A parking zoning method and system based on the interactive relationship between land use and traffic

Abstract

The present invention discloses a parking zoning method based on the interactive relationship between land use and traffic, comprising the following steps: S1, obtaining GIS spatial zoning data, land use data and traffic facility data and cleaning them; S2, based on the land use data and traffic facility data obtained in step S1, integrating and calculating the traffic and land use characteristics of the smallest spatial unit to obtain traffic indicators and land use characteristic indicators; S3, clustering the traffic indicators and land use characteristic indicators according to the clustering algorithm to obtain multiple characteristic clustering partitions, and extracting the parking zoning influencing factors from the interactive relationship between traffic and land use by coupling the land use space and traffic characteristics, and constructing a parking planning zoning indicator system that combines traffic and land use, qualitative and quantitative interaction. The parking zoning method and system based on the interactive relationship between land use and traffic provided by the present invention have the effect of guiding the scientific demarcation of parking zoning and promoting refined parking management.

Description

Technical Field

[0001] The present invention relates to the technical field of urban planning, and in particular to a parking zoning method and system based on the interactive relationship between land use and traffic. Background Art

[0002] Urban parking zoning is a technical means of organic interaction with parking management policies, and is also a technical support for scientific and rational parking planning, precise layout and supply of parking facilities. In general, there is no systematic parking zoning planning at home and abroad. Macro policy orientation and single policy measure zoning are more common, and parking zoning relies on qualitative analysis and subjective experience, which lacks scalability. A systematic analysis of existing parking zoning methods summarizes certain limitations and technical bottlenecks, which are mainly manifested in:

[0003] (1) Still based on empirical judgment and comprehensive qualitative analysis;

[0004] (2) Insufficient interaction and coupling between transportation facilities and land use space;

[0005] (3) There is a lack of parking zoning technology for the meso-scale.

[0006] In the context of urban multi-plan integration, integrated planning, construction and management, and high-quality development, the trend in formulating parking zoning is to coordinate the quantitative analysis of urban functions and land development, public transportation, road networks and other factors. Summary of the invention

[0007] In view of the above problems, a parking zoning method based on the interactive relationship between land use and traffic is provided, aiming to solve the problems existing in the prior art.

[0008] The specific technical solutions are as follows:

[0009] A parking zoning method based on the interactive relationship between land use and traffic, comprising the following steps:

[0010] S1. Obtain GIS spatial zoning data, land use data and transportation facility data and clean them;

[0011] S2. Based on the land use data and traffic facility data obtained in step S1, the traffic and land use characteristics of the smallest spatial unit are integrated and calculated to obtain traffic indicators and land use characteristic indicators;

[0012] S3, clustering analysis is performed on the traffic indicators and land use characteristic indicators according to the clustering algorithm to obtain multiple characteristic clustering partitions;

[0013] S4, clustering multiple features into different zones, using entropy weight method for comprehensive evaluation and weighted calculation, to form differentiated parking unit zones;

[0014] S5, fitting and morphologically correcting the boundaries of parking planning partitions to obtain macro and meso parking partitions serving parking planning management;

[0015] The traffic indicators and land use characteristic indicators in step S2 include traffic triggering intensity, public transportation accessibility, and traffic operation load, among which:

[0016] S21. The calculation method of traffic-induced intensity is:

[0017]

[0018] Where: is the traffic induced intensity in zone i, S hk is the land area of ​​the kth plot of land type h, is the average plot ratio of land use type h, F hk is the base plot ratio of the kth plot of land use type h, α h is the weight coefficient of each type of land use;

[0019] S22. Calculation method of public transportation accessibility:

[0020]

[0021] Where: is the public transportation accessibility index of zone i, AI modei represents the connection coefficient of modei type of transportation, n is the number of spatial grids in zone i;

[0022] S23. Calculation method of traffic operation load degree:

[0023]

[0024] In the formula, is the traffic load of zone i, x and y represent the starting and ending points of the road section, β xy is the road grade correction coefficient for section xy, d xy is the road congestion index correction coefficient of section xy, v xy is the traffic volume of section xy, c xy is the section capacity of section xy.

[0025] Furthermore, the spatial zoning data in step S1 includes traffic communities and planning management units, the land use data includes various land use types, land areas and floor area ratios, and the transportation facility data includes rail, bus network and road network supply and operation data.

[0026] Furthermore, step S3 adopts a clustering algorithm to perform characteristic clustering analysis based on the traffic indicators and land use characteristic indicators calculated in steps S21, S22, and S23, and obtains traffic-induced intensity zones, public transportation accessibility zones, and traffic operation load zones, respectively.

[0027] Furthermore, step S4 also includes:

[0028] S41. Use the range transformation method to normalize the traffic-induced intensity, public transportation accessibility, and traffic operation load to obtain the influence coefficient of the same quantitative index:

[0029]

[0030] In the formula, They are the traffic-induced intensity impact coefficient, public transportation accessibility index impact coefficient, and traffic operation load impact coefficient. is the minimum traffic-induced intensity in zone i, is the maximum traffic-induced intensity in zone i, is the minimum value of the public transportation accessibility index of zone i, is the maximum value of the public transportation accessibility index of zone i, is the minimum value of traffic load in zone i, is the maximum value of the traffic load in zone i;

[0031] S42, weighting the traffic-induced intensity influence coefficient, public transportation accessibility index influence coefficient, and traffic operation load influence coefficient obtained in step S41, with the weights being A, B, and C respectively;

[0032] S43, comprehensively evaluating and grading the sum of the products of the influence coefficients and weights of the three indicators to obtain three types of parking units;

[0033]

[0034] In the formula, F sumproduct is the comprehensive index of parking partitions, and F sumproduct The calculation results are divided into three levels, corresponding to three types of parking zones.

[0035] Furthermore, the boundary fitting and morphological correction in step S5 are delineated and corrected by administrative boundaries, mountains, rivers, railways and special control areas.

[0036] A parking zoning system based on the interactive relationship between land use and traffic, characterized by comprising a data acquisition module, a fusion calculation module, a cluster analysis module, a comprehensive calculation module and a fitting correction module;

[0037] The data acquisition module is used to acquire GIS spatial partition data, land use data and transportation facility data and clean them;

[0038] The fusion calculation module, based on the land use data and traffic facility data acquired in step S1, fuses and calculates the traffic and land use characteristics of the smallest spatial unit to obtain traffic indicators and land use characteristic indicators;

[0039] The cluster analysis module performs cluster analysis on traffic indicators and land use characteristic indicators according to a clustering algorithm to obtain multiple characteristic cluster partitions;

[0040] The comprehensive calculation module clusters multiple features into partitions, uses the entropy weight method to perform comprehensive evaluation and weighted measurement, and forms differentiated parking unit partitions;

[0041] The fitting and correction module fits and corrects the boundaries of the parking planning partitions to obtain macro and meso parking partitions for serving parking planning management;

[0042] The specific implementation of the fusion calculation module for calculating traffic indicators and land use characteristic indicators is as follows: traffic indicators and land use characteristic indicators include traffic induced intensity, public transportation accessibility and traffic operation load, among which:

[0043] The calculation method of traffic-induced intensity is:

[0044]

[0045] Where: is the traffic triggering intensity in zone i, S hk is the land area of ​​the kth plot of land type h, is the average plot ratio of land use type h, F hk is the base plot ratio of the kth plot of land use type h, α h is the weight coefficient of each type of land use;

[0046] Calculation method for public transportation accessibility:

[0047]

[0048] Where: is the public transportation accessibility index of zone i, AI modei represents the connection coefficient of modei type of transportation, n is the number of spatial grids in zone i;

[0049] Calculation method of traffic operation load degree:

[0050]

[0051] In the formula, is the traffic load of zone i, x and y represent the starting and ending points of the road section, β xy is the road grade correction coefficient for section xy, d xy is the road congestion index correction coefficient of section xy, v xy is the traffic volume of section xy, c xy is the section capacity of section xy.

[0052] Furthermore, the comprehensive calculation module specifically implements the calculation of parking unit partitions by using the range transformation method to normalize the traffic-induced intensity, public transportation accessibility, and traffic operation load to obtain the same quantitative index influence coefficient:

[0053]

[0054] In the formula, They are the traffic-induced intensity impact coefficient, public transportation accessibility index impact coefficient, and traffic operation load impact coefficient. is the minimum traffic-induced intensity in zone i, is the maximum traffic-induced intensity in zone i, is the minimum value of the public transportation accessibility index of zone i, is the maximum value of the public transportation accessibility index of zone i, is the minimum value of traffic load in zone i, is the maximum value of the traffic load in zone i;

[0055] The obtained traffic-induced intensity influence coefficient, public transportation accessibility index influence coefficient and traffic operation load influence coefficient are weighted and calibrated, and the weights are A, B and C respectively;

[0056] The sum of the products of the influence coefficients and weights of the three indicators is comprehensively evaluated and classified to obtain three types of parking units;

[0057]

[0058] In the formula, F sumproduct is the comprehensive index of parking partitions, and F sumproduct The calculation results are divided into three levels, corresponding to three types of parking zones.

[0059] In summary, the beneficial effects of this scheme are:

[0060] The parking zoning method and system based on the interactive relationship between land use and traffic provided by the present invention couples the land space and traffic characteristics, extracts the parking zoning influencing factors from the interactive relationship between traffic and land use, and constructs a parking planning zoning indicator system that combines traffic and land use, qualitative and quantitative. The parking zoning method and system based on the interactive relationship between land use and traffic provided by the present invention has the effect of guiding the scientific demarcation of parking zoning and promoting refined parking management. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 This is a flow chart of the urban parking planning zoning method based on the interactive relationship between transportation and land use. DETAILED DESCRIPTION

[0062] The claims of the present invention are further described in detail below in conjunction with specific embodiments and drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work also fall within the scope of protection of the present invention.

[0063] The present invention will be further described below in conjunction with specific embodiments, but the present invention is not limited thereto.

[0064] like Figure 1 As shown, the present embodiment provides a parking zoning method based on the interactive relationship between land use and traffic, comprising the following steps:

[0065] S1. Obtain GIS spatial zoning data, land use data and transportation facility data and clean them;

[0066] Preferably, the spatial partition data in step S1 includes traffic communities and planning management units, the land use data includes various land use types, land areas and plot ratios, and the transportation facility data includes rail, bus network and road network supply and operation data.

[0067] S2. Based on the land use data and traffic facility data obtained in step S1, the traffic and land use characteristics of the smallest spatial unit are integrated and calculated to obtain traffic indicators and land use characteristic indicators;

[0068] Preferably, the traffic indicators and land use characteristic indicators in step S2 include traffic induced intensity, public transportation accessibility and traffic operation load, wherein:

[0069] S21. The calculation method of traffic-induced intensity is:

[0070]

[0071] Where: is the traffic induced intensity in zone i, Shk is the land area of ​​the kth plot of land type h, is the average plot ratio of land use type h, F hk is the base plot ratio of the kth plot of land use type h, α h is the weight coefficient of each type of land use;

[0072] S22. Calculation method of public transportation accessibility:

[0073]

[0074] Where: is the public transportation accessibility index of zone i, AI nodei represents the connection coefficient of modei type of transportation, n is the number of spatial grids in zone i;

[0075] S23. Calculation method of traffic operation load degree:

[0076]

[0077] In the formula, is the traffic load of zone i, x and y represent the starting and ending points of the road section, β xy is the road grade correction coefficient for section xy, d xy is the road congestion index correction coefficient of section xy, v xy is the traffic volume of section xy, c xy is the section capacity of section xy.

[0078] It should be noted that, referring to the land construction intensity index control table in the "Regulations on Land Construction Intensity Management in the Main Urban Area of ​​Wuhan City", it is recommended to use residential land R, commercial and business land B, public service land A, industrial land M, green land and square land G. The higher the planning benchmark floor area ratio, the greater the weight value.

[0079] It should also be noted that the road grade correction coefficients recommended for expressways, trunk roads, secondary trunk roads and branch roads are 0.8, 1.0, 0.9 and 0.7 respectively. The road congestion index correction coefficient is recommended to be 0.5-1.0 according to the degree of congestion of the road section.

[0080] S3, clustering analysis is performed on the traffic indicators and land use characteristic indicators according to the clustering algorithm to obtain multiple characteristic clustering partitions;

[0081] Preferably, step S3 adopts a clustering algorithm to perform characteristic clustering analysis based on the traffic indicators and land use characteristic indicators calculated in steps S21, S22, and S23, and obtains traffic-induced intensity zones, public transportation accessibility zones, and traffic operation load zones, respectively.

[0082] It should be noted that the cluster analysis method: a two-dimensional graph theory clustering method is used to perform spatial clustering on the minimum analysis unit according to the spatial adjacency relationship and the similarity of the attributes of each spatial unit. In order to avoid spatial units with similar attributes but non-adjacent spaces being divided into two different categories, the k-means method is used to optimize the clustering results.

[0083] S4, clustering multiple features into different zones, using entropy weight method for comprehensive evaluation and weighted calculation, to form differentiated parking unit zones;

[0084] Preferably, step S4 further includes:

[0085] S41. Use the range transformation method to normalize the traffic-induced intensity, public transportation accessibility, and traffic operation load to obtain the influence coefficient of the same quantitative index:

[0086]

[0087] In the formula, They are the traffic-induced intensity impact coefficient, public transportation accessibility index impact coefficient, and traffic operation load impact coefficient. is the minimum traffic-induced intensity in zone i, is the maximum traffic-induced intensity in zone i, is the minimum value of the public transportation accessibility index of zone i, is the maximum value of the public transportation accessibility index of zone i, is the minimum value of traffic load in zone i, is the maximum value of the traffic load in zone i;

[0088] S42, weighting the traffic-induced intensity influence coefficient, public transportation accessibility index influence coefficient, and traffic operation load influence coefficient obtained in step S41, with the weights being A, B, and C respectively;

[0089] S43, comprehensively evaluating and grading the sum of the products of the influence coefficients and weights of the three indicators to obtain three types of parking units;

[0090]

[0091] In the formula, F sumproduct is the comprehensive index of parking partitions, and F sumproduct The calculation results are divided into three levels, corresponding to three types of parking zones.

[0092] It should be noted that, taking Wuhan as an example, according to the urban status of Wuhan, the weights can be A=0.4, B=0.4, and C=0.2 respectively.

[0093] It should also be noted that Fsumproduct The calculation results are divided into three levels according to (0,0.4], (0.4,0.75), and [0.75,1], corresponding to the three types of parking zones.

[0094]

[0095] S5. Fit and modify the morphology of the parking planning partition boundaries to obtain macro and meso parking partitions serving parking planning management.

[0096] Preferably, the boundary fitting and morphological correction in step S5 are delineated and corrected by administrative boundaries, mountains, rivers, railways and special control areas.

[0097] A parking zoning system based on the interactive relationship between land use and traffic, comprising a data acquisition module, a fusion calculation module, a cluster analysis module, a comprehensive calculation module and a fitting correction module;

[0098] Data acquisition module, used to obtain GIS spatial partition data, land use data and transportation facility data and clean them;

[0099] The fusion calculation module, based on the acquired land use data and transportation facility data, integrates and calculates the transportation and land use characteristics of the smallest spatial unit to obtain the transportation index and land use characteristic index;

[0100] The cluster analysis module performs cluster analysis on traffic indicators and land use characteristic indicators according to the clustering algorithm to obtain multiple characteristic cluster partitions;

[0101] The comprehensive calculation module clusters multiple features into partitions, uses the entropy weight method for comprehensive evaluation and weighted measurement, and forms differentiated parking unit partitions;

[0102] The fitting and correction module fits and corrects the boundaries of the parking planning partitions to obtain macro and meso parking partitions that serve parking planning management.

[0103] Preferably, the fusion calculation module specifically implements the calculation of traffic indicators and land use characteristic indicators as follows: the traffic indicators and land use characteristic indicators include traffic triggering intensity, public transportation accessibility and traffic operation load, where:

[0104] The calculation method of traffic-induced intensity is:

[0105]

[0106] Where: is the traffic triggering intensity in zone i, S hk is the land area of ​​the kth plot of land type h, is the average plot ratio of land use type h, F hkis the base plot ratio of the kth plot of land use type h, α h is the weight coefficient of each type of land use;

[0107] Calculation method for public transportation accessibility:

[0108]

[0109] Where: is the public transportation accessibility index of zone i, AI modei represents the connection coefficient of modei type of transportation, n is the number of spatial grids in zone i;

[0110] Calculation method of traffic operation load degree:

[0111]

[0112] In the formula, is the traffic load of zone i, x and y represent the starting and ending points of the road section, β xy is the road grade correction coefficient for section xy, d xy is the road congestion index correction coefficient of section xy, v xy is the traffic volume of section xy, c xy is the section capacity of section xy.

[0113] Preferably, the comprehensive calculation module specifically implements the calculation of parking unit partitions by using the range transformation method to normalize the traffic induced intensity, public transportation accessibility index and traffic operation load degree to obtain the same quantitative index influence coefficient:

[0114]

[0115] In the formula, They are the traffic-induced intensity impact coefficient, public transportation accessibility index impact coefficient, and traffic operation load impact coefficient. is the minimum traffic-induced intensity in zone i, is the maximum traffic-induced intensity in zone i, is the minimum value of the public transportation accessibility index of zone i, is the maximum value of the public transportation accessibility index of zone i, is the minimum value of the traffic load in zone i, is the maximum value of the traffic load in zone i;

[0116] The obtained traffic-induced intensity influence coefficient, public transportation accessibility index influence coefficient and traffic operation load influence coefficient are weighted and calibrated, and the weights are A, B and C respectively;

[0117] The sum of the products of the influence coefficients and weights of the three indicators is comprehensively evaluated and classified to obtain three types of parking units;

[0118]

[0119] In the formula, F sumproduct is the comprehensive index of parking partitions, and F sumproduct The calculation results are divided into three levels, corresponding to three types of parking zones.

[0120] It should be noted that, taking Wuhan as an example, according to the urban status of Wuhan, the weights can be A=0.4, B=0.4, and C=0.2 respectively.

[0121] It should also be noted that F sumproduct The calculation results are divided into three levels according to (0,0.4], (0.4,0.75), and [0.75,1], corresponding to the three types of parking zones.

[0122]

[0123] Working principle: The present invention integrates and calculates the data of land space, transportation facilities, traffic operation and other data in each spatial unit, extracts the characteristic indicators of land use and traffic interaction such as traffic triggering intensity, traffic accessibility, and traffic operation load, and forms corresponding characteristic clustering partitions. The parking unit partitions are delineated through a comprehensive evaluation of spatial constraints and indicators, and the boundaries are fitted in combination with relevant planning and management policy requirements to obtain parking partitions for macro and meso scales, further improving the scientificity, efficiency and applicability of parking partitions in multiple application scenarios such as parking planning, management and policy formulation.

[0124] The above are only preferred embodiments of the present invention, and are not intended to limit the implementation methods and protection scope of the present invention. Those skilled in the art should be aware that all solutions obtained by equivalent substitutions and obvious changes made using the contents of the specification of the present invention should be included in the protection scope of the present invention.

Claims

1. A parking zoning method based on the interactive relationship between land use and traffic, characterized in that: The following steps are involved: S1. Obtain GIS spatial zoning data, land use data and transportation facility data and clean them; S2. Based on the land use data and traffic facility data obtained in step S1, the traffic and land use characteristics of the smallest spatial unit are integrated and calculated to obtain traffic indicators and land use characteristic indicators; S3, clustering analysis is performed on the traffic indicators and land use characteristic indicators according to the clustering algorithm to obtain multiple characteristic clustering partitions; S4, clustering multiple features into different zones, using entropy weight method for comprehensive evaluation and weighted calculation, to form differentiated parking unit zones; S5. Fitting and morphologically correcting the boundaries of the parking planning partitions to obtain service parking planning and management parking partitions; The traffic indicators and land use characteristic indicators in step S2 include traffic triggering intensity, public transportation accessibility, and traffic operation load, among which: S21. The calculation method of traffic-induced intensity is: Where: is the traffic triggering intensity in zone i, S hk is the land area of ​​the kth plot of land type h, is the average plot ratio of land use type h, F hk is the base plot ratio of the kth plot of land use type h, α h is the weight coefficient of each type of land use; S22. Calculation method of public transportation accessibility: Where: is the public transportation accessibility index of zone i, AU modei represents the connection coefficient of modei type of transportation, n is the number of spatial grids in zone i; S23. Calculation method of traffic operation load degree: In the formula, is the traffic load of zone i, x and y represent the starting and ending points of the road section, β xy is the road grade correction coefficient for section xy, d xy is the road congestion index correction coefficient of section xy, v xy is the traffic volume of road section xy, c xy is the section capacity of section xy.

2. A parking zoning method based on the interactive relationship between land use and traffic according to claim 1, characterized in that: The spatial partition data in step S1 includes traffic communities and planning management units, the land use data includes various land use types, land areas and plot ratios, and the transportation facility data includes rail, bus network and road network supply and traffic operation data.

3. A parking zoning method based on the interactive relationship between land use and traffic according to claim 2, characterized in that: Step S3 uses a clustering algorithm to perform feature clustering analysis based on the traffic indicators and land use characteristic indicators calculated in steps S21, S22, and S23, and obtains traffic-induced intensity zones, public transportation accessibility zones, and traffic operation load zones, respectively.

4. A parking zoning method based on the interactive relationship between land use and traffic according to claim 3, characterized in that: Step S4 also includes: S41. Use the range transformation method to normalize the traffic-induced intensity, public transportation accessibility, and traffic operation load to obtain the influence coefficient of the same quantitative index: In the formula, They are the traffic-induced intensity impact coefficient, public transportation accessibility index impact coefficient, and traffic operation load impact coefficient. is the minimum traffic-induced intensity in zone i, is the maximum traffic-induced intensity in zone i, is the minimum value of the public transportation accessibility index of zone i, is the maximum value of the public transportation accessibility index of zone i, is the minimum value of traffic load in zone i, is the maximum value of the traffic load in zone i; S42, weighting the traffic-induced intensity influence coefficient, public transportation accessibility index influence coefficient, and traffic operation load influence coefficient obtained in step S41, with the weights being A, B, and C respectively; S43, comprehensively evaluating and grading the sum of the products of the influence coefficients and weights of the three indicators to obtain three types of parking units; In the formula, F sumproduct is the comprehensive index of parking partitions, and F sumproduct The calculation results are divided into three levels, corresponding to three types of parking zones.

5. The parking zoning method based on the interactive relationship between land use and traffic according to claim 4 is characterized in that: The boundary fitting and morphological correction in step S5 are delineated and corrected by administrative boundaries, mountains, rivers, railways and special control areas.

6. A parking zoning system based on the interactive relationship between land use and traffic, characterized in that: It includes data acquisition module, fusion calculation module, cluster analysis module, comprehensive calculation module and fitting correction module; The data acquisition module is used to acquire GIS spatial partition data, land use data and transportation facility data and clean them; The fusion calculation module, based on the acquired land use data and traffic facility data, fuses and calculates the traffic and land use characteristics of the smallest spatial unit to obtain traffic indicators and land use characteristic indicators; The cluster analysis module performs cluster analysis on traffic indicators and land use characteristic indicators according to a clustering algorithm to obtain multiple characteristic cluster partitions; The comprehensive calculation module clusters multiple features into partitions, uses the entropy weight method to perform comprehensive evaluation and weighted measurement, and forms differentiated parking unit partitions; The fitting and correction module fits and corrects the boundaries of the parking planning partition to obtain the service parking planning and management parking partition; The specific implementation of the fusion calculation module for calculating traffic indicators and land use characteristic indicators is as follows: traffic indicators and land use characteristic indicators include traffic induced intensity, public transportation accessibility and traffic operation load, among which: The calculation method of traffic-induced intensity is: Where: is the traffic induced intensity in zone i, S hk is the land area of ​​the kth plot of land type h, is the average plot ratio of land use type h, F hk is the base plot ratio of the kth plot of land use type h, α h is the weight coefficient of each type of land use; Calculation method for public transportation accessibility: Where: is the public transportation accessibility index of zone i, AU modei represents the connection coefficient of modei type of transportation, n is the number of spatial grids in zone i; Calculation method of traffic operation load degree: In the formula, is the traffic load of zone i, x and y represent the starting and ending points of the road section, β xy is the road grade correction coefficient of section xy, d xy is the road congestion index correction coefficient of section xy, v xy is the traffic volume of road section xy, c xy is the section capacity of section xy.

7. The parking zoning system based on the interactive relationship between land use and traffic according to claim 6 is characterized in that: The comprehensive calculation module specifically implements the calculation of parking unit partitions by using the range transformation method to normalize the traffic-induced intensity, public transportation accessibility, and traffic operation load to obtain the same quantitative index influence coefficient: In the formula, They are the traffic-induced intensity impact coefficient, public transportation accessibility index impact coefficient, and traffic operation load impact coefficient. is the minimum traffic-induced intensity in zone i, is the maximum traffic-induced intensity in zone i, is the minimum value of the public transportation accessibility index of zone i, is the maximum value of the public transportation accessibility index of zone i, is the minimum value of traffic load in zone i, is the maximum value of the traffic load in zone i; The obtained traffic-induced intensity influence coefficient, public transportation accessibility index influence coefficient and traffic operation load influence coefficient are weighted and calibrated, and the weights are A, B and C respectively; The sum of the products of the influence coefficients and weights of the three indicators is comprehensively evaluated and classified to obtain three types of parking units; In the formula, F sumproduct is the comprehensive index of parking partitions, and F sumproduct The calculation results are divided into three levels, corresponding to three types of parking zones.

Images