Urban open block evaluation and analysis method and system

Abstract

The invention discloses a city open block evaluation analysis method and system, and the method comprises the steps: setting an initial open block influence region of a city, obtaining the traffic volume of each road in the influence region before and after the opening of the initial open block influence region, calculating the saturation degree of each road before and after the opening, determining an affected road according to the road saturation degree, and carrying out the evaluation analysis of the urban open block. Determining the influence range of the influence area of the open block; constructing an evaluation analysis index system; establishing an evaluation analysis method model: determining an index grey class level quantitative standard according to an index layer, calculating a whitening weight function characteristic value, and constructing a whitening weight function; weighting each index layer, and calculating a gray clustering coefficient and a clustering coefficient vector; and according to the obtained clustering coefficient vector, determining a grey class to which the block is opened and affiliated, and further outputting a result for evaluating whether the block is suitable for being opened or not. From qualitative and quantitative angles, the invention provides an effective and reliable evaluation analysis method for block opening.

Description

Technical Field

[0001] The present invention relates to the field of urban traffic planning, and in particular to an evaluation and analysis method and system for urban open blocks. Background Art

[0002] In order to enhance the vitality of the urban economy and build a comfortable urban traffic environment, the urban development model of "small blocks and dense road networks" has gradually replaced the urban development model of "large blocks and wide roads", and open blocks have gradually become a direction of urban development. At the same time, open blocks also bring some unfavorable factors, such as block safety management, property rights protection, noise nuisance, etc. Therefore, in the urban traffic planning stage, it is urgent to evaluate and analyze the feasibility and necessity of opening a block. Based on this, the present invention proposes an evaluation and analysis method for urban open blocks, which provides a scientific basis for the evaluation and analysis of whether blocks are open during urban planning and construction, and provides a reference for urban traffic planning managers. The present invention has important reference and practical significance. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide an evaluation and analysis method and system for urban open blocks, in view of the technical problem that it is difficult to determine the feasibility and necessity of opening urban blocks in the existing technology.

[0004] The technical solution adopted by the present invention to solve its technical problem is: The present invention provides an evaluation and analysis method for urban open blocks, the method comprising the following steps: Step 1: Set the preliminary open block impact area of ​​the city, obtain the traffic volume of each road in the preliminary open block impact area before and after the opening, calculate the saturation of each road before and after the opening, determine the affected roads based on the road saturation, and then determine the impact range of the open block impact area; Step 2: Construct an evaluation and analysis indicator system, which includes two characteristic layers: traffic characteristic layer and social impact characteristic layer, and further divide the characteristic layer into 12 indicator layers; Step 3: Establish an evaluation analysis method model, including: determining the quantitative standard of the gray class level of the indicator according to the indicator layer, calculating the characteristic value of the whitening weight function, and constructing the whitening weight function; assigning weights to each indicator layer, and calculating the gray clustering coefficient and clustering coefficient vector; Step 4: Based on the obtained clustering coefficient vector, determine the gray class to which the block belongs, and then output the result of evaluating whether the block is suitable for opening.

[0005] Furthermore, the method of step 1 of the present invention comprises: Step 1.1: The area enclosed by the first main road immediately adjacent to the road where the open block is located is used as the preliminary open block impact area; Step 1.2: Within the initially determined open block impact area, obtain the traffic volume of each road during the peak hours before and after the block opening. The peak hour traffic volume is the average of the morning and evening peak traffic volumes for at least three consecutive days. Step 1.3: Calculate the saturation of each road before and after the block is opened; Step 1.4: Determine the affected roads based on the calculated saturation of each road before and after the block opening; Step 1.5: After determining the affected roads, the area enclosed by the outermost affected roads centered on the open block is the open block impact area. If there are roads that cannot be enclosed, the affected roads are extended outward to intersect with the adjacent main roads. The enclosed area formed is the open block impact area.

[0006] Furthermore, the method of step 1.3 of the present invention includes: Will p 1. p 2 as the saturation index of each road before and after the block is opened: p 1 =v 1 / c , p 2 =v 2 / c , c = c 0· m · f 1. f 2. f 3 in, v 1 is the one-way peak hour traffic volume of the road before the block was opened; v 2 is the peak hour traffic volume of the road in one direction after the block is opened; c is the traffic capacity of the road section; c 0 is the possible traffic capacity; m is the number of one-way lanes; f 1 is the reduction factor of lane width and lateral clearance on traffic capacity; f 2 is the reduction factor of driver conditions on traffic capacity; f 3 is the traffic composition reduction factor; The method of step 1.4 includes: The area affected by the preliminary open block is n roads, and the saturation of each road is p n , p 1n Opening the front road for the neighborhood n saturation, p 2n Opening back roads for neighborhoods n saturation; if satisfiedp 1n <0.9, p 2n <0.9, and p 2n / p 1n >1.2, or when p 1n <0.9, p 2n ≥0.9, and p 2n / p 1n ≥1, or when p 1n ≥0.9, p 2n ≥0.9, and p 2n / p 1n When ≥1, it means the road n For the affected roads; if p 1n ≥0.9, p 2n <0.9, and p 2n / p 1n When <1, it means the road n Not an affected road.

[0007] Furthermore, the method of step 2 of the present invention comprises: Step 2.1: Based on the characteristics of open blocks, an evaluation and analysis index system is constructed, which includes two characteristic layers: the traffic characteristic layer T and social impact feature layer S ; Step 2.2, Traffic feature layer T It includes 7 indicator layers, namely, the road network density in the affected area T1 , the area ratio of street blocks in the affected area T2 , intersection density in the impact area T3 , Non-linear coefficient of road network in the affected area T4 , Impact area road network connectivity T5 , Average distance between roads in the affected area T6 , affecting the speed of vehicles on the road network in the area T7 ; Step 2.3: Social Impact Feature Layer S It includes five social impact characteristic layers, namely the parking convenience of each road in the impact area S1 , safety of open streets S2 , open block road entrances and exits for convenience S3, the noise environment impact of open blocks S4 , open blocks as road integrity S5 .

[0008] Furthermore, the indicator layer and social impact feature layer of the present invention include: Road network density in the affected area T1 for:

[0009] in, l n is the length of each road n in the affected area, s The area of ​​the development block impact zone; The block road area ratio T2 in the impact area is:

[0010] in, r n is the area of ​​each road n in the affected area, s The area of ​​the development block impact zone; Intersection density in the affected area T3 for:

[0011] in, c is the number of intersections in the impact area, s The area of ​​the development block impact zone; Comprehensive non-linear coefficient of road network in the affected area T4 for: ,

[0012] in, t ij for i , j The nonlinear coefficient between points, N is the number of road network nodes in the affected area, l 1 is the actual length of the starting and ending points of the road network, l 2 is the spatial length of the starting and ending points of the road network; Impact area road network connectivity T5 for:

[0013] in, J is the number of road network edges in the affected area, N is the number of road network nodes in the affected area; Average distance between roads in the affected area T6 for:

[0014] in, d ij for i , j Node spacing, J is the number of road network edges in the impact area; Road network speed in the affected area T7 for:

[0015] in, v n is the speed of the vehicle on the nth road, n is the number of roads; Parking convenience of roads in the affected area S1 for:

[0016] in, L s is the length of the road within the impact area where parking is allowed, w s The width of the road where parking is allowed in the impact area. p is the population in the affected area; Safety in open streets S2 for: The safety level of the blocks after opening is divided into: strong, relatively strong, average, relatively weak, and weak, with values ​​of 0.9, 0.7, 0.5, 0.3, and 0.1 respectively.

[0017] Convenience of entrances and exits of open block roads S3 for:

[0018] in, k is the total number of entrances and exits on the open block road; Noise environmental impact of open blocks S4 for: According to the noise environment impact effect, it is divided into: good, better, average, poor, and bad, with the assigned values ​​being 0.9, 0.7, 0.5, 0.3, and 0.1 respectively; Open Blocks as Road Integrity S5 for: After the blocks are opened and the original streets are used as roads, whether the original street facilities can meet the conditions for use as roads, including road conditions and traffic conditions, is divided into: good, better, average, poor, and bad based on a complete urban road, with values ​​of 0.9, 0.7, 0.5, 0.3, and 0.1 respectively.

[0019] Furthermore, the method of step 3 of the present invention includes: Step 3.1: Divide the indicators into three levels: I, II, and III, where I is "not suitable for opening", II is "allowable for opening", and III is "suitable for opening". Determine the quantitative standard for the gray level of the indicators based on the corresponding thresholds set for each indicator layer; The quantitative standards for the gray level of each indicator are as follows: (1) Road network density in the affected area T1 (Unit: km / km 2 ) Road network density in the affected area T1 is a positive impact indicator, among which: T1 ≤1.26, grade III; when 1.26< T1 ≤1.54, grade II; when 1.54< T1 , level is Ⅰ.

[0020] (2) Street area ratio within the affected area T2 (unit:%) Block road area ratio within the affected area T2 is a positive impact indicator, where: 20% of the road area ratio is used as the standard value for the road to be suitable for block opening. T2 ≤20%, grade III; when 20%< T2 ≤25%, grade II; when 25%< T2 , level is Ⅰ.

[0021] (3) Intersection density in the impact area T3 (Unit: per 0.01km 2 ) Intersection density in the affected area T3 is a negative impact indicator, where: T3 ≥3, grade III; when 2≤ T3 <3, grade is Ⅱ; when T3 <2, level is Ⅰ.

[0022] (4) Comprehensive non-linear coefficient of the road network in the affected area T4 Comprehensive non-linear coefficient of road network in the affected area T4 is a negative impact indicator, where: T4 ≥1.3, grade III; when 1.2≤ T4 <1.3, grade is Ⅱ; when T4 <1.2, grade is Ⅰ.

[0023] (5) Impact on road network connectivity within the area T5 Impact area road network connectivity T5 is a positive impact indicator, where: T5≤2.9, grade III; when 2..9< T5 ≤3.2, grade II; when 3.2< T5 , level is Ⅰ.

[0024] (6) Average distance between roads in the affected area T6 (Unit: m) Average distance between roads in the affected area T6 is a positive impact indicator, where: T6 ≤200, grade is III; when 200< T6 ≤230, grade II; when 230< T6 , level is Ⅰ.

[0025] (7) Impact on road network speed within the area T7 (Unit: km / h) Road network speed in the affected area T7 is a positive impact indicator, where: T7 ≤20, grade is III; when 20< T7 ≤35, grade II; when 35< T7 , level is Ⅰ.

[0026] (8) Parking convenience of roads within the affected area S1 Parking convenience of roads in the affected area S1 is a positive impact indicator, where: S1 ≤0.13, grade is III; when 0.13< S1 ≤0.18, grade II; when 0.18< S1 , level is Ⅰ.

[0027] (9) Safety of open streets S2 Safety in open streets S2 is a negative impact indicator, where: S2 ≥0.7, grade III; when 0.3< S2 <0.7, grade is Ⅱ; when S2 ≤0.3, grade I.

[0028] (10) Convenience of entrances and exits to open streets S3 Convenience of entrances and exits of open block roads S3 is a positive impact indicator, where: S3 ≤2, level is III; when 2< S3 ≤4, grade II; when 4< S3 , level is Ⅰ.

[0029] (11) Noise impact on open streets S4 Noise environmental impact of open blocks S4 is a negative impact indicator, where: S4 ≥0.7, grade III; when 0.3< S4 <0.7, grade is Ⅱ; when S4 ≤0.3, grade I.

[0030] (12) Integrity of open blocks as roads S5 Open Blocks as Road Integrity S5 are positive impact indicators, among which: S5 ≤0.3, grade is III; when 0.3< S5 ≤0.7, grade II; when 0.7< S5 , level is Ⅰ.

[0031] Step 3.2: Based on the gray level quantization standard of each indicator layer in step 3.1, calculate the corresponding whitening weight function eigenvalue l jk ;index j No. k The value ranges of the gray classes are different. j =1, 2, ..., 12; k = 1, 2, 3, then the eigenvalue l jk Also different, the formula is:

[0032] Step 3.3: Calculate each indicator layer x ij Standardized processing indicators Z ij ; Step 3.4: Construct whitening weight function f j k ( x ); Step 3.5: Assign weights to each indicator layer. The weighting methods include: Subjective weighting, using AHP hierarchical analysis method to obtain each indicator layer x j Corresponding subjective weight α j ; Objectively assign weights and use entropy analysis to obtain each indicator layer x j Corresponding subjective weight β j ; Comprehensive empowerment, the formula is:

[0033] Step 3.6: Calculate the grey clustering coefficient and clustering coefficient vector.

[0034] Furthermore, the method of step 3.4 of the present invention includes: The gray class number is in the interval (-∞, x j k ( u )], then the whitening weight function is:

[0035] The gray class number is in the interval [ x j k (1), x j k ( u )], then the whitening weight function is:

[0036] The gray class number is in the interval [ x j k ( u ), +∞), then the whitening weight function is: .

[0037] Furthermore, the method of step 3.6 of the present invention includes: Based on the indicators in step 3.1, the levels of the blocks are divided into three levels according to whether they are open, which correspond to three gray clustering coefficients: y k , where k=1,2,3, and each coefficient is a whitening weight function f j k ( x ) and comprehensive weight o j The weighted sum of is calculated as follows: , ,

[0038] Then, the clustering coefficient vector is y k= ( y 1, y 2, y 3).

[0039] Furthermore, the method of step 4 of the present invention includes: Based on the clustering coefficient vector in step 3.6, determine the gray category to which the block belongs, that is, unsuitable for opening, possible for opening, or suitable for opening; according to the clustering maximum principle, max ( y k )= y k * , then the indicator is judged to belong to the gray category k *, you can evaluate whether the block is suitable for opening.

[0040] The present invention provides an evaluation and analysis system for urban open blocks, comprising: a memory for storing executable computer programs; The processor is used to implement the above-mentioned urban open block evaluation and analysis method when executing the executable computer program stored in the memory.

[0041] The beneficial effects produced by the present invention are: This paper provides an evaluation and analysis method for urban open blocks. It proposes, for the first time, a qualitative and quantitative analysis method for the impact zone of block opening. It comprehensively considers the impact of open blocks on urban transportation and social impact, constructing a multi-layered comprehensive evaluation system consisting of a traffic characteristic layer, a social impact characteristic layer, and twelve indicator layers. Furthermore, a mathematical analysis model is established, resulting in an effective and reliable evaluation and analysis method for block opening. This method is streamlined, efficient, rational, and scientific. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The present invention will be further described below with reference to the accompanying drawings and embodiments, in which: Figure 1 This is a flowchart of an evaluation and analysis method for urban open blocks; Figure 2 This is a schematic diagram of the urban open block evaluation index system; Figure 3 This is a schematic diagram of the urban open block evaluation index system; Figure 4 Schematic diagram of the model for urban open block evaluation and analysis methods. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0044] like Figure 1As shown, the present invention provides an evaluation and analysis method for urban open blocks, and the evaluation method process is: determine the impact range of the open block → construct an evaluation and analysis indicator system → establish an evaluation and analysis method model → evaluate whether the block is suitable for opening.

[0045] Step 1: Aiming at the limitations of the existing block impact range determination method, a "qualitative + quantitative" analysis method is proposed to determine the impact range of the open block and the evaluation method process (such as Figure 2 The specific steps are as follows: preliminarily determine the impact area of ​​the open block → obtain the traffic volume of each road in the impact area before and after the block is opened → calculate the saturation of each road before and after the block is opened → determine the affected roads → determine the impact area of ​​the open block.

[0046] In order to better understand step 1, the present invention is described below.

[0047] First, the impact area of ​​the open block is preliminarily determined: the area enclosed by the first main road adjacent to the road where the open block is located is used as the preliminarily determined impact area of ​​the open block.

[0048] Secondly, obtain the traffic volume of each road in the impact area before and after the block is opened: within the impact area of ​​the preliminarily determined open block, investigate and obtain the traffic volume of each road during the peak period before and after the block is opened, where the peak hour traffic volume is the average of the morning and evening peak traffic volumes for no less than three consecutive days.

[0049] Secondly, calculate the saturation of each road before and after the block is opened: p 1. p 2 respectively As an indicator of the saturation of each road before and after the block is opened: p 1 =v 1 / c , p 2 =v 2 / c , c = c 0· m · f 1. f 2. f 3 in, v 1—one-way peak hour traffic volume of the road before the block was opened; v 2—one-way peak hour traffic volume of the road after the block is opened; c—road section traffic capacity; c 0—Possible traffic capacity (pcu / h); m —Number of one-way lanes; f 1—Reduction factor of lane width and lateral clearance on traffic capacity; f 2—Reduction factor of driver condition on traffic capacity; f 3—Traffic composition reduction factor.

[0050] Next, determine the affected roads: Set the initial open block impact area n roads, and the saturation of each road is p n , p 1n Opening the front road for the neighborhood n saturation, p 2n Opening back roads for neighborhoods n saturation; if satisfied p 1n <0.9, p 2n <0.9, and p 2n / p 1n >1.2, or when p 1n <0.9, p 2n ≥0.9, and p 2n / p 1n ≥1, or when p 1n ≥0.9, p 2n ≥0.9, and p 2n / p 1n When ≥1, it means the road n For the affected roads; if p 1n ≥0.9, p 2n <0.9, and p 2n / p 1n When <1, it means the road n Not an affected road; The first threshold corresponds to 0.9, and the second threshold corresponds to 1.2.

[0051] Finally, determine the open block impact area: After determining the affected roads, the area enclosed by the outermost affected roads centered on the open block is the open block impact area; when enclosing, if there are roads that cannot be enclosed, the affected roads will be extended outward and intersect with the adjacent main roads. The enclosed area formed will be the open block impact area.

[0052] Step 2: Based on the characteristics of the open blocks, an evaluation and analysis index system is constructed (e.g. Figure 3As shown in Figure 2), it contains 2 feature layers and 12 indicator layers; 2 feature layers are traffic feature layers. T and social impact feature layer S Traffic characteristic layer T Contains 7 indicator layers, social impact characteristic layer S There are five social impact characteristic layers in turn.

[0053] In order to better understand step 2, the present invention is described below.

[0054] Traffic feature layer T It contains 7 indicator layers, namely the road network density in the impact area T1 , the area ratio of street blocks in the affected area T2 , intersection density in the impact area T3 , Non-linear coefficient of road network in the affected area T4 , Impact area road network connectivity T5 , Average distance between roads in the affected area T6 , affecting the speed of vehicles on the road network in the area T7 Social impact characteristic layer S There are five social impact characteristic layers, namely the parking convenience of each road in the impact area. S1 , safety of open streets S2 , open block road entrances and exits for convenience S3 , the noise environment impact of open blocks S4 , open blocks as road integrity S5 .

[0055] The values ​​of each indicator layer are obtained as follows: (1) Road network density in the affected area T1

[0056] in, l n —The length of each road n in the affected area, s —The area of ​​the development block’s impact zone.

[0057] (2) Street area ratio T2 within the affected area

[0058] in, r n —The area of ​​each road n in the affected area, s —The area of ​​the development block’s impact zone.

[0059] (3) Intersection density in the impact area T3

[0060] in, c —Number of intersections in the affected area, s —The area of ​​the development block’s impact zone.

[0061] (4) Comprehensive non-linear coefficient of the road network in the affected area T4 ,

[0062] in, t ij — i , j The nonlinear coefficient between points, N —Number of road network nodes in the affected area, l 1—the actual length of the starting and ending points of the road network, l 2—The spatial length of the starting and ending points of the road network.

[0063] (5) Impact on road network connectivity within the area T5

[0064] in, J —Number of road network edges in the affected area, N —Number of road network nodes in the affected area.

[0065] (6) Average distance between roads in the affected area T6

[0066] in, d ij — i , j Node spacing, J —Number of road network edges within the impact area.

[0067] (7) Impact on road network speed within the area T7

[0068] in, v n —the speed of the vehicle on the nth road, n —Number of roads.

[0069] (8) Parking convenience of roads within the affected area S1

[0070] in, L s —The length of roads within the impact area where parking is permitted, ws —Road width within the impact zone where parking is permitted, p —The population in the affected area.

[0071] (9) Safety of open streets S2 The safety level of the blocks after opening is divided into: strong, relatively strong, average, relatively weak, and weak, with values ​​of 0.9, 0.7, 0.5, 0.3, and 0.1 respectively.

[0072] (10) Convenience of entrances and exits to open streets S3

[0073] in, k —Total number of entrances and exits on open street streets (11) Noise impact on open streets S4 According to the noise environment impact effect, it is divided into: good, better, average, poor, and bad, and the values ​​are 0.9, 0.7, 0.5, 0.3, and 0.1 respectively.

[0074] (12) Integrity of open blocks as roads S5 After the blocks are opened and the original streets are used as roads, whether the original street facilities can meet the conditions for use as roads, including road conditions, traffic conditions, etc., is divided into: good, better, average, poor, and bad based on a complete urban road, and the values ​​are 0.9, 0.7, 0.5, 0.3, and 0.1 respectively.

[0075] Step 3: Construct an evaluation and analysis method model for urban open blocks, and the evaluation method process (e.g. Figure 4 The specific steps are as follows: determine the quantitative standard of the gray class level of indicators → calculate the eigenvalue of the whitening weight function → standardize the processing indicators of each indicator layer → construct the whitening weight function → assign weights to each indicator layer → calculate the gray clustering coefficient and clustering coefficient vector.

[0076] In order to better understand step three, the present invention is described below.

[0077] First, determine the quantitative standards for the gray-class grades of indicators. Indicators are divided into three levels: I, II, and III, with I being "not suitable for opening," II being "allowable for opening," and III being "suitable for opening." Each indicator layer can be divided into positive impact indicators and negative impact indicators. The higher the grade, the more favorable the block opening is for the positive impact indicators and the more unfavorable it is for the negative impact indicators. The quantitative standards for the gray-class grades of each indicator are as follows: (1) Road network density in the affected area T1 (Unit: km / km 2 ), is a positive impact indicator, where:T1 ≤1.26, grade III; when 1.26< T1 ≤1.54, grade II; when 1.54< T1 , level is Ⅰ.

[0078] (2) Street area ratio within the affected area T2 (Unit:%) is a positive impact indicator, where: 20% of the road area ratio is used as the standard value for the road to be suitable for block opening. T2 ≤20%, grade III; when 20%< T2 ≤25%, grade II; when 25%< T2 , level is Ⅰ.

[0079] (3) Intersection density in the impact area T3 (Unit: per 0.01km 2 ), is a negative impact indicator, where: T3 ≥3, grade III; when 2≤ T3 <3, grade is Ⅱ; when T3 <2, level is Ⅰ.

[0080] (4) Comprehensive non-linear coefficient of the road network in the affected area T4 , is a negative impact indicator, where: T4 ≥1.3, grade III; when 1.2≤ T4 <1.3, grade is Ⅱ; when T4 <1.2, grade is Ⅰ.

[0081] (5) Impact on road network connectivity within the area T5 , is a positive impact indicator, where: T5 ≤2.9, grade III; when 2..9< T5 ≤3.2, grade II; when 3.2< T5 , level is Ⅰ.

[0082] (6) Average distance between roads in the affected area T6 (Unit: m), is a positive impact indicator, where: T6 ≤200, grade is III; when 200< T6 ≤230, grade II; when 230< T6 , level is Ⅰ.

[0083] (7) Impact on road network speed within the area T7 (Unit: km / h), is a positive impact indicator, where: T7 ≤20, grade is III; when 20< T7 ≤35, grade II; when 35< T7 , level is Ⅰ.

[0084] (8) Parking convenience of roads within the affected area S1 , is a positive impact indicator, where: S1 ≤0.13, grade is III; when 0.13< S1 ≤0.18, grade II; when 0.18< S1 , level is Ⅰ.

[0085] (9) Safety of open streets S2 , is a negative impact indicator, where: S2 ≥0.7, grade III; when 0.3< S2 <0.7, grade is Ⅱ; when S2 ≤0.3, grade I.

[0086] (10) Convenience of entrances and exits to open streets S3 , is a positive impact indicator, where: S3 ≤2, level is III; when 2< S3 ≤4, grade II; when 4< S3 , level is Ⅰ.

[0087] (11) Noise impact on open streets S4 , is a negative impact indicator, where: S4 ≥0.7, grade III; when 0.3< S4 <0.7, grade is Ⅱ; when S4 ≤0.3, grade I.

[0088] (12) Integrity of open blocks as roads S5 , which are positive impact indicators, among which: S5 ≤0.3, grade is III; when 0.3< S5 ≤0.7, grade II; when 0.7< S5 , level is Ⅰ.

[0089] Secondly, calculate the eigenvalue of the whitening weight function; based on the gray level quantization standard of each indicator layer in step 3.1, calculate the corresponding eigenvalue of the whitening weight function l jk .index j ( j =1, 2, ..., 12) k (k=1, 2, 3) gray classes have different value ranges, so the eigenvalue l jk are also different, as shown below:

[0090] Secondly, each indicator layer x ij Standardized processing indicators Zij ; Positive impact indicators:

[0091] Negative impact indicators:

[0092] From this, construct the whitening weight function f j k ( x ); (1) The number of gray classes is in the interval (-∞, x j k ( u )], then the whitening weight function is

[0093] (2) The number of gray classes is in the range [ x j k (1), x j k ( u )], then the whitening weight function is

[0094] (3) The number of gray classes is in the range [ x j k ( u ), +∞), then the whitening weight function is

[0095] Then, each indicator layer is weighted; subjective weighting is given, and the AHP hierarchical analysis method is used to obtain the x j Corresponding subjective weight α j ; Objectively assign weights and use entropy analysis to obtain the index levels x j Corresponding subjective weight β j ; The comprehensive empowerment is as follows: .

[0096] Finally, calculate the grey clustering coefficient and clustering coefficient vector; based on the indicators in step 3.1, the blocks are divided into three levels according to whether they are open, which correspond to three grey clustering coefficients: y k (k=1,2,3), each coefficient is a whitening weight functionf j k ( x ) and comprehensive weight o j The weighted sum of , the clustering coefficient vector is y k= ( y 1, y 2, y 3) The calculation method is as follows: , ,

[0097] Step 4: Based on the clustering coefficient vector in step 3.6, the gray category of the block opening can be analyzed and determined, that is, not suitable for opening, can be opened, or suitable for opening. According to the cluster maximum principle, max ( y k )= y k * , then the indicator is judged to belong to the gray category k *, according to the corresponding grade, you can evaluate whether the block is suitable for opening.

[0098] In order to better understand step 4, the present invention is described below.

[0099] For example, the clustering coefficient vector of a city block y k= (0.62, 0.25, 0.13), the corresponding gray class membership is: Level III "suitable for opening" membership is 0.62, Level II "can be opened" membership is 0.25, Level I "not suitable for opening" membership is 0.13, then max ( y k )= y k * =0.62, corresponding to level III “suitable for opening”, based on which the block can be evaluated as suitable for opening.

[0100] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0101] It should be understood that those skilled in the art can make improvements or changes based on the above description, and all such improvements and changes should fall within the scope of protection of the appended claims of the present invention.

Claims

1. A method for evaluating and analyzing urban open blocks, characterized in that: The method comprises the following steps: Step 1: Set the preliminary open block impact area of ​​the city, obtain the traffic volume of each road in the preliminary open block impact area before and after the opening, calculate the saturation of each road before and after the opening, determine the affected roads based on the road saturation, and then determine the impact range of the open block impact area; Step 2: Construct an evaluation and analysis indicator system, which includes two characteristic layers: traffic characteristic layer and social impact characteristic layer, and further divide the characteristic layer into 12 indicator layers; Step 3: Establish an evaluation analysis method model, including: determining the quantitative standard of the gray class level of the indicator according to the indicator layer, calculating the characteristic value of the whitening weight function, and constructing the whitening weight function; assigning weights to each indicator layer, and calculating the gray clustering coefficient and clustering coefficient vector; Step 4: Based on the obtained clustering coefficient vector, determine the gray class to which the block belongs, and then output the result of evaluating whether the block is suitable for opening.

2. The evaluation and analysis method for urban open blocks according to claim 1, characterized in that: The method of step 1 comprises: Step 1.1: The area enclosed by the first main road immediately adjacent to the road where the open block is located is used as the preliminary open block impact area; Step 1.2: Within the initially determined open block impact area, obtain the traffic volume of each road during the peak hours before and after the block opening. The peak hour traffic volume is the average of the morning and evening peak traffic volumes for at least three consecutive days. Step 1.3: Calculate the saturation of each road before and after the block is opened; Step 1.4: Determine the affected roads based on the calculated saturation of each road before and after the block opening; Step 1.5: After determining the affected roads, the area enclosed by the outermost affected roads centered on the open block is the open block impact area. If there are roads that cannot be enclosed, the affected roads are extended outward to intersect with the adjacent main roads. The enclosed area formed is the open block impact area.

3. The evaluation and analysis method for urban open blocks according to claim 2, characterized in that: The method of step 1.3 includes: Will ρ 1. ρ 2 as the saturation index of each road before and after the block is opened: ρ 1 =v 1 / c ， ρ 2 =v 2 / c ， c = c 0· m · f 1· f 2· f 3 in, v 1 is the one-way peak hour traffic volume of the road before the block was opened; v 2 is the peak hour traffic volume of the road in one direction after the block is opened; c is the traffic capacity of the road section; c 0 is the possible traffic capacity; m is the number of one-way lanes; f 1 is the reduction factor of lane width and lateral clearance on traffic capacity; f 2 is the reduction factor of driver conditions on traffic capacity; f 3 is the traffic composition reduction factor; The method of step 1.4 includes: The area affected by the preliminary open block is n roads, and the saturation of each road is ρ n , ρ 1n Opening the front road for the neighborhood n saturation, ρ 2n Opening back roads for neighborhoods n saturation; if satisfied ρ 1n < first threshold, ρ 2n < the first threshold, and ρ 2n / ρ 1n > the second threshold, or when ρ 1n < first threshold, ρ 2n ≥ the first threshold, and ρ 2n / ρ 1n ≥1, or when ρ 1n ≥ the first threshold, ρ 2n ≥ the first threshold, and ρ 2n / ρ 1n When ≥1, it means the road n For the affected roads; if ρ 1n ≥ the first threshold, ρ 2n < the first threshold, and ρ 2n / ρ 1n When <1, it means that the road n Not an affected road.

4. The evaluation and analysis method for urban open blocks according to claim 1, characterized in that: The method of step 2 comprises: Step 2.1: Based on the characteristics of open blocks, construct an evaluation and analysis index system including two characteristic layers: traffic characteristic layer T and social impact feature layer S ; Step 2.2, Traffic feature layer T It includes 7 indicator layers, namely, road network density in the impact area T1 , the area ratio of street blocks in the affected area T2 , intersection density in the impact area T3 , Non-linear coefficient of road network in the impact area T4 , Impact area road network connectivity T5 , Average distance between roads in the affected area T6 , affecting the speed of road networks in the area T7 ; Step 2.3: Social Impact Feature Layer S It includes five social impact characteristic layers, namely the parking convenience of each road in the impact area S1 , safety of open streets S2 , open block road entrances and exits for convenience S3 , the noise environment impact of open blocks S4 , open blocks as road integrity S5 .

5. The evaluation and analysis method for urban open blocks according to claim 4, characterized in that: The indicator layer and social impact feature layer include: Road network density in the affected area T1 for: in, l n is the length of each road n in the affected area, s The area of ​​the development block impact zone; The block road area ratio T2 in the impact area is: in, r n is the area of ​​each road n in the affected area, s The area of ​​the development block impact zone; Intersection density in the affected area T3 for: in, c is the number of intersections in the impact area, s The area of ​​the development block impact zone; Comprehensive non-linear coefficient of road network in the affected area T4 for: ， in, t ij for i , j The nonlinear coefficient between points, N is the number of road network nodes in the affected area, l 1 is the actual length of the starting and ending points of the road network, l 2 is the spatial length of the starting and ending points of the road network; Impact area road network connectivity T5 for: in, J is the number of road network edges in the affected area, N is the number of road network nodes in the affected area; Average distance between roads in the affected area T6 for: in, d ij for i , j Node spacing, J is the number of road network edges in the impact area; Road network speed in the affected area T7 for: in, v n is the speed of the vehicle on the nth road, n is the number of roads; Parking convenience of roads in the affected area S1 for: in, L s is the length of the road within the impact area where parking is allowed, w s The width of the road where parking is allowed in the impact area. p is the population in the affected area; Safety in open streets S2 for: The safety level of the block after opening is divided into: strong, relatively strong, average, relatively weak, weak, and assigned values ​​in sequence; Convenience of entrances and exits of open block roads S3 for: in, k is the total number of entrances and exits on the open block road; Noise environmental impact of open blocks S4 for: According to the noise environment impact effect, it is divided into: good, better, average, poor, and bad, and assigned values ​​in sequence; Open Blocks as Road Integrity S5 for: After the blocks are opened and the original streets are used as roads, whether the original street facilities can meet the conditions for use as roads, including road conditions and traffic conditions, are divided into: good, better, average, poor, and bad, and assigned values ​​in order based on a complete urban road.

6. The evaluation and analysis method for urban open blocks according to claim 5, characterized in that: The method of step 3 includes: Step 3.1: Divide the indicators into three levels: I, II, and III, where I is "not suitable for opening", II is "allowable for opening", and III is "suitable for opening". Determine the quantitative standard for the gray level of the indicators based on the corresponding thresholds set for each indicator layer. Step 3.2: Based on the gray level quantization standard of each indicator layer in step 3.1, calculate the corresponding whitening weight function eigenvalue λ jk ;index j No. k The value ranges of the gray classes are different. j =1, 2, ..., 12; k = 1, 2, 3, then the eigenvalue λ jk Also different, the formula is: Step 3.3: Calculate each indicator layer x ij Standardized processing indicators Z ij ; Step 3.4: Construct whitening weight function f j k ( x ); Step 3.5: Assign weights to each indicator layer. The weighting methods include: Subjective weighting, using AHP hierarchical analysis method to obtain each indicator layer x j Corresponding subjective weight α j ; Objectively assign weights and use entropy analysis to obtain each indicator layer x j Corresponding subjective weight β j ; Comprehensive empowerment, the formula is: Step 3.6: Calculate the grey clustering coefficient and clustering coefficient vector.

7. The evaluation and analysis method for urban open blocks according to claim 6, characterized in that: The method of step 3.4 includes: The gray class number is in the interval (-∞, x j k ( u )], then the whitening weight function is: The gray class number is in the range [ x j k (1), x j k ( u )], then the whitening weight function is: The gray class number is in the range [ x j k ( u ), +∞), then the whitening weight function is: 。 8. The evaluation and analysis method for urban open blocks according to claim 7, characterized in that: The method of step 3.6 includes: Based on the indicators in step 3.1, the levels of the blocks are divided into three levels according to whether they are open, which correspond to three gray clustering coefficients: ψ k , where k=1,2,3, and each coefficient is a whitening weight function f j k ( x ) and comprehensive weight ω j The weighted sum of is calculated as follows: ， ， Then, the clustering coefficient vector is ψ k= ( ψ 1, ψ 2, ψ 3).

9. The evaluation and analysis method for urban open blocks according to claim 8, characterized in that: The method of step 4 includes: Based on the clustering coefficient vector in step 3.6, determine the gray category to which the block belongs, that is, unsuitable for opening, possible for opening, or suitable for opening; according to the clustering maximum principle, max ( ψ k )= ψ k * , then the indicator is judged to belong to the gray category k *, you can evaluate whether the block is suitable for opening.

10. An evaluation and analysis system for urban open blocks, characterized in that: include: a memory for storing executable computer programs; The processor is configured to implement the urban open block evaluation and analysis method according to any one of claims 1 to 9 when executing the executable computer program stored in the memory.

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