Method for estimating regional road vehicle emission based on typical traffic volume investigation

Abstract

The application discloses a method for estimating regional road motor vehicle emission based on typical traffic flow investigation, and relates to the technical field of motor vehicle emission estimation, and comprises the following steps: constructing a test road, obtaining experimental emission based on the test road; obtaining a first emission threshold and a second emission threshold based on the experimental emission; obtaining a first parameter value and a second parameter value based on the first emission threshold, the second emission threshold and the experimental emission; obtaining a parameter fitting function based on the first parameter value and the second parameter value; obtaining a guessed path based on the information of the investigation-estimated regional road and a traffic checkpoint; obtaining the total emission of the regional road based on the guessed path and the parameter fitting function; the application aims to solve the problem that the prior art fails to fully consider the actual influence of the regional road environment on motor vehicle emission, and it is difficult to accurately obtain the driving path and speed of a target vehicle, thereby leading to inaccurate emission estimation results.

Description

Technical Field

[0001] This invention relates to the field of motor vehicle emission estimation technology, specifically a method for estimating regional road motor vehicle emissions based on typical traffic flow surveys. Background Technology

[0002] With the continuous growth of motor vehicle ownership, motor vehicle exhaust emissions have become one of the important sources of urban air pollution. Accurately estimating regional road motor vehicle emissions is of great significance for formulating effective environmental policies, improving air quality, optimizing traffic management measures, and evaluating emission reduction effects. Therefore, investigating and estimating regional road motor vehicle emissions is of great significance.

[0003] Traditional methods for estimating vehicle emissions on regional roads typically obtain emission factors based on different fuel types, emission stages, and vehicle specifications. However, these emission data are mostly based on ideal operating conditions and do not fully reflect emission characteristics under actual road conditions. Since the regional road environment significantly impacts vehicle driving behavior, the actual emissions generated during normal driving deviate from those under ideal conditions. Furthermore, existing technologies struggle to accurately obtain the specific driving paths and speeds of unfamiliar vehicles, further increasing the difficulty of emission estimation. For example, patent CN116307837A discloses a regional vehicle emission assessment method and system based on multi-source monitoring technology, but this scheme fails to effectively consider the impact of the regional road environment on emissions and struggles to accurately obtain the target vehicle's driving path and speed, leading to certain errors in the emission estimation results. Therefore, existing technologies for vehicle emission estimation generally suffer from insufficient consideration of the impact of the road environment and difficulty in obtaining driving behavior information, requiring urgent improvement. Summary of the Invention

[0004] This invention aims to at least partially address one of the technical problems in the prior art. It involves constructing a test road, obtaining experimental emissions based on the test road, obtaining a first emission threshold and a second emission threshold based on the experimental emissions, obtaining a first parameter value and a second parameter value based on the first emission threshold, the second emission threshold, and the experimental emissions, obtaining a parameter fitting function based on the first parameter value and the second parameter value, obtaining a guessed path based on the surveyed and estimated information of regional roads and traffic checkpoints, and obtaining the total emissions of regional roads based on the guessed path and the parameter fitting function. This addresses the problem that existing technologies fail to consider the influence of regional road environment on vehicle emissions, and that the travel path and speed of the target vehicle being detected are difficult to obtain accurately, leading to inaccurate estimations of vehicle emissions.

[0005] To achieve the above objectives, this application provides a method for estimating regional road vehicle emissions based on typical traffic flow surveys, comprising the following steps:

[0006] Obtain basic category information for motor vehicles;

[0007] Construct test roads and obtain experimental emissions based on the test roads;

[0008] The first and second emission thresholds were obtained based on the experimental emission levels.

[0009] The first parameter value and the second parameter value are obtained based on the first emission threshold, the second emission threshold, and the experimental emission amount;

[0010] Obtain the parameter fitting function based on the first parameter value and the second parameter value;

[0011] Based on the information obtained from the survey and estimation of regional roads and traffic checkpoints, the route was guessed.

[0012] The total emissions of regional roads are obtained by guessing the path and fitting the parameter function.

[0013] Furthermore, obtaining basic category information for motor vehicles includes the following sub-steps:

[0014] The system obtains the fuel type, namely gasoline and diesel; the emission stage of motor vehicles, namely China I, China II, China III, China IV, China V and China VI; and the vehicle type, namely mini passenger car, small passenger car, medium passenger car, large passenger car, mini truck, small truck, medium truck and large truck.

[0015] Furthermore, constructing test roads and obtaining experimental emissions based on these test roads includes the following sub-steps:

[0016] Under different conditions of fuel type, motor vehicle pollutant emission stage, and motor vehicle type, a first number of motor vehicles were selected and marked as experimental motor vehicles.

[0017] A target area road of length Sl is set as the test road. Under the same conditions of fuel type, motor vehicle pollutant emission stage and motor vehicle type, the experimental motor vehicle passes through the test road at different speeds, and the time for each experimental motor vehicle to pass through the test road is obtained and marked as Tl.

[0018] Obtain the emissions generated by each car as it travels on the test road and label them as experimental emissions.

[0019] Furthermore, obtaining the first emission threshold and the second emission threshold based on the experimental emissions includes the following sub-steps:

[0020] Under the same conditions of fuel type, motor vehicle pollutant emission stage, and motor vehicle type, the experimental emissions were sorted from smallest to largest and labeled as Sp1 to Sp2. i ;

[0021] Find the value of the first position as k1*D, where k1 is the first coefficient, the range of k1 is (0, 0.5), and D is the first quantity; obtain the integer part of the first position value and mark it as W1;

[0022] Find the second position value as k2*D, where k2 is the second coefficient and the range of k2 is (0.5, 1); obtain the integer part of the second position value and mark it as W2;

[0023] Sp (w1) The corresponding experimental emissions are labeled F1, and Sp... (w2) The corresponding experimental emissions are labeled F2;

[0024] The first emission threshold is calculated as: F1 - (F2 - F1) / (k2 - k1) × k1;

[0025] The second emission threshold is calculated as: F2+(F2-F1) / (k2-k1)×(1-k2).

[0026] Furthermore, obtaining the first parameter value and the second parameter value based on the first emission threshold, the second emission threshold, and the experimental emission amount includes the following sub-steps:

[0027] The experimental emissions that are greater than or equal to the first emission threshold and less than or equal to the second emission threshold are recorded and marked as the screening emissions.

[0028] The first parameter value is obtained as: Sl / Tl;

[0029] The second parameter value is obtained as: Pf / Tl; where Pf is the screening emission amount.

[0030] Furthermore, obtaining the parameter fitting function based on the first parameter value and the second parameter value includes the following sub-steps:

[0031] Establish a Cartesian coordinate system with the first parameter value as the horizontal axis data and the second parameter value as the vertical axis data, and mark it as the reference coordinate system;

[0032] The first parameter value and the second parameter value are used as the x-coordinate and y-coordinate of the coordinate point, respectively, and marked as the reference coordinate point;

[0033] Plot the reference coordinate points in the reference coordinate system to obtain a reference scatter plot;

[0034] The initial fitting function is obtained by fitting the function to the scatter plot.

[0035] Furthermore, obtaining the parameter fitting function based on the first parameter value and the second parameter value also includes the following sub-steps:

[0036] Substitute the second number of first parameter values ​​into the initial fitting function to obtain the initial function value;

[0037] The value obtained by multiplying the initial function value by Tl is marked as the initial emission amount;

[0038] Determine whether all initial emissions are greater than or equal to the first emission threshold corresponding to the first parameter value and less than or equal to the second emission threshold corresponding to the first parameter value. If not, add a third number of experimental vehicles under different fuel types, motor vehicle pollutant emission stages, and motor vehicle types, and repeatedly obtain the initial fitting function until all initial emissions are greater than or equal to the first emission threshold corresponding to the first parameter value and less than or equal to the second emission threshold corresponding to the first parameter value. If so, mark the initial function value as the parameter fitting function.

[0039] Furthermore, the route estimation based on the survey-estimated information on regional roads and traffic checkpoints includes the following sub-steps:

[0040] Represent regional roads as line segments and mark them as route segments. Mark the intersections between route segments as intersection points. Obtain traffic checkpoints at the intersection points and mark them as checkpoint points.

[0041] Establish a Cartesian coordinate system, labeled as the checkpoint coordinate system, and draw the route segments and checkpoints in the checkpoint coordinate system.

[0042] Furthermore, the method of obtaining and guessing routes based on the information of regional roads and traffic checkpoints estimated by the survey also includes the following sub-steps:

[0043] Obtain the time and location of each vehicle passing through the checkpoint, and mark them as real-time time and actual passing point;

[0044] Obtain the sequence numbers of the actual points passed through in ascending order according to the real-time time sequence;

[0045] Determine whether the actual points passed by adjacent sequence numbers are adjacent intersections. If so, obtain the shortest route segment between the two actual points passed by and mark it as an adjacent segment.

[0046] If not, connect the two actual points passed through to obtain the connecting line segment; obtain the actual point with the smaller sequence number among the two actual points passed through and mark it as the starting point; mark the route segment with the starting point as the endpoint as the initial line segment; obtain the initial line segment with an angle of less than 90° with the connecting line segment and mark it as the candidate line segment; obtain the intersection point of the other endpoint of the candidate line segment and mark it as the filtering intersection point.

[0047] Obtain the actual point with the larger sequence number from the two actual points passed through, and mark it as the destination point passed through; determine whether the filtered intersection point and the destination point passed through are adjacent intersection points. If so, obtain the route segment between the filtered intersection point and the destination point passed through, and mark it as a hypothetical segment. If not, repeat the process of using the filtered intersection point as the starting point to obtain candidate segments and the filtered intersection point, until the filtered intersection point and the destination point passed through are adjacent intersection points.

[0048] Obtain all candidate line segments and hypothetical line segments. Find the shortest path between the starting point and the ending point, formed by the candidate line segments and hypothetical line segments, and mark it as the guessed path.

[0049] Furthermore, obtaining the total emissions from regional roads based on the guessed path and parameter fitting function includes the following sub-steps:

[0050] Get the length of all guessed paths and adjacent line segments, and label it as Ss; get the maximum difference in real time for each vehicle, and label it as Ts;

[0051] The value of the third parameter is: Ss / Ts;

[0052] Substitute the value of the third parameter as the x-axis into the corresponding parameter fitting function to obtain the prediction function value;

[0053] The value obtained by multiplying the prediction function value by Ts is labeled as the predicted emissions;

[0054] The total predicted emissions of all motor vehicles on roads in the survey area within the survey period are obtained and labeled as the total emissions of roads in the area.

[0055] The beneficial effects of this invention are as follows: This invention constructs a test road, obtains experimental emissions based on the test road; obtains a first emission threshold and a second emission threshold based on the experimental emissions; obtains a first parameter value and a second parameter value based on the first emission threshold, the second emission threshold, and the experimental emissions; obtains a parameter fitting function based on the first parameter value and the second parameter value; obtains a guessed path based on the information of regional roads and traffic checkpoints estimated by survey; and obtains the total emissions of regional roads based on the guessed path and the parameter fitting function. The advantage is that this method can effectively reduce the impact of the regional road environment on the emission estimation results, and at the same time, relying on the vehicle information obtained from traffic checkpoints, it can more accurately predict the actual driving path of vehicles, thereby significantly improving the accuracy and reliability of motor vehicle emission estimation.

[0056] This invention obtains an initial function value by substituting a second number of first parameter values ​​into an initial fitting function. The advantage lies in further determining whether the initial function value is within the actual first emission threshold and second emission threshold to judge the accuracy of the prediction of the initial fitting function. If it is inaccurate, the initial fitting function is updated to obtain a more accurate parameter fitting function, thereby making the estimation of motor vehicle emissions more accurate. Attached Figure Description

[0057] Figure 1 This is a flowchart illustrating the steps of the method of the present invention;

[0058] Figure 2 This is a schematic diagram of an initial fitting function of the present invention;

[0059] Figure 3 This is a schematic diagram of the connecting line segments of the present invention;

[0060] Figure 4 This is a schematic diagram of the guessing path of the present invention. Detailed Implementation

[0061] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0062] Example 1, please refer to Figure 1 As shown, this application provides a method for estimating regional road vehicle emissions based on typical traffic flow surveys, including the following steps:

[0063] Step S1: Obtain basic category information of the motor vehicle; Step S1 includes the following sub-steps:

[0064] Step S101: Obtain the fuel type, which is gasoline and diesel; obtain the emission stage of motor vehicles, which is China I, China II, China III, China IV, China V and China VI; obtain the vehicle type, which is mini passenger car, small passenger car, medium passenger car, large passenger car, mini truck, small truck, medium truck and large truck; since different motor vehicles have different emissions, it is necessary to analyze different types of vehicles.

[0065] Step S2: Construct a test road and obtain experimental emissions based on the test road; Step S2 includes the following sub-steps:

[0066] Step S201: Select a first number of motor vehicles under different conditions of fuel type, motor vehicle pollutant emission stage and motor vehicle type, and mark them as experimental motor vehicles; a single data point cannot summarize the regularity, so a first number is set, for example, the first number is set to 20;

[0067] Step S202: Set a target area road of length Sl as the test road. Under the same conditions of fuel type, motor vehicle pollutant emission stage and motor vehicle type, make the experimental motor vehicle pass through the test road at different speeds, and obtain the time for each experimental motor vehicle to pass through the test road, which is marked as Tl; using the target area road as the test road makes the data more relevant.

[0068] Step S203: Obtain the emissions generated by each vehicle passing through the test road and mark them as experimental emissions;

[0069] In practical applications, for example, under the conditions of gasoline type, China VI emission standard, and medium-sized passenger vehicle, a target area road with a length of 2km is set as the test road. The time Tl for each experimental vehicle to pass through the test road is 0.1h, and the experimental emissions are 5.62g, 5.81g, ..., 6.22g.

[0070] Step S3: Obtain the first emission threshold and the second emission threshold based on the experimental emission levels; Step S3 includes the following sub-steps:

[0071] Step S301: Under the same conditions of fuel type, motor vehicle pollutant emission stage, and motor vehicle type, the experimental emissions are sorted from smallest to largest and labeled as Sp1 to Sp2. i ;

[0072] Step S302: Calculate the first position value as k1*D, where k1 is the first coefficient, the range of k1 is (0, 0.5), and D is the first quantity; obtain the integer part of the first position value and mark it as W1; in order to obtain the experimental emission amount with a smaller i, the range of k1 is (0, 0.5), and the specific value of k1 can be selected as the middle value of (0, 0.5), 0.25;

[0073] Step S303: Calculate the second position value as k2*D, where k2 is the second coefficient and the range of k2 is (0.5, 1); obtain the integer part of the second position value and mark it as W2; the first position value is to obtain the experimental emission amount with a smaller value of i, so the range of k2 is (0.5, 1), and the specific value of k2 can be selected as the middle value of (0.5, 1), 0.75.

[0074] Step S304, Sp (w1) The corresponding experimental emissions are labeled F1, and Sp...(w2) The corresponding experimental emissions are labeled F2;

[0075] Step S305, calculate the first emission threshold as: F1-(F2-F1) / (k2-k1)×k1; the first emission threshold is the minimum value of the historical difference when the experimental emission is uniformly distributed. However, the actual experimental emission is relatively concentrated due to the same conditions. If it exceeds the first emission threshold, it can be identified as an abnormal experimental emission.

[0076] Step S306, calculate the second emission threshold as: F2+(F2-F1) / (k2-k1)×(1-k2);

[0077] In practical applications, for example, when D is 20, k1 is 0.25, and k2 is 0.75, the first position value is calculated as: k1*D = 5, the integer part of the first position value is 5, so W1 = 5. The second position value is calculated as: k2*D = 15, the integer part of the second position value is 15, so W2 = 15, and Sp is obtained. (5) The corresponding experimental emission amount is 5.77g, so F1 = 5.77g. (The last part, "Sp," appears to be a typo and can be omitted.) (15) The corresponding experimental emission amount is 6.07g, so F2 = 6.07. The first emission threshold is calculated as: 5.77 - (6.07 - 5.77) / (0.75 - 0.25) × 0.25 = 5.62. The second emission threshold is calculated as: 6.07 + (6.07 - 5.77) / (0.75 - 0.25) × (1 - 0.75) = 6.22.

[0078] Step S4 involves obtaining the first parameter value and the second parameter value based on the first emission threshold, the second emission threshold, and the experimental emission amount. Step S4 includes the following sub-steps:

[0079] Step S401: Obtain experimental emissions that are greater than or equal to the first emission threshold and less than or equal to the second emission threshold, and mark them as screening emissions;

[0080] Step S402, obtain the first parameter value as: Sl / Tl;

[0081] Step S403: Obtain the second parameter value as: Pf / Tl; where Pf is the filtered emission amount; where the first parameter value can represent the vehicle speed and the second parameter value can represent the emission rate.

[0082] In practical applications, when Sl is 2km and Tl is 0.1h, the first parameter value is obtained as: 2 / 0.1 = 20. For example, if the emission amount is 5.62g, the second parameter value is obtained as: 5.62 / 0.1 = 56.2.

[0083] Step S5: Obtain the parameter fitting function based on the first parameter value and the second parameter value; Step S5 includes the following sub-steps:

[0084] Step S501: Establish a Cartesian coordinate system with the first parameter value as the horizontal axis data and the second parameter value as the vertical axis data, and mark it as the reference coordinate system;

[0085] Step S502: Use the first parameter value and the second parameter value as the x-coordinate and y-coordinate of the coordinate point, respectively, and mark them as reference coordinate points;

[0086] Step S503: Plot the reference coordinate points in the reference coordinate system to obtain a reference scatter plot;

[0087] Step S504: The initial fitting function is obtained by performing function fitting on the scatter plot; where the first parameter value can represent the vehicle speed and the second parameter value can represent the emission rate; vehicle speed is related to emission rate, so function fitting can be performed.

[0088] Step S505: Substitute a second number of first parameter values ​​into the initial fitting function to obtain the initial function value; for example, the second number is 10, to verify the accuracy of the initial fitting function;

[0089] Step S506: Multiply the initial function value by Tl and mark the resulting value as the initial emission amount;

[0090] Step S507: Determine whether all initial emissions are greater than or equal to the first emission threshold corresponding to the first parameter value and less than or equal to the second emission threshold corresponding to the first parameter value. If not, increase the number of experimental vehicles by a third number under different fuel types, motor vehicle pollutant emission stages, and motor vehicle types, and repeatedly obtain the initial fitting function until all initial emissions are greater than or equal to the first emission threshold corresponding to the first parameter value and less than or equal to the second emission threshold corresponding to the first parameter value. If so, mark the initial function value as the parameter fitting function. The inaccuracy of the initial fitting function may be due to insufficient data in the fitting function. Increasing the number by half of the first number will solve the problem. When the first number is 20, the third number is 10.

[0091] For practical applications, please refer to Figure 2 As shown, the initial fitting function is obtained under the conditions of gasoline type, China VI emission standard, and medium-sized passenger vehicle. For example, when the first parameter value is 20, substituting it into the initial fitting function yields a vertical coordinate of 48.1, and the initial emission amount is: 48.1 × 0.1 = 4.81. The first emission threshold corresponding to the first parameter value of 20 is 5.62, and the second emission threshold is 6.22. Then, 4.81 satisfies the conditions of being greater than or equal to 5.62 and less than or equal to 6.22. The initial fitting function is marked as the parametric fitting function.

[0092] Step S6 involves obtaining a route guess based on the information from the surveyed and estimated regional roads and traffic checkpoints; Step S6 includes the following sub-steps:

[0093] Step S601: Obtain the area roads represented by line segments and mark them as route segments. Mark the intersections between the route segments as intersection points. Obtain the traffic checkpoints at the intersection points and mark them as checkpoint points. Traffic checkpoints can obtain the passing information of each vehicle based on the license plate.

[0094] Step S602: Establish a Cartesian coordinate system, mark it as the checkpoint coordinate system, and draw the route segment and checkpoint points in the checkpoint coordinate system;

[0095] Step S603: Obtain the time and location of each vehicle passing through the checkpoint, and mark them as real-time time and actual passing point;

[0096] Step S604: Obtain the sequence numbers of the actual points passed through in ascending order according to the real-time time sequence;

[0097] Step S605: Determine whether the actual passing point corresponding to the adjacent sequence number is an adjacent intersection point. If so, obtain the shortest route segment between the two actual passing points and mark it as an adjacent segment. Because the license plate data obtained by the traffic checkpoint is an image, there may be situations where the license plate of the following vehicle is obscured by a large vehicle in front, or the checkpoint equipment may malfunction, resulting in the failure to obtain the real-time passing point when passing through this checkpoint. Therefore, it is necessary to make a judgment.

[0098] Step S606: If not, connect the two actual passing points to obtain the connecting line segment; obtain the actual passing point with the smaller sequence number among the two actual passing points and mark it as the starting passing point; mark the route segment with the starting passing point as the endpoint as the initial line segment; obtain the initial line segment with an angle of less than 90° with the connecting line segment and mark it as the candidate line segment; obtain the intersection point of the other endpoint of the candidate line segment and mark it as the filtering intersection point; obtaining candidate line segments would greatly increase the amount of calculation if all routes that can pass through the actual passing points were obtained.

[0099] Step S607: Obtain the actual point with the larger sequence number among the two actual points passed through, and mark it as the destination point passed through; determine whether the filtered intersection point and the destination point passed through are adjacent intersection points. If so, obtain the route segment between the filtered intersection point and the destination point passed through, and mark it as a hypothetical segment. If not, repeat the process of using the filtered intersection point as the starting point passed through, obtaining candidate segments and the filtered intersection point, until the filtered intersection point and the destination point passed through are adjacent intersection points.

[0100] Step S608: Obtain all candidate line segments and hypothetical line segments, and obtain the shortest path between the starting point and the ending point formed by the candidate line segments and hypothetical line segments, and mark it as the guessed path; generally, drivers will take the shortest path when driving, so the shortest path between the starting point and the ending point formed by the candidate line segments and hypothetical line segments is set as the guessed path.

[0101] For practical applications, please refer to Figure 3 and Figure 4 As shown, the obtained guessed path.

[0102] Step S7: Obtain the total emissions from regional roads based on the guessed path and parameter fitting function; Step S7 includes the following sub-steps:

[0103] Step S701: Obtain the length of all guessed paths and adjacent line segments, marked as Ss; obtain the maximum difference in real-time time for each vehicle, marked as Ts;

[0104] Step S702, obtain the value of the third parameter as: Ss / Ts;

[0105] Step S703: Substitute the value of the third parameter as the x-axis into the corresponding parameter fitting function to obtain the prediction function value;

[0106] Step S704: Multiply the prediction function value by Ts and mark the resulting value as the predicted emissions;

[0107] Step S705: Obtain the sum of the predicted emissions of all motor vehicles on the roads in the area within the survey period, and mark it as the total emissions of the roads in the area; the survey period is generally set to 1 hour, but since the traffic flow is different at different times, the 1-hour survey period can be set at different periods.

[0108] For practical applications, please refer to Figure 3 and Figure 4 As shown, the length of all guessed paths and adjacent line segments is 2.1km; the maximum difference in real-time time for each vehicle is 0.05h; the third parameter value is 42; 42 is used as the abscissa and substituted into the corresponding parameter fitting function to obtain the prediction function value of 111; the predicted emission is: 111 × 0.05h = 5.55g; the sum of all predicted emissions is obtained as the total emissions of the regional roads.

[0109] Example 2: This application also provides an electronic device, which may include: a processor, a communication interface, a memory, and a communication bus, wherein the processor, communication interface, and memory communicate with each other through the communication bus. The memory stores computer-readable instructions, which the processor can call. When the processor executes the computer-readable instructions in the memory, it will perform the following functions according to the steps in the method for estimating regional road vehicle emissions based on typical traffic flow surveys: obtaining basic vehicle category information; constructing a test road and obtaining experimental emissions; determining a first emission threshold and a second emission threshold based on the experimental emissions; calculating a first parameter value and a second parameter value based on the first emission threshold, the second emission threshold, and the experimental emissions; obtaining a parameter fitting function based on the first parameter value and the second parameter value; obtaining a guessed path based on the surveyed and estimated regional road and traffic checkpoint information; and obtaining the total regional road emissions based on the guessed path and the parameter fitting function.

[0110] Furthermore, the logical instructions in the aforementioned memory can be implemented as software functional units and stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of this application, or its contribution to the prior art, can be implemented in the form of a software product. This computer software product is stored in a storage medium and contains several instructions for causing a computer device (such as a personal computer, server, or network device) to execute all or part of the steps of the methods described in the embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RkM), magnetic disks, or optical disks.

[0111] Example 3: This application also provides a computer program product, which includes a computer program stored on a computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the method provided by the above methods for estimating regional road vehicle emissions based on typical traffic flow surveys. This method includes: obtaining basic category information of motor vehicles; constructing a test road and collecting experimental emissions based on the test road; determining a first emission threshold and a second emission threshold based on the experimental emissions; calculating a first parameter value and a second parameter value based on the emission thresholds and the experimental emissions; constructing a parameter fitting function based on the parameter values; combining regional road survey data and traffic checkpoint information to infer vehicle travel paths; and finally, estimating the total emissions of motor vehicles on regional roads based on the inferred paths and the parameter fitting function.

[0112] Example 4: This application also provides a computer-readable storage medium storing a computer program. When the program is executed by a processor, it performs various steps in the method for estimating regional road vehicle emissions based on typical traffic flow surveys, to achieve the following functions: obtaining basic vehicle category information; constructing test roads and collecting experimental emissions; determining a first emission threshold and a second emission threshold based on the experimental emissions; calculating a first parameter value and a second parameter value based on the first emission threshold, the second emission threshold, and the experimental emissions; constructing a parameter fitting function based on the parameter values; inferring vehicle travel paths by combining regional road survey data and traffic checkpoint information; and finally, estimating the total vehicle emissions of the regional roads based on the inferred paths and the parameter fitting function.

[0113] Based on the above description of the embodiments, the embodiments of the present invention can be provided as methods, systems, or computer program products. Based on this understanding, the above technical solutions, in essence or in terms of their contribution to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / ROM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in various embodiments or certain parts of the embodiments.

[0114] In the embodiments provided in this application, it should be understood that the disclosed system or method can be implemented in other ways. The embodiments described above are merely illustrative. For example, the division of modules or units is only a logical functional division, and there may be other division methods in actual implementation. Furthermore, multiple modules or units may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the coupling or direct coupling or communication connection shown or discussed may be through some communication interfaces. The indirect coupling or communication connection between systems, modules, and units may be electrical, mechanical, or other forms.

[0115] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for estimating the amount of vehicle emissions on regional roads based on typical traffic volume surveys, characterized by, The method comprises the following steps: acquiring basic category information of the motor vehicle; constructing a test road and acquiring experimental emission based on the test road; acquiring a first emission threshold and a second emission threshold based on the experimental emission; acquiring a first parameter value and a second parameter value based on the first emission threshold, the second emission threshold and the experimental emission; acquiring a parameter fitting function based on the first parameter value and the second parameter value; acquiring a suspected path based on information of the survey-estimated regional road and traffic checkpoint; acquiring a total regional road emission based on the suspected path and the parameter fitting function; acquiring the suspected path based on the survey-estimated information of the regional road and the traffic checkpoint comprises the following sub-steps: acquiring regional road line segments, marking them as route line segments, acquiring intersection points between the route line segments, marking them as intersection points, acquiring traffic checkpoints at positions of the intersection points, marking them as checkpoint points; establishing a planar rectangular coordinate system, marking it as a checkpoint coordinate system, and drawing the route line segments and the checkpoint points in the checkpoint coordinate system; acquiring time and position of each motor vehicle passing through the checkpoint points, marking them as real-time time and actual passing points; acquiring actual passing points in ascending order according to the real-time time and assigning them sequence numbers from small to large; determining whether the actual passing points corresponding to adjacent sequence numbers are adjacent intersection points, if yes, acquiring the shortest route line segment between the two actual passing points, marking it as an adjacent line segment; if not, connecting the two actual passing points to acquire a connecting line segment; acquiring the actual passing point with a smaller sequence number among the two actual passing points, marking it as a starting passing point, and acquiring the route line segment with the starting passing point as an end point, marking it as an initial line segment; acquiring the initial line segment with an angle less than 90° with the connecting line segment, marking it as a candidate line segment, and acquiring the intersection point of the other end point of the candidate line segment, marking it as a screening intersection point; acquiring the actual passing point with a larger sequence number among the two actual passing points, marking it as a terminal passing point, and determining whether the screening intersection point and the terminal passing point are adjacent intersection points, if yes, acquiring the route line segment between the screening intersection point and the terminal passing point, marking it as a hypothetical line segment, if not, repeating the process of taking the screening intersection point as the starting passing point, acquiring the candidate line segment and the screening intersection point, until the screening intersection point and the terminal passing point are adjacent intersection points; acquiring all the candidate line segments and the hypothetical line segments, and acquiring the shortest path between the starting passing point and the terminal passing point composed of the candidate line segments and the hypothetical line segments, marking it as the suspected path.

2. The method of estimating regional road mobile source emissions based on a typical traffic survey according to claim 1, wherein, The acquiring of the basic category information of the motor vehicle comprises the following sub-steps: acquiring fuel types, respectively gasoline type and diesel type, acquiring motor vehicle pollutant emission stages, respectively national stage one, national stage two, national stage three, national stage four, national stage five and national stage six, and acquiring motor vehicle types, respectively micro passenger car, small passenger car, medium passenger car, large passenger car, micro truck, small truck, medium truck and large truck.

3. The method of estimating regional road mobile source emissions based on a typical traffic survey according to claim 2, wherein, The constructing of the test road and the acquiring of the experimental emission based on the test road comprise the following sub-steps: selecting a first number of motor vehicles under the condition of different fuel types, motor vehicle pollutant emission stages and motor vehicle types, marking them as experimental motor vehicles; Setting a region road of a target with a length of Sl as a test road, making experimental motor vehicles pass through the test road at different speeds under the condition of the same fuel type, motor vehicle pollutant emission stage and motor vehicle type, obtaining the time of each experimental motor vehicle passing through the test road, marked as Tl; Obtaining the emission amount generated by each vehicle passing through the test road, marked as experimental emission amount.

4. The method of estimating regional road mobile source emissions based on a typical traffic survey according to claim 3, wherein, Obtaining the first emission threshold and the second emission threshold based on the experimental emission amount includes the following sub-steps: The experimental emissions are sorted in ascending order under the same fuel type, motor vehicle pollutant emission stage, and motor vehicle type conditions and are labeled Sp1 to Sp i ; Obtaining the first position value as: k1*D, wherein k1 is the first coefficient, the range of k1 is: (0, 0.5), and D is the first quantity; obtaining the integer part of the first position value, marked as W1; Obtaining the second position value as: k2*D, wherein k2 is the second coefficient, the range of k2 is: (0.5, 1); obtaining the integer part of the second position value, marked as W2; Sp （w1） The corresponding experimental discharge is marked as F1, Sp （w2） The corresponding experimental discharge is marked as F2; Obtaining the first emission threshold as: F1-(F2-F1) / (k2-k1)*k1; Obtaining the second emission threshold as: F2+(F2-F1) / (k2-k1)*(1-k2).

5. The method of estimating regional road mobile source emissions based on a typical traffic survey according to claim 4, wherein, Obtaining the first parameter value and the second parameter value based on the first emission threshold, the second emission threshold and the experimental emission amount includes the following sub-steps: Obtaining the experimental emission amount between and including the first emission threshold and less than or equal to the second emission threshold, marked as screening emission amount; Obtaining the first parameter value as: Sl / Tl; Obtaining the second parameter value as: Pf / Tl; wherein Pf is the screening emission amount.

6. The method of estimating regional road mobile source emissions based on a typical traffic survey according to claim 5, wherein, Obtaining the parameter fitting function based on the first parameter value and the second parameter value includes the following sub-steps: Establishing a plane rectangular coordinate system, marked as reference coordinate system, with the first parameter value as the horizontal axis data and the second parameter value as the vertical axis data; Taking the first parameter value and the second parameter value as the horizontal coordinate and the vertical coordinate of the coordinate point respectively, marked as reference coordinate point; Drawing the reference coordinate point in the reference coordinate system to obtain a reference scatter plot; Obtaining an initial fitting function by function fitting on the reference scatter plot.

7. The method of estimating regional road mobile source emissions based on a typical traffic survey according to claim 6, wherein, Obtaining the parameter fitting function based on the first parameter value and the second parameter value also includes the following sub-steps: Obtaining the initial function value by substituting the second quantity of first parameter values into the initial fitting function; Multiplying the initial function value by Tl to obtain a value, marked as initial emission amount; Judging whether all initial emission amounts are greater than or equal to the first emission threshold corresponding to the first parameter value and less than or equal to the second emission threshold corresponding to the first parameter value, if not, increasing the third quantity of experimental motor vehicles under the condition of different fuel types, motor vehicle pollutant emission stages and motor vehicle types, repeating the obtaining of the initial fitting function until all initial emission amounts are greater than or equal to the first emission threshold corresponding to the first parameter value and less than or equal to the second emission threshold corresponding to the first parameter value, if yes, marking the initial function value as the parameter fitting function.

8. The method of estimating regional road mobile source emissions based on a typical traffic survey according to claim 7, wherein, Obtaining the total emission amount of the region road based on the guessed path and the parameter fitting function includes the following sub-steps: Obtaining the length of all guessed paths and adjacent line segments, marked as Ss; obtaining the maximum value of the difference of the real-time time of each motor vehicle, marked as Ts; Obtaining the third parameter value as: Ss / Ts; The third parameter value is substituted into the corresponding parameter fitting function as the abscissa to obtain a predicted function value; The predicted function value is multiplied by Ts to obtain a value, which is marked as the predicted emission amount; The sum of the predicted emission amounts of all motor vehicles on the regional road within the survey time is obtained, which is marked as the total emission amount of the regional road.

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