bdissorder until the Bdissorder is empty, so that the boundary sequence point coordinates are obtained, and the face area outline can be directly generated.

8. The method for generating traffic isochronal circle according to claim 7, wherein the method for converting road networks in different directions into one-way road networks comprises the following steps:

s11, determining a field for indicating the direction;

s13, a link with a topological reverse direction is adopted, and the road topological starting point number and the road topological end point number are exchanged;

9. Electronic device, characterized in that it comprises a memory and a processor, the memory storing a computer program, the processor implementing the steps of a traffic isochron generation method according to any one of claims 1 to 8 when executing said computer program.

10. Computer readable storage medium, on which a computer program is stored, which computer program, when being executed by a processor, carries out a traffic isochron generation method as claimed in any one of claims 1 to 8.