Vehicle base TOD integrated design multi-dimensional factor decision-making method and system

Abstract

The invention relates to a vehicle base TOD integrated design multi-dimensional factor decision-making method and system. At present, a method for analyzing the influence weight of each factor of a vehicle base TOD integrated design strategy does not exist. The method comprises the following steps: carrying out a vehicle base TOD integrated scheme decision; establishing a decision analysis model; main factors influencing vehicle base TOD integration are obtained according to model analysis; and completing a vehicle base TOD integrated scheme decision. According to the vehicle base TOD integrated design multi-dimensional factor decision-making method and system based on the analytic hierarchy process provided by the invention, the influence weight of each factor in the vehicle base TOD integrated design is analyzed, and beneficial reference and guidance are provided for planning, construction and management of an urban rail transit vehicle base; the method has important theoretical and practical significance.

Description

Technical Field

[0001] The present invention relates to the technical field of urban planning and design, and in particular to a multi-dimensional factor decision-making method and system for integrated design of vehicle base TOD. Background Art

[0002] As a public transportation-oriented urban development model, TOD (Transit-Oriented Development) can effectively promote the sustainable development of urban transportation. As an important part of urban rail transit, the integrated construction of vehicle bases in TOD has a great impact on improving urban land use efficiency, creating diversified public spaces, and thus optimizing the urban environment, reducing traffic pressure, and promoting the sustainable development of cities.

[0003] Although the development of the property above the vehicle base has effectively solved the problem of land resource shortage, during the development and construction process, the development project involves land ownership issues, inconsistent construction schedules, overlapping functions, and changing business formats of the complex. There are also design difficulties in terms of spatial layout, structural design, traffic planning, and fire protection design. At the same time, there are many factors that influence each other between the vehicle base and the property above. The multi-dimensional factors that influence the relationship between the vehicle base and the property above include: (1) site and surrounding planning; (2) relative location of the site; (3) overall layout of the base; and (4) humanized measures.

[0004] However, there is currently no method to analyze the influencing weights of various factors in the integrated design strategy of vehicle base TOD. Summary of the invention

[0005] The purpose of the present invention is to provide a multi-dimensional factor decision-making method and system for vehicle base TOD integrated design, so as to at least solve the problem of the current lack of a method for analyzing the influence weights of various factors in vehicle base TOD integrated design.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is:

[0007] The multi-dimensional factor decision-making method for integrated design of vehicle base TOD includes the following steps:

[0008] Carry out vehicle base TOD integrated plan decision-making;

[0009] Establish decision analysis models;

[0010] According to the model analysis, the main factors affecting vehicle base TOD integration are obtained;

[0011] Complete the decision on the vehicle base TOD integration plan.

[0012] Further, we will make decisions on the integrated TOD plan for the vehicle base, including:

[0013] Identify the multi-dimensional factors that affect the vehicle base plan;

[0014] Identify the multi-dimensional factors that affect vehicle base TOD development plans.

[0015] Furthermore, a decision analysis model is established, including:

[0016] Construct a hierarchical model based on multidimensional factors;

[0017] Construct a judgment matrix through a hierarchical model;

[0018] Calculate the single-level weights and single-level consistency tests in the judgment matrix;

[0019] Total hierarchical ordering and total consistency test.

[0020] Furthermore, the hierarchical model includes two second-level indicators, four third-level indicators, and seventeen fourth-level indicators:

[0021] Secondary indicators include vehicle base and TOD development;

[0022] The third-level indicators include the planning of the site and its surroundings, the relative location of the site, the overall layout of the site and humanized measures;

[0023] The four-level indicators include area planning, traffic planning, site functions, commuting distance, relative positions of maintenance depots and operation warehouses, functional zoning, building layout, pipeline settings, fire protection, green ecology, ventilation and lighting, convenient facilities, business formats, public spaces, reserved vacant land development locations, reserved vacant land development areas, and noise and vibration.

[0024] Furthermore, the single-level weights in the judgment matrix are calculated as follows:

[0025] Multiply the elements of the judgment matrix row by row to get the product M of the row elements i ;

[0026] The product of each row M i Take n power respectively and get W i ';

[0027] The vector W i 'Normalize and get the weight W of each factor i ;

[0028] Calculate the maximum eigenvalue λ of the judgment matrix max .

[0029] Furthermore, the elements of the judgment matrix are multiplied row by row to obtain the product M of the row elements. i ,include:

[0030]

[0031] Where:

[0032] A is the judgment matrix;

[0033] The product of each row M i Take n powers respectively and get vector W i ',include:

[0034]

[0035] The vector W i 'Normalize and get the weight W of each factor i ,include:

[0036]

[0037] Calculate the maximum eigenvalue λ of the judgment matrix max ,include:

[0038]

[0039] Where:

[0040] AW is the product of the judgment matrix and the weight vector.

[0041] Further, single-level consistency checks include:

[0042] CI=(λ max -n) / (n-1)

[0043] CR=CI / RI

[0044] Where:

[0045] CI is the consistency index;

[0046] n is the number of comparison factors;

[0047] CR is the consistency ratio;

[0048] RI is the random consistency index;

[0049] Total consistency check, including:

[0050]

[0051] Where:

[0052] CI is the consistency index;

[0053] RI is the average random consistency index;

[0054] CR is the consistency ratio.

[0055] The multi-dimensional factor decision-making system for integrated TOD design of vehicle bases includes:

[0056] Development module, used to make vehicle base TOD integrated plan decisions;

[0057] Establish modules for building decision analysis models;

[0058] The analysis module is used to derive the main factors affecting vehicle base TOD integration based on model analysis;

[0059] The module is completed to complete the vehicle base TOD integrated plan decision.

[0060] Furthermore, the development modules include:

[0061] The first determination submodule is used to determine the multi-dimensional factors that affect the vehicle base plan;

[0062] The second determination submodule is used to determine the multi-dimensional factors that affect the vehicle base TOD development plan.

[0063] Furthermore, the building blocks include:

[0064] The construction submodule is used to construct a hierarchical structure model based on multi-dimensional factors;

[0065] The construction submodule is used to construct the judgment matrix through the hierarchical structure model;

[0066] The calculation submodule is used to calculate the single-level weights and consistency tests in the judgment matrix;

[0067] The sorting submodule is used for hierarchical total sorting and consistency verification.

[0068] Compared with the prior art, the present invention has the following beneficial effects:

[0069] The present invention provides a multi-dimensional factor decision-making method and system for the integrated design of vehicle base TOD based on the hierarchical analysis method, and analyzes the influence weights of various factors in the integrated design of vehicle base TOD. The results show that in order to realize the integrated design of urban rail vehicle base TOD, it is necessary to consider both the vehicle base and TOD development. Among them, the overall plan layout under the cover and the relative position of the site have the largest influence weight, which is the primary consideration in design planning, followed by consideration of the site and surrounding planning. The influence weight of humanized measures is relatively small, which is the last consideration. Therefore, the present invention provides a useful reference and guidance for the planning, construction and management of urban rail transit vehicle bases, and has important theoretical and practical significance. The applicability and optimization strategy of the method of the present invention in vehicle bases of different cities and different sizes can be further explored to achieve wider application and promotion. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, drawings of other embodiments can be obtained based on these drawings without paying creative work.

[0071] Figure 1 It is a flow chart of the present invention;

[0072] Figure 2 It is a relationship diagram between the TOD integrated design of the urban planning vehicle base of the present invention and the secondary and tertiary factors;

[0073] Figure 3 It is the relationship diagram between the vehicle base of the present invention and the third and fourth level factors;

[0074] Figure 4 It is the relationship diagram between TOD development and third and fourth level factors of the present invention;

[0075] Figure 5 It is the general plan under the vehicle base cover;

[0076] Figure 6 It is the overall plan of property development covered by the vehicle base. DETAILED DESCRIPTION

[0077] In order to facilitate the understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. The preferred embodiments of the present invention are given in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thoroughly understood.

[0078] It should be noted that similar reference numerals and letters represent similar items, and therefore, once an item is defined in one embodiment, it does not need to be further defined and explained in subsequent embodiments. In addition, the term "comprising" and the like and any variation thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0079] It should also be noted that although the order of steps is mentioned in the method description, in some cases, they may be performed in an order different from that shown here, and this should not be construed as a limitation on the order of the steps.

[0080] The present invention provides a multi-dimensional factor decision method for integrated design of vehicle base TOD, comprising the following steps:

[0081] S1: Conduct vehicle base TOD integrated plan decision-making;

[0082] S101: Determine the multi-dimensional factors that affect the vehicle base plan;

[0083] S102: Determine the multi-dimensional factors that affect the vehicle base TOD development plan.

[0084] S2: Establish decision analysis model;

[0085] S201: Constructing a hierarchical model based on multidimensional factors;

[0086] S202: constructing a judgment matrix through a hierarchical structure model;

[0087] S203: Calculate the single-level weight and single-level consistency test in the judgment matrix;

[0088] S2031: Multiply the elements of the judgment matrix row by row to obtain the product M of the row elements i ,include:

[0089]

[0090] Where:

[0091] A is the judgment matrix;

[0092] S2032: Product M of each row i Take n powers respectively and get vector W i ',include:

[0093]

[0094] S2033: vector W i 'Normalize and get the weight W of each factor i ,include:

[0095]

[0096] S2034: Calculate the maximum eigenvalue λ of the judgment matrix max ,include:

[0097]

[0098] Where:

[0099] AW is the product of the judgment matrix and the weight vector.

[0100] S2035: Single-level consistency check, including:

[0101] CI=(λ max -n) / (n-1)

[0102] CR=CI / RI

[0103] Where:

[0104] CI is the consistency index;

[0105] n is the number of comparison factors;

[0106] CR is the consistency ratio;

[0107] RI is the random consistency index.

[0108] S204: Total hierarchical sorting and total consistency check.

[0109] S2041: total hierarchical order;

[0110] S2042: Total consistency check, including:

[0111]

[0112] Where:

[0113] CI is the consistency index;

[0114] CR is the consistency ratio;

[0115] RI is the average random consistency index.

[0116] S3: Based on the model analysis, the main factors affecting vehicle base TOD integration are obtained;

[0117] S4: Complete the decision on the vehicle base TOD integration plan.

[0118] Example:

[0119] like Figure 1 As shown, the present invention provides a multi-dimensional factor decision method for integrated design of vehicle base TOD, comprising the following steps:

[0120] S1: Conduct vehicle base TOD integrated plan decision-making;

[0121] S101: Determine the multi-dimensional factors that affect the vehicle base plan;

[0122] (1) Site and surrounding area planning: The planning of the vehicle base directly determines the overall utilization rate of the vehicle base and plays a positive role in promoting the development of the above-ground properties. It mainly includes factors such as area planning and traffic planning.

[0123] (2) Relative location of the depot: Analyze the relative location of the vehicle base in the city and its impact on urban transportation and land use, mainly including factors such as the impact of the depot function and commuting distance.

[0124] (3) General layout under the cover: The development and design of the upper cover of the vehicle base should give priority to the safety and use functions of the lower body, and study the general layout of the vehicle base, mainly including the relative position relationship between the maintenance depot and the operation depot related to the track, functional zoning, building layout, pipeline setting, fire protection and other factors.

[0125] (4) Humanized measures: The vehicle base design incorporates the humanized design concept throughout to improve the quality of life of residents, mainly including factors such as green ecology, ventilation and lighting, and convenient facilities.

[0126] S102: Determine the multi-dimensional factors that affect the vehicle base TOD development plan.

[0127] (1) Site and surrounding planning: The site development is comprehensively analyzed in combination with urban planning within a larger area, mainly including factors such as district planning and transportation planning, business types, and public space.

[0128] (2) Relative position of the site: Analysis of the development of reserved vacant land, mainly including factors such as the location and area of ​​the reserved vacant land.

[0129] (3) General layout under the roof: mainly includes the relative position relationship between the maintenance warehouse and the operation warehouse related to the track, functional zoning, building layout, fire protection, noise and vibration and other factors.

[0130] S2: Establish decision analysis model;

[0131] S201: Constructing a hierarchical model based on multidimensional factors;

[0132] like Figure 2-Figure 4 As shown in the figure, the multi-dimensional factors of vehicle base TOD integration include 2 secondary indicators B, 4 tertiary indicators C and 17 quaternary indicators D, and a hierarchical model is established.

[0133] Secondary indicator B includes vehicle base and TOD development;

[0134] Level 3 index C includes the planning of the site and its surroundings, the relative location of the site, the overall layout of the site and humanized measures;

[0135] The fourth-level indicator D includes area planning, traffic planning, site functions, commuting distance, relative positions of maintenance warehouses and operation warehouses, functional zoning, building layout, pipeline settings, fire protection, green ecology, ventilation and lighting, convenient facilities, business formats, public spaces, reserved vacant land development locations, reserved vacant land development areas and noise and vibration.

[0136] S202: construct a judgment matrix through a hierarchical structure model, and establish a judgment matrix of the next layer to the previous layer.

[0137] The value of each element in the judgment matrix is ​​determined by the 1 to 9 digit scaling method, as shown in Table 1:

[0138] Table 1 Meaning of ratio scale

[0139] Scale value definition illustrate 1 Equally important <![CDATA[C i and C j Both elements are equally important]]> 3 Slightly important <![CDATA[C i Than C j Slightly important]]> 5 Obviously important <![CDATA[C i Than C j Clearly important]]> 7 Strongly important <![CDATA[C i Than C j Strongly important]]> 9 Absolutely important <![CDATA[C i Than C j Absolutely important]]>

[0140] Note: 2, 4, 6, 8 are the middle values ​​of the two judgment levels in Table 1. If factor i is compared with factor j, C ij , then factor j is compared with factor i to get 1 / C ij .

[0141] C i With C j Equally important, C ij =1, C ji =1; C i Than C j Slightly important, then C ij =3, C ji =1 / 3; and so on, thus forming a judgment matrix of one level factor relative to the previous level factor.

[0142] Through the above method, we can get the judgment matrix of the second layer on the first layer:

[0143]

[0144] The judgment matrix of the third layer on the second layer (B1-C layer judgment matrix):

[0145]

[0146] The judgment matrix of the fourth layer on the third layer:

[0147]

[0148] S203: Calculate the single-level weight and single-level consistency test in the judgment matrix;

[0149] S2031: Multiply the elements of the judgment matrix row by row to obtain the product M of the row elements i ,include:

[0150]

[0151] Where:

[0152] A is the judgment matrix;

[0153] S2032: Product M of each rowi Take n powers respectively and get vector W i ',include:

[0154]

[0155] S2033: vector W i 'Normalize and get the weight W of each factor i ,include:

[0156]

[0157] S2034: Calculate the maximum eigenvalue λ of the judgment matrix max ,include:

[0158]

[0159] Where:

[0160] AW is the product of the judgment matrix and the weight vector.

[0161] S2035: Single-level consistency check, including:

[0162] CI=(λ max -n) / (n-1)

[0163] CR=CI / RI

[0164] Where:

[0165] CI is the consistency index;

[0166] n is the number of comparison factors;

[0167] CR is the consistency ratio;

[0168] RI is the random consistency index.

[0169] When CR < 0.1, the consistency of the judgment matrix is ​​considered acceptable, otherwise the judgment matrix should be modified.

[0170] The RI values ​​are shown in Table 2:

[0171] Table 2 Random consistency index RI value

[0172] n 1 2 3 4 5 6 7 8 9 10 11 12 RI 0.00 0.00 0.58 0.80 1.12 1.26 1.36 1.41 1.46 1.49 1.52 1.54

[0173] The single-level weights and single-level consistency tests are obtained through the above root method, as shown in Tables 3 and 4:

[0174] Table 3A-B 1 -CD single-level weight and consistency test

[0175]

[0176] Table 4A-B 2 -CD single-level weight and consistency test

[0177]

[0178] S204: Total hierarchical sorting and total consistency check.

[0179] S2041: Total ranking of levels

[0180] Table 5 Total weight ranking of factors in layer B-C

[0181]

[0182] Table 6B 1 - Total weight ranking of CD layer factors

[0183]

[0184] Table 7B 2 - Total weight ranking of CD layer factors

[0185]

[0186] B 1 -CD, B 2 -CD single-level weight vector combination matrix is ​​multiplied with AB weight vector to obtain the weight of each indicator in D layer.

[0187] W=(0.0177,0.0536,0.0971,0.0194,0.1492,0.1300,0.0738,0.0145,0.036,0.0173,0.035,0

[0188] .0173,0.0395,0.0128,0.1799,0.0899,0.0177) T

[0189] The above formula is used to rank the importance of the 17 factors affecting the integrated design strategy of vehicle base TOD, as shown in Table 8:

[0190] Table 8 Total weight ranking of factors in layer B-D

[0191]

[0192] S2041: Total consistency check

[0193] Sort the total weight of BC layer factors

[0194]

[0195] The obtained consistency ratio CR=0.0164<0.1, the consistency test of the judgment matrix passed, and therefore the weight calculation results of this group can be accepted.

[0196] Sort the total weight of factors in the B1-CD layers

[0197]

[0198] The obtained consistency ratio CR=0.0068<0.1, the consistency test of the judgment matrix passed, and therefore the weight calculation results of this group can be accepted.

[0199] Sort the total weight of factors in the B2-CD layers

[0200]

[0201] The obtained consistency ratio CR=0.0045<0.1, the consistency test of the judgment matrix passed, and therefore the weight calculation results of this group can be accepted.

[0202] S3: Based on the model analysis, the main factors affecting vehicle base TOD integration are obtained;

[0203] From S2, we can see that the two development entities, vehicle base and TOD development, are equally important for the integrated design of TOD of urban rail vehicle base (weights are both 0.5). The order of influence of the four C-level factors on the integrated design of TOD of urban rail vehicle base is: general layout under the roof (0.4209), relative position of the yard (0.3863), yard and surrounding planning (0.1235), and humanized measures (0.0693). The order of influence of the 17 D-level factors on the integrated design of TOD of urban rail vehicle base is: reserved vacant land development position (0.1799), relative position of maintenance depot and operation depot (0.3863), and humanized measures (0.1235). system (0.1492), functional zoning (0.1300), site function (0.0971), reserved white land development area (0.0899), building layout (0.0738), traffic planning (0.0536), ventilation and lighting (0.0520), business format (0.0395), fire protection (0.0385), commuting distance (0.0194), area planning (0.0177), noise and vibration (0.0177), convenient facilities (0.0173), green ecology (0.0173), pipeline setting (0.0145), and public space (0.0128).

[0204] To sum up, to realize the integrated TOD design of urban rail vehicle base, it is necessary to consider both the vehicle base and TOD development. Among them, the overall layout under the roof and the relative position of the site have the greatest influence weight and are the primary consideration in design planning. The second is the consideration of the site and surrounding planning. In comparison, humanized measures have a smaller influence weight and are the last factor to be considered.

[0205] S4: Complete the decision on the vehicle base TOD integration plan.

[0206] The S2 calculation results show that the consistency tests of the judgment matrices at all levels have passed. Therefore, it is feasible to use the hierarchical analysis method to determine the relative importance of the main influencing factors of the TOD integrated design strategy for urban rail vehicle bases.

[0207] In this embodiment, case verification is also carried out, as follows:

[0208] Taking a certain city's property development vehicle base as an example, the factors affecting the TOD integrated decision-making of its vehicle base are verified.

[0209] like Figure 5 and Figure 6 As shown, the north and east sides of the vehicle base are existing roads, and the south side is a planned road. The vehicle base project is located below the cover, and the property development is carried out above the cover, including commercial housing, kindergartens, nine-year compulsory education schools, community centers, etc. The two sides of the cover are vacant land development areas.

[0210] Table 9A-B 1 -CD single-level weight and consistency test

[0211] matrix Weight vector of hierarchical single ordering Eigenvalue Consistency Check AB <![CDATA[(0.5,0.5) T ]]> 2 0＜0.1 <![CDATA[B 1 -C]]> <![CDATA[(0.0938,0.2133,0.5525,0.1404) T ]]> 4.05 0.02＜0.1 <![CDATA[C 1 -D]]> <![CDATA[(0.3333,0.6667) T ]]> 2 0＜0.1 <![CDATA[C 2 -D]]> <![CDATA[(0.8333,0.1667) T ]]> 2 0＜0.1 <![CDATA[C 3 -D]]> <![CDATA[(0.4191,0.2549,0.1609,0.0590,0.1061) T ]]> 5.08 0.0174＜0.1 <![CDATA[C 4 -D]]> <![CDATA[(0.2,0.6,0.2) T ]]> 3 0＜0.1

[0212] Table 10A-B 2 -CD single-level weight and consistency test

[0213] matrix Weight vector of hierarchical single ordering Eigenvalue Consistency Check AB <![CDATA[(0.5,0.5) T ]]> 2 0＜0.1 <![CDATA[B 2 -C]]> <![CDATA[(0.1958,0.4934,0.3108) T ]]> 3.05 0.0516＜0.1 <![CDATA[C 5 -D]]> <![CDATA[(0.0993,0.2497,0.4914,0.1596) T ]]> 4.04 0.017＜0.1 <![CDATA[C 6 -D]]> <![CDATA[(0.75,0.25) T ]]> 2 0＜0.1 <![CDATA[C 7 -D]]> <![CDATA[(0.1897,0.4063,0.2280,0.0606,0.1154) T ]]> 5.08 0.0178＜0.1

[0214] B 1 -CD, B 2 -CD single-level weight vector combination matrix is ​​multiplied with AB weight vector to obtain the weight of each indicator in D layer.

[0215] W=(0.02535,0.055715,0.08887,0.01778,0.145255,0.133555,0.07988,0.0163,0.03872

[0216] 5,0.01404,0.04212,0.01404,0.04811,0.015625,0.185025,0.061675,0.017935) T

[0217] The above formula is used to rank the importance of the factors affecting the integrated design strategy of the vehicle base TOD, as shown in Table 11:

[0218] Table 11 Total weight ranking of factors in layer B-D

[0219]

[0220] B 1 -CD consistency test indicators are:

[0221]

[0222] B 2 -CD consistency test indicators are:

[0223]

[0224] B 1 -CD and B 2 -CD consistency ratios were CR=0.0139<0.10 and CR=0.0176<0.10, respectively, and both passed the consistency test.

[0225] According to the above calculation results, the consistency test of each level judgment matrix has passed. Therefore, it is feasible to use the hierarchical analysis method to study the integrated decision-making of urban rail vehicle base TOD.

[0226] Embodiment 2:

[0227] This embodiment provides a vehicle base TOD integrated design multi-dimensional factor decision system, including:

[0228] Development module, used to make vehicle base TOD integrated plan decisions;

[0229] Establish modules for building decision analysis models;

[0230] The analysis module is used to derive the main factors affecting vehicle base TOD integration based on model analysis;

[0231] The module is completed to complete the vehicle base TOD integrated plan decision.

[0232] Furthermore, the development modules include:

[0233] The first determination submodule is used to determine the multi-dimensional factors that affect the vehicle base plan;

[0234] The second determination submodule is used to determine the multi-dimensional factors that affect the vehicle base TOD development plan.

[0235] Furthermore, the building blocks include:

[0236] The construction submodule is used to construct a hierarchical structure model based on multi-dimensional factors;

[0237] The construction submodule is used to construct the judgment matrix through the hierarchical structure model;

[0238] The calculation submodule is used to calculate the single-level weights and consistency tests in the judgment matrix;

[0239] The sorting submodule is used for hierarchical total sorting and consistency verification.

[0240] The above specific examples are used to illustrate the present invention, which is only used to help understand the present invention and is not intended to limit the present invention. For those skilled in the art, according to the concept of the present invention, some simple deductions, modifications or substitutions can be made.

Claims

1. A multi-dimensional factor decision-making method for integrated TOD design of vehicle bases, characterized by: The following steps are involved: Carry out vehicle base TOD integrated plan decision-making; Establish decision analysis models; According to the model analysis, the main factors affecting vehicle base TOD integration are obtained; Complete the decision on the vehicle base TOD integration plan.

2. The multi-dimensional factor decision-making method for integrated TOD design of vehicle bases according to claim 1 is characterized by: Conduct vehicle base TOD integrated plan decision-making, including: Identify the multi-dimensional factors that affect the vehicle base plan; Identify the multi-dimensional factors that affect vehicle base TOD development plans.

3. The multi-dimensional factor decision-making method for integrated TOD design of vehicle bases according to claim 1 is characterized by: Establish a decision analysis model, including: Construct a hierarchical model based on multidimensional factors; Construct a judgment matrix through a hierarchical model; Calculate the single-level weights and single-level consistency tests in the judgment matrix; Total hierarchical ordering and total consistency test.

4. The multi-dimensional factor decision-making method for integrated TOD design of vehicle bases according to claim 3 is characterized by: The hierarchical model includes two second-level indicators, four third-level indicators, and seventeen fourth-level indicators: Secondary indicators include vehicle base and TOD development; The third-level indicators include the planning of the site and its surroundings, the relative location of the site, the overall layout of the site and humanized measures; The four-level indicators include area planning, traffic planning, site functions, commuting distance, relative positions of maintenance depots and operation warehouses, functional zoning, building layout, pipeline settings, fire protection, green ecology, ventilation and lighting, convenient facilities, business formats, public spaces, reserved vacant land development locations, reserved vacant land development areas, and noise and vibration.

5. The multi-dimensional factor decision-making method for integrated TOD design of vehicle bases according to claim 3 is characterized by: To calculate the single-level weights in the judgment matrix, the steps are as follows: Multiply the elements of the judgment matrix row by row to get the product M of the row elements i ; The product of each row M i Take n power respectively and get W i '; The vector W i 'Normalize and get the weight W of each factor i ; Calculate the maximum eigenvalue λ of the judgment matrix max .

6. The multi-dimensional factor decision-making method for integrated TOD design of vehicle bases according to claim 5 is characterized by: Multiply the elements of the judgment matrix row by row to get the product M of the row elements i ,include: Where: A is the judgment matrix; The product of each row M i Take n powers respectively and get vector W i ',include: The vector W i 'Normalize and get the weight W of each factor i ,include: Calculate the maximum eigenvalue λ of the judgment matrix max ,include: Where: AW is the product of the judgment matrix and the weight vector.

7. The multi-dimensional factor decision-making method for integrated TOD design of vehicle bases according to claim 3 is characterized by: Single-level consistency check, including: CI=(λ max −n) / (n−1) CR=CI / RI Where: CI is the consistency index; n is the number of comparison factors; CR is the consistency ratio; RI is the random consistency index; Total consistency check, including: Where: CI is the consistency index; RI is the average random consistency index; CR is the consistency ratio.

8. The vehicle base TOD integrated design multi-dimensional factor decision-making system is characterized by: include: Development module, used to make vehicle base TOD integrated plan decisions; Establish modules for building decision analysis models; The analysis module is used to derive the main factors affecting vehicle base TOD integration based on model analysis; The module is completed to complete the vehicle base TOD integrated plan decision.

9. The vehicle base TOD integrated design multi-dimensional factor decision system according to claim 8 is characterized by: The modules include: The first determination submodule is used to determine the multi-dimensional factors that affect the vehicle base plan; The second determination submodule is used to determine the multi-dimensional factors that affect the vehicle base TOD development plan.

10. The vehicle base TOD integrated design multi-dimensional factor decision system according to claim 8, characterized in that: The build modules include: The construction submodule is used to construct a hierarchical structure model based on multi-dimensional factors; The construction submodule is used to construct the judgment matrix through the hierarchical structure model; The calculation submodule is used to calculate the single-level weights and consistency tests in the judgment matrix; The sorting submodule is used for hierarchical total sorting and consistency verification.

Images