Method for predicting friction coefficient of asphalt pavement in ice and snow weather

Abstract

The invention relates to the technical field of risk management and control of expressways and urban expressways, in particular to a real-time prediction method for asphalt pavement friction coefficients in ice and snow weather. Comprising friction coefficient prediction models of an iced road surface, a snowy road surface and a snowy ablation road surface. The influence factor for determining the friction coefficient of the iced road surface is the thickness of the ice layer, and a good exponential function relationship exists between the thickness of the ice layer and the friction coefficient. The friction coefficient of the snowy road surface is obviously influenced by relative sliding in the snow layer, and the thickness of the snow layer is the key for determining sliding between the inner layers of the snow layer. The accumulated snow melting road surface, the ice layer and the snow layer have negative effects on the anti-sliding performance of the road surface, and a good exponential function relation exists between the total ice and snow thickness of the accumulated snow melting road surface and the friction coefficient. According to the method, a friction system prediction equation is established by adopting a nonlinear regression method, real-time prediction can be carried out for different road surface states, and friction coefficient parameters are provided for traffic risk management and control of expressways in severe weather in winter and urban expressways in ice and snow weather.

Description

Technical Field

[0001] The present invention relates to the technical field of risk management and control of expressways and urban expressways, and in particular to a real-time prediction method for the friction coefficient of an asphalt pavement in icy and snowy weather. Background Art

[0002] The skid resistance of the road surface has a very important impact on driving safety. In severe winter weather conditions, the road surface is covered with snow or ice, which will significantly reduce the skid resistance. There is a significant statistical relationship between the skid resistance of the road surface and the accident rate. Snowfall will increase the accident rate and injury rate by 84% and 75% respectively. When the road is covered with snow or ice, my country's highways often adopt a station closure management strategy, resulting in the transfer of traffic operation risks, reduced road network service capacity, loss of traffic revenue and reduced user satisfaction. Although the ability of the road surface to melt ice and remove snow can be enhanced by improving its material properties, it does not achieve zero coverage of snow or ice on the road surface.

[0003] Equipment that directly tests the friction coefficient of the road surface can be divided into continuous testing equipment (tire in contact with the road surface) and single-point testing equipment (rubber slider in contact with the road surface). Foreign scholar Bhoopalam conducted a systematic study on the interaction between tires and ice surfaces, taking into account the effects of load, tire pressure, tire pattern, temperature, and ice surface type. Scholar Dan used a pendulum tester (BPT) to test the anti-skid performance of various winter roads, analyzed the effects of road surface temperature, ice thickness, and water film thickness, and finally proposed an empirical evaluation model for the anti-skid performance of the road surface. Scholar Tan used a dynamic friction coefficient tester (DFT) to systematically study the anti-skid performance of rubber sliders on icy roads. For snowy roads, scholars tried to use BPT or DFT to test their anti-skid performance, but the slider cannot simulate the rolling characteristics of tires. Scholar Salimi used a synchronous tractor (Real Time Traction Tool) to test the lateral force coefficient of icy and snowy roads in a closed section.

[0004] In icy and snowy weather, the ice and snow on the road surface gradually accumulate. Existing studies have explored the impact of various factors on the skid resistance of winter roads. However, due to the limitations of the field environment, the test can only be carried out after the ice or snow has finished falling. Therefore, it is impossible to fully predict the attenuation of the skid resistance of the road surface. In addition, there is a lack of in-depth research on the applicability of the pendulum instrument to ice and snow covered roads. Summary of the invention

[0005] The purpose of this invention is to propose a prediction model for the change of the friction coefficient of asphalt pavement during the whole process of icy and snowy weather. The model covers the process more completely and in-depth to solve the imperfections of the current research on the attenuation of the anti-skid performance of pavements in icy and snowy weather.

[0006] To achieve the above object, the present invention provides the following solutions:

[0007] Test and analysis of anti-skid performance of icy pavement: Based on the decay relationship between pavement ice thickness and pavement anti-skid performance, a nonlinear regression method is used to fit the icy pavement friction coefficient prediction model;

[0008] Snow pavement anti-skid performance test and analysis: Based on the relationship between the snow accumulation state and the relative sliding inside the snow layer, a road friction coefficient prediction model under floating snow-compacted snow state and compacted snow state is obtained;

[0009] Test and analysis of the anti-skid performance of snow-melting pavement: According to the influence of the change of the thickness of the snow and ice layers on the pavement during the snow melting process on the anti-skid ability of the pavement, the relationship between the total thickness of the ice-snow mixture and the friction coefficient is fitted, and a prediction model for the pavement friction coefficient under snow melting conditions is obtained.

[0010] Furthermore, the icy road surface is a natural freezing phenomenon of the asphalt road surface of the highway in winter, including ice formed due to water accumulation on the road surface after snow removal, and dark ice may also be formed due to freezing fog, freezing drizzle or freezing rain.

[0011] Furthermore, the cumulative simulation method of the road surface ice layer laboratory is as follows: first, precipitate the road surface at room temperature to make it completely wet, then quickly lower the ambient temperature to form an ice layer on the road surface, and complete relevant tests; then, control the road surface temperature at -6℃~-5℃, use a spray bottle to spray water mist on the road surface, wait for 5 minutes after each spraying, and then complete relevant tests; finally, use the icing function of the environmental chamber to perform low-temperature precipitation at -5℃ until the ice layer completely covers the macro texture of the road surface, forming a thick ice road surface for testing the minimum value of the anti-skid performance of the icy road surface.

[0012] Furthermore, the test plan first simulates the accumulation and melting of ice and snow cover by spraying water mist, snowfall or heating, and then conducts relevant tests, mainly including: (1) using Vaisala pavement condition sensor to detect the thickness of ice and snow cover; (2) using T2GO (portable continuous friction coefficient tester) to test the friction coefficient of the road surface; (3) using a pendulum instrument to test the swing value (BPN) of the road surface.

[0013] The anti-skid performance test of icy pavement includes: simulation of ice accumulation on the road surface and anti-skid performance test of icy pavement. The main process is: artificial snowfall is carried out on the dry road surface three times at -10°C, and the thickness of floating snow is 5-8mm each time. After the snowfall is completed, the anti-skid performance of the floating snow or floating snow-compacted snow mixed road surface is tested first, and then the floating snow is rolled back and forth 5 times by the test wheels of T2GO to form a compacted snow road surface, and then the snow-covered road surface in the compacted state is tested. In order to study the impact of temperature changes on the anti-skid performance of snow-covered pavement, after the third snowfall test is completed, the ambient temperature is gradually increased to 0°C, and the friction coefficient of the snow-covered road surface under different temperature conditions is tested. Finally, the friction coefficient prediction model of asphalt pavement under icy pavement state is obtained as follows:

[0014]

[0015] Where: μ——friction coefficient; x1—ice thickness (mm)

[0016] The anti-skid performance test of the snow-covered road surface includes: simulation of snow layer accumulation on the road surface and anti-skid performance test of icy road surface. The main process is: artificial snowfall is carried out on the dry road surface three times at -10°C, and the thickness of floating snow is 5-8mm each time. After the snowfall is completed, the anti-skid performance of the floating snow or floating snow-compacted snow mixed road surface is tested first, and then the floating snow is rolled back and forth 5 times by the test wheels of T2GO to form a compacted snow road surface, and then the snow-covered road surface in the compacted state is tested. In order to study the impact of temperature changes on the anti-skid performance of snow-covered roads, after the third snowfall test is completed, the ambient temperature is gradually increased to 0°C, and the friction coefficient of the snow-covered road surface under different temperature conditions is tested. Finally, the friction coefficient prediction model of asphalt pavement under snow-covered road surface state is obtained as follows:

[0017] 1. Floating and compacted snow conditions:

[0018] Snowfall: <10 mm, μ = 0.46;

[0019] Snowfall: 1020 mm, μ = 0.42;

[0020] Snowfall: 2030 mm, μ = 0.36;

[0021] 2. Compacted snow status:

[0022]

[0023] Where: μ——friction coefficient; x2—road surface temperature (-10~0℃);

[0024] The anti-skid performance test of the snow-melting pavement includes: road surface snow melting simulation and snow-melting pavement anti-skid performance test. The main process is: the compacted snow on the road surface will melt due to rising ambient temperature, heating of vehicle exhaust gas or rolling of car tires. After the friction coefficient test of the snowy road surface is completed, the ambient temperature is adjusted to 10°C. When the road surface temperature rises to -1°C~0°C, the thickness of the road surface cover is detected and the anti-skid performance of the road surface is tested. This time point is used as the starting point of the snowy road surface melting test (0min), and then the test is carried out every 10 minutes. Finally, the friction coefficient prediction model of asphalt pavement under the snow melting state is obtained as follows:

[0025]

[0026] Where: μ——friction coefficient; x3—thickness of ice-snow mixture (mm);

[0027] The beneficial effects of the present invention are:

[0028] The invention uses a nonlinear regression method to establish a friction coefficient prediction model for different road conditions (icy road, snowy road, snow-melted road). The above model is based on experimental data and mathematical models, and can accurately predict the anti-skid performance of the road surface, providing real-time friction coefficient parameters for traffic management departments, thereby effectively reducing the impact of severe winter weather on road traffic safety. For example, under severe weather conditions, traffic managers can adjust traffic control measures in a timely manner based on the prediction results to improve road safety and traffic efficiency.

[0029] This method analyzes the key factors that affect the skid resistance of icy and snowy roads, such as ice thickness, internal sliding of the snow layer, etc. By establishing mathematical relationships with these factors, the accuracy and reliability of the prediction model are improved, enabling it to be effectively applied in different climate conditions and road conditions.

[0030] In order to ensure the reliability of the prediction model, this proposal also proposes a series of standardized experimental methods, such as laboratory simulation of road surface ice accumulation and artificial snowfall testing. The above experimental methods can not only simulate the ice and snow conditions on the real road surface, but also verify and correct the prediction model, making it more reliable in practical applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 Schematic diagram of the surface morphology of the road surface after ice formation in the present invention; (a) is ice formation on a wet road surface; (b) is ice formation on a fine water mist; (c) is covered with a thick ice layer;

[0032] Figure 2 The growth of the road surface covering during the spraying of water mist in the present invention;

[0033] Figure 3The anti-skid performance test results of icy road surface in the present invention;

[0034] Figure 4 Schematic diagram of the surface characteristics of the compacted snow road surface in the present invention; wherein (a1) is a snowfall of 5-10 mm; (b1) is a snowfall of 10-20 mm; (c1) is a snowfall of 20-30 mm;

[0035] Figure 5 The friction coefficient test result of the snow road surface in the present invention;

[0036] Figure 6 Schematic diagram of local characteristics of snow melting road surface in the present invention; (d) is 20 minutes; (e) is 60 minutes; (f) is 120 minutes;

[0037] Figure 7 The thickness of the road surface covering material changes during the snow melting process in the present invention;

[0038] Figure 8 The anti-skid performance test results of the snow melting road surface in the present invention;

[0039] Fig. 9 It is a schematic diagram of the friction coefficient fitting curve of the icy road surface and the snow melting road surface in the present invention;

[0040] Fig.10 It is a schematic diagram of the fitting curve of the friction coefficient of the compacted snow road surface in the present invention;

[0041] Fig.11 It is a schematic diagram of the friction coefficient corresponding to different road surface covering thicknesses in the present invention. DETAILED DESCRIPTION

[0042] The following will be combined with the drawings in the experimental analysis process of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0043] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0044] The present invention aims at the existing anti-skid performance detection methods of icy and snowy roads, such as continuous testing and single-point testing, and uses tools such as pendulum tester (BPT), dynamic friction coefficient tester (DFT), synchronous tractor (Real Time Traction Tool) to test the anti-skid performance of icy and snowy roads, and proposes a prediction model for the anti-skid performance of icy and snowy roads that is not restricted by the environment. In the prediction of the anti-skid performance of asphalt pavement in icy and snowy weather, this model only needs to clarify the ice thickness of the road surface, snowfall (snow thickness), road surface temperature, and ice-snow mixture thickness.

[0045] like Figure 1 As shown in the figure, in the process of establishing the friction coefficient prediction model for icy pavement, the surface characteristics of the icy pavement are first observed. The initial thin ice pavement is formed by gradually cooling the wet pavement to form an ice layer on the road surface. The water on the surface of the coarse aggregate flows to the gaps between the coarse aggregate due to gravity. When the water film reaches the freezing temperature, the surface of the coarse aggregate is basically in a dry state. Therefore, after cooling, the ice layer only appears in the gaps between the coarse aggregate, and no ice layer is formed on its surface. In addition, since the road surface has the ability to drain water laterally, the thickness of the ice layer formed in the gaps between the coarse aggregate is very thin, and the friction coefficient and swing value of the road surface do not change significantly. It can be seen that under the condition of normal drainage on the road surface, the cooling and freezing of the wet road surface after snow removal has little effect on the anti-skid performance of the road surface.

[0046] like Figure 2 As shown in the figure, when spraying water mist, the road surface temperature is between -5℃ and -6℃, which is equivalent to a cold wall surface, and the aggregate has hydrophilic characteristics. Therefore, after the water droplets come into contact with the surface of the coarse aggregate, they do not gather and flow, but quickly condense to form an ice layer, which makes the ice layer on the road surface increase continuously. After the third spraying, the road surface state sensor detected a water film (such as Figure 2 ), indicating that the micro texture of the coarse aggregate on the road surface has been completely covered by the ice layer, and the tire rubber will only be in contact with the ice layer; and the further growth of the ice layer begins to develop into the gaps between the coarse aggregates, reducing the volume of the tire rubber embedded in the road surface.

[0047] like Figure 3 As shown in the figure, T2GO continuously collects the friction coefficient at different positions of the road surface, and the results are represented by a box plot (corresponding to the left vertical axis), and the mean is connected by a straight line to reflect the change law of the friction coefficient; BPN is the mean of the results of 5 tests (corresponding to the right vertical axis). With the increase in the number of spraying times, the mean of the tire-road friction coefficient and BPN show similar change laws. The attenuation of the road surface anti-skid performance is mainly concentrated in the first three ice-covering processes. It can be seen that the accumulation of ice on the surface of coarse aggregate is the main reason for the decline in the road surface anti-skid performance.

[0048] like Figure 4As shown in the figure, in the process of establishing the friction coefficient prediction model of snow-covered road surface, the surface characteristics of the snow-covered road surface are first observed. After the first snowfall and compaction, the snow filled the gaps between the coarse aggregates, but the edges and corners of the top of most of the coarse aggregates were still clearly visible; after the second snowfall and compaction, only a few coarse aggregates were not completely covered by the snow, and the snow layer left clear tire marks; after the third snowfall and compaction, the road surface was completely covered by snow.

[0049] Similar to ice, the contact between tire rubber and snow will also cause the road surface's anti-skid performance to decrease; however, due to the soft and loose nature of the snow layer, the interaction between the tire rubber and the macro texture of the road surface under the snow layer is still effective, and the tire rubber embedded in the snow layer also has the effect of increasing friction, so the overall level of anti-skid performance of snowy roads is higher than that of icy roads. When the snow layer falls on the road surface, it first appears in a floating snow state, and then changes to a compacted state after being rolled by the tire load. When the traffic volume is large, the road surface will not accumulate too much floating snow, but when the traffic volume is small, a mixed state of compacted bottom snow and loose surface snow will appear.

[0050] like Figure 5 As shown in the figure, the friction coefficient of the snow-covered road surface in a mixed state of floating snow and compacted snow decreases with the increase of the thickness of the compacted snow layer at the bottom, and the friction coefficient is restored after being compacted by the tires. That is, the friction coefficient of the snow-covered road surface in the compacted state is almost not affected by the increase of the snow layer thickness, and its mean value is stable at around 0.45.

[0051] The bonding force between the snow layer and the surface of the coarse aggregate is not as strong as that between the ice layer. Therefore, in addition to the low friction between the rubber and snow layer interface, the relative sliding inside the snow layer will also affect the anti-skid performance of the snow-covered road surface. For snow-covered roads in a mixed state of floating snow and compacted snow, there is no effective bonding between the floating snow and the compacted snow during the tire rolling process. If the floating snow is not sufficiently constrained by the macro texture at this time, a large degree of relative sliding will occur within the snow layer, resulting in a decrease in friction. Therefore, when the thickness of the bottom compacted snow increases and the gaps between the coarse aggregates are filled, resulting in a decrease in the structural depth, the constraint of the macro texture on the floating snow decreases, and the anti-skid performance of the road surface is significantly reduced.

[0052] For compacted snow layers, part of the snow is embedded in the macro texture, and the snow layer has strong adhesion, so it is not easy for the layers to slide relative to each other during tire braking. Therefore, the increase in snow layer thickness does not significantly affect the anti-skid performance of compacted snowy roads. However, the increase in road surface temperature will make the compacted snow layer fluffy, reduce the adhesion within the snow layer, and lead to a decrease in the friction coefficient.

[0053] like Figure 6 As shown in the figure, for the snow-melting road surface, as the melting time increases, an obvious ice layer appears on the road surface, and the road surface state gradually changes from compacted snow to a mixed state of snow-ice-water. The thickness of the snow layer continues to decrease, and finally the original texture of the road surface is revealed.

[0054] like Figure 7 , Figure 8 As shown in the figure, from 0 to 30 minutes, although the road surface temperature is stable between -1 and 0℃, the snow layer becomes fluffy due to the absorption of environmental heat, and its thickness increases. Then, the water film formed by the melting of the snow on the surface penetrates downward and is absorbed by the snow layer to form an ice layer, resulting in a further reduction in the friction coefficient. From 30 to 80 minutes, the thin ice layer on the surface of the snow continues to melt, and part of the formed water film penetrates into the snow below, causing the snow to turn into an ice layer, and the other part flows on the surface of the ice layer, so the thickness of the ice layer and the water film both increase; at this stage, the ice and snow cover still completely covers the original texture of the road surface, and the tire rubber only contacts the ice layer, so the reduction in the thickness of the snow layer has no effect on the friction coefficient. From 90 to 120 minutes, the thickness of the snow layer continues to decrease, and the ice layer thickness begins to decrease after reaching the maximum value, and the original texture of the road surface in some areas begins to appear, so that the anti-skid performance is restored.

[0055] In the early stage of melting, since there was no obvious ice layer on the road surface, the pendulum instrument could not be used for testing; however, the anti-skid performance of the road surface was tested using the pendulum instrument 40 minutes after melting. Although the pendulum value showed a similar change pattern to the friction coefficient, its growth rate was significantly faster. After melting for 120 minutes, the pendulum value had returned to the level of a normal wet road surface.

[0056] like Fig. 9 As shown in the figure, for icy pavement, the ice layer reduces the anti-skid performance of the pavement by covering the micro-texture of the coarse aggregate surface and the macro-texture composed of the gaps between the coarse aggregates. Therefore, the thickness of the ice layer has a decisive influence on the friction coefficient of the icy pavement. By using the nonlinear regression method to establish the friction coefficient prediction equation, it can be found that there is a good exponential function relationship between the ice layer thickness and the friction coefficient, and the goodness of fit is 0.986. For the melting snow pavement, the snow layer on the surface will turn into an ice layer. Although the tire rubber only contacts the thin ice layer on the surface during braking, the snow layer under the ice layer that has not melted also plays a role in covering the original texture of the road surface. Therefore, both the ice layer and the snow layer have a negative impact on the anti-skid performance of the pavement. There is a good exponential function relationship between the total thickness of ice and snow on the snow-melting pavement and the friction coefficient, and the goodness of fit is 0.989. Comparing the friction coefficient fitting curves of the snow-melting pavement and the icy pavement, when the covering thickness is greater than 0.5 mm, the two curves basically coincide; when the covering thickness is less than 0.5 mm, the value of the icy pavement fitting curve is lower. This is because when the snow melts, the texture and edges of the top surface of the coarse aggregate are restored first, and the residual ice and snow mixture is located in the gaps between the coarse aggregate. The ice layer in the gaps has relatively little effect on the anti-skid performance of the road surface, so the friction coefficient of the road surface is higher.

[0057] like Figure 6As shown in the figure, for roads with floating snow or floating snow-compacted snow, the thickness of the snow layer is the key to determining the sliding between the inner layers of the snow layer. When the snowfall is less than 10 mm, the average tire-road friction coefficient is 0.46; when the snowfall is between 10 mm and 20 mm, the average friction coefficient is 0.42; when the snowfall is between 20 mm and 30 mm, the average friction coefficient is 0.36.

[0058] like Fig.10 As shown in the figure, for compacted snow, the relative sliding between layers within the snow layer is mainly affected by the road surface temperature. There is a good exponential function relationship between the road surface temperature and the friction coefficient, and the goodness of fit is 0.989.

[0059] Based on the analysis of the anti-skid performance test results of the aforementioned icy road surface, snowy road surface, and snow-melted road surface, the prediction model of the friction coefficient of different road surface conditions can be summarized as shown in Table 1 below.

[0060] Table 1 Prediction model of friction coefficient of snow-covered road surface

[0061]

[0062] Calculation example:

[0063] In February 2019, a highway in northern my country was closed for a long time due to snowfall. The data of a monitoring point during the closure was substituted into the corresponding friction coefficient prediction model, and the calculation results are shown in the figure below. The predicted values ​​of the road friction coefficient during the closure of the highway are in the following order from small to large: ice-snow mixed road surface (0.25-0.36), ice-water mixed road surface (0.36-0.62), snow-covered road surface (0.41-0.42) and dry road surface (1.23).

[0064] The present invention respectively demonstrates the decisive influencing factors of the pavement anti-skid performance of icy pavement, snowy pavement and snow-melted pavement, and defines the pavement friction coefficient prediction models under different pavement conditions, so as to realize the real-time prediction of the pavement friction coefficient of highways under icy and snowy weather conditions, and provide a reference basis for the intelligent management and control of highways.

[0065] The embodiments described above are only descriptions of the preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the protection scope determined by the claims of the present invention.

Claims

1. A method for predicting friction coefficient of asphalt pavement in snowy weather, characterized in that: include: According to the decay relationship between the pavement ice thickness and the pavement anti-skid performance, a nonlinear regression method is used to fit the icy pavement friction coefficient prediction model. According to the relationship between the snow accumulation state and the relative sliding inside the snow layer, the road friction coefficient prediction model under the floating snow-compacted snow state and compacted snow state is obtained; According to the influence of the thickness change of snow and ice layer on the road surface during snow melting on the anti-skid ability of the road surface, the relationship between the total thickness of ice-snow mixture and the friction coefficient is fitted, and a prediction model of road friction coefficient under snow melting conditions is obtained.

2. The method for predicting the friction coefficient of asphalt pavement in snowy weather according to claim 1 is characterized in that: include: The cumulative simulation method of the road surface ice layer laboratory is as follows: first, precipitate the road surface at room temperature to make it completely wet, then quickly lower the ambient temperature to form an ice layer on the road surface, and complete relevant tests; then, control the road surface temperature at -6℃~-5℃, use a spray bottle to spray water mist on the road surface, wait for 5 minutes after each spraying, and then complete relevant tests; finally, use the icing function of the environmental chamber to perform low-temperature precipitation at -5℃ until the ice layer completely covers the macro texture of the road surface, forming a thick ice road surface for testing the minimum value of the anti-skid performance of the icy road surface.

3. The method for predicting the friction coefficient of asphalt pavement in snowy weather according to claim 1, characterized in that: include: The simulation of snow accumulation on a road surface is completed through artificial snowfall. Three artificial snowfalls are carried out on a dry road surface at -10°C, and the thickness of the floating snow is 5 to 8 mm each time. After the snowfall is completed, the anti-skid performance of the floating snow or floating snow-compacted snow mixed road surface is tested first, and then the floating snow is rolled back and forth 5 times by the T2GO test wheels to form a compacted snow road surface, and then the snow-covered road surface in a compacted state is tested. After the test is completed after the third snowfall, the ambient temperature is gradually increased to 0°C to test the friction coefficient of the snow-covered road surface under different temperature conditions.

4. The method for predicting the friction coefficient of asphalt pavement in snowy weather according to claim 3 is characterized in that: After the friction coefficient test of the snow-covered road surface is completed, the ambient temperature is adjusted to 10℃. When the road surface temperature rises to -1℃~0℃, the thickness of the road surface cover is detected and the anti-skid performance of the road surface is tested. This time point is recorded as 0min as the starting point of the snow road surface melting test, and then the test is carried out every 10min.

5. The method for predicting the friction coefficient of asphalt pavement in snowy weather according to claim 3 is characterized in that: T2GO is used to continuously collect the friction coefficient at different positions, and the change law of the friction coefficient is reflected by connecting the mean value with a straight line; the pendulum instrument tests the swing value of the road surface and records the mean value of the test results; the friction coefficient prediction model of asphalt pavement under icy road conditions is obtained: Where μ is the friction coefficient and x1 is the thickness of the ice layer (mm).

6. The method for predicting the friction coefficient of asphalt pavement in snowy weather according to claim 3 is characterized in that: The friction coefficient prediction model of snow-covered road surface under different compaction degrees is as follows: Floating and compacted snow conditions: Snowfall: <10 mm, μ = 0.46; Snowfall: 10-20 mm, μ = 0.42; Snowfall: 20-30 mm, μ = 0.36; Compacted snow status: Wherein, μ is the friction coefficient; x2 is the road surface temperature, and x2 is -10 to 0°C.

7. The method for predicting the friction coefficient of asphalt pavement in snowy weather according to claim 4, characterized in that: The friction coefficient prediction model of the road surface under different snow melting conditions is as follows: Where, μ is the friction coefficient; x3 is the thickness of the ice-snow mixture (mm).

Images