Evaluation index system construction and evaluation method for construction time sequence of urban composite channel

Abstract

The invention discloses an evaluation index system construction method for a construction time sequence of an urban composite channel, relates to the technical field of traffic engineering and urban planning, and solves the problems of facility layout conflict, traffic operation disturbance, low efficiency of resource allocation and the like caused by the lack of scientific time sequence overall planning of the construction time sequence of an existing urban rail-road composite channel. The construction method comprises the following steps: S11, dividing a city composite channel construction process into a plurality of evaluation stages of construction time sequence influence; s12, determining an evaluation dimension in each evaluation stage; s13, extracting an evaluation criterion based on each evaluation dimension; s14, refining a plurality of secondary evaluation indexes according to each evaluation criterion, and constructing an evaluation index system according to the secondary evaluation indexes; and S15, determining the meaning, the calculation method and the numerical value acquisition mode of each secondary evaluation index. The invention further discloses an evaluation method for the construction time sequence of the urban composite channel. According to the invention, the scientificity of traffic planning decision and the efficiency and benefit of engineering implementation can be improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of traffic engineering and urban planning, more particularly, it relates to the evaluation index system construction and evaluation method of urban composite channel construction time sequence. BACKGROUND

[0002] With the continuous growth of travel demand in central urban areas and the tightening of space resources, the traditional "staged, system" construction mode has been difficult to adapt to the current system complexity of high coupling of rail and road. In many important traffic corridors, rail and road show a composite form of close plane and complementary function, and new construction and expansion projects more and more use "rail + road" integrated design and construction methods. The channel with a close distance of more than 5KM or more than 3 stations between rail and road is called urban rail-road composite channel. The composite channel puts forward higher requirements for construction management, especially in construction time sequence arrangement. If there is a lack of scientific time sequence arrangement, it is easy to cause engineering conflicts, structural overlaps, traffic disturbances, resource waste and other problems, which seriously affect the construction period and system operation efficiency. Therefore, it is urgent to study the influence of composite channel under different construction time sequence on traffic system and social economy, and to provide an important basis for supporting efficient coordination and intelligent management of future urban multi-mode traffic system. SUMMARY

[0003] The technical problem to be solved by the present application is to provide an evaluation index system construction and evaluation method for urban composite channel construction time sequence to solve the problems of facility layout conflict, traffic operation disturbance and resource allocation inefficiency caused by the lack of scientific time sequence arrangement of existing urban rail-road composite channel construction time sequence.

[0004] The evaluation index system construction method for urban composite channel construction time sequence provided by the present application comprises: S11: dividing the urban composite channel construction process into multiple evaluation stages of construction time sequence influence; S12: determining the evaluation dimensions in each evaluation stage; S13: refining evaluation criteria based on each evaluation dimension; S14: refining multiple secondary evaluation indexes according to each evaluation criterion, and constructing an evaluation index system according to the evaluation stage, evaluation dimension, evaluation criterion and secondary evaluation index; S15: defining the meaning, calculation method and numerical value acquisition method of each secondary evaluation index.

[0005] Further improvement, in S11, the evaluation stage includes the construction stage and the post-construction stage, the method for dividing the urban complex corridor construction process into multiple construction time influence evaluation stages is to obtain the traffic system operation state and the social and economic feedback characteristics in the urban complex corridor construction process, and divide the urban complex corridor construction process into the construction stage and the post-construction stage according to the traffic system operation state and the social and economic feedback characteristics.

[0006] Further, in S12, the evaluation dimensions include the traffic function level, the engineering construction condition and the construction effect, and the method for determining the evaluation dimensions in each evaluation stage is to select the traffic function level and the engineering construction condition as the evaluation dimensions in the construction stage, and select the construction effect as the evaluation dimension in the post-construction stage.

[0007] The evaluation method of the urban complex corridor construction time sequence, the evaluation method includes: S21: based on the evaluation index system construction method of the urban complex corridor construction time sequence described above, a comprehensive evaluation index set is established; S22: based on the comprehensive evaluation index set, a state space is established and a state offset vector is obtained; S23: a fuzzy level mapping function is constructed according to the state offset vector and a fuzzy evaluation matrix is generated; S24: the fuzzy evaluation matrix is operated based on a level score vector to obtain an index score vector; S25: the CRITIC method is used and the index weight is determined based on the comprehensive evaluation index set; S26: the comprehensive evaluation score is calculated through the index score vector and the index weight, and the comprehensive evaluation score is taken as the evaluation result of the evaluation index system of the urban complex corridor construction.

[0008] Further improvement, in S21, the method for establishing the comprehensive evaluation index set is, the secondary evaluation index is used to establish an original index set, the original sample data matrix is constructed according to the original index set, the correlation coefficient between all index pairs in the original sample data matrix is calculated, and the expression of the correlation coefficient between all index pairs is, ; wherein, x i and y i denote the value of the i-th sample on the index i and X and Y , and and denote the indexX and Y sample mean, n denotes the sample number, ; based on the correlation coefficient, the secondary evaluation index is optimized to obtain a comprehensive evaluation index set.

[0009] Further, in S22, a method for establishing a state space based on the comprehensive evaluation index set and obtaining a state offset vector is, constructing specific index values of the comprehensive evaluation index set as a state space of a scheme to be evaluated and forming a state vector of different schemes , wherein, S i denotes the value of the first i index; an ideal state vector is constructed according to a historical optimal state or a theoretical optimal state ; obtaining a state offset vector of each scheme according to the state vector of each scheme and the ideal state vector , wherein denotes the offset between the first i index relative to the ideal value of the index; the offset is normalized to obtain a final state offset vector , wherein denotes the maximum acceptable offset of the first i index.

[0010] Further, in S23, a method for constructing a fuzzy level mapping function according to the state offset vector and generating a fuzzy evaluation matrix is, setting a fuzzy evaluation level set and a first boundary threshold for dividing the fuzzy evaluation level set θ 1, a second boundary threshold θ 2 and a third boundary threshold θ 3, constructing a superior level membership function according to the first boundary threshold θ 1 and the state offset vector , constructing a medium level membership function according to the second boundary threshold θ 2 and the state offset vector , and constructing a poor level membership function according to the third boundary threshold θ 3 and the state offset vector ; The expression for constructing the superior level membership function according to the first boundary threshold θ 1 is: ; wherein, is the superior level membership function; ; wherein, is a poor level membership function; ; wherein, is a poor level membership function; According to the excellent level membership function, the medium level membership function and the poor level membership function, the membership of each index in three evaluation levels is calculated respectively, and a fuzzy evaluation matrix is generated, and the expression for generating the fuzzy evaluation matrix is, ; wherein, U is the fuzzy evaluation matrix.

[0011] Further, in S24, the method for operating the fuzzy evaluation matrix based on the level score vector to obtain the index score vector is, According to the fuzzy evaluation level set define the score vector corresponding to different evaluation levels wherein, γ 1 is an excellent level score vector, γ 2 is a medium level score vector, γ3 is a poor level score vector; According to the score vector and the fuzzy evaluation matrix, the index score vector in the kth scheme is calculated, and the expression for obtaining the index score vector is, ; wherein, is the index score vector of the kth scheme.

[0012] Further, in S25, the method for determining the index weight by using the CRITIC method on the index score vector is, S31: obtaining the numerical value of the ith index in the kth scheme , the numerical value of the ith index is dimensionless, when the numerical value of the ith index is a positive index, the numerical value of the ith index is dimensionless, and the expression for dimensionless processing of the numerical value of the ith index is, ; wherein, is the index value after dimensionless processing, is the maximum value of the index in each scheme to be evaluated, is the minimum value of the index in each scheme to be evaluated; , the numerical value of the ith index When it is a negative indicator, the value of the i-th indicator The expression for dimensionless processing is: ; S32: Calculate the standard deviation of each index based on the dimensionless index values. The expression for calculating the standard deviation is as follows: ; in, Let be the standard deviation of the i-th index value. For all the schemes to be evaluated, the first The average value of each indicator, where m is the number of schemes; S33: Calculate the index conflict rate based on the correlation coefficients between all index pairs in S21. The expression for calculating the index conflict rate is as follows: ; in, For the index conflict of the j-th index value, Let be the correlation coefficient between the i-th and j-th indicator values, and n be the total number of indicators; S34: Calculate the information content of the j-th indicator based on the conflict and standard deviation of the indicators. The expression for calculating the information content of the j-th indicator is as follows: ; S35: Calculate the indicator weights based on the amount of information. The expression for calculating the indicator weights is as follows: ; in, The weights are the indicator weights.

[0013] Furthermore, in S26, the method for calculating the comprehensive evaluation score using the indicator score vector and indicator weights is as follows: The final comprehensive evaluation score of each scheme is calculated using the indicator score vector obtained in S24 and the indicator weights obtained in S25. The expression for the final comprehensive evaluation score of each scheme is as follows: ; in, The final comprehensive evaluation score for each plan is... m The number of solutions.

[0014] Beneficial effects The advantages of this invention are: The application sets up the evaluation index system construction method of the urban composite channel construction time sequence, the construction method combines the composite channel construction time sequence influence evaluation index system from the traffic system operation and the social economic influence perspective, the system divides two stages of the construction and the post-construction, and sets up nine evaluation criteria and a plurality of detailed indexes from three dimensions of the traffic function level, the engineering construction condition and the construction effect, to form the multi-dimensional and staged evaluation index system; the comprehensive evaluation method comprehensively evaluates and analyzes different construction time sequence schemes of the composite channel, optimizes the evaluation index set by using the maximum irrelevance principle, constructs the state space and the state offset vector, reflects the difference between each scheme and the ideal state, introduces the fuzzy grade mapping function, forms the fuzzy evaluation matrix, calculates the index score of each scheme based on the grade score vector, and objectively determines the index weight by combining the CRITIC method, and finally realizes the comprehensive score calculation and the good and bad order of different construction time sequence schemes, so that the construction time sequence scheme selection in the early stage of the urban rail and road composite channel construction is realized, and the application has the advantages of rigorous evaluation logic, quantitative and transparent calculation process, strong adaptability and the like, and helps to improve the scientificity of the traffic planning decision and the efficiency and benefit of the engineering implementation. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 The application is the evaluation index system construction method and the comprehensive evaluation method of the urban composite channel construction time sequence; Figure 2 The application is the evaluation index system construction method and the comprehensive evaluation method of the urban composite channel construction time sequence; Figure 3 The application is the evaluation index system construction method and the comprehensive evaluation method of the urban composite channel construction time sequence; Figure 4 The application is the evaluation index system construction method and the comprehensive evaluation method of the urban composite channel construction time sequence; Figure 5 The application is the evaluation index system construction method and the comprehensive evaluation method of the urban composite channel construction time sequence; Figure 6 The application is the evaluation index system construction method and the comprehensive evaluation method of the urban composite channel construction time sequence; Figure 7 The application is the evaluation index system construction method and the comprehensive evaluation method of the urban composite channel construction time sequence; Figure 8 The application is the evaluation index system construction method and the comprehensive evaluation method of the urban composite channel construction time sequence. DETAILED DESCRIPTION

[0016] The application is the evaluation index system construction method and the comprehensive evaluation method of the urban composite channel construction time sequence.

[0017] Reference Figures 1-8The present invention provides a method for constructing an evaluation index system for the construction sequence of urban composite passageways, comprising the following steps: S11: Evaluation stages for the impact of the construction sequence of the composite corridor; the stage division is based on the traffic system operation status and socio-economic feedback characteristics during the construction process of the urban rail-road composite corridor, dividing the impact assessment into the construction phase and the post-construction phase; the construction phase, from the start of corridor construction until the simultaneous completion and commissioning of the two types of facilities (rail and road), is the period of concentrated construction disturbance and the most significant impact on the operation of the surrounding traffic system; the post-construction phase refers to the period after both the rail and road have been completed and put into operation. During this phase, the network structure tends to stabilize and the traffic function is gradually released, which is a key window period for observing the differences in long-term traffic improvement and social benefits brought about by different construction sequences.

[0018] S12: Determine the evaluation dimensions for the impact of the construction sequence of the composite corridor; the evaluation dimensions are based on the phase division in S11. During the construction phase, traffic function level and engineering construction status are selected as the two major evaluation dimensions, and after construction, construction effect is selected as the main evaluation dimension. Among them, the traffic function level dimension directly reflects the impact of different construction sequences on operational effects such as travel efficiency, traffic order, and travel experience; the engineering construction status dimension focuses on the technical complexity of the project, the coordination of the time sequence, construction interference, and implementation costs; the construction effect dimension is used to measure the external impact and incremental value generated by the composite corridor at the socio-economic level, the level of transportation system coordination, and the level of public resource allocation after completion, with particular attention to the impact of the construction sequence of the composite corridor on travel structure and socio-economic development.

[0019] S13: Evaluation criteria for the impact of the construction sequence of composite transportation corridors; these criteria are based on the three core evaluation dimensions identified in S12, and are refined by combining the multiple impacts of the construction sequence of composite transportation corridors on the operational mechanism of the transportation system and urban spatial development. Specifically: For the transportation function level dimension, three types of evaluation criteria are set under this dimension: ground transportation service level (… A 1) Public transportation service level ( A 2) Macroeconomic indicators of travel ( A 3); For the dimension of project construction status, three evaluation criteria are set under this dimension, namely: time sequence ( A 4) Engineering difficulty ( A 5) Project cost ( A 6); Regarding the construction effectiveness dimension, three evaluation criteria are set under this dimension, namely: changes in travel demand ( A 7) Changes in travel structure ( A 8) Economic and social impacts ( A 9).

[0020] S14: Refine the evaluation index of the influence of composite channel construction timing; the evaluation index is further defined based on the evaluation criteria determined in S13.

[0021] Wherein, the ground traffic service level ( A 1) Subordinate to 8 secondary indicators, respectively: road saturation ( A 11 ), intersection saturation ( A 12 ), average speed during peak hours ( A 13 ), arterial speed fluctuation coefficient ( A 14 ), average delay at intersections ( A 15 ), intersection congestion rate during peak hours ( A 16 ), traffic index ( A 17 ), road congestion mileage ( A 18 ).

[0022] Public transport service level ( A 2) Subordinate to 5 secondary indicators, respectively: bus and subway passenger flow intensity ( A 21 ), bus and subway passenger flow intensity ( A 22 ), bus and subway peak passenger load rate ( A 23 ), bus and subway off-peak passenger load rate ( A 24 ) Average transfer coefficient ( A 25 ).

[0023] Travel macro indicators ( A 3) Subordinate to 4 secondary indicators, respectively: resident travel time delay index ( A 31 ), resident travel time ( A 32 ), commuting time proportion ( A 33 ), traffic accident rate ( A 34 ).

[0024] Timing duration ( A 4) Subordinate to 1 secondary indicator, namely the planned duration length ( A 41 ).

[0025] Engineering difficulty ( A5) subordinate 1 secondary index, namely construction technology difficulty coefficient A 51 ).

[0026] Project cost ( A 6) subordinate 3 secondary indexes, respectively: investment cost ( A 61 ), cost overrun rate ( A 62 ), cost benefit ratio ( A 63 ).

[0027] Travel demand change ( A 7) subordinate 2 secondary indexes, respectively: travel volume growth rate ( A 71 ), travel frequency change ( A 72 ).

[0028] Travel structure change ( A 8) subordinate 3 secondary indexes, respectively: public transportation / subway travel proportion ( A 81 , A 82 ), travel mode diversity index ( A 83 ).

[0029] Economic and social impact ( A 9) subordinate 4 secondary indexes, respectively: surrounding regional economic growth rate ( A 91 ), investment effect coefficient ( A 92 ), social satisfaction ( A 93 ), investment return rate ( A 94 ).

[0030] S15: the meaning or specific definition and calculation method of the evaluation index of the construction time sequence influence of the composite channel are determined; the present application takes the road section saturation as an example: the road section saturation ( A 11 ) is defined as the ratio of the traffic flow through the road section in unit time to the road traffic capacity, which is used to measure the running load degree of the road section under certain conditions in a certain period, and the calculation formula is , wherein: q is the measured traffic flow through the road section in unit period, c is the design traffic capacity of the road section.

[0031] The second object of the application is achieved by the following technical solution: a composite channel construction timing influence fuzzy comprehensive evaluation model based on state offset, i.e., an evaluation method for the urban composite channel construction timing of the application, which comprises the following steps: S21: constructing a comprehensive evaluation index set to improve the effectiveness and calculability of multi-index evaluation; the comprehensive evaluation index set is based on the initial evaluation index system established in the first object of the application, the average correlation degree of the index combination is extracted by using the principle of maximum irrelevance, the initial index system is filtered and optimized in combination with the availability of actual data and the importance or irreplaceability of each index in the evaluation dimension, and finally a simple and strong distinguishing power comprehensive evaluation index set is constructed.

[0032] Further, in S21, the comprehensive evaluation index set is constructed as follows: According to all the specific secondary indexes in the urban rail-road composite channel construction timing influence evaluation index system constructed in the first object of the application, an original index set is established , using the relevant data of historical composite channels, each historical scheme is a row (assuming there are m data samples, n specific evaluation indexes), each index value is a column, and an original sample data matrix of m x n is constructed.

[0033] The Pearson correlation coefficient between two indexes is calculated, for two indexes X and Y , the Pearson correlation coefficient r XY is calculated as follows: ; Wherein, x i and y i represent the values of the i th sample on the indexes X and Y , and represent the sample means of the indexes X and Y , n represents the sample number, , the larger the value, the stronger the positive correlation, the smaller the value, the stronger the negative correlation, and close to 0, which means approximately irrelevant.

[0034] Based on this method, the correlation coefficients between all indicator pairs are calculated. Taking the principle of maximizing non-correlation as the guiding principle, the indicators are optimized by combining multiple factors such as the importance of the indicators and the availability of indicator data among the highly correlated indicators, so as to obtain the final comprehensive evaluation indicator set with the least redundancy and the strongest information representativeness.

[0035] S22: Establish a state space and state offset vector to quantify the difference between the evaluation object and the ideal state; the state space is constructed based on the comprehensive evaluation index set constructed in S21, and the numerical performance of the scheme to be evaluated in each index dimension is combined and represented as a state vector. At the same time, an "ideal state" vector is set as the evaluation reference benchmark. The ideal state can be set by expert knowledge, historical best solution, industry standard or goal-oriented method; the state offset vector is obtained by calculating the difference between the state vector of each scheme and the ideal state vector in each index dimension.

[0036] Furthermore, in S22, the state space and state offset vector are established, as follows: Based on the comprehensive evaluation index set selected by S21, the specific index values ​​of these core indicators are used to construct the state space of the schemes to be evaluated, forming state vectors for different schemes. ,in S i Indicates the first i The values ​​of each indicator are determined; based on the historical best state or the theoretical best state, the ideal values ​​of each indicator are determined, and an ideal state vector is constructed. The difference between the state vector of each scheme and the ideal state is defined as the state offset; therefore, the state offset vector of each scheme can be calculated. ,in Indicates the first i The deviation of each indicator from its ideal value; to unify the units of measurement, the deviation is normalized. This yields the final state offset vector, where Indicates the first i The maximum acceptable offset for each indicator.

[0037] S23: Construct a fuzzy level mapping function and generate a fuzzy evaluation matrix to realize the system transformation of state deviation into level judgment; the fuzzy level mapping function is a mapping function that converts the deviation of each evaluation scheme from the ideal state in each indicator dimension into the membership degree of the fuzzy level. The appropriate membership degree function is selected for characterization according to the distribution characteristics of each indicator or evaluation requirements; the fuzzy level is a number of pre-set evaluation levels, commonly including "excellent", "good", "poor", etc., which represent the performance level of the scheme in the indicator dimension; the fuzzy evaluation matrix is ​​a matrix composed of the membership degree vectors of each scheme, which stores the membership degree information of all schemes to be evaluated for each indicator under each fuzzy level.

[0038] Furthermore, in S23, a fuzzy level mapping function is constructed and a fuzzy evaluation matrix is ​​generated, as follows: First, define the fuzzy evaluation level set. Set the first boundary threshold for classifying the excellent, average, and poor fuzzy levels. θ 1. Second boundary threshold θ 2 and the third boundary threshold θ 3. This invention uses a family of triangular membership functions to construct a fuzzy hierarchy mapping function. The fuzzy membership functions for different levels are defined as follows: Membership function of superiority level: ; in, This is the membership function for the superiority level.

[0039] Medium-level membership function: ; in, This is a membership function of intermediate level.

[0040] ; in, This is the difference in membership degree function.

[0041] Based on the family of membership functions, for any index i The offset relative to the ideal state calculated in S22 The index can be calculated. i Membership degree of the three fuzzy evaluation levels The membership degree represents the degree of fuzziness in which the offset belongs to the corresponding evaluation level. The larger the membership degree value, the more the offset belongs to the corresponding level, thus enabling the mapping of state deviation to evaluation level.

[0042] According to the fuzzy grade mapping function, the membership of each index in three evaluation grades is calculated respectively to form a fuzzy evaluation matrix U, wherein each row represents each index and each column represents the membership of each fuzzy evaluation grade: ; wherein U is the fuzzy evaluation matrix.

[0043] S24: Calculate the index score vector of each scheme based on the grade score vector; the grade score vector is a vector that quantifies the advantages and disadvantages of the fuzzy grades in S23, and the higher the grade, the higher the score. The comprehensive fuzzy score is obtained by multiplying the fuzzy evaluation matrix constructed by S23 and the grade score vector.

[0044] Further, in S24, the index score vector of each scheme is calculated based on the grade score vector, as follows: First, according to the grade classification of , the score vector corresponding to different grades is defined , wherein the higher the grade, the higher the score; for the kth scheme, the score vector of each index in the kth scheme is calculated according to the following formula : .

[0045] S25: Establish an index weight determination method based on the CRITIC method to objectively reflect the distinguishing ability and information redundancy of each evaluation index in the current comprehensive evaluation system, and further reflect the actual influence of each index on the comprehensive evaluation result; the CRITIC method is a method for evaluating the amount of information provided by each index to the comprehensive evaluation system by calculating the standard deviation of each index and the correlation coefficient between the indexes, and the index with higher information amount obtains larger weight, thereby realizing objective weight allocation based on data driving; the comprehensive evaluation result is the weighted sum result of the index score vector and the index weight obtained in S24.

[0046] Further, in S25, the index weight determination method based on the CRITIC method is established, the index standard deviation and information amount of each normalized index are calculated to quantify the distinguishing ability and effective information carrying capacity of the index, and then the weight of each index in the comprehensive evaluation model is determined, as follows: First, the data of each index is dimensionless; for the value of the ith index in the kth scheme , if the index is a positive index, i.e. the larger the index value, the better, then the dimensionless processing is carried out by the following formula; ; if the index is a negative index, i.e. the smaller the index value, the better, then the dimensionless processing is carried out by the following formula; ; wherein, is the dimensionless value of the i-th index in the k-th scheme, is the maximum value of the index in all the schemes to be evaluated, is the minimum value of the index in all the schemes to be evaluated.

[0047] Then the standard deviation of each index is calculated by the following formula: ; wherein, is the standard deviation of the i-th index value, is the average value of the i-th index value in all the schemes to be evaluated, and m is the number of schemes; after obtaining the correlation coefficient between each two indexes according to the correlation coefficient calculation method in S21, the index conflict is calculated: ; wherein, is the index conflict of the j-th index value, is the correlation coefficient between the i-th index value and the j-th index value, and n is the total number of indexes. The conflict of an index is reflected by the correlation. The stronger the correlation with other indexes, the smaller the conflict of the index with other indexes, the more information reflected, the more repetition of the evaluation content, and the weaker the evaluation strength of the index to some extent, which can reduce the weight allocated to the index. Then the information amount of the index is calculated by the following formula:

[0048] j : C ; wherein, C j is the information amount of the j-th index; Finally, the weight of each index is calculated according to the information amount, as follows: ; wherein, is the index weight.

[0049] The weight vector of all indexes of the k-th scheme is obtained by this method , m is the number of schemes.

[0050] S26: calculating the final comprehensive evaluation score of each scheme to realize the final ranking and the judgment of advantages and disadvantages; the comprehensive evaluation score is obtained by weighted summation of the index score vector obtained in S24 and the weight of each index determined in S25.

[0051] ​Furthermore, in S26, the final comprehensive evaluation score of each scheme is calculated, defined as the score vector of each indicator obtained in S24. and the weight vectors of each indicator obtained in S25 The vector dot product, i.e., the weighted sum of the two, is calculated using the following formula: ; in, The final comprehensive evaluation score for each plan is... m The number of solutions.

[0052] By comparing the final evaluation scores of different solutions, the merits of each solution can be determined.

[0053] To better understand the above technical solution, the present invention will be described in detail below with specific implementation examples.

[0054] Based on previously collected data including road traffic flow, subway and bus passenger flow, and resident travel surveys, and combined with resident travel demand forecasting, traffic flow forecasting, and traffic simulation methods, a comprehensive evaluation and analysis of the construction timeline schemes for urban rail-road composite corridors was conducted. The schemes are divided as follows: (1) Rail first, road later: Road construction is carried out after the rail has been built; (2) Road first, rail later: Rail construction is carried out after the road has been built; (3) Road and rail are constructed at the same time: The composite channel is planned as a whole and constructed at the same time.

[0055] By analyzing the maximum correlation between the indicators in the multi-indicator evaluation system constructed in the first objective of this invention, and considering the availability of indicator data, the road segment saturation ( A 11 ), intersection saturation ( A 12 Traffic Index A 17 ), public transport passenger flow intensity ( A 21 ), subway passenger flow intensity ( A 22 ), average transfer coefficient ( A 25 ), Residents' travel time delay index ( A 31 ), planned construction period length ( A 41 ), technical difficulty coefficient ( A 51 ), investment costs A 61 ), travel volume growth rate (A 71 ), the proportion of bus travel ( A 81 ), the proportion of subway travel ( A 82 ), the economic growth rate of the surrounding area ( A 91 ), social satisfaction ( A 93 ), the return on investment ( A 94 ) 16 indicators to build a comprehensive evaluation index set, and the specific index value of these core indicators is constructed as the state space of the scheme to be evaluated, forming the state vector of different schemes. According to the historical optimal state or the theoretical optimal state, the ideal value of each index is determined, and the ideal state vector is constructed. The state space corresponding to each scheme is shown in the following Figure 4 The offset vector between each scheme and the ideal is calculated, and the result is shown in the following Figure 5

[0056] The boundary threshold parameters for dividing the excellent, medium and poor fuzzy levels are defined θ 1, θ 2, θ 3 are 0.3, 0.5, 0.7 respectively, and the level scores are 80, 50, 20 respectively. The membership degree of each index in the three evaluation levels and the final index score are calculated, and the result is shown in the following Figure 6

[0057] According to S25, the standardized index value, index standard deviation, index conflict, information amount and final index weight of each index in the three schemes are calculated, and the result is shown in the following Figure 7

[0058] Finally, the final comprehensive evaluation score of each scheme is calculated, which is defined as the vector inner product of the index score vector G （k） calculated in S24 and the index weight vector W （k） calculated in S25. The final scheme score result is shown in the following Figure 8

[0059] The results show that in this example, the corresponding index value of each scheme, the track-first road-later scheme is optimal, the simultaneous construction scheme is second, and the road-first track-later scheme is the worst. The comprehensive evaluation method established by the present application can accurately reflect the specific influence of construction time sequence difference on the system, and has good rationality, discriminability and practical applicability, which can provide strong support for scientific decision-making of urban composite channels.

[0060] ​​​​The above merely describes the preferred embodiments of the present application, and it should be pointed out that for those skilled in the art, several modifications and improvements can be made without departing from the structure of the present application, and these will not affect the effect of the present application and the practicality of the patent.

Claims

1. A method for constructing an evaluation index system for the construction sequence of urban composite corridors, characterized in that, The construction method includes: S11: Divide the construction process of urban composite corridors into multiple evaluation stages of the impact of construction sequence; S12: Determine the evaluation dimensions for each of the evaluation stages; S13: Extract evaluation criteria based on each of the evaluation dimensions; S14: Based on each of the evaluation criteria, multiple secondary evaluation indicators are refined, and an evaluation indicator system is constructed based on the evaluation stage, evaluation dimension, evaluation criteria, and secondary evaluation indicators. S15: Clarify the meaning, calculation method, and numerical acquisition method of each of the secondary evaluation indicators.

2. The method for constructing an evaluation index system for the construction sequence of urban composite corridors according to claim 1, characterized in that, In S11, the evaluation phase includes the construction phase and the post-construction phase.

3. The method for constructing an evaluation index system for the construction sequence of urban composite corridors according to claim 2, characterized in that, In S12, the evaluation dimensions include traffic function level, engineering construction status, and construction effect. During the construction phase, traffic function level and engineering construction status are selected as evaluation dimensions, and during the post-construction phase, construction effect is selected as evaluation dimensions.

4. An evaluation method for the construction sequence of urban composite corridors, characterized in that, The evaluation method includes: S21: To establish a comprehensive evaluation index set based on the evaluation index system construction method for the construction sequence of urban composite passages as described in any one of claims 1-3; S22: Establish the state space and obtain the state offset vector based on the comprehensive evaluation index set; S23: Construct a fuzzy level mapping function and generate a fuzzy evaluation matrix based on the state offset vector; S24: Perform calculations on the fuzzy evaluation matrix based on the grade scoring vector to obtain the indicator score vector; S25: Use the CRITIC method and determine the index weights based on the comprehensive evaluation index set; S26: Calculate the comprehensive evaluation score using the indicator score vector and indicator weights, and use the comprehensive evaluation score as the evaluation result of the evaluation indicator system for the construction of urban composite channels.

5. The evaluation method for the construction sequence of urban composite corridors according to claim 4, characterized in that, In S21, the method for establishing the comprehensive evaluation index set is as follows: An initial indicator set is established based on the secondary evaluation indicators. An initial sample data matrix is ​​constructed based on the initial indicator set. The correlation coefficient between all indicator pairs in the initial sample data matrix is ​​calculated. The expression for calculating the correlation coefficient between all indicator pairs is as follows: ； in, x i and y i Indicates the first i Each sample in the indicator X and Y The value on, and Indicators X and Y The sample mean, n Indicates the number of samples. Based on the correlation coefficient, the secondary evaluation indicators are optimized to obtain a comprehensive evaluation indicator set.

6. The evaluation method for the construction sequence of urban composite corridors according to claim 5, characterized in that, In S22, the method for establishing the state space and obtaining the state offset vector based on the comprehensive evaluation index set is as follows: The specific index values ​​of the comprehensive evaluation index set are used to construct the state space of the scheme to be evaluated, and state vectors of different schemes are formed. ,in, S i Indicates the first i The values ​​of each indicator; constructing an ideal state vector based on the historical best state or the theoretical best state. ; The state offset vector of each scheme is obtained based on the state vector and the ideal state vector of each scheme. ,in Indicates the first i The offset of an indicator relative to its ideal value; for the offset The final state offset vector is obtained by normalization. ,in Indicates the first i The maximum acceptable offset for each indicator.

7. The evaluation method for the construction sequence of urban composite corridors according to claim 6, characterized in that, In S23, the method for constructing the fuzzy level mapping function and generating the fuzzy evaluation matrix based on the state offset vector is as follows: Set a fuzzy evaluation level set and a first boundary threshold for dividing the set of fuzzy evaluation levels. θ 1. Second boundary threshold θ 2 and the third boundary threshold θ 3. Based on the first boundary threshold θ 1 and state offset vector Construct the membership function of the superior level, based on the second boundary threshold. θ 2 and state offset vector Construct the membership function of the intermediate level, based on the third boundary threshold. θ 3 and state offset vector Construct the difference-level membership function; According to the first boundary threshold θ The expression for constructing the membership function of the superiority level is: ; in, For the membership function of the superior level; ； in, For intermediate-level membership functions; ； in, The difference in membership degree function; A fuzzy level mapping function is constructed based on the superior level membership function, the intermediate level membership function, and the inferior level membership function. The expression of the fuzzy level mapping function is as follows: ,in U i For fuzzy level mapping function; Based on the membership functions for the excellent, medium, and poor grades, the membership degree of each indicator at the three evaluation grades is calculated, and a fuzzy evaluation matrix is ​​generated. The expression for generating the fuzzy evaluation matrix is ​​as follows: ； Where U is the fuzzy evaluation matrix.

8. The evaluation method for the construction sequence of urban composite corridors according to claim 7, characterized in that, In S24, the method for obtaining the index score vector by operating on the fuzzy evaluation matrix based on the level rating vector is as follows: According to the fuzzy evaluation level set Define the rating vectors corresponding to different evaluation levels. ,in, γ 1 represents the excellent rating vector. γ 2 represents the intermediate-level rating vector. γ3 This is a poor rating vector; Based on the scoring vector and the fuzzy evaluation matrix, the index score vector of the k-th scheme is calculated, and the expression for the index score vector is obtained as follows: ； in, Let be the index score vector for the k-th scheme.

9. The evaluation method for the construction sequence of urban composite corridors according to claim 8, characterized in that, In S25, the method for determining the index weights using the CRITIC method to the index score vector is as follows: S31: Obtain the value of the i-th index in the k-th scheme. The value of the i-th index Perform dimensionless processing, when the value of the i-th index... When it is a positive indicator, the value of the i-th indicator The expression for dimensionless processing is: ； in, The index value is after dimensionless processing. This represents the maximum value of the indicator among all the options to be evaluated. This is the minimum value of the indicator among all the schemes to be evaluated; When the value of the i-th indicator When it is a negative indicator, the value of the i-th indicator The expression for dimensionless processing is: ； S32: Calculate the standard deviation of each index based on the dimensionless index values. The expression for calculating the standard deviation is as follows: ； in, Let be the standard deviation of the i-th index value. For all the schemes to be evaluated, the first i The average value of each indicator, where m is the number of schemes; S33: Calculate the index conflict rate based on the correlation coefficients between all index pairs in S21. The expression for calculating the index conflict rate is as follows: ； in, For the index conflict of the j-th index value, Let be the correlation coefficient between the i-th and j-th indicator values, and n be the total number of indicators; S34: Calculate the information content of the j-th indicator based on the conflict and standard deviation of the indicators. The expression for calculating the information content of the j-th indicator is as follows: ;in, C j The information content of the j-th indicator is shown in the figure. S35: Calculate the indicator weights based on the amount of information. The expression for calculating the indicator weights is as follows: ； in, The weights are the indicator weights.

10. The evaluation method for the construction sequence of urban composite corridors according to claim 9, characterized in that, In S26, the method for calculating the comprehensive evaluation score using the indicator score vector and indicator weights is as follows: The final comprehensive evaluation score of each scheme is calculated using the indicator score vector obtained in S24 and the indicator weights obtained in S25. The expression for the final comprehensive evaluation score of each scheme is as follows: ； in, This is the final comprehensive evaluation score for each plan.

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