Road black ice detection method and detection device

Abstract

The invention provides a road black ice detection method and device, and the method comprises the steps: collecting a road surface temperature value, an air humidity value, a wind speed value and a vehicle flow value in real time for a target road under the condition of no rainfall; determining a dew point temperature value based on the road surface temperature value and the air humidity value, and judging whether the road surface temperature value and the duration at the current moment meet a dew formation condition or not; if yes, determining a dew freezing index based on the dew point temperature value, the road surface temperature value and the duration time, and judging whether the dew freezing index is greater than or equal to a dew freezing threshold value or not; if yes, whether the road surface temperature value at the target moment is larger than or equal to the freezing point temperature value is judged; and if yes, determining a black ice freezing index based on the freezing point temperature value, the road surface temperature value, the wind speed value and the vehicle flow value so as to determine whether the black ice exists on the target road at the target moment. According to the method, the accuracy and efficiency of black ice detection and the road safety are improved.

Description

Technical Field

[0001] The present application relates to the technical field of highway black ice detection, and in particular to a method and device for detecting road black ice. Background Art

[0002] Black ice is a thin layer of ice that forms under conditions of low temperature and high humidity. It usually occurs between sunset and sunrise. Since black ice is difficult to identify with the naked eye, especially on highways, once it forms without warning, it can easily cause traffic accidents.

[0003] At present, the existing technology for detecting the formation of black ice on roads mainly includes: on the one hand, relying on overly heavy meteorological big data information and ice detection based on machine learning, which reduces the accuracy and efficiency of black ice detection; on the other hand, it is aimed at detecting the formation of ice on the road surface after precipitation, but it is impossible to detect the formation of black ice on the road surface without precipitation conditions. Black ice in the absence of precipitation conditions is formed when the driver and passengers are not mentally prepared, which poses a great threat to vehicle driving and reduces the safety of vehicle driving on the road. Summary of the invention

[0004] In view of this, the purpose of the present application is to provide a method and device for detecting black ice on roads. By real-time collection of data such as temperature and humidity on a target road in a highway without precipitation, it is determined whether the target road meets the condensation conditions, so as to calculate and judge the dew icing index under the condensation conditions. When the temperature drops below the freezing point, it is determined whether there is black ice on the target road at the target time based on the calculated black ice icing index, thereby improving the accuracy and efficiency of black ice detection, and thereby improving the safety of vehicle driving on the road.

[0005] The present application provides a method for detecting black ice on a road, the method comprising:

[0006] For a target road on a highway without precipitation, the road surface temperature value of the target road and the air humidity value, wind speed value and vehicle flow value corresponding to the target road are collected in real time;

[0007] Based on the road surface temperature value and the air humidity value, determining a dew point temperature value corresponding to the target road, and judging whether the road surface temperature value and duration of the target road at the current moment meet the condensation condition corresponding to the dew point temperature value;

[0008] If the condensation condition is met, the dew icing index of the target road at the current moment is determined using a preset dew icing index formula based on the dew point temperature value, the road surface temperature value and the duration, and it is determined whether the dew icing index is greater than or equal to a preset dew icing threshold value;

[0009] If it is greater than or equal to the dew freezing threshold, determining whether the road surface temperature value of the target road at a target time after the current time is greater than or equal to a preset freezing point temperature value;

[0010] If it is greater than or equal to the freezing point temperature value, then based on the freezing point temperature value, the road surface temperature value, the wind speed value and the vehicle flow value, a preset black ice icing index formula is used to determine the black ice icing index of the target road at the target time, and based on the black ice icing index, determine whether there is black ice on the target road at the target time.

[0011] Furthermore, the detection method also includes:

[0012] In response to obtaining result feedback information sent by the user according to the actual black ice situation, based on the result feedback information, the first empirical coefficient in the dew freezing index formula and the black ice freezing index formula are respectively adjusted to the second empirical coefficient to update the dew freezing index formula and the black ice freezing index formula.

[0013] Further, in response to obtaining result feedback information sent by the user according to the actual black ice situation, based on the result feedback information, adjusting the first empirical coefficient in the dew freezing index formula and the black ice freezing index formula to the second empirical coefficient respectively to update the dew freezing index formula and the black ice freezing index formula, including:

[0014] In response to obtaining result feedback information sent by the user according to the actual black ice situation, determining a feedback change amount corresponding to the result feedback information;

[0015] Based on the feedback change amount and the first condensation empirical coefficient in the dew freezing index formula, a second condensation empirical coefficient is determined using a preset empirical coefficient adjustment formula, and the first condensation empirical coefficient in the dew freezing index formula is adjusted to the second condensation empirical coefficient to update the dew freezing index formula;

[0016] Based on the feedback change and the first icing empirical coefficient in the black ice icing index formula, a second icing empirical coefficient is determined using a preset empirical coefficient adjustment formula, and the first icing empirical coefficient in the black ice icing index formula is adjusted to the second icing empirical coefficient to update the black ice icing index formula.

[0017] Furthermore, the determining of the dew point temperature value corresponding to the target road based on the road surface temperature value and the air humidity value includes:

[0018] Based on the road surface temperature value and the air humidity value, using a preset temperature and humidity function to calculate temperature and humidity variables;

[0019] Based on the temperature and humidity variables, a dew point temperature value corresponding to the target road is determined using a preset dew point formula.

[0020] Further, the determining whether the road surface temperature value and duration of the target road at the current moment meet the condensation condition corresponding to the dew point temperature value includes:

[0021] Determining whether the road surface temperature value of the target road at the current moment belongs to the condensation temperature interval corresponding to the dew point temperature value;

[0022] If the road surface temperature value does not belong to the condensation temperature range, it is determined that the condensation condition is not met;

[0023] If the road surface temperature value belongs to the condensation temperature interval, then for the current moment, determining whether the duration corresponding to the road surface temperature value belonging to the condensation temperature interval is greater than a preset time threshold;

[0024] If the duration is less than or equal to the preset time threshold, it is determined that the condensation condition is not met;

[0025] If the duration is greater than the preset time threshold, it is determined that the condensation condition is met.

[0026] Further, the condensation temperature range corresponding to the dew point temperature value is determined by the following steps:

[0027] Determine the dew point temperature value as the upper limit value corresponding to the dew condensation temperature interval, and determine the preset freezing point temperature value as the lower limit value corresponding to the dew condensation temperature interval;

[0028] Based on the upper limit value and the lower limit value, a condensation temperature interval corresponding to the dew point temperature value is determined.

[0029] Further, the determining whether there is black ice on the target road at the target time based on the black ice icing index includes:

[0030] Determining whether the black ice freezing index is greater than or equal to a preset black ice freezing threshold;

[0031] If the black ice icing index is less than the black ice icing threshold, determining that there is no black ice on the target road at the target time;

[0032] If the black ice icing index is greater than or equal to the black ice icing threshold, it is determined that black ice exists on the target road at the target time.

[0033] The present application also provides a device for detecting black ice on a road, the device comprising:

[0034] A data acquisition module is used to collect the road surface temperature value of the target road in the expressway and the air humidity value, wind speed value and vehicle flow value corresponding to the target road in real time;

[0035] a condensation judgment module, configured to determine a dew point temperature value corresponding to the target road based on the road surface temperature value and the air humidity value, and to judge whether the road surface temperature value and duration of the target road at a current moment meet a condensation condition corresponding to the dew point temperature value;

[0036] an icing judgment module, configured to determine the dew icing index of the target road at the current moment by using a preset dew icing index formula based on the dew point temperature value, the road surface temperature value and the duration if the condensation condition is met, and to judge whether the dew icing index is greater than or equal to a preset dew icing threshold value;

[0037] A freezing point judgment module, used to judge whether the road surface temperature value of the target road at a target time after the current time is greater than or equal to a preset freezing point temperature value if it is greater than or equal to the dew freezing threshold;

[0038] The black ice judgment module is used to determine the black ice icing index of the target road at the target time based on the freezing point temperature value, the road surface temperature value, the wind speed value and the vehicle flow value if it is greater than or equal to the freezing point temperature value, and determine whether there is black ice on the target road at the target time based on the black ice icing index.

[0039] Furthermore, the detection device further includes a coefficient adjustment module, and the coefficient adjustment module is used to:

[0040] In response to obtaining result feedback information sent by the user according to the actual black ice situation, based on the result feedback information, the first empirical coefficient in the dew freezing index formula and the black ice freezing index formula are respectively adjusted to the second empirical coefficient to update the dew freezing index formula and the black ice freezing index formula.

[0041] Further, when the coefficient adjustment module is used to respond to the result feedback information sent by the user according to the actual black ice situation, based on the result feedback information, adjust the first empirical coefficient in the dew freezing index formula and the black ice freezing index formula to the second empirical coefficient to update the dew freezing index formula and the black ice freezing index formula, the coefficient adjustment module is used to:

[0042] In response to obtaining result feedback information sent by the user according to the actual black ice situation, determining a feedback change amount corresponding to the result feedback information;

[0043] Based on the feedback change amount and the first condensation empirical coefficient in the dew freezing index formula, a second condensation empirical coefficient is determined using a preset empirical coefficient adjustment formula, and the first condensation empirical coefficient in the dew freezing index formula is adjusted to the second condensation empirical coefficient to update the dew freezing index formula;

[0044] Based on the feedback change and the first icing empirical coefficient in the black ice icing index formula, a second icing empirical coefficient is determined using a preset empirical coefficient adjustment formula, and the first icing empirical coefficient in the black ice icing index formula is adjusted to the second icing empirical coefficient to update the black ice icing index formula.

[0045] Further, when the condensation judgment module is used to determine the dew point temperature value corresponding to the target road based on the road surface temperature value and the air humidity value, the condensation judgment module is used to:

[0046] Based on the road surface temperature value and the air humidity value, using a preset temperature and humidity function to calculate temperature and humidity variables;

[0047] Based on the temperature and humidity variables, a dew point temperature value corresponding to the target road is determined using a preset dew point formula.

[0048] Furthermore, when the condensation judgment module is used to judge whether the road surface temperature value and duration of the target road at the current moment meet the condensation condition corresponding to the dew point temperature value, the condensation judgment module is used to:

[0049] Determining whether the road surface temperature value of the target road at the current moment belongs to the condensation temperature interval corresponding to the dew point temperature value;

[0050] If the road surface temperature value does not belong to the condensation temperature range, it is determined that the condensation condition is not met;

[0051] If the road surface temperature value belongs to the condensation temperature interval, then for the current moment, determining whether the duration corresponding to the road surface temperature value belonging to the condensation temperature interval is greater than a preset time threshold;

[0052] If the duration is less than or equal to the preset time threshold, it is determined that the condensation condition is not met;

[0053] If the duration is greater than the preset time threshold, it is determined that the condensation condition is met.

[0054] Furthermore, when the condensation judgment module is used to determine the condensation temperature interval corresponding to the dew point temperature value, the condensation judgment module is used to:

[0055] Determine the dew point temperature value as the upper limit value corresponding to the dew condensation temperature interval, and determine the preset freezing point temperature value as the lower limit value corresponding to the dew condensation temperature interval;

[0056] Based on the upper limit value and the lower limit value, a condensation temperature interval corresponding to the dew point temperature value is determined.

[0057] Further, when the black ice determination module is used to determine whether there is black ice on the target road at the target time based on the black ice icing index, the black ice determination module is used to:

[0058] Determining whether the black ice freezing index is greater than or equal to a preset black ice freezing threshold;

[0059] If the black ice icing index is less than the black ice icing threshold, determining that there is no black ice on the target road at the target time;

[0060] If the black ice icing index is greater than or equal to the black ice icing threshold, it is determined that black ice exists on the target road at the target time.

[0061] An embodiment of the present application also provides an electronic device, including: a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate through the bus, and when the machine-readable instructions are executed by the processor, the steps of the method for detecting black ice on the road as described above are performed.

[0062] An embodiment of the present application further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the method for detecting black ice on roads as described above are executed.

[0063] The present application provides a method and device for detecting black ice on roads, the method comprising: for a target road on a highway without precipitation, collecting the road surface temperature value of the target road and the air humidity value, wind speed value and vehicle flow value corresponding to the target road in real time; determining the dew point temperature value corresponding to the target road based on the road surface temperature value and the air humidity value, and judging whether the road surface temperature value and duration of the target road at the current moment meet the condensation condition corresponding to the dew point temperature value; if the condensation condition is met, determining the dew icing index based on the dew point temperature value, the road surface temperature value and the duration using a preset dew icing index formula. The dew freezing index of the target road at the current moment is determined, and whether the dew freezing index is greater than or equal to a preset dew freezing threshold value; if it is greater than or equal to the dew freezing threshold value, whether the road surface temperature value of the target road at a target moment after the current moment is greater than or equal to a preset freezing point temperature value; if it is greater than or equal to the freezing point temperature value, based on the freezing point temperature value, the road surface temperature value, the wind speed value and the vehicle flow value, the black ice freezing index of the target road at the target moment is determined using a preset black ice freezing index formula, and based on the black ice freezing index, whether there is black ice on the target road at the target moment.

[0064] Compared with the existing methods that rely on excessively heavy meteorological big data information and machine learning-based ice detection and detection of road ice formation after precipitation, the real-time collection of data such as temperature and humidity of the target road in the highway under non-precipitation conditions is carried out to determine whether the target road meets the condensation conditions, so as to calculate and judge the dew icing index under the condensation conditions, and when the temperature drops below the freezing point, it is determined whether there is black ice on the target road at the target time based on the calculated black ice icing index, thereby improving the accuracy and efficiency of black ice detection, and thereby improving the safety of vehicle driving on the road.

[0065] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, preferred embodiments are specifically cited below and described in detail with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0067] Figure 1 One of the flow charts of a method for detecting black ice on a road provided in an embodiment of the present application;

[0068] Figure 2 A second flowchart of a method for detecting black ice on a road provided in an embodiment of the present application;

[0069] Figure 3 This is one of the structural schematic diagrams of a road black ice detection device provided in an embodiment of the present application;

[0070] Figure 4 A second structural schematic diagram of a device for detecting black ice on a road provided in an embodiment of the present application;

[0071] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0072] To make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application usually described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, each other embodiment obtained by those skilled in the art without making creative work belongs to the scope of protection of the present application.

[0073] Research has found that, at present, the existing technology for detecting the formation of black ice on the road mainly includes: on the one hand, relying on overly heavy meteorological big data information and ice detection based on machine learning, which reduces the accuracy and efficiency of black ice detection; on the other hand, it is aimed at detecting the formation of ice on the road surface after precipitation, but it is impossible to detect the formation of black ice on the road surface without precipitation conditions. Black ice in the absence of precipitation conditions is formed when the driver and passengers are not mentally prepared, which poses a great hazard to vehicle driving and reduces the safety of vehicle driving on the road.

[0074] Based on this, an embodiment of the present application provides a method for detecting black ice on roads. By real-time collection of data such as temperature and humidity on a target road in a highway without precipitation, it is determined whether the target road meets condensation conditions, so as to calculate and judge the dew icing index under the condensation conditions. When the temperature drops below the freezing point, it is determined whether there is black ice on the target road at the target time based on the calculated black ice icing index, thereby improving the accuracy and efficiency of black ice detection, and thereby improving the safety of vehicle driving on the road.

[0075] See also Figure 1 , Figure 1 This is one of the flow charts of a method for detecting black ice on roads provided in an embodiment of the present application. Figure 1 As shown in the figure, the method for detecting black ice on roads provided in the embodiment of the present application includes:

[0076] S101. For a target road on a highway without precipitation, a road surface temperature value of the target road and an air humidity value, a wind speed value, and a vehicle flow value corresponding to the target road are collected in real time.

[0077] It should be noted that in the embodiment of the present application, the target road is not limited to an expressway, but may also be a highway that can collect the road surface temperature value and the air humidity value, wind speed value and vehicle flow value corresponding to the road in real time.

[0078] In the embodiment of the present application, the no precipitation condition means that no precipitation occurs in the space where the target road is located during the detection period of the embodiment of the present application.

[0079] In this step, for the target road in the expressway under non-precipitation conditions, the road surface temperature value of the target road is collected in real time by a surveillance camera with thermal imaging function in the target road; the meteorological information data such as the air humidity value and wind speed value corresponding to the target road is collected in real time by a small meteorological station along the target road; and the vehicle flow value corresponding to the target road is collected in real time by a gantry ETC antenna installed on the target road.

[0080] In summary, by collecting the road surface temperature, air humidity, wind speed and vehicle flow values ​​of the target road section in real time, the dependence on complex meteorological data is significantly reduced, which not only reduces the implementation cost but also improves the flexibility and real-time performance of black ice detection.

[0081] S102. Determine a dew point temperature value corresponding to the target road based on the road surface temperature value and the air humidity value, and judge whether the road surface temperature value and duration of the target road at the current moment meet the condensation condition corresponding to the dew point temperature value.

[0082] In the embodiment of the present application, the dew point temperature value is the temperature value when the air is cooled to a saturated state (i.e., the relative humidity reaches 100%) while the water vapor content remains unchanged. When the air temperature drops to the dew point temperature, the water vapor in the air will begin to condense into liquid water, forming dewdrops, fog or clouds; among them, the dew point temperature value can help us understand the humidity level in the air. A higher dew point temperature means that the air contains more moisture, while a lower dew point means that the air is drier.

[0083] Here, the condensation condition corresponding to the dew point temperature value includes: the road surface temperature value belongs to the condensation temperature interval corresponding to the dew point temperature value and the duration corresponding to the road surface temperature value belonging to the condensation temperature interval is greater than a preset time threshold.

[0084] In this way, if the condensation condition corresponding to the dew point temperature value is met, it indicates that there is a possibility of condensation on the target road, and the target road enters a condensation state, and has sufficient time to accumulate sufficient dew required for ice formation.

[0085] Specifically, in order to capture the changes in the condensation state, a duration variable is introduced to describe the duration of condensation. When the condensation time reaches the preset time threshold, the amount of dew accumulated is sufficient to enter the next stage of black ice formation.

[0086] In one embodiment of the present application, in a specific implementation, the step of determining the dew point temperature value corresponding to the target road based on the road surface temperature value and the air humidity value in step S102 may include:

[0087] S1021. Based on the road surface temperature value and the air humidity value, calculate the temperature and humidity variables using a preset temperature and humidity function.

[0088] In this step, the road surface temperature value of the target road section and the air humidity value corresponding to the target road section are input into the expression of the preset temperature and humidity function to calculate the temperature and humidity variables.

[0089] S1022. Based on the temperature and humidity variables, determine the dew point temperature value corresponding to the target road using a preset dew point formula.

[0090] In this step, the temperature and humidity variables are input into the expression of the preset dew point formula to calculate the dew point temperature value corresponding to the target road.

[0091] In an embodiment of the present application, the expression of the preset dew point formula is as follows.

[0092]

[0093] Wherein, Td represents the dew point temperature value corresponding to the target road; α(T, RH) represents the temperature and humidity variables; T represents the road surface temperature value; RH represents the air humidity value; a and b are constants respectively.

[0094] In one embodiment of the present application, in a specific implementation, the step of determining in step S102 whether the road surface temperature value and duration of the target road at the current moment meet the condensation condition corresponding to the dew point temperature value may include:

[0095] S1023: Determine whether the road surface temperature value of the target road at the current moment belongs to the condensation temperature interval corresponding to the dew point temperature value.

[0096] In one implementation of the present application, during specific implementation, step S1023 may include:

[0097] S10231. Determine the dew point temperature value as the upper limit value corresponding to the dew condensation temperature range, and determine the preset freezing point temperature value as the lower limit value corresponding to the dew condensation temperature range.

[0098] In this step, the dew point temperature value calculated based on the road surface temperature value of the target section and the air humidity value corresponding to the target section is determined as the upper limit value corresponding to the condensation temperature range; then, the preset freezing point temperature value is determined as the lower limit value corresponding to the condensation temperature range.

[0099] The preset freezing point temperature value refers to the temperature at which pure water changes from liquid to solid (i.e., freezes) under standard atmospheric pressure (usually 101.325 kPa). For pure water, this temperature value is generally 0°C (32 degrees Fahrenheit or 273.15 Kelvin). When the water temperature drops to the freezing point, under appropriate conditions, water will begin to form ice crystals.

[0100] S10232. Determine a condensation temperature interval corresponding to the dew point temperature value based on the upper limit value and the lower limit value.

[0101] In an embodiment of the present application, when the dew point temperature value is Td and the preset freezing point temperature value is Tf, the condensation temperature interval corresponding to the dew point temperature value is (Tf, Td). For example, when the dew point temperature value is 5 and the preset freezing point temperature value is 0, the condensation temperature interval corresponding to the dew point temperature value is (0, 5).

[0102] S1024: If the road surface temperature value does not belong to the condensation temperature range, determine that the condensation condition is not met.

[0103] In this step, when the road surface temperature value does not belong to the condensation temperature interval formed by the dew point temperature value and the freezing point temperature value, it indicates that the temperature is too low and there is no dew or the temperature is too high and no ice will form, and it is determined that the condensation condition is not met at this time.

[0104] S1025: If the road surface temperature value belongs to the condensation temperature interval, then for the current moment, determine whether the duration corresponding to the road surface temperature value belonging to the condensation temperature interval is greater than a preset time threshold.

[0105] In this step, when the road surface temperature value belongs to the condensation temperature interval, it indicates that there is a possibility of condensation at this time, and the target road section enters the condensation state. It is further determined whether the target road section has sufficient time to complete the accumulation of sufficient dew required for freezing, that is, whether the duration corresponding to the road surface temperature value belonging to the condensation temperature interval is greater than the preset time threshold.

[0106] For example, when the road surface temperature value T of the target road section first belongs to the condensation temperature range (Tf, Td) at 15:05, and the time at this time is 15:10, during this time period, the road surface temperature value T has always belonged to the condensation temperature range (Tf, Td), and the duration is 5 minutes.

[0107] In the embodiment of the present application, the preset time threshold can be specifically calibrated according to the specific situation of the target road section, the experience of historical data and the actual detection requirements.

[0108] S1026: If the duration is less than or equal to the preset time threshold, determine that the condensation condition is not met.

[0109] In this step, when the duration is less than or equal to the preset time threshold, it indicates that the time for accumulating dew is too short and sufficient dew cannot be accumulated to freeze, and it is determined that the condensation condition is not met at this time.

[0110] S1027: If the duration is greater than the preset time threshold, it is determined that the condensation condition is met.

[0111] In the embodiment of the present application, since the formation of black ice is premised on the presence of sufficient dew on the road surface, in the judgment of the condensation state, when the road surface temperature value of the target road section belongs to the dew point temperature interval composed of the preset freezing point temperature value and the dew point temperature value, the moisture in the air gradually condenses into dew on the road surface. As time goes by, the dew gradually accumulates to form road black ice.

[0112] S103. If the condensation condition is met, the dew icing index of the target road at the current moment is determined using a preset dew icing index formula based on the dew point temperature value, the road surface temperature value and the duration, and a determination is made as to whether the dew icing index is greater than or equal to a preset dew icing threshold value.

[0113] In this step, when the road surface temperature value of the target road section meets the condensation condition corresponding to the dew point temperature value, the dew point temperature value, the road surface temperature value and the duration are input into a preset dew freezing index formula to determine the dew freezing index of the target road at the current moment.

[0114] In an embodiment of the present application, the preset dew freezing index formula is as follows.

[0115] CT dew =k1×(Td-T)×t.

[0116] Among them, CT dew It represents the dew freezing index of the target road at the current moment; Td represents the dew point temperature value corresponding to the target road; T represents the road surface temperature value of the target road; t represents the duration; k1 represents the first condensation experience coefficient, which is used to adjust the condensation speed under different conditions.

[0117] Here, the dew freezing index of the target road at the current moment can reflect the condensation state of the target road section, that is, when the road surface temperature value is higher than the freezing point temperature value but lower than the dew point temperature value, the water vapor in the air will condense into dew on the road surface. The greater the temperature difference between the dew point temperature value and the road surface temperature value, the faster the condensation process will be. If the condensation lasts long enough, the amount of dew will reach the conditions for forming black ice.

[0118] Furthermore, the dew freezing index of the target road at the current moment is numerically compared with a preset dew freezing threshold to determine whether the dew freezing index is greater than or equal to the preset dew freezing threshold.

[0119] Among them, the preset dew and ice threshold can be specifically calibrated according to the specific conditions of the target road section, the experience of historical data and the actual detection requirements.

[0120] Here, when the dew icing index of the target road at the current moment is greater than or equal to the preset dew icing threshold, it indicates that the dew accumulation has reached a sufficient amount, the condensation stage ends, and it is judged that the black ice formation stage has begun.

[0121] S104: If it is greater than or equal to the dew freezing threshold, determine whether the road surface temperature value of the target road at a target time after the current time is greater than or equal to a preset freezing point temperature value.

[0122] In this step, when the dew freezing index is greater than or equal to the preset dew freezing threshold, based on the current time of the target road, an externally specified or preset target time is selected from the times after the current time to determine whether the road surface temperature value at the target time is greater than or equal to the preset freezing point temperature value.

[0123] In an embodiment of the present application, after the dew is sufficiently formed, that is, the dew freezing index is greater than or equal to the preset dew freezing threshold, if the road surface temperature drops further until it drops below the freezing point temperature value, the dew will freeze rapidly to form road black ice.

[0124] Furthermore, when the dew freezing index is greater than or equal to the preset dew freezing threshold, if the road surface temperature value continues to rise, or the degree of decrease cannot reach the temperature value below the freezing point, there is no need to further detect and judge the formation of black ice.

[0125] S105. If it is greater than or equal to the freezing point temperature value, then based on the freezing point temperature value, the road surface temperature value, the wind speed value and the vehicle flow value, a preset black ice icing index formula is used to determine the black ice icing index of the target road at the target time, and based on the black ice icing index, determine whether there is black ice on the target road at the target time.

[0126] In this step, when the dew freezing index is greater than or equal to the preset dew freezing threshold, and the road surface temperature value at a target moment after the current moment is greater than or equal to the preset freezing point temperature value, the freezing point temperature value, the road surface temperature value, the wind speed value and the vehicle flow value are input into the preset black ice freezing index formula to determine the black ice freezing index of the target road at the target moment.

[0127] In an embodiment of the present application, the preset black ice freezing index formula is as follows.

[0128]

[0129] Among them, CT ice It represents the black ice freezing index of the target road at the target time; Tf represents the freezing point temperature value; W represents the wind speed value; D represents the vehicle flow value; T represents the road surface temperature value; k2, k3, k4 respectively represent the first icing experience coefficients, which are respectively used to adjust the influence of the temperature difference between the road surface temperature value and the freezing point temperature value, the wind speed value and the vehicle flow value on the freezing speed.

[0130] Here, the black ice freezing index is used to indicate that when dew has already formed, when the road surface temperature of the target road section drops below the freezing point temperature value, black ice begins to form. Specifically, the greater the temperature difference between the freezing point temperature value and the road surface temperature value, the faster the freezing speed; when the wind speed value is greater, it will help to speed up the cooling of the dew and accelerate the freezing; when the vehicle flow value is greater, the heat generated by vehicle friction and the disturbance of the dew will slow down the formation of black ice.

[0131] Further, in one embodiment of the present application, in a specific implementation, the step of determining whether there is black ice on the target road at the target time based on the black ice icing index in step S105 may include:

[0132] S1051. Determine whether the black ice freezing index is greater than or equal to a preset black ice freezing threshold.

[0133] In this step, the black ice icing index of the target road at the target time is numerically compared with a preset black ice icing threshold to determine whether the black ice icing index is greater than or equal to the preset black ice icing threshold.

[0134] Among them, the black ice threshold can be specifically calibrated according to the specific conditions of the target road section, the experience of historical data and the actual detection requirements.

[0135] S1052: If the black ice icing index is less than the black ice icing threshold, determine that there is no black ice on the target road at the target time.

[0136] S1053: If the black ice icing index is greater than or equal to the black ice icing threshold, it is determined that black ice exists on the target road at the target time.

[0137] In summary, in the embodiments of the present application, the formation process of black ice is described in stages, that is, from the judgment of the gradual accumulation of dew to the judgment of the freezing formation of black ice. The first stage reflects that the formation of dew needs to meet the dual conditions of temperature and time, and emphasizes the condensation process before the formation of black ice; the second stage integrates the influence of the temperature difference between the road surface temperature value and the freezing point temperature value, wind speed and traffic volume, and describes in detail the process of the speed of dew freezing, which can more accurately predict the timing of black ice formation, provide timely and reliable warnings for highway management and vehicle drivers, and reduce the occurrence of black ice accidents.

[0138] In this way, since the formation mechanism of black ice under non-precipitation conditions is taken into consideration and the relationship between the road surface temperature value, the dew point temperature value and the freezing point temperature value is analyzed, the condensation and icing process can be effectively identified, and accurate black ice prediction can be carried out comprehensively under various environmental conditions, especially at night and when the humidity changes greatly, thereby reducing the safety hazards caused by black ice.

[0139] Furthermore, based on the detection result of whether there is black ice on the target road at the target time, warning information is issued, and black ice warning information is issued for the target road section. At the same time, in conjunction with the highway information release system, passing vehicles are prompted, and the highway operation and management party is prompted to carry out relevant emergency plan disposal.

[0140] In this way, through the road black ice detection method provided by the embodiment of the present application, combined with the judgment process of black ice risk prediction, early warning information can be quickly issued. When the black ice risk is predicted, the system will notify the driver in time to provide them with better safety protection. This timely early warning mechanism significantly improves the driver's risk awareness and reduces potential traffic accidents.

[0141] Optional, see Figure 2 , Figure 2This is a second flow chart of a method for detecting black ice on a road provided in an embodiment of the present application. Figure 2 As shown in, the road black ice detection method provided in the embodiment of the present application includes step S106 in addition to steps S101 to S105. Specifically, step S106 is used to illustrate a method for adjusting the empirical coefficients in the dew icing index formula and the black ice icing index formula based on the result feedback information sent by the user according to the actual black ice situation, so as to improve the adaptability, accuracy and user trust of road black ice detection.

[0142] S106. In response to obtaining result feedback information sent by the user according to the actual black ice situation, based on the result feedback information, the first empirical coefficient in the dew freezing index formula and the black ice freezing index formula are respectively adjusted to the second empirical coefficient to update the dew freezing index formula and the black ice freezing index formula.

[0143] In an embodiment of the present application, the first empirical coefficient includes the first condensation empirical coefficient included in the dew freezing index formula and the first icing empirical coefficient included in the black ice freezing index formula.

[0144] Among them, the first condensation empirical coefficient is used to adjust the condensation speed under different conditions; the first freezing empirical coefficient includes three empirical coefficients, which are used to adjust the influence of the temperature difference between the road surface temperature value and the freezing point temperature value, the wind speed value and the vehicle flow value on the freezing speed.

[0145] In one implementation of the present application, during specific implementation, step S106 may include:

[0146] S1061. In response to obtaining result feedback information sent by the user according to actual black ice conditions, determine a feedback change amount corresponding to the result feedback information.

[0147] In this step, through feedback channels such as mobile applications or online platforms, users can send result feedback information based on actual conditions, including whether there is dew, whether there is ice, and the specific section and time of encountering black ice. Based on the result feedback information, the timestamp, location and other relevant data of the user's feedback are periodically recorded.

[0148] In an embodiment of the present application, when the result feedback information is that there is dew on the target road but black ice is not detected, the first preset value is determined as the feedback change amount; when the result feedback information is that there is ice on the target road but black ice is not detected, the second preset value is determined as the feedback change amount; when the result feedback information is that the black ice detection result is consistent with the actual situation, the third preset value is determined as the feedback change amount.

[0149] Among them, the first preset value is generally set to 1; the second preset value is generally set to -1; and the first preset value is generally set to 0.

[0150] S1062. Based on the feedback change and the first condensation empirical coefficient in the dew freezing index formula, a second condensation empirical coefficient is determined using a preset empirical coefficient adjustment formula, and the first condensation empirical coefficient in the dew freezing index formula is adjusted to the second condensation empirical coefficient to update the dew freezing index formula.

[0151] S1063. Based on the feedback change and the first icing empirical coefficient in the black ice icing index formula, a preset empirical coefficient adjustment formula is used to determine a second icing empirical coefficient, and the first icing empirical coefficient in the black ice icing index formula is adjusted to the second icing empirical coefficient to update the black ice icing index formula.

[0152] In the embodiment of the present application, the expression of the preset empirical coefficient adjustment formula is as follows.

[0153] k new =k old +α×Δk.

[0154] Among them, k new represents the second empirical coefficient (the second condensation empirical coefficient and the second icing empirical coefficient); k old represents the first empirical coefficient (the first condensation empirical coefficient and the first icing empirical coefficient); α represents the adjustment factor to determine the adjustment amplitude; Δk (1, -1 or 0) represents the feedback change amount corresponding to the result feedback information; the adjustment factor can be specifically set according to the accuracy and frequency of user feedback.

[0155] Here, the second empirical coefficient reflects the latest environmental conditions and user experience. Through the feedback information of user feedback and the adjustment of the empirical coefficient, it can more flexibly adapt to different environmental conditions and regional characteristics, improve the response capability to the formation of black ice, and can still perform effective black ice detection in the absence of accurate meteorological data.

[0156] In this way, by dynamically adjusting the empirical coefficient, the actual road conditions can be reflected more accurately, reducing false alarms and missed alarms in road black ice detection. At the same time, users are actively encouraged to participate in feedback and their trust in road black ice detection is enhanced to improve traffic safety on target roads.

[0157] The method for detecting black ice on roads provided in the embodiments of the present application determines whether the target road meets the condensation conditions by real-time collection of data such as temperature and humidity on the target road in the highway under non-precipitation conditions, so as to calculate and determine the dew icing index under the condensation conditions. When the temperature drops below the freezing point, it is determined whether there is black ice on the target road at the target time based on the calculated black ice icing index, thereby improving the accuracy and efficiency of black ice detection and further improving the safety of vehicle driving on the road.

[0158] See also Figure 3 , Figure 4 , Figure 3 This is one of the structural schematic diagrams of a road black ice detection device provided in an embodiment of the present application. Figure 4 This is a second structural diagram of a road black ice detection device provided in an embodiment of the present application. Figure 3 As shown in , the detection device 300 includes:

[0159] The data acquisition module 310 is used to collect the road surface temperature value of the target road in the highway and the air humidity value, wind speed value and vehicle flow value corresponding to the target road in real time;

[0160] A condensation determination module 320 is used to determine the dew point temperature value corresponding to the target road based on the road surface temperature value and the air humidity value, and to determine whether the road surface temperature value and duration of the target road at the current moment meet the condensation condition corresponding to the dew point temperature value;

[0161] The icing judgment module 330 is used to determine the dew icing index of the target road at the current moment by using a preset dew icing index formula based on the dew point temperature value, the road surface temperature value and the duration if the condensation condition is met, and to judge whether the dew icing index is greater than or equal to a preset dew icing threshold value;

[0162] The freezing point judgment module 340 is used to judge whether the road surface temperature value of the target road at a target time after the current time is greater than or equal to a preset freezing point temperature value if it is greater than or equal to the dew freezing threshold;

[0163] The black ice judgment module 350 is used to determine the black ice icing index of the target road at the target time based on the freezing point temperature value, the road surface temperature value, the wind speed value and the vehicle flow value if it is greater than or equal to the freezing point temperature value, and determine whether there is black ice on the target road at the target time based on the black ice icing index.

[0164] Further, such as Figure 4As shown in , the detection device 300 further includes a coefficient adjustment module 360, and the coefficient adjustment module 360 ​​is used to:

[0165] In response to obtaining result feedback information sent by the user according to the actual black ice situation, based on the result feedback information, the first empirical coefficient in the dew freezing index formula and the black ice freezing index formula are respectively adjusted to the second empirical coefficient to update the dew freezing index formula and the black ice freezing index formula.

[0166] Further, the coefficient adjustment module 360 ​​is used to respond to the result feedback information sent by the user according to the actual black ice situation, and based on the result feedback information, adjust the first empirical coefficient in the dew freezing index formula and the black ice freezing index formula to the second empirical coefficient to update the dew freezing index formula and the black ice freezing index formula. The coefficient adjustment module 360 ​​is used to:

[0167] In response to obtaining result feedback information sent by the user according to the actual black ice situation, determining a feedback change amount corresponding to the result feedback information;

[0168] Based on the feedback change amount and the first condensation empirical coefficient in the dew freezing index formula, a second condensation empirical coefficient is determined using a preset empirical coefficient adjustment formula, and the first condensation empirical coefficient in the dew freezing index formula is adjusted to the second condensation empirical coefficient to update the dew freezing index formula;

[0169] Based on the feedback change and the first icing empirical coefficient in the black ice icing index formula, a second icing empirical coefficient is determined using a preset empirical coefficient adjustment formula, and the first icing empirical coefficient in the black ice icing index formula is adjusted to the second icing empirical coefficient to update the black ice icing index formula.

[0170] Further, when the condensation determination module 320 is used to determine the dew point temperature value corresponding to the target road based on the road surface temperature value and the air humidity value, the condensation determination module 320 is used to:

[0171] Based on the road surface temperature value and the air humidity value, using a preset temperature and humidity function to calculate temperature and humidity variables;

[0172] Based on the temperature and humidity variables, a dew point temperature value corresponding to the target road is determined using a preset dew point formula.

[0173] Furthermore, when the condensation judgment module 320 is used to judge whether the road surface temperature value and duration of the target road at the current moment meet the condensation condition corresponding to the dew point temperature value, the condensation judgment module 320 is used to:

[0174] Determining whether the road surface temperature value of the target road at the current moment belongs to the condensation temperature interval corresponding to the dew point temperature value;

[0175] If the road surface temperature value does not belong to the condensation temperature range, it is determined that the condensation condition is not met;

[0176] If the road surface temperature value belongs to the condensation temperature interval, then for the current moment, determining whether the duration corresponding to the road surface temperature value belonging to the condensation temperature interval is greater than a preset time threshold;

[0177] If the duration is less than or equal to the preset time threshold, it is determined that the condensation condition is not met;

[0178] If the duration is greater than the preset time threshold, it is determined that the condensation condition is met.

[0179] Furthermore, when the condensation determination module 320 is used to determine the condensation temperature interval corresponding to the dew point temperature value, the condensation determination module 320 is used to:

[0180] Determine the dew point temperature value as the upper limit value corresponding to the dew condensation temperature interval, and determine the preset freezing point temperature value as the lower limit value corresponding to the dew condensation temperature interval;

[0181] Based on the upper limit value and the lower limit value, a condensation temperature interval corresponding to the dew point temperature value is determined.

[0182] Further, when the black ice determination module 350 is used to determine whether the target road has black ice at the target time based on the black ice icing index, the black ice determination module 350 is used to:

[0183] Determining whether the black ice freezing index is greater than or equal to a preset black ice freezing threshold;

[0184] If the black ice icing index is less than the black ice icing threshold, determining that there is no black ice on the target road at the target time;

[0185] If the black ice icing index is greater than or equal to the black ice icing threshold, it is determined that black ice exists on the target road at the target time.

[0186] The road black ice detection device provided in the embodiment of the present application determines whether the target road meets the condensation conditions by real-time collection of data such as temperature and humidity on the target road in the highway under non-precipitation conditions, so as to calculate and determine the dew icing index under the condensation conditions. When the temperature drops below the freezing point, it determines whether there is black ice on the target road at the target time based on the calculated black ice icing index, thereby improving the accuracy and efficiency of black ice detection, and further improving the safety of vehicle driving on the road.

[0187] See also Figure 5 , Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 5 As shown in , the electronic device 500 includes a processor 510 , a memory 520 and a bus 530 .

[0188] The memory 520 stores machine-readable instructions executable by the processor 510. When the electronic device 500 is running, the processor 510 communicates with the memory 520 via the bus 530. When the machine-readable instructions are executed by the processor 510, the above-mentioned Figure 1 as well as Figure 2 The steps of the method for detecting black ice on roads in the method embodiment shown, and the specific implementation methods can be found in the method embodiment, which will not be repeated here.

[0189] The present application also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the computer program can execute the above-mentioned Figure 1 as well as Figure 2 The steps of the method for detecting black ice on roads in the method embodiment shown, and the specific implementation methods can be found in the method embodiment, which will not be repeated here.

[0190] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0191] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0192] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0193] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0194] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present application can essentially be embodied in the form of a software product, or in other words, the part that contributes to the prior art or the part of the technical solution. 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 application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0195] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present application, which are used to illustrate the technical solutions of the present application, rather than to limit them. The protection scope of the present application is not limited thereto. Although the present application is described in detail with reference to the above-mentioned embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-mentioned embodiments within the technical scope disclosed in the present application, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A method for detecting black ice on a road, characterized in that: The detection method comprises: For a target road on a highway without precipitation, the road surface temperature value of the target road and the air humidity value, wind speed value and vehicle flow value corresponding to the target road are collected in real time; Based on the road surface temperature value and the air humidity value, determining a dew point temperature value corresponding to the target road, and judging whether the road surface temperature value and duration of the target road at the current moment meet the condensation condition corresponding to the dew point temperature value; If the condensation condition is met, the dew icing index of the target road at the current moment is determined using a preset dew icing index formula based on the dew point temperature value, the road surface temperature value and the duration, and it is determined whether the dew icing index is greater than or equal to a preset dew icing threshold value; If it is greater than or equal to the dew freezing threshold, determining whether the road surface temperature value of the target road at a target time after the current time is greater than or equal to a preset freezing point temperature value; If it is greater than or equal to the freezing point temperature value, then based on the freezing point temperature value, the road surface temperature value, the wind speed value and the vehicle flow value, a preset black ice icing index formula is used to determine the black ice icing index of the target road at the target time, and based on the black ice icing index, determine whether there is black ice on the target road at the target time.

2. The method according to claim 1, characterized in that The detection method further comprises: In response to obtaining result feedback information sent by the user according to the actual black ice situation, based on the result feedback information, the first empirical coefficient in the dew freezing index formula and the black ice freezing index formula are respectively adjusted to the second empirical coefficient to update the dew freezing index formula and the black ice freezing index formula.

3. The method according to claim 2, characterized in that The step of responding to the result feedback information sent by the user according to the actual black ice situation and adjusting the first empirical coefficient in the dew freezing index formula and the black ice freezing index formula to the second empirical coefficient based on the result feedback information to update the dew freezing index formula and the black ice freezing index formula includes: In response to obtaining result feedback information sent by the user according to the actual black ice situation, determining a feedback change amount corresponding to the result feedback information; Based on the feedback change amount and the first condensation empirical coefficient in the dew freezing index formula, a second condensation empirical coefficient is determined using a preset empirical coefficient adjustment formula, and the first condensation empirical coefficient in the dew freezing index formula is adjusted to the second condensation empirical coefficient to update the dew freezing index formula; Based on the feedback change and the first icing empirical coefficient in the black ice icing index formula, a second icing empirical coefficient is determined using a preset empirical coefficient adjustment formula, and the first icing empirical coefficient in the black ice icing index formula is adjusted to the second icing empirical coefficient to update the black ice icing index formula.

4. The method according to claim 1, characterized in that The step of determining the dew point temperature value corresponding to the target road based on the road surface temperature value and the air humidity value includes: Based on the road surface temperature value and the air humidity value, using a preset temperature and humidity function to calculate temperature and humidity variables; Based on the temperature and humidity variables, a dew point temperature value corresponding to the target road is determined using a preset dew point formula.

5. The method according to claim 1, characterized in that The determining whether the road surface temperature value and duration of the target road at the current moment meet the condensation condition corresponding to the dew point temperature value includes: Determining whether the road surface temperature value of the target road at the current moment belongs to the condensation temperature interval corresponding to the dew point temperature value; If the road surface temperature value does not belong to the condensation temperature range, it is determined that the condensation condition is not met; If the road surface temperature value belongs to the condensation temperature interval, then for the current moment, determining whether the duration corresponding to the road surface temperature value belonging to the condensation temperature interval is greater than a preset time threshold; If the duration is less than or equal to the preset time threshold, it is determined that the condensation condition is not met; If the duration is greater than the preset time threshold, it is determined that the condensation condition is met.

6. The method according to claim 5, characterized in that Determine the dew point temperature range corresponding to the dew point temperature value by following the steps below: Determine the dew point temperature value as the upper limit value corresponding to the dew condensation temperature interval, and determine the preset freezing point temperature value as the lower limit value corresponding to the dew condensation temperature interval; Based on the upper limit value and the lower limit value, a condensation temperature interval corresponding to the dew point temperature value is determined.

7. The method according to claim 1, characterized in that The determining, based on the black ice icing index, whether there is black ice on the target road at the target time comprises: Determining whether the black ice freezing index is greater than or equal to a preset black ice freezing threshold; If the black ice icing index is less than the black ice icing threshold, determining that there is no black ice on the target road at the target time; If the black ice icing index is greater than or equal to the black ice icing threshold, it is determined that black ice exists on the target road at the target time.

8. A device for detecting black ice on a road, characterized in that: The detection device comprises: A data acquisition module is used to collect the road surface temperature value of the target road in the expressway and the air humidity value, wind speed value and vehicle flow value corresponding to the target road in real time; a condensation judgment module, configured to determine a dew point temperature value corresponding to the target road based on the road surface temperature value and the air humidity value, and to judge whether the road surface temperature value and duration of the target road at a current moment meet a condensation condition corresponding to the dew point temperature value; an icing judgment module, configured to determine the dew icing index of the target road at the current moment by using a preset dew icing index formula based on the dew point temperature value, the road surface temperature value and the duration if the condensation condition is met, and to judge whether the dew icing index is greater than or equal to a preset dew icing threshold value; A freezing point judgment module, used to judge whether the road surface temperature value of the target road at a target time after the current time is greater than or equal to a preset freezing point temperature value if it is greater than or equal to the dew freezing threshold; The black ice judgment module is used to determine the black ice icing index of the target road at the target time based on the freezing point temperature value, the road surface temperature value, the wind speed value and the vehicle flow value if it is greater than or equal to the freezing point temperature value, and determine whether there is black ice on the target road at the target time based on the black ice icing index.

9. An electronic device, characterized in that: include: A processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate through the bus, and the machine-readable instructions are executed by the processor to execute the steps of the method for detecting black ice on the road as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for detecting black ice on roads as claimed in any one of claims 1 to 7 are executed.

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