Road maintenance operation area traffic organization strategy generation method and equipment considering carbon emission cost

Abstract

The invention relates to a road maintenance operation area traffic organization strategy generation method and equipment considering carbon emission cost. The method comprises the following steps: collecting actual road data; the method comprises the following steps: constructing a road maintenance operation area model based on actual road data, performing a traffic simulation orthogonal experiment of a maintenance operation area, performing delay rule analysis based on simulation data, fusing traffic volume, cart ratio and traffic delay three-dimensional indexes, and obtaining a management and control threshold value of a closed lane in a maintenance project; taking the management and control threshold value and the minimum construction window period as constraints, generating a plurality of maintenance work area traffic organization strategies, and calculating the owner cost, the user cost and the environment cost of each scheme; and establishing an importance weight matrix based on different decision targets, obtaining the total score of the traffic organization strategy of each maintenance work area through weighted summation, and outputting the traffic organization strategy of the maintenance work area with the optimal total score. Compared with the prior art, the lane closing strategy, the speed limit value and the working area length are dynamically optimized, and the lowest comprehensive cost is achieved.

Description

Technical Field

[0001] This invention relates to the field of low-carbon traffic management, and in particular to a method and device for generating traffic organization strategies for road maintenance work areas that take into account carbon emission costs. Background Technology

[0002] With the continuous expansion of the highway network and the sustained growth of traffic flow, traffic organization in highway maintenance work areas has become crucial for ensuring traffic safety, improving traffic efficiency, and reducing environmental impact. Traditional maintenance traffic organization strategies primarily focus on traffic flow, construction safety, and engineering costs, neglecting the environmental impact of maintenance operations, especially carbon emissions. In recent years, with increased environmental awareness and the proposal of carbon neutrality goals, how to consider carbon emission costs in maintenance traffic organization and achieve low-carbon, scientific maintenance has become an urgent problem to be solved.

[0003] Existing technologies have the following shortcomings: First, traffic delay assessment has limitations. Traditional methods rely on macroscopic models and do not incorporate microscopic traffic simulation analysis of dynamic effects such as lane closures and speed limits, resulting in low accuracy in delay prediction. Second, there is insufficient quantification of carbon emissions. Existing carbon emission models do not consider changes in vehicle operating conditions in maintenance work areas (such as queuing and speed limits), and parameters rely on foreign databases, resulting in poor localization adaptability. Finally, there is a singular evaluation system for maintenance projects. Existing solutions often focus on economic or efficiency indicators, lacking a comprehensive consideration of carbon emissions, user costs, and safety, making it difficult to achieve global optimization.

[0004] Chinese patent CN112070454B discloses a design method for a highway maintenance construction area control and safety management system. This method consists of five systems: a highway maintenance construction area control and management system, a highway maintenance construction quality, progress, and safety management system, and a highway maintenance construction area completion and acceptance management system. Through area control calculation methods, the optimal safety zone for the maintenance construction area is obtained. Based on actual conditions, the reasonable length of each stage of the construction area is determined more scientifically, improving construction safety. Simultaneously, the use of RFID equipment and infrared cameras improves the safety factor of construction personnel, reduces the risk of injury or death, and reduces construction costs, bringing higher economic benefits to owners and construction units. However, this patent primarily focuses on the efficiency and safety of construction supervision and management, and comprehensively weighs carbon emissions, user costs, and safety.

[0005] In summary, there is a need to propose a method for generating traffic organization strategies for road maintenance work areas that integrates traffic simulation, dynamic carbon emission modeling, and comprehensive cost analysis. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of the existing technology and provide a method and equipment for generating traffic organization strategies for road maintenance work areas that takes into account carbon emission costs. This method can accurately measure traffic delays and carbon emissions under different traffic organization schemes, dynamically optimize lane closure strategies, speed limits and work area lengths, and achieve the lowest overall cost.

[0007] The objective of this invention can be achieved through the following technical solutions: A method for generating traffic organization strategies for road maintenance work areas that considers carbon emission costs, the method comprising: Collect actual highway data, including highway geometry design, traffic flow characteristics, and vehicle composition data; Based on the actual highway data, a highway maintenance work area model is constructed, and an orthogonal traffic simulation experiment is conducted in the maintenance work area. Based on the simulation data, the three-dimensional indicators of traffic volume, large vehicle ratio and traffic delay are integrated to analyze the delay pattern and obtain the control threshold of closed lanes in the maintenance project. Based on the control threshold and minimum construction window period of the closed lanes in the maintenance project, multiple traffic organization strategies for maintenance work areas are generated according to the highway maintenance work area model, and the owner cost, user cost and environmental cost of each scheme are calculated. An importance weighting matrix is ​​established based on different decision-making objectives. Based on this importance weighting matrix, owner costs, user costs, and environmental costs, a weighted summation is used to obtain the total score of the traffic organization strategy for each maintenance work area. The traffic organization strategy for the maintenance work area with the optimal total score is then output. The user cost includes vehicle operating cost, and the environmental cost includes additional carbon emission cost due to traffic delay. When calculating the cost, the vehicle speed-fuel consumption model is fitted by actual measurement method, and the vehicle movement on the current highway is divided into different states based on queuing theory. The vehicle speed-fuel consumption model is used to calculate the vehicle fuel consumption and carbon emission under different states, and the vehicle operating cost and additional carbon emission cost due to traffic delay are calculated based on the vehicle fuel consumption and carbon emission.

[0008] Furthermore, the actual highway data is collected through roadside video recording, ETC gantry data, drone photography, closed-circuit television monitoring technology, and floating car technology. The highway geometry design includes lane layout, road segment length, and maintenance work area planning scope; The traffic flow characteristics include macroscopic traffic flow attributes and microscopic traffic flow attributes. The macroscopic traffic flow attributes include daily traffic volume, hourly flow distribution, average speed, direction coefficient, and peak hours. The microscopic traffic flow attributes include vehicle following, lane changing, and overtaking parameters. The vehicle composition data includes the proportion of vehicle types.

[0009] Furthermore, a heatmap scoring mechanism is introduced into the orthogonal traffic simulation experiment of the maintenance work area. Traffic volume, large vehicle ratio, and traffic delay are used as scoring indicators. Based on the simulation data, a delay-safety margin curve is fitted, and the heatmap score, average road segment delay, and traffic density corresponding to the curve's sudden increase critical point are identified as the control threshold for closing lanes in the maintenance project. This ensures that the heatmap score, average road segment delay, and traffic density after the implementation of the traffic organization strategy in the maintenance work area generated subsequently are less than the control threshold. The traffic delay includes deceleration delay, queuing delay, speed limit delay, and acceleration delay, which are calculated based on the simulation data.

[0010] Furthermore, the owner's costs include road construction costs, maintenance costs, management fees, supervision fees, and design fees; the user's costs also include safety costs and delay costs; and the environmental costs also include the carbon emission costs of the entire maintenance process.

[0011] Furthermore, the safety cost is the cost incurred due to additional accidents caused by the existence of maintenance work areas, and the safety cost is calculated based on the current highway accident rate, traffic volume, and unit accident value; the delay cost is calculated based on the predicted delay duration, the preset user unit time value, and the average number of passengers per vehicle.

[0012] Furthermore, the process of constructing the vehicle speed-fuel consumption model includes: Based on the vehicle composition data, typical vehicles of each model were selected, and fuel consumption flow meters were installed on the experimental vehicles to record fuel consumption under experimental driving conditions at preset speeds and fixed lengths. The experiment was repeated and the average value was taken to obtain discrete fuel consumption data. A speed-fuel consumption curve was fitted to construct a vehicle speed-fuel consumption model.

[0013] Furthermore, in the highway maintenance work area model, the highway maintenance section is set with functional zones based on the preset work area setting regulations. The functional zones include warning zones, upstream transition zones, longitudinal buffer zones, work zones, downstream transition zones, and termination zones.

[0014] Furthermore, based on queuing theory, the process of breaking down the current vehicle motion on the highway into different states includes: Based on the traffic organization strategy of the maintenance work area and the highway maintenance work area model, a simulation experiment was conducted. The maintenance lanes in the strategy were closed and functional zones were set. The simulation output showed the remaining traffic capacity of the highway, the real-time traffic volume, vehicle trajectory data, instantaneous vehicle speed and traffic density. If the remaining capacity of each road segment is greater than the simulated real-time traffic volume, then the vehicle movement is determined to be in a non-queuing state. Otherwise, the vehicle travel intervals with instantaneous speeds less than the preset queuing speed threshold, travel positions in the upstream transition zone and longitudinal buffer zone, and traffic density greater than the preset maximum traffic density are selected from the vehicle trajectory data. These continuous intervals are merged as queuing segments, and the vehicle movement in the queuing segments is determined to be in a queuing state. The vehicle movement in the remaining road segments is determined to be in a non-queuing state.

[0015] Furthermore, the process of calculating vehicle fuel consumption and carbon emissions under different conditions includes: Simulation experiments were conducted based on the traffic organization strategy of the maintenance work area and the highway maintenance work area model to obtain the instantaneous speed, driving position, driving time and traffic density of vehicles. Based on simulation experimental data, the instantaneous speeds of all vehicles in the queuing and non-queuing sections are selected, and the arithmetic average is taken to obtain the average vehicle speed in the queuing area and the average vehicle speed in the non-queuing area. The length of the congestion is calculated by the vehicle's driving position, and the queuing length and the driving length in the non-queuing section are obtained by combining the total length of the maintenance section. The average vehicle speed in the queuing area, the queue length, the average vehicle speed in the non-queuing area, and the driving length in the non-queuing section are substituted into the vehicle speed-fuel consumption model to calculate the vehicle fuel consumption and carbon emissions under the two conditions during maintenance operations.

[0016] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the method for generating a traffic organization strategy for road maintenance work areas that takes into account carbon emission costs, as described above.

[0017] Compared with the prior art, the beneficial effects of the present invention include: 1. This invention addresses the shortcomings of traditional road maintenance methods, such as low accuracy in predicting traffic delays, insufficient quantification of carbon emissions, and a single evaluation system. Through simulation, dynamic modeling, and comprehensive evaluation of highways, it achieves refined, low-carbon, and globally optimized traffic organization in maintenance work areas. This ensures construction safety and continuity while reducing overall life-cycle costs, adapting to high-traffic scenarios such as highways and urban expressways, and providing a feasible technical solution for traffic maintenance under carbon neutrality goals. This invention integrates three-dimensional indicators—traffic volume, large vehicle ratio, and traffic delay—for delay pattern analysis, replacing traditional single-traffic-volume decision rules. This improves the accuracy of traffic delay prediction and control, dynamically responding to the time-varying characteristics of traffic flow and avoiding secondary congestion caused by conservative or overly closed strategies. In cost calculation, the invention divides vehicle groups into queuing and non-queuing states, calculating fuel consumption and carbon emissions under different states separately. This overcomes the accuracy deficiencies of traditional methods for calculating average speed across the entire road segment, accurately capturing the impact of vehicle operating conditions changes on carbon emissions in maintenance work areas. Furthermore, by constructing a vehicle speed-fuel consumption model through actual measurement, the calculation has high adaptability and is more accurate.

[0018] 2. The traffic organization strategy cost calculation in the maintenance work area of ​​this invention considers owner costs, user costs, and environmental costs, breaking through the limitations of traditional evaluation based on a single economic or efficiency indicator. It establishes a comprehensive evaluation system that integrates owner costs, user costs, and environmental costs, covering all dimensions of costs such as materials and equipment, delays, fuel consumption, accidents, and carbon emissions. It achieves a multi-objective trade-off between economy, environment, and efficiency, and the evaluation results are deeply consistent with the actual engineering needs. It not only ensures the continuity of construction but also balances various costs, making it more globally optimal than traditional decision-making. Attached Figure Description

[0019] Figure 1 This is a flowchart of the method of the present invention; Figure 2 This is a schematic diagram illustrating the vehicle delays generated by the work area according to the present invention; Figure 3 This is a flowchart of the comprehensive cost evaluation system for highway maintenance engineering of the present invention; Figure 4 This is a heatmap of traffic volume, large vehicle ratio, and traffic delay for a closed lane in this embodiment of the invention. Figure 5 This is a heatmap of traffic volume, large vehicle ratio, and traffic delay for a closed two-lane road in this embodiment of the invention. Figure 6 This is a diagram of the lane closure decision algorithm model for an 8-lane highway in an embodiment of the present invention. Figure 7 This is a flowchart of the closed period determination method of the present invention; Figure 8 This is a comparison chart of the improved method in this embodiment of the invention with the calculation results of existing research methods and the MOVES model. Detailed Implementation

[0020] 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, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0021] Example 1 A method for generating traffic organization strategies for road maintenance work areas that takes into account carbon emission costs, such as Figure 1 As shown, the method includes: Step S1: Collect actual highway data, including highway geometry design, traffic flow characteristics, and vehicle composition data.

[0022] Actual highway data is collected through roadside video recording, ETC gantry data, drone photography, closed-circuit television (CCTV) monitoring technology, and floating car methods.

[0023] Highway geometry design includes lane layout, road segment length, and the planning scope of maintenance work areas; Traffic flow characteristics include macroscopic and microscopic attributes. Macroscopic attributes include daily traffic volume, hourly flow distribution, average speed, direction coefficient, and peak hours. Microscopic attributes include vehicle following, lane changing, and overtaking parameters. Vehicle composition data includes the proportion of vehicle types.

[0024] When using image data, end-to-end image recognition algorithms can be used to count various types of vehicles and collect refined parameters such as lane layout, macro-level traffic flow attributes (flow rate, average speed), micro-level attributes (following, lane changing, overtaking parameters), and vehicle type of the engineering road section, which serve as the data foundation for the next step of maintenance work area simulation.

[0025] Step S2: Design an orthogonal simulation experiment of traffic in the maintenance work area, analyze the delay pattern based on the simulation data, and determine the control threshold of closed lanes in the maintenance project.

[0026] Step S2 specifically involves: constructing a highway maintenance work area model based on actual highway data, conducting orthogonal traffic simulation experiments in the maintenance work area, and analyzing delay patterns by integrating three-dimensional indicators of traffic volume, large vehicle ratio, and traffic delay based on simulation data, in order to obtain the control threshold for closed lanes in the maintenance project.

[0027] In the orthogonal experiment of traffic simulation in the maintenance work area, a heat map scoring mechanism is introduced, with traffic volume, large vehicle ratio, and traffic delay as scoring indicators. The evaluation criteria for traffic volume, large vehicle ratio, and traffic delay are obtained based on the statistical relationship between actual traffic volume, large vehicle ratio, traffic delay, and safety on the highway. The heat map score is obtained through a weighted algorithm. Finally, a delay-safety margin curve is fitted based on the simulation data. The heat map score, average road segment delay, and traffic density corresponding to the curve's sudden increase critical point are identified as the control threshold for closing lanes in the maintenance project. This ensures that the heat map score, average road segment delay, and traffic density after the implementation of the traffic organization strategy in the maintenance work area are less than the control threshold.

[0028] In this embodiment, based on the aforementioned actual highway data, a highway maintenance work area model with the same lane layout is constructed on the VISSIM traffic simulation software. The highway maintenance section is divided into functional zones, including a warning zone, an upstream transition zone, a longitudinal buffer zone, a work zone, a downstream transition zone, and a termination zone. This division aims to ensure the safety of the construction area and guide passing vehicles to smoothly adjust their speeds.

[0029] like Figure 2 As shown, vehicles begin to decelerate when approaching the upstream transition zone, resulting in a deceleration delay; after decelerating to a stable speed, they begin to enter the queuing state at this speed, and the queuing speed, which is lower than the initial speed, naturally causes a queuing delay; after entering the work area, they drive according to the speed limit requirements of the work area, and after reaching the downstream transition zone, they accelerate to leave the construction section.

[0030] In the simulation, based on the concept of orthogonal experimental design, multiple combinations of parameters such as traffic volume level, large vehicle ratio, number of closed lanes, speed limit, and working area length were calibrated with equal step intervals. The influencing factors of traffic volume, large vehicle ratio, speed limit, and number of closed lanes were studied respectively. Specifically, a heat map scoring mechanism was introduced, and the three-dimensional indicators of traffic volume (Q), large vehicle ratio (P), and traffic delay (D) were integrated to find the threshold point.

[0031] Highway maintenance work often involves lane closures. When a lane is closed, vehicles that were originally traveling in that lane are forced to move to other open lanes. This leads to a surge in traffic density on the open lanes, reducing road space and traffic capacity. Determining the number of lanes to close during maintenance work requires considering factors such as the highway grade, the total number of lanes, and the traffic volume of the road segment, as well as the minimum traffic flow required to cause congestion on highways of different grades and numbers of lanes.

[0032] Large vehicles, due to their size, occupy more road space, and their characteristics, such as speed, acceleration, deceleration, and lane-changing speed, differ from those of smaller vehicles. Therefore, they represent an uncertain factor affecting the operational status of the road system. When lanes are reduced due to maintenance work, the overall impact of large vehicles on road traffic flow becomes even more significant.

[0033] Traffic delays are the outward manifestation of a decrease in the capacity of highways due to a combination of factors, namely, the delay in vehicle speed caused by various reasons, resulting in a speed lower than normal. The causes of traffic delays on road sections usually include factors such as increased traffic volume, the proportion of large vehicles, a reduction in the number of lanes, a narrowing of lane width, and a decrease in the capacity of construction sections.

[0034] Traditional lane closure maintenance management relies on a single indicator, using traffic volume (e.g., 1500 veh / h per lane in a certain country or region) as the basis for decision-making, ignoring key factors such as the large vehicle ratio and speed dispersion, leading to conservative or excessive closure strategies. Such static rules cannot dynamically respond to the time-varying characteristics of traffic flow (e.g., surges in traffic during peak hours), easily causing secondary congestion. Reasonable maintenance projects should ensure both traffic efficiency and safety. Therefore, this invention introduces a multi-factor heatmap scoring mechanism based on traffic volume, large vehicle ratio, and traffic delay. This mechanism considers the service level and speed consistency of the maintained road section, fits a delay-safety margin curve based on traffic simulation data, identifies sudden surge thresholds as control thresholds, and adjusts lane closure strategies accordingly. This approach embodies the concept of refined traffic management, balancing safety and efficiency, while also allowing for temporary adjustments to closure control thresholds through manual review under special conditions (e.g., emergency maintenance), providing a degree of flexibility.

[0035] Specifically, traffic delays consist of four types: deceleration delays, queuing delays, speed limit delays, and acceleration delays. These four types of delays can be calculated using the following methods: Deceleration delay: In the formula: S d The deceleration distance (m) when the vehicle enters the work area; V f The free-flow speed (km / h) of vehicles traveling normally on the upstream non-maintenance road section. Vw The vehicle speed (km / h) within the maintenance work area; Q(t) For maintenance of the construction section t Traffic volume at any given time (veh / h); S This marks the start of maintenance work; E This marks the end of the maintenance work.

[0036] Queue delays: In the formula: q 1 j for j The number of vehicles queuing in the upstream transition zone during the time period; q 2 j for jThe number of vehicles queuing in the upstream transition zone at the end of the time period; T for j The length of the time period.

[0037] Speed ​​limit delay: In the formula: t w This represents the average travel time for vehicles to pass through the maintenance section. t e j The average travel time for vehicles to pass through a road segment when the segment is not maintained; c w To maintain the traffic capacity of the maintenance work area; Q m j for j Traffic volume on road sections requiring maintenance during specific time periods.

[0038] Accelerating delays: In the formula: a a This represents the acceleration of the vehicle as it leaves the work area, typically taken as 2.5 m / s². 2 ; q j-1 It refers to the first j-1 The number of vehicles queuing on the upstream section at the end of the time period; d j Indicates the work area number j The duration of each time interval. Setting these parameters is crucial for simulating and analyzing traffic delays in the work area.

[0039] Based on the four types of delays, a total traffic delay model for highway maintenance work areas can be established as follows: In the formula: f M This is a correction parameter for the maintenance and construction method; its value depends on the specific maintenance and construction method selected. D total The average total delay per vehicle caused by maintenance work.

[0040] Step S3: Establish a vehicle speed-fuel consumption improvement model based on the deconstruction of vehicle motion state.

[0041] The process of building the vehicle speed-fuel consumption model includes: Based on vehicle composition data, typical vehicles of each model were selected, and fuel consumption flow meters were installed on the experimental vehicles to record fuel consumption under experimental driving conditions at preset speeds and fixed lengths. The experiment was repeated and the average value was taken to obtain discrete fuel consumption data. A speed-fuel consumption curve was fitted to construct a vehicle speed-fuel consumption model.

[0042] Specifically, in this embodiment, the traffic simulation orthogonal experiment also outputs traffic simulation trajectory files, including vehicle instantaneous speed and acceleration data. Existing methods all calculate vehicle additional carbon emissions using the MOVES model. However, the vehicle emission rate and other attributes in the MOVES model are based on data from the United States, which differs from domestic data. Secondly, model evaluation is highly dependent on data and the calculations are relatively complex.

[0043] Therefore, this invention obtains basic fuel consumption models for various vehicle types on highways and national / provincial trunk roads by referencing experimental methods. Specifically, it selects typical vehicles of each type (small, medium, and large passenger and freight vehicles), installs fuel consumption flow meters on the experimental vehicles, and records fuel consumption at specific speeds and fixed distances. w The formula for calculating fuel consumption under wheel measurement is: Multiple experiments were conducted, and the average value was taken to obtain a set of discrete points representing the speed-fuel consumption relationship of this vehicle model. A fitting function was then used to... The final model is obtained.

[0044] Step S4: Construct a dynamic decision-making algorithm for lane closure and formulate a closure plan.

[0045] Step S4 specifically involves using the control threshold and minimum construction window period for closed lanes in the maintenance project as constraints, and employing a lane closure dynamic decision-making algorithm to generate multiple traffic organization strategies for maintenance work areas based on the highway maintenance work area model, which is the closure schedule.

[0046] The specific process is as follows: Based on actual highway data, the input parameters are defined as the large vehicle ratio (P) and traffic volume (Q). The control thresholds for lane closures during maintenance are obtained using steps in S2. Based on these control thresholds and the minimum construction window, a dynamic lane closure decision algorithm is used to formulate a lane closure schedule, i.e., the traffic organization strategy for the maintenance work area. The lane closure schedule meets two basic conditions: the traffic volume during the closure period is within the permissible range for lane closure; and the closure periods should be as continuous as possible and of a certain length to ensure a continuous and sufficient window for construction. The table includes specific data on closed lanes, closure times, and closure lengths.

[0047] Step S5: Establish a comprehensive cost evaluation system for highway maintenance based on pavement life cycle assessment (LCA) and life cycle cost assessment (LCCA).

[0048] Life Cycle Assessment (LCA) is a systematic analytical method for assessing the environmental impact of road surfaces, considering the entire process from raw material sourcing, production, construction, use, maintenance to disposal. This method considers multiple environmental indicators such as energy consumption, greenhouse gas emissions, air pollution, water pollution, and solid waste, aiming to promote more sustainable road construction and maintenance practices.

[0049] The calculation process of road life cycle cost assessment (LCCA) divides all costs into two categories according to the bearer: owner costs and user costs.

[0050] Therefore, step S5 is as follows: Figure 3 As shown, based on LCA and LCCA, the owner's cost, user cost, and environmental cost of each scheme are calculated, and finally all costs are unified into economic costs.

[0051] Owner costs are direct economic costs, including road construction costs, maintenance costs, management fees, supervision fees, and design fees.

[0052] User costs include vehicle operating costs, safety costs, and delay costs (additional travel time).

[0053] Environmental costs include the carbon emission costs of the entire maintenance process and the additional carbon emission costs of traffic delays.

[0054] Safety costs are the costs incurred due to additional accidents caused by the existence of maintenance work areas. Safety costs are calculated based on the current highway accident rate, traffic volume, and unit accident value. Delay costs are calculated based on predicted delay duration, preset user unit time value, and average number of passengers per vehicle.

[0055] When calculating costs, the vehicle speed-fuel consumption model is fitted by actual measurement, and the vehicle movement on the current highway is divided into queuing state and non-queuing state based on queuing theory. The vehicle fuel consumption and carbon emissions in the two states are calculated respectively, and the vehicle operating cost and additional carbon emission cost due to traffic delay are calculated based on the vehicle fuel consumption and carbon emissions.

[0056] Queuing theory is a mathematical theory that focuses on analyzing queuing phenomena caused by demand exceeding service capacity in a service system, and seeking a reasonable coordination between demand and service. This theory has been applied in many fields, particularly playing a significant role in traffic delay analysis, traffic facility design and management, and capacity assessment.

[0057] During the simulation, observing the traffic flow reveals that queuing gradually appears in the upstream transition zone as the input traffic volume increases. When the outermost lane is closed for construction, the queuing in the upstream transition zone intensifies and vehicle delays increase rapidly once the traffic volume in a single lane exceeds 800 vehicles per hour.

[0058] Based on the observed simulation phenomena, it was found that the traffic flow was relatively good in the warning zone, working zone, downstream transition zone, and termination zone. Only at the end of the warning zone and the upstream transition zone did phenomena such as stopping and queuing occur. It can be analyzed that the main factor causing queuing is the lateral conflict between the traffic flow in the closed lane and the traffic flow in the adjacent open lane. The lateral conflict before the start of the working zone is too large, and vehicles in the closed lane cannot merge into the adjacent lane in time.

[0059] The mechanism by which delays in maintenance and construction control zones generate carbon emissions can be summarized as follows: when vehicles pass through the control zone, their operating conditions change, resulting in the consumption of more fuel and the generation of more carbon emissions over the same travel distance.

[0060] From the perspective of vehicle motion, vehicle speeds are relatively stable during queuing and also relatively stable while driving within the work area. Therefore, when calculating additional carbon emissions, instead of using the average speed over the entire process as in existing studies, the motion process can be broken down into two states: queuing and non-queuing. In the queuing state, vehicle speeds are relatively stable, meaning they are traveling at the queuing speed. In the non-queuing state, because speed limits are implemented in the warning zone, vehicle speeds upstream of the queue, in the work area, and downstream transition zone are also relatively stable at levels close to the speed limit. Therefore, the average speeds of both motion states can be used for calculations, thus improving upon existing calculation methods.

[0061] The process of breaking down the current vehicle movement on the highway into queuing states and non-queuing states includes: Simulation experiments were conducted based on the traffic organization strategy of the maintenance work area and the highway maintenance work area model. The maintenance lanes in the strategy were closed and functional zones were set. The simulation output showed the remaining traffic capacity of the highway, the real-time traffic volume, vehicle trajectory data, instantaneous vehicle speed and traffic density. If the remaining capacity of each road segment is greater than the simulated real-time traffic volume, then the vehicle movement is determined to be in a non-queuing state. Otherwise, the vehicle travel intervals with instantaneous speeds less than the preset queuing speed threshold, travel positions in the upstream transition zone and longitudinal buffer zone, and traffic density greater than the preset maximum traffic density are selected from the vehicle trajectory data. These continuous intervals are merged as queuing segments, and the vehicle movement in the queuing segments is determined to be in a queuing state. The vehicle movement in the remaining road segments is determined to be in a non-queuing state.

[0062] The process of calculating vehicle fuel consumption and carbon emissions in queued and non-queued states includes: Simulation experiments were conducted based on traffic organization strategies for maintenance work areas and highway maintenance work area models to obtain vehicle instantaneous speed, driving position, driving time and traffic density. Based on simulation experimental data, the instantaneous speeds of all vehicles in the queuing and non-queuing sections are selected, and the arithmetic average is taken to obtain the average vehicle speed in the queuing area and the average vehicle speed in the non-queuing area. The length of the congestion is calculated by the vehicle's driving position, and the queuing length and the driving length in the non-queuing section are obtained by combining the total length of the maintenance section. The average vehicle speed in the queuing area, the queue length, the average vehicle speed in the non-queuing area, and the driving length in the non-queuing section are substituted into the vehicle speed-fuel consumption model to calculate the vehicle fuel consumption and carbon emissions under the two conditions during maintenance operations.

[0063] In this embodiment, the method for calculating vehicle fuel consumption and carbon emissions in queuing and non-queuing states is a novel calculation method for easily and reliably calculating the additional carbon emissions caused by vehicle delays due to maintenance work. Compared to existing methods that calculate the average speed of vehicles throughout the work area, this invention decomposes the movement of the vehicle group into two states: queuing and non-queuing. In the queuing state, the traffic flow speed is relatively stable, i.e., traveling at the queuing speed; in the non-queuing state, since speed limits are implemented in the warning zone, the vehicle speed upstream of the queue, in the work area, and in the downstream transition zone is also relatively stable at a level close to the speed limit. Therefore, the average vehicle speed in both states can be used for calculation, improving upon existing calculation methods.

[0064] Specifically, the formula for the improved calculation method is as follows: in, F 1 mi for i Fuel consumption per 100 kilometers when vehicles are in a queue; F 2 mi for i Fuel consumption per 100 kilometers for vehicle model when not in a queue; v1 The average speed of vehicles in the queuing area; v 2 The average speed of vehicles outside the queuing area; d Queue length and These are the parameters to be calibrated under this operating condition; EG For total carbon emissions from vehicles. Fuel density, in kg / L; Carbon emission factor for fuel, expressed in kg / kg; The distance traveled is measured in kilometers.

[0065] Owner costs include road construction costs, maintenance costs, management fees, supervision fees, and design fees. The specific calculation can be divided into the raw material acquisition stage, the transportation stage, and the construction stage.

[0066] The inventory analysis in the raw material acquisition stage mainly calculates the environmental impact of all pavement material production processes prior to pavement construction. This process includes not only the environmental impact of the production processes of materials such as asphalt, cement, and aggregates, but also the transportation, mixing, and processing of these materials.

[0067] The environmental impact calculation method at this stage is similar to the budgeting method, calculating the overall environmental impact by multiplying the amount of materials and equipment used by the environmental impact per unit of use; while the environmental impact per unit of use can be calculated by multiplying the energy consumption per unit of use by the environmental impact per unit of energy combustion. Taking carbon emissions as an example, if there are a total of n This type of energy and consumes the first i Materials and equipment for this type of energy include m(i) If the total carbon emissions are calculated using the following formula: In the formula: Q i For the first i The consumption of this type of energy; Q j For the first j The amount of materials or equipment used; q ij For the first j The unit consumption of a certain type of material or equipment i The amount of energy consumed. In the formula: E total Total carbon emissions; C fi For the first i Carbon emission factors of various energy sources.

[0068] The raw materials and units involved in highway maintenance construction are shown in Table 1, the equipment involved in construction and the types of energy used are shown in Table 2, and the carbon emission factors of various raw materials and end-use energy are shown in Tables 3 and 4 respectively.

[0069] Table 1 Types of raw materials for highway maintenance and construction Table 2 Types of Highway Maintenance and Construction Equipment and Energy Types Table 3 Carbon emission factors and data sources for highway maintenance and construction raw materials Table 4. Calorific value and carbon emission factor of final energy The calculation for the transportation phase is based on the carbon emissions generated by the fuel energy consumption of the transport vehicles, and is considered as a separate phase in the calculation. Detailed considerations for transport vehicles are as follows: The starting point for the calculation is the point in time and space where the transport vehicle leaves the production plant / mixing station; The vehicle type is set with reference to the "Construction Machinery Shift Cost Quota (2011)"

[104] . If the standard does not list it, the approximate vehicle parameters can be used for calculation. The vehicle's transport capacity is calculated based on the maximum loading weight, with options for full-load transport and empty return. The calculation endpoint is the time and space point when the transport vehicle returns to the production plant / mixing station empty.

[0070] The input parameters required for this stage of calculation are: ① the mass (t) of surface layer, base layer, and subbase layer materials required for 1km of road surface; ② the load capacity of the required transport vehicles; ③ transport distance and transport speed; ④ fuel consumption per shift; ⑤ fuel energy carbon emission factor.

[0071] The calculation formula is as follows, which is based on the fuel consumption of a vehicle or machine: In the formula: T p For transport vehicles p The main work shift; E p,f For transport vehicles p fuel or energy during shift work f Consumption amount; C f For fuel or energy f Carbon emission factors. In the formula:T p For transport vehicles p Total work shift; q p The total number of vehicles required for transportation (in vehicles); S m The transportation distance (km) between the material source locations such as mixing plants and production plants and the construction site; v p The speed (km / h) of the transport vehicle is determined based on its location along the transport route; M i for i The quality of the material; L p For transport vehicles p The load capacity (t).

[0072] The construction phase primarily calculates the environmental impact of processes such as road surface leveling, paving, and compaction. The method for calculating the environmental impact at this stage is similar to that at the raw material acquisition stage, calculating the overall environmental impact by multiplying the amount of materials and equipment used by the environmental impact per unit of use. Specific data can be obtained by calculating energy consumption based on the shift quotas and consumption per shift in construction specifications, or by drawing analogies to the actual conditions of similar projects.

[0073] Safety costs in user costs refer to the costs incurred due to additional accidents caused by the existence of maintenance work areas. The specific calculation method is as follows: In user costs, vehicle operating costs mainly refer to fuel costs. Fuel consumption can be calculated using formulas for fuel consumption and carbon emissions under two different conditions during maintenance work. The formula for calculating the total fuel consumption of vehicles during maintenance work is as follows: In the formula: F i for i Fuel consumption per 100 kilometers for the vehicle model; d The distance traveled by vehicles in the construction section, in km; V i for i Hourly flow rate for vehicle type, in veh / h; T The duration of construction is expressed in hours (h).

[0074] The calculation of delay time cost in user costs requires setting the value per unit of user time, and then calculating it based on the predicted traffic delay, as shown in the following formula: Step S6: Evaluation, analysis, and decision-making regarding traffic organization schemes.

[0075] Step S6 specifically involves: establishing an importance weight matrix based on different decision objectives; obtaining the total score of traffic organization strategies for each maintenance work area by weighted summation based on the importance weight matrix, owner costs, user costs, and environmental costs; and outputting the traffic organization strategy for the maintenance work area with the best total score.

[0076] In this embodiment, the total cost and various local costs of different traffic organization schemes for maintenance work areas are compared. An importance weight matrix is ​​established based on different decision objectives, the cost values ​​are standardized, and the traffic organization scheme with the lowest overall cost is selected based on the final weighted sum of the evaluation scores.

[0077] Example 2 This embodiment is based on the above embodiment 1, and takes the maintenance project to be carried out on a certain section of an east-west dual eight-lane expressway as an example to illustrate its practical application.

[0078] Over time, this lane has developed longitudinal cracks, transverse cracks, ruts, potholes, insufficient skid resistance, and localized pavement subsidence, necessitating the development of a maintenance plan to address the affected road sections. Based on a method combining CCTV monitoring technology with automatic vehicle target identification and counting, traffic flow and characteristics of the target road section were continuously monitored to obtain the hourly traffic volume distribution Q. Traffic parameters such as the large vehicle ratio P, directional coefficient, and peak hour traffic volume were calculated. The traffic volume distribution is shown in Table 5.

[0079] Table 5 Main Traffic Characteristic Parameters The simulation scenario was designed using VISSIM. Referring to the requirements of the "Highway Maintenance Safety Operation Regulations," the warning zone was set to 2000m, the upstream transition zone to 200m, the downstream transition zone to 80m, and the termination zone to 30m. The work zone length was initially set to 1km, and then changed to 2km, 3km, and 4km after completing all corresponding work conditions. Based on the traffic characteristics collected above, parameters such as conflict zone priority, vehicle type ratio, expected speed distribution, and speed control in different sections of the work zone were calibrated. When one lane was closed, the input traffic volume ranged from 1200 veh / h to 6000 veh / h, increasing by 400 veh / h for a total of 12 sets of traffic volumes. When two lanes were closed, the input traffic volume ranged from 1200 veh / h to 4000 veh / h, increasing by 400 veh / h for a total of 8 sets of traffic volumes. The coupled heatmaps of traffic volume, large vehicle ratio, and traffic delay under single-lane and two-lane closures were output respectively. Figure 4 and Figure 5As shown.

[0080] Analyzing the output microscopic vehicle trajectory and traffic flow data reveals that when the score is ≥75, the average road segment delay is ≥45 seconds / vehicle, and the traffic density is ≥22 vehicles / km, reaching the congestion warning threshold. The frequency curve of accumulated additional carbon emissions surges, indicating that traffic flow has entered a non-linear deterioration phase. Furthermore, the vehicle speed curve shows that the service level threshold drops from "stable flow" to "restricted flow," manifested as increased speed volatility and poor speed consistency, reflecting a significant increase in driving behavior instability and a higher risk of traffic accidents. Therefore, we use a score of 75 as the control threshold and formulate a dynamic lane closure strategy as shown in Table 6. For an 8-lane highway, when the traffic volume is 2800 veh / h, the lane closure strategy can be freely formulated, and closing one or two lanes in one direction will not cause significant traffic delays. When the traffic volume is between 2800 veh / h and 5200 veh / h, it is necessary to consider the large vehicle ratio to decide whether to close one or two lanes. When the traffic volume exceeds 5200 veh / h, lane closures for maintenance are not recommended. Since traffic delays in the work area under high traffic volume are highly sensitive to both traffic volume and the large vehicle ratio, this means that if the traffic volume on a road segment is already high, even a small increase in traffic volume or a slight decrease in road capacity due to unforeseen events or other reasons can lead to a surge in traffic delays and congestion. Therefore, especially for high-volume highways, it is essential to conduct refined traffic organization and management in the work area based on the traffic volume-large vehicle ratio, and the formulation of lane closure strategies should be rigorous.

[0081] Table 6 Lane Closure Strategies for 8-Lane Highways Based on Heatmap Scoring Based on the above analysis process, the decision model for the graph closure algorithm is as follows: Figure 6 As shown, the algorithm includes 8 decision-making processes and 3 output results. Input (Q, P) data generates the number of lane closures per hour. It is important to note that a minimum continuous closure time t should be set, such as t ≥ 4 hours. This rule is used to further determine the possible closure periods output by the lane closure decision model. Figure 7 As shown, all time periods that meet the minimum continuous closure duration are selected, and the selected time periods constitute the daily lane closure schedule.

[0082] Analysis shows that weekday traffic volume is lower than weekend traffic volume; therefore, a continuous weekday closure is proposed. Surveys indicate that the ratio of large vehicles to road sections on weekdays is P=0.145, and the hourly traffic volume distribution on weekdays is: Qh=(412, 235, 247, 245, 198, 513, 884, 1283, 2480, 2785, 2472, 2241, 1878, 2167, 2448, 2674, 2758, 2884, 3067, 2148, 1486, 1059, 942, 567). Input P and Qh into the lane closure decision model, and output the set of lanes that can be closed, nh = (2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2). After screening, the lane closure strategy that can be adopted is as follows: close 2 lanes from 0:00 to 8:00, close 1 lane from 8:00 to 20:00, and close 2 lanes from 20:00 to 00:00.

[0083] When analyzing a specific maintenance case, such as the maintenance of lanes 3 and 4 on the south side, the road surface milling and repaving length is 5km, with a construction period of 20 days. Based on the lane closure strategy, three traffic organization construction schemes are set up: closing 1 lane, with a work area length of 1km and a total of 10 work zones; closing 2 lanes, with a work area length of 1km and a total of 5 work zones; closing 2 lanes, with the work area divided into 2 sections of 2km each and 1 section of 1km each. The speed limit is set at 80km / h, and a comprehensive highway maintenance cost evaluation system based on LCA and LCCA can be adopted.

[0084] By calculating the owner's cost (Tables 7 and 8), user cost (Table 9), and environmental cost (Table 10), the conclusion drawn from the calculation results is that the sum of the engineering costs, user costs, and environmental costs corresponding to the total carbon emissions generated during the entire maintenance and construction period is shown in Table 11: Scheme 1 > Scheme 2 > Scheme 3.

[0085] Table 7 Scope of Maintenance Works and Owner Costs Table 8 Other Owner Costs for Maintenance Works Table 9. Cost Calculation List for Different Schemes Table 10 Carbon Emissions from Maintenance Measures and Additional Carbon Costs Due to Traffic Delays for Different Options Table 11 Cost Comparison of Three Traffic Organization Schemes While traditional direct cost comparison is intuitive and simple, it may not accurately describe the importance of each cost component (indicator) for cost types with significantly different dimensions. Therefore, this invention employs a weighted scoring method for evaluation.

[0086] Using owner costs, environmental costs, and user costs as three indicators, which are clearly inverse indicators, we proceed with the following three steps: standardization, weighting, and calculation of the total score.

[0087] ①Standardization An unweighted standardization method is used, meaning that the score of each indicator is determined by the reciprocal of the ratio of that indicator value to the maximum value among all possible solutions for that indicator. The standardization formula is as follows: In the formula: X ij For the first i The first scheme j Scoring of each indicator; K ij For the first i The first scheme j The value of each indicator; K jmax For the first j The maximum value of each indicator.

[0088] ②Indicator weighting Since there is no universally accepted view on the importance of various costs in the comprehensive evaluation, and it is a rather subjective issue, four weighting schemes are set up to represent equal importance, owner cost-oriented, environmental cost-oriented, and user cost-oriented, as shown in Table 12.

[0089] Table 12 Indicator Weighting Scheme ③ Calculate the score Table 13 shows the calculated scores of the three traffic organization schemes under different weighting schemes. A higher score indicates a better traffic organization scheme. It can be seen that under all four weighting schemes, traffic organization scheme 2 scores higher than schemes 1 and 3, making it the optimal scheme. However, a direct comparison of total costs leads to scheme 1 being the optimal scheme, indicating a discrepancy between the evaluation results of the two methods. Ultimately, the evaluation results of both methods should be combined, and the decision on the traffic organization scheme should be based on the specific objectives of the actual maintenance project.

[0090] Table 13 Evaluation Results of Traffic Organization Schemes under Different Weighting Taking a specific highway maintenance project as an example, the proposed strategy design method is applied to verify its effectiveness and practicality. Through comparison of actual data, it is demonstrated that this method can significantly reduce carbon emissions and overall costs, and improve the environmental and economic benefits of maintenance operations.

[0091] Example 3 This embodiment is based on the above embodiment 1. It discloses a comparison between the calculation of vehicle fuel consumption and carbon emissions in queuing and non-queuing states based on the vehicle speed-fuel consumption model proposed in embodiment 1 and the prior art, highlighting the effectiveness of the calculation method in this method.

[0092] In this embodiment, a simulated scenario with a speed limit of 80 km / h, a vehicle-to-large ratio of 0.20, a closed lane, and a working area length of 1 km was selected as the experimental conditions. The calculation results of the improved calculation method in Example 1 were compared with the calculation methods of existing studies that take the average speed of the entire process and the calculation results of the MOVES model. The results are as follows: Figure 8 As shown, the calculated values ​​from the improved method are higher than those from existing research methods but lower than those from the MOVES model. When traffic volume is low, the results from the improved method and existing research methods are not significantly different. However, as traffic volume increases, the difference between the two methods gradually becomes more pronounced, which can indirectly illustrate the changing pattern of additional carbon emissions.

[0093] Further analysis of the differences between the improved calculation method and the existing research method reveals the relative differences in the calculation results, as shown in Table 14. It can be seen that when traffic volume increases from 4400 veh / h to 4800 veh / h, the relative difference between the improved method and the existing research method increases dramatically from 4.28% to 9.24%, exceeding 10% at even higher traffic volumes. The maximum relative difference is 13.6% at 5200 veh / h. The magnitude of this relative difference reflects the extent to which the existing research method underestimates the additional carbon emissions from traffic delays. The changing pattern of the relative difference is basically consistent with the changing pattern of traffic delays with traffic volume, both showing a sharp increase at 4800 veh / h. This demonstrates that the improved calculation method can more accurately assess the additional carbon emissions from delays compared to the existing research method, highlighting the necessity and effectiveness of the improved calculation method.

[0094] Table 14 Comparison of results between the improved calculation method and the original method Example 4 Based on Embodiment 1, this embodiment provides an electronic device, including: one or more processors and a memory, wherein the memory stores one or more programs, the one or more programs including instructions for executing the aforementioned method for generating traffic organization strategies for road maintenance work areas that takes into account carbon emission costs.

[0095] At the hardware level, the electronic device includes a processor, internal bus, network interface, memory, and non-volatile memory, and may also include other hardware required for business operations. The processor reads the corresponding computer program from the non-volatile memory into memory and then runs it to implement the aforementioned method for generating traffic organization strategies for road maintenance work areas that considers carbon emission costs. Of course, in addition to software implementation, this invention does not exclude other implementation methods, such as logic devices or a combination of hardware and software, etc. That is to say, the execution subject of the following processing flow is not limited to individual logic units, but can also be hardware or logic devices.

[0096] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0097] Computer-readable media include both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0098] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for generating traffic organization strategies for road maintenance work areas that considers carbon emission costs, characterized in that, The method includes: Collect actual highway data, including highway geometry design, traffic flow characteristics, and vehicle composition data; Based on the actual highway data, a highway maintenance work area model is constructed, and an orthogonal traffic simulation experiment is conducted in the maintenance work area. Based on the simulation data, the three-dimensional indicators of traffic volume, large vehicle ratio and traffic delay are integrated to analyze the delay pattern and obtain the control threshold of closed lanes in the maintenance project. Based on the control threshold and minimum construction window period of the closed lanes in the maintenance project, multiple traffic organization strategies for maintenance work areas are generated according to the highway maintenance work area model, and the owner cost, user cost and environmental cost of each scheme are calculated. An importance weighting matrix is ​​established based on different decision-making objectives. Based on this importance weighting matrix, owner costs, user costs, and environmental costs, a weighted summation is used to obtain the total score of the traffic organization strategy for each maintenance work area. The traffic organization strategy for the maintenance work area with the optimal total score is then output. The user cost includes vehicle operating cost, and the environmental cost includes additional carbon emission cost due to traffic delay. When calculating the cost, the vehicle speed-fuel consumption model is fitted by actual measurement method, and the vehicle movement on the current highway is divided into different states based on queuing theory. The vehicle speed-fuel consumption model is used to calculate the vehicle fuel consumption and carbon emission under different states, and the vehicle operating cost and additional carbon emission cost due to traffic delay are calculated based on the vehicle fuel consumption and carbon emission.

2. The method for generating traffic organization strategies for road maintenance work areas considering carbon emission costs according to claim 1, characterized in that, The actual highway data was collected through roadside video recording, ETC gantry data, drone photography, closed-circuit television monitoring technology, and floating car method. The highway geometry design includes lane layout, road segment length, and maintenance work area planning scope; The traffic flow characteristics include macroscopic traffic flow attributes and microscopic traffic flow attributes. The macroscopic traffic flow attributes include daily traffic volume, hourly flow distribution, average speed, direction coefficient, and peak hours. The microscopic traffic flow attributes include vehicle following, lane changing, and overtaking parameters. The vehicle composition data includes the proportion of vehicle types.

3. The method for generating traffic organization strategies for road maintenance work areas considering carbon emission costs according to claim 1, characterized in that, The orthogonal traffic simulation experiment of the maintenance work area introduces a heat map scoring mechanism, using traffic volume, large vehicle ratio, and traffic delay as scoring indicators. Based on the simulation data, a delay-safety margin curve is fitted, and the heat map score, average road segment delay, and traffic density corresponding to the curve's sudden increase critical point are identified as the control threshold for lane closures in the maintenance project. This ensures that the heat map score, average road segment delay, and traffic density after the implementation of the traffic organization strategy in the maintenance work area are less than the control threshold. The traffic delay includes deceleration delay, queuing delay, speed limit delay, and acceleration delay, which are calculated based on the simulation data.

4. The method for generating traffic organization strategies for road maintenance work areas considering carbon emission costs according to claim 1, characterized in that, The owner's costs include road construction costs, maintenance costs, management fees, supervision fees, and design fees; the user's costs also include safety costs and delay costs; and the environmental costs also include the carbon emission costs of the entire maintenance process.

5. The method for generating traffic organization strategies for road maintenance work areas considering carbon emission costs according to claim 4, characterized in that, The safety cost is the cost incurred due to additional accidents caused by the existence of maintenance work areas, and the safety cost is calculated based on the current highway accident rate, traffic volume, and unit accident value; the delay cost is calculated based on the predicted delay duration, the preset user unit time value, and the average number of passengers per vehicle.

6. The method for generating traffic organization strategies for road maintenance work areas considering carbon emission costs according to claim 1, characterized in that, The process of constructing the vehicle speed-fuel consumption model includes: Based on the vehicle composition data, typical vehicles of each model were selected, and fuel consumption flow meters were installed on the experimental vehicles to record fuel consumption under experimental driving conditions at preset speeds and fixed lengths. The experiment was repeated and the average value was taken to obtain discrete fuel consumption data. A speed-fuel consumption curve was fitted to construct a vehicle speed-fuel consumption model.

7. The method for generating traffic organization strategies for road maintenance work areas considering carbon emission costs according to claim 1, characterized in that, In the highway maintenance work area model, the highway maintenance section is set up with functional zones based on the preset work area setting regulations. The functional zones include warning zone, upstream transition zone, longitudinal buffer zone, work zone, downstream transition zone and termination zone.

8. The method for generating traffic organization strategies for road maintenance work areas considering carbon emission costs according to claim 7, characterized in that, The process of breaking down the current vehicle motion on the highway into different states based on queuing theory includes: Based on the traffic organization strategy of the maintenance work area and the highway maintenance work area model, a simulation experiment was conducted. The maintenance lanes in the strategy were closed and functional zones were set. The simulation output showed the remaining traffic capacity of the highway, the real-time traffic volume, vehicle trajectory data, instantaneous vehicle speed and traffic density. If the remaining capacity of each road segment is greater than the simulated real-time traffic volume, then the vehicle movement is determined to be in a non-queuing state. Otherwise, the vehicle travel intervals with instantaneous speeds less than the preset queuing speed threshold, travel positions in the upstream transition zone and longitudinal buffer zone, and traffic density greater than the preset maximum traffic density are selected from the vehicle trajectory data. These continuous intervals are merged as queuing segments, and the vehicle movement in the queuing segments is determined to be in a queuing state. The vehicle movement in the remaining road segments is determined to be in a non-queuing state.

9. A method for generating traffic organization strategies for road maintenance work areas considering carbon emission costs, as described in claim 8, is characterized in that... The process of calculating vehicle fuel consumption and carbon emissions under different conditions includes: Simulation experiments were conducted based on the traffic organization strategy of the maintenance work area and the highway maintenance work area model to obtain the instantaneous speed, driving position, driving time and traffic density of vehicles. Based on simulation experimental data, the instantaneous speeds of all vehicles in the queuing and non-queuing sections are selected, and the arithmetic average is taken to obtain the average vehicle speed in the queuing area and the average vehicle speed in the non-queuing area. The length of the congestion is calculated by the vehicle's driving position, and the queuing length and the driving length in the non-queuing section are obtained by combining the total length of the maintenance section. The average vehicle speed in the queuing area, the queue length, the average vehicle speed in the non-queuing area, and the driving length in the non-queuing section are substituted into the vehicle speed-fuel consumption model to calculate the vehicle fuel consumption and carbon emissions under the two conditions during maintenance operations.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method for generating traffic organization strategies for road maintenance work areas that takes into account carbon emission costs as described in any one of claims 1-9.

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