Traffic development coordination evaluation method, device and equipment

Abstract

The invention provides a traffic development coordination evaluation method, apparatus and device. The method comprises the steps of obtaining a first information set related to traffic transportation of a target area; obtaining a second information set related to population, economy and transportation demands of the target area; calculating and determining the abundance space matching degree of elements contained in the two sets at least based on the first information set and the second information set; a target coordination type representing traffic development coordination in the target area is calculated and determined based on the abundance space matching degree obtained through calculation; and when the target coordination type meets the optimization requirement, determining a target optimization strategy for improving the coordination of the corresponding target geographic area at least based on the target coordination type. The traffic development coordination evaluation method can efficiently and accurately evaluate the traffic development coordination of different areas.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of computer technology, and in particular to a method, apparatus and equipment for evaluating the coordination of transportation development. Background Technology

[0002] With the acceleration of urbanization, the interaction between transportation systems, the environment, and other factors is becoming increasingly close. Transportation has both ancillary and guiding functions. The former refers to the role of transportation development in serving regional economic and social development; the latter refers to how transportation development, by providing high-quality travel and transportation services, creates spatial advantages in unevenly distributed areas, guiding the agglomeration and diffusion of economic and social development factors, and thus feeding back into economic and social development.

[0003] In existing technologies, Data Envelopment Analysis (DEA) models are frequently used to evaluate transportation efficiency. For example, some studies have constructed evaluation systems for integrated transportation systems based on DEA methods, aiming to analyze the operational status of each subsystem; others have introduced AHP-grey relational analysis to determine weights and established improved C²R models to assess safety benefits for highway BOT+EPC projects. Although these methods have solved the evaluation problem of multiple inputs and multiple outputs to some extent, their core is still based on linear assumptions, making it difficult to accurately characterize the complex nonlinear coupling characteristics between transportation supply and demand and population and economic factors. In addition, existing evaluations often focus on ex-post static analysis, lacking the ability to perceive dynamic trends in real time, making it difficult for decision-makers to adjust transportation planning in a timely manner to adapt to the new demands of population growth and economic development.

[0004] Therefore, there is an urgent need for a transportation development coordination evaluation method that can comprehensively consider population distribution, economic development level and transportation demand matching degree, and has efficient real-time processing capabilities, in order to solve the technical bottlenecks of existing technologies such as single evaluation dimensions, overly strong linear assumptions in the model, and lagging dynamic response. Summary of the Invention

[0005] This invention provides a method, apparatus, and equipment for evaluating the coordination of transportation development, which can be used to efficiently and accurately evaluate the coordination of transportation development in different regions.

[0006] To address the aforementioned technical problems, embodiments of the present invention provide a method for evaluating the coordination of traffic development, comprising: Obtain the first set of information related to transportation in the target area; Obtain a second set of information related to population, economy, and transportation needs of the target area; The abundance spatial matching degree of the elements contained in the two sets is calculated and determined based at least on the first information set and the second information set; Based on the calculated abundance spatial matching degree, the target coordination type characterizing the coordination of traffic development in the target region is determined; When the target coordination type meets the optimization requirements, at least based on the target coordination type, a target optimization strategy for improving the coordination of the corresponding target geographical area is determined.

[0007] In some embodiments, obtaining the first set of transportation-related information for the target area includes: Obtain information on the layout of transportation facilities in the target area and the corresponding spatial advantages, transportation demand network structure, and spatial service level of the existing transportation network.

[0008] In some embodiments, obtaining a second set of information related to population, economic, and transportation needs of the target area includes: Obtain population information, economic information, transportation types, and corresponding demand information for the target area. The economic information includes total GDP and GDP per capita. The transportation types include passenger transport and freight transport. The corresponding demand information includes passenger demand, freight demand, and total passenger and freight demand.

[0009] In some embodiments, the target area is a county, and the method further includes: Obtain a third information set corresponding to the overall geographical area where the target area is located. The third information set is related to transportation and contains elements of the same type as the elements contained in the first information set. Obtain a fourth information set for the entire geographical region. This fourth information set is related to population and economy, and contains elements of the same type as those in the second information set. Based on the Lorenz distribution curve analysis, the third and fourth information sets are calculated to determine the degree of spatial distribution balance of transportation elements, population elements, economic elements, and transportation demand elements in the geographical region. Using the spatial distribution balance of the geographical region as a reference, the abundance spatial matching degree of the target region is calculated as an auxiliary method.

[0010] In some embodiments, the step of calculating and determining the abundance spatial matching degree of elements contained in the two sets based at least on the first information set and the second information set includes: The traffic advantage of the target area is calculated and determined based on the first information set. The degree of spatial distribution balance in the geographical region is used as a reference to dedimensionalize the degree of transportation advantage. Based on the spatial distribution balance, the dimensionless transportation advantage, and each element in the second information set, the abundance spatial matching degree between the transportation advantage and the population, economic, and transportation demand elements in the second information set is calculated and determined.

[0011] In some embodiments, the step of calculating and determining the abundance spatial matching degree between the transportation advantage degree and the population, economic, and transportation demand elements in the second information set, based on the spatial distribution balance, the dimensionless transportation advantage degree, and each element in the second information set, includes: Based on the degree of spatial distribution balance, determine the number of counties and districts within the geographical area, the transportation advantage of each county and district, and the first population, first total GDP, first per capita GDP, and first transportation demand of each county and district. The traffic advantage concentration index of the target area is calculated and determined based on the dimensionless traffic advantage, the traffic advantage of each county / district, and the number of counties / districts. Based on the population, economic and transportation demand elements in the second information set, determine the second population size, second total GDP, second GDP per capita and second transportation demand of the target area. The population concentration index of the target area is calculated and determined based on the second population size, the first population size, and the number of county / district areas. The economic concentration index of the target region is calculated and determined based on the second total GDP, the second GDP per capita, the first total GDP, the first GDP per capita, the number of counties and districts, the second population, and the first population. The transportation demand concentration index of the target area is calculated and determined based on the second transportation demand, the first transportation demand, and the number of counties and districts. Calculate the ratios of the population concentration index, economic concentration index, transportation demand concentration index, and transportation advantage concentration index, respectively; Based on each ratio, the spatial matching degree of the abundance of population elements, economic elements, and transportation demand elements relative to transportation elements in the target area is determined.

[0012] In some embodiments, determining the target coordination type characterizing the coordination of traffic development in the target region based on the calculated abundance spatial matching degree includes: Determine the weight coefficients of the spatial matching degree of the abundance of population factors, economic factors, and transportation demand factors relative to transportation factors in the target area, respectively. Based on the weighting coefficients and spatial matching degrees of each abundance, the comprehensive coordination of transportation elements with population elements, economic elements, and transportation demand elements in the target area is calculated and determined. The target coordination type is determined based on the comprehensive coordination and the preset evaluation criteria corresponding to different coordination types. The coordination types include advanced, moderately advanced, lagging, and extremely lagging.

[0013] In some embodiments, when the target coordination type meets the optimization requirements, determining a target optimization strategy for improving the coordination of the corresponding target geographical region, at least based on the target coordination type, includes: When the target coordination type is different from the standard coordination type, a candidate optimization strategy is determined from the self-optimization strategy set based on the target coordination type. The optimization strategy set includes multiple optimization strategies, and each optimization strategy is matched with a coordination type. Based on the geographical location of the target area, the first information set, and the second information set, the elements that can be optimized and the priority of each element are determined. Based on the aforementioned elements and their corresponding priorities, the candidate optimization strategies are adjusted to obtain a target optimization strategy that adapts to the actual situation of the target region.

[0014] Another embodiment of the present invention also provides a traffic development coordination evaluation device, characterized in that it includes: The first acquisition module is used to acquire a first set of information related to transportation in the target area; The second acquisition module is used to acquire a second set of information related to population, economy and transportation needs of the target area; The first calculation module is used to calculate and determine the abundance spatial matching degree of the elements contained in the two sets based at least on the first information set and the second information set; The second calculation module is used to calculate and determine the target coordination type that characterizes the coordination of traffic development in the target area based on the calculated abundance spatial matching degree. The first determining module is used to determine, at least based on the target coordination type, a target optimization strategy for improving the coordination of the corresponding target geographical region when the target coordination type meets the optimization requirements.

[0015] Another embodiment of the present invention also provides an electronic device, comprising: At least one processor; and, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to implement the traffic development coordination evaluation method as described in any of the embodiments above. Based on the disclosure of the above embodiments, it can be understood that the beneficial effects of the embodiments of the present invention include obtaining a first information set related to transportation and a second information set related to population, economy and transportation demand of a target area, and calculating and determining the abundance spatial matching degree of the elements contained in the two sets based at least on the first information set and the second information set. Then, based on the calculated abundance spatial matching degree, a target coordination type characterizing the coordination of transportation development in the target area can be determined. Through this target coordination type, the coordination status of transportation development in the target area can be perceived by the human eye. At the same time, in order to further improve the evaluation of coordination, when the target coordination type meets the optimization requirements, the system of this application will also determine a target optimization strategy for improving the coordination of the corresponding target geographical area based at least on the target coordination type. That is, based on the method of this application, the system can output evaluation information containing the target coordination type characterizing the above-mentioned coordination status and the corresponding optimization and improvement strategy. The evaluation information is comprehensive and has high analysis efficiency. The output evaluation information is highly consistent with the actual situation of the target area and has high reference value for the statistics and governance of the target area.

[0016] Other features and advantages of this application will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the application. The objectives and other advantages of this application may be realized and obtained by means of the structures particularly pointed out in the written description, claims, and drawings.

[0017] The technical solution of this application will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0018] The accompanying drawings are provided to further illustrate the present application and form part of the specification. They are used together with the embodiments of the present application to explain the application and do not constitute a limitation thereof. In the drawings: Figure 1 This is a flowchart illustrating the traffic development coordination evaluation method in an embodiment of the present invention.

[0019] Figure 2 This is a schematic diagram illustrating the application process of the traffic development coordination evaluation method in this embodiment of the invention.

[0020] Figure 3 This is a structural block diagram of the traffic development coordination evaluation device in an embodiment of the present invention. Detailed Implementation

[0021] The specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings, but these are not intended to limit the scope of the invention.

[0022] It should be understood that various modifications can be made to the embodiments disclosed herein. Therefore, the following description should not be considered as limiting, but merely as an example of embodiments. Other modifications within the scope and spirit of this disclosure will be apparent to those skilled in the art.

[0023] The accompanying drawings, which are included in and form part of this specification, illustrate embodiments of the present disclosure and, together with the general description of the disclosure given above and the detailed description of the embodiments given below, serve to explain the principles of the disclosure.

[0024] These and other features of the invention will become apparent from the following description of preferred forms of embodiments given as non-limiting examples, with reference to the accompanying drawings.

[0025] It should also be understood that although the invention has been described with reference to some specific examples, those skilled in the art can certainly implement many other equivalent forms of the invention, which have the features described in the claims and are therefore all within the scope of protection defined herein.

[0026] The above and other aspects, features and advantages of this disclosure will become more apparent when taken in conjunction with the accompanying drawings and in view of the following detailed description.

[0027] Specific embodiments of the present disclosure are described thereafter with reference to the accompanying drawings; however, it should be understood that the disclosed embodiments are merely examples of the present disclosure and can be implemented in various ways. Well-known and / or repeated functions and structures are not described in detail to avoid unnecessary or redundant details that could obscure the present disclosure. Therefore, the specific structural and functional details disclosed herein are not intended to be limiting, but merely to serve as the basis and representative basis for the claims to teach those skilled in the art to use the present disclosure in a variety of substantially any suitable detailed structures.

[0028] This specification may use the phrases “in one embodiment,” “in another embodiment,” “in yet another embodiment,” or “in still another embodiment,” all of which may refer to one or more of the same or different embodiments according to this disclosure.

[0029] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0030] like Figure 1 and Figure 2 As shown, this embodiment of the invention provides a method for evaluating the coordination of traffic development, including: S1: Obtain the first set of information related to transportation in the target area; S2: Obtain a second set of information related to population, economic and transportation needs of the target area; S3: Calculate and determine the abundance spatial matching degree of the elements contained in the two sets based at least on the first information set and the second information set; S4: Based on the calculated abundance spatial matching degree, determine the target coordination type that characterizes the coordination of traffic development in the target region; S5: When the target coordination type meets the optimization requirements, at least based on the target coordination type, determine a target optimization strategy to improve the coordination of the corresponding target geographical area.

[0031] Based on the above, this embodiment mainly obtains a first information set related to transportation and a second information set related to population, economy, and transportation demand in the target area. It then calculates and determines the abundance spatial matching degree of the elements contained in the two sets based at least on the first and second information sets. Subsequently, based on the calculated abundance spatial matching degree, it determines the target coordination type characterizing the coordination of transportation development in the target area. Through this target coordination type, the coordination status of transportation development in the target area can be readily perceived. Furthermore, to further improve the evaluation of coordination, when the target coordination type meets optimization requirements, the system also determines a target optimization strategy to improve the coordination of the corresponding target geographical area, at least based on the target coordination type. In other words, the method of this embodiment is based on the dual function of transportation in regional economic and social development. It approaches the issue from the perspective of the adaptability of the regional transportation infrastructure system supply to the needs of economic and social development, evaluating the coordination of social development of transportation infrastructure in the target area based on the matching degree between transportation resources and the spatial distribution of population, economy, and transportation demand.

[0032] Based on the method of this embodiment, the system can output evaluation information that includes the target coordination type and corresponding optimization and improvement strategies that characterize the above-mentioned coordination state. The evaluation information is comprehensive and has high analysis efficiency. The output evaluation information is highly consistent with the actual situation of the target area and has high reference value for the statistics and governance of the target area.

[0033] In one embodiment, obtaining the first set of transportation-related information for the target area includes: S6: Obtain information on the layout of transportation facilities in the target area and the corresponding spatial advantages, transportation demand network structure, and spatial service level of the existing transportation network.

[0034] Based on the information in the first information set, the density of transportation facilities, the influence of trunk lines, and the locational advantages of the target area can be determined.

[0035] The acquisition of the second set of information related to population, economic, and transportation needs of the target area includes: S7: Obtain population information, economic information, transportation type and corresponding demand information of the target area. The economic information includes total GDP and GDP per capita. The transportation type includes passenger transport and freight transport. The corresponding demand information includes passenger demand, freight demand and total passenger and freight demand.

[0036] Of course, the information in the first and second information sets is not limited to the above information. It can also obtain information such as the spatial organization patterns and characteristics of passenger and freight flows, the spatial service level of the transportation infrastructure system and its network economy and scale economy attributes, as well as the development characteristics and stages of urban agglomerations and their resource and environmental constraints, the evolution trend of urban networks, and the characteristics of industrial transfer and structural upgrading.

[0037] Based on the information obtained above, this embodiment primarily aims to evaluate the coordination between the transportation geography and social development patterns of the region to be evaluated. First, it analyzes the comprehensive transportation geography of the case region from three aspects: the layout of transportation facilities and the spatial advantages they create, the structural characteristics of the transportation demand network, and the spatial service level of the existing transportation network. Second, using the integrated indicator of transportation advantage degree as a representation of the regional transportation geography, it analyzes the coordination between transportation elements and population distribution, economic distribution, and transportation demand distribution from a spatial matching perspective. Finally, it comprehensively evaluates the coordination between the transportation geography and social development patterns of the case region based on the evaluation results of the above three aspects. Finally, based on the analysis results, it proposes relevant suggestions to promote the coordinated development of transportation and society, i.e., target optimization strategies.

[0038] Furthermore, in this embodiment, the target area is a county-level district; that is, the method in this embodiment is implemented using a county-level district as the basic evaluation unit. Accordingly, the method further includes: S8: Obtain a third information set corresponding to the entire geographical area where the target area is located. The third information set is related to transportation and contains elements of the same type as the elements contained in the first information set. S9: Obtain a fourth information set for the entire geographical region, wherein the fourth information set is related to population and economy, and contains elements of the same type as those contained in the second information set. S10: Based on the Lorenz distribution curve analysis, calculate the third and fourth information sets to determine the degree of spatial distribution balance of transportation elements, population elements, economic elements, and transportation demand elements in the geographical region; S11: Using the spatial distribution balance of the geographical region as a reference, assist in calculating the spatial matching degree of abundance in the target region.

[0039] For example, a geographical region containing multiple counties is identified, with the target region being one of these counties. Information on transportation, population, economy, and transport demand is obtained for each county within the geographical region. Then, the Lorenz distribution curve is used to analyze the spatial distribution equilibrium of transportation, population, economic, and transport demand factors in each county. Simultaneously, the concentration trend of spatial distribution of transportation, population, economic, and transport demand factors (collectively referred to as economic equipment factors) in each county can be calculated and predicted. Finally, the spatial distribution equilibrium of the corresponding geographical region is determined by comprehensively considering the equilibrium of each county. If the spatial distribution of transportation factors perfectly matches that of population, economy, and transport demand factors, the Lorenz distribution curves of all economic and social factors will be completely consistent. The greater the difference between the curves, the greater the difference in the equilibrium of spatial distribution among the factors, and the lower the spatial matching degree.

[0040] In another embodiment, the step of calculating and determining the abundance spatial matching degree of elements contained in the two sets based at least on the first information set and the second information set includes: S12: Calculate and determine the traffic advantage of the target area based on the first information set; S13: Based on the spatial distribution balance of the geographical region as a reference, the transportation advantage degree is dedimensionalized; S14: Based on the spatial distribution balance, the dimensionless transportation advantage, and each element in the second information set, calculate and determine the abundance spatial matching degree between the transportation advantage and the population element, economic element, and transportation demand element in the second information set.

[0041] For example, firstly, the spatial distribution balance of a geographical region, i.e., the average level of coordination of the geographical region, is used as a reference to dedimensionalize the factors of transportation advantage and population, economy, and transportation demand. Then, based on this, the coordination of transportation and social development in different counties and districts is classified according to the abundance of transportation and socio-economic factors relative to the regional average level.

[0042] For example, the step of calculating and determining the abundance spatial matching degree between the transportation advantage degree and the population, economic, and transportation demand elements in the second information set based on the spatial distribution balance, the dimensionless transportation advantage degree, and each element in the second information set includes: S15: Based on the degree of spatial distribution balance, determine the number of counties and districts within the geographical area, the transportation advantage of each county and district, and the first population, first total GDP, first per capita GDP, and first transportation demand of each county and district. S16: Calculate and determine the traffic advantage concentration index of the target area based on the dimensionless traffic advantage, the traffic advantage of each county / district, and the number of counties / districts. S17: Based on the population, economic and transportation demand elements in the second information set, determine the second population size, second total GDP, second GDP per capita and second transportation demand of the target area; S18: Calculate and determine the population concentration index of the target area based on the second population size, the first population size, and the number of county / district areas; S19: Calculate and determine the economic concentration index of the target region based on the second total GDP, the second per capita GDP, the first total GDP, the first per capita GDP, the number of counties / districts, the second population, and the first population; S20: Calculate and determine the transportation demand concentration index of the target area based on the second transportation demand, the first transportation demand, and the number of county / district areas; S21: Calculate the ratios of the population concentration index, economic concentration index, transportation demand concentration index, and transportation advantage concentration index, respectively; S22: Based on each ratio, determine the spatial matching degree of the abundance of population elements, economic elements, and transportation demand elements relative to transportation elements in the target area.

[0043] For example, taking the coordination between transportation advantage and population factors in the target area as an example, the transportation advantage concentration index, population concentration index, and relative abundance index (abundance spatial matching degree) are defined as follows: In the formula, TSIi is the transportation advantage concentration index of county i, PII is the population concentration index of county i, and TS_Pi is the abundance index of population factor relative to transportation factor of county i; TSI is the transportation advantage of county i, POPi is the total population of county i, and n is the total number of counties in the region. When the population or transportation advantage of a county is equal to the average of all counties in the region, the value of PII or TSIi is 1; the higher the value, the greater the advantage of population or transportation advantage relative to the regional average. When TS_Pi equals 1, it indicates that the abundance of transportation factor in county i is comparable to the abundance of population factor relative to the average level of the geographical region; when TS_Pi is greater than 1, it indicates that the abundance of transportation factor in county i is lower than the abundance of population factor relative to the average level of the geographical region, that is, transportation development lags behind population development; conversely, it indicates that transportation development is ahead of population development.

[0044] The calculation of the economic concentration index and the transportation demand concentration index of the target region follows the same method as the calculation of the population concentration index, differing only in the parameters. Specifically, the economic concentration index requires calculating the total GDP concentration index and the GDP per capita concentration index, then averaging these two values ​​to obtain the target region's economic concentration index. Since transportation demand involves both freight and passenger demand, the concentration indices for freight demand and passenger demand must be calculated separately, then averaged to obtain the corresponding transportation demand concentration index for the target region. Similarly, the calculation of the economic and transportation demand abundance indices of the target region involves separately calculating the total GDP abundance index, GDP per capita abundance index, freight demand abundance index, and passenger demand abundance index, then averaging these values ​​to obtain the abundance indices of economic factors and transportation demand relative to transportation factors in the target region.

[0045] For example, ; In the formula, TS_Gi and TS_Di are the abundance indices of economic factors and transportation demand relative to transportation factors, respectively. The former is determined by integrating the degree of spatial matching between GDP and GDP per capita and transportation advantage, while the latter is determined by integrating the degree of spatial matching between passenger demand and freight demand and transportation advantage. TS_GDPi, TS_PGDPi, TS_PDi, and TS_CDi are the abundance indices of GDP, GDP per capita, passenger demand, and freight demand relative to transportation factors, respectively.

[0046] Furthermore, the determination of the target coordination type characterizing the coordination of traffic development in the target region based on the calculated abundance spatial matching degree includes: S23: Determine the weighting coefficients of the spatial matching degree of the abundance of population elements, economic elements, and transportation demand elements relative to transportation elements in the target area, respectively. S24: Calculate and determine the comprehensive coordination of transportation elements with population elements, economic elements, and transportation demand elements in the target area based on the weighting coefficients and spatial matching degrees of each abundance. S25: Based on the comprehensive coordination and the preset evaluation criteria corresponding to different coordination types, the target coordination type is determined, including advanced, moderately advanced, lagging and extremely lagging types.

[0047] Specifically, the weighting coefficients for population, economic, and transportation needs are denoted as α, β, and γ, respectively. Their specific values ​​are not fixed and can be determined based on actual circumstances. In this embodiment, the calculation is performed with each weight being 1 / 3. After calculating the various abundance indices of the target area, the comprehensive coordination can be calculated based on the following formula. : After calculating the overall coordination score, its value can be matched with preset coordination score ranges corresponding to different coordination types to ultimately determine the target coordination type. Alternatively, each type of coordination score can be matched with the aforementioned coordination score ranges, or the corresponding coordination reference ranges, to determine the coordination type for each type of coordination. For example: Taking the coordination between transportation and population (TS_Pi) as an example, based on the distribution of TS_Pi, the coordination between transportation and population can be further subdivided into four types based on the advanced and lagging types, referring to the standards in the following examples: ① Advanced type: the population concentration index is much lower than the transportation advantage index, and TS_Pi is less than 0.6; ② Moderately advanced type: TS_Pi is between 0.6 and 1.0; ③ Lagging type: TS_Pi is between 1.0 and 2.0; ④ Extremely lagging type: TS_Pi is greater than 2.0. Considering the auxiliary and guiding functions of transportation to regional economic and social development, moderate advancement is the most ideal coordination state. Excessive advancement will lead to a waste of transportation resources and provide a transportation foundation for the occurrence of the siphon effect; while in the lagging state, transportation will become a constraint on urban and regional economic and social development.

[0048] In another embodiment, when the target coordination type meets the optimization requirements, determining a target optimization strategy for improving the coordination of the corresponding target geographical area, at least based on the target coordination type, includes: S26: When the target coordination type is different from the standard coordination type, a candidate optimization strategy is determined from the self-optimization strategy set based on the target coordination type. The optimization strategy set includes multiple optimization strategies, and each optimization strategy is matched with a coordination type. S27: Based on the geographical location of the target area, the first information set, and the second information set, analyze and determine the elements that can be optimized and the priority of each element; S28: Adjust the candidate optimization strategy based on the elements and their corresponding priorities to obtain a target optimization strategy that adapts to the actual situation of the target area.

[0049] For example, taking the standard coordination type as moderately advanced as an example, when the target coordination type is not moderately advanced, it can be determined that it meets the optimization requirements. At this time, the system can select candidate optimization strategies that match the target coordination type from the stored set of optimization strategies. However, the candidate optimization strategies cannot be tailored to the actual situation of every county or district. Therefore, in order to make the optimization strategy more consistent with the actual situation of the target area, the system can comprehensively analyze the target area's geographical location, the first information set, the second information set, and prior knowledge about the target area, such as the target area's historical development, the advantages and disadvantages of its geographical conditions, its economic manufacturing type (tourism, industry, software technology, etc.), population age distribution, the number of migrants, and the development of adjacent target areas. It can also combine this with expectations for the future development of the target area to determine the elements that can be optimized, such as the type, quantity, coverage, population, and GDP per capita of transportation infrastructure, and determine the priority of each element. Then, the system can adaptively modify and adjust the information in the candidate optimization strategies according to the optimization elements and priorities, and finally obtain a target optimization strategy that conforms to the actual situation of the target area and meets the future development expectations of the target area.

[0050] like Figure 3 As shown, another embodiment of the present invention also provides a traffic development coordination evaluation device 100, comprising: The first acquisition module is used to acquire a first set of information related to transportation in the target area; The second acquisition module is used to acquire a second set of information related to population, economy and transportation needs of the target area; The first calculation module is used to calculate and determine the abundance spatial matching degree of the elements contained in the two sets based at least on the first information set and the second information set; The second calculation module is used to calculate and determine the target coordination type that characterizes the coordination of traffic development in the target area based on the calculated abundance spatial matching degree. The first determining module is used to determine, at least based on the target coordination type, a target optimization strategy for improving the coordination of the corresponding target geographical region when the target coordination type meets the optimization requirements.

[0051] In some embodiments, obtaining the first set of transportation-related information for the target area includes: Obtain information on the layout of transportation facilities in the target area and the corresponding spatial advantages, transportation demand network structure, and spatial service level of the existing transportation network.

[0052] In some embodiments, obtaining a second set of information related to population, economic, and transportation needs of the target area includes: Obtain population information, economic information, transportation types, and corresponding demand information for the target area. The economic information includes total GDP and GDP per capita. The transportation types include passenger transport and freight transport. The corresponding demand information includes passenger demand, freight demand, and total passenger and freight demand.

[0053] In some embodiments, the target area is a county, and the device further includes: The third acquisition module is used to acquire a third information set of the entire geographical area corresponding to the target area. The third information set is related to transportation and contains elements of the same type as the elements contained in the first information set. The fourth acquisition module is used to acquire a fourth information set of the entire geographical region. The fourth information set is related to population and economy, and contains elements of the same type as those in the second information set. The third calculation module is used to analyze and calculate the third information set and the fourth information set based on the Lorenz distribution curve, and to determine the degree of spatial distribution balance of transportation elements, population elements, economic elements and transportation demand elements in the geographical region. The first calculation module is also used to assist in calculating the abundance spatial matching degree of the target area by using the spatial distribution balance of the geographical area as a reference.

[0054] In some embodiments, the step of calculating and determining the abundance spatial matching degree of elements contained in the two sets based at least on the first information set and the second information set includes: The traffic advantage of the target area is calculated and determined based on the first information set. The degree of spatial distribution balance in the geographical region is used as a reference to dedimensionalize the degree of transportation advantage. Based on the spatial distribution balance, the dimensionless transportation advantage, and each element in the second information set, the abundance spatial matching degree between the transportation advantage and the population, economic, and transportation demand elements in the second information set is calculated and determined.

[0055] In some embodiments, the step of calculating and determining the abundance spatial matching degree between the transportation advantage degree and the population, economic, and transportation demand elements in the second information set, based on the spatial distribution balance, the dimensionless transportation advantage degree, and each element in the second information set, includes: Based on the degree of spatial distribution balance, determine the number of counties and districts within the geographical area, the transportation advantage of each county and district, and the first population, first total GDP, first per capita GDP, and first transportation demand of each county and district. The traffic advantage concentration index of the target area is calculated and determined based on the dimensionless traffic advantage, the traffic advantage of each county / district, and the number of counties / districts. Based on the population, economic and transportation demand elements in the second information set, determine the second population size, second total GDP, second GDP per capita and second transportation demand of the target area. The population concentration index of the target area is calculated and determined based on the second population size, the first population size, and the number of county / district areas. The economic concentration index of the target region is calculated and determined based on the second total GDP, the second GDP per capita, the first total GDP, the first GDP per capita, the number of counties and districts, the second population, and the first population. The transportation demand concentration index of the target area is calculated and determined based on the second transportation demand, the first transportation demand, and the number of counties and districts. Calculate the ratios of the population concentration index, economic concentration index, transportation demand concentration index, and transportation advantage concentration index, respectively; Based on each ratio, the spatial matching degree of the abundance of population elements, economic elements, and transportation demand elements relative to transportation elements in the target area is determined.

[0056] In some embodiments, determining the target coordination type characterizing the coordination of traffic development in the target region based on the calculated abundance spatial matching degree includes: Determine the weight coefficients of the spatial matching degree of the abundance of population factors, economic factors, and transportation demand factors relative to transportation factors in the target area, respectively. Based on the weighting coefficients and spatial matching degrees of each abundance, the comprehensive coordination of transportation elements with population elements, economic elements, and transportation demand elements in the target area is calculated and determined. The target coordination type is determined based on the comprehensive coordination and the preset evaluation criteria corresponding to different coordination types. The coordination types include advanced, moderately advanced, lagging, and extremely lagging.

[0057] In some embodiments, when the target coordination type meets the optimization requirements, determining a target optimization strategy for improving the coordination of the corresponding target geographical region, at least based on the target coordination type, includes: When the target coordination type is different from the standard coordination type, a candidate optimization strategy is determined from the self-optimization strategy set based on the target coordination type. The optimization strategy set includes multiple optimization strategies, and each optimization strategy is matched with a coordination type. Based on the geographical location of the target area, the first information set, and the second information set, the elements that can be optimized and the priority of each element are determined. Based on the aforementioned elements and their corresponding priorities, the candidate optimization strategies are adjusted to obtain a target optimization strategy that adapts to the actual situation of the target region.

[0058] Another embodiment of the present invention also provides an electronic device, comprising: At least one processor; and, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to implement the traffic development coordination evaluation method as described in any of the embodiments above.

[0059] Another embodiment of the present invention also provides an electronic device, comprising: At least one processor; and, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to implement the traffic development coordination evaluation method as described in any of the embodiments above.

[0060] Another embodiment of the present invention also provides a storage medium including a stored program, wherein, when the program is executed, a device including the storage medium is controlled to perform the traffic development coordination evaluation method as described in any of the embodiments above.

[0061] This invention also provides a computer program product, which is tangibly stored on a computer-readable medium and includes computer-readable instructions. When executed, these computer-executable instructions cause at least one processor to perform a traffic development coordination evaluation method as described in the embodiments above. It should be understood that the various solutions in this embodiment have the corresponding technical effects in the above-described method embodiments, and will not be repeated here.

[0062] It should be noted that the computer storage medium in this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access storage medium (RAM), a read-only storage medium (ROM), an erasable programmable read-only storage medium (EPROM or flash memory), an optical fiber, a portable compact disk read-only storage medium (CD-ROM), an optical storage medium, a magnetic storage medium, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program configured for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, antenna, optical fiber, RF, etc., or any suitable combination thereof.

[0063] One or more embodiments in this application are intended to cover all such substitutions, modifications, and variations falling within the broad scope of this application. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of one or more embodiments in this application should be included within the protection scope of this application. The above embodiments are merely exemplary embodiments of the present invention and are not intended to limit the present invention; the protection scope of the present invention is defined by the claims.

Claims

1. A method for evaluating the coordination of transportation development, characterized in that, include: Obtain the first set of information related to transportation in the target area; Obtain a second set of information related to population, economy, and transportation needs of the target area; The abundance spatial matching degree of the elements contained in the two sets is calculated and determined based at least on the first information set and the second information set; Based on the calculated abundance spatial matching degree, the target coordination type characterizing the coordination of traffic development in the target region is determined; When the target coordination type meets the optimization requirements, at least based on the target coordination type, a target optimization strategy for improving the coordination of the corresponding target geographical area is determined.

2. The method for evaluating the coordination of transportation development according to claim 1, characterized in that, The first set of transportation-related information about the target area includes: Obtain information on the layout of transportation facilities in the target area and the corresponding spatial advantages, transportation demand network structure, and spatial service level of the existing transportation network.

3. The method for evaluating the coordination of transportation development according to claim 1, characterized in that, The acquisition of the second set of information related to population, economic, and transportation needs of the target area includes: Obtain population information, economic information, transportation types, and corresponding demand information for the target area. The economic information includes total GDP and GDP per capita. The transportation types include passenger transport and freight transport. The corresponding demand information includes passenger demand, freight demand, and total passenger and freight demand.

4. The method for evaluating the coordination of transportation development according to claim 1, characterized in that, The target area is a county / district, and the method further includes: Obtain a third information set corresponding to the overall geographical area where the target area is located. The third information set is related to transportation and contains elements of the same type as the elements contained in the first information set. Obtain a fourth information set for the entire geographical region. This fourth information set is related to population and economy, and contains elements of the same type as those in the second information set. Based on the Lorenz distribution curve analysis, the third and fourth information sets are calculated to determine the degree of spatial distribution balance of transportation elements, population elements, economic elements, and transportation demand elements in the geographical region. Using the spatial distribution balance of the geographical region as a reference, the abundance spatial matching degree of the target region is calculated as an auxiliary method.

5. The method for evaluating the coordination of transportation development according to claim 4, characterized in that, The step of calculating and determining the abundance spatial matching degree of elements contained in the two sets based at least on the first information set and the second information set includes: The traffic advantage of the target area is calculated and determined based on the first information set. The degree of spatial distribution balance in the geographical region is used as a reference to dedimensionalize the degree of transportation advantage. Based on the spatial distribution balance, the dimensionless transportation advantage, and each element in the second information set, the abundance spatial matching degree between the transportation advantage and the population, economic, and transportation demand elements in the second information set is calculated and determined.

6. The method for evaluating the coordination of transportation development according to claim 5, characterized in that, The process of calculating and determining the abundance spatial matching degree between the transportation advantage degree and the population, economic, and transportation demand elements in the second information set, based on the spatial distribution balance, the dimensionless transportation advantage degree, and each element in the second information set, includes: Based on the degree of spatial distribution balance, determine the number of counties and districts within the geographical area, the transportation advantage of each county and district, and the first population, first total GDP, first per capita GDP, and first transportation demand of each county and district. The traffic advantage concentration index of the target area is calculated and determined based on the dimensionless traffic advantage, the traffic advantage of each county / district, and the number of counties / districts. Based on the population, economic and transportation demand elements in the second information set, determine the second population size, second total GDP, second GDP per capita and second transportation demand of the target area. The population concentration index of the target area is calculated and determined based on the second population size, the first population size, and the number of county / district areas. The economic concentration index of the target region is calculated and determined based on the second total GDP, the second per capita GDP, the first total GDP, the first per capita GDP, the number of counties and districts, the second population, and the first population. The transportation demand concentration index of the target area is calculated and determined based on the second transportation demand, the first transportation demand, and the number of counties and districts. Calculate the ratios of the population concentration index, economic concentration index, transportation demand concentration index, and transportation advantage concentration index, respectively; Based on each ratio, the spatial matching degree of the abundance of population elements, economic elements, and transportation demand elements relative to transportation elements in the target area is determined.

7. The method for evaluating the coordination of transportation development according to claim 1, characterized in that, The calculation-based abundance spatial matching degree determines the target coordination type characterizing the coordination of traffic development in the target region, including: Determine the weight coefficients of the spatial matching degree of the abundance of population factors, economic factors, and transportation demand factors relative to transportation factors in the target area, respectively. Based on the weighting coefficients and spatial matching degrees of each abundance, the comprehensive coordination of transportation elements with population elements, economic elements, and transportation demand elements in the target area is calculated and determined. The target coordination type is determined based on the comprehensive coordination and the preset evaluation criteria corresponding to different coordination types. The coordination types include advanced, moderately advanced, lagging, and extremely lagging.

8. The method for evaluating the coordination of transportation development according to claim 1, characterized in that, When the target coordination type meets the optimization requirements, the step of determining a target optimization strategy for improving the coordination of the corresponding target geographical region, based at least on the target coordination type, includes: When the target coordination type is different from the standard coordination type, a candidate optimization strategy is determined from the self-optimization strategy set based on the target coordination type. The optimization strategy set includes multiple optimization strategies, and each optimization strategy is matched with a coordination type. Based on the geographical location of the target area, the first information set, and the second information set, the elements that can be optimized and the priority of each element are determined. Based on the aforementioned elements and their corresponding priorities, the candidate optimization strategies are adjusted to obtain a target optimization strategy that adapts to the actual situation of the target region.

9. A device for evaluating the coordination of transportation development, characterized in that, include: The first acquisition module is used to acquire a first set of information related to transportation in the target area; The second acquisition module is used to acquire a second set of information related to population, economy and transportation needs of the target area; The first calculation module is used to calculate and determine the abundance spatial matching degree of the elements contained in the two sets based at least on the first information set and the second information set; The second calculation module is used to calculate and determine the target coordination type that characterizes the coordination of traffic development in the target area based on the calculated abundance spatial matching degree. The first determining module is used to determine, at least based on the target coordination type, a target optimization strategy for improving the coordination of the corresponding target geographical region when the target coordination type meets the optimization requirements.

10. An electronic device, characterized in that, include: At least one processor; as well as, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to implement the traffic development coordination evaluation method as described in any one of claims 1-8.

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