Traffic carbon emission detection method and system and intelligent terminal

Abstract

The invention relates to a traffic carbon emission detection method and system and an intelligent terminal, and relates to the technical field of carbon emission, and the method comprises the steps: obtaining the total amount of carbon emission, heat detection information and image detection information; according to the consistency between the image detection information and the reference image information, determining to complete adjustment or determine an adjustment angle; calculating an angle vector deviation value according to the adjustment angle and the reference angle; controlling a preset image detection device to perform rotation adjustment according to the angle vector deviation value, and obtaining heat detection information and image detection information again; determining a heat distribution position according to the image detection information and the heat detection information; determining an estimated emission amount at the heat distribution position according to the image detection information and the characteristics of the carbon emission device; the difference between the total carbon emission amount and the estimated emission amount is calculated and serves as the automobile carbon emission amount; and uploading the carbon emission of the automobile to a carbon emission detection platform and outputting prompt information. The method has the effect of improving the accuracy of detecting the carbon emission of the automobile.

Description

Technical Field

[0001] The present invention relates to the field of carbon emission technology, and in particular to a method, system and intelligent terminal for detecting traffic carbon emissions. Background Art

[0002] At present, the calculation of urban transportation carbon emissions is of great significance for understanding the impact of urban transportation on climate change, formulating policies and measures to reduce carbon emissions, optimizing the energy consumption structure, and realizing the green and low-carbon transformation of urban transportation.

[0003] As the global climate change problem becomes increasingly serious, urban transportation, as an important component of greenhouse gas emissions, has made the accounting and management of its carbon emissions an important part of urban sustainable development. The current energy-saving and emission reduction detection technology directly detects carbon emissions within a range through sensors, and records and uploads the detected carbon emissions.

[0004] The current energy-saving and emission-reduction detection technology is used to detect the total amount of carbon emissions within the scope. The transportation industry is complex, and there are various factors on the road that increase carbon emissions, which leads to deviations in the carbon emissions detection data for transportation. Summary of the invention

[0005] In order to improve the accuracy of detecting automobile carbon emissions, the present invention provides a method, system and intelligent terminal for detecting traffic carbon emissions.

[0006] In a first aspect, the present invention provides a method for detecting traffic carbon emissions, which adopts the following technical solution:

[0007] A method for detecting traffic carbon emissions, comprising:

[0008] Obtain the total carbon emissions, heat detection information and image detection information on the road surface;

[0009] Determining the completion of adjustment or determining the adjustment angle according to the consistency between the image detection information and the preset reference image information;

[0010] Calculate the angle vector deviation value according to the adjustment angle and the preset reference angle;

[0011] Controlling a preset image detection device to rotate and adjust according to the angle vector deviation value, and reacquiring heat detection information and image detection information;

[0012] Determine the heat distribution location based on the image detection information and the heat detection information;

[0013] At the heat distribution location, the estimated emission is determined based on the image detection information and the preset carbon emission device characteristics;

[0014] Calculate the difference between the total carbon emissions and the estimated emissions and use it as the vehicle’s carbon emissions;

[0015] Upload the car's carbon emissions to the preset carbon emissions detection platform and output the preset prompt information.

[0016] By adopting the above technical scheme, the image detection information is compared with the reference image information to correct the image detection information, and the estimated emissions corresponding to the carbon emission devices on the road are determined by the image detection information. The carbon emissions of the car are then calculated and output based on the estimated emissions. This can eliminate the carbon emissions generated by other devices on the road, and record and upload the carbon emissions generated by cars on the road, thereby improving the accuracy of detecting car carbon emissions.

[0017] Optional verification methods for estimated emissions include:

[0018] Select a frame from the image detection information according to the preset vegetation features, and define the selected position as the vegetation position;

[0019] Determine the shadow coverage area and light coverage area based on vegetation position and image detection information;

[0020] Obtain location information and season information corresponding to the location information;

[0021] Determine the vegetation type and color corresponding to the vegetation location based on vegetation characteristics and seasonal information;

[0022] Determine carbon absorption by shaded vegetation based on shaded area and seasonal information;

[0023] Determine the carbon absorption of light vegetation based on light coverage area and seasonal information;

[0024] The sum of carbon absorption by shaded vegetation and carbon absorption by light vegetation is calculated as the total carbon absorption by vegetation;

[0025] Determine vegetation carbon uptake correction based on vegetation type and seasonal information;

[0026] Determine dust coverage information based on image detection information and vegetation color;

[0027] Determine vegetation cover absorption correction based on dust cover information and vegetation type;

[0028] The total carbon absorption of vegetation is updated according to the product of the total carbon absorption of vegetation, the correction of carbon absorption of vegetation and the correction of absorption of vegetation cover;

[0029] The difference between the estimated emissions and the updated total carbon uptake by vegetation is calculated to update the estimated emissions.

[0030] By adopting the above technical solution, the estimated carbon emissions can be corrected at different time periods based on the vegetation around the road surface, thereby improving the accuracy of the estimated carbon emissions and further improving the accuracy of detecting automobile carbon emissions.

[0031] Optionally, the verification method before uploading the vehicle carbon emissions to the carbon emissions detection platform includes:

[0032] Obtain the car model and the driving speed of the car in the image detection information;

[0033] Get the fuel consumption of the car per unit time according to the car model;

[0034] Get the tire pressure value of the car;

[0035] Determine the base deformation distance of the tire according to the vehicle model and tire pressure value;

[0036] Determine the actual deformation distance based on the image detection information and the preset tire features;

[0037] Determine the deformation deviation value according to the reference deformation distance and the actual deformation distance;

[0038] Determine the added weight value according to the deformation deviation value;

[0039] Determine the base vehicle weight value according to the vehicle model;

[0040] Calculate the sum of the base vehicle weight value and the added weight value and use it as the running weight value;

[0041] According to the driving weight value, the actual fuel consumption per unit time and the actual carbon emission corresponding to the actual fuel consumption are determined;

[0042] The actual carbon emissions are taken as the vehicle’s carbon emissions and uploaded to the carbon emissions detection platform.

[0043] By adopting the above technical solution, the fuel consumption corresponding to different cars in the image detection information is detected, and the weight of the car is determined by the deformation of the corresponding tires of the car. The total fuel consumption of the car is then corrected according to the weight of the car, and the carbon emissions of the car are calculated and uploaded, thereby reducing the impact of different car weights on the carbon emissions of the car, thereby improving the accuracy of detecting the carbon emissions of the car.

[0044] Optionally, the verification method before uploading the automobile carbon emissions to the carbon emissions detection platform also includes:

[0045] According to the comparison between the actual carbon emissions and the carbon emissions of the vehicle, the actual carbon emissions are determined as the carbon emissions of the vehicle and uploaded to the carbon emission detection platform or the weight detection information of the vehicle is obtained;

[0046] Determine tire deformation distance based on weight detection information and tire pressure value;

[0047] Determine whether to complete adjustment or output prompt information according to the comparison between the tire deformation distance and the actual deformation distance;

[0048] Update the actual fuel consumption per unit time based on the weight detection information;

[0049] The vehicle carbon emissions are updated according to the updated actual fuel consumption and uploaded to the carbon emissions detection platform.

[0050] By adopting the above technical solution, the tire deformation distance corresponding to the actual weight of the car is compared with the actual deformation distance to know the abnormality of the tire, and the carbon emissions of the car are re-detected and uploaded based on the actual weight of the car, thereby reducing the impact of tire abnormalities on the carbon emissions of the car, thereby improving the accuracy of detecting the carbon emissions of the car.

[0051] Optionally, the verification method before uploading the automobile carbon emissions to the carbon emissions detection platform also includes:

[0052] Determine the driving position of the car based on the image detection information;

[0053] Determine the slope position according to the driving position and obtain the speed information of the vehicle engine;

[0054] Determine the fuel consumption per unit time based on the speed information;

[0055] Determine the slope factor based on the slope location;

[0056] Update the slope fuel consumption according to the slope fuel consumption and the slope coefficient;

[0057] The slope carbon emissions are calculated based on the updated slope fuel consumption through a preset calculation database, and the slope carbon emissions are uploaded to the carbon emission detection platform as the vehicle's carbon emissions.

[0058] By adopting the above technical solution, the slope carbon emissions are determined by the corresponding fuel consumption when a car is driving on a sloped road and uploaded to the carbon emission detection platform as the car's carbon emissions, thereby reducing the impact of the slope on the car's carbon emissions and improving the accuracy of detecting the car's carbon emissions.

[0059] Optionally, the verification method before uploading the automobile carbon emissions to the carbon emissions detection platform also includes:

[0060] Determine the gap parameters according to the image detection information and the preset gap characteristics;

[0061] Determine the slip area based on the comparison between the gap parameter and the preset reference gap parameter;

[0062] Determine the slip coefficient based on the clearance parameters;

[0063] Determine the vehicle's slippage fuel consumption based on the slip coefficient and actual fuel consumption;

[0064] Determine the carbon emissions from skidding according to the vehicle's skidding fuel consumption and a preset calculation database, and use the carbon emissions from skidding as the vehicle's carbon emissions and upload them to the carbon emission detection platform;

[0065] A three-dimensional road surface model is established based on the image detection information and compared with a preset benchmark reference model to determine the concave-convex parameters;

[0066] Determine the repair coordinates based on the slip coefficient and slip area;

[0067] Determine whether the slip area is concave based on the concave-convex parameters;

[0068] If the slip area is not a concave surface, the tapping depth is determined according to the concave-convex parameters and the preset reference concave depth;

[0069] Determine the value of the knocking force according to the knocking depth;

[0070] Controlling a preset knocking device to knock the slipping area according to the knocking force value and the repair coordinates;

[0071] If the slip area is concave, the filling height is determined according to the concave-convex parameters and the filling device preset on the beating device is controlled to pave it flat, and the slip coefficient is re-determined;

[0072] According to the comparison between the re-determined slip coefficient and the preset reference slip coefficient, it is determined that the adjustment or update of the repair coordinates is completed and the preset knocking device is controlled to knock the slip area.

[0073] By adopting the above technical scheme, the slip coefficient corresponding to the slip area on the road surface is used to update the automobile carbon emissions and upload it, and the slip coefficient of the slip area is reduced through the uneven conditions corresponding to the slip area, thereby reducing the impact of road slippage on automobile carbon emissions and reducing the impact of the slip area on the carbon emissions of subsequent vehicles.

[0074] Optionally, the specific steps after determining the slip coefficient according to the gap parameter also include:

[0075] Get the road surface humidity value of the road surface;

[0076] Determine the rain state or ice and snow state of the road surface according to the road surface humidity value, image detection information and preset rain and snow characteristics;

[0077] If it is snowing, the snowfall speed of the car is obtained;

[0078] Determine snow fuel consumption based on snow driving speed;

[0079] Update the slip coefficient according to the road surface humidity value;

[0080] Update snowfall fuel consumption according to snowfall fuel consumption and slip coefficient;

[0081] Determine the snowfall carbon emissions based on the updated snowfall fuel consumption and the preset calculation database, and upload the snowfall carbon emissions as the vehicle carbon emissions to the carbon emission detection platform;

[0082] If it is in the raining state, the raining driving speed of the car is obtained;

[0083] Update the slip coefficient according to the road surface humidity value;

[0084] Determine the rainfall fuel consumption based on the driving speed in rainfall;

[0085] Update the rainfall fuel consumption according to the rainfall fuel consumption and the rainfall coefficient;

[0086] The rainfall carbon emissions are determined based on the updated rainfall fuel consumption and the preset calculation database, and the rainfall carbon emissions are uploaded to the carbon emission detection platform as the vehicle carbon emissions.

[0087] By adopting the above technical solution, the speed of the road surface in rainy and snowy weather and the slippage of the car in rainy and snowy weather are determined, and the car's carbon emissions are updated and uploaded, thereby reducing the impact of road slippage in rainy and snowy weather on the car's carbon emissions.

[0088] Optionally, the calculation method corresponding to the calculation database includes:

[0089] V CO2 ≈a×n×Δr b × c ×ρ 汽 ×M CO2 ×Q CO2 , V CO2 is the hourly carbon dioxide emission of the car, a is the displacement of the car, Δr is the speed of the car, b is the coefficient of the car that has been tested in advance, w is the load number corresponding to the weight of the car in advance, c is the reference coefficient of the car in advance, ρ 汽 is the density of gasoline, M CO2 is the percentage of carbon content in gasoline, Q CO2 The amount of carbon dioxide gas produced corresponding to the carbon content in gasoline.

[0090] In the second aspect, the present application provides a system for detecting traffic carbon emissions, which adopts the following technical solution:

[0091] A traffic carbon emission detection system, comprising:

[0092] An acquisition module is used to obtain the total carbon emissions, heat detection information, image detection information, location information, season information, vehicle model, driving speed, tire pressure value, weight detection information, speed information, road humidity value, snowfall driving speed, and rainfall driving speed;

[0093] A memory for storing a program for a method for detecting traffic carbon emissions;

[0094] The program in the memory can be loaded and executed by the processor to implement a method for detecting traffic carbon emissions.

[0095] In a third aspect, the present application provides a smart terminal, which adopts the following technical solution:

[0096] An intelligent terminal comprises a memory and a processor. The memory stores a computer program which can be loaded and executed by the processor for a method for detecting traffic carbon emissions.

[0097] In summary, the present application includes at least one of the following beneficial technical effects:

[0098] 1. Compare the image detection information with the reference image information to correct the image detection information, and determine the estimated emissions corresponding to the carbon emission devices on the road through the image detection information, and then calculate the carbon emissions of the car through the estimated emissions and output them, so as to exclude the carbon emissions generated by other devices on the road, and record and upload the carbon emissions generated by the car on the road, thereby improving the accuracy of detecting the carbon emissions of the car;

[0099] 2. The estimated carbon emissions can be corrected at different time periods by the vegetation around the road surface, thereby improving the accuracy of the estimated carbon emissions and further improving the accuracy of detecting automobile carbon emissions;

[0100] 3. The fuel consumption corresponding to different cars in the image detection information is detected, and the weight of the car is determined by the deformation of the corresponding tires of the car. The total fuel consumption of the car is then corrected according to the weight of the car, and the carbon emissions of the car are calculated and uploaded, thereby reducing the impact of different car weights on the carbon emissions of the car, thereby improving the accuracy of detecting car carbon emissions. BRIEF DESCRIPTION OF THE DRAWINGS

[0101] Figure 1 is a flow chart of a method for detecting traffic carbon emissions according to an embodiment of the present invention;

[0102] Figure 2 is a method flow chart of a method for verifying estimated emissions according to an embodiment of the present invention;

[0103] Figure 3 This is the method flow of the verification method of the automobile carbon emissions before uploading to the carbon emissions detection platform in the embodiment of the present invention Figure 1 ;

[0104] Figure 4 This is the method flow of the verification method of the automobile carbon emissions before uploading to the carbon emissions detection platform in the embodiment of the present invention Figure 2 ;

[0105] Figure 5 This is the method flow of the verification method of the automobile carbon emissions before uploading to the carbon emissions detection platform in the embodiment of the present invention Figure 3 . DETAILED DESCRIPTION

[0106] The following is combined with Figures 1 to 5 The present invention is further described in detail with examples.

[0107] Reference Figure 1 The present application embodiment discloses a method for detecting traffic carbon emissions, comprising the following steps:

[0108] Step S100: Obtaining the total amount of carbon emissions, heat detection information, and image detection information on the road surface.

[0109] The total carbon emission refers to the total amount of carbon dioxide emitted on the road surface, and the parameter detected by the carbon dioxide sensor preset on the road surface is used as the total carbon emission. The heat detection information refers to the information on the heat generated on the road surface, and the parameter detected by the heat sensor preset on the road surface is used as the heat detection information. The image detection information refers to the image information on the road surface, and the image obtained by shooting the image detection device preset on the road surface is used as the image detection information. In this embodiment, the image detection device can be a camera. The range detected by the heat sensor is the same as that of the camera.

[0110] Step S101: determining whether the adjustment is completed or determining the adjustment angle according to the consistency between the image detection information and the preset reference image information.

[0111] The reference image information refers to the image taken when the road surface is just repaired, which is formed by the operator taking and storing it in advance. The adjustment angle refers to the angle of the camera on the road surface after adjustment. When the image detection information is consistent with the reference image information, it means that the camera on the road surface is not offset, and no adjustment is made and detection continues. When the image detection information is inconsistent with the reference image information, it means that the camera on the road surface is offset, and the angle of the line offset between the image detection information and the reference image information is used as the adjustment angle.

[0112] Step S102: Calculate an angle vector deviation value according to the adjustment angle and a preset reference angle.

[0113] The reference angle refers to the angle of the camera pre-installed on the road surface, which is set and stored by the operator in advance. The angle vector deviation value refers to the vector deviation value between the adjustment angle and the reference angle, and the difference between the adjustment angle and the reference angle is calculated and used as the angle vector deviation value.

[0114] Step S103: controlling a preset image detection device to perform rotation adjustment according to the angle vector deviation value, and reacquiring heat detection information and image detection information.

[0115] By controlling a preset image detection device to perform rotation adjustment with an angle vector deviation value and reacquiring heat detection information and image detection information, the carbon emissions of the automobile within the range of the image detection information can be correctly calculated.

[0116] Step S104: determining the heat distribution position according to the image detection information and the heat detection information.

[0117] The heat distribution position refers to the distribution position of the heat corresponding to the image detection information, and the position corresponding to the heat detection information is marked in the image detection information as the heat distribution position.

[0118] Step S105: at the heat distribution position, determine the estimated emission amount according to the image detection information and the preset carbon emission device characteristics.

[0119] The carbon emission device feature refers to other devices that can produce carbon dioxide other than automobiles, which are pre-set and stored by the operator. The estimated emissions refer to the total emissions of carbon dioxide estimated to be produced by other devices on the road other than automobiles. The estimated emissions are determined from the preset heat database by marking the carbon emission device at the heat distribution position and the heat generated by the carbon emission device. The heat database stores the estimated carbon emissions corresponding to the heat generated by different carbon emission devices. The heat database is manually set and will not be described here.

[0120] Step S106: Calculate the difference between the total carbon emissions and the estimated emissions and use it as the carbon emissions of the vehicle.

[0121] Automobile carbon emissions refer to the carbon emissions generated when a car is driving on the road. The difference between the total carbon emissions and the estimated emissions is calculated and used as the automobile carbon emissions.

[0122] Step S107: Upload the automobile carbon emissions to a preset carbon emissions detection platform and output preset prompt information.

[0123] The carbon emission detection platform refers to a platform used to record and store the carbon emissions generated by the car when it is driving, which is formed after the operator pre-sets and stores it. Prompt information refers to information used to prompt the carbon emissions of the road surface and the abnormality of the car, which is formed after the operator pre-sets and stores it. The carbon emissions of the car are uploaded to the carbon emission detection platform and the prompt information is output.

[0124] exist Figure 1 In step S105, in order to further ensure the rationality of the verification method of the estimated emission, it is necessary to further analyze and calculate the verification method of the estimated emission. Figure 2 The steps shown are explained in detail.

[0125] Reference Figure 2 , the verification methods for estimated emissions include:

[0126] Step S200: selecting a frame from the image detection information according to preset vegetation features, and defining the selected position as a vegetation position.

[0127] Vegetation features refer to the features of vegetation on the road surface, which are set and stored by the operator in advance. Vegetation positions refer to the positions where vegetation exists on the road surface. The positions where vegetation features exist are selected from the image detection information as vegetation positions.

[0128] Step S201: determining the shadow coverage area and the light coverage area according to the vegetation position and the image detection information.

[0129] The shadow coverage area refers to the area of ​​vegetation covered by shadows on the road surface, and the light coverage area refers to the area of ​​vegetation covered by sunlight on the road surface. The size parameters of vegetation covered by shadows and vegetation covered by sunlight are selected through the image detection information frame, and the areas corresponding to the size parameters of shadows and sunlight are calculated as the shadow coverage area and light coverage area.

[0130] Step S202: Acquire location information and season information corresponding to the location information.

[0131] The location information refers to the longitude and latitude corresponding to the carbon dioxide detection on the road surface, and the season information refers to the temperature and humidity of the season corresponding to the location information. The location corresponding to the image detection device on the road surface is located by GPS as the location information, and the season corresponding to the location information is queried through the network as the season information.

[0132] Step S203: Determine the vegetation type and vegetation color corresponding to the vegetation position according to the vegetation characteristics and season information.

[0133] Vegetation type refers to the type of vegetation on the road surface. The type of vegetation corresponding to the vegetation features identified by the image detection information is used as the vegetation type. Vegetation color refers to the color of vegetation on the road surface in different seasons. The color corresponding to the vegetation type in the seasonal information is used as the vegetation color.

[0134] Step S204: determining the carbon absorption amount of the shadow vegetation according to the shadow coverage area and season information.

[0135] The carbon absorption of shadow vegetation refers to the amount of carbon dioxide absorbed by vegetation under the shadow of the road surface. The carbon absorption of shadow vegetation is matched from the preset plant database through the shadow coverage area and season information. The plant database pre-stores the carbon absorption of vegetation corresponding to different plants in different seasons under sunlight or shadow coverage. The plant database is artificially set and will not be described here.

[0136] Step S205: determining the light vegetation carbon absorption amount according to the light coverage area and season information.

[0137] The carbon absorption of light vegetation refers to the amount of carbon dioxide absorbed by vegetation under sunlight on the road surface. The carbon absorption of light vegetation is matched from the plant database through the light coverage area and seasonal information.

[0138] Step S206: Calculate the sum of the carbon absorption amount of the shadow vegetation and the carbon absorption amount of the light vegetation as the total carbon absorption amount of the vegetation.

[0139] The total amount of carbon absorption by vegetation refers to the total amount of carbon dioxide absorbed by vegetation on the road surface. The total amount of carbon absorption by vegetation is calculated as the sum of the carbon absorption by shadow vegetation and the carbon absorption by light vegetation.

[0140] Step S207: Determine the vegetation carbon absorption correction amount according to vegetation type and season information.

[0141] The vegetation carbon absorption correction refers to the parameters for correcting the total amount of vegetation carbon absorption corresponding to different vegetation types. The corresponding parameters are matched from the preset correction database through vegetation type and season information as the vegetation carbon absorption correction. The correction database stores the correction values ​​of carbon absorption corresponding to different vegetation in different seasons and different degrees of dust coverage, and also stores the carbon emission correction values ​​of cars corresponding to different slopes, degrees of road slippage, and rainy and snowy weather. The correction database is set manually and will not be described in detail here.

[0142] Step S208: Determine dust coverage information according to the image detection information and the vegetation color.

[0143] The dust coverage information refers to information on the degree of dust coverage on vegetation on the road surface. The degree of dust coverage is obtained by performing color comparison between the image detection information and the vegetation color as the dust coverage information.

[0144] Step S209: determining the vegetation cover absorption correction amount according to the dust cover information and the vegetation type.

[0145] The vegetation cover absorption correction refers to the parameter for correcting the total amount of vegetation carbon absorption when dust exists on the vegetation on the road surface. The vegetation cover absorption correction is matched from the correction database through dust cover information and vegetation type.

[0146] Step S210: updating the total carbon absorption amount of vegetation according to the product of the total carbon absorption amount of vegetation and the correction amount of carbon absorption of vegetation and the correction amount of absorption of vegetation cover.

[0147] The new total vegetation carbon absorption is obtained by calculating the product of the total vegetation carbon absorption, the vegetation carbon absorption correction and the vegetation cover absorption correction.

[0148] Step S211: Calculate the difference between the estimated emission and the updated total vegetation carbon absorption to update the estimated emission.

[0149] By calculating the difference between the estimated emissions and the updated total vegetation carbon uptake as the new estimated emissions, the impact of plants on the deviation of estimated emissions can be reduced, thereby improving the accuracy of automobile carbon emissions.

[0150] exist Figure 1 In step S107, in order to further ensure the rationality of the verification method before the vehicle carbon emissions are uploaded to the carbon emissions detection platform, it is necessary to further analyze and calculate the verification method before the vehicle carbon emissions are uploaded to the carbon emissions detection platform. Figure 3 The steps shown are explained in detail.

[0151] Reference Figure 3 , the verification methods before uploading the automobile carbon emissions to the carbon emissions detection platform include:

[0152] Step S300: Obtain the car model and the driving speed of the car in the image detection information.

[0153] The car model refers to the model corresponding to the car on the road. The car model is obtained by identifying the car license plate through image detection information and querying the car model. The driving speed refers to the speed of the car on the road. The parameters obtained by the speed sensor preset on the car are matched from the preset speed database. The speed database stores the real-time speed of different car models and the corresponding speed of the car.

[0154] Step S301: retrieve the fuel consumption of the vehicle per unit time according to the vehicle model.

[0155] The fuel consumption of a car refers to the fuel consumption of the car corresponding to the car model per unit time. The fuel consumption of the car is obtained by querying the parameters corresponding to the car model and retrieving the fuel consumption of the car per unit time.

[0156] Step S302: Obtain the tire pressure value of the vehicle.

[0157] The tire pressure value refers to the air pressure value corresponding to the tires of the car on the road. The air pressure value corresponding to the tires of the car on the road is retrieved through the car-machine interconnection system preset in the car. The car-machine interconnection system refers to the system used to record and store the parameters in the car for the convenience of subsequent retrieval of the parameters in the car, which is pre-set and stored by the operator.

[0158] Step S303: determining a reference deformation distance of the tire according to the vehicle model and the tire pressure value.

[0159] The reference deformation distance refers to the reference deformation distance of the tire under the tire pressure value corresponding to the car model on the road. The reference deformation distance is matched from the preset car database through the car model and tire pressure value. The car database stores the deformation distance of the tire corresponding to the weight of different car models when unloaded and different tire pressure values, as well as the fuel consumption per unit time corresponding to different car weights.

[0160] Step S304: determining the actual deformation distance according to the image detection information and the preset tire features.

[0161] Tire features refer to features such as the color and shape of the tire, which are preset and stored by the operator. The shape corresponding to the tire feature is identified from the image detection information, and the difference between the distance between the tire contact surface and the tire center and the tire radius is calculated as the actual deformation distance.

[0162] Step S305: determining a deformation deviation value according to the reference deformation distance and the actual deformation distance.

[0163] The deformation deviation value refers to the deviation value between the reference deformation distance and the actual deformation distance. The difference between the reference deformation distance and the actual deformation distance is calculated and used as the deformation deviation value.

[0164] Step S306: Determine the added weight value according to the deformation deviation value.

[0165] The added weight value refers to the added weight value of the car on the road, and the added weight value is matched from the car database through the deformation deviation value.

[0166] Step S307: Determine a reference vehicle weight value according to the vehicle model.

[0167] The reference vehicle weight value refers to the reference weight value of the vehicle when it is unloaded corresponding to the vehicle model. The parameters corresponding to the vehicle model are queried and the weight value of the vehicle when it is unloaded is retrieved as the reference vehicle weight value.

[0168] Step S308: Calculate the sum of the reference vehicle weight value and the added weight value and use it as the driving weight value.

[0169] The running weight value refers to the weight value of the car traveling on the road. The sum of the base car weight value and the added weight value is calculated as the running weight value.

[0170] Step S309: determining the actual fuel consumption per unit time and the actual carbon emission corresponding to the actual fuel consumption according to the driving weight value.

[0171] Actual fuel consumption refers to the fuel consumption corresponding to the actual driving of the car on the road per unit time. The actual fuel consumption is matched from the car database through the driving weight value.

[0172] Step S310: updating the vehicle carbon emissions according to the updated actual fuel consumption and uploading the vehicle carbon emissions to the carbon emissions detection platform.

[0173] The carbon emission parameters are calculated from the preset calculation database through the actual fuel consumption and the carbon emission of the vehicle is updated, and the carbon emission of the vehicle is uploaded to the carbon emission detection platform, thereby reducing the impact of different vehicle weights on the carbon emission of the vehicle. The calculation database refers to the carbon emission corresponding to the actual fuel consumption, which is specifically explained in step S800.

[0174] exist Figure 1 In step S107, in order to further ensure the rationality of the verification method before the vehicle carbon emissions are uploaded to the carbon emissions detection platform, it is necessary to further analyze and calculate the verification method before the vehicle carbon emissions are uploaded to the carbon emissions detection platform. Figure 4 The steps shown are explained in detail.

[0175] Reference Figure 4 , the verification method before uploading the automobile carbon emissions to the carbon emissions detection platform also includes:

[0176] Step S400: According to the comparison between the actual carbon emissions and the carbon emissions of the vehicle, the actual carbon emissions are determined as the carbon emissions of the vehicle and uploaded to the carbon emission detection platform or the weight detection information of the vehicle is obtained.

[0177] The weight detection information refers to the comparison between the actual carbon emissions and the carbon emissions of the car. When the actual carbon emissions are not less than the carbon emissions of the car, it means that there is no abnormality in the tire, and the actual carbon emissions are used as the carbon emissions of the car and uploaded to the carbon emission detection platform. When the actual carbon emissions are not less than the carbon emissions of the car, it means that there is an abnormality in the tire, and the weight sensor preset on the road is used to detect the corresponding car parameters as weight detection information.

[0178] Step S401: determining the tire deformation distance according to the weight detection information and the tire pressure value.

[0179] The tire deformation distance refers to the tire deformation distance corresponding to the weight detection information of the car and the tire pressure value. The tire deformation distance is matched from the car database through the weight detection information and the tire pressure value.

[0180] Step S402: determining whether the adjustment is completed or outputting prompt information according to the comparison between the tire deformation distance and the actual deformation distance.

[0181] By comparing the tire deformation distance with the actual deformation distance, when the tire deformation distance is not less than the actual deformation distance, it means that the tire is normal, and the carbon emissions of the vehicle will not be adjusted. When the tire deformation distance is less than the actual deformation distance, it means that the tire is abnormal, and a prompt message is output to prompt the driver to change the tire.

[0182] Step S403: updating the actual fuel consumption per unit time according to the weight detection information.

[0183] Actual fuel consumption refers to the actual fuel consumption of a car traveling on the road per unit time. The corresponding parameters are matched from the car database through weight detection information to update the actual fuel consumption.

[0184] Step S404: updating the vehicle carbon emissions according to the updated actual fuel consumption and uploading the vehicle carbon emissions to the carbon emissions detection platform.

[0185] The vehicle carbon emissions are updated by using the parameters calculated from the calculation database through the updated actual fuel consumption, and the vehicle carbon emissions are uploaded to the carbon emissions detection platform, thereby reducing the impact of deviations in vehicle carbon emissions caused by tire abnormalities and improving the accuracy of detecting vehicle carbon emissions.

[0186] exist Figure 1 In step S107, in order to further ensure the rationality of the verification method before the vehicle carbon emissions are uploaded to the carbon emissions detection platform, it is necessary to further analyze and calculate the verification method before the vehicle carbon emissions are uploaded to the carbon emissions detection platform. Figure 5 The steps shown are explained in detail.

[0187] Reference Figure 5 , the verification method before uploading the automobile carbon emissions to the carbon emissions detection platform also includes:

[0188] Step S500: Determine the driving position of the vehicle according to the image detection information.

[0189] The driving position refers to the position of the car on the road in the image detection information, and the position corresponding to the license plate number of the car is identified from the image detection information as the driving position.

[0190] Step S501: Determine the slope position according to the driving position and obtain the speed information of the vehicle engine.

[0191] The slope position refers to the position of the slope of the road on which the car is driving. The slope position is determined by the driving position falling into the preset slope range. When the driving position falls into the slope range, it means that the car is driving on the slope, and the driving position is used as the slope position. The slope range refers to the range corresponding to the uphill or downhill on the road, which is pre-set and stored by the operator. The speed information refers to the information of the car speed corresponding to the car speed when the car is driving on the slope position. The parameters detected by the speed sensor preset on the car are used as the speed information.

[0192] Step S502: Determine the slope fuel consumption per unit time according to the speed information.

[0193] Slope fuel consumption refers to the fuel consumption of a car when it travels uphill or downhill on a road per unit time. The slope fuel consumption is matched from the speed database through the speed information.

[0194] Step S503: Determine the slope coefficient according to the slope position.

[0195] The slope coefficient refers to the correction coefficient corresponding to different slopes when a car is driving uphill or downhill on the road. The slope coefficient is matched from the preset correction database according to the slope position.

[0196] Step S504: updating the slope fuel consumption according to the slope fuel consumption and the slope coefficient.

[0197] By calculating the product value between the slope fuel consumption and the slope coefficient, and using the parameter corresponding to the product value to update the slope fuel consumption, the influence of deviation on the fuel consumption of the vehicle when the vehicle is driving uphill or downhill on the road can be corrected.

[0198] Step S505: Calculate the slope carbon emissions according to the updated slope fuel consumption through a preset calculation database, and upload the slope carbon emissions as the vehicle carbon emissions to the carbon emission detection platform.

[0199] Slope carbon emissions refer to the carbon emissions of a car when it is driving on uphill and downhill roads. The updated slope fuel consumption is calculated using parameters from a preset calculation database as the slope carbon emissions. The specific calculation steps refer to step S800, and the slope carbon emissions are uploaded to the carbon emission detection platform as the car's carbon emissions, thereby reducing the impact of the slope on the deviation of the car's carbon emissions, thereby improving the accuracy of detecting the car's carbon emissions.

[0200] exist Figure 1 In step S107 shown, in order to further ensure the rationality of the verification method before the automobile carbon emissions are uploaded to the carbon emissions detection platform, it is necessary to perform further separate analysis and calculation on the verification method before the automobile carbon emissions are uploaded to the carbon emissions detection platform.

[0201] The verification method before uploading the vehicle carbon emissions to the carbon emissions detection platform also includes:

[0202] Step S600: determining gap parameters according to image detection information and preset gap features.

[0203] Gap features refer to the features corresponding to irregularly shaped holes on the road surface, which are pre-set and stored by the operator. Gap parameters refer to the shape, size, and distance between gaps on the road surface. The gaps are identified from the image detection information through gap features, and the shape, size, and distance between gaps are calculated as gap parameters after selecting the image.

[0204] Step S601: Determine the slip area based on the comparison between the gap parameter and the preset reference gap parameter.

[0205] The reference gap parameter refers to the reference parameters such as the shape, size and distance between each gap corresponding to the gap on the road surface, which are preset and stored by the operator. The slip area refers to the area on the road surface where slipping occurs. The gap parameter is compared with the reference gap parameter. When the gap parameter is not greater than the reference gap parameter, it means that the car is not likely to slip on the road surface. When the gap parameter is greater than the reference gap parameter, it means that the car is likely to slip on the road surface. The area on the road surface where the gap parameter is greater than the reference gap parameter is regarded as the slip area.

[0206] Step S602: Determine the slip coefficient according to the clearance parameter.

[0207] The slip coefficient refers to the correction coefficient of carbon emissions corresponding to when a car slips on the road. The slip coefficient is matched from the correction database through the gap parameters.

[0208] Step S603: Determine the vehicle's slippage fuel consumption according to the slip coefficient and the actual fuel consumption.

[0209] The skidding fuel consumption of a car refers to the fuel consumption corresponding to the car skidding on the road per unit time. The product of the slip coefficient and the actual fuel consumption is calculated and used as the skidding fuel consumption of the car.

[0210] Step S604: Determine the carbon emissions due to skidding according to the fuel consumption due to skidding of the vehicle and a preset calculation database, and use the carbon emissions due to skidding as the carbon emissions of the vehicle and upload it to the carbon emission detection platform.

[0211] Skidding carbon emissions refer to the carbon emissions generated when a car skids on the road. The parameters calculated by the car's skidding fuel consumption through a preset calculation database are used as the skidding carbon emissions. The specific calculation method is described in step S800, and the skidding carbon emissions are used as the car's carbon emissions and uploaded to the carbon emission detection platform, thereby reducing the impact of road skidding on the data deviation of the car's carbon emissions.

[0212] Step S605: Establish a three-dimensional road surface model based on the image detection information and compare it with a preset benchmark reference model to determine the concave-convex parameters.

[0213] The road surface three-dimensional model refers to a three-dimensional virtual model of the road surface, which is formed by inputting parameters such as the road surface and the gaps on the road surface in the image detection information into a preset simulation system to form a model as the road surface three-dimensional model. The benchmark reference model refers to a benchmark three-dimensional virtual model used for comparison and reference of the road surface, which is formed by pre-outputting parameters such as the road surface and the gaps on the road surface in the benchmark image information and inputting them into a preset simulation system to form a model as the benchmark three-dimensional virtual model. The simulation system refers to the simulation software used to establish a three-dimensional virtual model. The bump parameter refers to the deviation value parameter of the bump of the road surface, which is calculated by comparing the parameters corresponding to the three-dimensional road surface model with the benchmark reference model and calculating the deviation value of each parameter as the bump parameter.

[0214] Step S606: Determine the repair coordinates according to the slip coefficient and the slip area.

[0215] The repair coordinates refer to the position coordinates of the repaired road slip area. The repair range is determined by the slip area, and the slip coefficient is matched to the repair coordinates from the preset repair database. The repair database stores the repair coordinates corresponding to different slip coefficients, and also stores the force values ​​of the knocking device corresponding to different knocking depths. The knocking device refers to an unmanned vehicle equipped with nails and uses the nails to knock the slip area to increase the friction of the road surface. The repair database is set manually and will not be described in detail here.

[0216] Step S607: Determine whether the slip area is a concave surface according to the concave-convex parameters.

[0217] The positive and negative conditions of the concave-convex parameter are used to determine whether the slipping area is concave. When the concave-convex parameter is positive, it indicates that the slipping area is not concave. When the concave-convex parameter is negative, it indicates that the slipping area is concave.

[0218] Step S608: If the slipping area is not a concave surface, the tapping depth is determined according to the concave-convex parameter and a preset reference concave depth.

[0219] The knocking depth refers to the depth of the preset knocking device knocking on the slipping area. The reference depression depth refers to the reference depression depth corresponding to the knocking device knocking on the slipping area, which is set and stored in advance by the operator. When the slipping area is not concave, it means that it can be knocked directly, and the sum of the concave-convex parameter and the reference depression depth is calculated and used as the knocking depth.

[0220] Step S609: Determine the tapping force value according to the tapping depth.

[0221] The knocking force value refers to the force value corresponding to when the knocking device knocks the slipping area, and the knocking force value is matched from the repair database according to the knocking depth.

[0222] Step S610: controlling a preset tapping device to tap the slipping area according to the tapping force value and the repair coordinates.

[0223] The friction force of the slipping area can be repaired by controlling the knocking device to knock the slipping area with the knocking force value and the repair coordinates.

[0224] Step S611: If the slip area is a concave surface, the filling height is determined according to the concave-convex parameters and the filling device preset on the beating device is controlled to level it, and the slip coefficient is re-determined.

[0225] The filling device refers to an unmanned vehicle used to fill the road surface. The filling height refers to the height corresponding to the slipping area. When the slipping area is concave, it means that the road surface needs to be filled. The value corresponding to the concave and convex parameters is used as the filling height, and the slipping area is paved at the filling height, and the image gap information is re-acquired, and the gap parameters and slip coefficient in the slipping area are re-determined.

[0226] Step S612: Determine the completion of adjusting or updating the repair coordinates based on the comparison between the re-determined slip coefficient and the preset reference slip coefficient, and control the preset tapping device to tap the slip area.

[0227] The reference slip coefficient refers to the reference coefficient of the slip area corresponding to the reference gap parameter, which is set in advance by the operator and stored. When the slip coefficient is not less than the reference slip coefficient, it means that the car is not easy to slip after the slip area is paved, and the tapping device is not controlled to tap. When the slip coefficient is less than the reference slip coefficient, it means that the car is still easy to slip after the slip area is paved, and the parameters matched from the repair database are updated by the re-determined slip coefficient to update the repair coordinates and control the tapping device to tap, so as to reduce the impact of road slip on the data deviation of automobile carbon emissions and reduce the impact of slip in the slip area on subsequent automobile driving.

[0228] In step S602 shown above, in order to further ensure the rationality of the specific steps after determining the slip coefficient according to the gap parameters, it is necessary to perform further separate analysis and calculation on the specific steps after determining the slip coefficient according to the gap parameters, which is explained in detail through the steps shown below.

[0229] The specific steps after determining the slip coefficient based on the gap parameters include:

[0230] Step S700: Obtain the road surface humidity value of the road surface.

[0231] The road surface humidity value refers to the humidity value of the road surface in the image detection information, and is a parameter obtained by detecting a humidity sensor preset within the shooting range of the image detection information as the road surface humidity value.

[0232] Step S701: Determine the rain state or ice and snow state of the road surface according to the road surface humidity value, image detection information and preset rain and snow characteristics.

[0233] Rain and snow features refer to features such as rain, snowflakes or hail, which are preset and stored by the operator. Rainfall status refers to the state where there is rain on the road surface in the image detection information, and ice and snow status refers to the state where there is snowfall or hail on the road surface in the image detection information. Rain and snow features are identified through image detection information, and different road humidity values ​​of rain and snow are correspondingly combined to determine the rain state or ice and snow state of the road surface.

[0234] Step S702: If it is snowing, the snowfall driving speed of the vehicle is obtained.

[0235] Snowfall driving speed refers to the driving speed of a car when snow falls on the road. When snow falls on the road, the speed parameter detected by the speed sensor preset on the car and converted by the speed corresponding to the car model is used as the snowfall driving speed.

[0236] Step S703: Determine the snowfall fuel consumption according to the snowfall driving speed.

[0237] Snowfall fuel consumption refers to the fuel consumption of a car when snow falls on the road. The snowfall fuel consumption is matched from the speed database through the snowfall driving speed.

[0238] Step S704: Update the slip coefficient according to the road surface humidity value.

[0239] The slip coefficient is updated by matching the parameters from the correction database using the road surface humidity value, thus facilitating subsequent analysis.

[0240] Step S705: Update the snowfall fuel consumption according to the snowfall fuel consumption and the slip coefficient.

[0241] The snowfall fuel consumption is updated by calculating the product of the snowfall fuel consumption and the slip coefficient, which facilitates subsequent analysis.

[0242] Step S706: Determine the snowfall carbon emissions according to the updated snowfall fuel consumption and the preset calculation database, and upload the snowfall carbon emissions as the vehicle carbon emissions to the carbon emission detection platform.

[0243] Snowfall carbon emissions refer to the carbon emissions generated when snow falls on the road. The updated snowfall fuel consumption is calculated through the calculation database to obtain the snowfall carbon emissions, and the snowfall carbon emissions are uploaded to the carbon emission detection platform as the car's carbon emissions, thereby reducing the impact of data deviation caused by slippery road conditions in snowy weather on car carbon emissions.

[0244] Step S707: If it is raining, the driving speed of the vehicle during raining is obtained.

[0245] Rainfall driving speed refers to the driving speed of the car when it is raining on the road. When it is raining on the road, the speed parameter detected by the speed sensor preset on the car and converted by the speed corresponding to the car model is used as the rainfall driving speed.

[0246] Step S708: Update the slip coefficient according to the road surface humidity value.

[0247] The slip coefficient is updated by matching the parameters from the correction database using the road surface humidity value, thus facilitating subsequent analysis.

[0248] Step S709: Determine the rainfall fuel consumption according to the driving speed during rainfall.

[0249] Rainfall fuel consumption refers to the fuel consumption of a car when it rains on the road. The rainfall fuel consumption is matched from the speed database through the driving speed during rainfall.

[0250] Step S710: updating the rainfall fuel consumption according to the rainfall fuel consumption and the rainfall coefficient.

[0251] The fuel consumption due to snowfall is updated by calculating the product of the fuel consumption due to snowfall and the slip coefficient, which facilitates subsequent analysis.

[0252] Step S711: determine the rainfall carbon emissions according to the updated rainfall fuel consumption and the preset calculation database, and upload the rainfall carbon emissions as the vehicle carbon emissions to the carbon emission detection platform.

[0253] Rainfall carbon emissions refer to the carbon emissions generated when it rains on the road. The updated rainfall fuel consumption is used to calculate the rainfall carbon emissions through the calculation database, and the rainfall carbon emissions are uploaded to the carbon emission detection platform as the vehicle carbon emissions, thereby reducing the impact of road slippery conditions in rainy weather on data deviations in vehicle carbon emissions.

[0254] exist Figure 5 In step S505 shown, in order to further ensure the rationality of the calculation method corresponding to the calculation database, it is necessary to perform further separate analysis and calculation on the calculation method corresponding to the calculation database, which is specifically described in detail through the following steps.

[0255] The calculation methods corresponding to the calculation database include:

[0256] Step S800: is the hourly carbon dioxide emission of the car, a is the displacement of the car, Δr is the speed of the car, b is the coefficient of the car that has been tested in advance, w is the load number corresponding to the weight of the car in advance, c is the reference coefficient of the car in advance, ρ 汽 is the density of gasoline, is the percentage of carbon content in gasoline, The amount of carbon dioxide gas produced corresponding to the carbon content in gasoline.

[0257] It is known that the experimental parameter a is usually set to 0.0015, the displacement n of the car is obtained by querying the car model, the car speed Δr is obtained in real time by the speed sensor, the coefficient b is obtained by the car through experiments in advance, the load w increases as the car speed increases, the reference coefficient c is usually set to 1.2, and the density ρ of gasoline 汽 Generally 0.75kg / L, the percentage of carbon content in gasoline Generally 85%, the amount of carbon dioxide produced corresponding to the carbon content in gasoline Generally The experimental parameters a, coefficient b, reference coefficient c and the corresponding parameters are obtained after the staff conducts experiments based on the workload w.

[0258] Based on the same inventive concept, an embodiment of the present invention provides a system for detecting traffic carbon emissions, including:

[0259] An acquisition module is used to obtain the total carbon emissions, heat detection information, image detection information, location information, season information, vehicle model, driving speed, tire pressure value, weight detection information, speed information, road humidity value, snowfall driving speed, and rainfall driving speed;

[0260] A memory for storing a program for a method for detecting traffic carbon emissions;

[0261] The program in the memory can be loaded and executed by the processor to implement a method for detecting traffic carbon emissions.

[0262] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0263] Based on the same inventive concept, an embodiment of the present invention provides an intelligent terminal, including a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and execute a method for detecting traffic carbon emissions.

[0264] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0265] The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should also be regarded as the protection scope of the present invention.

Claims

1. A method for detecting traffic carbon emissions, characterized in that: include: Obtain the total carbon emissions, heat detection information and image detection information on the road surface; Determining the completion of adjustment or determining the adjustment angle according to the consistency between the image detection information and the preset reference image information; Calculate the angle vector deviation value according to the adjustment angle and the preset reference angle; Controlling a preset image detection device to rotate and adjust according to the angle vector deviation value, and reacquiring heat detection information and image detection information; Determine the heat distribution location based on the image detection information and the heat detection information; At the heat distribution location, the estimated emission is determined based on the image detection information and the preset carbon emission device characteristics; Calculate the difference between the total carbon emissions and the estimated emissions and use it as the vehicle’s carbon emissions; Upload the car's carbon emissions to the preset carbon emissions detection platform and output the preset prompt information.

2. A method for detecting traffic carbon emissions according to claim 1, characterized in that: Methods for verifying estimated emissions include: Select a frame from the image detection information according to the preset vegetation features, and define the selected position as the vegetation position; Determine the shadow coverage area and light coverage area based on vegetation position and image detection information; Obtain location information and season information corresponding to the location information; Determine the vegetation type and color corresponding to the vegetation location based on vegetation characteristics and seasonal information; Determine carbon absorption by shaded vegetation based on shaded area and seasonal information; Determine the carbon absorption of light vegetation based on light coverage area and seasonal information; The sum of carbon absorption by shaded vegetation and carbon absorption by light vegetation is calculated as the total carbon absorption by vegetation; Determine vegetation carbon uptake correction based on vegetation type and seasonal information; Determine dust coverage information based on image detection information and vegetation color; Determine vegetation cover absorption correction based on dust cover information and vegetation type; The total carbon absorption of vegetation is updated according to the product of the total carbon absorption of vegetation, the correction of carbon absorption of vegetation and the correction of absorption of vegetation cover; The difference between the estimated emissions and the updated total carbon uptake by vegetation is calculated to update the estimated emissions.

3. A method for detecting traffic carbon emissions according to claim 1, characterized in that: The verification methods before uploading the automobile carbon emissions to the carbon emissions testing platform include: Obtain the car model and the driving speed of the car in the image detection information; Get the fuel consumption of the car per unit time according to the car model; Get the tire pressure value of the car; Determine the base deformation distance of the tire according to the vehicle model and tire pressure value; Determine the actual deformation distance based on the image detection information and the preset tire features; Determine the deformation deviation value according to the reference deformation distance and the actual deformation distance; Determine the added weight value according to the deformation deviation value; Determine the base vehicle weight value according to the vehicle model; Calculate the sum of the base vehicle weight value and the added weight value and use it as the running weight value; According to the driving weight value, the actual fuel consumption per unit time and the actual carbon emission corresponding to the actual fuel consumption are determined; The actual carbon emissions are taken as the vehicle’s carbon emissions and uploaded to the carbon emissions detection platform.

4. A method for detecting traffic carbon emissions according to claim 3, characterized in that: The verification method before uploading the vehicle carbon emissions to the carbon emissions detection platform also includes: According to the comparison between the actual carbon emissions and the carbon emissions of the vehicle, the actual carbon emissions are determined as the carbon emissions of the vehicle and uploaded to the carbon emission detection platform or the weight detection information of the vehicle is obtained; Determine tire deformation distance based on weight detection information and tire pressure value; Determine whether to complete adjustment or output prompt information according to the comparison between the tire deformation distance and the actual deformation distance; Update the actual fuel consumption per unit time based on the weight detection information; The vehicle carbon emissions are updated according to the updated actual fuel consumption and uploaded to the carbon emissions detection platform.

5. A method for detecting traffic carbon emissions according to claim 4, characterized in that: The verification method before uploading the vehicle carbon emissions to the carbon emissions detection platform also includes: Determine the driving position of the car based on the image detection information; Determine the slope position according to the driving position and obtain the speed information of the vehicle engine; Determine the fuel consumption per unit time based on the speed information; Determine the slope factor based on the slope location; Update the slope fuel consumption according to the slope fuel consumption and the slope coefficient; The slope carbon emissions are calculated based on the updated slope fuel consumption through a preset calculation database, and the slope carbon emissions are uploaded to the carbon emission detection platform as the vehicle's carbon emissions.

6. A method for detecting traffic carbon emissions according to claim 4, characterized in that: The verification method before uploading the vehicle carbon emissions to the carbon emissions detection platform also includes: Determine the gap parameters according to the image detection information and the preset gap characteristics; Determine the slip area based on the comparison between the gap parameter and the preset reference gap parameter; Determine the slip coefficient based on the clearance parameters; Determine the vehicle's slippage fuel consumption based on the slip coefficient and actual fuel consumption; Determine the carbon emissions from skidding according to the vehicle's skidding fuel consumption and a preset calculation database, and use the carbon emissions from skidding as the vehicle's carbon emissions and upload them to the carbon emission detection platform; A three-dimensional road surface model is established based on the image detection information and compared with a preset benchmark reference model to determine the concave-convex parameters; Determine the repair coordinates based on the slip coefficient and slip area; Determine whether the slip area is concave based on the concave-convex parameters; If the slip area is not a concave surface, the tapping depth is determined according to the concave-convex parameters and the preset reference concave depth; Determine the knocking force value according to the knocking depth; Controlling a preset knocking device to knock the slipping area according to the knocking force value and the repair coordinates; If the slip area is concave, the filling height is determined according to the concave-convex parameters and the filling device preset on the beating device is controlled to pave it flat, and the slip coefficient is re-determined; According to the comparison between the re-determined slip coefficient and the preset reference slip coefficient, it is determined that the adjustment or update of the repair coordinates is completed and the preset knocking device is controlled to knock the slip area.

7. A method for detecting traffic carbon emissions according to claim 6, characterized in that: The specific steps after determining the slip coefficient based on the gap parameters include: Get the road surface humidity value of the road surface; Determine the rain state or ice and snow state of the road surface according to the road surface humidity value, image detection information and preset rain and snow characteristics; If it is snowing, the snowfall speed of the car is obtained; Determine snow fuel consumption based on snow driving speed; Update the slip coefficient according to the road surface humidity value; Update snowfall fuel consumption according to snowfall fuel consumption and slip coefficient; Determine the snowfall carbon emissions based on the updated snowfall fuel consumption and the preset calculation database, and upload the snowfall carbon emissions as the vehicle carbon emissions to the carbon emission detection platform; If it is in the raining state, the raining driving speed of the car is obtained; Update the slip coefficient according to the road surface humidity value; Determine the rainfall fuel consumption based on the driving speed in rainfall; Update the rainfall fuel consumption according to the rainfall fuel consumption and the rainfall coefficient; The rainfall carbon emissions are determined based on the updated rainfall fuel consumption and the preset calculation database, and the rainfall carbon emissions are uploaded to the carbon emission detection platform as the vehicle carbon emissions.

8. A method for detecting traffic carbon emissions according to claim 5, characterized in that: The calculation methods corresponding to the calculation database include: V CO2 ≈a×n×Δr b × c ×ρ 汽 ×M CO2 ×Q CO2 , V CO2 is the hourly carbon dioxide emission of the car, a is the displacement of the car, Δr is the speed of the car, b is the coefficient of the car that has been tested in advance, w is the load number corresponding to the weight of the car in advance, c is the reference coefficient of the car in advance, ρ 汽 is the density of gasoline, M CO2 is the percentage of carbon content in gasoline, Q CO2 The amount of carbon dioxide gas produced corresponding to the carbon content in gasoline.

9. A traffic carbon emissions detection system, characterized in that: include: An acquisition module is used to obtain the total carbon emissions, heat detection information, image detection information, location information, season information, vehicle model, driving speed, tire pressure value, weight detection information, speed information, road humidity value, snowfall driving speed, and rainfall driving speed; A memory for storing a program of a method for detecting traffic carbon emissions according to any one of claims 1 to 8; The program in the memory can be loaded and executed by the processor to implement a method for detecting traffic carbon emissions as claimed in any one of claims 1 to 8.

10. An intelligent terminal, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executes a method for detecting traffic carbon emissions as claimed in any one of claims 1 to 8.

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