Intelligent snow-melting anti-skid system, method and equipment for expressway and medium

Abstract

The invention provides an intelligent snow-melting anti-skid system, method and equipment for an expressway and a medium, and belongs to the technical field of road traffic safety guarantee. The system comprises a road condition monitoring module which is used for obtaining road data of an expressway in real time; the meteorological data acquisition module is used for acquiring meteorological data of an area where the expressway is located in real time; the intelligent snow-melting anti-skid equipment module is arranged on a preset road section of the expressway and is used for performing snow-melting agent spraying treatment, snow removal treatment and pavement heating treatment on the expressway according to a control instruction of the data processing and control center; the data processing and control center is used for receiving the road data and the meteorological data, predicting the snowfall confidence coefficient of a related road section through a snowfall confidence coefficient model according to the meteorological data, generating an operation scheme by integrating a prediction result and the road data, generating a control instruction according to the operation scheme, and sending the control instruction to the intelligent snow melting anti-skid equipment module; and the spraying amount of the snow-melting agent, snow removal parameters and pavement heating power are dynamically adjusted.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of road traffic safety guarantee, and more particularly to a highway intelligent snow melting and anti-skid system, method, device and medium. BACKGROUND

[0002] In winter, heavy snow and ice on highways pose a serious threat to traffic safety, and traffic accidents caused by vehicle skidding and loss of control occur frequently, greatly affecting road traffic efficiency and the safety of people's lives and property. Currently, traditional snow melting and anti-skid measures mainly use manual salt spreading and mechanical snow removal. Manual salt spreading relies on manual operation, which is extremely inefficient. In the face of large areas of snow-covered road sections, it is difficult to complete the work in a short time and cannot guarantee road safety in a timely manner. Moreover, it is difficult to accurately control the amount of salt, and excessive salt not only wastes resources, but also corrodes the road structure, shortens the service life of the road, pollutes the surrounding soil and water, and damages the ecological environment. Mechanical snow removal improves work efficiency to some extent, but also has significant limitations. The equipment has a limited operating range and cannot effectively remove snow in complex road sections such as bridges, tunnel entrances, and sharp curves. Moreover, mechanical snow removal is severely restricted by adverse weather conditions. In extreme weather such as heavy snow and strong winds, the equipment has difficulty operating and cannot remove snow in a timely manner, leaving the road in a dangerous state for a long time. In addition, existing snow melting and anti-skid systems generally lack accurate monitoring capabilities for real-time road conditions. They cannot obtain key parameters such as road temperature, humidity, snow thickness, ice thickness, and friction coefficient in real time, and it is also difficult to accurately predict and warn about snow and ice conditions in combination with weather forecast information. During the operation process, these systems do not have intelligent control functions and cannot automatically optimize snow melting and anti-skid operation plans based on actual snow conditions, road conditions, traffic flow, and other factors. This often results in overuse of resources or substandard operation results, causing waste of manpower, material resources, and financial resources, and the system cannot provide efficient and reliable safety guarantees for highways. SUMMARY

[0003] To solve the above problems, the present application provides a highway intelligent snow melting and anti-skid system, method, device and medium, which realizes real-time collection and processing of road and weather data through multi-module cooperation, dynamically generates operation plans using intelligent models, and accurately controls snow melting and anti-skid equipment, thereby achieving active prevention and efficient disposal of highway ice and snow disasters, ensuring traffic safety and improving resource utilization efficiency.

[0004] To achieve the above-mentioned purpose, the present application realizes the following technical solutions: In a first aspect, the present application provides a highway intelligent snow melting and anti-skid system, comprising: The road condition monitoring module, the weather data acquisition module, the intelligent snow melting and anti-skid device module and the data processing and control center are connected with each other through a network. The road condition monitoring module is installed on the key sections of the expressway to obtain the road data of the expressway in real time, and the road data includes the pavement temperature, humidity, snow thickness, ice thickness, friction coefficient and road image. The weather data acquisition module is used to acquire the weather data of the area where the expressway is located in real time. The intelligent snow melting and anti-skid device module is arranged on the preset sections of the expressway to perform snow melting agent spraying treatment, snow removal treatment and pavement heating treatment on the expressway according to the control instruction of the data processing and control center. The data processing and control center is used to receive the road data and weather data, predict the snowfall confidence of the relevant sections through a snowfall confidence model according to the weather data, generate an operation scheme by comprehensively considering the prediction result and the road data, and send the control instruction to the intelligent snow melting and anti-skid device module according to the operation scheme to dynamically adjust the snow melting agent spraying amount, snow removal parameter and pavement heating power.

[0005] In an optional embodiment, the road condition monitoring module includes a distributed sensor unit and a high-definition camera. The distributed sensor unit is arranged at the key sections and interval points of the expressway to acquire the pavement temperature, humidity, snow thickness, ice thickness and friction coefficient in real time. The key sections of the expressway include but are not limited to bridges, tunnel entrances, curved road sections and uphill and downhill road sections. The high-definition camera is used to capture real-time road images to identify the snow and ice state and traffic flow.

[0006] In an optional embodiment, the weather data acquisition module includes a weather data interface and an along-line weather station. The weather data interface is used to access the forecast data of the local weather data platform to obtain the predicted snowfall amount, snowfall intensity and temperature trend. The along-line weather station is arranged at the preset positions along the expressway to acquire wind speed data and wind direction data.

[0007] In an optional embodiment, the intelligent snow melting and anti-skid device module includes a snow melting agent spraying device, a snow removal shovel device and a heating cable system. The snow melting agent spraying device is equipped with a heating anti-blocking system to determine the spraying amount and spraying range according to the control instruction and perform snow melting agent spraying treatment on the pavement. The snow removal shovel device is used to adjust the shovel angle and operation intensity according to the control instruction to perform snow removal treatment on the pavement. The heating cable system is arranged on a high-risk section of a highway, and is used for heating treatment of the road surface according to control and management of starting and stopping and adjustment of heating power.

[0008] In a second aspect, the embodiments of the present application also provide a highway intelligent snow-melting and anti-skid method, comprising: The road condition monitoring module is used to acquire the road surface temperature, humidity, snow thickness, ice thickness, friction coefficient and road image of the highway in real time as road data, and send the road data to the data processing and control center; The weather data acquisition module is used to acquire the predicted snowfall, snowfall intensity, temperature trend, wind speed data and wind direction data of a preset position of the area where the highway is located in real time as weather data, and send the weather data to the data processing and control center; The data processing and control center is used to predict the snowfall confidence of the relevant section according to the weather data through a snowfall confidence model, generate a control instruction according to a work scheme generated based on the prediction result and the road data, and send the control instruction to the intelligent snow-melting and anti-skid device module; The intelligent snow-melting and anti-skid device module is used to perform snow-melting agent spraying treatment, snow removal treatment and road surface heating treatment on the highway according to the control instruction, snow-melting agent spraying amount, snow removal parameters and road surface heating power.

[0009] In an optional embodiment, the step of predicting the snowfall confidence of the relevant section according to the weather data through a snowfall confidence model comprises: The random forest algorithm is used to construct the snowfall confidence model, and the model is optimized based on training samples composed of a preset weather data training set by using a segmented weighted cross-entropy loss function; The predicted snowfall, snowfall intensity, temperature trend and real-time road surface temperature and humidity are input into the snowfall confidence model, and the snowfall confidence C of the relevant section is output.

[0010] In an optional embodiment, the segmented weighted cross-entropy loss function comprises:

[0011] wherein M is the total number of training samples, j is the sample index, is a snowfall sample weight coefficient, is a non-snowfall sample penalty coefficient, is a real label of the training sample j, is the snowfall confidence of the training sample j; when the actual snowfall intensity of the training sample j is greater than or equal to 0.8, =1.5; otherwise, =1.0; When the road surface temperature corresponding to the training sample j is greater than 2℃, = 2, otherwise, = 1.0; When = 1, it indicates that snowfall occurs; when = 0, it indicates that snowfall does not occur.

[0012] In an optional embodiment, the comprehensive prediction result and the road data are used to generate a work scheme, including: Real-time acquisition of the road surface temperature T, the road surface humidity S, the snow thickness H snow , the ice thickness H ice , the friction coefficient MC, and the road image; Based on the road surface temperature T in a preset time period, the road surface temperature reduction rate t is calculated; The road image is input into an image recognition model, and the real-time vehicle number in the picture is recognized to determine the traffic density Dt; When C is greater than or equal to 80% and T is less than or equal to 1℃, the snow-melting agent spraying amount Q is calculated by the formula Q = k1*Spred+k2*t; wherein Spred is the snowfall intensity corresponding to the snowfall confidence C, k1 is a snowfall amount coefficient, and k2 is a temperature reduction compensation coefficient; When H snow is greater than or equal to 3cm, the snowplow blade inclination angle θ is calculated by the formula θ = 15°+2.5°*H snow , and the work speed v of the snowplow blade device is calculated by the formula ; When S is greater than or equal to 80%, the local meteorological data platform is accessed through the meteorological data acquisition module to obtain the temperature drop value X in the past 1 hour, and if X is greater than or equal to 5℃, the heating cable system heating power per unit road surface area P is calculated by the formula P = G*H ice ; wherein G is an ice-melting power coefficient; When MC is less than 0.4, the snow-melting agent spraying amount Q is increased by 10%; When MC is less than 0.3, the heating cable system heating power per unit road surface area P is increased by 20%; Based on the calculated snow-melting agent spraying amount Q, the snowplow blade inclination angle θ, the work speed v of the snowplow blade device, and the heating cable system heating power per unit road surface area P, a work scheme is generated.

[0013] In a third aspect, the embodiments of the present application also provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the expressway intelligent snow-melting and anti-skid method according to any one of the above.

[0014] In a fourth aspect, the embodiments of the present application further provide a storage medium having a computer program stored thereon, wherein the computer program is executed by a processor to implement the steps of the intelligent snow-melting and anti-skid method for expressway as described in any of the above.

[0015] From the above technical solutions, the present application has the following advantages: The intelligent snow-melting and anti-skid system and method for expressway provided by the present application can realize real-time and accurate acquisition of road surface state, traffic flow and meteorological information through the road condition monitoring module and the meteorological data acquisition module, scientifically predict snowfall conditions in combination with a snowfall confidence model, and comprehensively analyze and generate a dynamic operation scheme by the data processing and control center, so as to accurately regulate the snow-melting agent spraying amount, snow removal parameters and road heating power, so that the intelligent snow-melting and anti-skid equipment module can carry out snow-melting, snow removal and heating treatment in a targeted manner. The intelligent snow-melting and anti-skid system and method for expressway provided by the present application not only improves the intelligent and accurate level of snow-melting and anti-skid operation, reduces the overuse of snow-melting agent and energy waste, but also can flexibly adjust the operation strategy according to the road conditions and weather changes, effectively cope with the snow and ice problems of high-risk sections such as bridges and tunnel entrances, and guarantee the traffic safety and efficiency of the expressway under complex weather conditions.

[0016] The present application can realize real-time and accurate monitoring of road conditions, traffic flow and meteorological information by using the distributed sensors and high-definition cameras of the road condition monitoring module to acquire detailed road data such as road surface temperature and snow depth, and road images, and combining the forecast data and real-time meteorological data along the line accessed by the meteorological data acquisition module, thereby providing a solid data foundation for subsequent decision-making.

[0017] The present application can predict snowfall conditions in advance by using a snowfall confidence model based on a random forest algorithm and a segmented weighted cross-entropy loss function, and combining meteorological data to predict the snowfall confidence of the relevant section, so as to change the snow-melting and anti-skid operation from passive response to active prevention, and improve the control ability of snow and ice risks.

[0018] The data processing and control center of the present application comprehensively predicts the results and road data, generates a personalized operation scheme through multi-dimensional formula calculation, dynamically adjusts the snow-melting agent spraying amount, snow removal shovel angle and speed, road heating power and other parameters, avoids overuse of snow-melting agent and energy waste, and realizes efficient use of resources.

[0019] The intelligent snow-melting and anti-skid equipment module of the present application integrates snow-melting agent spraying, snow removal shovel, heating cable and other devices, provides diversified processing modes such as spraying, snow removal and heating for high-risk sections such as bridges and tunnel entrances and different snow and ice levels, and cooperatively plays a role to effectively cope with various ice and snow scenes.

[0020] The application can eliminate the hidden danger of snow and ice on the expressway in time, improve the friction coefficient of the road surface, ensure the traffic safety of vehicles in complex weather, reduce the traffic congestion caused by ice and snow weather, and improve the overall traffic operation efficiency of the expressway through accurate monitoring, scientific prediction and dynamic operation. BRIEF DESCRIPTION OF DRAWINGS

[0021] In order to more clearly illustrate the technical solutions of the present application, the drawings needed to be used in the description will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0022] Figure 1 The system structure principle diagram of the intelligent snow melting and anti-skid system of the expressway provided by the present application.

[0023] Figure 2 The flowchart of the intelligent snow melting and anti-skid method of the expressway provided by the present application.

[0024] Figure 3 The structure diagram of the electronic device provided by the present application. DETAILED DESCRIPTION

[0025] In the following detailed description of the specific steps of the intelligent snow melting and anti-skid system and method of the expressway, various embodiments of the present disclosure will be described more fully. The present disclosure can have various embodiments, and adjustments and changes can be made therein. However, it should be understood that there is no intention to limit various embodiments of the present disclosure to the specific embodiments disclosed herein, but the present disclosure should be understood to cover all adjustments, equivalents and / or alternatives falling within the spirit and scope of various embodiments of the present disclosure.

[0026] In the following, the term "include" or "may include" used in various embodiments of the present disclosure indicates the presence of the disclosed functions, operations or elements, and does not limit the addition of one or more functions, operations or elements. In addition, as used in various embodiments of the present disclosure, the terms "include", "have" and their synonyms only mean to indicate a specific feature, number, step, operation, element, component or combination of the foregoing, and should not be understood as first excluding the presence or addition of one or more other features, numbers, steps, operations, elements, components or combinations of the foregoing, or the possibility of one or more features, numbers, steps, operations, elements, components or combinations of the foregoing.

[0027] With reference to the drawings of the embodiments of the present application, the technical solutions in the embodiments of the present application will be described clearly and completely. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of the present application.

[0028] Please refer to Figure 1 Fig. 1 is a system structure schematic diagram of a high-speed intelligent snow-melting and anti-skid system in an embodiment, which comprises a road condition monitoring module, a meteorological data acquisition module, an intelligent snow-melting and anti-skid device module, and a data processing and control center. The road condition monitoring module, the meteorological data acquisition module, and the intelligent snow-melting and anti-skid device module are respectively connected to the data processing and control center through a network.

[0029] The road condition monitoring module is installed at key sections of the high-speed highway to obtain real-time road data of the high-speed highway, which includes road surface temperature, humidity, snow thickness, ice thickness, friction coefficient, and road images.

[0030] In the specific embodiment, the road condition monitoring module comprises a distributed sensor unit and a high-definition camera.

[0031] The distributed sensor unit is arranged at key sections and interval points of the high-speed highway to collect real-time road surface temperature, humidity, snow thickness, ice thickness, and friction coefficient. The key sections of the high-speed highway include, but are not limited to, bridges, tunnel entrances, curved road sections, uphill and downhill road sections.

[0032] As can be seen, a plurality of distributed sensor units are installed at key sections of the high-speed highway (such as bridges, tunnel entrances, curves, uphill and downhill sections, etc.) and at every certain interval of ordinary road sections. These sensor units can monitor real-time road condition parameters such as road surface temperature, humidity, snow thickness, ice thickness, and friction coefficient.

[0033] The high-definition camera is used to capture real-time road images to identify snow and ice conditions and traffic flow.

[0034] The meteorological data acquisition module is used to collect real-time meteorological data of the area where the high-speed highway is located.

[0035] In the specific embodiment, the meteorological data acquisition module comprises a meteorological data interface and an along-line weather station.

[0036] The meteorological data interface is used to access forecast data from the local meteorological data platform to obtain predicted snowfall amount, snowfall intensity, and temperature trends. For example, the meteorological data interface is connected to the meteorological data interface of the local meteorological data platform to obtain real-time weather forecast information for the area where the expressway is located, including meteorological data such as snowfall amount, snowfall intensity, and temperature trends.

[0037] Weather stations are set up at pre-set locations along the highway to collect wind speed and direction data. By accurately collecting localized weather data, such as wind speed and direction, they provide a more accurate understanding of the weather environment around the road.

[0038] The intelligent snow-melting and anti-skid equipment module is set up on a preset section of the highway, and is used to spray snow-melting agents, remove snow and heat the road surface on the highway according to the control instructions of the data processing and control center.

[0039] In a specific embodiment, the intelligent snow melting and anti-skid equipment module includes a snow melting agent spraying device, a snow removal shovel device and a heating cable system.

[0040] The de-icing agent spraying devices are equipped with a heating and anti-clogging system. They determine the spraying volume and range based on control commands, applying de-icing agent to the road surface. Multiple intelligent de-icing agent spraying devices are installed along the highway. These devices precisely adjust the spraying volume and range based on control commands. Each spraying device is equipped with a heating system to ensure normal de-icing agent spraying in low-temperature environments and prevent clogging.

[0041] A snowplow is a device that adjusts the angle and force of the plow according to control commands to remove snow from the road surface. For example, a snowplow with automatic angle and force adjustment is used to clear thick snow. The plow automatically activates and adjusts operating parameters based on road conditions and weather data to achieve optimal snow removal results.

[0042] Heating cable systems are deployed along pre-defined high-risk sections of highways. They heat the road surface by controlling the start / stop and adjusting the heating power according to control measures. For example, this system installs heating cable systems on certain sections of the road. When the system detects the risk of icing or has already frozen, it heats and melts the ice, ensuring a good friction coefficient.

[0043] The data processing and control center is used to receive road data and meteorological data, predict the snowfall confidence of relevant road sections based on the meteorological data through the snowfall confidence model, generate an operation plan based on the comprehensive prediction results and road data, and generate control instructions based on the operation plan and send them to the intelligent snow melting and anti-skid equipment module to dynamically adjust the snow melting agent spraying amount, snow removal parameters and road surface heating power.

[0044] In the specific embodiment, the data processing and control center is specifically used for: receiving real-time data from the road condition monitoring module and the weather data acquisition module, and comprehensively analyzing and processing. Through the built-in intelligent algorithm, according to the road conditions, weather conditions and traffic flow and other factors, the best snow melting and anti-skid operation scheme is formulated.

[0045] sending control instructions to the intelligent snow melting and anti-skid equipment module, accurately controlling the operation state of the snow melting agent spraying device, snow shovel device and heating cable system and other equipment, and realizing intelligent snow melting and anti-skid operation.

[0046] In the embodiment, through the distributed sensors and high-definition cameras of the road condition monitoring module, the road data such as road surface temperature and snow thickness and road images of key sections are accurately and real-timely collected, combined with the weather forecast data and real-time wind speed and direction accessed by the weather data acquisition module, to provide comprehensive information support for the data processing and control center; the center scientifically predicts snowfall conditions by means of a snowfall confidence model, generates a dynamic operation scheme after comprehensive analysis, accurately controls the operation parameters of the snow melting agent spraying device, snow shovel device and heating cable system in the intelligent snow melting and anti-skid equipment module, realizes dynamic adaptation of snow melting agent spraying amount, snow removal parameters and heating power, can not only targetedly deal with the ice and snow problems of high-risk sections such as bridges and tunnel entrances, reduce overuse of snow melting agent and energy waste, but also can improve the accuracy and efficiency of snow melting and anti-skid operation through intelligent collaborative operation, effectively guarantee the traffic safety of the expressway in snowy weather.

[0047] As shown in Figure 2 the following is an embodiment of an expressway intelligent snow melting and anti-skid method provided by the embodiment of the present disclosure, which belongs to the same inventive concept as the above-mentioned embodiments of the expressway intelligent snow melting and anti-skid system. Details not described in the embodiment of the expressway intelligent snow melting and anti-skid method can be referred to the above-mentioned embodiments of the expressway intelligent snow melting and anti-skid system.

[0048] An expressway intelligent snow melting and anti-skid method, comprising the following steps: S1: acquiring, by a road condition monitoring module, road surface temperature, humidity, snow thickness, ice thickness, friction coefficient and road images of an expressway in real time as road data, and sending the road data to a data processing and control center.

[0049] S2: acquiring, by a weather data acquisition module, predicted snowfall amount, snowfall intensity, temperature trend of an area where the expressway is located, and wind speed data and wind direction data of a preset position in real time as weather data, and sending the weather data to the data processing and control center.

[0050] In the above steps, the road condition monitoring module and the meteorological data acquisition module continuously collect various data, and transmit the data to the data processing and control center in real time.

[0051] S3: Through the data processing and control center, the snowfall confidence of the relevant road section is predicted according to the meteorological data through the snowfall confidence model, the prediction results and the road data are comprehensively predicted to generate the operation scheme, and the control instruction is sent to the intelligent snow melting and anti-skid device module according to the operation scheme.

[0052] In the specific embodiment, the data processing and control center analyzes the received data to determine the degree of snow and ice accumulation on the current road, the development trend, and the influence of meteorological changes on the road conditions. At the same time, combined with the traffic flow data, the potential threat degree of snow and ice accumulation to traffic safety is evaluated.

[0053] According to the data analysis results, the data processing and control center uses intelligent algorithms to develop a snow melting and anti-skid operation scheme. If it is predicted that there will be snowfall soon and the road surface temperature is close to the freezing point, the intelligent snow melting agent spraying device is started in advance, and the initial snow melting agent spraying amount is determined according to the snowfall amount and road surface temperature and other factors. When it is monitored that there is snow on the road surface and the thickness reaches a certain threshold, the snow shovel device is automatically started, and the angle and operation speed of the snow shovel are adjusted according to the snow thickness and road slope and other conditions. If it is found that the road surface has icing phenomenon or high icing risk (such as high humidity and sudden temperature drop), the heating cable system is started in time for ice melting operation, and the heating power is adjusted according to the ice thickness.

[0054] Finally, the data processing and control center converts the developed operation scheme into specific control instructions and sends them to the intelligent snow melting and anti-skid device module.

[0055] In this step, the snowfall confidence of the relevant road section is predicted according to the meteorological data through the snowfall confidence model to realize the prediction and determination of the degree of snow and ice accumulation on the current road, the development trend, and the influence of meteorological changes on the road conditions.

[0056] The snowfall confidence model is constructed by using the random forest algorithm, and is optimized based on the training samples composed of the pre-set meteorological data training set by using the segmented weighted cross-entropy loss function.

[0057] The segmented weighted cross-entropy loss function includes:

[0058] Wherein, M is the total number of training samples, j is the sample index, is the snowfall sample weight coefficient, is the non-snowfall sample penalty coefficient, is the true label of the training sample j, is the snowfall confidence of the training sample j; When the actual snowfall intensity of the training sample j is greater than or equal to 0.8, = 1.5; otherwise, = 1.0; When the road surface temperature corresponding to the training sample j is greater than 2℃, = 2, otherwise, = 1.0; When = 1, it means that snowfall occurs; when = 0, it means that snowfall does not occur.

[0059] In actual application, the predicted snowfall, snowfall intensity, temperature trend, and real-time road surface temperature and humidity are input into the snowfall confidence model to output the snowfall confidence C of the relevant road section.

[0060] The generation process of the operation scheme includes, for example: First, the real-time road surface temperature T, road surface humidity S, snow thickness Hsnow, ice thickness Hice, friction coefficient MC, and road image are obtained; the road surface temperature T in a preset time period is calculated to obtain the road surface cooling rate t; the road image is input into an image recognition model to recognize the real-time number of vehicles in the picture to determine the traffic density Dt.

[0061] Then, based on the collected and summarized data, the control parameters of the snow-melting agent spraying device, snow shovel device, and heating cable system are determined through judgment and analysis, and the operation scheme is generated.

[0062] Mainly includes the following three aspects: The first aspect is that when C≥80% and T≤1℃, the snow-melting agent spraying amount Q is calculated by the formula Q=k1×Spred+k2×t; wherein, Spred is the snowfall intensity corresponding to the snowfall confidence C, k1 is the snowfall amount coefficient, and k2 is the temperature drop compensation coefficient.

[0063] The second aspect is that when H snow ≥ 3cm, the snow shovel inclination angle θ is calculated by the formula θ=15°+2.5°×H snow ice, and the operation speed v of the snow shovel device is calculated by the formula

[0064] The third aspect is that when S≥80%, the past 1 hour temperature drop value X is obtained by accessing the local meteorological data platform through the meteorological data acquisition module, and if X≥5℃, the heating cable system heating power P per unit road surface area is calculated by the formula P=G×Hice; wherein, G is the ice melting power coefficient.

[0065] ​In addition, in the method, the control parameters are adjusted according to the real-time collected friction coefficient MC, so as to ensure the operation effect. Specifically, when MC < 0.4, the snow-melting agent spraying amount Q is increased by 10%; and when MC < 0.3, the heating cable system heating power P per unit road surface area is increased by 20%.

[0066] Finally, after the above process, the operation scheme is generated based on the calculated snow-melting agent spraying amount Q, snow shovel inclination angle θ, snow shovel device operation speed v and heating cable system heating power P per unit road surface area.

[0067] S4: The intelligent snow-melting and anti-skid equipment module sprays snow-melting agent, removes snow and heats the road surface according to the control instructions of the snow-melting agent spraying amount, the snow removal parameters and the road heating power.

[0068] In the specific embodiment, each device in the intelligent snow-melting and anti-skid equipment module operates accurately according to the received instructions. For example, the snow-melting agent spraying device adjusts the spraying amount, spraying angle and spraying frequency according to the instructions; the snow shovel device removes snow according to the set parameters; and the heating cable system adjusts the heating power and working time according to the requirements.

[0069] In addition, in the operation process, the road condition monitoring module continuously monitors the changes of the road conditions and feeds back the real-time data to the data processing and control center, so as to timely adjust the operation scheme and the equipment operation parameters, and ensure the effectiveness and accuracy of the snow-melting and anti-skid operation.

[0070] The intelligent snow-melting and anti-skid method for expressways provided in the embodiment realizes the intelligent regulation and control of the snow-melting and anti-skid operation by real-time acquisition of road data such as road surface temperature and snow thickness and regional meteorological data, accurate prediction of snowfall conditions relying on a snowfall confidence model, dynamic calculation of parameters such as snow-melting agent spraying amount, snow shovel angle and speed and road heating power through a multi-dimensional formula based on the prediction results and the road data and generation of an operation scheme. The method can flexibly adjust the operation strategy according to factors such as snowfall confidence, road condition and traffic flow, such as dynamically increasing the snow-melting agent amount or the heating power according to the friction coefficient, so as to ensure the pertinence and effectiveness of the snow-melting and anti-skid operation, avoid resource waste, and proactively cope with the ice and snow risks, thereby significantly improving the traffic safety and traffic operation efficiency of the expressway under complex weather conditions.

[0071] Figure 3 A hardware structure schematic diagram of an electronic device for implementing various embodiments of the present application.

[0072] The expressway intelligent snow-melting and anti-skidding method provided by the embodiments of the present application can be applied to an electronic device. Those skilled in the art can understand that the electronic device structure involved in the embodiments of the present application does not constitute a limitation on the electronic device, and the electronic device can include more or fewer components than the diagram, or combine certain components, or different component arrangements. In the embodiments of the present application, the electronic device includes but is not limited to a laptop computer, a desktop computer, a workstation, a personal digital assistant, a server, a blade server, a mainframe computer, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as a personal digital processor, a cellular phone, a smart phone, a wearable device, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples, and are not intended to limit the implementation of the embodiments of the present application described herein and / or claimed.

[0073] The electronic device can include a processor, an external memory interface, an internal memory, a universal serial bus (USB) interface, a charge management module, a power management module, a battery, a wireless communication module, an audio module, a speaker, a microphone, a sensor module, a key, a camera, a display screen, and a SIM card interface, and the like.

[0074] The processor can include one or more processing units, such as: the processor can include a central processing unit (CPU), an application processor (AP), a modem processor, a graphics processing unit (GPU), an image signal processor (ISP), a controller, a memory, a video codec, a digital signal processor (DSP), a baseband processor, and / or a neural-network processing unit (NPU), and the like. Among them, different processing units can be independent devices, or can be integrated in one or more processors.

[0075] Among them, the processor can be the nerve center and command center of the electronic device. The controller can generate operation control signals according to instruction operation codes and timing signals to complete the control of fetching and executing instructions.

[0076] The processor can further include a memory that stores instructions and data. In some embodiments, the memory in the processor is a cache memory. The memory can hold instructions or data that the processor has recently used or is likely to use again. If the processor needs to use the instructions or data again, it can call them directly from the memory. This avoids repeated access and reduces the processor's latency, thus improving system efficiency.

[0077] The external memory interface can be used to connect an external memory card, such as a MicroSD card, to extend the storage capacity of the electronic device. The external memory card communicates with the processor through the external memory interface to implement data storage functions. For example, music, video, and other files are saved in the external memory card.

[0078] The internal memory can be used to store computer executable program code, which includes instructions. The processor executes various functional applications and data processing of the electronic device by running the instructions stored in the internal memory. The internal memory can include a program storage area and a data storage area. The internal memory can include a high-speed random access memory and can also include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, a universal flash storage (UFS), etc.

[0079] The wireless communication function of the electronic device can be implemented through an antenna, a wireless communication module, a modem processor, and a baseband processor, etc.

[0080] The wireless communication module can provide a wireless communication solution including wireless local area networks (WLAN) (such as wireless fidelity (Wi-Fi) networks), Bluetooth (BT), global navigation satellite systems (GNSS), frequency modulation (FM), near field communication (NFC), infrared technology (IR), etc. applied to the electronic device.

[0081] The electronic device can implement audio functions, etc. through an audio module, a speaker, a receiver, a microphone, an earphone interface, and an application processor, etc.

[0082] The electronic device can implement a shooting function through an ISP, a camera, a video codec, a GPU, a display screen, and an application processor, etc.

[0083] The electronic device can realize display function through GPU, display screen and application processor.

[0084] The GPU is a microprocessor for image processing, connecting the display screen and the application processor. The GPU is used to perform mathematical and geometric calculations for graphics rendering. The processor can include one or more GPUs that execute program instructions to generate or change display information.

[0085] The display screen is used to display images, videos, etc. The display screen includes a display panel.

[0086] The electronic device realizes the highway intelligent snow melting and anti-skid method. The highway intelligent snow melting and anti-skid method realizes accurate operation and flexible adjustment by dynamically calculating and regulating snow melting, snow removal and heating parameters based on real-time collection of road and meteorological data and prediction results of a snowfall confidence model, thereby achieving the beneficial effects of avoiding resource waste, efficiently dealing with ice and snow risks, and improving traffic safety and traffic efficiency.

[0087] In the storage medium provided in the present application, a program product capable of realizing the highway intelligent snow melting and anti-skid method is stored.

[0088] The highway intelligent snow melting and anti-skid method comprises: The road condition monitoring module is used to acquire the road surface temperature, humidity, snow thickness, ice thickness, friction coefficient and road image of the highway in real time as road data, and send the road data to the data processing and control center; The meteorological data acquisition module is used to acquire the predicted snowfall, snowfall intensity, temperature trend of the area where the highway is located, and wind speed data and wind direction data of the preset position in real time as meteorological data, and send the meteorological data to the data processing and control center; The data processing and control center is used to predict the snowfall confidence of the relevant road section through the snowfall confidence model according to the meteorological data, generate a work scheme by comprehensively predicting the results and the road data, and send a control instruction to the intelligent snow melting and anti-skid device module according to the work scheme; The intelligent snow melting and anti-skid device module is used to spray snow melting agent, remove snow and heat the road surface according to the control instruction.

[0089] In some possible implementations, the highway intelligent snow melting and anti-skid method of the present disclosure can be realized in the form of a program product, which includes program code for causing a terminal device to execute the steps according to various exemplary embodiments of the present disclosure described in the above "Exemplary Method" section of the present specification when the program product is run on the terminal device.

[0090] The storage medium of the present disclosure can employ any combination of one or more computer-readable media. The computer-readable media can be a computer- readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium include the following: an electrical connection having one or more wires, a portable disc, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0091] The foregoing description of the disclosed embodiments enables a person skilled in the art to implement or use the invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the generic principles defined herein can be applied to other embodiments without departing from the spirit or scope of the invention. Accordingly, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An intelligent snow melting and anti-skid system for highways, characterized by: include: The road condition monitoring module, meteorological data collection module, intelligent snow melting and anti-skid equipment module and data processing and control center are connected to the data processing and control center through the network respectively; The road condition monitoring module is installed at key sections of the highway to obtain real-time highway road data, including road surface temperature, humidity, snow thickness, ice thickness, friction coefficient, and road images; Meteorological data collection module, used to collect real-time meteorological data in the area where the expressway is located; The intelligent snow-melting and anti-skid equipment module is installed on a preset section of the highway and is used to spray snow-melting agents, remove snow, and heat the road surface according to the control instructions of the data processing and control center. The data processing and control center is used to receive road data and meteorological data, predict the snowfall confidence of relevant road sections based on the meteorological data through the snowfall confidence model, generate an operation plan based on the comprehensive prediction results and road data, and generate control instructions based on the operation plan and send them to the intelligent snow melting and anti-skid equipment module to dynamically adjust the snow melting agent spraying amount, snow removal parameters and road surface heating power.

2. The intelligent snow melting and anti-skid system for highways according to claim 1 is characterized in that: The road condition monitoring module includes distributed sensor units and high-definition cameras; Distributed sensor units are deployed at key highway sections and interval points to collect real-time information on road surface temperature, humidity, snow depth, ice thickness, and friction coefficient. Key highway sections include but are not limited to bridges, tunnel entrances, curved sections, and uphill and downhill sections. High-definition cameras are used to capture real-time road images to identify snow and ice conditions and traffic flow.

3. The intelligent snow melting and anti-skid system for highways according to claim 2 is characterized in that: The meteorological data acquisition module includes a meteorological data interface and meteorological stations along the route; Meteorological data interface, used to access forecast data from the local meteorological data platform to obtain predicted snowfall amount, snowfall intensity, and temperature trends; Meteorological stations along the highway are set up at preset locations along the highway to collect wind speed and direction data.

4. The intelligent snow melting and anti-skid system for highways according to claim 3 is characterized in that: The intelligent snow melting and anti-skid equipment module includes a snow melting agent spraying device, a snow removal shovel device and a heating cable system; The snow-melting agent spraying device is equipped with a heating and anti-blocking system, which is used to determine the spraying amount and spraying range according to the control instructions and spray the snow-melting agent on the road surface; Snow removal shovel device, used to adjust the shovel body angle and operating force according to control instructions to remove snow from the road surface; The heating cable system is installed in high-risk sections of highways and is used to start and stop and adjust the heating power according to control management to heat the road surface.

5. An intelligent snow melting and anti-skid method for highways, characterized in that: The system adopts the intelligent snow melting and anti-skid system for highways as described in any one of claims 1 to 4; The method comprises: The road condition monitoring module obtains the road surface temperature, humidity, snow thickness, ice thickness, friction coefficient, and road images of the highway in real time as road data, and sends the road data to the data processing and control center; The meteorological data collection module collects in real time the predicted snowfall amount, snowfall intensity, temperature trend, and wind speed and direction data of the preset location in the area where the expressway is located as meteorological data, and sends the meteorological data to the data processing and control center; The data processing and control center uses the snowfall confidence model to predict the snowfall confidence of relevant road sections based on meteorological data. The prediction results and road data are combined to generate an operation plan, and control instructions are generated based on the operation plan and sent to the intelligent snow melting and anti-skid equipment module; Through the intelligent snow-melting and anti-skid equipment module, snow-melting agent spraying, snow removal and road surface heating treatment are carried out on the highway according to the control instructions of snow-melting agent spraying amount, snow removal parameters and road surface heating power.

6. The intelligent snow melting and anti-skid method for highways according to claim 5, characterized in that: The snowfall confidence model is used to predict the snowfall confidence of the relevant road section based on the meteorological data, including: A random forest algorithm is used to construct a snowfall confidence model, and the piecewise weighted cross entropy loss function is used to optimize the model based on training samples consisting of a preset meteorological data training set. The predicted snowfall amount, snowfall intensity, temperature trend, and real-time road surface temperature and humidity are input into the snowfall confidence model to output the snowfall confidence C of the relevant road section.

7. The intelligent snow melting and anti-skid method for highways according to claim 6, characterized in that: The piecewise weighted cross entropy loss function includes: Among them, M is the total number of training samples, j is the sample index, is the snowfall sample weight coefficient, is the penalty coefficient for non-snowfall samples, is the true label of training sample j, is the snowfall confidence of training sample j; When the actual snowfall intensity of training sample j is greater than or equal to 0.8, =1.5; otherwise, =1.0; When the road surface temperature corresponding to training sample j is greater than 2°C, =2, otherwise, =1.0; when =1, it means snowfall occurs; when =0, indicating that no snowfall occurs.

8. The intelligent snow melting and anti-skid method for highways according to claim 7, characterized in that: The comprehensive prediction results and road data are used to generate an operation plan, including: Real-time acquisition of road surface temperature T, road surface humidity S, and snow thickness H snow , ice thickness H ice , friction coefficient MC, road image; Calculate the road surface cooling rate t based on the road surface temperature T during a preset time period; The road image is input into the image recognition model to identify the real-time number of vehicles in the image to determine the traffic density Dt; When C ≥ 80% and T ≤ 1°C, the snowmelt spraying amount Q is calculated using the formula Q = k1 × Spred + k2 × t; where Spred is the snowfall intensity corresponding to the snowfall confidence level C, k1 is the snowfall coefficient, and k2 is the temperature drop compensation coefficient. When H snow When the distance is ≥3cm, the formula θ=15°+2.5°×H snow Calculate the snow shovel tilt angle θ and use the formula Calculate the operating speed v of the snow removal shovel device; When S≥80%, the meteorological data acquisition module is used to access the local meteorological data platform in real time to obtain the temperature drop value X in the past hour. If X≥5℃, the formula P=G×H is used. ice Calculate the heating power P per unit road surface area of ​​the heating cable system; where G is the ice melting power coefficient; When MC is less than 0.4, the amount of snow-melting agent sprayed Q is increased by 10%; When MC is less than 0.3, the heating power P of the heating cable system per unit road surface area is increased by 20%; An operation plan is generated based on the calculated snowmelt spraying amount Q, the snowplow tilt angle θ, the snowplow device operating speed v, and the heating power P of the heating cable system per unit road surface area.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the intelligent snow melting and anti-skid method for highways as claimed in any one of claims 5 to 8 are implemented.

10. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the intelligent snow melting and anti-skid method for highways as claimed in any one of claims 5 to 8 are implemented.

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