Urban subway freight transport system development suitability evaluation method

Abstract

The invention belongs to the field of underground space development and application and traffic transportation planning, and particularly relates to an urban subway freight transport system development suitability evaluation method. Comprising the following steps: step (1), establishing an urban subway freight system development suitability analysis framework; (2) evaluation indexes and quantitative calculation of the development suitability of the urban subway freight system; (3) collecting multi-source data; and (4) determining an index processing process and an evaluation criterion. The invention provides a qualitative and quantitative combined method for evaluating the suitability of a comprehensive logistics solution based on urban subway freight, the evaluation content is comprehensive, the operability is high, and reliable decision support is provided for sustainable transition of urban freight transportation from a road dominant mode to railway collaborative transportation.

Description

Technical Field

[0001] The invention belongs to the field of underground space development and application and transportation planning, and specifically relates to a method for evaluating the suitability of urban subway freight system development. Background Art

[0002] Using subways to implement underground logistics, that is, the subway-underground logistics co-construction system (Metro-based ULS) is currently a major and preferred form. Conceptually, it requires certain changes to the subway operation mode and facilities along the line, and uses the surplus transportation capacity and high accessibility of the track to transport standardized cargo units to stations along the way by running specially designed new trains. Compared with the independent construction of tunnels, the cost and difficulty of carrying out underground logistics based on subways are lower, and it can quickly form a network and exert benefits. With subways as the carrier, through layered network layout and transportation mode integration, multiple systems can achieve business collaboration and provide "door-to-door" urban distribution services. It is currently technically feasible to integrate underground logistics through subway reconstruction or new construction. Urban rail transit is mainly based on subways, and the rich network facilities are expected to be fully utilized. By reasonably setting up passenger and freight transportation organizations, the comprehensive service capacity of the subway network can be improved. Once a network is formed, subway freight also has good compatibility and scalability, and has great potential in promoting a fundamental change in the urban transportation and logistics model.

[0003] Compared with road freight, the subway freight system has obvious advantages. On the one hand, the system utilizes underground rail transit infrastructure, has high-speed and stable transportation capabilities, is not affected by external factors, and provides faster delivery services. On the other hand, the networked subway freight system can reduce the negative externalities brought to the city by ground freight. As a low-carbon and environmentally friendly logistics method, its transportation process will not cause urban traffic congestion and environmental pollution, and will help improve the urban environment. In addition, the development of intelligent technology can realize real-time tracking and management of goods, which is conducive to the transformation and upgrading of the logistics industry.

[0004] Therefore, the current situation is that the subway-underground logistics intermodal system is a new model for utilizing urban underground space to promote the development of urban logistics planning. Developing a subway-based underground logistics system is an important means to implement and improve urban intelligent low-carbon logistics infrastructure and build a new type of comprehensive transportation system. Summary of the invention

[0005] The purpose of the present invention is to provide a method for evaluating the suitability of urban subway freight system development.

[0006] The technical solution to achieve the purpose of the present invention is: a method for evaluating the suitability of urban subway freight system development, comprising the following steps:

[0007] Step (1): Establish a framework for analyzing the suitability of urban subway freight system development;

[0008] Step (2): Development of suitability evaluation indicators and quantitative calculation of urban subway freight system;

[0009] Step (3): Multi-source data collection;

[0010] Step (4): Establishment of indicator processing and evaluation criteria.

[0011] Furthermore, step (1) includes the following steps:

[0012] Step (11): Based on the SWOT method, a suitability analysis framework for the development of the urban subway freight system is constructed, the main strengths, weaknesses, opportunities and challenges of the implementation of the urban subway freight system project are identified, and a SWOT matrix is ​​formulated;

[0013] Step (12): Using the questionnaire survey method, the importance scores of the above indicators are obtained based on the experts' evaluation of the SWOT analysis indicators, and new evaluation indicators are proposed;

[0014] Step (13): Determine the selection of indicators for the evaluation of the suitability of urban subway freight system development based on the SWOT analysis framework.

[0015] Furthermore, the evaluation indicators for the suitability of urban subway freight system development in step (2) include two types: benefit-based indicators and cost-based indicators;

[0016] The specific benefit indicators include network capacity C1, infrastructure C2, demand scale C3, consumption and market C4, environmental benefits C5, urban economy C6, and 10 、The urgency of truck restrictions 11 , combined with the calculation formula of each indicator, the calculated value of each evaluation indicator is obtained based on the data obtained by multi-source data collection;

[0017] The cost-based indicators specifically include: proximity to urban logistics hubs C6, proximity to customers C7, transportation-oriented development C8, and implementation costs C9. The calculated values ​​of each evaluation indicator are obtained by combining the calculation formulas of each indicator and based on the data obtained through multi-source data collection.

[0018] Furthermore, the quantitative calculation method of the benefit-based evaluation index is as follows:

[0019] Calculate the network capacity C1, which is used to reflect the freight capacity of the urban rail transit network. The calculation formula is as follows:

[0020]

[0021] where λ 11 ∈(0, 1),λ 12 ∈(0 , 1),λ 11 +λ 12 =1

[0022] Among them, C1 is the network capacity indicator; SA Fmodule is the total area of ​​passenger and freight shared stations in the urban rail transit network; Ucap FPS is the capacity per unit area of ​​installed modules; is the number of passenger trains associated with each relevant route i; is the maximum possible number of freight train services; Ucap EC is the cargo capacity of the additional compartment; Ucap DT is the vehicle load of a dedicated freight train; 11 and λ 12 are the weights corresponding to the two items respectively.

[0023] The basic data for calculating the maximum possible number of freight train services comes from the timetable information of each subway line obtained from the website of the subway operator of each city. The calculation formula is as follows:

[0024]

[0025] in, is the end time of passenger service; is the time when the last dedicated freight train service starts; MT i is the time before the start of the last dedicated freight train service on the next day; the constant δ is the departure frequency of dedicated freight trains; the operation of dedicated freight trains is subject to HT([Δt]). It is assumed that at most one dedicated freight train service can be added between two adjacent passenger services; HT i (j, j+1) represents the interval between passenger trains j and j+1; i∈Ω represents the set of lines in the urban rail transit network, and j∈M represents the set of passenger train services;

[0026] Infrastructure C2, this indicator is used to reflect the richness of dedicated railway facilities. The calculation formula is as follows:

[0027] C2=N station ×N transfer ×URTL

[0028] Among them, C2 is the infrastructure indicator; N station is the number of urban rail transit stations; N transfer is the number of urban rail transit transfer stations; URTL is the length of the urban rail transit network;

[0029] Demand scale C3, this indicator is used to reflect the demand scale of urban freight, and the calculation formula is as follows:

[0030] C3=N EP ×N SMRS

[0031] Among them, C3 is the demand scale indicator, N EP is the number of e-commerce packages delivered in the city each year, N SMRS is the total number of shopping malls and retail stores in the city;

[0032] Consumption and Market C4, this indicator is used to reflect the market size and operating conditions of the urban logistics industry. The calculation formula is as follows:

[0033] C4=λ 41 ×LBI+λ 42 ×RSG,λ 41 ∈(0,1),λ 42 ∈(0,1),λ 41 +λ 42 =1

[0034] Among them, C4 is the consumption and market index, LBI is the annual operating income of the urban logistics market, reflecting the market size and operating conditions of the urban logistics industry; RSG is the annual retail sales of social commodities, reflecting the purchasing power of citizens and the prosperity of the urban economy. 41 is the relative weight value of LBI, λ 42 is the relative weight value of RSG;

[0035] Environmental benefit C5, this indicator is used to reflect the environmental benefit of the subway freight system. The calculation formula is as follows:

[0036]

[0037] Among them, C5 is the environmental benefit index of the subway freight system; is the number of passenger trains associated with each relevant route i; is the maximum possible number of freight train services; Ucap EC is the cargo capacity of the additional compartment; Ucap DT It is the car load of a dedicated freight train; is the average daily driving distance of a single truck; REV is the utilization rate of electric vehicles in urban logistics activities; Ucap truck is the average daily cargo volume transported by each truck; α CO is the cost of treating carbon monoxide (CO) produced per kilometer of truck travel; is the cost of handling carbon dioxide (CO2) produced per kilometer of truck travel; is the nitrogen oxides (NOX ) processing cost; α PM is the cost of treating particulate matter (PM) generated per kilometer of truck travel; α noise is the cost of handling the noise generated per kilometer of truck travel;

[0038] Urban Economy C 10 , this indicator is used to reflect the economic basis required for the implementation of the subway freight system. The calculation formula is as follows:

[0039] C 10 =GDP / POP×(λ 101 ×FGBR+λ 102 ×TIFA),λ 101 ∈(0,1),λ 102 ∈(0,1),λ 101 +λ 102 =1

[0040] Among them, C 10 is the city's economic indicator; GDP is gross domestic product; POP is population; FGBR is fiscal general budget revenue; TIFA is total fixed asset investment. 101 is the relative weight value of the general budget revenue; 102 is the relative weight value of the total fixed asset investment;

[0041] The urgency of truck restrictions 11 , this indicator is used to reflect the contribution of the subway freight system to urban freight mobility. The calculation formula is as follows:

[0042] C 11 =BanT×BanA×N truck

[0043] Among them, C 11 is the urgency indicator of the truck restriction, BanT is the daily truck ban period; BanA is the area of ​​the truck ban zone; N truck is the number of trucks affected.

[0044] Furthermore, the quantitative calculation method of cost-based evaluation indicators is as follows:

[0045] The upstream logistics hub proximity C6 is used to reflect the spatial proximity between the upstream logistics hub and the subway freight network. The calculation formula is as follows:

[0046]

[0047] Among them, C6 is the proximity index of urban logistics hubs, ‖S‖ is the number of ULHs, |z s -z k| is the Euclidean distance between the upstream logistics hub and the urban rail transit station; upstream logistics hub s∈S; urban rail transit station k∈K; K is the set of all stations. Rules: If the first nearest station belongs to Line i, then K′ is defined as the set of stations excluding all stations on Line i; if the second nearest station belongs to Line j, then K″ is defined as the set of stations excluding all stations on Line i and Line j;

[0048] Proximity to customers C7, this indicator is used to reflect the proximity between the urban rail transit network and the final destination of urban delivery. The calculation formula is as follows:

[0049]

[0050] Where C7 is the proximity index of the urban rail transit network to customers; UR(ε) is the total area of ​​urban areas with a population density exceeding ε; F(ε) is the number of urban rail transit stations in the UR(ε) area; |z q -z k | is the Euclidean distance between a registered postal service site q and its nearest station;

[0051] Transportation-oriented development C8, this indicator is used to reflect the standard for evaluating the suitability of the subway freight system. The calculation formula is as follows:

[0052]

[0053] Among them, C8 is a public transportation-oriented development index, and TOD is a city's public transportation-oriented development index. is the conversion factor;

[0054] Implementation cost C9, this indicator is used to reflect the economic feasibility of the subway freight system, and the calculation formula is as follows:

[0055]

[0056] Among them, C9 is the implementation cost indicator, ConsC is the construction cost per kilometer of the urban rail transit line that has been in operation recently; OperC is the annual operating cost of urban rail transit; URTL is the length of the urban rail transit network; λ 91 is the relative weight value of the construction cost per kilometer of the recently operated urban rail transit line; 92 It is the relative weight value of the annual operating cost of urban rail transit averaged by network length.

[0057] Furthermore, step (3) specifically includes the following steps:

[0058] Step (31): Obtaining relevant data of the urban subway freight system;

[0059] Data related to urban subway freight systems include railway length, number of lines, trains and services, average daily passenger flow, number of urban rail transit stations, and station ; The number of urban rail transit transfer stations N transfer , urban rail transit annual operating cost OperC, total number of trains, daily services, TOD index data;

[0060] Step (32): Obtaining data related to urban transportation and logistics;

[0061] Data related to urban transportation and logistics include the number of e-commerce packages delivered in the city each year N EP 、Number of trucks affected truck , Number of registered postal service sites N RPS , the total number of shopping malls and retail stores in the city N SMRS , the daily truck travel ban period BanT, the area of ​​the truck ban zone BanA, and the average daily driving distance of a single truck Annual operating income of urban logistics market LBI;

[0062] Calculate the demand scale C3 indicator and the urgency of truck restrictions C based on the acquired data 11 Indicator, environmental benefit C5, upstream logistics hub proximity C6, proximity to customers C7, urban economy C 10 And the attribute values ​​of consumption and market C4 indicators.

[0063] Furthermore, step (4) specifically includes the following steps:

[0064] Step (41): Calculate the weight of each evaluation index using hierarchical analysis;

[0065] Step (411): construct a pairwise comparison matrix using the 1-9 scaling method;

[0066] Step (412): solving the pairwise comparison matrix;

[0067] Step (413): consistency check;

[0068] Step (42): using the VIKOR method to comprehensively evaluate and determine the suitability level of urban subway freight system development;

[0069] Step (421): construct a decision matrix and perform index value normalization processing;

[0070] Step (422): Determine a positive ideal solution and a negative ideal solution;

[0071] Step (423): Calculate the group benefit index S i and individual regret indicators Y i ;

[0072] Step (424): Decision Index R i calculate;

[0073] Step (43): Comprehensive evaluation criteria for the suitability of urban subway freight system development:

[0074] Based on the comprehensive score of indicators and decision index R of the development suitability of urban subway freight system through AHP-VIKOR i , evaluate the suitability of urban subway freight system development, comprehensive score of indicators and decision index R i The order of size is the order of suitability of the alternative options.

[0075] Compared with the prior art, the present invention has the following significant advantages:

[0076] The present invention can provide a quantitative calculation method for the suitability evaluation of urban subway freight system development, which is applicable to the suitability evaluation of subway freight system development in all cities; the data collection method is accurate and convenient; the selection of evaluation indicators fully considers economic factors and development factors; the standardized basis of evaluation indicators and indicator weights are generally applicable, which improves the efficiency and reliability of the suitability evaluation of urban subway freight system development. The present invention can provide data support and decision-making reference for the deep integration of passenger and freight transportation in the urban context and the potential merger of subway freight system and logistics industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] Figure 1 Develop a suitability assessment flow chart for an urban metro freight system;

[0078] Figure 2 This is the SWOT model analysis diagram of the urban subway freight system;

[0079] Figure 3 Develop a suitability evaluation index measurement map for urban subway freight systems;

[0080] Figure 4 The subway network layouts of the 16 cities tested;

[0081] Figure 5 Develop a suitability index evaluation score map for an urban metro freight system. DETAILED DESCRIPTION

[0082] The present invention is further described in detail below in conjunction with the accompanying drawings.

[0083] A method for evaluating the suitability of urban subway freight system development includes the following steps:

[0084] Step 1: Establish a framework for analyzing the suitability of urban subway freight system development;

[0085] Step 2: Develop the evaluation index and quantitative calculation method of suitability of urban subway freight system;

[0086] Step 3: Multi-source data collection method;

[0087] Step 4: Establishment of indicator processing and evaluation criteria;

[0088] Step 5. Application example of the suitability assessment method for subway freight system development.

[0089] Furthermore, in the step 1, according to the SWOT analysis method, the main driving factors and obstacles for the implementation of the subway freight system project are identified, a suitability analysis framework for the development of the urban subway freight system is constructed, and indicators reflecting the SWOT performance of the subway freight system project are determined;

[0090] 1.1 Based on the SWOT method, the urban subway freight system development suitability analysis framework is formulated as follows: Figure 2 As shown;

[0091] Step 1.1.1: Analyze the impact of large freight demand, government leadership and top-down development strategy, engineering and infrastructure capabilities, social-environmental benefits, efficiency advantages, supply chain integration and profitability, system organization and expansion flexibility on the development of urban subway freight systems from the perspectives of urban economy and urban development, and then analyze the opportunities for the development of urban subway freight systems;

[0092] Step 1.1.2: Interpret the complexity of urban freight distribution, high initial investment, logistics disadvantages and vulnerabilities, lack of technical standards and planning guidelines, market fragmentation and its negative impact, and incompatibility between urban rail transit and urban logistics at the national and regional levels, and then analyze the threats to the external environment for the development of urban subway freight systems;

[0093] Step 1.1.3: Analyze the advantages of developing a metro freight system for the city, mainly covering the interests of stakeholders, alignment with national development goals, emerging technologies and market indicators;

[0094] Step 1.1.4: Analyze the weaknesses of the urban metro freight system development, mainly covering unreasonable planning and decision-making, ambiguity in public awareness and attitude, inadequate governance and management, and abuse and blind following of indicators;

[0095] Step 1.2 Use a questionnaire survey method to invite experts to score each SWOT indicator and propose new indicators;

[0096] Step 1.2.1, invite nine experts to evaluate the 18 indicators based on the city context, using a Likert scale to rate each indicator, ranging from 1 (not very relevant) to 5 (most relevant);

[0097] Step 1.2.2, calculate the final importance score of indicator j, such as Figure 2 As shown;

[0098]

[0099] Among them, Score j is the importance score of SWOT indicator j; a ij is the original score of expert i for indicator j; n ij is a weight parameter, which depends on the closeness of the expert's expertise to the indicator's knowledge domain.

[0100] Step 1.3: Determine the selection of indicators for evaluating the suitability of urban subway freight system development based on the SWOT analysis framework. The process of evaluating indicators in this invention is as follows: Figure 3 As shown; the engineering and infrastructure capacity indicators can be quantitatively described using network capacity indicators, infrastructure indicators, customer proximity indicators and urban logistics hub proximity indicators;

[0101] A large number of freight demand indicators can be quantitatively described using demand scale indicators;

[0102] Emerging technologies and market indicators can be quantitatively described using consumption and market indicators;

[0103] Social-environmental benefit indicators can be quantitatively described using environmental benefit indicators;

[0104] In line with national development target indicators, it can be quantitatively described using transportation-oriented development indicators;

[0105] The efficiency advantage and supply chain integration and profitability indicators can be quantitatively described using implementation cost indicators;

[0106] In addition, urban economic indicators and urgency indicators for truck restrictions were proposed.

[0107] Furthermore, in step 2, the calculation of the subway freight system development suitability evaluation index includes the following steps:

[0108] 2.1 Calculate the network capacity C1, which is used to reflect the freight capacity of the urban rail transit network;

[0109] The network capacity C1 is represented by the available space for installing freight-related modules in the passenger-freight sharing station and the comprehensive freight capacity of the railway;

[0110] 2.1.1 Calculate the available space for installing freight-related modules in the passenger-freight sharing station. The calculation formula is as follows:

[0111] S=SA Fmodule ×Ucap FPS

[0112] Where S is the available space value for installing freight-related modules in the passenger-freight sharing station; SA is Fmodule is the total area of ​​passenger and freight shared stations in the urban rail transit network; Ucap FPS is the capacity per unit area of ​​installed modules;

[0113] 2.1.2 Calculate the comprehensive freight capacity of the railway. The comprehensive freight capacity of the railway is obtained by accumulating the daily freight capacity of Line i under the FoT-EC operation mode and the daily freight capacity of Line i under the FoT-DT operation mode. The calculation formula is as follows:

[0114]

[0115] Among them, C is the comprehensive freight volume of the railway; is the number of passenger trains associated with each relevant line i; Ucap EC is the cargo capacity of the additional compartment; Ucap DT It is the car load of a dedicated freight train; is the maximum possible number of freight train services, calculated as follows:

[0116]

[0117] in, is the end time of passenger service; The last DFT service start time; MT i is the time before the start of the last dedicated freight train service on the next day; the constant δ is the departure frequency of dedicated freight trains; the operation of dedicated freight trains is subject to HT([Δt]). It is assumed that at most one dedicated freight train service can be added between two adjacent passenger services; HT i (j, j+1) represents the interval between passenger trains j and j+1; i∈Ω represents the set of lines in the urban rail transit network, and j∈M represents the set of passenger train services.

[0118] 2.1.3 Calculation of network capacity C1

[0119]

[0120] where λ 11 ∈(0,1),λ 12 ∈(0,1),λ 11 +λ 12 =1

[0121] Among them, C1 is the network capacity indicator; SA Fmodule 、Ucap FPS , Ucap EC 、Ucap DT The meaning is the same as above; 11 and λ 12 are the weights corresponding to the two items respectively.

[0122] 2.2 Calculation of infrastructure C2, which is used to reflect the richness of dedicated railway facilities, is calculated as follows:

[0123] C2=N station ×N transfer ×URTL

[0124] Among them, C2 is the infrastructure indicator; N station is the number of urban rail transit stations; N transfer is the number of urban rail transit transfer stations; URTL is the length of the urban rail transit network.

[0125] 2.3 Calculate the demand scale C3. This indicator is used to reflect the demand scale of urban freight. The calculation formula is as follows:

[0126] C3=N EP ×N SMRS

[0127] Among them, C3 is the demand scale indicator, N EP is the number of e-commerce packages delivered in the city each year, N SMRS It is the total number of shopping malls and retail stores in the city.

[0128] 2.4 Calculation of consumption and market C4. This indicator is used to reflect the market size and operating conditions of the urban logistics industry. The calculation formula is as follows:

[0129] C4=λ 41 ×LBI+λ 42 ×RSG,λ 41 ∈(0,1),λ 42 ∈(0,1),λ 41 +λ 42 =1

[0130] Among them, C4 is the consumption and market index, LBI is the annual operating income of the urban logistics market, reflecting the market size and operating conditions of the urban logistics industry; RSG is the annual retail sales of social commodities, reflecting the purchasing power of citizens and the prosperity of the urban economy. 41 is the relative weight value of LBI, λ 42 is the relative weight value of RSG.

[0131] 2.5 Calculation of environmental benefit C5. This indicator is used to reflect the environmental benefit of the subway freight system. The calculation formula is as follows: Among them, C5 is the environmental benefit index of the subway freight system; is the number of passenger trains associated with each relevant route i; is the maximum possible number of freight train services; Ucap EC is the cargo capacity of the additional compartment; Ucap DT It is the car load of a dedicated freight train; is the average daily driving distance of a single truck; REV is the utilization rate of electric vehicles in urban logistics activities; Ucap truck is the average daily cargo volume transported by each truck; α CO is the cost of treating carbon monoxide (CO) produced per kilometer of truck travel; is the cost of handling carbon dioxide (CO2) produced per kilometer of truck travel; is the nitrogen oxides (NO X ) processing cost; α PM is the cost of treating particulate matter (PM) generated per kilometer of truck travel; α noise is the cost of handling the noise generated per kilometer of truck travel.

[0132] 2.6 Calculate the proximity of the upstream logistics hub C6. This index is used to reflect the proximity of the spatial distance between the upstream logistics hub and the subway freight network. The calculation formula is as follows:

[0133]

[0134] Among them, C6 is the proximity index of urban logistics hubs, ‖S‖ is the number of ULHs, |z s -z k | is the Euclidean distance between the upstream logistics hub and the urban rail transit station; the upstream logistics hub s ∈S; urban rail transit station k∈K; K is the set of all stations. Rules: If the first nearest station belongs to Line i, then K′ is defined as the set of stations excluding all stations on Line i; if the second nearest station belongs to Line j, then K″ is defined as the set of stations excluding all stations on Line i and Line j.

[0135] 2.7 Calculate the proximity to customers C7, which is used to reflect the proximity between the urban rail transit network and the final destination of urban delivery. The calculation formula is as follows:

[0136]

[0137] Where C7 is the proximity index of the urban rail transit network to customers; UR(ε) is the total area of ​​urban areas with a population density exceeding ε; F(ε) is the number of urban rail transit stations in the UR(ε) area; |z q -z k | is the Euclidean distance between a registered postal service site q and its nearest station.

[0138] 2.8 Calculate the transportation-oriented development C8, which is used to reflect the standard for evaluating the suitability of the subway freight system. The calculation formula is as follows:

[0139]

[0140] Among them, C8 is a public transportation-oriented development index, and TOD is a city's public transportation-oriented development index. is the conversion factor.

[0141] 2.9 Calculate the implementation cost C9, which is used to reflect the economic feasibility of the subway freight system. The calculation formula is as follows:

[0142]

[0143] Among them, C9 is the implementation cost indicator, ConsC is the construction cost per kilometer of the urban rail transit line that has been in operation recently; OperC is the annual operating cost of urban rail transit; URTL is the length of the urban rail transit network; λ 91 is the relative weight value of the construction cost per kilometer of the recently operated urban rail transit line; 92 It is the relative weight value of the annual operating cost of urban rail transit averaged by network length.

[0144] 2.10 Calculation of Urban Economy C 10 , this indicator is used to reflect the economic basis required for the implementation of the subway freight system. Its calculation formula is as follows:

[0145] C 10 =GDP / POP×(λ 101 ×FGBR+λ 102 ×TIFA),λ 101 ∈(0,1),λ 102 ∈(0,1),λ 101 +λ 102 =1

[0146] Among them, C 10 is the city's economic indicator; GDP is gross domestic product; POP is population; FGBR is fiscal general budget revenue; TIFA is total fixed asset investment. 101is the relative weight value of the general budget revenue; 102 It is the relative weight value of the total amount of fixed asset investment.

[0147] 2.11 Calculation of the urgency of the truck limit C 11 , this indicator is used to reflect the contribution of the subway freight system to urban freight mobility, and its calculation formula is as follows:

[0148] C 11 =BanT×BanA×N truck

[0149] Among them, C 11 is the urgency indicator of the truck restriction, BanT is the daily truck ban period; BanA is the area of ​​the truck ban zone; N truck is the number of trucks affected.

[0150] Furthermore, in the step three, the basic data required for the suitability evaluation index of the urban subway freight system development in the area to be studied is obtained through multi-source data collection, and all the acquired data are screened and mined to obtain the parameters required for the analysis index. The multi-source data includes data related to the urban subway freight system and basic data related to the urban population and economy, and specifically includes the following steps:

[0151] Step 3.1: Obtain relevant data of urban subway freight system;

[0152] The relevant data include:

[0153] Railway length, number of lines, trains and services, average daily passenger flow, number of urban rail transit stations N station ; The number of urban rail transit transfer stations N transfer , annual operating cost of urban rail transit OperC, total number of trains, daily services, TOD index data, the specific situation is as follows:

[0154] Step 3.1.1: Obtain the railway length, number of lines, trains and services, average daily passenger flow, TOD index, and number of urban rail transit stations N according to the statistical reports released by the Metro Association. station ; The number of urban rail transit transfer stations N transfer , data on annual operating costs of urban metro freight OperC. Using the obtained relevant data, the attribute values ​​of the indicators of infrastructure C2, implementation costs C9 and transport-oriented development C8 can be calculated;

[0155] Step 3.1.2: Obtain the timetable information of each subway line from the website of the subway operator of each city; the timetable information data includes the end time of passenger service Last dedicated freight train service starts The departure frequency δ of the dedicated freight train, the interval HT between passenger trains j and j+1 i (j,j+1);

[0156] Dedicated freight train operation is subject to HT([Δt]). At most one DFT service can be added between two adjacent passenger services. Based on the collected subway timetable data, the maximum possible number of freight train services is calculated. The calculation formula is as follows: in, is the maximum possible number of freight train services, is the end time of passenger service; The last DFT service start time; MT i is the time before the start of the last dedicated freight train service compared to the first passenger service of the next day; δ is the departure frequency of dedicated freight trains; HT i (j,j+1) is the interval between passenger trains j and j+1; when HT i (j,j+1)≥[Δt] ij is 1, otherwise ξ ij It is 0.

[0157] Time during passenger service Calculate the network capacity C1, the calculation formula is as follows:

[0158]

[0159] where λ 11 ∈(0 , 1),λ 12 ∈(0 , 1),λ 11 +λ 12 =1

[0160] Among them, C1 is the network capacity indicator; SA Fmodule is a rough data of the total area of ​​FPSs in the urban rail transit network; Ucap FPS is the capacity per unit area of ​​installed modules; is the number of passenger trains associated with each relevant line i; Ucap EC is the freight capacity of the additional carriage; is the maximum possible number of freight train services; Ucap DT is the vehicle load of DFTs;

[0161] Step 3.2: Obtain urban traffic and logistics data;

[0162] The relevant data include: the number of e-commerce packages delivered in the city each year NEP 、Number of trucks affected truck , Number of registered postal service sites N RPS , the total number of shopping malls and retail stores in the city N SMRS , the daily truck travel ban period BanT, the area of ​​the truck ban zone BanA, and the average daily driving distance of a single truck The annual operating income of the urban logistics market is LBI, as follows:

[0163] Step 3.2.1: Obtain the number of e-commerce parcels delivered in the city each year N according to the published Statistical Bulletin of Urban Postal Industry Development in 2017 EP 、Number of trucks affected truck , annual operating income of urban logistics market LBI, number of registered postal service stations N RPS Data, using the acquired relevant data, the attribute value of the demand scale C3 indicator can be calculated;

[0164] Step 3.2.2: Obtain the total number of shopping malls and retail stores in the city N according to the published "Statistical Yearbook of Retail and Catering Chain Enterprises in 2017" SMRS data;

[0165] Step 3.2.3: Refer to the freight policies issued by the traffic management departments of the sample cities to determine the daily truck travel ban period BanT and the area of ​​the truck ban zone BanA. Using the obtained relevant data, the urgency of truck restrictions C can be calculated. 11 The attribute value of the indicator;

[0166] Step 3.2.4: Calculate the average daily distance travelled by a single truck based on the published Urban Transport Development Annual Report Numerical value: Using the acquired relevant data, the attribute value of the environmental benefit C5 indicator can be calculated;

[0167] Step 3.2.5: An empirical survey was conducted to obtain the remaining statistics that have not yet been fully recorded;

[0168] Step 3.2.6: The geographical coordinates of POIs are obtained through feedback from the Baidu Map application programming interface using data mining technology. The POIs include "subway station", "distribution center" and "express delivery". A distance matrix is ​​established after cleaning the original data. The attribute values ​​of the upstream logistics hub proximity C6 and the proximity to customers C7 indicators can be calculated using the obtained relevant data.

[0169] Step 3.3 Obtain data related to the city’s population and socio-economics;

[0170] The relevant data include: population, gross domestic product, total fixed asset investment, fiscal general budget revenue, annual retail sales of social commodities, population density over 60 people / hm2 2 The total land area is as follows:

[0171] Step 3.3.1: According to the published "XX City Statistical Yearbook", obtain data such as population POP, gross domestic product GDP, fiscal general budget revenue FGBR, total fixed asset investment TIFA, and annual retail sales of social goods RSG. Using the obtained relevant data, the city's economic C can be calculated. 10 and the attribute values ​​of the consumption and market C4 indicators;

[0172] Step 3.3.2: Obtain the real-time population heat map of the sample cities from 7:00 to 8:00 on December 26, 2021 by querying the location-based service (LBS) data platform on the Baidu Map API; identify cities with a population density of more than 60 people / hm2. 2 The total land area UR of (the threshold of high density area).

[0173] Furthermore, in the step 4, the entropy weighted analytic hierarchy process is used to calculate the weights of each evaluation index, and the VIKOR comprehensive evaluation method is used to calculate the decision index; specifically, the following steps are included:

[0174] Step 4.1 Use hierarchical analysis to calculate the weight of each evaluation index;

[0175] Step 4.1.1 uses the 1-9 scaling method to construct a pairwise comparison matrix, and the pairwise comparison matrix B is as follows:

[0176]

[0177] Among them, the matrix element b ij Indicates the evaluation index b i Evaluation index b j The relative importance of is determined by selecting the specific value from Table 41 below;

[0178] Table 41 Evaluation index pairwise comparison matrix element value table

[0179]

[0180] Step 4.1.2 solves the pairwise comparison matrix;

[0181] Calculate the relative weight of each evaluation index and use the constructed pairwise comparison matrix to calculate its maximum eigenvalue λ max The corresponding eigenvector W = [w i ] T , W is the relative weight of the corresponding evaluation index;

[0182] Step 4.1.3 consistency check;

[0183] To determine whether the weight results calculated above are reasonable, it is necessary to perform a consistency check on the pairwise comparison matrix. If the check passes, a decision can be made according to the calculated weight vector, otherwise a new judgment matrix needs to be reconstructed and calculated again. Usually, the consistency index CI, random consistency index RI and random consistency ratio CR are introduced to measure.

[0184] The calculation formula of the random consistency ratio CR is as follows:

[0185] CR=CI / RI

[0186] Among them, CR is the random consistency ratio; RI is the random consistency index, and CI is the consistency index. When the CR value does not exceed 0.1, it means that the weight calculation result meets the consistency requirement, and the normalized eigenvector can be used as the weight vector; otherwise, it is necessary to reconstruct the judgment matrix and adjust a ij Until the calculation results meet the consistency requirements.

[0187] The calculation formula of consistency index CI is as follows:

[0188] CI=(λ max -n) / (n-1)

[0189] Among them, CI is the consistency index; λ max represents the maximum eigenvalue of the judgment matrix, n represents the order of the judgment matrix; RI is the average random consistency index of the judgment matrix;

[0190] For the 1-11 order judgment matrix, the value of the random consistency index RI is as follows:

[0191] Table 41 Random Consistency Index RI Value Table

[0192]

[0193] Step 4.2: Use the improved VIKOR method to comprehensively evaluate and determine the suitability level of urban subway freight system development;

[0194] 4.2.1 Construct a decision matrix and normalize the index values;

[0195] Different indicators have different dimensions and cannot be directly compared. It is necessary to normalize the original indicators and construct the decision matrix H:

[0196]

[0197] Among them, h ij For alternative option p i Relative to the evaluation index qj Normalized measure of ;

[0198] 4.2.2 Determine the positive ideal solution and the negative ideal solution;

[0199] In order to increase the comparability of the results, the constructed decision matrix H is standardized. i It is represented by a benefit index and a cost index. The larger the value of the benefit index, the better the solution. When the benefit formula is used, the smaller the value of the cost index, the better the solution. According to the principle, the final alternative solution p is determined. i The positive ideal solution of and negative ideal solution function:

[0200]

[0201]

[0202] 4.2.3 Calculation of group benefit index S i and individual regret indicators Y i ;

[0203] The group benefit index S i , and its calculation formula is as follows:

[0204]

[0205] Among them, w j The attribute q representing the output of the AHP j The weight of h ij For alternative option p i Relative to the evaluation index q j Normalized measure of ;

[0206]

[0207] The individual regret indicator Y i , and its calculation formula is as follows:

[0208]

[0209] Among them, w j The indicator q representing the output of the AHP j The weight of h ij For alternative option p i Relative to the evaluation index q j Normalized measure of ;

[0210] 4.2.4 Decision Index R i calculate;

[0211] Considering the different impacts of different indicators on alternatives, the calculated weights are introduced into the VIKOR comprehensive evaluation calculation, and the alternative p is calculated using the following formula: i The compromise decision index R i :

[0212]

[0213] in, Set μ = 0.5, where μ represents the relative importance between group utility and individual regret;

[0214] Step 4.3: Comprehensive evaluation criteria for the suitability of urban subway freight system development:

[0215] The decision index R based on the suitability of the urban subway freight system development i , optimize the selection and sorting of the suitability of urban subway freight system development, and the decision index R i The order of size is the order of suitability of the alternatives;

[0216] Furthermore, in the step five, 16 cities are selected as options, and the comprehensive score results of the indicators are calculated based on the developed evaluation model. According to the evaluation criteria, the suitability of urban subway freight system development is determined, and the cities are divided into echelons, providing an application example for the developed subway freight system development suitability evaluation method.

[0217] The comprehensive scoring formula for the indicators of suitability for the development of the urban subway freight system is:

[0218]

[0219] Among them, R j is the comprehensive calculation value of the jth alternative; w j It is the indicator q output by the hierarchical analysis method j The weight of h ij is the alternative p i Relative to the evaluation index q j The normalized index value of

[0220] The comprehensive scores of the indicators of the 16 alternative solutions in this embodiment are shown in Figure 5 .

[0221] Example 1

[0222] This embodiment combines the subway freight systems of 16 advanced cities to provide a suitability evaluation method for the development of urban subway freight systems. The overall process diagram is as follows: Figure 1 As shown, the specific steps include:

[0223] Step 1: Construct a framework for analyzing the suitability of urban subway freight system development;

[0224] Based on the SWOT method, through qualitative analysis of the strengths, weaknesses, opportunities and threats of urban subway freight system development, an urban subway freight system development suitability evaluation index system is established, and an urban subway freight system development suitability analysis framework is constructed;

[0225] 1.1 Based on the SWOT method, the urban subway freight system development suitability analysis framework is formulated as follows: Figure 2 As shown;

[0226] Step 1.1.1: Analyze the impact of large freight demand, government leadership and top-down development strategy, engineering and infrastructure capabilities, social-environmental benefits, efficiency advantages, supply chain integration and profitability, system organization and expansion flexibility on the development of urban subway freight systems from the perspectives of urban economy and urban development, and then analyze the opportunities for the development of urban subway freight systems;

[0227] Step 1.1.2: Interpret the complexity of urban freight distribution, high initial investment, logistics disadvantages and vulnerabilities, lack of technical standards and planning guidelines, market fragmentation and its negative impact, and incompatibility between urban rail transit and urban logistics at the national and regional levels, and then analyze the threats to the external environment for the development of urban subway freight systems;

[0228] Step 1.1.3: Analyze the advantages of developing a metro freight system for the city, mainly covering the interests of stakeholders, alignment with national development goals, emerging technologies and market indicators;

[0229] Step 1.1.4: Analyze the weaknesses of the urban metro freight system development, mainly covering unreasonable planning and decision-making, ambiguity in public awareness and attitude, inadequate governance and management, and abuse and blind following of indicators;

[0230] Step 1.2 Use a questionnaire survey method to invite experts to score each SWOT indicator and propose new indicators;

[0231] Step 1.2.1, invite nine experts to evaluate the 18 indicators based on the city context, using a Likert scale to rate each indicator, ranging from 1 (not very relevant) to 5 (most relevant);

[0232] Step 1.2.2, calculate the final importance score of indicator j, such as Figure 2 As shown;

[0233]

[0234] Among them, a ijis the original score of expert i for indicator j; n ij is a weight parameter, which depends on the closeness of the expert’s expertise to the indicator’s knowledge domain, n ij ∈[0.2,3],

[0235] Step 1.3 Determine the selection of indicators for the evaluation of the suitability of the development of the urban subway freight system based on the SWOT analysis framework. The process of evaluating indicators in the present invention is as follows: Figure 3 shown.

[0236] The engineering and infrastructure capacity indicators can be quantitatively described using network capacity indicators, infrastructure indicators, customer proximity indicators, and city logistics hub proximity indicators;

[0237] The aforementioned large number of freight demand indicators can be quantitatively described using demand scale indicators;

[0238] The emerging technologies and market indicators can be quantitatively described using consumption and market indicators;

[0239] The social-environmental benefit index can be quantitatively described using the environmental benefit index;

[0240] The indicators that meet the national development goals can be quantitatively described using transportation-oriented development indicators;

[0241] The efficiency advantages and supply chain integration and profitability indicators can be quantitatively described using implementation cost indicators;

[0242] Furthermore, additional indicators of urban economics and urgency of truck restrictions were proposed.

[0243] Step 2: Develop the evaluation index and quantitative calculation method of suitability of urban subway freight system;

[0244] Indicator types include cost and benefit. The smaller the cost-type indicator, the better; the larger the benefit-type indicator, the better.

[0245] The cost-based indicators include: proximity to urban logistics hubs C6, proximity to customers C7, transportation-oriented development C8, and implementation costs C9; the benefit-based indicators include: network capacity C1, infrastructure C2, demand scale C3, consumption and market C4, environmental benefits C5, urban economy C6, and urban logistics hubs C7. 10 、The urgency of truck restrictions 11 ;

[0246] 2.1 Calculate the network capacity C1, which is used to reflect the freight capacity of the urban rail transit network;

[0247] The network capacity C1 is represented by the available space for installing freight-related modules in the passenger-freight sharing station and the comprehensive freight capacity of the railway;

[0248] 2.1.1 Calculate the available space for installing freight-related modules in the passenger-freight sharing station. The calculation formula is as follows:

[0249] S=SA Fmodule ×Ucap FPS

[0250] Where S is the available space for installing freight-related modules in the passenger-freight sharing station; SA Fmodule is the total area of ​​passenger and freight shared stations in the urban rail transit network; Ucap FPS is the capacity per unit area of ​​installed modules;

[0251] 2.1.2 Calculate the comprehensive freight capacity of the railway. The comprehensive freight capacity of the railway is obtained by accumulating the daily freight capacity of Line i under the FoT-EC operation mode and the daily freight capacity of Line i under the FoT-DT operation mode. The calculation formula is as follows:

[0252]

[0253] Among them, C is the comprehensive freight capacity of the railway; is the number of passenger trains associated with each relevant line i; Ucap EC is the cargo capacity of the additional compartment; Ucap DT It is the car load of a special freight train; is the maximum possible number of freight train services, calculated as follows:

[0254]

[0255] in, is the end time of passenger service; The last DFT service start time; MT i is the time before the start of the last dedicated freight train service on the next day; the constant δ is the departure frequency of dedicated freight trains; the operation of dedicated freight trains is subject to HT([Δt]). It is assumed that at most one dedicated freight train service can be added between two adjacent passenger services; HT i (j, j+1) represents the interval between passenger trains j and j+1; i∈Ω represents the set of lines in the urban rail transit network, and j∈M represents the set of passenger train services.

[0256] 2.1.3 The network capacity C1 is calculated based on the available space for installing freight-related modules in the passenger-freight shared station and the comprehensive freight capacity of the railway;

[0257]

[0258] where λ 11 ∈(0,1),λ 12 ∈(0,1),λ 11 +λ 12 =1

[0259] Among them, C1 is the network capacity indicator; SA Fmodule 、Ucap FPS , Ucap EC 、Ucap DT The meaning is the same as above; 11 and λ 12 are the weights corresponding to the two items respectively.

[0260] 2.2 Calculation of infrastructure C2, which is used to reflect the richness of dedicated railway facilities, is calculated as follows:

[0261] C2=N station ×N transfer ×URTL

[0262] Among them, C2 is the infrastructure indicator; N station is the number of urban rail transit stations; N transfer is the number of urban rail transit transfer stations; URTL is the length of the urban rail transit network.

[0263] 2.3 Calculate the demand scale C3. This indicator is used to reflect the demand scale of urban freight. The calculation formula is as follows:

[0264] C3=N EP ×N SMRS

[0265] Among them, C3 is the demand scale indicator, N EP is the number of e-commerce packages delivered in the city each year, N SMRS It is the total number of shopping malls and retail stores in the city.

[0266] 2.4 Calculation of consumption and market C4. This indicator is used to reflect the market size and operating conditions of the urban logistics industry. The calculation formula is as follows:

[0267] C4=λ 41 ×LBI+λ 42 ×RSG,λ 41 ∈(0,1),λ 42 ∈(0,1),λ 41 +λ 42 =1

[0268] Among them, C4 is the consumption and market index, LBI is the annual operating income of the urban logistics market, reflecting the market size and operating conditions of the urban logistics industry; RSG is the annual retail sales of social commodities, reflecting the purchasing power of citizens and the prosperity of the urban economy. 41 is the relative weight value of LBI, λ 42 is the relative weight value of RSG.

[0269] 2.5 Calculation of environmental benefit C5. This indicator is used to reflect the environmental benefit of the subway freight system. The calculation formula is as follows:

[0270]

[0271] Among them, C5 is the environmental benefit index of the subway freight system; is the number of passenger trains associated with each relevant route i; is the maximum possible number of freight train services; Ucap EC is the cargo capacity of the additional compartment; Ucap DT is a car load at a registered Postal Service site; is the average daily driving distance of a single truck; REV is the utilization rate of electric vehicles in urban logistics activities; Ucap truck is the average daily cargo volume transported by each truck; α CO is the cost of treating carbon monoxide (CO) produced per kilometer of truck travel; is the cost of handling carbon dioxide (CO2) produced per kilometer of truck travel; is the nitrogen oxides (NO X ) processing cost; α PM is the cost of treating particulate matter (PM) generated per kilometer of truck travel; α noise is the cost of handling the noise generated per kilometer of truck travel.

[0272] 2.6 Calculate the proximity of the upstream logistics hub C6. This index is used to reflect the proximity of the spatial distance between the upstream logistics hub and the subway freight network. The calculation formula is as follows:

[0273]

[0274] Among them, C6 is the proximity index of urban logistics hubs, ‖S‖ is the number of ULHs, |z s -z k| is the Euclidean distance between the upstream logistics hub and the urban rail transit station; upstream logistics hub s∈S; urban rail transit station k∈K; K is the set of all stations. Rules: If the first nearest station belongs to Line i, then K′ is defined as the set of stations excluding all stations on Line i; if the second nearest station belongs to Line j, then K″ is defined as the set of stations excluding all stations on Line i and Line j.

[0275] 2.7 Calculate the proximity to customers C7, which is used to reflect the proximity between the urban rail transit network and the final destination of urban delivery. The calculation formula is as follows:

[0276]

[0277] Where C7 is the proximity index of the urban rail transit network to customers; UR(ε) is the total area of ​​urban areas with a population density exceeding ε; F(ε) is the number of urban rail transit stations in the UR(ε) area; |z q -z k | is the Euclidean distance between a registered postal service site q and its nearest station.

[0278] 2.8 Calculate the transportation-oriented development C8, which is used to reflect the standard for evaluating the suitability of the subway freight system. The calculation formula is as follows:

[0279]

[0280] Among them, C8 is a public transportation-oriented development index, and TOD is a city's public transportation-oriented development index. is the conversion factor.

[0281] 2.9 Calculate the implementation cost C9, which is used to reflect the economic feasibility of the subway freight system. The calculation formula is as follows:

[0282]

[0283] Among them, C9 is the implementation cost indicator, ConsC is the construction cost per kilometer of the urban rail transit line that has been recently operated; OperC is the annual operating cost of urban rail transit; URTL, is the length of the urban rail transit network; λ 91 is the relative weight value of the construction cost per kilometer of the recently operated urban rail transit line; 92 It is the relative weight value of the annual operating cost of urban rail transit averaged by network length.

[0284] 2.10 Calculation of Urban Economy C 10 , this indicator is used to reflect the economic basis required for the implementation of the subway freight system. Its calculation formula is as follows:

[0285] C 10 =GDP / POP×(λ 101 ×FGBR+λ 102 ×TIFA),λ 101 ∈(0,1),λ 102 ∈(0,1),λ 101 +λ 102 =1

[0286] Among them, C 10 is the city's economic indicator; GDP is gross domestic product; POP is population; FGBR is fiscal general budget revenue; TIFA is total fixed asset investment. 101 is the relative weight value of the general budget revenue; 102 It is the relative weight value of the total amount of fixed asset investment.

[0287] 2.11 Calculation of the urgency of the truck limit C 11 , this indicator is used to reflect the contribution of the subway freight system to urban freight mobility, and its calculation formula is as follows:

[0288] C 11 =BanT×BanA×N truck

[0289] Among them, C 11 is the urgency indicator of the truck restriction, BanT is the daily truck ban period; BanA is the area of ​​the truck ban zone; N truck is the number of trucks affected.

[0290] Step 3: Multi-source data collection;

[0291] Step 3.1: Obtain relevant data of urban subway freight system;

[0292] The relevant data include railway length, number of lines, trains and services, average daily passenger flow, number of urban rail transit stations N station ; The number of urban rail transit transfer stations, N transfer , annual operating cost of urban rail transit OperC, total number of trains, daily service data TOD index, the specific situation is as follows:

[0293] Step 3.1.1 This embodiment obtains the route map of 16 sample urban rail transit systems, such as Figure 4 shown.

[0294] Step 3.1.2: Obtain the railway length, number of lines, trains and services, average daily passenger flow, TOD index, and number of urban rail transit stations N according to the statistical report (xx) released by the Metro Association station; The number of urban rail transit transfer stations, N transfer , urban subway freight annual operating cost OperC data; the relevant data of 16 urban subway freight systems selected in this embodiment are shown in Table 31 below:

[0295] Table 31 Urban rail transit data collection table

[0296]

[0297]

[0298] Using the relevant data obtained, the attribute values ​​of the indicators infrastructure C2, implementation costs C9 and transport-oriented development C8 can be calculated;

[0299] Step 3.1.3: Obtain the timetable information of each subway line from the website of the subway operator of each city; the timetable information data includes the end time of passenger service Last dedicated freight train service starts The departure frequency δ of the dedicated freight train, the interval HT between passenger trains j and j+1 i (j,j+1);

[0300] The operation of dedicated freight trains is subject to HT([Δt]). At most one dedicated freight train service can be added between two adjacent passenger services. The time between passenger services is calculated based on the collected subway timetable data. The calculation formula is as follows:

[0301]

[0302] in, is the maximum possible number of freight train services, is the end time of passenger service; The last DFT service start time; MT i is the time before the start of the last dedicated freight train service compared to the first passenger service of the next day; δ is the departure frequency of dedicated freight trains; HT i (j,j+1) is the interval between passenger trains j and j+1; when HT i (j,j+1)≥[Δt] ij is 1, otherwise ξ ij It is 0.

[0303] According to the time of passenger service Calculate the network capacity C1, the calculation formula is as follows:

[0304]

[0305] where λ 11 ∈(0,1),λ 12 ∈(0,1),λ 11 +λ 12 =1

[0306] Among them, C1 is the network capacity indicator; SA Fmodule is a rough data of the total area of ​​FPSs in the urban rail transit network; Ucap FPS is the capacity per unit area of ​​installed modules; is the number of passenger trains associated with each relevant line i; Ucap EC is the freight capacity of the additional carriage; is the maximum possible number of freight train services; Ucap DT is a car load at a registered Postal Service site;

[0307] Step 3.2: Obtain urban traffic and logistics data;

[0308] The relevant data include: the number of e-commerce packages delivered in the city each year N EP , the number of trucks affected N truck , Number of registered postal service sites N RPS , the total number of shopping malls and retail stores in the city N SMRS , the daily truck travel ban period BanT, the area of ​​the truck ban zone BanA, and the average daily driving distance of a single truck Annual operating income of urban logistics market LBI, the transportation and logistics related data of 16 urban subway freight systems selected in this embodiment are shown in Table 32 below:

[0309] Table 32 Urban transportation and logistics data collection table

[0310]

[0311]

[0312] Step 3.2.1: Obtain the number of e-commerce parcels delivered in the city each year N according to the published Statistical Bulletin of Urban Postal Industry Development in 2017 EP ,,Number of trucks affected truck , annual operating income of urban logistics market LBI, number of registered postal service stations N RPS Data, using the acquired relevant data, the attribute value of the demand scale C3 indicator can be calculated;

[0313] Step 3.2.2: Obtain the total number of shopping malls and retail stores in the city N according to the published "XX Retail and Catering Chain Enterprise Statistical Yearbook" SMRS data;

[0314] Step 3.2.3: Refer to the freight policies issued by the traffic management departments of the sample cities to determine the daily truck travel ban period BanT and the area of ​​the truck ban zone BanA. Using the obtained relevant data, the urgency of truck restrictions C can be calculated. 11 The attribute value of the indicator;

[0315] Step 3.2.4: Calculate the average daily distance travelled by a single truck based on the published Urban Transport Development Annual Report Numerical value: Using the acquired relevant data, the attribute value of the environmental benefit C5 indicator can be calculated;

[0316] Step 3.2.5: An empirical survey was conducted to obtain the remaining statistics that have not yet been fully recorded;

[0317] Step 3.2.6: The geographical coordinates of POIs are obtained through feedback from the Baidu Map application programming interface using data mining technology. The POIs include "subway station", "distribution center" and "express delivery". A distance matrix is ​​established after cleaning the original data. The attribute values ​​of the upstream logistics hub proximity C6 and the proximity to customers C7 indicators can be calculated using the obtained relevant data.

[0318] Step 3.3 Obtain data related to the city’s population and socio-economics;

[0319] The relevant data include: population, gross domestic product, total fixed asset investment, fiscal general budget revenue, annual retail sales of social commodities, population density over 60 people / hm2 2 The total land area, urban population and economic data of the 16 cities selected in this embodiment are shown in Table 33 below:

[0320] Table 33 Collection table of urban population and economic related data

[0321]

[0322]

[0323] Step 3.3.1: According to the published "XX City Statistical Yearbook", obtain data such as population POP, gross domestic product GDP, fiscal general budget revenue FGBR, total fixed asset investment TIFA, and annual retail sales of social goods RSG. Using the obtained relevant data, the city's economic C can be calculated. 10 and the attribute values ​​of the consumption and market C4 indicators;

[0324] Step 3.3.2: Obtain the real-time population heat map of 16 sample cities during 7:00-8:00 on xx / xx / xx by querying the location-based service (LBS) data platform on Baidu Map API; identify cities with a population density of more than 60 people / λm 2 The total land area UR of (the threshold of high density area).

[0325] Step 4: Establishment of indicator processing and evaluation criteria;

[0326] Step 4.1 Calculate the weight of each evaluation index by combining the analytic hierarchy process and expert group decision-making;

[0327] Step 4.1.1 Experts compare the relative importance of the 11 indicators in pairs, quantify the comparison results on a scale of 1-9, and construct a pairwise comparison matrix B:

[0328]

[0329] Among them, the matrix element b ij Indicates the evaluation index b i Evaluation index b j The relative importance of is determined by selecting the specific value from Table 41 below;

[0330] Table 41 Evaluation index pairwise comparison matrix element value table

[0331]

[0332] Step 4.1.2 Solve the pairwise comparison matrix

[0333] Calculate the relative weight of each evaluation index and use the constructed pairwise comparison matrix to calculate its maximum eigenvalue λ max The corresponding eigenvector, W = [w i ] T , W is the relative weight of the corresponding evaluation index;

[0334] Step 4.1.3 Consistency check

[0335] To determine whether the weight results calculated above are reasonable, it is necessary to perform a consistency test on the pairwise comparison matrix. If the test passes, a decision can be made according to the calculated weight vector, otherwise a new judgment matrix needs to be reconstructed and calculated again. The general consistency index CI, the average random consistency index RI and the random consistency ratio CR are usually introduced to measure.

[0336] The calculation formula of the random consistency ratio CR is as follows:

[0337] CR=CI / RI

[0338] Among them, CR is the random consistency ratio; RI is the random consistency index, and CI is the consistency index;

[0339] The calculation formula of consistency index CI is as follows:

[0340] CI=(λ max -n) / (n-1)

[0341] Among them, CI is the consistency index; λ max represents the maximum eigenvalue of the judgment matrix, n represents the order of the judgment matrix; RI is the average random consistency index of the judgment matrix;

[0342] For the 1-11 order judgment matrix, the value of the average random consistency index RI is as follows:

[0343] Table 41 Random Consistency Index RI Value Table

[0344]

[0345] When the CR value does not exceed 0.1, it means that the weight calculation result meets the consistency requirement, and the normalized eigenvector can be used as the weight vector; otherwise, it is necessary to reconstruct the judgment matrix and adjust a ij Until the calculation results meet the consistency requirements.

[0346] According to the consistency test results of the judgment matrix, the weight vector W of the urban subway freight system development suitability evaluation index system is determined as follows:

[0347] W=[0.067,0.139,0.09,0.076,0.174,0.077,0.068,0.048,0.155,0.057,0.049];

[0348] Step 4.2 Use the VIKOR method to comprehensively evaluate and determine the suitability level of urban subway freight system development;

[0349] 4.2.1 Construct a decision matrix and normalize the index values;

[0350] Different indicators have different dimensions and cannot be directly compared. It is necessary to normalize the original indicators and construct the decision matrix H:

[0351]

[0352] Among them, h ij For alternative option p i Relative to the evaluation index q j The normalized measure of .

[0353] 4.2.2 Determining positive and negative ideal solutions

[0354] In order to increase the comparability of the results, the constructed decision matrix H is standardized. i It is represented by a benefit index and a cost index. The larger the value of the benefit index, the better the solution. When the benefit formula is used, the smaller the value of the cost index, the better the solution. According to the principle, the final alternative solution p is determined. i The positive ideal solution of and negative ideal solution function:

[0355]

[0356]

[0357] in,

[0358] 4.2.3 Calculation of group benefit index S i and individual regret indicators Y i ;

[0359] The group benefit index S i , and its calculation formula is as follows:

[0360]

[0361] Among them, w j The attribute q representing the output of the AHP j The weight of h ij For alternative option p i Relative to the evaluation index q j Normalized measure of ;

[0362]

[0363] The individual regret indicator Y i , and its calculation formula is as follows:

[0364]

[0365] Among them, w j The attribute q representing the output of the AHP j The weight of h ij For alternative option p i Relative to the evaluation index q j Normalized measure of ;

[0366] 4.2.4 Decision Index R i calculate;

[0367] Considering the different impacts of different indicators on alternatives, the calculated weights are introduced into the VIKOR comprehensive evaluation calculation, and the alternative p is calculated using the following formula: i The compromise decision index R i :

[0368]

[0369] in, Set μ = 0.5, where μ represents the relative importance between group utility and individual regret;

[0370] Calculation of group benefit index S of 16 alternatives based on VIKOR method i , individual regret indicator Y i , decision index R i Value, the results are shown in Table 42;

[0371] Table 42 Group benefit index S of the evaluation scheme i , individual regret index Y i , decision index R i value

[0372]

[0373]

[0374] Step 4.3: Comprehensive evaluation criteria for the suitability of urban subway freight system development:

[0375] The decision index R based on the suitability of the urban subway freight system development i , optimize the selection and sorting of the suitability of urban subway freight system development, and the decision index R i The order of size is the order of suitability of the alternatives;

[0376] Using the decision index R in the VIKOR method i The result of ranking the index is that the order of alternative options is: A is the city most suitable for developing an urban subway freight system, followed by B, and then D, E, G, C, H, I, N, F, L, K, P, J, M, and O.

[0377] Step 5: Application example of suitability assessment method for subway freight system development;

[0378] In the step five, 16 cities are selected as options, and the comprehensive score results of the indicators are calculated based on the developed evaluation model. According to the evaluation criteria, the suitability of urban subway freight system development is determined, and the cities are divided into echelons, providing an application example for the developed subway freight system development suitability evaluation method.

[0379] The comprehensive scoring formula for the indicators of suitability for the development of the urban subway freight system is:

[0380]

[0381] Among them, R j is the comprehensive calculation value of the jth alternative; w j It is the indicator q output by the hierarchical analysis method j The weight of h ij is the alternative p i Relative to the evaluation index q j The normalized index value of

[0382] Calculate the comprehensive scores of the indicators for the suitability of the development of subway freight systems in the 16 cities, see Figure 5 ;

[0383] According to the evaluation criteria, the suitability echelons for the development of urban subway freight systems are divided. The comprehensive evaluation criteria for the suitability of the development of urban subway freight systems for the alternative options in this embodiment are shown in Table 5.

[0384] Table 5 Comprehensive evaluation criteria for the development suitability of urban subway freight systems

[0385]

[0386] Based on the comprehensive scores and scoring criteria of the indicators for the suitability of urban subway freight system development, a comprehensive evaluation was conducted on the suitability of subway freight system development in 16 cities. The results of the city echelon division are as follows:

[0387] (1) A and B are first-tier cities;

[0388] (2) D, E, G, C, and H belong to the second-tier cities;

[0389] (3) I, N, and F belong to the third-tier cities;

[0390] (4) L, K, P, J, M, and O belong to the fourth-tier cities.

[0391] According to the comprehensive evaluation value and referring to the evaluation criteria, it can be concluded that the development suitability of cities A and B selected in the embodiment is relatively high, and the suitability of 14 cities D, E, G, C, H, I, N, F, L, K, P, J, M, and O decreases in sequence; in the present invention, according to the calculation results of each indicator, corresponding optimization reference suggestions can be found, for example, promoting smart blocks, intelligent transportation systems (ITS) and digital economy, improving the suitability of subway freight system project development through the development of intelligent facilities and intelligent technologies, and through policy incentives, subway expansion and industrial upgrading.

[0392] The present invention is not limited to the embodiments described above. The above description of the specific embodiments is intended to describe and illustrate the technical solution of the present invention. The above specific embodiments are merely illustrative and not restrictive. It should be pointed out that without departing from the scope of the present invention and the scope of protection of the claims, a person of ordinary skill in the art may make several improvements and specific changes under the guidance of the present invention, which are all within the scope of protection of the present invention.

Claims

1. A method for evaluating the suitability of urban subway freight system development, characterized in that: The following steps are involved: Step (1): Establish a framework for analyzing the suitability of urban subway freight system development; Step (2): Development of suitability evaluation indicators and quantitative calculation of urban subway freight system; Step (3): Multi-source data collection; Step (4): Establishment of indicator processing and evaluation criteria.

2. The method according to claim 1, characterized in that Step (1) comprises the following steps: Step (11): Based on the SWOT method, a suitability analysis framework for the development of the urban subway freight system is constructed, the main strengths, weaknesses, opportunities and challenges of the implementation of the urban subway freight system project are identified, and a SWOT matrix is ​​formulated; Step (12): Using the questionnaire survey method, the importance scores of the above indicators are obtained based on the experts' evaluation of the SWOT analysis indicators, and new evaluation indicators are proposed; Step (13): Determine the selection of indicators for the evaluation of the suitability of urban subway freight system development based on the SWOT analysis framework.

3. The method according to claim 1, characterized in that Step (2) The evaluation indicators for the development suitability of urban subway freight systems include benefit-based indicators and cost-based indicators; The specific benefit indicators include network capacity C1, infrastructure C2, demand scale C3, consumption and market C4, environmental benefits C5, urban economy C6, and 10 、The urgency of truck restrictions 11 , combined with the calculation formula of each indicator, the calculated value of each evaluation indicator is obtained based on the data obtained by multi-source data collection; The cost-based indicators specifically include: proximity to urban logistics hubs C6, proximity to customers C7, transportation-oriented development C8, and implementation costs C9. The calculated values ​​of each evaluation indicator are obtained by combining the calculation formulas of each indicator and based on the data obtained through multi-source data collection.

4. The method according to claim 3, characterized in that The quantitative calculation method of benefit-based evaluation indicators is as follows: Calculate the network capacity C1, which is used to reflect the freight capacity of the urban rail transit network. The calculation formula is as follows: where 11 ∈(0,1),λ 12 ∈(0,1),λ 11 +λ 12 =1 Among them, C1 is the network capacity indicator; SA Fmodule is the total area of ​​passenger and freight shared stations in the urban rail transit network; Ucap FPS is the capacity per unit area of ​​installed modules; is the number of passenger trains associated with each relevant route i; is the maximum possible number of freight train services; Ucap EC is the cargo capacity of the additional compartment; Ucap DT is the vehicle load of a dedicated freight train; 11 and λ 12 are the weights corresponding to the two items respectively. The basic data for calculating the maximum possible number of freight train services comes from the timetable information of each subway line obtained from the website of the subway operator of each city. The calculation formula is as follows: in, is the end time of passenger service; is the time when the last dedicated freight train service starts; MT i is the time before the start of the last dedicated freight train service on the next day; the constant δ is the departure frequency of dedicated freight trains; the operation of dedicated freight trains is subject to HT([Δt]). It is assumed that at most one dedicated freight train service can be added between two adjacent passenger services; HT i (j, j+1) represents the interval between passenger trains j and j+1; i∈Ω represents the set of lines in the urban rail transit network, and j∈M represents the set of passenger train services; Infrastructure C2, this indicator is used to reflect the richness of dedicated railway facilities. The calculation formula is as follows: C2=N station ×N transfer ×URTL Among them, C2 is the infrastructure indicator; N station is the number of urban rail transit stations; N transfer is the number of urban rail transit transfer stations; URTL is the length of the urban rail transit network; Demand scale C3, this indicator is used to reflect the demand scale of urban freight, and the calculation formula is as follows: C3=N EP ×N SMRS Among them, C3 is the demand scale indicator, N EP is the number of e-commerce packages delivered in the city each year, N SMRS is the total number of shopping malls and retail stores in the city; Consumption and Market C4, this indicator is used to reflect the market size and operating conditions of the urban logistics industry. The calculation formula is as follows: C4=λ 41 ×LBI+λ 42 ×RSG,λ 41 ∈(0,1),λ 42 ∈(0,1),λ 41 +λ 42 =1 Among them, C4 is the consumption and market index, LBI is the annual operating income of the urban logistics market, reflecting the market size and operating conditions of the urban logistics industry; RSG is the annual retail sales of social commodities, reflecting the purchasing power of citizens and the prosperity of the urban economy; λ 41 is the relative weight value of LBI, λ 42 is the relative weight value of RSG; Environmental benefit C5, this indicator is used to reflect the environmental benefit of the subway freight system. The calculation formula is as follows: Among them, C5 is the environmental benefit index of the subway freight system; is the number of passenger trains associated with each relevant route i; is the maximum possible number of freight train services; Ucap EC is the cargo capacity of the additional compartment; Ucap DT It is the car load of a dedicated freight train; is the average daily driving distance of a single truck; REV is the utilization rate of electric vehicles in urban logistics activities; Ucap truck is the average daily cargo volume transported by each truck; α CO is the cost of treating carbon monoxide (CO) produced per kilometer of truck travel; is the cost of handling carbon dioxide (CO2) produced per kilometer of truck travel; α NOX is the nitrogen oxides (NO X ) processing cost; α PM is the cost of treating particulate matter (PM) generated per kilometer of truck travel; α noise is the cost of handling the noise generated per kilometer of truck travel; Urban Economy C 10 , this indicator is used to reflect the economic basis required for the implementation of the subway freight system. The calculation formula is as follows: C 10 =GDP / POP×(λ 101 ×FGBR+λ 102 ×TIFA),λ 101 ∈(0,1),λ 102 ∈(0,1),λ 101 +λ 102 =1 Among them, C 10 is the city economic indicator; GDP is the gross domestic product; POP is the population; FGBR is the general budget revenue; TIFA is the total fixed asset investment; λ 101 is the relative weight value of the general budget revenue; 102 is the relative weight value of the total fixed asset investment; The urgency of truck restrictions 11 , this indicator is used to reflect the contribution of the subway freight system to urban freight mobility. The calculation formula is as follows: C 11 =BanT×BanA×N truck Among them, C 11 is the urgency indicator of the truck restriction, BanT is the daily truck ban period; BanA is the area of ​​the truck ban zone; N truck is the number of trucks affected.

5. The method according to claim 4, characterized in that The quantitative calculation method of cost-based evaluation indicators is as follows: The upstream logistics hub proximity C6 is used to reflect the spatial proximity between the upstream logistics hub and the subway freight network. The calculation formula is as follows: Among them, C6 is the proximity index of urban logistics hubs, ‖S‖ is the number of ULHs, |z s -z k | is the Euclidean distance between the upstream logistics hub and the urban rail transit station; upstream logistics hub s∈S; urban rail transit station k∈K; K is the set of all stations; rule: if the first nearest station belongs to line i, then K′ is defined as the set of stations excluding all stations on line i; if the second nearest station belongs to line j, then K″ is defined as the set of stations excluding all stations on lines i and j; Proximity to customers C7, this indicator is used to reflect the proximity between the urban rail transit network and the final destination of urban delivery. The calculation formula is as follows: Where C7 is the proximity index of the urban rail transit network to customers; UR(ε) is the total area of ​​urban areas with a population density exceeding ε; F(ε) is the number of urban rail transit stations in the UR(ε) area; |z q -z k | is the Euclidean distance between a registered postal service site q and its nearest station; Transportation-oriented development C8, this indicator is used to reflect the standard for evaluating the suitability of the subway freight system. The calculation formula is as follows: Among them, C8 is a public transportation-oriented development index, and TOD is a city's public transportation-oriented development index. is the conversion factor; Implementation cost C9, this indicator is used to reflect the economic feasibility of the subway freight system, and the calculation formula is as follows: Among them, C9 is the implementation cost indicator, ConsC is the construction cost per kilometer of the urban rail transit line that has been in operation recently; OperC is the annual operating cost of urban rail transit; URTL is the length of the urban rail transit network; λ 91 is the relative weight value of the construction cost per kilometer of the recently operated urban rail transit line; 92 It is the relative weight value of the annual operating cost of urban rail transit averaged by network length.

6. The method according to claim 5, characterized in that Step (3) specifically includes the following steps: Step (31): Obtaining relevant data of the urban subway freight system; Data related to urban subway freight systems include railway length, number of lines, trains and services, average daily passenger flow, number of urban rail transit stations, and station ; The number of urban rail transit transfer stations N transfer , urban rail transit annual operating cost OperC, total number of trains, daily services, TOD index data; Step (32): Obtaining data related to urban transportation and logistics; Data related to urban transportation and logistics include the number of e-commerce packages delivered in the city each year N EP , the number of trucks affected N truck , Number of registered postal service sites N RPS , the total number of shopping malls and retail stores in the city N SMRS , the daily truck travel ban period BanT, the area of ​​the truck ban zone BanA, and the average daily driving distance of a single truck Annual operating income of urban logistics market LBI; Calculate the demand scale C3 indicator and the urgency of truck restrictions C based on the acquired data 11 Indicator, environmental benefit C5, upstream logistics hub proximity C6, proximity to customers C7, urban economy C 10 And the attribute values ​​of consumption and market C4 indicators.

7. The method according to claim 1, characterized in that Step (4) specifically includes the following steps: Step (41): Calculate the weight of each evaluation index using hierarchical analysis; Step (411): construct a pairwise comparison matrix using the 1-9 scaling method; Step (412): solving the pairwise comparison matrix; Step (413): consistency check; Step (42): using the VIKOR method to comprehensively evaluate and determine the suitability level of urban subway freight system development; Step (421): construct a decision matrix and perform index value normalization processing; Step (422): Determine a positive ideal solution and a negative ideal solution; Step (423): Calculate the group benefit index S i and individual regret indicators Y i ; Step (424): Decision Index R i calculate; Step (43): Comprehensive evaluation criteria for the suitability of urban subway freight system development: Based on the comprehensive score of indicators and decision index R of the development suitability of urban subway freight system through AHP-VIKOR i , evaluate the suitability of urban subway freight system development, comprehensive score of indicators and decision index R i The order of size is the order of suitability of the alternative options.

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