Online calculation method for traffic flow carbon emission in operation and maintenance period of highway with cooperative vehicle and road

Abstract

The invention discloses a vehicle-road cooperation highway operation and maintenance period traffic flow carbon emission online calculation method, and relates to the technical field of carbon emission monitoring, and the method comprises the following steps: 1, collecting the data information of vehicles in an operation and maintenance period; step 2, integrating and transmitting the data information; 3, processing and analyzing the data information; 4, constructing a carbon emission model to budget carbon emission; 5, formulating and executing an optimization strategy of carbon emission reduction; sixthly, abnormal early warning and response are conducted on abnormal carbon emission; according to the method, comprehensive data collection is realized, people flow monitoring data of a service area and data of a charging system can be acquired, a reliable data basis is provided for subsequent analysis and calculation, and meanwhile, data information is integrated and transmitted, so that the data collection efficiency is improved. The acquired data information can be uploaded to the intelligent operation and maintenance platform through the vehicle-road cooperation network, and the timeliness and accuracy of the data are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of carbon emission monitoring, and specifically to an online calculation method for carbon emissions from traffic flow during the operation and maintenance period of a highway using vehicle-road collaboration. Background Art

[0002] The construction of a highway carbon emission evaluation system has not yet been fully systematized and standardized. There are still certain research gaps and deficiencies both at home and abroad. Research and practice related to carbon emission accounting for transportation infrastructure at home and abroad mainly focus on the whole life cycle theory, accounting methods and models. Research on carbon emission measurement methods in the construction and industrial fields has gradually matured, but carbon emission accounting for transportation infrastructure is still in its infancy. Compared with fixed source emissions from industry and construction, the complexity of the transportation system and the characteristics of its mobile carbon sources increase the difficulty of measuring carbon emissions. The overall error can be reduced by using a combination strategy to comprehensively use multiple transportation carbon emission measurement methods. Carbon emission measurement methods that are consistent with the characteristics of my country's transportation infrastructure construction, operation and maintenance activities and engineering practices are still relatively weak, and a complete carbon emission accounting method system has not yet been formed.

[0003] At present, a large number of studies on highway life cycle carbon emissions at home and abroad focus on highway construction materials, such as asphalt, cement, and concrete. Since traditional methods can only monitor carbon emissions from static construction materials on highways, it is impossible to effectively integrate and obtain vehicle information, road information, and environmental information on the highway, and it is difficult to obtain dynamically changing carbon emission influencing factors, which limits the monitoring of carbon emissions, resulting in incomplete and inaccurate monitoring results, and unable to timely detect and respond to abnormal emissions, which can easily lead to carbon emissions being out of control when carbon emissions are abnormal. Summary of the Invention

[0004] The present invention provides a vehicle-road collaborative online calculation method for traffic flow carbon emissions during the operation and maintenance period of a highway, which can effectively solve the problem proposed in the above background technology that the traditional method can only monitor the carbon emissions of static construction materials on the highway, resulting in the inability to effectively integrate and obtain vehicle information, road information and environmental information on the highway, and it is difficult to obtain dynamically changing carbon emission influencing factors, thereby limiting the monitoring of carbon emissions, causing the monitoring results to be incomplete and inaccurate, and unable to timely detect and respond to abnormal emissions, which can easily lead to the problem of carbon emissions being out of control when carbon emissions are abnormal.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a vehicle-road collaborative online calculation method for carbon emissions from traffic flow during the operation and maintenance period of a highway. The calculation scope of carbon emissions during the operation and maintenance period of the highway includes carbon emissions from highway traffic and maintenance, operation and maintenance of highway ancillary equipment, green projects, and sustainable energy during operation, and includes the following steps:

[0006] Step 1: Collect data information of vehicles during operation and maintenance period;

[0007] Step 2: Integrate and transmit data information;

[0008] Step three, process and analyze the data information;

[0009] Step 4: Build a carbon emission model to budget carbon emissions;

[0010] Step 5: Develop and implement an optimized strategy for carbon emission reduction;

[0011] Step 6: Conduct abnormal warning and response to abnormal carbon emissions;

[0012] Step seven: Visualize the monitoring results.

[0013] According to the above technical solution, in step 1, high-precision sensors, monitoring equipment, and on-board communication equipment deployed on vehicles and roads are used to collect information on the speed, model, weight, and age of the vehicle. At the same time, the on-board communication equipment is used to obtain real-time status data and driving behavior data of the vehicle. The driving behavior data includes the number of sudden accelerations, sudden brakings, sudden lane changes, and average following distance.

[0014] In addition, when collecting data information, it also includes deploying relevant monitoring equipment in the service area to monitor the flow of people in the service area to understand the parking and transfer of vehicles. At the same time, it is also necessary to connect data with the toll collection system at the highway exit to collect data on the number of vehicles, vehicle type, and mileage, and strengthen the comprehensive grasp of traffic data information.

[0015] According to the above technical solution, in step 2, data information is uploaded to the data center of the intelligent company's operation and maintenance platform through the vehicle-road cooperative network, so as to obtain real-time information on the environmental conditions and infrastructure status of the highway and monitor the carbon dioxide emissions of vehicles passing through in real time;

[0016] Combined with geographic information system technology, the collected data information is associated with the geographic information of the highway and the location information of the service area, the traffic flow and carbon emissions in different geographical areas are analyzed, the key areas of carbon emissions are divided, and the detailed monitoring of traffic flows in different geographical areas is achieved.

[0017] According to the above technical solution, in step three, during data information processing and analysis, the data center receives the uploaded data and preprocesses it to ensure data quality. Specific preprocessing methods include data cleaning, data normalization, data denoising, and abnormal data detection.

[0018] Through vehicle-road collaborative technology, vehicle data can be seamlessly connected with data from road sensors and monitoring equipment, forming a real-time traffic data stream covering the entire road network.

[0019] According to the above technical solution, in step 4, after processing the collected vehicle data and environmental data with the help of artificial intelligence technology and machine learning algorithms, the vehicle traffic flow is modeled and simulated to realize the construction of the carbon emission calculation model during the operation and maintenance period;

[0020] Based on real-time traffic flow and driving speed analysis, the carbon emissions of vehicles under different traffic flows are predicted, enabling the model to accurately estimate the carbon emissions of vehicles based on vehicle type and driving speed, and compare and analyze with historical carbon emission data information to predict carbon emission levels under different traffic flows, and analyze the links that can reduce carbon emissions during operation and maintenance.

[0021] The calculation of carbon emissions can be broken down into the following parts:

[0022] Traffic phase: Carbon emissions are calculated based on vehicle mileage and vehicle type, and according to vehicle exhaust emission characteristics;

[0023] Maintenance phase: Count the energy and materials consumed during vehicle repair and maintenance, and estimate the carbon emissions generated by combining the equipment's own energy efficiency ratio;

[0024] Green projects: Evaluate the actual effectiveness of various energy conservation and emission reduction measures, including the carbon absorption capacity of green vegetation;

[0025] Sustainable energy: Evaluate the carbon reduction effect of renewable energy during operation and maintenance, such as solar energy and wind energy.

[0026] According to the above technical solution, in step 4, the carbon emissions of vehicles in each time period are calculated using the constructed operation and maintenance period carbon emission calculation model. The carbon emission factors for the highway operation and maintenance period are calculated by collecting measured data from various types of highways and various carbon emission factor data to calculate the carbon emission factors required for each operation stage. The measured data includes traffic volume, vehicle type, and vehicle speed. The carbon emissions of traffic vehicles are calculated mainly based on fuel consumption and carbon emission factors, and are specifically calculated using the following formula:

[0027] Carbon emissions = fuel consumption × carbon emission factor;

[0028] Among them, fuel consumption is obtained by measuring the fuel consumption of the vehicle during driving, while the carbon emission factor depends on the type of fuel. Different types of fuel have different carbon emission factors.

[0029] According to the above technical solution, in step five, based on the current data model and actual operation and maintenance conditions, artificial intelligence technology is used to simulate and predict traffic flow, identify key traffic congestion nodes and high-carbon emission sections, and estimate the total carbon emissions of traffic flow;

[0030] At the same time, identify situations that may lead to increased carbon emissions during the operation and maintenance process. Based on the actual operation and maintenance situation, specific improvement measures are arranged during maintenance and repair to reduce the additional carbon emissions caused by this and achieve energy conservation and emission reduction;

[0031] Specific measures include adjusting lane allocation, optimizing traffic light control, and adjusting speed limit signs to reduce carbon emissions caused by congestion.

[0032] According to the above technical solution, in step 6, abnormal carbon emissions are monitored and, upon discovery of abnormal emissions, an alarm is automatically generated for situations exceeding the normal emission range, thereby attracting the attention of management personnel and prompting them to take swift countermeasures. This provides a real-time abnormal warning mechanism, allowing timely measures to be taken to reduce carbon emissions.

[0033] Abnormal emissions include abnormal emissions caused by vehicle failures and abnormal carbon emissions caused by extreme weather conditions.

[0034] According to the above technical solution, in step 6, when issuing an early warning for abnormal carbon emissions, it is also necessary to set a carbon emission early warning threshold. When the carbon emissions on a single road section exceed the early warning threshold, an early warning is automatically triggered and pushed to the operation and maintenance platform. A multi-level early warning mechanism is established based on the early warning threshold, and early warning levels are divided into level one, level two, and level three, as follows:

[0035] When the carbon emission values ​​of three consecutive road sections are greater than or equal to the warning threshold by 20%, a Level 1 warning will be issued, and the road section flow restriction measures will be automatically triggered. The warning information will be pushed to the operation and maintenance platform, notifying on-site management personnel to conduct an investigation;

[0036] When the carbon emission values ​​of three consecutive road sections are greater than the warning threshold by 10% and less than the warning threshold by 20%, a Level 2 warning is issued and drones are activated for inspection.

[0037] When the carbon emission values ​​of three consecutive road sections are less than or equal to the warning threshold, a level 3 warning will be issued and key monitoring will be carried out through on-site monitoring equipment.

[0038] According to the above technical solution, in step seven, a customizable data visualization tool is provided to display carbon emission data, traffic flow, and maintenance progress information, helping maintenance personnel and managers to conduct in-depth analysis in order to formulate energy conservation and emission reduction strategies;

[0039] In addition, the carbon emission monitoring and prediction results can be intuitively displayed to operation and maintenance personnel in the form of charts, providing relevant decision-making support information so that operation and maintenance strategies can be adjusted in a timely manner to ensure that carbon emissions remain within the predetermined target range.

[0040] Compared with the prior art, the present invention has the following beneficial effects:

[0041] 1. By collecting data from vehicles during the operation and maintenance period, comprehensive data collection is achieved, including real-time speed, vehicle model, weight, age, mileage, and driving behavior. It can also acquire data from service area crowd monitoring and toll collection systems, providing rich monitoring data and a reliable data foundation for subsequent analysis and calculation. At the same time, by integrating and transmitting data information, the collected data can be uploaded to the intelligent operation and maintenance platform via the vehicle-road cooperative network, obtaining real-time environmental and infrastructure information, improving the timeliness and accuracy of the data.

[0042] By processing and analyzing data information, we have achieved data cleaning, normalization and denoising preprocessing methods. By preprocessing the data, we have ensured the quality of the data, guaranteed the accuracy of subsequent analysis and calculation, and improved the efficiency of data utilization.

[0043] 2. By building a carbon emission model to budget carbon emissions, it is convenient to build a carbon emission calculation model for the operation period based on the collected and processed data information, realize the prediction of carbon emissions under different traffic flows, and facilitate accurate estimation of vehicle carbon emissions to provide subsequent optimization strategies. Based on the results of model prediction and actual operation and maintenance conditions, it is convenient to formulate optimization strategies to reduce carbon emissions. By adjusting lane allocation and optimizing traffic light control to reduce congestion, carbon emissions can be effectively reduced.

[0044] 3. By carrying out abnormal early warning and response to abnormal carbon emissions, real-time monitoring and setting of early warning thresholds are achieved. In addition, alarms are automatically generated by identifying abnormal emissions. With the help of a multi-level early warning mechanism, multi-level responses are conveniently carried out according to different levels of early warning levels, so as to formulate different solutions, which can achieve rapid response to emergencies, reduce carbon emissions, and ensure operational safety. By providing customized data visualization tools, it is convenient to display carbon emission data, traffic flow and maintenance progress, helping managers and maintenance personnel to conduct in-depth analysis and make decisions, and ensure the effective implementation of operation and maintenance strategies. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention.

[0046] In the attached figure:

[0047] Figure 1 It is a flow chart of the steps of the online calculation method of the present invention. DETAILED DESCRIPTION

[0048] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0049] Example: Figure 1 As shown, the present invention provides a technical solution, a vehicle-road collaborative online calculation method for carbon emissions from traffic flow during the operation and maintenance period of a highway. The scope of carbon emissions calculation for the operation and maintenance period of the highway includes carbon emissions from highway traffic and maintenance, operation and maintenance of highway ancillary equipment, green projects, and sustainable energy during operation, including the following steps:

[0050] Step 1: Collect data information of vehicles during operation and maintenance period;

[0051] Step 2: Integrate and transmit data information;

[0052] Step three, process and analyze the data information;

[0053] Step 4: Build a carbon emission model to budget carbon emissions;

[0054] Step 5: Develop and implement an optimized strategy for carbon emission reduction;

[0055] Step 6: Conduct abnormal warning and response to abnormal carbon emissions;

[0056] Step seven: Visualize the monitoring results.

[0057] Based on the above technical solution, in step one, high-precision sensors, monitoring equipment, and onboard communication equipment deployed on vehicles and roads are used to collect information on vehicle speed, model, weight, and age. In addition, the onboard communication equipment is used to obtain real-time vehicle status data and driving behavior data. Driving behavior data includes the number of sudden accelerations, sudden braking, sudden lane changes, and average following distance.

[0058] In addition, when collecting data information, it also includes deploying relevant monitoring equipment in the service area to monitor the flow of people in the service area to understand the parking and transfer of vehicles. At the same time, it is also necessary to connect data with the toll collection system at the highway exit to collect data on the number of vehicles, vehicle type, and mileage, and strengthen the comprehensive grasp of traffic data information.

[0059] Based on the above technical solution, in step 2, data information is uploaded to the data center of the intelligent company's operation and maintenance platform through the vehicle-road cooperative network, so as to obtain real-time information on the environmental conditions and infrastructure status of the highway and monitor the carbon dioxide emissions of vehicles passing through in real time;

[0060] Combined with geographic information system technology, the collected data information is associated with the geographic information of the highway and the location information of the service area, the traffic flow and carbon emissions in different geographical areas are analyzed, the key areas of carbon emissions are divided, and the detailed monitoring of traffic flows in different geographical areas is achieved.

[0061] Based on the above technical solution, in step three, during data information processing and analysis, the data center receives the uploaded data and preprocesses it to ensure data quality. Specific preprocessing methods include data cleaning, data normalization, data denoising, and abnormal data detection.

[0062] Through vehicle-road collaborative technology, vehicle data can be seamlessly connected with data from road sensors and monitoring equipment, forming a real-time traffic data stream covering the entire road network.

[0063] Based on the above technical solution, in step 4, after processing the collected vehicle and environmental data with the help of artificial intelligence technology and machine learning algorithms, the vehicle traffic flow is modeled and simulated to build a carbon emission calculation model during the operation and maintenance period;

[0064] Based on real-time traffic flow and driving speed analysis, the carbon emissions of vehicles under different traffic flows are predicted, enabling the model to accurately estimate the carbon emissions of vehicles based on vehicle type and driving speed, and compare and analyze with historical carbon emission data information to predict carbon emission levels under different traffic flows, and analyze the links that can reduce carbon emissions during operation and maintenance.

[0065] The calculation of carbon emissions can be broken down into the following parts:

[0066] Traffic phase: Carbon emissions are calculated based on vehicle mileage and vehicle type, and according to vehicle exhaust emission characteristics;

[0067] Maintenance phase: Count the energy and materials consumed during vehicle repair and maintenance, and estimate the carbon emissions generated by combining the equipment's own energy efficiency ratio;

[0068] Green projects: Evaluate the actual effectiveness of various energy conservation and emission reduction measures, including the carbon absorption capacity of green vegetation;

[0069] Sustainable energy: Evaluate the carbon reduction effect of renewable energy during operation and maintenance, such as solar energy and wind energy.

[0070] Based on the above technical solution, in step 4, the carbon emissions of vehicles in each time period are calculated using the constructed operation and maintenance period carbon emission calculation model. The carbon emission factors for the highway operation and maintenance period are calculated by collecting measured data from various highways and various carbon emission factor data to calculate the carbon emission factors required for each operation stage. The measured data includes traffic volume, vehicle type, and vehicle speed. The carbon emissions calculation for traffic vehicles is mainly based on fuel consumption and carbon emission factors, and is specifically calculated using the following formula:

[0071] Carbon emissions = fuel consumption × carbon emission factor;

[0072] Among them, fuel consumption is obtained by measuring the fuel consumption of the vehicle during driving, while the carbon emission factor depends on the type of fuel. Different types of fuel have different carbon emission factors.

[0073] The carbon emission factors of various types of highway vehicles are shown in the table below:

[0074]

[0075]

[0076] Based on the above technical solution, in step five, artificial intelligence technology is used to simulate and predict traffic flow based on the current data model and actual operation and maintenance conditions, identify key traffic congestion nodes and high-carbon emission sections, and estimate the total carbon emissions of traffic flow;

[0077] At the same time, identify situations that may lead to increased carbon emissions during the operation and maintenance process. Based on the actual operation and maintenance situation, specific improvement measures are arranged during maintenance and repair to reduce the additional carbon emissions caused by this and achieve energy conservation and emission reduction;

[0078] Specific measures include adjusting lane allocation, optimizing traffic light control, and adjusting speed limit signs to reduce carbon emissions caused by congestion.

[0079] Based on the above technical solution, in step six, abnormal carbon emissions are monitored and, when abnormal emissions are detected, alarms are automatically generated for situations that exceed the normal emission range, attracting the attention of management personnel and prompting them to take swift countermeasures. This is a real-time abnormal warning mechanism, allowing timely measures to be taken to reduce carbon emissions.

[0080] Abnormal emissions include abnormal emissions caused by vehicle failures and abnormal carbon emissions caused by extreme weather conditions.

[0081] Based on the above technical solution, in step six, when issuing warnings for abnormal carbon emissions, it is also necessary to set a carbon emission warning threshold. When the carbon emissions on a single road section exceed the warning threshold, an alert is automatically triggered and pushed to the operation and maintenance platform. A multi-level warning mechanism is established based on the warning threshold, and warning levels are divided into level one, level two, and level three, as follows:

[0082] When the carbon emission values ​​of three consecutive road sections are greater than or equal to the warning threshold by 20%, a Level 1 warning will be issued, and the road section flow restriction measures will be automatically triggered. The warning information will be pushed to the operation and maintenance platform, notifying on-site management personnel to conduct an investigation;

[0083] When the carbon emission values ​​of three consecutive road sections are greater than the warning threshold by 10% and less than the warning threshold by 20%, a Level 2 warning is issued and drones are activated for inspection.

[0084] When the carbon emission values ​​of three consecutive road sections are less than or equal to the warning threshold, a level 3 warning will be issued and key monitoring will be carried out through on-site monitoring equipment.

[0085] Based on the above technical solution, in step seven, a customizable data visualization tool is provided to display carbon emissions data, traffic flow, and maintenance progress information, helping maintenance personnel and managers conduct in-depth analysis and formulate energy conservation and emission reduction strategies;

[0086] In addition, the carbon emission monitoring and prediction results can be intuitively displayed to operation and maintenance personnel in the form of charts, providing relevant decision-making support information so that operation and maintenance strategies can be adjusted in a timely manner to ensure that carbon emissions remain within the predetermined target range.

[0087] Finally, it should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described with reference to the aforementioned embodiments, those skilled in the art will be able to modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. An online calculation method for carbon emissions from traffic flow during the operation and maintenance period of a highway using vehicle-road collaboration, characterized by: The scope of carbon emissions calculation for the operation and maintenance phase of highways includes carbon emissions from highway traffic and maintenance, operation and maintenance of highway ancillary equipment, green projects, and sustainable energy during operation, including the following steps: Step 1: Collect data information of vehicles during operation and maintenance period; Step 2: Integrate and transmit data information; Step three, process and analyze the data information; Step 4: Build a carbon emission model to budget carbon emissions; Step 5: Develop and implement an optimized strategy for carbon emission reduction; Step 6: Conduct abnormal warning and response to abnormal carbon emissions; Step seven: Visualize the monitoring results.

2. The online calculation method for carbon emissions from traffic flow during the operation and maintenance period of a highway with vehicle-road collaboration according to claim 1 is characterized by: In step 1, high-precision sensors, monitoring equipment, and on-board communication equipment deployed on vehicles and roads are used to collect information on the speed, model, weight, and age of the vehicle. The on-board communication equipment is also used to obtain real-time status data and driving behavior data of the vehicle, including the number of sudden accelerations, sudden brakings, sudden lane changes, and average following distance. In addition, when collecting data information, it also includes deploying relevant monitoring equipment in the service area to monitor the flow of people in the service area to understand the parking and transfer of vehicles. At the same time, it is also necessary to connect data with the toll collection system at the highway exit to collect data on the number of vehicles, vehicle type, and mileage.

3. The online calculation method for carbon emissions from traffic flow during the operation and maintenance period of a highway with vehicle-road collaboration according to claim 1 is characterized by: In step 2, the data information is uploaded to the data center of the intelligent company's operation and maintenance platform through the vehicle-road cooperative network, so as to obtain real-time information on the environmental conditions and infrastructure status of the highway and monitor the carbon dioxide emissions of vehicles passing through in real time; Combined with geographic information system technology, the collected data information is associated with the geographic information of the highway and the location information of the service area, the traffic flow and carbon emissions in different geographical areas are analyzed, the key areas of carbon emissions are divided, and the detailed monitoring of traffic flows in different geographical areas is achieved.

4. The online calculation method for carbon emissions from traffic flow during the operation and maintenance period of a highway with vehicle-road collaboration according to claim 1 is characterized by: In step three, during data information processing and analysis, the data center receives the uploaded data and preprocesses it to ensure data quality. Specific preprocessing methods include data cleaning, data normalization, data denoising, and abnormal data detection. Through vehicle-road collaborative technology, vehicle data can be seamlessly connected with data from road sensors and monitoring equipment, forming a real-time traffic data stream covering the entire road network.

5. The online calculation method for carbon emissions from traffic flow during the operation and maintenance period of a highway with vehicle-road collaboration according to claim 1 is characterized by: In step 4, after processing the collected vehicle and environmental data using artificial intelligence technology and machine learning algorithms, vehicle traffic flow is modeled and simulated to construct a carbon emission calculation model for the operation and maintenance period; Based on real-time traffic flow and driving speed analysis, the carbon emissions of vehicles under different traffic flows are predicted, enabling the model to accurately estimate the carbon emissions of vehicles based on vehicle type and driving speed, and compare and analyze with historical carbon emission data information to predict carbon emission levels under different traffic flows, and analyze the links that can reduce carbon emissions during operation and maintenance. The calculation of carbon emissions can be broken down into the following parts: Traffic phase: Carbon emissions are calculated based on vehicle mileage and vehicle type, and according to vehicle exhaust emission characteristics; Maintenance phase: Count the energy and materials consumed during vehicle repair and maintenance, and estimate the carbon emissions generated by combining the equipment's own energy efficiency ratio; Green projects: Evaluate the actual effectiveness of various energy conservation and emission reduction measures, including the carbon absorption capacity of green vegetation; Sustainable energy: Evaluate the carbon reduction effect of renewable energy during operation and maintenance, such as solar energy and wind energy.

6. The online calculation method for carbon emissions from traffic flow during the operation and maintenance period of a highway with vehicle-road collaboration according to claim 5 is characterized by: In step 4, the carbon emissions of vehicles during each time period are calculated using the constructed carbon emission calculation model for the operation and maintenance period. The carbon emission factors for the highway operation and maintenance period are calculated by collecting measured data from various highways and various carbon emission factor data to calculate the carbon emission factors required for each operation phase. The measured data includes traffic volume, vehicle type, and vehicle speed. The carbon emissions of traffic vehicles are calculated mainly based on fuel consumption and carbon emission factors, and are specifically calculated using the following formula: Carbon emissions = fuel consumption × carbon emission factor; Among them, fuel consumption is obtained by measuring the fuel consumption of the vehicle during driving, while the carbon emission factor depends on the type of fuel. Different types of fuel have different carbon emission factors.

7. The online calculation method for carbon emissions from traffic flow during the operation and maintenance period of a highway with vehicle-road collaboration according to claim 1 is characterized by: Step 5: Based on the current data model and actual operation and maintenance conditions, artificial intelligence technology is used to simulate and predict traffic flow, identify key traffic congestion nodes and high-carbon emission sections, and estimate the total carbon emissions of traffic flow; At the same time, identify situations that may lead to increased carbon emissions during the operation and maintenance process. Based on the actual operation and maintenance situation, specific improvement measures are arranged during maintenance and repair to reduce the additional carbon emissions caused by this and achieve energy conservation and emission reduction; Specific measures include adjusting lane allocation, optimizing traffic light control, and adjusting speed limit signs to reduce carbon emissions caused by congestion.

8. The online calculation method for carbon emissions from traffic flow during the operation and maintenance period of a highway with vehicle-road collaboration according to claim 1 is characterized by: Step 6: By monitoring abnormal carbon emissions and automatically generating an alarm when abnormal emissions are found, if the emission exceeds the normal range, it will attract the attention of management personnel and prompt them to take swift countermeasures. This will establish a real-time abnormal warning mechanism and enable timely measures to reduce carbon emissions. Abnormal emissions include abnormal emissions caused by vehicle failures and abnormal carbon emissions caused by extreme weather conditions.

9. The online calculation method for carbon emissions from traffic flow during the operation and maintenance period of a highway with vehicle-road collaboration according to claim 8 is characterized by: In step 6, when issuing an early warning for abnormal carbon emissions, a carbon emission early warning threshold must be set. When carbon emissions on a single road section exceed the early warning threshold, an early warning is automatically triggered and pushed to the operation and maintenance platform. A multi-level early warning mechanism is established based on the early warning threshold, and early warning levels are divided into level one, level two, and level three, as follows: When the carbon emission values ​​of three consecutive road sections are greater than or equal to the warning threshold by 20%, a Level 1 warning will be issued, and the road section flow restriction measures will be automatically triggered. The warning information will be pushed to the operation and maintenance platform, notifying on-site management personnel to conduct an investigation; When the carbon emission values ​​of three consecutive road sections are greater than the warning threshold by 10% and less than the warning threshold by 20%, a Level 2 warning is issued and drones are activated for inspection. When the carbon emission values ​​of three consecutive road sections are less than or equal to the warning threshold, a level 3 warning will be issued and key monitoring will be carried out through on-site monitoring equipment.

10. The online calculation method for carbon emissions from traffic flow during the operation and maintenance period of a highway with vehicle-road collaboration according to claim 1 is characterized by: Step 7 provides customizable data visualization tools to display carbon emissions data, traffic flow, and maintenance progress information, helping maintenance personnel and managers conduct in-depth analysis to develop energy conservation and emission reduction strategies; In addition, the carbon emission monitoring and prediction results can be intuitively displayed to operation and maintenance personnel in the form of charts, providing relevant decision-making support information so that operation and maintenance strategies can be adjusted in a timely manner to ensure that carbon emissions remain within the predetermined target range.

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