Frozen rain area determination method and device, equipment, storage medium and program product

Abstract

The invention relates to the technical field of data processing, and discloses a freezing rain area determination method and device, equipment, a storage medium and a program product. The method comprises the following steps: acquiring information data acquired by a plurality of vehicles; based on the multiple pieces of information data, vehicle environment information corresponding to the information data of each vehicle is determined; screening the vehicle environment information to obtain target vehicle environment information; detecting whether a current area where a target vehicle corresponding to the target vehicle environment information is located is a target area; wherein if the current area where the target vehicle is located is the target area, the target area is determined to be the freezing rain area. According to the invention, a plurality of vehicles are used as mobile detection nodes, so that the coverage range of freezing rain detection can be obviously expanded. Especially in remote, complex terrain or economically underdeveloped areas, as long as vehicles run in the areas, monitoring can be carried out through information data collected by the vehicles.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a method, device, computer equipment, storage medium and program product for determining a freezing rain area. Background Art

[0002] With the impact of global climate change, extreme weather phenomena are becoming more frequent, including ice and snow disasters such as freezing rain. Freezing rain can cause ice on the road surface, seriously affecting road traffic safety.

[0003] In order to ensure smooth traffic and public safety, freezing rain detection devices are installed on roads to monitor and warn of freezing rain in real time, which has become an important means of modern traffic safety management. At present, road freezing rain detection devices mainly rely on advanced sensors and data processing technologies. These devices usually integrate multiple sensors, such as temperature, humidity, air pressure, wind speed, wind direction and other meteorological sensors, which can accurately measure the temperature, humidity and ice and snow coverage of the road surface.

[0004] However, freezing rain detection devices cannot cover all road areas, especially in remote areas, complex terrain or economically underdeveloped areas. Due to cost and technical limitations, freezing rain conditions in these areas are often unable to be accurately monitored. As a result, vehicles and pedestrians may face higher safety risks in these areas that cannot be covered by freezing rain detection devices. Summary of the invention

[0005] In view of this, the present invention provides a method, device, computer equipment, storage medium and program product for determining freezing rain areas, so as to solve the problem that freezing rain detection devices cannot cover all road areas, especially in remote areas, complex terrain or economically underdeveloped areas, where freezing rain conditions cannot be accurately monitored due to cost and technical limitations. This results in the problem that vehicles and pedestrians may face higher safety risks in these areas that cannot be covered by freezing rain detection devices.

[0006] In a first aspect, the present invention provides a method for determining a freezing rain area, the method comprising: acquiring information data collected by multiple vehicles; based on the multiple information data, determining the vehicle environment information corresponding to the information data of each vehicle; screening and processing the vehicle environment information to obtain target vehicle environment information; detecting whether the current area where the target vehicle corresponding to the target vehicle environment information is located is in the target area; wherein, if the current area where the target vehicle is located is in the target area, determining that the target area is a freezing rain area.

[0007] The method for determining the freezing rain area provided in this embodiment can significantly expand the coverage of freezing rain detection by using multiple vehicles as mobile detection nodes. Especially in remote areas, complex terrain or economically underdeveloped areas, as long as there are vehicles traveling in these areas, they can be monitored through the information data collected by the vehicles, solving the problem that the freezing rain detection device cannot cover all road areas, especially in remote areas, complex terrain or economically underdeveloped areas.

[0008] In an optional embodiment, the information data includes: vehicle equipment data, vehicle temperature data and vehicle anti-lock braking data; based on the multiple information data, the vehicle environment information corresponding to the information data of each vehicle is determined separately, including: based on the vehicle equipment data, determining the rainfall information and fog information; based on the multiple vehicle temperature data, determining the temperature difference information between the temperature inside the vehicle and the atmospheric temperature outside the vehicle; based on the multiple vehicle anti-lock braking data, determining the tire information of the vehicle; using the rainfall information, fog information, temperature difference information and the tire information of the vehicle as the vehicle environment information.

[0009] The method for determining the freezing rain area provided in this embodiment can obtain rainfall information and fog group information in real time by analyzing vehicle equipment data, such as data from a rain sensor and a fog group detection device, so that the driver can take timely countermeasures to avoid traffic accidents caused by bad weather. In addition, based on the vehicle anti-lock data, the state of the tire can be judged to prevent safety hazards caused by tire problems. Moreover, by analyzing the temperature data inside and outside the vehicle and calculating the temperature difference information, the driver can be provided with comfortable driving environment suggestions, such as whether to turn on the air conditioner, adjust the temperature inside the car, etc. Accurate tire information can help the driver understand the tire status, thereby reasonably arranging the replacement and maintenance of the tire and improving driving stability and comfort.

[0010] In an optional embodiment, the vehicle environmental information is screened and processed to obtain target vehicle environmental information, including: detecting whether the rainfall information is less than the preset rainfall information; detecting whether the fog group information is less than the preset fog group information; detecting whether the temperature difference is lower than the preset temperature; detecting whether the state of the vehicle's tires is in a side-slip state; taking the rainfall information not less than the preset rainfall information, the fog group information not less than the preset fog group information, the temperature difference information lower than the preset temperature information and the vehicle's tire information being in a side-slip state as the target vehicle environmental information.

[0011] The method for determining the freezing rain area provided in this embodiment can screen out the most relevant and accurate information for the current driving environment by setting preset conditions (preset rainfall information, preset fog information, preset temperature), reduce the interference of irrelevant information, and enable the driver or vehicle management system to focus more on processing key environmental factors, thereby improving the accuracy of the target vehicle environmental information.

[0012] In an optional embodiment, rainfall information and fog group information are determined based on vehicle equipment data, including: calculating rainfall information based on the vehicle's wiper status data; calculating fog group information based on the vehicle's fog lamp data and double flash lamp data.

[0013] The method for determining the freezing rain area provided in this embodiment can reflect the current rainfall intensity in real time by analyzing the wiper status data of the vehicle. There is a certain correlation between the wiper swing frequency and the rainfall. Therefore, the rainfall information can be calculated more accurately using this data, avoiding the delay or error that may exist in traditional rainfall measurement methods (such as rain gauges), and improving the real-time and accuracy of the data.

[0014] In an optional embodiment, the method also includes: generating a first map layer corresponding to the target vehicle environment information based on the target vehicle environment information; determining the vehicle environment information corresponding to the adjacent area of ​​the current area where the target vehicle is located corresponding to the target vehicle environment information based on the first map layer; wherein the adjacent area is an area where the target vehicle environment information has not been determined; generating a second map layer of the vehicle environment information corresponding to the adjacent area based on the vehicle environment information corresponding to the adjacent area; generating the target map layer based on the first map layer and the second map layer.

[0015] The method for determining the freezing rain area provided in this embodiment can obtain rainfall information and fog information in real time by analyzing the vehicle's wiper status, fog lights, and hazard lights, thereby generating a first map layer that accurately reflects the environment the vehicle is currently in. Based on the first map layer, the vehicle environment information of the adjacent area is further predicted and inferred, and a second map layer is generated, ensuring the timeliness and accuracy of the information.

[0016] In addition, through the combination of the first map layer and the second map layer, not only the area where the target vehicle is currently located is covered, but also the adjacent area where the target vehicle environment information is not determined, achieving comprehensive information coverage. In addition, the vehicle environment information of the adjacent area is obtained by inference and displayed in the second map layer, so that the entire target map layer has spatial continuity, allowing the driver or vehicle management system to better understand the overall situation of the vehicle's environment.

[0017] In an optional implementation, the target map layer is sent to a user terminal.

[0018] The method for determining the freezing rain area provided in this embodiment sends the target map layer to the user terminal, so that the user can understand the weather conditions of the corresponding area through the user terminal and make corresponding adjustments to the weather conditions.

[0019] In a second aspect, the present invention provides a device for determining a freezing rain area, the device comprising: an acquisition module for acquiring information data collected by multiple vehicles; a first determination module for determining, based on the multiple information data, vehicle environmental information corresponding to the information data of each vehicle; a screening module for screening the vehicle environmental information to obtain target vehicle environmental information; a second determination module for detecting whether the current area where the target vehicle corresponding to the target vehicle environmental information is located is in the target area; wherein, if the current area where the target vehicle is located is in the target area, the target area is determined to be a freezing rain area.

[0020] In a third aspect, the present invention provides a computer device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the method for determining a freezing rain area according to the first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0021] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the method for determining a freezing rain area according to the first aspect or any corresponding embodiment thereof.

[0022] In a fifth aspect, the present invention provides a computer program product, comprising computer instructions for causing a computer to execute the method for determining a freezing rain area according to the first aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0024] Figure 1 is a flow chart of a method for determining a freezing rain area according to an embodiment of the present invention;

[0025] Figure 2 is a flow chart of another method for determining a freezing rain area according to an embodiment of the present invention;

[0026] Figure 3 is a flow chart of another method for determining a freezing rain area according to an embodiment of the present invention;

[0027] Figure 4 is a structural block diagram of a device for determining a freezing rain area according to an embodiment of the present invention;

[0028] Figure 5 It is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0029] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are 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 those skilled in the art without creative work are within the scope of protection of the present invention.

[0030] Based on relevant technologies, in order to ensure smooth roads and public safety, setting up freezing rain detection devices on roads to monitor and warn of freezing rain in real time has become an important means of modern traffic safety management. At present, road freezing rain detection devices mainly rely on advanced sensors and data processing technologies. These devices usually integrate multiple sensors, such as temperature, humidity, air pressure, wind speed, wind direction and other meteorological sensors, which can accurately measure the temperature, humidity and ice and snow coverage of the road surface.

[0031] However, freezing rain detection devices cannot cover all road areas, especially in remote areas, complex terrain or economically underdeveloped areas. Due to cost and technical limitations, freezing rain conditions in these areas are often unable to be accurately monitored. As a result, vehicles and pedestrians may face higher safety risks in these areas that cannot be covered by freezing rain detection devices.

[0032] Based on this, the present invention provides a method for determining freezing rain areas, which can significantly expand the coverage of freezing rain detection by using multiple vehicles as mobile detection nodes. Especially in remote, complex terrain or economically underdeveloped areas, as long as there are vehicles traveling in these areas, they can be monitored through information data collected by the vehicles, solving the problem that freezing rain detection devices cannot cover all road areas, especially in remote, complex terrain or economically underdeveloped areas.

[0033] According to an embodiment of the present invention, an embodiment of a method for determining a freezing rain area is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0034] In this embodiment, a method for determining a freezing rain area is provided, which can be used in computer equipment, such as a computer, a server, etc. Figure 1 FIG. 4 is a flow chart of a method for determining a freezing rain area according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps:

[0035] Step S101, obtaining information data collected by multiple vehicles.

[0036] The information data can be the original data collected by the vehicle through various sensors, such as radar echoes, image data, temperature data, etc., specifically, it can be vehicle equipment data, vehicle temperature data, vehicle anti-lock braking data, etc., which are not specifically limited here. Specifically, the data can be transmitted to the data center through the vehicle's built-in communication system (such as 4G / 5G, Wi-Fi, Bluetooth, etc.). The data center downloads data from the vehicle regularly and can also obtain information data through other means, which are not specifically limited here and can be implemented by technicians in this field. For example: an autonomous driving car collects road slipperiness, visibility and temperature information through its installed lidar, camera and meteorological sensors, and transmits this information to the cloud data center.

[0037] Step S102: based on the plurality of information data, respectively determine the vehicle environment information corresponding to the information data of each vehicle.

[0038] Vehicle environmental information can be information that reflects the environmental status of the vehicle, such as road wetness, visibility, rainfall, etc., which is analyzed based on the original information data and is not specifically limited here. Specifically, machine learning algorithms can be used to classify and identify information data. Useful information can also be extracted from information data based on preset rules and thresholds. For example: through the analysis of radar echoes and image data, the system recognizes that there is water on the road and visibility is low. At the same time, according to the data from the meteorological sensor, it is known that the current temperature is below 0°C and the rainfall is too heavy. The preliminary judgment is that it may be freezing rain weather.

[0039] Step S103, filtering the vehicle environment information to obtain target vehicle environment information.

[0040] The target vehicle environment information can represent the vehicle environment information that is directly related to the target analysis (such as freezing rain area detection) after screening. Specifically, information that is not within the target range can be filtered out based on the geographic location. Information within a specific time period can also be filtered out based on the timestamp. The information can also be sorted and filtered according to its importance or confidence. For example: filter out vehicle environment information with rainfall information not less than the preset rainfall information, fog group information not less than the preset fog group information, temperature difference information lower than the preset temperature information, and vehicle tire information in the state of side slip, thereby indicating that freezing rain has occurred in this area.

[0041] Step S104, detecting whether the current area where the target vehicle corresponding to the target vehicle environment information is located is in the target area; wherein, if the current area where the target vehicle is located is in the target area, determining that the target area is a freezing rain area.

[0042] The target area may represent a specific geographical area that needs to be monitored and analyzed. The freezing rain area may refer to an area where freezing rain occurs, usually accompanied by low temperatures and continuous rainfall, resulting in ice on the road surface. Specifically, a machine learning model may be used to comprehensively consider a variety of factors for prediction and judgment. Predictions may also be made in other ways, which are not specifically limited here and may be implemented by those skilled in the art.

[0043] In one possible implementation, the AI ​​weather forecast model is used to predict freezing rain areas. Specifically, by training a large amount of Internet of Vehicles data, a high-precision forecast of future weather is achieved. The Internet of Vehicles data and weather forecast data results are used to learn weather forecasts. The vehicle speed and characteristics are identified, and the freezing rain impact and area are analyzed.

[0044] The freezing rain area is predicted through the time series prediction model. Specifically, based on the changing trend of historical Internet of Vehicles data, the exponential smoothing method is used to predict future weather conditions. Among them, the exponential smoothing method can characterize that the exponential smoothing value of any period is the weighted average of the actual observation value of the current period and the exponential smoothing value of the previous period. The weights decrease in geometric series, the first term of this series is the smoothing constant a, and the common ratio is (1-a).

[0045] Depending on the number of smoothing times, exponential smoothing can be divided into single exponential smoothing, double exponential smoothing, and triple exponential smoothing.

[0046] Single exponential smoothing method: Applicable to the situation where there is no obvious trend change in the time series. The prediction formula is: yt+1'=ayt+(1-a)yt', where yt+1' is the predicted value of period t+1, yt is the actual value of period t, and yt' is the predicted value of period t. Among them, the value range of the smoothing constant a is between 0 and 1. The value of a determines the smoothing level and the response speed to the difference between the predicted value and the actual result. For the freezing rain image area, the smoothing constant a is the average speed of the vehicle on the day / the average speed of the vehicle.

[0047] Freezing rain areas can be predicted through freezing rain recognition technology. Specifically, for different weather phenomena such as freezing rain, the model needs to select distinguishing features for extraction. For example, for fog recognition, features such as humidity, visibility, and fog lights are used; for rain recognition, features such as rain speed and humidity are used. The model is trained and optimized using the collected data and features. By adjusting the parameters and structure of the model, it can accurately identify the areas affected by freezing rain and other weather phenomena and the areas where events are eliminated.

[0048] The AI ​​freezing rain impact identification model can be used to predict freezing rain areas. Among them, the AI ​​freezing rain impact identification model uses deep learning and machine learning algorithms to process complex meteorological data, optimize experimental design, and improve the accuracy and efficiency of meteorological forecasts. Using advanced AI algorithms, the convolutional neural network (CNN) in deep learning efficiently processes and analyzes meteorological data to achieve accurate predictions of the time, location, and intensity of freezing rain. Integrate information from multiple data sources such as satellite remote sensing, ground observations, and radar detection, and use multi-source data fusion technology to improve the accuracy and reliability of freezing rain identification.

[0049] In one possible implementation, by monitoring changes in meteorological conditions in real time, the prediction model is adjusted in a timely manner to ensure the timeliness and accuracy of the prediction results.

[0050] In one possible implementation, by continuously collecting new meteorological data and feedback information, the model is continuously optimized and iterated to improve the adaptability and prediction performance of the model.

[0051] In one possible implementation, select reliable Internet of Vehicles data sources, which are provided by the Internet of Vehicles of various automobile companies. Obtain the latest Internet of Vehicles data from the data source in real time through the API interface. Remove duplicate, erroneous or abnormal data to ensure the accuracy and consistency of the data. Use the prediction model to parse the received raw data into the format required for map display: location, temperature, humidity, precipitation type, fog type, etc. Send requests to the data source regularly to obtain the latest Internet of Vehicles data. For example, poll once a minute, and the specific frequency depends on the update frequency of the data source and user needs. If the data source supports the push function, a push mechanism can be established to receive new data pushed by the data source in real time. This method reduces the delay of polling and realizes true real-time updates.

[0052] The method for determining the freezing rain area provided in this embodiment can significantly expand the coverage of freezing rain detection by using multiple vehicles as mobile detection nodes. Especially in remote areas, complex terrain or economically underdeveloped areas, as long as there are vehicles traveling in these areas, they can be monitored through the information data collected by the vehicles, solving the problem that the freezing rain detection device cannot cover all road areas, especially in remote areas, complex terrain or economically underdeveloped areas.

[0053] Combination Figure 2 As shown, in an optional implementation, the information data includes: vehicle equipment data, vehicle temperature data and vehicle anti-lock braking data; wherein the above step S102 includes:

[0054] Step S1021, determining rainfall information and fog group information based on vehicle equipment data.

[0055] The rainfall information may be the depth of rain that falls to the ground within a certain period of time, usually in millimeters. The fog group information may be fog groups that appear in local areas, which usually have low visibility and pose a threat to driving safety. Specifically, it is possible to determine whether the vehicle's wipers are turned on to determine whether rainfall and fog groups occur, and then directly read the reading of the rain sensor to obtain the rainfall information. It is also possible to determine whether there is a fog group phenomenon by analyzing the data of the visibility sensor, combined with parameters such as humidity and temperature, etc., which is not specifically limited here and can be implemented by those skilled in the art.

[0056] Specifically, the above step S1021 includes:

[0057] Step a1, calculating rainfall information according to the wiper status data of the vehicle.

[0058] Through a large amount of experimental data, a mapping relationship between wiper status data and rainfall is established. The mapping relationship can be linear or nonlinear, depending on the analysis results of the experimental data. The wiper status data can also be trained using a machine learning algorithm to obtain a model that can predict rainfall. This method can automatically learn complex relationships in the data and improve the accuracy of the prediction. The wiper status data can also be statistically analyzed to obtain the rainfall distribution corresponding to different wiper states. Then, according to the current wiper state, a suitable rainfall value is selected from the distribution as the prediction result, etc., which is not specifically limited here and can be implemented by technical personnel in this field. For example: The wiper of a vehicle continued to work at a medium speed for 10 minutes in a certain period of time. According to the established mapping relationship or machine learning model, it can be estimated that the rainfall during this period is approximately 20 mm.

[0059] Step a2, calculating the fog group information based on the vehicle's fog lamp data and double flash lamp data.

[0060] Set the threshold time and frequency for turning on the fog lights and hazard lights. When these data exceed the set threshold, it can be judged that there is a fog cluster phenomenon. By analyzing a large amount of historical data, a pattern relationship between the fog lights and hazard lights data and the fog cluster phenomenon is established. Then, this pattern relationship is used to judge the current data. The fog lights and hazard lights data are combined with the vehicle's speed, acceleration, direction and other data to make a comprehensive judgment. This method can improve the accuracy and reliability of the judgment, etc., and is not specifically limited here, and can be implemented by technical personnel in this field. For example: a vehicle suddenly turns on the fog lights and hazard lights within a certain period of time, and the duration exceeds 5 minutes. According to the set threshold judgment or pattern recognition method, it can be judged that there may be a fog cluster phenomenon in the area. At the same time, if it is found that the vehicle is decelerating in combination with the vehicle's speed data, the existence of fog cluster is further confirmed.

[0061] In one possible implementation, the number and time interval of raindrops are sensed by an infrared rain gauge (optical rain sensor), and the data is input into an efficient data processing algorithm for classification. For example, light rain (less than 10 mm / h), moderate rain (10-50 mm / h), and heavy rain (greater than 50 mm / h) can be distinguished. For different scenarios, the specific calculation method is as follows:

[0062] In light rainfall scenarios, due to the large number and density of raindrops, the algorithm needs to increase the sampling frequency and perform data filtering to remove abnormal data and noise to ensure that the wipers operate at an appropriate frequency.

[0063] In moderate rainfall scenarios, the raindrops are of uniform size, and the algorithm can perform normalization to eliminate the impact of size differences on data processing, allowing the wipers to adapt to raindrops of different sizes.

[0064] In heavy rain scenarios, raindrops are large and the time interval between raindrops is long. The algorithm needs to perform data calibration and correction processing to eliminate the impact of different raindrop sizes on data processing and adjust the working speed and mode of the wiper. The efficient data processing algorithm processes rainfall data in real time and immediately adjusts the working status of the wiper to ensure the driver's clear field of vision and improve driving safety.

[0065] Step S1022: determining temperature difference information between the temperature inside the vehicle and the atmospheric temperature outside the vehicle based on a plurality of vehicle temperature data.

[0066] The temperature difference information may represent the temperature difference between the temperature inside the vehicle and the atmospheric temperature outside the vehicle. For example, if the temperature sensor inside the vehicle shows a temperature of 20 degrees Celsius, while the temperature sensor outside the vehicle shows a temperature of 0 degrees Celsius, the calculated temperature difference is 20 degrees Celsius.

[0067] Step S1023, determining the tire information of the vehicle based on multiple vehicle anti-lock braking data.

[0068] Tire information may include parameters such as tire speed, slip rate, and grip. Specifically, the tire speed and slip rate changes can be analyzed by reading the data of the Anti-lock Braking System (ABS). Combined with the acceleration data of the vehicle, it is determined whether the tire grip is sufficient. For example, if the ABS system detects that the slip rate of a certain tire suddenly increases and the acceleration of the vehicle decreases, it is determined that the tire may be slipping.

[0069] Step S1024, taking rainfall information, fog information, temperature difference information and vehicle tire information as vehicle environment information.

[0070] The rainfall information, fog information, temperature difference information and tire information obtained in the previous three sub-steps are combined to form a complete vehicle environment information. This information is crucial for subsequent screening and freezing rain area detection. For example: rainfall information (10 mm), fog information (existence), temperature difference information (20 degrees Celsius), tire information (a certain tire is slipping), etc. are integrated into a vehicle environment information report.

[0071] The method for determining the freezing rain area provided in this embodiment can obtain rainfall information and fog group information in real time by analyzing vehicle equipment data, such as data from a rain sensor and a fog group detection device, so that the driver can take timely countermeasures to avoid traffic accidents caused by bad weather. In addition, based on the vehicle anti-lock data, the state of the tire can be judged to prevent safety hazards caused by tire problems. Moreover, by analyzing the temperature data inside and outside the vehicle and calculating the temperature difference information, the driver can be provided with comfortable driving environment suggestions, such as whether to turn on the air conditioner, adjust the temperature inside the car, etc. Accurate tire information can help the driver understand the tire status, thereby reasonably arranging the replacement and maintenance of the tire and improving driving stability and comfort.

[0072] In addition, by analyzing the vehicle's windshield wiper status data, the current rainfall intensity can be reflected in real time. There is a certain correlation between the wiper's swing frequency and the rainfall. Therefore, using this data, the rainfall information can be calculated more accurately, avoiding the delay or error that may exist in traditional rainfall measurement methods (such as rain gauges), and improving the real-time and accuracy of the data.

[0073] In an optional implementation, the above step S103 includes:

[0074] Step a1, detecting whether the rainfall information is less than the preset rainfall information.

[0075] The preset rainfall information can represent the rainfall threshold value set according to safety standards or experience, and is used to determine whether freezing rain occurs. Specifically, the current rainfall information can be numerically compared with the preset rainfall information. If the rainfall information is fuzzy (such as "light rain", "moderate rain", etc.), it can also be judged by defining the boundaries of these fuzzy concepts. For example: the current rainfall information is 10 mm / hour, and the preset rainfall information is 20 mm / hour, so it is judged that the current rainfall is less than the preset rainfall.

[0076] Step a2, detecting whether the fog group information is smaller than the preset fog group information.

[0077] If the current visibility is lower than the preset visibility threshold, it is judged that the fog situation is serious. It is also possible to detect the fog concentration and compare it with the preset threshold, etc., which is not specifically limited here and can be implemented by those skilled in the art. For example: the current visibility is 50 meters, and the preset visibility threshold is 100 meters, so it is judged that the current fog situation is serious.

[0078] Step a3, detecting whether the temperature difference is lower than a preset temperature.

[0079] The preset temperature may be a temperature difference threshold value set according to safety standards or experience. Specifically, the current temperature difference value is numerically compared with the preset temperature difference value. Other environmental factors, such as humidity, wind speed, etc., may also be considered in the comparison to more accurately determine whether the window is prone to fogging. For example, if the current temperature difference value is 15 degrees Celsius and the preset temperature difference threshold value is 10 degrees Celsius, it is determined that the current temperature difference value is large and may cause the window to fog.

[0080] Step a4, detecting whether the tires of the vehicle are in a side slip state.

[0081] The side slip state can be characterized as the side slip phenomenon of the tire during driving due to reasons such as slippery road surface and tire wear. Specifically, the wheel speed sensor can be used to detect the rotation speed and steering angle of the tire to determine whether the side slip occurs. The vehicle's anti-lock braking system (ABS) data can also be used to determine whether the tire is in a side slip state.

[0082] Step a5, taking the rainfall information not less than the preset rainfall information, the fog group information not less than the preset fog group information, the temperature difference information lower than the preset temperature information and the information that the vehicle's tires are in side slip as the target vehicle environment information.

[0083] The bad weather and vehicle status information detected in the previous four steps are integrated to form the target vehicle environment information. This information is of great significance for subsequent driving safety warnings and decisions.

[0084] The method for determining the freezing rain area provided in this embodiment can screen out the most relevant and accurate information for the current driving environment by setting preset conditions (preset rainfall information, preset fog information, preset temperature), reduce the interference of irrelevant information, and enable the driver or vehicle management system to focus more on processing key environmental factors, thereby improving the accuracy of the target vehicle environmental information.

[0085] In an optional embodiment, the above method further includes:

[0086] Step c1: generating a first map layer corresponding to the target vehicle environment information based on the target vehicle environment information.

[0087] The target vehicle's environmental information (such as rainfall, fog, temperature difference, tire side slip status, etc.) is presented in a visual form on the map to form a first map layer, thereby highlighting the current environmental conditions of the target vehicle. Specifically, different colors or icons are used to represent different environmental information. For example, red indicates heavy rainfall, yellow indicates severe fog, blue indicates large temperature difference, and green indicates normal. For example: the target vehicle is currently in an environment with heavy rainfall and severe fog, then on the first map layer, the area where the target vehicle is located will be marked in red and yellow.

[0088] In one possible implementation, the target vehicle environment information is obtained, which may specifically include real-time or recent rainfall, fog conditions, temperature differences, and specific vehicle conditions (such as tire side slip conditions). The accuracy and timeliness of this information is ensured so that the current environmental conditions can be accurately reflected on the map.

[0089] Select a suitable map as the bottom layer, which can be an electronic map, satellite map or other type of map. Make sure that the resolution and accuracy of the map meet the needs of displaying the target vehicle's environmental information. Design the corresponding layer elements according to the type of target vehicle environmental information. For example, different colors, icons or textures can be used to represent different environmental information. Design the style and layout of the layer elements to ensure that they are clearly identifiable and easy to understand on the map. Map the target vehicle environmental information to the corresponding location on the map. This usually involves converting the environmental information into coordinate points or areas on the map. For continuous environmental information (such as rainfall), it may be necessary to use gradient colors or contour lines to represent its distribution and intensity. Use a map rendering engine or graphics library to render the designed layer elements onto the map.

[0090] For example, the target vehicle is currently in an environment with heavy rainfall and severe fog, and the tires of the vehicle are in a side-slip state. In order to generate the corresponding first map layer, the following steps can be taken:

[0091] Use a high-resolution electronic map as the bottom layer. Use red to indicate areas with heavy rainfall, yellow to indicate areas with severe fog, and green to indicate normal areas; use flashing icons to indicate that the vehicle's tires are in a side-slip state. Map the information on rainfall, fog, and vehicle side-slip status to the corresponding positions on the map. Use a map rendering engine to render the designed layer elements onto the map to form a clearly identifiable first map layer.

[0092] Step c2, based on the first map layer, determining the vehicle environment information corresponding to the adjacent area of ​​the current area where the target vehicle is located corresponding to the target vehicle environment information; wherein the adjacent area is an area where the target vehicle environment information has not been determined.

[0093] Based on the environmental information of the area where the target vehicle is located on the first map layer, possible vehicle environmental information in its adjacent area (ie, the area where the target vehicle environmental information is not determined) is inferred.

[0094] First, according to the first map layer, the area where the target vehicle is currently located is identified. This area is where the vehicle environment information has been determined, such as rainfall, fog, temperature, etc. Next, identify areas adjacent to the target area but where the vehicle environment information has not yet been determined. These adjacent areas may be geographical areas bordering the target area, or areas defined based on some spatial relationship (such as distance, direction, etc.). Analyze the possible correlation between the environmental information of the target area and the adjacent areas. For example, if the target area has a large rainfall, then the adjacent areas may also have similar rainfall trends. Based on the above correlation analysis, infer the possible vehicle environment information of the adjacent areas. For example: The first map layer shows that the target vehicle is currently in an area with a large rainfall. Based on this information, it can be inferred that the adjacent areas may also have a high rainfall. To verify this inference, historical meteorological data can be consulted, or real-time sensor data from adjacent areas can be viewed. The inferred rainfall information can be applied to subsequent driving decisions, such as choosing a safer driving path or adjusting the vehicle speed.

[0095] Step c3: generating a second map layer of vehicle environment information corresponding to the adjacent areas based on the vehicle environment information corresponding to the adjacent areas.

[0096] Collect and integrate vehicle environment information about adjacent areas. Design the style and elements of the second map layer based on the type and characteristics of the vehicle environment information in the adjacent areas. For example, different colors, icons, or textures can be used to represent different environmental information (such as rainfall, temperature, wind speed, etc.). Map the integrated vehicle environment information in adjacent areas to the corresponding locations on the map. Use a map rendering engine or graphics library to render the designed layer elements onto the map to form the second map layer.

[0097] Step c4: generating a target map layer based on the first map layer and the second map layer.

[0098] The first map layer and the second map layer may be superimposed using map rendering software or geographic information system (GIS) tools. The two layers may also be distinguished using different display methods: for example, using different colors or icons to represent the information of the current area and the adjacent area of ​​the target vehicle, or using borders, shadows and other effects to distinguish them, etc., which are not specifically limited here and can be implemented by those skilled in the art.

[0099] The method for determining the freezing rain area provided in this embodiment can obtain rainfall information and fog information in real time by analyzing the vehicle's wiper status, fog lights, and hazard lights, thereby generating a first map layer that accurately reflects the environment the vehicle is currently in. Based on the first map layer, the vehicle environment information of the adjacent area is further predicted and inferred, and a second map layer is generated, ensuring the timeliness and accuracy of the information.

[0100] In addition, through the combination of the first map layer and the second map layer, not only the area where the target vehicle is currently located is covered, but also the adjacent area where the target vehicle environment information is not determined, achieving comprehensive information coverage. In addition, the vehicle environment information of the adjacent area is obtained by inference and displayed in the second map layer, so that the entire target map layer has spatial continuity, allowing the driver or vehicle management system to better understand the overall situation of the vehicle's environment.

[0101] In an optional implementation, the above method further includes: sending the target map layer to a user terminal.

[0102] The user terminal can represent a device that receives and displays the target map layer, such as a smart phone, a tablet computer, a car navigation system, etc. Specifically, a transmission connection is established with the user terminal using a network communication protocol (such as HTTP, HTTPS, WebSocket, etc.). The user identity is verified (such as using a user name and password, a token, etc.) to ensure the security of the transmission. The target map layer is sent to the user terminal through the established transmission connection.

[0103] The method for determining the freezing rain area provided in this embodiment sends the target map layer to the user terminal, so that the user can understand the weather conditions of the corresponding area through the user terminal and make corresponding adjustments to the weather conditions.

[0104] In one possible embodiment, combining Figure 3 As shown, the above method also includes:

[0105] Enter the scheduled task. The scheduled task can represent the task of starting the freezing rain area detection.

[0106] Determine whether the vehicle is powered on. For example, in area A, there are 30,000 vehicles, and 10,000 of the 30,000 vehicles are powered on.

[0107] When the vehicle is in event trigger mode, it detects whether there is rain, snow or fog in the area, whether the air temperature and humidity are too low, and identifies whether there is a dangerous area.

[0108] Report the results of rain, snow, fog events, low air temperature and humidity, and identification of dangerous areas.

[0109] Regularly detect whether powered-on vehicles are gathered in the same time and space;

[0110] If powered-on vehicles gather in the same time and space, a map layer including a weather layer, a temperature and humidity layer, and a danger zone layer is generated.

[0111] Publish the information corresponding to the map layers to various map vendors.

[0112] The method for determining the freezing rain area provided in this embodiment can significantly expand the coverage of freezing rain detection by using multiple vehicles as mobile detection nodes. Especially in remote areas, complex terrain or economically underdeveloped areas, as long as there are vehicles traveling in these areas, they can be monitored through the information data collected by the vehicles, solving the problem that the freezing rain detection device cannot cover all road areas, especially in remote areas, complex terrain or economically underdeveloped areas.

[0113] In the present embodiment, a device for determining a freezing rain area is also provided, and the device is used to implement the above-mentioned embodiments and preferred embodiments, and the descriptions that have been made will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware of a predetermined function. Although the device described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware is also possible and conceived.

[0114] This embodiment provides a device for determining a freezing rain area. Figure 4 As shown, it includes: an acquisition module 401, used to acquire information data collected by multiple vehicles; a first determination module 402, used to determine the vehicle environment information corresponding to the information data of each vehicle based on the multiple information data; a screening module 403, used to screen the vehicle environment information to obtain the target vehicle environment information; a second determination module 404, used to detect whether the current area where the target vehicle corresponding to the target vehicle environment information is located is in the target area; wherein, if the current area where the target vehicle is located is in the target area, the target area is determined to be a freezing rain area.

[0115] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0116] The device for determining the freezing rain area in this embodiment is presented in the form of a functional unit, where the functional unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0117] The embodiment of the present invention also provides a computer device having the above Figure 4The device for determining the freezing rain area is shown.

[0118] See also Figure 5 , Figure 5 is a schematic diagram of the structure of a computer device provided by an optional embodiment of the present invention, such as Figure 5 As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in or on the memory to display the graphical information of the GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 5 A processor 10 is taken as an example.

[0119] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0120] The memory 20 stores instructions executable by at least one processor 10, so that at least one processor 10 executes the method shown in the above embodiment.

[0121] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0122] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0123] The computer device further comprises a communication interface 30 for the computer device to communicate with other devices or a communication network.

[0124] The embodiment of the present invention also provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0125] A part of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the existence of the computer program instruction in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc., and accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium accessible to the computer.

[0126] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A method for determining a freezing rain area, characterized in that: The method comprises: Obtain information data collected by multiple vehicles; Based on the plurality of information data, respectively determine the vehicle environment information corresponding to the information data of each vehicle; Screening and processing the vehicle environment information to obtain target vehicle environment information; Detect whether the current area where the target vehicle is located corresponding to the target vehicle environment information is in the target area; wherein, if the current area where the target vehicle is located is in the target area, determine that the target area is a freezing rain area.

2. The method for determining a freezing rain area according to claim 1, characterized in that: The information data includes: vehicle equipment data, vehicle temperature data and vehicle anti-lock braking data; based on the plurality of information data, the vehicle environment information corresponding to each of the vehicle information data is determined to include: Based on the vehicle equipment data, determining rainfall information and fog group information; Based on the plurality of vehicle temperature data, determining temperature difference information between the temperature inside the vehicle and the atmospheric temperature outside the vehicle; Determining information of tires of the vehicle based on the plurality of vehicle anti-lock braking data; The rainfall information, fog information, temperature difference information and vehicle tire information are used as vehicle environment information.

3. The method for determining a freezing rain area according to claim 2, characterized in that: The vehicle environment information is filtered and processed to obtain target vehicle environment information, including: Detecting whether the rainfall information is less than preset rainfall information; Detecting whether the fog group information is smaller than the preset fog group information; Detecting whether the temperature difference is lower than a preset temperature; Detecting whether the tire of the vehicle is in a side slip state; The target vehicle environment information is that the rainfall information is not less than the preset rainfall information, the fog group information is not less than the preset fog group information, the temperature difference information is lower than the preset temperature information, and the vehicle tire information is in side slip.

4. The method for determining a freezing rain area according to claim 2, characterized in that: Based on the vehicle equipment data, determining rainfall information and fog group information includes: Calculate rainfall information based on the vehicle's windshield wiper status data; The fog group information is calculated based on the vehicle's fog lamp data and double flash lamp data.

5. The method for determining a freezing rain area according to claim 3, characterized in that: The method further comprises: Based on the target vehicle environment information, generating a first map layer corresponding to the target vehicle environment information; Determine, based on the first map layer, vehicle environment information corresponding to an adjacent area of ​​a current area where the target vehicle is located corresponding to the target vehicle environment information; wherein the adjacent area is an area where the target vehicle environment information has not been determined; Based on the vehicle environment information corresponding to the adjacent area, generating a second map layer of vehicle environment information corresponding to the adjacent area; A target map layer is generated based on the first map layer and the second map layer.

6. The method for determining a freezing rain area according to claim 5, characterized in that: The target map layer is sent to the user terminal.

7. A device for determining a freezing rain area, characterized in that: The device comprises: An acquisition module, used to acquire information data collected by multiple vehicles; A first determination module, configured to determine the vehicle environment information corresponding to each of the information data of the vehicle based on the plurality of information data; A screening module, used for screening the vehicle environment information to obtain target vehicle environment information; The second determination module is used to detect whether the current area where the target vehicle is located corresponding to the target vehicle environmental information is in the target area; wherein, if the current area where the target vehicle is located is in the target area, the target area is determined to be a freezing rain area.

8. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method for determining a freezing rain area according to any one of claims 1 to 6 by executing the computer instructions.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method for determining a freezing rain area according to any one of claims 1 to 6.

10. A computer program product, characterized in that The method comprises computer instructions for causing a computer to execute the method for determining a freezing rain area according to any one of claims 1 to 6.

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