A traffic carbon flow network diagram drawing method based on vehicle network pile data fusion

Abstract

The application provides a traffic carbon flow network diagram drawing method based on vehicle network road pile data fusion, comprising the following steps: acquiring multi-element heterogeneous data of new energy vehicle network road piles in a traffic network; establishing a traffic carbon emission calculation model of new energy vehicle network road pile cooperation according to network segment division and vehicle classification; and calculating traffic carbon emissions in combination with the multi-element heterogeneous data of the vehicle network road piles; based on the traffic carbon emission calculation model, a traffic network carbon flow area model is established; and based on the traffic carbon emission calculation model and the traffic network carbon flow area model, a traffic carbon flow network diagram containing new energy vehicle network road pile information is drawn by using the gomphus energy distribution method. The application can solve the problems of difficult tracking and quantification of automobile carbon emissions in the traffic field, and unclear carbon peak path, and can directly show the traffic network carbon footprint tracking process, carbon flow trend and traffic network electrification level by drawing the traffic carbon flow network diagram containing new energy vehicle network road pile information by using the gomphus energy distribution method.

Description

Technical Field

[0001] This invention belongs to the field of smart power distribution network technology, and specifically proposes a method for drawing traffic carbon flow network maps based on vehicle-network-road-pile data fusion. Background Technology

[0002] Driven by climate change and the energy crisis, low-carbon development has gradually become a globally recognized goal and an important pathway to sustainable development for human society. Currently, achieving carbon peaking and carbon neutrality, as a macro-level strategic objective, faces complexities and high mobility in its implementation at the urban transportation sector, encountering challenges such as difficulty in calculating specific indicators and refining concrete measures. Promoting carbon peaking and carbon neutrality in the transportation sector is crucial for accelerating the industry's green and low-carbon transformation and driving high-quality development in transportation. However, domestic vehicle-to-grid (V2G) collaboration is constrained by factors such as electricity prices, electricity market reforms, and high initial equipment costs. To fully unleash the economic potential of V2G collaboration, relevant policies, market mechanisms, and regulatory rules still need refinement. Currently, the difficulty in tracking and quantifying vehicle carbon emissions and the unclear carbon peaking pathways in the transportation sector make it difficult to directly obtain data on transportation carbon emissions, thus affecting adjustments to carbon neutrality strategies. Summary of the Invention

[0003] To address this issue, this invention proposes a method for drawing traffic carbon flow network maps based on vehicle-network-road-pile data fusion. This method overcomes existing problems in the transportation sector, such as the difficulty in tracking and quantifying vehicle carbon emissions and the unclear carbon peaking paths, which hinder the intuitive acquisition of traffic carbon emissions and consequently affect the adjustment of carbon neutrality strategies. The technical solution adopted by this invention is as follows:

[0004] A method for drawing traffic carbon flow network maps based on vehicle-network-road-pile data fusion includes:

[0005] S1: Obtain multi-dimensional heterogeneous data of new energy vehicles, networks, and road piles in the transportation network; establish a traffic carbon emission calculation model for the coordinated operation of new energy vehicles, networks, and road piles based on network segment division and vehicle classification; and calculate traffic carbon emissions by combining the multi-dimensional heterogeneous data of vehicles, networks, and road piles.

[0006] S2: Based on the transportation carbon emission calculation model, establish a regional model of carbon flow in the transportation network;

[0007] S3: Based on the traffic carbon emission calculation model and the traffic network carbon flow regional model, a traffic carbon flow network map containing information on new energy vehicle network piles is drawn using the Sankey energy diversion method.

[0008] Optionally, the vehicle-to-grid (V2G) heterogeneous data includes vehicle speed, vehicle type, energy consumption data, road topology, driving route, and real-time power consumption data, distribution location and number of new energy charging piles within the region, as recorded by various roadside devices and on-board devices.

[0009] The traffic carbon emission calculation model for new energy vehicle network-pile coordination, established based on network segmentation and vehicle classification, includes:

[0010] The urban transportation network is divided into multiple segments. The diverse and heterogeneous data corresponding to each segment are then split into independent segment data, and a transportation network segment dataset SEG is constructed.

[0011] SEG = {s1,s2,...,s} i ,...,s n};

[0012] Where n is the total number of minimum-measurement traffic network segments, s i Each represents an independent dataset representing a different traffic network segment, i∈(1,2,...,n), and SEG represents the total dataset of the traffic network segments.

[0013] Existing common vehicles are divided into two primary vehicle categories: traditional energy vehicles and new energy vehicles. Each primary vehicle category is further subdivided to obtain secondary vehicle categories.

[0014] Using each traffic network segment as the smallest unit of measurement, calculation models for the total carbon emissions of traditional energy vehicles and new energy vehicles are established respectively.

[0015] Optionally, the calculation model for the total carbon emissions of traditional energy vehicles and new energy vehicles is established separately, using each traffic network segment as the smallest unit of measurement, including:

[0016] Using each traffic network segment as the smallest unit of measurement, the formula for calculating the energy consumption of all traditional energy vehicles under the same secondary vehicle category within a single traffic network segment is as follows:

[0017] (E i ,R)=∑ j P j ·T j ·Wt j

[0018] Among them, E i Let P be the fossil fuel energy consumption of vehicles belonging to the second-level vehicle category of traditional energy vehicles within traffic network segment i, P be the specific power of each vehicle, j represent vehicles belonging to the same second-level vehicle category within traffic network segment i, T be the duration of travel of a single vehicle within traffic network segment i, Wt be the mass of a single vehicle, and R represent different second-level vehicle categories under traditional energy motor vehicles; (E i The product of R and the carbon emissions per unit of energy is used as a calculation model for the total carbon emissions of traditional energy vehicles in traffic network segment i.

[0019] Optionally, the calculation model for the total carbon emissions of traditional energy vehicles and new energy vehicles is established separately, using each traffic network segment as the smallest unit of measurement, including:

[0020] Using each network segment as the smallest unit of measurement, establish the total carbon emissions of all new energy vehicles under the same secondary vehicle category within a single traffic network segment:

[0021]

[0022] Among them, EE i Let be the total carbon emissions of all new energy vehicles within traffic network segment i, r represent different secondary vehicle categories under new energy vehicles, j represent vehicles belonging to the same secondary vehicle category within traffic network segment i, Wt be the mass of a single vehicle, f be the resistance encountered during driving, x be the driving distance, V be the vehicle speed, η be the motor efficiency, and E be the total carbon emissions of all new energy vehicles within traffic network segment i. l k1 represents the energy loss transmitted from the power plant to the charging pile via the power grid, k2 represents the carbon emission factor per kilowatt-hour of electricity generated, and k2 represents the carbon emission factor per kilowatt-hour of electricity generated by the power grid.

[0023] Optionally, S2 includes:

[0024] Based on the aforementioned traffic network segment dataset SEG, multiple traffic network segments are used as the smallest unit of measurement and combined into four types of areas: residential area, commercial area, industrial area, and suburbs. A regional model of traffic network carbon flow is then established as follows:

[0025]

[0026] Where E represents the total carbon emissions in a certain type of region, A represents the region type, and EC i Let R represent the total carbon emissions of all conventional energy vehicles within transportation network segment i, and let EE represent the set of conventional energy vehicles. i This represents the total carbon emissions of all new energy vehicles within transportation network segment i.

[0027] Optionally, S3 includes:

[0028] Using the Sankey energy diversion method, a traffic carbon flow network map containing information on new energy vehicle network piles was drawn, and the carbon flow process in the traffic network was divided into the energy production level, the energy flow area level, and the energy consumption level.

[0029] Among them, the energy production level is the initial level, which includes three modules: total carbon emissions of diesel from traditional energy vehicles, total carbon emissions of gasoline from traditional energy vehicles, and total carbon emissions of electric vehicles from new energy vehicles. The traffic carbon emission calculation model is imported into each module of the initial level to calculate the proportion of the carbon flow branch width between each module to the total branch width.

[0030] The energy flow region level is the intermediate level, which includes four modules: residential area road network group, commercial area road network group, industrial area road network group and suburban road network group. The transportation network carbon flow regional model is imported into each module of the intermediate level, and the proportion of carbon flow branch width between each module to the total branch width is calculated.

[0031] The energy consumption level is the final level. In the Sankey diagram, the carbon flow process starts from the energy production level, passes through the energy flow region level, and finally flows to the energy consumption level.

[0032] Optionally, in the two modules of total carbon emissions from diesel fuel in traditional energy vehicles and total carbon emissions from gasoline fuel in traditional energy vehicles, the proportion of carbon flow branch width to the total branch width is the same as the proportion of carbon emissions from traditional energy consumed by traditional energy vehicles to the total carbon emissions. In the module of total carbon emissions from electric power in new energy vehicles, the proportion of carbon flow branch width to the total branch width is the same as the proportion of carbon emissions from electric power consumed by new energy vehicles to the total carbon emissions.

[0033] The beneficial effects of the technical solution provided by this invention are:

[0034] To address the challenges of tracking and quantifying vehicle carbon emissions and the lack of clear carbon peaking pathways in the transportation sector, this study gathers data on new energy vehicle networks and charging infrastructure based on electricity data. Building upon the integration of energy, transportation, and information networks, it identifies the convergence points between the power energy network and urban transportation development. By proposing a multi-dimensional heterogeneous data fusion method based on network segmentation and vehicle classification, it establishes a collaborative transportation carbon emission calculation model for new energy vehicle networks and charging infrastructure, enabling quantitative calculation of transportation network carbon emission levels. Simultaneously, it establishes regional carbon flow models for transportation networks across four typical regions to study and analyze the spatiotemporal distribution characteristics of transportation energy consumption.

[0035] By using the Sankey energy diversion method to draw a traffic carbon flow network map containing information on new energy vehicle network charging piles, it is possible to intuitively display the process of tracking the carbon footprint of the traffic network, the trend of carbon flow, and the level of electrification of the traffic network. It can take into account the balance of the power system, urban traffic management, and the consumption of new energy, thus contributing to the construction of green carbon transportation and serving the national carbon peaking and carbon neutrality strategy. Attached Figure Description

[0036] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0037] Figure 1 This is a flowchart illustrating a traffic carbon flow network map drawing method based on vehicle-network-road-pile data fusion proposed in an embodiment of the present invention. Detailed Implementation

[0038] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0039] The terms "first," "second," "third," "fourth," etc. (if present) in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein.

[0040] It should be understood that in the various embodiments of the present invention, the sequence number of each process does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0041] It should be understood that in this invention, "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such process, method, product, or device.

[0042] It should be understood that in this invention, "multiple" refers to two or more. "And / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, "and / or B" can represent: A existing alone, A and B existing simultaneously, and B existing alone. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "Contains A, B, and C", "Contains A, B, and C" means that all three A, B, and C are contained; "Contains A, B, or C" means that one of A, B, and C is contained; "Contains A, B, and / or C" means that any one, two, or three of A, B, and C are contained.

[0043] It should be understood that in this invention, "B corresponding to A", "B corresponding to A", "A and B correspond", or "B and A correspond" means that B is associated with A, and B can be determined based on A. Determining B based on A does not mean determining B solely based on A; B can also be determined based on A and / or other information. Matching A and B is defined as a similarity between A and B that is greater than or equal to a preset threshold.

[0044] Depending on the context, "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection."

[0045] The technical solution of the present invention will be described in detail below with reference to specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0046] Example:

[0047] like Figure 1 As shown in the figure, this embodiment proposes a method for drawing traffic carbon flow network maps based on vehicle-network-road-pile data fusion, including:

[0048] S1: Obtain multi-dimensional heterogeneous data of new energy vehicles, networks, and road piles in the transportation network; establish a traffic carbon emission calculation model for the coordinated operation of new energy vehicles, networks, and road piles based on network segment division and vehicle classification; and calculate traffic carbon emissions by combining the multi-dimensional heterogeneous data of vehicles, networks, and road piles.

[0049] S2: Based on the transportation carbon emission calculation model, establish a regional model of carbon flow in the transportation network;

[0050] S3: Based on the traffic carbon emission calculation model and the traffic network carbon flow regional model, a traffic carbon flow network map containing information on new energy vehicle network piles is drawn using the Sankey energy diversion method.

[0051] In this embodiment, step S1 obtains multi-dimensional heterogeneous data of the traffic network, such as real-time power consumption data of various roadside devices, vehicle-mounted devices and new energy charging piles, through the city brain central hub. By proposing a multi-dimensional heterogeneous data fusion method of vehicle-network-road-pile based on network segment division and vehicle classification, the data is cleaned and standardized, and a traffic carbon emission calculation model of new energy vehicle-network-pile collaboration is established to realize the quantitative calculation of the traffic network carbon emission level.

[0052] Step S1 contains 5 sub-steps, as follows:

[0053] S1.1 Obtain multi-dimensional heterogeneous data of new energy vehicle network charging piles through the city brain central hub. The multi-dimensional heterogeneous data of vehicle network charging piles includes vehicle speed, vehicle type, energy consumption data, road topology, driving route and real-time power consumption data of new energy charging piles, distribution location and number in the region recorded by various roadside equipment and vehicle-mounted equipment.

[0054] S1.2, the urban transportation network is divided into multiple segments, and the corresponding multi-dimensional heterogeneous data for each segment is split into independent segment data, and a transportation network segment dataset SEG is constructed.

[0055] SEG = {s1,s2,...,s} i ,...,s n}

[0056] n is the total number of the minimum-measurement traffic network segments, s i Represents independent datasets for different traffic network segments, i∈(1,2,...,n), and SEG represents the total dataset of traffic network segments.

[0057] S1.3 categorizes existing common vehicles into two primary vehicle categories: traditional energy vehicles and new energy vehicles. Each primary category is further subdivided into secondary vehicle categories. Specifically, the primary vehicle categories of traditional energy vehicles and new energy vehicles can be further divided into six secondary vehicle categories: automobiles, large trucks, buses, small trucks, electric buses, and electric private cars. These are:

[0058] R∈{cars, trucks, buses, vans}

[0059] r∈{electric buses, electric private cars}

[0060] Among them, automobiles, large trucks, buses and small trucks are classified as traditional energy motor vehicles (R), while electric buses and electric private cars are classified as new energy motor vehicles (r).

[0061] S1.4, In this step, the energy consumption and total carbon emissions of traditional energy vehicles are calculated based on information such as traffic flow, power-to-weight ratio, and driving time. Each network segment is used as the smallest calculation unit. The formula for the energy consumption of all vehicles under a certain secondary vehicle category of traditional energy vehicles within a network segment is as follows:

[0062] (E i ,R)=∑ j P j ·T j ·Wt j ;

[0063] Among them, E iThe fossil fuel energy consumption of a vehicle belonging to a certain secondary vehicle category of traditional energy vehicles within a single network segment; P is the specific power of each vehicle; j represents the number of vehicles belonging to the same secondary vehicle category within a certain network segment, with the total number being the traffic flow m; T is the duration of a single vehicle's journey within the network segment; Wt is the mass of a single vehicle; R represents different secondary vehicle types under traditional energy motor vehicles.

[0064] (E) i The product of R and the carbon emissions per unit of energy is used as a calculation model for the total carbon emissions of traditional energy vehicles in traffic network segment i.

[0065] The specific formula is as follows:

[0066]

[0067]

[0068] (E GΣ ,R)=10(E G ,R);

[0069] (E DΣ ,R)=10(E D ,R).

[0070] In this embodiment, based on the divided network segments and the calculated energy consumption, one-tenth of the network segments are taken as a sample. The total carbon emissions of all traditional energy vehicles in the sample are calculated, and the total carbon emissions are estimated based on the obtained sample. If E G E represents the total carbon dioxide emissions from the gasoline consumed by the cars in the sample. D Let the total carbon dioxide emissions from the diesel fuel consumed by the cars in the sample be:

[0071] The total carbon emissions of all gasoline-powered conventional energy vehicles of the same category within all network segments are:

[0072] (E GΣ ,R)=10(E G ,R)

[0073] The total carbon emissions of all diesel-powered conventional energy vehicles of the same category within all network segments are:

[0074] (E DΣ ,R)=10(E D ,R)

[0075] Among them, E DΣ E represents the total CO2 emissions of gasoline for the same category of vehicles across all network segments. DΣ R represents the total CO2 emissions of diesel fuel from vehicles of the same category across all network segments, where R represents different secondary vehicle types under conventional energy vehicles.

[0076] S1.5, In this step, each network segment is used as the smallest calculation unit to establish the total carbon emissions of all new energy vehicles under the same secondary vehicle category within a single traffic network segment:

[0077]

[0078] Among them, EE i Let be the total carbon emissions of all new energy vehicles within traffic network segment i, r represent different secondary vehicle categories under new energy vehicles, j represent vehicles belonging to the same secondary vehicle category within traffic network segment i, Wt be the mass of a single vehicle, f be the resistance encountered during driving, x be the driving distance, V be the vehicle speed, η be the motor efficiency, and E be the total carbon emissions of all new energy vehicles within traffic network segment i. l k1 represents the energy loss transmitted from the power plant to the charging pile via the power grid, k2 represents the carbon emission factor per kilowatt-hour of electricity production, and k2 represents the carbon emission factor per kilowatt-hour of electricity generated by the power grid.

[0079] In the calculation of k1, considering the different sources of electricity, such as solar, hydropower, wind power, coal power, and natural gas, the carbon emission factor per kilowatt-hour of electricity generated by new energy vehicles is calculated based on their different proportions.

[0080] k1=∑ z p z c z

[0081] Where z represents different sources of electrical energy, p z c represents the proportion of various electrical energy sources. z Carbon emission factors for various sources of electricity.

[0082] Therefore, the total carbon emissions of new energy vehicles across all network segments are:

[0083] (E e∑ ,r)=∑ i (EE i ,r)

[0084] Among them, E eΣ The total CO2 emissions of new energy vehicles across all network segments are represented by 'i', where 'i' represents different network segments and 'r' represents different secondary vehicle types under new energy vehicles.

[0085] In this embodiment, S2 includes:

[0086] Based on the aforementioned traffic network segment dataset SEG, multiple traffic network segments are used as the smallest unit of measurement and combined into four types of areas: residential area, commercial area, industrial area, and suburbs. A regional model of traffic network carbon flow is then established as follows:

[0087]

[0088] Where E represents the total carbon emissions in a certain type of region, A represents the region type, and EC i Let R represent the total carbon emissions of all conventional energy vehicles within transportation network segment i, and let EE represent the set of conventional energy vehicles. i This represents the total carbon emissions of all new energy vehicles within transportation network segment i.

[0089] In this embodiment, S3 includes: drawing a traffic carbon flow network map containing new energy vehicle network pile information using the Sankey energy diversion method, and dividing the carbon flow process in the traffic network into energy production level, energy flow area level, and energy consumption level;

[0090] Among them, the energy production level is the initial level, which includes three modules: total carbon emissions of diesel from traditional energy vehicles, total carbon emissions of gasoline from traditional energy vehicles, and total carbon emissions of electric vehicles from new energy vehicles. The traffic carbon emission calculation model is imported into each module of the initial level to calculate the proportion of the carbon flow branch width between each module to the total branch width.

[0091] The energy flow region level is the intermediate level, which includes four modules: residential area road network group, commercial area road network group, industrial area road network group and suburban road network group. The transportation network carbon flow regional model is imported into each module of the intermediate level, and the proportion of carbon flow branch width between each module to the total branch width is calculated.

[0092] The energy consumption level is the final level. In the Sankey diagram, the carbon flow process starts from the energy production level, passes through the energy flow region level, and finally flows to the energy consumption level.

[0093] In this embodiment, the specific drawing operation of the traffic carbon flow network diagram is as follows:

[0094] By using the Sankey energy diversion method, a traffic carbon flow network map containing information on new energy vehicle network piles was drawn, and the carbon flow process in the traffic network was divided into three levels: energy production, energy flow areas, and energy consumption.

[0095] The initial level is the energy production level, which includes three modules: total carbon emissions from diesel fuel in traditional energy vehicles, total carbon emissions from gasoline fuel in traditional energy vehicles, and total carbon emissions from electricity in new energy vehicles. In the modules of total carbon emissions from diesel fuel in traditional energy vehicles and total carbon emissions from gasoline fuel in traditional energy vehicles, the proportion of carbon flow branch width to the total branch width is the same as the proportion of carbon emissions generated by the traditional energy consumed by the vehicle to the total carbon emissions. The total carbon emissions generated by the traditional energy consumed by the vehicle are obtained in step S1.4. In the module of total carbon emissions from electricity in new energy vehicles, the proportion of carbon flow branch width to the total branch width is the same as the proportion of carbon emissions generated by the electricity consumed by the vehicle to the total carbon emissions. The total carbon emissions generated by the electricity consumed by the vehicle are obtained in step S1.5.

[0096] The intermediate level represents the energy flow area level, comprising four modules: residential road network group, commercial road network group, industrial road network group, and suburban road network group. Within each module, the proportion of carbon flow branch width to the total branch width should be the same as the proportion of carbon emissions of each area to the total carbon emissions obtained in step S2. The middle end represents the energy flow area portion, also comprising four modules: residential road network group, commercial road network group, industrial road network group, and suburban road network group. Within each module, the proportion of carbon flow branch width to the total branch width should be the same as the proportion of carbon emissions of each area to the total carbon emissions obtained in step S2.

[0097] The termination level is the energy consumption level, which includes six secondary vehicle categories: automobiles, large trucks, buses, small trucks, new energy buses, and new energy private cars. It represents the total carbon emissions of vehicles under each secondary category calculated in S1.4 and S1.5, and a loss module is set up according to the conservation of energy and matter. In each module, the proportion of carbon flow branch width to the total branch width should be the same as the proportion of carbon emissions and loss of each vehicle to the total carbon emissions.

[0098] The carbon flow process in the Sankey diagram flows from the energy production level through the energy flow through the regional level, and finally to the energy consumption level.

[0099] The serial numbers in the above embodiments are for descriptive purposes only and do not represent the order in which the components are assembled or used.

[0100] The above description is merely an embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A traffic carbon flow network mapping method based on vehicle network pile data fusion, characterized in that, The method for drawing the traffic carbon flow network map includes the following steps: S1: Obtain multi-dimensional heterogeneous data of new energy vehicles, networks, and road piles in the transportation network; establish a traffic carbon emission calculation model for the coordinated operation of new energy vehicles, networks, and road piles based on network segment division and vehicle classification; and calculate traffic carbon emissions by combining the multi-dimensional heterogeneous data of vehicles, networks, and road piles. S2: Based on the transportation carbon emission calculation model, establish a regional model of carbon flow in the transportation network; S3: Based on the traffic carbon emission calculation model and the traffic network carbon flow regional model, draw a traffic carbon flow network map containing information on new energy vehicle network piles using the Sankey energy diversion method; The traffic carbon emission calculation model for new energy vehicle network-pile coordination, established based on network segmentation and vehicle classification, includes: The urban transportation network is divided into multiple segments. The diverse and heterogeneous data corresponding to each segment are then split into independent segment data, and a transportation network segment dataset SEG is constructed. SEG = {s1, s2,..., s i , ..., s n} ; Where n is the total number of minimum-measurement traffic network segments, s i Each represents an independent dataset representing a different traffic network segment, i∈(1, 2,... , n), and SEG represents the total dataset of the traffic network segments. Existing common vehicles are divided into two primary vehicle categories: traditional energy vehicles and new energy vehicles. Each primary vehicle category is further subdivided to obtain secondary vehicle categories. Using each traffic network segment as the smallest unit of measurement, calculation models for the total carbon emissions of traditional energy vehicles and new energy vehicles are established separately. S2 includes: Based on the aforementioned traffic network segment dataset SEG, multiple traffic network segments are used as the smallest unit of measurement and combined into four types of areas: residential area, commercial area, industrial area, and suburbs. A regional model of traffic network carbon flow is then established as follows: ； Where E represents the total carbon emissions in a certain type of region, A represents the region type, and EC i Let R represent the total carbon emissions of all conventional energy vehicles within transportation network segment i, and let EE represent the set of conventional energy vehicles. i The total carbon emissions of all new energy vehicles within transportation network segment i; S3 includes: Using the Sankey energy diversion method, a traffic carbon flow network map containing information on new energy vehicle network piles was drawn, and the carbon flow process in the traffic network was divided into the energy production level, the energy flow area level, and the energy consumption level. Among them, the energy production level is the initial level, which includes three modules: total carbon emissions of diesel from traditional energy vehicles, total carbon emissions of gasoline from traditional energy vehicles, and total carbon emissions of electric vehicles from new energy vehicles. The traffic carbon emission calculation model is imported into each module of the initial level to calculate the proportion of the carbon flow branch width between each module to the total branch width. The energy flow region level is the intermediate level, which includes four modules: residential area road network group, commercial area road network group, industrial area road network group and suburban road network group. The transportation network carbon flow regional model is imported into each module of the intermediate level, and the proportion of carbon flow branch width between each module to the total branch width is calculated. The energy consumption level is the final level. In the Sankey diagram, the carbon flow process starts from the energy production level, passes through the energy flow region level, and finally flows to the energy consumption level.

2. The traffic carbon flow network mapping method based on vehicle network pile data fusion according to claim 1, characterized in that, The diverse and heterogeneous data of the vehicle-to-grid network includes vehicle speed, vehicle type, energy consumption data, road topology, driving routes, and real-time power consumption data, distribution location and number of new energy charging piles within the region, as recorded by various roadside devices and on-board devices.

3. The method for drawing a traffic carbon flow network map based on vehicle-network-road-pile data fusion according to claim 1, characterized in that, The calculation models for the total carbon emissions of traditional energy vehicles and new energy vehicles are established separately, using each traffic network segment as the smallest unit of measurement. These models include: Using each traffic network segment as the smallest unit of measurement, the formula for calculating the energy consumption of all traditional energy vehicles under the same secondary vehicle category within a single traffic network segment is as follows: ； Among them, E i Let P be the fossil fuel energy consumption of vehicles belonging to the second-level vehicle category of traditional energy vehicles within traffic network segment i, P be the specific power of each vehicle, j represent vehicles belonging to the same second-level vehicle category within traffic network segment i, T be the duration of a single vehicle's journey within traffic network segment i, Wt be the mass of a single vehicle, and R represent different second-level vehicle categories under traditional energy motor vehicles. The product of the energy unit and the carbon emission amount is taken as a calculation model of the total carbon emission amount of the traditional energy motor vehicle on the traffic network segment i. The product of the energy unit and the carbon emission amount is taken as a calculation model of the total carbon emission amount of the traditional energy motor vehicle on the traffic network segment i.

4. The traffic carbon flow network mapping method based on vehicle network pile data fusion according to claim 1, characterized in that, The calculation models for the total carbon emissions of traditional energy vehicles and new energy vehicles are established separately, using each traffic network segment as the smallest unit of measurement. These models include: Using each network segment as the smallest unit of measurement, establish the total carbon emissions of all new energy vehicles under the same secondary vehicle category within a single traffic network segment: ； Among them, EE i Let be the total carbon emissions of all new energy vehicles within traffic network segment i, r represent different secondary vehicle categories under new energy vehicles, j represent vehicles belonging to the same secondary vehicle category within traffic network segment i, Wt be the mass of a single vehicle, f be the resistance encountered during driving, x be the driving distance, V be the vehicle speed, η be the motor efficiency, and E be the total carbon emissions of all new energy vehicles within traffic network segment i. l k1 represents the energy loss transmitted from the power plant to the charging pile via the power grid, k2 represents the carbon emission factor per kilowatt-hour of electricity generated, and k2 represents the carbon emission factor per kilowatt-hour of electricity generated by the power grid.

5. The traffic carbon flow network mapping method based on vehicle network pile data fusion according to claim 1, characterized in that, In the two modules, namely the total carbon emissions of diesel fuel from conventional energy vehicles and the total carbon emissions of gasoline fuel from conventional energy vehicles, the proportion of carbon flow branch width to the total branch width is the same as the proportion of carbon emissions generated by conventional energy consumed by conventional energy vehicles to the total carbon emissions. In the module, namely the total carbon emissions of electric power from new energy vehicles, the proportion of carbon flow branch width to the total branch width is the same as the proportion of carbon emissions generated by electric power consumed by new energy vehicles to the total carbon emissions.

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