CN112766567A - Method, system and storage medium for evaluating urban road network planning implementation effect - Google Patents
Method, system and storage medium for evaluating urban road network planning implementation effect Download PDFInfo
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Abstract
The application relates to an evaluation method, a system and a storage medium for urban road network planning implementation effect, which solve the defect that an evaluation system for urban road network planning implementation effect only evaluates the passing function reliability, and comprises the following steps of respectively calculating the weight value of each road section through a pre-established weight formula based on the predicted number of traffic accidents in unit time of the road sections of different types and the passing function reliability of the road sections of different types; and taking the sum of the weight values of all the road sections on the road network as an evaluation value of the road network, and highlighting the imported road network planning graph mark and the evaluation value. The method and the device can perform comprehensive quantitative analysis on the road network planning map from two angles of the number of the traffic accidents in unit time and the reliability of the function, more reasonably evaluate the applicability of different road network layout forms, and provide higher reference value for the design and optimization decision of the urban road network planning scheme.
Description
Technical Field
The application relates to the technical field of urban planning evaluation methods, in particular to an evaluation method, a system and a storage medium for urban road network planning implementation effect.
Background
The urban road network is a framework for urban construction and is also a carrier for urban traffic; plays an important role in urban construction and social and economic development and influences the daily life of residents.
The existing evaluation system for urban road network planning implementation effect quantitatively evaluates the applicability of different urban road network layout forms mainly according to the passing functional reliability of road segment units, and provides reference value for the design and optimization decision of urban road network planning schemes, and the specific use mode is as follows: after a user imports a road network planning graph designed by the user aiming at a destination, an evaluation system of urban road network planning implementation effect quantitatively evaluates the functional reliability of the road network planning graph imported by the user through a built-in through-function reliability evaluation system, outputs a numerical value of through-function reliability, compares the numerical value of the functional reliability of the imported road network planning graph at this time with a result of comparison of the numerical values of the functional reliability of the historically imported road network planning graph, sorts the results according to the comparison result and displays the results to the user for viewing.
In view of the above-mentioned related technologies, the inventor considers that there is a defect that whether the design of the road network planning is reasonable or not has an important influence on the road traffic safety because the factors related to the roads occupy a considerable proportion in the influence of various factors on the traffic accident, and the current evaluation system for the implementation effect of the urban road network planning only evaluates the reliability of the passing function and has room for improvement.
Disclosure of Invention
In order to more reasonably evaluate the applicability of different road network layout forms and provide higher reference value for the design and optimization decision of an urban road network planning scheme, the application provides an evaluation method and system for the implementation effect of urban road network planning and a storage medium.
In a first aspect, the present application provides a method for evaluating an implementation effect of urban road network planning, which adopts the following technical scheme:
a method for evaluating the implementation effect of urban road network planning comprises the following steps:
acquiring a road network planning graph which is designed aiming at a target and is imported into an evaluation system of an urban road network planning implementation effect by a user;
the method comprises the steps that road sections on a road network planning graph are subjected to type division, and the road sections on the road network planning graph are defined to be different in types;
respectively predicting the times of traffic accidents of different types of road sections on a road network planning graph in unit time, and meanwhile, analyzing and calculating the passing function reliability of the different types of road sections by using a pre-constructed road section passing reliability model;
respectively calculating the weight value of each road section through a pre-constructed weight formula based on the predicted number of the traffic accidents of the different road sections in unit time and the passing function reliability of the different road sections;
taking the sum of the weighted values of all road sections on the road network as an evaluation value of the road network, comparing the evaluation value with evaluation values of all road network planning graphs designed aiming at the same destination historically, sequencing at least road network planning graph marks from top to bottom according to the evaluation values, and labeling the imported road network planning graph marks and the evaluation values in an emphatic mode.
By adopting the technical scheme, the comprehensive quantitative analysis can be performed on the road network planning diagram introduced by the user from two angles of the number of the traffic accidents in unit time and the passing functional reliability, and compared with the single-dimensional quantitative analysis of the passing functional reliability, the applicability of different road network layout forms can be more reasonably evaluated, and higher reference value is provided for the design and optimization decision of the urban road network planning scheme.
Optionally, the step of classifying the types of the road segments on the road network planning graph is as follows:
identifying and acquiring a schematic diagram of each road section on a road network planning diagram;
and inquiring road section types corresponding to the schematic diagrams which are compared and consistent one by taking the schematic diagrams of each road section on the road network planning diagram as inquiry objects one by one from a preset first database in which the road section types and the schematic diagrams of the road sections of the corresponding types are stored, thereby acquiring the types of each road section on the road network planning diagram.
By adopting the technical scheme, each road section of the road network planning map is subjected to segmentation processing and is compared and analyzed with different types of road sections prestored in the first database, so that the road section types of the current road network planning map can be effectively analyzed.
Optionally, the predicting step of the number of the traffic accidents in unit time of the different types of road segments on the road network planning map is as follows:
acquiring planning time for completing construction of a target road network;
predicting the traffic volume of different road sections of the target area after construction of the road network is completed based on the historical traffic volume of different road sections of the target area;
inquiring the traffic volume and the number of the traffic accidents in unit time of the same type of road section by taking the road sections of different types of the target road network as inquiry objects one by one from a preset second database storing the road sections of the local area, the positions of the road sections of the corresponding type, the current traffic volume of the corresponding road section and the number of the traffic accidents in unit time of the corresponding road section;
if the same type of road sections are multiple, the current traffic volume of the same type of road sections is used as a deducted number one by one, the predicted traffic volume of the target corresponding type of road sections is used as a uniform deducted number, and if the obtained difference value falls into a preset difference value range, the current traffic volume of the same type of road sections corresponding to the corresponding difference value is used as a reference quantity;
acquiring the mean value of all reference quantities and the mean value of the number of traffic accidents in unit time of the same type of road sections corresponding to all reference quantities;
taking the predicted traffic volume of the target corresponding type road section as a front item and the mean value of all reference quantities as a back item, acquiring the ratio of the predicted traffic volume of the target corresponding type road section to the mean value of all reference quantities, and taking the product of the ratio and the mean value of the number of the traffic accidents per unit time of the same type road section corresponding to all reference quantities as the number of the traffic accidents per unit time of the target corresponding type road section;
if only one road section of the same type is available, the predicted traffic volume of the road section of the corresponding type of the target place is used as a front item, the current traffic volume of the road section of the same type is used as a back item, the ratio of the predicted traffic volume of the road section of the corresponding type of the target place to the current traffic volume of the road section of the same type is calculated, and the product of the ratio and the number of times of traffic accidents of the road section of the same type in unit time is used as the number of times of the traffic accidents of the road section of the corresponding type of.
By adopting the technical scheme, the traffic volume and the number of times of the traffic accidents in unit time of other road sections of the same type in the local area and the historical traffic volume condition of the corresponding road sections in the target area are effectively combined, the number of times of the traffic accidents in unit time after construction of the road sections of different types on the road network planning map can be more effectively and accurately predicted, and therefore the accuracy of evaluating the applicability of the network layout forms of different roads is improved.
Optionally, the traffic volume prediction step of the road network of different target road sections after construction is as follows:
acquiring interval time based on planning time for completing construction of a target road network and current time;
the method comprises the steps that current traffic volumes of target corresponding road section types are acquired one by taking the current time of the target road section types as query objects from a preset third database storing different road section types of target places and historical traffic volumes of corresponding road sections, and meanwhile the traffic volumes of the target corresponding road section types and the current time of a preset interval time period are acquired one by taking the time of the target road section types from the current time period as query objects;
taking the current traffic volume of the corresponding road section type of the target as a deducted number, taking the traffic volume of the corresponding road section type of the target away from the current time of a preset interval time period as a deducted number, and taking the obtained difference value as a traffic volume change value of the preset interval time period before the critical point of the corresponding road section type;
taking the interval time as a front item and the preset interval time period as a back item, acquiring the ratio of the interval time to the preset interval time period, and taking the product of the ratio and the traffic volume change value of the preset interval time period before the critical point as the integral change quantity of the corresponding road section type;
and taking the sum of the overall variable quantity of the corresponding road section type and the traffic quantity of the corresponding road section type of the current target as the predicted traffic quantity of the road section of the target area after the construction of the road network is completed.
By adopting the technical scheme, the construction period of the road sections on the road network planning map and the historical traffic volume condition of the current road section of the target area are effectively combined, the traffic volumes of different road sections after construction are effectively and accurately predicted, and therefore the prediction accuracy of the number of the traffic accidents of different road sections in unit time after construction is indirectly improved.
Optionally, the step of calculating the passing function reliability of different types of road segments by using the pre-constructed road segment passing reliability model analysis is as follows:
acquiring the actual length of each type of road section mark in the road network planning map, and synchronously inquiring the reasonable maximum distance of each type of road section according to the road section types of the road network planning map from a preset fourth database which stores the road section types and the reasonable maximum distances of the corresponding type of road sections;
calculating the passing function reliability of different types of road sections one by applying a pre-constructed road section passing reliability model, wherein the pre-constructed road section passing reliability model is as follows:
Pi=Li/Limax，
wherein:
i is the ith category in all road section types;
Pithe passing function reliability of the i-th road section is obtained;
Lithe actual length of the ith road section;
Limaxa reasonable maximum distance for the class i road segment.
By adopting the technical scheme, the passing function reliability of each road section can be effectively analyzed by acquiring the actual length marked by each type road section in the road network planning map, the reasonable maximum distance of each type road section and applying the pre-constructed road section passing reliability model.
Optionally, the pre-constructed weight formula is as follows:
Yi=(1/Ai)*q+Bi*p,
wherein:
i is the ith category in all road section types;
Yithe weight value of the ith road section is obtained;
Aithe number of the traffic accidents in unit time of the ith road section is calculated;
q is the weight ratio of the number of the traffic accidents in unit time of the road section;
Bithe passing function reliability of the i-th road section is obtained;
and p is the weight ratio of the passing function reliability of the road section.
By adopting the technical scheme, the passing function reliability of the road section and the number of times of the traffic accidents in unit time of the road section are comprehensively considered in a formula mode, so that the applicability of different road network layout forms is more reasonably evaluated, and higher reference value is provided for the design and optimization decision of the urban road network planning scheme.
In a second aspect, the present application provides an evaluation system for urban road network planning implementation effect, which adopts the following technical scheme:
an evaluation system for urban road network planning implementation effect, comprising a memory, a processor and a program stored on the memory and capable of running on the processor, wherein the program can be loaded and executed by the processor to implement the evaluation method for urban road network planning implementation effect according to any one of the preceding claims.
By adopting the technical scheme, the comprehensive quantitative analysis can be performed on the road network planning graph led in by the user from two angles of the number of the traffic accidents in unit time and the passing functional reliability through the calling of the program, and compared with the single-dimensional quantitative analysis of the passing functional reliability, the applicability of different road network layout forms can be more reasonably evaluated, and higher reference value is provided for the design and optimization decision of the urban road network planning scheme.
In a third aspect, the present application provides a computer storage medium, which adopts the following technical solutions:
a computer storage medium comprising a program which can be loaded by a processor for implementing a method for assessing the effectiveness of an implementation of urban road network planning according to any of the preceding claims.
By adopting the technical scheme, the comprehensive quantitative analysis can be performed on the road network planning graph led in by the user from two angles of the number of the traffic accidents in unit time and the passing functional reliability through the calling of the program, and compared with the single-dimensional quantitative analysis of the passing functional reliability, the applicability of different road network layout forms can be more reasonably evaluated, and higher reference value is provided for the design and optimization decision of the urban road network planning scheme.
To sum up, the beneficial technical effect of this application does:
1. dividing the urban road network into a plurality of road section units, and performing comprehensive evaluation by combining the functional reliability and the number of times of traffic accidents in unit time to provide reference value for the design and optimization decision of the urban road network planning scheme;
2. the user can know the ranking condition of the evaluation value of the imported road network planning graph in the currently recorded road network planning graph.
Drawings
Fig. 1 is a schematic step diagram of a method for evaluating an implementation effect of urban road network planning according to an embodiment of the present application.
Fig. 2 is a schematic diagram illustrating the step of classifying road segments located on the road network planning graph in step S200 in fig. 1.
Fig. 3 is a schematic diagram of the steps for predicting the number of traffic accidents per unit time of different types of road segments on the road network planning map mentioned in step S300 in fig. 1.
Fig. 4 is a detailed step diagram of step S3b0 in fig. 3.
Fig. 5 is a schematic diagram of the step of calculating the reliability of the passing function of different types of road segments by using the pre-constructed road segments through reliability model analysis, which is mentioned in step S300 of fig. 1.
Detailed Description
The present application is described in further detail below with reference to the attached drawings.
Referring to fig. 1, the method for evaluating the implementation effect of urban road network planning disclosed by the present application includes steps S100 to S500.
In step S100, a road network planning map designed for a target area, which is introduced by a user into an evaluation system for evaluating an urban road network planning implementation effect, is acquired.
The method for importing the road network planning map designed for the target area into the evaluation system for the urban road network planning implementation effect in step S100 may be to directly pull the file of the road network planning map to a file import module of the system to complete the import, or to query and obtain the location of the file of the road network planning map through the file import module of the system and click the file of the road network planning map to complete the import.
In step S200, the road segments on the road network planning map are classified into different types, and the road segments on the road network planning map are defined to have different types.
Referring to fig. 2, step S200 can be divided into steps S210 to S220.
In step S210, a schematic diagram of each road segment on the road network planning graph is identified and acquired.
The identification and acquisition manner of the schematic diagram of each road segment on the road network planning map mentioned in step S210 may be implemented by performing image identification through a convolutional neural network, where the convolutional neural network identification manner is to perform gray processing and normalization processing on the planning map, divide the processed planning map into a plurality of image data, and identify the road segments in each image content respectively.
In step S220, the road segment types corresponding to the schematic diagrams that are compared and consistent are queried one by one from the preset first database storing the road segment types and the schematic diagrams of the road segments of the corresponding types as query objects, so as to obtain the type of each road segment on the road network planning map.
The road segment types mentioned in step S220 may be classified by applying a system clustering method, and the road segments are classified into four categories, namely, a first road segment category, a second road segment category, a third road segment category and a fourth road segment category.
The first category of road segments comprises road segment types of: one board 2 lane, one board 4 lane, two board 4 lanes, and three board 4 lanes.
The second category of road segments includes road segment types of: one 6 lanes of boards, two 6 lanes of boards, three 6 lanes of boards and four 8 lanes of boards.
The third category of road segments includes road segment types: one plate 8 lane and two plates 8 lane.
The fourth category of road segments contains road segment types: four boards 6 lanes and an elevated road 10 lane.
In step S300, the number of times of traffic accidents of different types of road segments on the road network planning map in unit time is predicted, and meanwhile, the reliability of passing functions of the different types of road segments is calculated by applying the pre-constructed road segment passing reliability model analysis.
Referring to fig. 3, the step of predicting the number of accidents per unit time for different types of links on the road network planning map mentioned in step S300 can be divided into steps S3a0 to S3g0, wherein step S3d0 and step S3g0 are parallel steps, and step S3e0 and step S3f0 are successive steps after step S3d 0.
In step S3a0, a planning time for completing construction of the target road network is acquired.
The planning time for completing construction of the road network of the target location mentioned in step S3a0 may be obtained by calling a database in which planning time for completing construction of the road network of the corresponding target location is prestored.
In step S3b0, the traffic volume of the road network after the construction of the road network is predicted for the different road sections of the target area based on the traffic volume of the history of the different road sections of the target area.
Referring to fig. 4, the step of predicting the traffic volume of the target road with different links after the construction of the road network mentioned in step S3b0 can be divided into steps S3b1 to S3b 5.
In step S3b1, the separation time is obtained based on the planning time for completing the construction of the target road network and the current time.
For example, if the construction completion time of the target road network is 2025 years and 4 months, and the current time is 2021 years and 2 months, the time interval is 50 months.
In step S3b2, from a third database storing historical traffic volumes of different road segment types and corresponding road segments of the target location, the current traffic volume of the road segment type of the target location is acquired one by one with the current time of the road segment type of the target location as the query object, and the traffic volume of the time of the road segment type of the target location from the current preset interval time is acquired one by one with the time of the road segment type of the target location from the current preset interval time as the query object.
In step S3b3, the current traffic volume of the target corresponding link type is used as the decremented number, the traffic volume of the target corresponding link type from the current time of the preset interval time period is used as the decremented number, and the obtained difference value is used as the traffic volume change value of the preset interval time period before the corresponding link type critical point.
In step S3b4, the interval time is used as a front term, the preset interval time period is used as a back term, a ratio of the interval time to the preset interval time period is obtained, and a product of the ratio and a traffic volume change value of the preset interval time period before the critical point is used as an overall change amount of the corresponding link type.
In step S3b5, the sum of the total variation of the corresponding link type and the traffic volume of the corresponding link type at the current target is used as the traffic volume of the predicted target road link after the construction of the road network is completed.
For example, assuming that the preset interval time period is 1 month, the traffic volume change value of the preset interval time period before the critical point of the corresponding road segment type is a, the interval time is 50 months, and the traffic volume of the current target road segment type is 30a, the predicted traffic volume of the target road segment after the construction of the road network is 80 a.
In step S3c0, from a preset second database storing the road segments of the local area, the positions of the road segments of the corresponding type, the current traffic volume of the corresponding road segments, and the number of the traffic accidents per unit time of the corresponding road segments, the traffic volume of the road segments of the same type and the number of the traffic accidents per unit time are inquired one by using the different types of road segments of the target road network as the inquiry objects.
The number of traffic accidents per unit time in step S3c0 may be 1 year traffic accident number, but the unit time is not limited to 1 year, and may be 1 month or half year.
In step S3d0, if there are a plurality of the same type of road segments, the current traffic volume of the same type of road segments is used as the subtracted number one by one, the predicted traffic volume of the target corresponding type of road segments is used as the uniform subtracted number, and if the obtained difference value falls within the preset difference value range, the current traffic volume of the same type of road segments corresponding to the corresponding difference value is used as the reference volume.
In step S3e0, the average value of all the reference quantities and the average value of the number of the traffic accidents per unit time of the same type of the road sections corresponding to all the reference quantities are obtained.
In step S3f0, the predicted traffic volume of the target corresponding type road segment is used as the front term, the average value of all the reference quantities is used as the back term, the ratio of the predicted traffic volume of the target corresponding type road segment to the average value of all the reference quantities is obtained, and the product of the ratio and the average value of the number of the traffic accidents per unit time of the same type road segment corresponding to all the reference quantities is used as the number of the traffic accidents per unit time of the target corresponding type road segment.
For example, if the same type of road segments corresponding to the road segment type of a certain target place are 3, the same type of road segments are a, b and c, the traffic volume of the first road segment is d, the number of traffic accidents in unit time of the first road segment is g, the traffic volume of the second road segment is e, the number of traffic accidents in unit time of the second road segment is h, the traffic volume of the third road segment is f, the number of traffic accidents in unit time of the third road segment is i, the average value of the traffic volumes of the third road segment is (d + e + f)/3, the average value of the number of traffic accidents in unit time of the third road segment is (g + h + i)/3, and if the predicted traffic volume of the corresponding type of road segment of the target place is x, the number of traffic accidents in unit time of the corresponding type of the target place is { x [ (d + e + f)/3] }.
In step S3g0, if there is only one type of road segment, the predicted traffic volume of the target corresponding type of road segment is used as the previous item, the current traffic volume of the same type of road segment is used as the next item, the ratio of the predicted traffic volume of the target corresponding type of road segment to the current traffic volume of the same type of road segment is calculated, and the product of the ratio and the number of times of traffic accidents per unit time of the same type of road segment is used as the number of times of traffic accidents per unit time of the target corresponding type of road segment.
Referring to fig. 5, the step of calculating the passing function reliability of different types of links through reliability model analysis using the previously constructed links mentioned in step S300 may be divided into steps S3a0 through S3B 0.
In step S3a0, the actual length of each type road segment label in the road network planning map is obtained, and the reasonable maximum distance of each type road segment is found out synchronously from the preset fourth database storing the road segment types and the reasonable maximum distances of the corresponding type road segments according to the road segment types of the road network planning map.
In step S3B0, the passing function reliability of the different types of road segments is calculated one by one using the pre-constructed road segment passing reliability model as follows: pi=Li/LimaxWherein: i is the ith category in all road section types; piThe passing function reliability of the i-th road section is obtained; l isiThe actual length of the ith road section; l isimaxA reasonable maximum distance for the class i road segment.
In step S400, a weight value of each link is calculated by a pre-constructed weight formula based on the predicted number of traffic accidents per unit time of the different types of links and the passing function reliability of the different types of links, respectively.
The pre-constructed weight formula mentioned in step S400 is as follows: y isi=(1/Ai)*q+BiP, wherein: i is the ith category in all road section types; y isiThe weight value of the ith road section is obtained; a. theiThe number of the traffic accidents in unit time of the ith road section is calculated; q is the weight ratio of the number of times of traffic accidents in unit time of road section, BiIs the ith roadThe pass function reliability of the segment; and p is the weight ratio of the passing function reliability of the road section.
In step S500, the sum of the weighted values of all the road segments on the road network is used as the evaluation value of the road network, and compared with the evaluation values of all the road network planning maps designed for the same destination historically, at least some road network planning map markers are sorted from top to bottom according to the evaluation values, and the currently imported road network planning map markers and the evaluation values are highlighted.
In step S500, the highlighting and marking of the current importing road network layout drawing and the evaluation value may be in a manner of bolding a font, or in a manner of marking in different colors.
An embodiment of the present invention provides a computer-readable storage medium, which includes a program capable of being loaded and executed by a processor to implement any one of the methods shown in fig. 1-5.
The computer-readable storage medium includes, for example: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
Based on the same inventive concept, an embodiment of the present invention provides an evaluation system for an implementation effect of urban road network planning, which includes a memory and a processor, wherein the memory stores a program capable of running on the processor to implement any one of the methods shown in fig. 1 to 5.
It will be clear to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional modules is merely used as an example, and in practical applications, the above function distribution may be performed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to perform all or part of the above described functions. For the specific working processes of the system, the apparatus and the unit described above, reference may be made to the corresponding processes in the foregoing method embodiments, and details are not described here again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, a module or a unit may be divided into only one logical function, and may be implemented in other ways, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, a network device, or the like) or a processor (processor) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: u disk, removable hard disk, read only memory, random access memory, magnetic or optical disk, etc. for storing program codes.
The embodiments of the present invention are preferred embodiments of the present invention, and the scope of the present invention is not limited by these embodiments, so: all equivalent changes made according to the structure, shape and principle of the invention are covered by the protection scope of the invention.
Claims (8)
1. A method for evaluating the implementation effect of urban road network planning is characterized by comprising the following steps:
acquiring a road network planning graph which is designed aiming at a target and is imported into an evaluation system of an urban road network planning implementation effect by a user;
the method comprises the steps that road sections on a road network planning graph are subjected to type division, and the road sections on the road network planning graph are defined to be different in types;
respectively predicting the times of traffic accidents of different types of road sections on a road network planning graph in unit time, and meanwhile, analyzing and calculating the passing function reliability of the different types of road sections by using a pre-constructed road section passing reliability model;
respectively calculating the weight value of each road section through a pre-constructed weight formula based on the predicted number of the traffic accidents of the different road sections in unit time and the passing function reliability of the different road sections;
taking the sum of the weighted values of all road sections on the road network as an evaluation value of the road network, comparing the evaluation value with evaluation values of all road network planning graphs designed aiming at the same destination historically, sequencing at least road network planning graph marks from top to bottom according to the evaluation values, and labeling the imported road network planning graph marks and the evaluation values in an emphatic mode.
2. The method for evaluating the implementation effect of urban road network planning according to claim 1, wherein the step of classifying the road segments on the road network planning map is as follows:
identifying and acquiring a schematic diagram of each road section on a road network planning diagram;
and inquiring road section types corresponding to the schematic diagrams which are compared and consistent one by taking the schematic diagrams of each road section on the road network planning diagram as inquiry objects one by one from a preset first database in which the road section types and the schematic diagrams of the road sections of the corresponding types are stored, thereby acquiring the types of each road section on the road network planning diagram.
3. The method for evaluating the implementation effect of urban road network planning according to claim 1, wherein the method comprises the following steps: the prediction steps of the number of the traffic accidents of different types of road sections in unit time on the road network planning map are as follows:
acquiring planning time for completing construction of a target road network;
predicting the traffic volume of different road sections of the target area after construction of the road network is completed based on the historical traffic volume of different road sections of the target area;
inquiring the traffic volume and the number of the traffic accidents in unit time of the same type of road section by taking the road sections of different types of the target road network as inquiry objects one by one from a preset second database storing the road sections of the local area, the positions of the road sections of the corresponding type, the current traffic volume of the corresponding road section and the number of the traffic accidents in unit time of the corresponding road section;
if the same type of road sections are multiple, the current traffic volume of the same type of road sections is used as a deducted number one by one, the predicted traffic volume of the target corresponding type of road sections is used as a uniform deducted number, and if the obtained difference value falls into a preset difference value range, the current traffic volume of the same type of road sections corresponding to the corresponding difference value is used as a reference quantity;
acquiring the mean value of all reference quantities and the mean value of the number of traffic accidents in unit time of the same type of road sections corresponding to all reference quantities;
taking the predicted traffic volume of the target corresponding type road section as a front item and the mean value of all reference quantities as a back item, acquiring the ratio of the predicted traffic volume of the target corresponding type road section to the mean value of all reference quantities, and taking the product of the ratio and the mean value of the number of the traffic accidents per unit time of the same type road section corresponding to all reference quantities as the number of the traffic accidents per unit time of the target corresponding type road section;
if only one road section of the same type is available, the predicted traffic volume of the road section of the corresponding type of the target place is used as a front item, the current traffic volume of the road section of the same type is used as a back item, the ratio of the predicted traffic volume of the road section of the corresponding type of the target place to the current traffic volume of the road section of the same type is calculated, and the product of the ratio and the number of times of traffic accidents of the road section of the same type in unit time is used as the number of times of the traffic accidents of the road section of the corresponding type of.
4. The method according to claim 3, wherein said method comprises: the method for predicting the traffic volume of different road sections of the target area after construction of the road network comprises the following steps:
acquiring interval time based on planning time for completing construction of a target road network and current time;
the method comprises the steps that current traffic volumes of target corresponding road section types are acquired one by taking the current time of the target road section types as query objects from a preset third database storing different road section types of target places and historical traffic volumes of corresponding road sections, and meanwhile the traffic volumes of the target corresponding road section types and the current time of a preset interval time period are acquired one by taking the time of the target road section types from the current time period as query objects;
taking the current traffic volume of the corresponding road section type of the target as a deducted number, taking the traffic volume of the corresponding road section type of the target away from the current time of a preset interval time period as a deducted number, and taking the obtained difference value as a traffic volume change value of the preset interval time period before the critical point of the corresponding road section type;
taking the interval time as a front item and the preset interval time period as a back item, acquiring the ratio of the interval time to the preset interval time period, and taking the product of the ratio and the traffic volume change value of the preset interval time period before the critical point as the integral change quantity of the corresponding road section type;
and taking the sum of the overall variable quantity of the corresponding road section type and the traffic quantity of the corresponding road section type of the current target as the predicted traffic quantity of the road section of the target area after the construction of the road network is completed.
5. The method for evaluating the implementation effect of urban road network planning according to claim 1, wherein the method comprises the following steps: the method for calculating the passing function reliability of different types of road sections by applying the pre-constructed road sections through reliability model analysis comprises the following steps:
acquiring the actual length of each type of road section mark in the road network planning map, and synchronously inquiring the reasonable maximum distance of each type of road section according to the road section types of the road network planning map from a preset fourth database which stores the road section types and the reasonable maximum distances of the corresponding type of road sections;
calculating the passing function reliability of different types of road sections one by applying a pre-constructed road section passing reliability model, wherein the pre-constructed road section passing reliability model is as follows:
Pi=Li/Limax，
wherein:
i is the ith category in all road section types;
Pithe passing function reliability of the i-th road section is obtained;
Lithe actual length of the ith road section;
Limaxa reasonable maximum distance for the class i road segment.
6. The method according to claim 5, wherein said method comprises: the pre-constructed weight formula is as follows:
Yi=(1/Ai)*q+Bi*p,
wherein:
i is the ith category in all road section types;
Yithe weight value of the ith road section is obtained;
Aithe number of the traffic accidents in unit time of the ith road section is calculated;
q is the weight ratio of the number of the traffic accidents in unit time of the road section;
Bithe passing function reliability of the i-th road section is obtained;
and p is the weight ratio of the passing function reliability of the road section.
7. An evaluation system for urban road network planning implementation effect is characterized in that: the evaluation method comprises a memory, a processor and a program stored on the memory and running on the processor, wherein the program can be loaded and executed by the processor to realize the evaluation method of the implementation effect of the urban road network planning according to any one of claims 1 to 6.
8. A computer storage medium, characterized in that: program capable of being loaded and executed by a processor for implementing a method for evaluating the effectiveness of a city road network planning implementation according to any one of claims 1 to 6.
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