Road surface temperature prediction method

Abstract

The invention discloses a pavement temperature prediction method, and relates to the technical field of temperature prediction. The method comprises the following steps: acquiring current meteorological data, topographic data and relative position of the sun of a pavement to be measured; determining an initial solar radiation flux and an initial long wave radiation flux of the pavement to be measured based on the current meteorological data; based on the topographic data and the relative position of the sun, determining whether the to-be-measured road surface is shielded by the surrounding topography, and determining a shielding factor of the to-be-measured road surface under the condition that the to-be-measured road surface is shielded by the surrounding topography; and correcting the initial solar radiation flux and the initial long-wave radiation flux based on the shielding factor, and determining a temperature prediction value of the to-be-measured pavement based on the corrected solar radiation flux, the corrected long-wave radiation flux and a preset heat balance formula. Therefore, the precision of mountain road temperature prediction is improved.

Description

Technical Field

[0001] The present application relates to the technical field of temperature prediction, and in particular to a method for predicting road surface temperature. Background Art

[0002] Pavement temperature prediction is of great significance for preventing and dealing with road icing. At present, most pavement temperature prediction methods mainly rely on meteorological data and historical data to predict pavement temperature. However, for mountainous roads located in plateaus, high cold, and high altitudes, these pavement temperature prediction methods do not take into account the shielding effect of the mountain on the road surface. Therefore, the existing pavement temperature prediction methods are not suitable for temperature prediction on mountainous roads, and their temperature prediction accuracy is low. Summary of the invention

[0003] The main purpose of this application is to provide a road surface temperature prediction method to improve the accuracy of mountain road temperature prediction.

[0004] To achieve the above objectives, the present application provides a road surface temperature prediction method, comprising: Obtain the current meteorological data, terrain data and relative position of the sun of the road to be tested; Determining the initial solar radiation flux and the initial long-wave radiation flux of the road surface to be tested based on the current meteorological data; Based on the terrain data and the relative position of the sun, determining whether the road surface to be tested is shielded by surrounding terrain, and if the road surface to be tested is shielded by surrounding terrain, determining a shielding factor of the road surface to be tested; The initial solar radiation flux and the initial long-wave radiation flux are corrected based on the shielding factor, and the temperature prediction value of the road surface to be tested is determined based on the corrected solar radiation flux, the corrected long-wave radiation flux and a preset heat balance formula.

[0005] Optionally, determining whether the road surface to be tested is obscured by the surrounding terrain based on the terrain data and the relative position of the sun includes: simulating the road surface to be tested and its surrounding terrain based on the terrain data to obtain a terrain model, and gridding the terrain model to obtain a plurality of terrain units; for any terrain unit, determining whether the road surface to be tested is obscured by the mountain represented by the terrain unit based on the relative position of the sun, the spatial coordinate data of the terrain unit and the spatial coordinate data of the road surface to be tested; if there is a terrain unit among all the terrain units in which the represented mountain obscures the road surface to be tested, then it is determined that the road surface to be tested is obscured by the surrounding terrain.

[0006] Optionally, the determining whether the road to be tested is blocked by the mountain represented by the terrain unit based on the relative position of the sun, the spatial coordinate data of the terrain unit and the spatial coordinate data of the road to be tested comprises: determining a first target vector based on the relative position of the sun and the spatial coordinate data of the terrain unit, and determining a second target vector based on the spatial coordinate data of the terrain unit and the spatial coordinate data of the road to be tested; determining whether simulated sunlight intersects the plane where the terrain unit is located based on the normal vector of the plane where the terrain unit is located, the first target vector and the second target vector; wherein the simulated sunlight is the intersection of the sun and the mountain. a connecting straight line between the road surfaces to be tested; when the simulated sunlight intersects the plane where the terrain unit is located, based on the relative position of the sun, the spatial coordinate data of the terrain unit and the spatial coordinate data of the road surface to be tested, determine the vectors of the vertices of the terrain unit pointing to the intersection and the vectors of the vertices of the terrain unit pointing to the centroid of the terrain unit, and determine whether the intersection is within the terrain unit based on the vectors of each vertex; wherein the intersection is the intersection of the simulated sunlight and the plane where the terrain unit is located; if it is determined that the intersection is within the terrain unit, it is determined that the road surface to be tested is obscured by the mountain represented by the terrain unit.

[0007] Optionally, the spatial coordinate data of the terrain unit includes the spatial coordinates of each vertex of the terrain unit; the determining whether the simulated sunlight intersects with the plane where the terrain unit is located based on the normal vector of the plane where the terrain unit is located, the first target vector and the second target vector comprises: determining whether the simulated sunlight intersects with the plane where the terrain unit is located based on the normal vector of the plane where the terrain unit is located, the first target vector and the second target vector, and using the following formula (1): (1) The method of determining the vectors of each vertex of the terrain unit pointing to the intersection point based on the relative position of the sun, the spatial coordinate data of the terrain unit and the spatial coordinate data of the road surface to be measured comprises: for a vertex of any terrain unit, determining a first vertex vector based on the relative position of the sun and the spatial coordinates of the vertex, determining a second vertex vector based on the spatial coordinates of the vertex and the spatial coordinate data of the road surface to be measured, and determining the vector of the vertex pointing to the intersection point using the following formula (2): (2) In the formula, D is the judgment factor; is the normal vector of the plane where the terrain unit is located; is the first target vector; is the second target vector; is the angle between the normal vector of the plane where the terrain unit is located and the second target vector; is the angle between the normal vector of the plane where the terrain unit is located and the first target vector; A vector pointing from the first vertex of the terrain unit to the intersection point; A second vertex vector of the first vertex of the terrain unit; is a first vertex vector of a first vertex of the terrain unit; is the internal frequency division ratio of the intersection point, , is the distance from the intersection point to the sun, is the distance from the intersection point to the center of gravity of the road surface to be measured.

[0008] Optionally, determining the shielding factor of the road surface to be tested includes: based on the terrain model, simulating the emission of a number of scan lines with the center of gravity of the road surface to be tested as the base point, and taking the ratio of the scan lines intersecting the plane where the terrain unit is located to all the scan lines as the shielding factor; the angle between each of the scan lines and the preset direction is less than 90°; or, using a fisheye camera to capture an image with the road surface to be tested as the base point and the preset direction as the shooting direction, and taking the ratio of the area of ​​the obstruction in the image to the area of ​​the image as the shielding factor.

[0009] Optionally, the initial solar radiation flux includes an initial direct radiation flux and an initial scattered radiation flux, and the correcting the initial solar radiation flux and the initial long-wave radiation flux based on the shielding factor includes: correcting the initial solar radiation flux based on the shielding factor and using the following formula (3): (3) Based on the shielding factor, the initial long-wave radiation flux is corrected using the following formula (4): (4) In the formula, is the corrected solar radiation flux; is the initial direct radiation flux; is the initial scattered radiation flux; It is the judgment value of whether the direct solar radiation is blocked, 0 for blocked and 1 for unblocked; is the angle between the vector centered toward the sun and the normal vector of the plane where the road surface to be measured is located; is the shielding factor; is the corrected long-wave radiation flux; is the initial long-wave radiation flux; is the longwave radiation flux emitted by the surface.

[0010] Optionally, after determining the initial solar radiation flux and the initial long-wave radiation flux of the road surface to be tested based on the current meteorological data, the method further includes: determining whether the road surface to be tested is currently shielded by a vehicle; and when it is determined that the road surface to be tested is shielded by a vehicle, determining the long-wave radiation flux emitted by the bottom of the vehicle using the following formula (5): (5) In the formula, is the longwave radiation flux emitted from the bottom of the vehicle; is the emissivity of the bottom of the vehicle; is the Stefan-Boltzmann constant; is the bottom temperature of the vehicle; For the vehicle at time The time to pass through the road to be tested within 10 minutes; The method of determining the temperature prediction value of the road surface to be tested based on the corrected solar radiation flux, the corrected long-wave radiation flux and a preset heat balance formula includes: determining the temperature prediction value of the road surface to be tested based on the corrected solar radiation flux, the corrected long-wave radiation flux, the long-wave radiation flux emitted from the bottom of the vehicle and a preset heat balance formula.

[0011] Optionally, determining the predicted temperature value of the road surface to be tested based on the corrected solar radiation flux, the corrected long-wave radiation flux, the long-wave radiation flux emitted from the bottom of the vehicle and a preset heat balance formula includes: The solar radiation flux received by the road surface to be tested is determined based on the corrected solar radiation flux using the following formula (6): (6) The long-wave radiation flux received by the road surface to be tested is determined by using the following formula (7) based on the corrected long-wave radiation flux and the long-wave radiation flux emitted by the bottom of the vehicle: (7) The temperature prediction value of the road surface to be tested is determined by using the following preset heat balance formula (8) and based on the solar radiation flux received by the road surface to be tested and the long-wave radiation flux received by the road surface to be tested: (8) In the formula, The solar radiation flux received by the road surface to be tested; is the absorption rate of the road surface to be tested; is the corrected solar radiation flux; For the vehicle at time The time to pass through the road to be tested within 10 minutes; The long-wave radiation flux received by the road surface to be tested; is the corrected long-wave radiation flux; is the emissivity of the bottom of the vehicle; is the Stefan-Boltzmann constant; is the bottom temperature of the vehicle; is the volume heat capacity of the road surface layer to be tested; is the predicted value of the temperature of the road surface to be tested; is the thickness of the road surface layer to be tested; is the heat conduction flux of the road surface to be tested; is the long-wave radiation flux emitted by the road surface to be tested; The sensible heat flux generated by the wind caused by the vehicle and the natural wind.

[0012] Optionally, after the terrain model is gridded to obtain a plurality of terrain units, the method further includes: based on the terrain model, the terrain model is divided into a plurality of regions with the road surface to be tested as the center and according to a plurality of preset radii; for any region, the terrain units in the region are combined multiple times to obtain a plurality of new terrain units, and if there is a target terrain unit in all the new terrain units, the vertices of the target terrain unit are corrected using a preset vertex correction formula; the target terrain unit is an adjacent new terrain unit with different sizes and slopes after combination.

[0013] Optionally, before determining whether the road surface to be tested is obscured by the surrounding terrain, the method further includes: for any new terrain unit, based on the terrain model, simulating the emission of a scan line to the new terrain unit with the center of gravity of the road surface to be tested as the base point, if the scan line intersects with the plane where any other new terrain unit is located, then the new terrain unit is determined to be an invisible terrain unit; otherwise, the new terrain unit is determined to be a visible terrain unit; for any terrain unit, based on the relative position of the sun, the spatial coordinate data of the terrain unit and the spatial coordinate data of the road surface to be tested, determining whether the road surface to be tested is obscured by the mountain represented by the terrain unit includes: for any visible terrain unit, based on the relative position of the sun, the spatial coordinate data of the visible terrain unit and the spatial coordinate data of the road surface to be tested, determining whether the road surface to be tested is obscured by the mountain represented by the visible terrain unit.

[0014] The pavement temperature prediction method of the present application determines whether the pavement to be tested is shielded by the surrounding terrain through the terrain data of the pavement to be tested and the relative position of the sun. If the pavement to be tested is shielded by the surrounding terrain, the shielding factor of the pavement to be tested is calculated, and the initial solar radiation flux and the initial long-wave radiation flux are corrected using the shielding factor; finally, the temperature of the pavement to be tested is predicted based on the corrected solar radiation flux, the corrected long-wave radiation flux and a preset heat balance formula. By considering the loss of radiation flux caused by the mountain shielding effect and correcting the radiation flux, the influence of mountain terrain on pavement temperature change is simulated, thereby improving the accuracy of temperature prediction of mountain roads. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is one of the flow charts of the road surface temperature prediction method of the embodiment of the present application; Figure 2 This is the second flowchart of the road surface temperature prediction method of the embodiment of the present application; Figure 3 is a schematic diagram of a terrain model of a specific example of the present application; Figure 4 This is the third flow chart of the road surface temperature prediction method of the embodiment of the present application; Figure 5 It is one of the schematic diagrams of the plane where the simulated sunlight and terrain units are located in the embodiment of the present application; Figure 6 This is the second schematic diagram of the simulated sunlight and the plane where the terrain unit is located in the embodiment of the present application; Figure 7 This is the third schematic diagram of the simulated sunlight and the plane where the terrain unit is located in the embodiment of the present application; Figure 8 is a schematic diagram of scan lines in an embodiment of the present application; Fig. 9 This is the fourth flow chart of the road surface temperature prediction method of the embodiment of the present application; Fig.10 is a schematic diagram of the regional division of a terrain model of a specific example of the present application; Fig.11 is a schematic diagram of a combined front and rear terrain unit of a specific example of the present application; Fig.12 is a schematic diagram of an invisible terrain unit of a specific example of the present application; Fig.13 is a comparison result diagram of the predicted value and the actual value of the road surface temperature at 3 points in time in a specific embodiment of the present application; Fig.14 is a comparison result diagram of the predicted value and the actual value of the road surface temperature at 7:30 in a specific embodiment of the present application; Fig.15is a comparison result diagram of the predicted value and the actual value of the road surface temperature at 12 o'clock in a specific embodiment of the present application; Fig.16 This is a comparison result diagram of the predicted value and the actual value of the road surface temperature at 16:30 in a specific embodiment of the present application; Fig.17 is a comparison result diagram of the predicted value and the actual value of the road surface temperature at 21 o'clock in a specific embodiment of the present application; Fig.18 is a schematic diagram of a road surface temperature prediction device according to an embodiment of the present application; Fig.19 An example of a physical structure diagram of an electronic device is provided; In the figure, 1800, road surface temperature prediction device; 1810, acquisition module; 1820, initial value calculation module; 1830, judgment module; 1840, correction prediction module; 1910, processor; 1920, communication interface; 1930, memory; 1940, communication bus.

[0016] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solutions and advantages of this application clearer, the technical solutions in this application will be clearly and completely described below in conjunction with the drawings in this application. Obviously, the described embodiments are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0018] With the increase in road network density in the mountainous areas of southwest my country, the plateau, high-cold and high-altitude geographical environment not only exacerbates the damage rate of asphalt pavement, but also traffic accidents caused by low temperature and icing in winter occur frequently. Global climate change makes extreme winter cold waves frequent. Therefore, the management of mountainous roads in plateau, high-cold and high-altitude areas faces severe challenges.

[0019] Road management personnel usually maintain the service level of winter roads by spreading deicing salt. The road surface conditions are monitored by road weather sensors and closed-circuit televisions installed on the main roads, or the time for snow removal and deicing salt spreading is determined by patrol cars during snowfall. However, the above methods are inefficient; and it is difficult to conduct large-scale and frequent monitoring because of the waste of manpower and financial resources. Therefore, a large number of research institutions are developing various road surface temperature prediction models (Road Surface Temperature Forecast, RSTF model). By predicting the road surface temperature a few hours to a day in advance, the RSTF model can not only be used to determine when to remove snow, spread deicing salt, implement tire restrictions and close roads to implement winter road management more efficiently, but also can be used to determine the possibility of low-temperature cracking of asphalt road surfaces. The accuracy of the low-temperature grading selection of asphalt materials and the probability of asphalt pavement cracking can be judged by statistically comparing the predicted road surface temperature with the low-temperature grading of asphalt binder.

[0020] At present, the existing road surface temperature prediction methods mainly rely on meteorological data or historical data to predict the road surface temperature. For example, a prediction method that has been made public is to use the powerful time series analysis ability of the LSTM neural network model to learn the long-term dependencies in historical data to achieve road surface temperature prediction. However, this method requires multiple iterative calculations to adjust the model parameters, which means that a large amount of data is required; in addition, this statistical method is relatively easy to establish a model, but its accuracy has obvious errors due to the differences in natural conditions in different regions, and the model parameters need to be readjusted to eliminate the influence of different natural conditions. At the same time, with the increase in the number of influencing factors in various dimensions such as vehicle shading, radiation, and sensible heat, it becomes difficult to quantify the contribution of each influencing factor to road surface temperature prediction.

[0021] For another example, another prediction method that has been made public is to further determine the road surface temperature by combining the road surface temperature forecast value with various auxiliary meteorological parameters. However, this method does not take into account the shielding effect of mountain roads. For another example, another prediction method that has been made public is to improve the existing vertex measurement, use a mobile detection vehicle to obtain a time period of road surface temperature data, input it into the temperature difference model, and obtain the predicted road surface temperature. This method can dynamically monitor the weather conditions, geographical environment, and road surface temperature of the entire line; however, this method requires a large amount of data to correct the temperature difference model, and this method only considers meteorological factors, so it is not suitable for mountain roads.

[0022] It can be seen that the existing road surface temperature prediction methods do not take into account the shielding effect of objects such as mountains and vehicles, and are not suitable for temperature prediction of roads in high-altitude mountainous areas, and the prediction accuracy is not high.

[0023] Based on this, the embodiment of the present application provides a road surface temperature prediction method, which adopts the heat balance method and takes into account the loss of solar radiation and long-wave radiation received by the road surface caused by the shielding effect of objects such as mountains and vehicles, so as to simulate the influence of mountainous terrain such as high cold on the change of road surface temperature. At the same time, in order to speed up the calculation time, the embodiment of the present application also adopts a calculation method of combining adjacent terrain units and ignoring invisible terrain units to improve the calculation prediction efficiency. The road surface temperature prediction method of the embodiment of the present application is described in detail below.

[0024] Figure 1 FIG. 1 is one of the flow charts of the road surface temperature prediction method according to an embodiment of the present application. Figure 1 As shown, the road surface temperature prediction method may include the following steps: Step 110: Obtain current meteorological data, terrain data and relative position of the sun of the road surface to be tested.

[0025] Step 120: Determine the initial solar radiation flux and the initial long-wave radiation flux of the road surface to be tested based on the current meteorological data.

[0026] Step 130: Based on the terrain data and the relative position of the sun, determine whether the road surface to be tested is shielded by the surrounding terrain, and if the road surface to be tested is shielded by the surrounding terrain, determine the shielding factor of the road surface to be tested.

[0027] Step 140: Correct the initial solar radiation flux and the initial long-wave radiation flux based on the shielding factor, and determine the temperature prediction value of the road surface to be tested based on the corrected solar radiation flux, the corrected long-wave radiation flux and a preset heat balance formula.

[0028] First, it should be noted that the road surface temperature prediction method of the embodiment of the present application can be applied to electronic devices such as servers, microcontrollers, etc., and executed by the processor of the electronic device. For example, the road surface temperature prediction method of the embodiment of the present application can be applied in the scene of mountain road maintenance, and the road surface prediction method can be executed by the processor of the road maintenance management system server.

[0029] In this embodiment, the road surface to be tested may be a road surface in an area, and the current meteorological data of the road surface to be tested refers to: the current meteorological data of the area where the road surface to be tested is located. The current meteorological data of the road surface to be tested may include (but not limited to): various cloud amounts, atmospheric transmittance, cloud base temperature, near-surface water vapor partial pressure, near-surface air absolute temperature, low cloud absolute cloud base temperature, middle cloud absolute cloud base temperature, high cloud absolute cloud base temperature, etc. The terrain data of the road surface to be tested may include (but not limited to): spatial position coordinate data of the road surface and the surrounding mountains, elevation data, slope and aspect data, and land type data, and any other data that can reflect the relative position relationship between the road surface to be tested and the surrounding mountains. The relative position of the sun refers to the relative position of the sun relative to the road surface to be tested, the mountains around the road surface to be tested, etc. at the test time.

[0030] The current weather data of the road to be tested and the relative position of the sun can be obtained from the weather database of the Meteorological Bureau; for example, all weather data of the location can be obtained from the weather database according to the geographical location of the road to be tested. The terrain data of the road to be tested can be obtained from various geographic databases, such as the National Geographic Information Center (NGCC), OpenStreetMap (OSM), etc.

[0031] Furthermore, after obtaining the current meteorological data of the road surface to be tested, the initial solar radiation flux and the initial long-wave radiation flux of the road surface to be tested can be calculated based on the current meteorological data. It should be noted that the initial solar radiation flux and the initial long-wave radiation flux mainly refer to the theoretical values ​​of solar radiation and long-wave radiation received by the road surface to be tested without considering the shielding effect of objects. In this embodiment, the initial solar radiation flux mainly includes direct solar radiation flux and scattered solar radiation flux, and the initial long-wave radiation flux mainly includes sky long-wave radiation flux.

[0032] Two calculation methods for the initial solar radiation flux and the initial long-wave radiation flux are provided below. The first method is for when there are no clouds above the road surface to be tested, and the second method is for when there are clouds above the road surface to be tested. It is understandable that if there are clouds in the sky, the clouds will lose some solar radiation, so the initial solar radiation flux and the initial long-wave radiation flux need to be calculated appropriately according to the current cloud cover of the road surface to be tested.

[0033] In the first calculation method, when there is no cloud above the road surface to be tested, the initial solar radiation flux is mainly composed of direct solar radiation flux and scattered solar radiation flux. The direct solar radiation flux and scattered solar radiation flux can be calculated by the following formula (9) and formula (10) respectively: (9) (10) In the formula, is the direct solar radiation flux (i.e. the initial direct solar radiation flux); h is the solar altitude angle, unit: degree; J is the solar constant, unit: ; p is the atmospheric transmittance; is the solar diffuse radiation flux (i.e. the initial diffuse radiation flux); sin is the sine function; and The sum is the initial solar radiation flux when there is no cloud over the road surface to be tested. .

[0034] When there is no cloud over the road surface to be tested, the initial long-wave radiation flux will be affected by gases such as water vapor on the surface. Water vapor will have a certain absorption and re-radiation effect on the long-wave radiation. Therefore, the initial long-wave radiation flux can be corrected and calculated using the following formula (11): (11) In the formula, is the initial long-wave radiation flux when there is no cloud above the road surface to be tested; is the Stefan-Boltzmann constant, unit: ; is the absolute temperature of the air near the surface, unit: ; Represents the partial pressure of water vapor in the air close to the surface, in mmHg.

[0035] The second calculation method is that when there are clouds above the road surface to be tested, the clouds will cause loss of solar radiation. Therefore, when calculating the initial solar radiation flux, it is necessary to consider the cloud cover above the road surface to be tested. The initial solar radiation flux can be specifically corrected by the following formulas (12), (13) and (14): (12) (13) (14) In the formula, is the initial solar radiation flux when there are clouds above the road surface to be tested; y is the correction coefficient; is the initial solar radiation flux when there is no cloud over the road surface to be tested; C all is the total cloud cover above the road surface to be tested; C l is the lower cloud cover above the road surface to be tested.

[0036] Furthermore, if there are clouds above the road surface to be tested, the clouds will block part of the long-wave radiation emitted by the sky. At the same time, the clouds will also emit long-wave radiation to the ground. Therefore, the long-wave radiation flux that can enter the ground surface can be regarded as the sum of the long-wave radiation flux emitted by the clouds and the long-wave radiation flux emitted by the sky. The initial long-wave radiation flux can be corrected by the following formula (15): (15) In the formula, is the initial long-wave radiation flux when there are clouds above the road surface to be tested; C l is the cloud cover below the road surface to be tested; C m is the mid-level cloud cover of the road to be tested; C h is the upper cloud cover of the road to be tested; T cl is the absolute cloud base temperature of low clouds, unit: K; T cm is the absolute cloud base temperature of the middle cloud, unit: K; T ch is the absolute cloud base temperature of high clouds, unit: K.

[0037] It should be noted that the atmospheric transmittance, various cloud amounts, and temperature involved in the above formulas are all current meteorological data and can be directly obtained from existing meteorological databases.

[0038] Therefore, the appropriate calculation method of the initial solar radiation flux and the initial long-wave radiation flux can be selected according to whether there are clouds above the road surface to be tested, so that the solar radiation changes of the road surface to be tested can be understood and calculated more comprehensively and accurately, making the subsequent road surface temperature prediction more accurate and providing a more reliable basis for practical applications.

[0039] Furthermore, after the initial solar radiation flux and initial long-wave radiation flux of the road surface to be tested are determined, it is possible to analyze whether the mountains surrounding the road surface to be tested block the road surface to be tested based on the above-mentioned terrain data and the relative position of the sun. If the surrounding mountains block the road surface to be tested, it is necessary to correct the initial solar radiation flux and initial long-wave radiation flux to ensure the accuracy of subsequent road surface temperature prediction. If the surrounding mountains do not block the road surface to be tested, it is not necessary to correct the initial solar radiation flux and initial long-wave radiation flux, and the aforementioned calculated initial solar radiation flux and initial long-wave radiation flux can be directly used, and the heat balance formula constructed later can be used to obtain the predicted value of the road surface temperature to be tested.

[0040] In step 130, when it is determined that the road surface to be tested is shielded by the surrounding terrain based on the terrain data and the relative position of the sun, a shielding factor of the road surface to be tested can be calculated, and the shielding factor can be used to correct the initial solar radiation flux and initial long-wave radiation flux calculated above.

[0041] It should be noted that the shielding factor can be used to characterize the degree to which the road surface to be tested is shielded by the surrounding terrain, so as to determine the degree to which the surrounding terrain affects the solar radiation and long-wave radiation of the road surface to be tested. Therefore, the shielding factor can be determined based on the relative position relationship between the sun, the mountain, and the road surface to be tested.

[0042] In step 140, after the shielding factor of the road surface to be tested is obtained, the shielding factor can be used to correct the initial solar radiation flux and the initial long-wave radiation flux to obtain the corrected solar radiation flux and the corrected long-wave radiation flux; further, the preset heat balance formula is used to directly calculate the temperature prediction value of the road surface to be tested.

[0043] It is understandable that the heat balance method determines the road surface temperature by constructing an energy balance equation using the heat flux of weather, ground and other related factors. Heat exchange such as solar radiation, radiation back reflection caused by clouds, scattered radiation, ground radiation, thermal radiation from the vehicle chassis and road heat conduction put the road surface in an energy balance state. At the same time, solar radiation is considered to be one of the main factors affecting the road surface temperature. There are situations where mountains along mountain roads block solar radiation, resulting in certain losses of solar radiation and long-wave radiation. By constructing a theoretical formula of thermal balance, the road surface temperature prediction method of the embodiment of the present application has better accuracy and applicability.

[0044] Based on this, in this embodiment, the preset heat balance formula can include the solar radiation flux of the sun (i.e., the corrected solar radiation flux described in this embodiment), the long-wave radiation flux caused by clouds (i.e., the corrected long-wave radiation flux described in this embodiment), the long-wave radiation flux emitted by the vehicle chassis, the road surface heat conduction flux, the long-wave radiation flux of the road surface, and the sensible heat flux generated by the vehicle and natural wind.

[0045] Therefore, this embodiment realizes road surface temperature prediction by adopting the heat balance method, and when calculating the radiation flux of the road surface to be tested, the influence of surrounding mountains and vehicles on the radiation flux is taken into account, and it is corrected using the shielding factor, and finally a more accurate road surface temperature prediction result can be obtained.

[0046] The following is a detailed introduction to the process of determining whether the road surface to be tested is shielded by the surrounding terrain and calculating the shielding factor in the embodiment of the present application.

[0047] Figure 2 This is the second flow chart of the road surface temperature prediction method of the embodiment of the present application. Figure 2 As shown, in some embodiments, determining whether the road surface to be tested is shielded by the surrounding terrain based on the terrain data and the relative position of the sun in step 130 may include the following steps: Step 210: Simulate the road surface to be tested and its surrounding terrain based on the terrain data to obtain a terrain model, and divide the terrain model into grids to obtain a plurality of terrain units.

[0048] Step 220: for any terrain unit, based on the relative position of the sun, the spatial coordinate data of the terrain unit and the spatial coordinate data of the road surface to be tested, determine whether the road surface to be tested is obscured by the mountain represented by the terrain unit; Step 230: If there is a terrain unit in which the represented mountain blocks the road surface to be measured among all the terrain units, it is determined that the road surface to be measured is blocked by the surrounding terrain.

[0049] It should be noted that the embodiment of the present application mainly uses three-dimensional simulation software to simulate the spatial position relationship between the road surface to be tested, the surrounding mountains and the sun to determine whether the road surface to be tested is obscured by the surrounding terrain. In the subsequent process, as long as the terrain unit, terrain model, scan line, etc. are mentioned, they are all simulated by the three-dimensional simulation software.

[0050] Specifically, a three-dimensional simulation software can be used to perform a three-dimensional simulation of the road surface to be tested and the surrounding terrain according to the terrain data of the road surface to be tested, and a terrain model can be obtained. In this embodiment, the three-dimensional simulation software can be a three-dimensional simulation software such as ArcGIS software. The terrain model obtained by ArcGIS software simulation is taken as an example to introduce the subsequent process in detail.

[0051] It should be noted that ArcGIS software can create and process digital elevation models, which are raster datasets that represent terrain surfaces. Digital elevation models can be used to perform various terrain analyses, such as slope, aspect, slope classification, etc. Contour maps can also be generated based on digital elevation model data to visually display the undulations of terrain. In addition, terrain profiles can be generated to show the terrain changes on a specific path. Most importantly, ArcGIS software can generate three-dimensional terrain models, providing realistic terrain visualization effects. Users can rotate, zoom, and roam the three-dimensional terrain model for more intuitive analysis.

[0052] In this embodiment, ArcGIS software can be used to simulate the terrain model of the road surface to be tested and the surrounding terrain according to the terrain data of the road surface to be tested. After the terrain model is simulated, the terrain model can be gridded to divide the road surface to be tested and the surrounding terrain into several planes with different slopes and slope directions, and these planes are different terrain units. The grid in this embodiment is mainly a triangular grid, and the subsequent calculation and judgment processes are also implemented based on the triangular grid.

[0053] Figure 3 is a schematic diagram of a terrain model of a specific example of this application. Figure 3As can be seen in the figure, a triangular grid is a terrain unit. Different terrain units may have different elevations. The more prominent the terrain unit, the higher the elevation, and the more concave the terrain unit, the lower the elevation. Different terrain units may also have different slopes and directions. The slope and direction of the terrain unit are the slope and direction of the actual mountain. It should also be noted that the plane where the terrain unit is located represents the surface of the actual mountain or road surface.

[0054] After obtaining the terrain model and dividing it into several terrain units, the mountain represented by each terrain unit is analyzed in turn to see whether it blocks the road surface to be tested. Taking a terrain unit as an example, it is possible to determine whether the mountain represented by the terrain unit blocks the road surface to be tested based on the spatial coordinate data of the terrain unit, the relative position of the sun relative to the road surface to be tested and the terrain unit, and the spatial coordinate data of the road surface to be tested, and using a pre-constructed formula.

[0055] If one or more terrain units among all terrain units block the road surface to be measured, it is determined that the road surface to be measured is blocked by the surrounding terrain.

[0056] It should be noted that the spatial coordinate data of the terrain unit and the spatial coordinate data of the road surface to be measured can be geographic spatial coordinates, which can be composed of longitude, latitude, and elevation. The spatial coordinate data of the terrain unit and the spatial coordinate data of the road surface to be measured can be directly obtained from an existing geographic coordinate system, such as the National Basic Geographic Information Center (NGCC) and WGS (World Geodetic System). The spatial coordinate data of the terrain unit and the spatial coordinate data of the road surface to be measured can also be spatial coordinate data in the terrain model. Specifically, a three-dimensional coordinate system can be established with any point in the terrain model as the origin. On the basis of the three-dimensional coordinate system, the spatial coordinate data of each terrain unit and the spatial coordinate data of the road surface to be measured can be obtained. The form of the spatial coordinate data of the terrain unit and the spatial coordinate data of the road surface to be measured is not specifically limited here.

[0057] Figure 4 This is the third flow chart of the road surface temperature prediction method of the embodiment of the present application. Figure 4 As shown, in some embodiments, determining whether the road surface to be tested is blocked by the mountain represented by the terrain unit based on the relative position of the sun, the spatial coordinate data of the terrain unit, and the spatial coordinate data of the road surface to be tested in step 220 may include the following steps: Step 410: Determine a first target vector based on the relative position of the sun and the spatial coordinate data of the terrain unit, and determine a second target vector based on the spatial coordinate data of the terrain unit and the spatial coordinate data of the road surface to be measured.

[0058] Step 420: Based on the normal vector of the plane where the terrain unit is located, the first target vector and the second target vector, determine whether the simulated sunlight intersects with the plane where the terrain unit is located; wherein the simulated sunlight is a straight line connecting the sun and the road surface to be tested.

[0059] Step 430: In the case where the simulated sunlight intersects the plane where the terrain unit is located, based on the relative position of the sun, the spatial coordinate data of the terrain unit and the spatial coordinate data of the road surface to be tested, determine the vectors from each vertex of the terrain unit to the intersection and the vectors from each vertex of the terrain unit to the centroid of the terrain unit, and determine whether the intersection is within the terrain unit based on the vectors of each vertex; wherein the intersection is the intersection of the simulated sunlight and the plane where the terrain unit is located.

[0060] Step 440: If it is determined that the intersection point is within the terrain unit, it is determined that the road surface to be tested is obscured by the mountain represented by the terrain unit.

[0061] Continue to refer Figure 3 It should be noted that the first target vector is the sun pointing to the terrain unit E s The vector of the center of mass, the second target vector is the terrain unit E s The center of mass points to the road surface to be tested E r The vector of the terrain unit is Figure 3 The terrain unit corresponds to the plane where the triangle mesh is located.

[0062] In this embodiment, it is possible to first determine whether the simulated sunlight intersects with the plane where the terrain unit is located based on the terrain model; if it intersects, it indicates that the mountain represented by the terrain unit may cause obstruction to the road surface to be tested; if it does not intersect, it indicates that the mountain represented by the terrain unit will not cause obstruction to the road surface to be tested. At this time, it can be directly determined that the terrain unit does not obstruct the road surface to be tested. If the planes where all terrain units are located do not intersect with the simulated sunlight, it can be directly determined that the road surface to be tested is not obstructed by the surrounding terrain. It should be noted that the simulated sunlight can be: a straight line connecting the center point of the simulated sun in the terrain model and the center point of the road surface to be tested. This embodiment uses this straight line to represent all the sunlight irradiated on the road surface to be tested, so as to facilitate subsequent calculations.

[0063] Take the spatial coordinate data as the spatial coordinate data in the terrain model as an example. Specifically, in the process of determining whether the simulated sun rays intersect with the plane where the terrain unit is located, the first target vector can be obtained based on the spatial coordinate data of the simulated sun in the terrain model and the spatial coordinate data of the centroid of the terrain unit. , and then determine the second target vector according to the spatial coordinate data of the centroid of the terrain unit and the spatial coordinate data of the centroid (or center point) of the road surface to be measured .

[0064] Furthermore, after obtaining the first target vector and the second target vector, the normal vector of the plane where the terrain unit is located, the first target vector and the second target vector are used to determine whether the simulated sunlight intersects with the plane where the terrain unit is located. This embodiment uses the parallelogram law to calculate the vector corresponding to the simulated sunlight through the first target vector and the second target vector, and then determines whether the simulated sunlight intersects with the plane where the terrain unit is located based on the relationship between the vector corresponding to the simulated sunlight and the normal vector of the plane where the terrain unit is located.

[0065] Figure 5 FIG. 1 is one of the schematic diagrams of the plane where the simulated sunlight and terrain units are located in the embodiment of the present application. Figure 5 As shown, the first target vector Normal vector to the plane P where the terrain unit is located The angle between , the second target vector Normal vector to the plane P where the terrain unit is located The angle between , terrain unit E s The intersection point of plane P and simulated sunlight is C.

[0066] Continue to refer Figure 5 In some embodiments, it is possible to determine whether the simulated sunlight intersects the plane where the terrain unit is located based on the normal vector of the plane where the terrain unit is located, the first target vector, and the second target vector, and using the following formula (1): (1) In the formula, D is the judgment factor; is the normal vector of the plane where the terrain unit is located; is the first target vector; is the second target vector; is the angle between the normal vector of the plane where the terrain unit is located and the second target vector; It is the angle between the normal vector of the plane where the terrain unit is located and the first target vector.

[0067] In this embodiment, when D is less than or equal to 0, it is determined that the simulated sunlight intersects the plane P where the terrain unit is located at point C; when D is greater than 0, it is determined that the simulated sunlight does not intersect the plane P where the terrain unit is located.

[0068] Furthermore, when determining that the simulated sunlight intersects the plane where the terrain unit is located, it is then determined whether the intersection of the simulated sunlight and the plane where the terrain unit is located is within the terrain unit (i.e., inside the triangular grid where the centroid unit is located); if the intersection is within the terrain unit, it indicates that the mountain represented by the terrain unit will block the sunlight from shining on the road surface to be tested, that is, it will cause shielding on the road surface to be tested; if the intersection is not within the terrain unit, it indicates that the mountain represented by the terrain unit will not block the sunlight from shining on the road surface to be tested, and thus will not produce a shielding effect.

[0069] In this embodiment, the determination of whether the intersection point is within the terrain unit is still determined by the parallelogram rule. Specifically, the parallelogram rule is used to first determine the vectors from the vertices of the terrain unit to the intersection point, and the vectors from the vertices of the terrain unit cell to the centroid of the terrain unit; then, based on the relationship between the vectors from the vertices of the terrain unit cell to the intersection point and the vectors from the vertices of the terrain unit cell to the centroid of the terrain unit, it is determined whether the intersection point is within the terrain unit. It should be noted that, with reference to Figure 3 , the vertices of the terrain unit are the three vertices of the triangle mesh.

[0070] Figure 6 This is the second schematic diagram of the simulated sunlight and the plane where the terrain unit is located according to the embodiment of the present application. Figure 6 In the figure, vertex 1 of the terrain unit is taken as an example to show the relationship between the vector of vertex 1 pointing to the added point C, the vector of vertex 1 pointing to the sun, and the vector of vertex 1 pointing to the road surface to be tested.

[0071] refer to Figure 6 In some embodiments, determining the vectors of each vertex of the terrain unit pointing to the intersection point based on the relative position of the sun, the spatial coordinate data of the terrain unit, and the spatial coordinate data of the road surface to be measured may include: Taking the vertex of a terrain unit as an example, the first vertex vector can be determined based on the relative position of the sun and the spatial coordinates of the vertex, and the second vertex vector can be determined based on the spatial coordinates of the vertex and the spatial coordinate data of the road surface to be measured. Specifically, if the spatial coordinate data is the spatial coordinate data in the terrain model, the first vertex vector can be determined by using the spatial coordinates of the sun and the spatial coordinates of the vertex of the terrain unit, and then the second vertex vector can be determined by using the spatial coordinates of the vertex and the spatial coordinates of the center of gravity (or center point) of the road surface to be measured. Furthermore, the vector pointing from vertex 1 to intersection C can be determined using the following formula (2): (2) In the formula, The vector pointing to the intersection point from the first vertex of the terrain unit; The second vertex vector of the first vertex of the terrain unit; The first vertex vector of the first vertex of the terrain unit; is the internal frequency division ratio of the intersection point, , is the distance from the intersection point to the sun, is the distance from the intersection point to the center of gravity of the road surface to be tested. By the above method, the vectors of the remaining vertices of the terrain unit pointing to the intersection point C can be calculated in sequence, that is, and .

[0072] In addition, the vector from each vertex to the centroid of the terrain unit can be directly calculated using the spatial coordinates of each vertex and the spatial coordinates of the centroid of the terrain unit. Figure 7 FIG3 is a third schematic diagram of the plane where the simulated sunlight and terrain unit are located in the embodiment of the present application. Figure 7 Taking the vertices in as an example, the vectors pointing to the centroid of the terrain unit from vertex 1, vertex 2, and vertex 3 are recorded as: , and . Further, if and , and , and If all the outer product values ​​have the same sign, then the intersection point C is determined to exist in the terrain cell E. s If the value of any outer product has a different sign from the values ​​of the other outer products, then it is determined that the intersection point C is not in the terrain unit E. s The inside of the centroid. The above calculation method can be used to determine whether the intersection point C of the simulated sunlight and the plane where the terrain unit is located is inside the terrain unit; if it is inside, it is determined that the road surface to be tested is blocked by the mountain represented by the terrain unit; if it is not inside, it is determined that the road surface to be tested is not blocked by the mountain represented by the terrain unit.

[0073] The above method can be used to judge all terrain units once. If one or more terrain units among all terrain units cause shielding to the road surface to be tested, it is determined that the road surface to be tested is shielded by the surrounding terrain, and the initial solar radiation flux and the initial long-wave radiation flux need to be corrected; if all terrain units will not cause shielding to the road surface to be tested, it is determined that the road surface to be tested is not shielded by the surrounding terrain, and there is no need to correct the initial solar radiation flux and the initial long-wave radiation flux.

[0074] Furthermore, when it is determined that the road surface to be tested is shielded by the surrounding terrain, a shielding factor needs to be calculated to correct the initial solar radiation flux and the initial long-wave radiation flux using the shielding factor. This embodiment provides two methods for calculating the shielding factor. In actual application, any one of the two methods can be selected to calculate the shielding factor.

[0075] In some embodiments, the shielding factor of the road surface to be tested can be determined by simulating, based on a terrain model, emitting a number of scan lines with the center of gravity of the road surface to be tested as a base point, and taking the ratio of the scan lines intersecting the plane where the terrain unit is located to all the scan lines as the shielding factor; the angle between each scan line and the preset direction is less than 90°.

[0076] Figure 8 Schematic diagram of scanning lines in an embodiment of the present application. Figure 8 In the terrain model, three-dimensional simulation software can be used, and the center of gravity of the road surface to be tested is used as the reference point to launch several scanning lines above the road surface. It should be noted that the angle between each scanning line and the preset direction is less than 90°, and the preset direction can be: a direction perpendicular to the plane of the road surface to be tested and upward. In short, the scanning line is launched in any direction above the road surface.

[0077] Furthermore, the method of judging whether the simulated sunlight intersects with the plane where the terrain unit is located can be used to judge whether each scan line intersects with each terrain unit again. This will not be repeated here. After the judgment is completed, the total number of scan lines and the number of scan lines that do not intersect with the terrain unit can be determined, and the ratio between the number of scan lines that intersect with the terrain unit and the total number of scan lines can be used as the shielding factor. Specifically, the shielding factor can be calculated using the following formula (16): (16) In the formula, f all is the shielding factor; N all is the total number of scan lines; N ij is the number of intersecting scan lines of the scan line corresponding to the i-th road surface to be tested and the j-th terrain unit. It can be understood that the ratio of the number of intersecting scan lines to the total number of all scan lines can reflect the degree of occlusion of the road surface to be tested by the surrounding mountains.

[0078] In some embodiments, the method for determining the shielding factor of the road surface to be tested can also be: using a fisheye camera to shoot an image with the road surface to be tested as the base point and a preset direction as the shooting direction, and taking the ratio of the area of ​​the shielding object in the image to the image area as the shielding factor.

[0079] It should be noted that the shielding object in this embodiment may include any object that shields the road surface to be measured, such as a mountain, a vehicle, a roadblock, etc.

[0080] Specifically, the fisheye camera available on the market can be used to take the center of gravity of the road to be tested as the base point and shoot images along the preset direction. The image will include the sky area, mountain area, vehicle area, etc. At this time, the ratio of the area of ​​the obstruction area to the total area of ​​the image can be calculated and used as the obstruction factor. It can be understood that the ratio of the obstruction to the overall image can also reflect the degree of obstruction of the road to be tested by surrounding obstructions such as mountains and vehicles.

[0081] The process of using the masking factor for correction is introduced in detail below.

[0082] In some embodiments, the initial solar radiation flux may include an initial direct radiation flux (i.e., the above-mentioned direct solar radiation flux) and an initial scattered radiation flux (i.e., the above-mentioned scattered solar radiation flux). In some embodiments, after the shielding factor is calculated, the initial solar radiation flux and the initial long-wave radiation flux are corrected based on the shielding factor, including: The initial solar radiation flux is corrected based on the shading factor using the following formula (3): (3) The initial longwave radiation flux is corrected based on the shielding factor using the following formula (4): (4) In the formula, is the corrected solar radiation flux, unit: ; is the initial direct radiation flux, unit: ; is the initial diffuse radiation flux, unit: ; It is the judgment value of whether the direct solar radiation is blocked, 0 for blocked and 1 for unblocked; is the angle between the vector centered toward the sun and the normal vector of the plane where the road surface to be measured is located; is the masking factor; is the corrected long-wave radiation flux, unit: ; is the initial long-wave radiation flux, unit: ; is the longwave radiation flux emitted by the surface, unit: .

[0083] It is understandable that the road surface in mountainous areas is usually not only shielded by the surrounding mountains, but also by the vehicles on the road. Therefore, the shielding effect of the vehicle will also affect the radiation flux incident on the road surface. The embodiment of the present application also takes into account the impact of the shielding effect of the vehicle on the radiation flux incident on the road surface to correct the radiation flux incident on the road surface, thereby further improving the accuracy of subsequent road surface temperature prediction.

[0084] Based on this, in some embodiments, after determining the initial solar radiation flux and the initial long-wave radiation flux of the road surface to be tested based on the current meteorological data, the road surface temperature prediction method may further include: determining whether the road surface to be tested is currently shielded by a vehicle; when it is determined that the road surface to be tested is shielded by a vehicle, the Stefan-Boltzmann law is used to calculate, that is, formula (5) is used to determine the long-wave radiation flux emitted from the bottom of the vehicle: (5) In the formula, is the long-wave radiation flux emitted from the bottom of the vehicle; is the emissivity of the vehicle bottom; is the Stefan-Boltzmann constant; is the vehicle bottom temperature; For vehicles at time The time to pass the road to be tested.

[0085] In addition, in some embodiments, determining the temperature prediction value of the road surface to be tested based on the corrected solar radiation flux, the corrected long-wave radiation flux and a preset heat balance formula in step 140 may include: determining the temperature prediction value of the road surface to be tested based on the corrected solar radiation flux, the corrected long-wave radiation flux, the long-wave radiation flux emitted from the bottom of the vehicle and a preset heat balance formula.

[0086] In this embodiment, the time when a vehicle passes through the road surface to be tested can be obtained by setting a camera near the road surface to be tested, and taking a video of the road surface to be tested by the camera to determine the time when the vehicle passes through the road surface to be tested. The time when a vehicle passes through the road surface to be tested can also be obtained by using an intelligent transportation system or mobile application developed by a third party to obtain traffic information of the road surface to be tested in real time and obtain the time when the vehicle passes through the road surface to be tested. The method for obtaining the time when a vehicle passes through the road surface to be tested is not specifically limited here. Similarly, it is also possible to determine whether a vehicle is currently passing through the road surface to be tested in the above manner, thereby determining whether the road surface to be tested is currently blocked by a vehicle.

[0087] In some embodiments, after obtaining the corrected solar radiation flux, the corrected long-wave radiation flux, and the long-wave radiation flux emitted from the bottom of the vehicle, the following formula (6) can be used to determine the solar radiation flux received by the road surface to be tested based on the corrected solar radiation flux: (6) In the formula, is the solar radiation flux received by the road surface to be tested; is the absorption rate of the road surface to be tested; is the corrected solar radiation flux; For vehicles at time It should be noted that the solar radiation flux received by the road surface to be tested in this embodiment takes into account the reduction of radiation incident on the road surface to be tested caused by the shielding effect caused by the passing of vehicles, thereby correcting the initial solar radiation flux again and improving the accuracy of the solar radiation flux of the road surface to be tested.

[0088] Furthermore, the long-wave radiation flux received by the road surface to be tested can be determined based on the corrected long-wave radiation flux and the long-wave radiation flux emitted by the bottom of the vehicle using the following formula (7): (7) In the formula, is the long-wave radiation flux received by the road surface to be tested; is the corrected long-wave radiation flux; is the emissivity of the vehicle bottom; is the Stefan-Boltzmann constant; is the bottom temperature of the vehicle. It should be noted that formula (7) directly integrates formula (5) into the calculation formula of the long-wave radiation flux received by the road surface to be tested, that is, the corrected long-wave radiation flux and the long-wave radiation flux emitted by the bottom of the vehicle are integrated to obtain the long-wave radiation flux received by the road surface to be tested.

[0089] Finally, the above parameters can be substituted into the following pre-built heat balance formula (8): (8) In the formula, is the volume heat capacity of the pavement layer to be tested; is the predicted temperature value of the road surface to be tested; is the thickness of the road surface layer to be tested; is the heat conduction flux of the road surface to be tested; is the long-wave radiation flux emitted by the road surface to be tested; is the sensible heat flux caused by the wind caused by the vehicle and the natural wind; t is the time.

[0090] Among them, the heat conduction flux of the road surface to be tested The calculation can be performed by referring to the discrete Fourier equation, and specifically by using the following formula (17): (17) In the formula, is the thermal conductivity of the road surface layer to be tested, unit: ; is the measured temperature of the road surface to be tested, unit: °C; is the measured temperature of the road unit s-1 adjacent to the lower surface of the road surface to be tested, unit: °C; is the distance between the center of gravity of the road surface to be measured and the road unit s-1.

[0091] Long-wave radiation flux emitted by the road surface to be tested Following the Stefan-Boltzmann law, it can be calculated using the following formula (18): (18) In the formula, is the emissivity of the road surface to be tested.

[0092] Furthermore, according to Newton's law of cooling, the sensible heat flux generated by the wind caused by the vehicle and the natural wind It can be calculated using the following formula (19): (19) In the formula, is the atmospheric temperature, unit: °C; is the heat transfer coefficient between the road surface and the atmosphere, unit: , we can simulate it with wind speed according to the empirical model and get: , It is the natural wind speed or the wind speed caused by the vehicle at 0.2m above the ground, which can be obtained by measurement.

[0093] In this thermal balance model, the actual measured temperature of the road surface to be tested is The initial conditions of the thermal balance model are obtained by measuring the road surface before the experiment.

[0094] Thus, by establishing a heat balance equation based on the balance of energy received and released by the road surface to be tested, and then substituting the corrected solar radiation flux received by the road surface to be tested and the long-wave radiation flux received by the road surface to be tested into the preset heat balance formula, the temperature prediction value of the road surface to be tested can be obtained. It can be seen from the established heat balance equation that the embodiment of the present application takes many factors into consideration when predicting temperature, thereby reducing the possibility of missing key factors and improving the accuracy of road surface temperature prediction.

[0095] In this embodiment, an accelerated calculation method for combining adjacent terrain units and ignoring invisible terrain units is also provided, thereby reducing calculation time and improving the efficiency of road surface temperature prediction. The following is a detailed introduction to the accelerated calculation method for combining adjacent terrain units and ignoring invisible terrain units.

[0096] Fig. 9 This is the fourth flow chart of the road surface temperature prediction method of the embodiment of the present application. Fig. 9 As shown, in some embodiments, after the terrain model is gridded in step 210 to obtain a plurality of terrain units, the road surface temperature prediction method may further include the following steps: Step 910: Based on the terrain model, the terrain model is divided into multiple areas with the road surface to be tested as the center and according to multiple preset radii.

[0097] Step 920: For any area, combine the terrain units in the area multiple times to obtain multiple new terrain units. If there is a target terrain unit among all the new terrain units, the vertices of the target terrain unit are corrected using a preset vertex correction formula; the target terrain unit is an adjacent new terrain unit with different sizes and slopes after combination.

[0098] Specifically, three-dimensional simulation software can be used based on the terrain model, with the center of gravity of the road surface to be tested as the base point, and the terrain model can be divided into multiple areas according to multiple preset radii. Fig.10 is a schematic diagram of the regional division of a terrain model of a specific example of this application. Fig.10 , you can set n preset radii , and divide the terrain model according to these preset radii, we can get There are n-1 regions in total.

[0099] Taking a region as an example, terrain units of different sizes in the region can be combined in stages to reduce the number of terrain units, thereby reducing some judgment and calculation processes for terrain units.

[0100] Fig.11 Schematic diagram of a combined front and rear terrain unit of a specific example of the present application. Fig.11 Taking the terrain unit in as an example, the staged combination process of terrain units is introduced. Fig.11 In (A), some terrain units can be combined in pairs to obtain Fig.11 The four terrain units shown in (B): to , to Both of them combine two triangular terrain units that share a hypotenuse to obtain a quadrilateral terrain unit.

[0101] After the first combination, check to Is r the same as before the merger? to r belong to the same region, and check whether the areas of the four quadrilateral terrain units are the same; if both conditions are met, to Perform the second combination and get Fig.11 A quadrilateral terrain unit shown in (C) (i.e., the new terrain unit described in this embodiment).

[0102] If the terrain unit Adjacent to terrain units of different sizes and slopes (i.e., target terrain units described in this embodiment), the target terrain units are, for example, Fig.11 The topographic unit in (C) ; then there will be gaps in the terrain model, for example Fig.11 At this time, it is necessary to correct these two terrain units. elevation.

[0103] Specifically, in relation to the terrain unit In adjacent quadrilateral surface units, two terrain units will need to be corrected The common vertices of Move to terrain unit On the edge ab of . Common vertex This movement is achieved by changing the elevation by the following preset vertex correction formula (20): To achieve: (20) In the formula, For public vertices The change in elevation; and For terrain units The elevation of vertices a and b, unit: m; is the length of side ab, unit: m; From vertex a to the common vertex Distance, unit: m.

[0104] After correcting the rectangular terrain unit, the rectangular terrain unit can be evenly divided into two triangular terrain units, for example Fig.11 The two triangular terrain units shown in (D) are used to facilitate subsequent calculations.

[0105] In the above manner, all terrain units in the terrain model can be combined multiple times, thereby effectively reducing the number of terrain units and improving the efficiency of road surface temperature prediction.

[0106] In some embodiments, before determining in step 130 whether the road surface to be tested is obscured by the surrounding terrain, the road surface temperature prediction method may further include: for any new terrain unit, based on the terrain model, simulating the emission of a scan line to the new terrain unit with the center of gravity of the road surface to be tested as the base point; if the scan line intersects with the plane where any other new terrain unit is located, then the new terrain unit is determined to be an invisible terrain unit; otherwise, the new terrain unit is determined to be a visible terrain unit.

[0107] In some embodiments, for any terrain unit, based on the relative position of the sun, the spatial coordinate data of the terrain unit and the spatial coordinate data of the road surface to be measured, determining whether the road surface to be measured is obscured by the mountain represented by the terrain unit may include: for any visible terrain unit, based on the relative position of the sun, the spatial coordinate data of the visible terrain unit and the spatial coordinate data of the road surface to be measured, determining whether the road surface to be measured is obscured by the mountain represented by the visible terrain unit.

[0108] Fig.12 It is a schematic diagram of an invisible terrain unit of a specific example of the present application.

[0109] refer to Fig.12 Specifically, in the terrain model, if the center of gravity of the road to be tested is directed toward the new terrain unit E s1 A scan line is sent out, and the scan line is consistent with the new terrain unit E s1 New terrain unit E in front s2 intersect, it means that the new terrain unit E s1 The road surface to be measured is not visible to the terrain element. In this case, the reflected solar radiation and the new terrain element E s1 The radiation flux to the road surface to be measured is replaced by the new terrain unit E s2 Shielding, therefore, new terrain unit E s1 There is no thermal effect or shielding effect on the road surface to be tested.

[0110] In this embodiment, these new terrain units that have no thermal effect and shielding effect on the road surface to be tested may not be calculated, thereby further saving the time spent on road surface temperature prediction and improving prediction efficiency.

[0111] The following uses three typical measuring points as examples to further introduce the road surface temperature prediction method of the embodiment of the present application. Fig.13 is a comparison result diagram of the predicted value and the actual value of the road surface temperature at 3 points in time in a specific embodiment of the present application; Fig.14 is a comparison result diagram of the predicted value and the actual value of the road surface temperature at 7:30 in a specific embodiment of the present application; Fig.15 is a comparison result diagram of the predicted value and the actual value of the road surface temperature at 12 o'clock in a specific embodiment of the present application; Fig.16 This is a comparison result diagram of the predicted value and the actual value of the road surface temperature at 16:30 in a specific embodiment of the present application; Fig.17 This is a comparison result diagram of the predicted value and actual value of the road surface temperature at 21:00 in a specific embodiment of the present application.

[0112] like Figure 13-Figure 17As shown, according to the above steps, the road surface temperature at measuring point 1 (the road surface exposed to sunlight during the day) in Example 1 at 3:00, 7:30, 12:00, 16:30, and 21:00 in one day is calculated respectively, and compared with the actual measured values.

[0113] like Figure 13-Figure 17 As shown, according to the above steps, the road surface temperature at measuring point 2 (the road surface in the shadow) in Example 2 at 3:00, 7:30, 12:00, 16:30, and 21:00 in one day is calculated respectively, and compared with the actual measured values.

[0114] like Figure 13-Figure 17 As shown, according to the above steps, the road surface temperature at 3:00, 7:30, 12:00, 16:30, and 21:00 in one day at measuring point 3 (the road surface at the tunnel entrance) in Example 3 is calculated respectively, and compared with the measured values. Since measuring point 3 is at the tunnel entrance, the long-wave radiation received by the road surface increases due to the increase in structures, and the final result is that the road surface temperature rises accordingly.

[0115] It can be seen from the above three embodiments that the temperature prediction value obtained by the pavement temperature prediction method of the embodiment of the present application is very close to the actual value. Therefore, the pavement temperature prediction method of the embodiment of the present application is more suitable for temperature prediction of pavement in high-cold mountainous areas, and the obtained prediction result is more accurate.

[0116] In addition, Table 1 shows the time consumed for road surface temperature prediction when combining terrain units and ignoring invisible terrain units; the time consumed for road surface temperature prediction when combining terrain units; and the time consumed for road surface temperature prediction when ignoring invisible terrain units. It can be seen from Table 1 that when combining terrain units and ignoring invisible terrain units, the time consumed for road surface temperature prediction can be significantly reduced, greatly improving the efficiency of temperature prediction.

[0117] Table 1 Comparison of the time consumed for road surface temperature prediction

[0118] In summary, compared with the prior art, the embodiments of the present application have the following advantages and beneficial effects: 1. The embodiment of the present application predicts the road surface temperature by the heat balance method. When calculating the road surface solar radiation flux, the shielding effect is taken into account to correct the radiation flux, so that a more accurate prediction result can be obtained; 2. The embodiment of the present application utilizes a high-speed calculation method to overcome the problem of long time of traditional numerical calculation, reduce the time consumed by road surface temperature prediction, and greatly improve the efficiency of temperature prediction; 3. The embodiment of the present application can be used to determine when to remove snow and spread de-icing salt, as well as when to implement tire restrictions and close roads, by predicting the road surface temperature several hours to one day in advance, so as to implement winter road management more efficiently; 4. The embodiment of the present application can be used to determine the possibility of low-temperature cracking of asphalt pavement. By statistically comparing the predicted pavement temperature with the low-temperature classification of asphalt binder, the accuracy of the low-temperature classification selection of asphalt materials and the probability of asphalt pavement cracking can be determined.

[0119] 5. The method for predicting road surface temperature in high-cold mountainous areas taking into account the mountain shielding effect proposed in the embodiment of the present application has high calculation efficiency, accurate calculation results, and high promotion and application value.

[0120] Based on the above embodiments, the embodiments of the present application also provide a road surface temperature prediction device. Fig.18 is a schematic diagram of a road surface temperature prediction device according to an embodiment of the present application. Fig.18 As shown, the road surface temperature prediction device 1800 may include an acquisition module 1810, an initial value calculation module 1820, a judgment module 1830 and a correction prediction module 1840 which are connected in sequence.

[0121] Among them, the acquisition module 1810 is used to obtain the current meteorological data, terrain data and relative position of the sun of the road surface to be tested; the initial value calculation module 1820 is used to determine the initial solar radiation flux and the initial long-wave radiation flux of the road surface to be tested based on the current meteorological data; the judgment module 1830 is used to determine whether the road surface to be tested is shielded by the surrounding terrain based on the terrain data and the relative position of the sun, and determine the shielding factor of the road surface to be tested when the road surface to be tested is shielded by the surrounding terrain; the correction prediction module 1840 is used to correct the initial solar radiation flux and the initial long-wave radiation flux based on the shielding factor, and determine the temperature prediction value of the road surface to be tested based on the corrected solar radiation flux, the corrected long-wave radiation flux and the preset thermal balance formula.

[0122] Therefore, through the terrain data of the road surface to be tested and the relative position of the sun, it is determined whether the road surface to be tested is shielded by the surrounding terrain. If the road surface to be tested is shielded by the surrounding terrain, the shielding factor of the road surface to be tested is calculated, and the shielding factor is used to correct the initial solar radiation flux and the initial long-wave radiation flux; finally, the temperature of the road surface to be tested is predicted based on the corrected solar radiation flux, the corrected long-wave radiation flux and the preset heat balance formula. By considering the loss of radiation flux caused by the mountain shielding effect and correcting the radiation flux, the influence of mountain terrain on road surface temperature change is simulated, thereby improving the accuracy of temperature prediction of mountain roads.

[0123] It should be noted that for details not disclosed in the road surface temperature prediction device of this embodiment, please refer to the details disclosed in the embodiment of the road surface temperature prediction method in the embodiments of this specification, and will not be repeated here.

[0124] Based on the above embodiments, Fig.19 An example of a physical structure diagram of an electronic device is shown in FIG. Fig.19 As shown, the electronic device may include: a processor 1910, a communication interface 1920, a memory 1930 and a communication bus 1940, wherein the processor 1910, the communication interface 1920 and the memory 1930 communicate with each other through the communication bus 1940. The processor 1910 may call the logic instructions in the memory 1930 to execute the road surface temperature prediction method, including: obtaining the current meteorological data, terrain data and relative position of the sun of the road surface to be tested; determining the initial solar radiation flux and the initial long-wave radiation flux of the road surface to be tested based on the current meteorological data; determining whether the road surface to be tested is shielded by the surrounding terrain based on the terrain data and the relative position of the sun, and determining the shielding factor of the road surface to be tested when the road surface to be tested is shielded by the surrounding terrain; correcting the initial solar radiation flux and the initial long-wave radiation flux based on the shielding factor, and determining the temperature prediction value of the road surface to be tested based on the corrected solar radiation flux, the corrected long-wave radiation flux and the preset heat balance formula.

[0125] In addition, the logic instructions in the above-mentioned memory 1930 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0126] On the basis of the above embodiments, on the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the road surface temperature prediction method provided by the above methods, including: obtaining the current meteorological data, terrain data and relative position of the sun of the road surface to be tested; determining the initial solar radiation flux and initial long-wave radiation flux of the road surface to be tested based on the current meteorological data; determining whether the road surface to be tested is shielded by the surrounding terrain based on the terrain data and the relative position of the sun, and determining the shielding factor of the road surface to be tested when the road surface to be tested is shielded by the surrounding terrain; correcting the initial solar radiation flux and the initial long-wave radiation flux based on the shielding factor, and determining the temperature prediction value of the road surface to be tested based on the corrected solar radiation flux, the corrected long-wave radiation flux and a preset thermal balance formula.

[0127] On the basis of the above embodiments, on another aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the road surface temperature prediction method provided by the above methods, including: obtaining current meteorological data, terrain data and relative position of the sun of the road surface to be tested; determining the initial solar radiation flux and initial long-wave radiation flux of the road surface to be tested based on the current meteorological data; determining whether the road surface to be tested is shielded by the surrounding terrain based on the terrain data and the relative position of the sun, and determining the shielding factor of the road surface to be tested if the road surface to be tested is shielded by the surrounding terrain; correcting the initial solar radiation flux and the initial long-wave radiation flux based on the shielding factor, and determining the temperature prediction value of the road surface to be tested based on the corrected solar radiation flux, the corrected long-wave radiation flux and a preset heat balance formula.

[0128] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0129] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

Claims

1. A road surface temperature prediction method, characterized in that: include: Obtain the current meteorological data, terrain data and relative position of the sun of the road to be tested; Determining the initial solar radiation flux and the initial long-wave radiation flux of the road surface to be tested based on the current meteorological data; Based on the terrain data and the relative position of the sun, determining whether the road surface to be tested is shielded by surrounding terrain, and if the road surface to be tested is shielded by surrounding terrain, determining a shielding factor of the road surface to be tested; The initial solar radiation flux and the initial long-wave radiation flux are corrected based on the shielding factor, and the temperature prediction value of the road surface to be tested is determined based on the corrected solar radiation flux, the corrected long-wave radiation flux and a preset heat balance formula.

2. The road surface temperature prediction method according to claim 1, characterized in that: The determining, based on the terrain data and the relative position of the sun, whether the road surface to be tested is shielded by surrounding terrain includes: Simulating the road surface to be tested and its surrounding terrain based on the terrain data to obtain a terrain model, and dividing the terrain model into grids to obtain a plurality of terrain units; For any terrain unit, based on the relative position of the sun, the spatial coordinate data of the terrain unit and the spatial coordinate data of the road surface to be tested, determine whether the road surface to be tested is obscured by the mountain represented by the terrain unit; If there is a terrain unit in all the terrain units in which the represented mountain shields the road surface to be measured, it is determined that the road surface to be measured is shielded by the surrounding terrain.

3. The road surface temperature prediction method according to claim 2, characterized in that: The determining whether the road surface to be tested is blocked by the mountain represented by the terrain unit based on the relative position of the sun, the spatial coordinate data of the terrain unit and the spatial coordinate data of the road surface to be tested comprises: Determine a first target vector based on the relative position of the sun and the spatial coordinate data of the terrain unit, and determine a second target vector based on the spatial coordinate data of the terrain unit and the spatial coordinate data of the road surface to be measured; Based on the normal vector of the plane where the terrain unit is located, the first target vector and the second target vector, determining whether the simulated sunlight intersects with the plane where the terrain unit is located; wherein the simulated sunlight is a straight line connecting the sun and the road surface to be tested; In the case where the simulated sunlight intersects with the plane where the terrain unit is located, based on the relative position of the sun, the spatial coordinate data of the terrain unit and the spatial coordinate data of the road surface to be tested, the vectors of each vertex of the terrain unit pointing to the intersection and the vectors of each vertex of the terrain unit pointing to the centroid of the terrain unit are determined, and based on the vectors of each vertex, it is determined whether the intersection is within the terrain unit; wherein the intersection is the intersection of the simulated sunlight and the plane where the terrain unit is located; If it is determined that the intersection point is within the terrain unit, then it is determined that the road surface to be tested is obscured by the mountain represented by the terrain unit.

4. The road surface temperature prediction method according to claim 3, characterized in that: The spatial coordinate data of the terrain unit includes the spatial coordinates of each vertex of the terrain unit; The determining, based on the normal vector of the plane where the terrain unit is located, the first target vector, and the second target vector, whether the simulated sunlight intersects with the plane where the terrain unit is located, comprises: Based on the normal vector of the plane where the terrain unit is located, the first target vector and the second target vector, the following formula (1) is used to determine whether the simulated sunlight intersects the plane where the terrain unit is located: （1） The step of determining the vectors of each vertex of the terrain unit pointing to the intersection point based on the relative position of the sun, the spatial coordinate data of the terrain unit and the spatial coordinate data of the road surface to be measured comprises: For the vertex of any terrain unit, a first vertex vector is determined based on the relative position of the sun and the spatial coordinates of the vertex, a second vertex vector is determined based on the spatial coordinates of the vertex and the spatial coordinate data of the road surface to be tested, and a vector pointing from the vertex to the intersection is determined using the following formula (2): （2） In the formula, D is the judgment factor; is the normal vector of the plane where the terrain unit is located; is the first target vector; is the second target vector; is the angle between the normal vector of the plane where the terrain unit is located and the second target vector; is the angle between the normal vector of the plane where the terrain unit is located and the first target vector; A vector pointing from the first vertex of the terrain unit to the intersection point; A second vertex vector of the first vertex of the terrain unit; is a first vertex vector of a first vertex of the terrain unit; is the internal frequency division ratio of the intersection point, , is the distance from the intersection point to the sun, is the distance from the intersection point to the center of gravity of the road surface to be measured.

5. The road surface temperature prediction method according to claim 2, characterized in that: Determining the shielding factor of the road surface to be tested includes: Based on the terrain model, a plurality of scanning lines are simulated with the center of gravity of the road surface to be tested as the base point, and the ratio of the scanning lines intersecting the plane where the terrain unit is located to all the scanning lines is used as the shielding factor; the angle between each scanning line and the preset direction is less than 90°; or, An image is captured using a fisheye camera with the road surface to be measured as a base point and the preset direction as a shooting direction, and the ratio of the area of ​​the shielding object in the image to the area of ​​the image is used as the shielding factor.

6. The road surface temperature prediction method according to claim 1, characterized in that: The initial solar radiation flux includes an initial direct radiation flux and an initial scattered radiation flux, and the correcting the initial solar radiation flux and the initial long-wave radiation flux based on the shielding factor includes: The initial solar radiation flux is corrected based on the shading factor using the following formula (3): （3） Based on the shielding factor, the initial long-wave radiation flux is corrected using the following formula (4): （4） In the formula, is the corrected solar radiation flux; is the initial direct radiation flux; is the initial scattered radiation flux; is the judgment value of whether the direct solar radiation is blocked, 0 for blocked and 1 for unblocked; θ is the angle between the vector centered toward the sun and the normal vector of the plane where the road surface to be tested is located; is the shielding factor; is the corrected long-wave radiation flux; is the initial long-wave radiation flux; is the longwave radiation flux emitted by the surface.

7. The road surface temperature prediction method according to claim 1, characterized in that: After determining the initial solar radiation flux and the initial long-wave radiation flux of the road surface to be tested based on the current meteorological data, the method further includes: Determining whether the road surface to be tested is currently blocked by a vehicle; When it is determined that the road surface to be tested is shielded by a vehicle, the long-wave radiation flux emitted from the bottom of the vehicle is determined using the following formula (5): （5） In the formula, is the longwave radiation flux emitted from the bottom of the vehicle; is the emissivity of the bottom of the vehicle; is the Stefan-Boltzmann constant; is the bottom temperature of the vehicle; For the vehicle at time The time to pass through the road to be tested within 10 minutes; The step of determining the predicted temperature value of the road surface to be tested based on the corrected solar radiation flux, the corrected long-wave radiation flux and a preset heat balance formula includes: Based on the corrected solar radiation flux, the corrected long-wave radiation flux, the long-wave radiation flux emitted from the bottom of the vehicle and a preset heat balance formula, a temperature prediction value of the road surface to be tested is determined.

8. The road surface temperature prediction method according to claim 7, characterized in that: The method of determining the predicted temperature value of the road surface to be tested based on the corrected solar radiation flux, the corrected long-wave radiation flux, the long-wave radiation flux emitted from the bottom of the vehicle and a preset heat balance formula includes: The solar radiation flux received by the road surface to be tested is determined based on the corrected solar radiation flux using the following formula (6): （6） The long-wave radiation flux received by the road surface to be tested is determined by using the following formula (7) based on the corrected long-wave radiation flux and the long-wave radiation flux emitted by the bottom of the vehicle: （7） The temperature prediction value of the road surface to be tested is determined by using the following preset heat balance formula (8) and based on the solar radiation flux received by the road surface to be tested and the long-wave radiation flux received by the road surface to be tested: （8） In the formula, The solar radiation flux received by the road surface to be tested; is the absorption rate of the road surface to be tested; is the corrected solar radiation flux; For the vehicle at time The time to pass through the road to be tested within 10 minutes; The long-wave radiation flux received by the road surface to be tested; is the corrected long-wave radiation flux; is the emissivity of the bottom of the vehicle; is the Stefan-Boltzmann constant; is the bottom temperature of the vehicle; is the volume heat capacity of the road surface layer to be tested; is the predicted value of the temperature of the road surface to be tested; is the thickness of the road surface layer to be tested; is the heat conduction flux of the road surface to be tested; is the long-wave radiation flux emitted by the road surface to be tested; The sensible heat flux generated by the wind caused by the vehicle and the natural wind.

9. The road surface temperature prediction method according to claim 2, characterized in that: After meshing the terrain model to obtain a plurality of terrain units, the method further includes: Based on the terrain model, the terrain model is divided into a plurality of regions with the road surface to be tested as the center and according to a plurality of preset radii; For any area, the terrain units in the area are combined multiple times to obtain multiple new terrain units. If there is a target terrain unit among all the new terrain units, the vertices of the target terrain unit are corrected using a preset vertex correction formula; the target terrain unit is an adjacent new terrain unit with different sizes and slopes after combination.

10. The road surface temperature prediction method according to claim 9, characterized in that: Before determining whether the road surface to be tested is obscured by surrounding terrain, the method further includes: For any new terrain unit, based on the terrain model, simulate emitting a scan line to the new terrain unit with the center of gravity of the road surface to be tested as a base point. If the scan line intersects with the plane where any other new terrain unit is located, the new terrain unit is determined to be an invisible terrain unit; otherwise, the new terrain unit is determined to be a visible terrain unit. The determining, for any terrain unit, whether the road to be tested is blocked by a mountain represented by the terrain unit based on the relative position of the sun, the spatial coordinate data of the terrain unit, and the spatial coordinate data of the road to be tested, comprises: For any visible terrain unit, based on the relative position of the sun, the spatial coordinate data of the visible terrain unit and the spatial coordinate data of the road surface to be tested, it is determined whether the road surface to be tested is blocked by the mountain represented by the visible terrain unit.

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