CN114999113A - Real-time prediction method for icing state of highway pavement - Google Patents

Real-time prediction method for icing state of highway pavement Download PDF

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CN114999113A
CN114999113A CN202210539941.7A CN202210539941A CN114999113A CN 114999113 A CN114999113 A CN 114999113A CN 202210539941 A CN202210539941 A CN 202210539941A CN 114999113 A CN114999113 A CN 114999113A
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icing
early warning
highway
control system
central control
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姜小磊
聂磊晶
余春
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Jiangxi Vocational and Technical College of Communication
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    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
    • G08B21/02—Alarms for ensuring the safety of persons
    • G08B21/10—Alarms for ensuring the safety of persons responsive to calamitous events, e.g. tornados or earthquakes
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00—Measuring arrangements characterised by the use of optical techniques
    • G01B11/02—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness
    • G01B11/06—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness for measuring thickness ; e.g. of sheet material
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B7/00—Measuring arrangements characterised by the use of electric or magnetic techniques
    • G01B7/02—Measuring arrangements characterised by the use of electric or magnetic techniques for measuring length, width or thickness
    • G01B7/06—Measuring arrangements characterised by the use of electric or magnetic techniques for measuring length, width or thickness for measuring thickness
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
    • G01D21/00—Measuring or testing not otherwise provided for
    • G01D21/02—Measuring two or more variables by means not covered by a single other subclass
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/95—Radar or analogous systems specially adapted for specific applications for meteorological use
    • G01S13/951—Radar or analogous systems specially adapted for specific applications for meteorological use ground based
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
    • G08B21/18—Status alarms
    • G08B21/182—Level alarms, e.g. alarms responsive to variables exceeding a threshold
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
    • Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Abstract

The invention discloses a real-time prediction method for an icing state of a highway pavement, which comprises the steps of arranging integrated sensors of temperature, wind speed, rainfall and traffic flow on the highway at intervals, transmitting data to an icing prediction model in real time, calculating icing probability, and uploading the icing probability to a central control system and carrying out early warning when the icing probability is greater than a set value; and arranging ice measuring instruments on the highway at intervals, sending a command to the ice measuring instruments on the corresponding road sections by the central control system after the primary early warning is started, monitoring the primary early warning area in time, and uploading icing thickness data to the central control system and carrying out secondary early warning once icing is monitored. The method can effectively meet the detection requirements of the highway on the high precision and timeliness of the frozen state of the pavement, and ensure the safe driving of vehicles on the highway.

Description

Real-time prediction method for icing state of highway pavement
Technical Field
The invention belongs to the technical field of highway supervision, and particularly relates to a real-time prediction method for an icing state of a highway pavement.
Background
The highway is an important component of the traffic network in China, is distributed all over the country and is a transportation requirement in China. And the vehicle needs to run at high speed on the highway, so the requirement on road conditions is extremely high, the road surface condition is good, and the safe running of the vehicle can be effectively ensured.
And the environmental conditions of a plurality of road sections in the expressway are not good, and the road surface is often frozen. When the road surface is frozen, the vehicle is easy to slip, and serious traffic accidents are caused. In order to avoid such traffic accidents, a high-speed manager needs to timely handle the icing state of the road surface.
At present, cameras are arranged on road sections for video monitoring, so that road surface images are acquired in real time to judge the icing state of the road surface. However, the method is greatly influenced by the environment, and cannot ensure that a better light environment is available for image acquisition all day long; and when the pavement is initially iced, the ice is not easy to be found; the predicted icy state of the pavement cannot be extracted; causing the ice state of the road surface to be treated untimely.
Disclosure of Invention
In order to solve the problems, the invention provides a real-time prediction method for the icing state of the highway, which can effectively meet the detection requirements of the highway on the high precision and timeliness of the icing state of the highway and ensure the safe driving of vehicles on the highway.
In order to achieve the purpose, the invention adopts the technical scheme that: a real-time prediction method for the icing state of a highway pavement comprises the following steps:
arranging temperature, wind speed, rainfall and traffic flow integrated sensors at intervals on a highway, transmitting data to an icing prediction model in real time, calculating icing probability, and uploading the icing probability to a central control system and carrying out early warning when the icing probability is greater than a set value;
and arranging ice measuring instruments on the highway at intervals, sending a command to the ice measuring instruments on the corresponding road sections by the central control system after the primary early warning is started, monitoring the primary early warning area in time, and uploading icing thickness data to the central control system and carrying out secondary early warning once icing is monitored.
Further, the temperature, the wind speed, the rainfall and the traffic flow of the road surface are used as road surface ice condensation sample data, big data analysis is carried out on road surface icing influence factors on the basis of the acquired historical data of road surface ice condensation and the acquired real-time data, supervised learning is carried out according to different environments, and an icing prediction model is established.
Further, a calculation model is established in the icing prediction model, and the icing probability at the current time t is calculated as follows:
Figure BDA0003650243180000021
wherein TE t Is the temperature value, S t Is the wind speed value, R t Is the amount of rainfall, TR t Is the traffic flow, omega 1 、ω 2 、ω 3 And ω 4 The weight coefficients corresponding to the temperature, the wind speed, the rainfall and the traffic flow are obtained by sample data training.
Further, radar ice measuring instruments are arranged on the highway at intervals, after the primary early warning is started, the central control system sends commands to the radar ice measuring instruments on the corresponding road sections, the primary early warning area is monitored in time, and once icing is monitored, icing thickness data are uploaded to the central control system and secondary early warning is carried out;
the active infrared ice monitor is installed simultaneously on the icing frequency-sending road section, a primary early warning result is monitored more accurately, icing is monitored, and icing thickness data are uploaded to a central control system and secondary early warning are carried out.
Further, when the millimeter wave radar is adopted to carry out real-time icing monitoring on the road surface: the radar transmits a high-frequency millimeter wave signal, and the echo is subjected to signal processing; judging the icing condition and the icing thickness based on the difference of the echoes of the ground, ice or water objects; and if icing is monitored, uploading data in real time and giving an early warning.
Further, in order to more accurately acquire the icing thickness data, when the icing frequency generation section adopts active infrared ice monitoring:
the infrared laser is directly irradiated on the icing surface of the object, the energy of the laser reflected by the icing surface of the object is received through the photoelectric detector, the reflection coefficients of the icing surface under different incidence angles and observation angles are obtained through calculation, and the icing condition of the surface of the object is deduced according to the icing coefficients. The method can detect the icing condition of a fixed area, and has higher precision, larger environmental influence and higher manufacturing cost compared with a radar detection method.
Further, a real-time display screen is installed on a section where the icing frequently occurs, the display screen is connected to the central control system, when the section sends out secondary early warning, the icing condition of the road surface is displayed in real time, and the driver driving on the section is informed through real-time early warning.
The beneficial effects of the technical scheme are as follows:
the method comprises the steps of firstly, arranging temperature, wind speed, rainfall and traffic flow integrated sensors at intervals on a highway, transmitting data to an icing prediction model in real time, calculating icing probability, and uploading the icing probability to a central control system and carrying out early warning when the icing probability is greater than a set value; then, arranging ice measuring instruments on the highway at intervals by using the system, sending a command to the ice measuring instruments on the corresponding road sections by the central control system after primary early warning is started, monitoring a primary early warning area in time, and uploading icing thickness data to the central control system and carrying out secondary early warning once icing is monitored; the detection requirements of the expressway on the high precision and timeliness of the icing state can be effectively met, and the safe driving of vehicles on the expressway is guaranteed.
The method takes the temperature, the wind speed, the rainfall and the traffic flow of the road surface as road surface ice condensation sample data, carries out big data analysis on road surface icing influencing factors based on the acquired historical data of road surface ice condensation and the acquired real-time data, carries out supervised learning aiming at different environments, and establishes an icing prediction model; the icing prediction model is used for carrying out early warning once, and the road section to be iced can be effectively predicted according to environmental factors and is regarded as a key attention object. Then, simultaneously installing an active infrared ice monitor on the icing frequent road section by using a radar ice measuring instrument, and performing secondary early warning; the icing state of the pavement which is focused on is pertinently detected, and a primary early warning result is more accurately monitored; thereby enabling accurate detection of detailed icing conditions. By adopting the method, the calculated amount can be effectively retrieved, and the detection real-time performance is improved; meanwhile, according to the combination of two-stage early warning, the road section to be frozen and the real-time freezing state of the road section can be acquired with high precision.
Drawings
FIG. 1 is a schematic flow chart of a real-time predicting method for the icing condition of the highway pavement according to the invention;
FIG. 2 is a schematic diagram of a highway icing prediction model in an embodiment of the invention;
FIG. 3 is a schematic diagram of an installation of millimeter wave radar monitoring in an embodiment of the present invention;
FIG. 4 is a schematic diagram of the principle of active infrared ice monitoring in an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described with reference to the accompanying drawings.
In this embodiment, referring to fig. 1, the present invention provides a real-time predicting method for an icing condition of a highway pavement, including the steps of:
arranging temperature, wind speed, rainfall and traffic flow integrated sensors at intervals on a highway, transmitting data to an icing prediction model in real time, calculating icing probability, and uploading the icing probability to a central control system and carrying out early warning when the icing probability is greater than a set value;
and arranging ice measuring instruments on the highway at intervals, sending a command to the ice measuring instruments on the corresponding road sections by the central control system after the primary early warning is started, monitoring the primary early warning area in time, and uploading icing thickness data to the central control system and carrying out secondary early warning once icing is monitored.
As an optimization scheme 1 of the above embodiment, as shown in fig. 2, the temperature, the wind speed, the rainfall and the traffic flow of the road surface are used as road surface ice-condensation sample data, large data analysis is performed on road surface ice-condensation influencing factors based on the acquired historical data of road surface ice-condensation and the acquired real-time data, supervised learning is performed for different environments, and an ice prediction model is established.
Establishing a calculation model in the icing prediction model, wherein the icing probability of the current moment t is calculated as follows:
Figure BDA0003650243180000051
wherein TE t Is the temperature value, S t Is the wind speed value, R t Is the amount of rainfall, TR t The traffic flow is the traffic flow, namely the number of vehicles passing through the road section in unit time; omega 1 、ω 2 、ω 3 And ω 4 The weight coefficients corresponding to the temperature, the wind speed, the rainfall and the traffic flow are obtained by sample data training.
As an optimization scheme 2 of the embodiment, the radar ice measuring instruments are arranged on the highway at intervals, the central control system sends commands to the radar ice measuring instruments on the corresponding road sections after the primary early warning is started, the primary early warning area is monitored in time, and once icing is monitored, icing thickness data are uploaded to the central control system and secondary early warning is carried out;
and an active infrared ice monitor is installed at the icing frequency generation road section, a primary early warning result is monitored more accurately, icing is monitored, and icing thickness data are uploaded to a central control system and secondary early warning is carried out.
Wherein, as shown in fig. 3, utilize the transport rod to erect the millimeter wave radar at the roadside, adopt the millimeter wave radar to carry out real-time icing monitoring time to the road surface: the radar transmits a high-frequency millimeter wave signal, and the echo is subjected to signal processing; judging the icing condition and the icing thickness based on the difference of the echoes of the ground, ice or water objects; and if icing is monitored, uploading data in real time and giving an early warning.
The current road surface can be determined to be the frozen ground, the watery ground, the frozen ground and the frozen thickness according to the echo waveform and the wave value.
As shown in fig. 4, in order to more accurately obtain the icing thickness data, when the icing frequency generation section adopts active infrared ice monitoring: the infrared laser is directly irradiated on the icing surface of the object, the energy of the laser reflected by the icing surface of the object is received through the photoelectric detector, the reflection coefficients of the icing surface under different incident angles and observation angles are obtained through calculation, and the icing condition of the surface of the object is deduced according to the icing coefficient. The method can detect the icing condition of a fixed area, and has higher precision compared with a radar detection method, but is greatly influenced by the environment and has higher manufacturing cost.
The current road surface can be determined to be the frozen ground, the watery ground, the frozen ground and the frozen thickness according to the reflection coefficient.
As an optimization scheme 3 of the embodiment, a real-time display screen is installed on a section where icing frequently occurs, the display screen is connected to a central control system, when the section sends out secondary early warning, the icing condition of the road surface is displayed in real time, and the driver driving on the section is informed through real-time early warning.
The foregoing shows and describes the general principles and features of the present invention, together with the advantages thereof. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.

Claims (7)

1. A real-time prediction method for an icing state of a highway pavement is characterized by comprising the following steps:
arranging temperature, wind speed, rainfall and traffic flow integrated sensors at intervals on a highway, transmitting data to an icing prediction model in real time, calculating icing probability, and uploading the icing probability to a central control system and carrying out early warning when the icing probability is greater than a set value;
and arranging ice measuring instruments on the highway at intervals, sending a command to the ice measuring instruments on the corresponding road sections by the central control system after the primary early warning is started, monitoring the primary early warning area in time, and uploading icing thickness data to the central control system and carrying out secondary early warning once icing is monitored.
2. The method for predicting the icing condition of the expressway according to claim 1, wherein the temperature, the wind speed, the rainfall and the traffic flow of the road surface are taken as sample data of the icing on the road surface, big data analysis is performed on influence factors of the icing on the road surface based on historical data of the icing on the road surface and collected real-time data, supervised learning is performed on different environments, and an icing prediction model is established.
3. The method for predicting the icing condition of the expressway pavement in real time according to claim 2, wherein a calculation model is built in the icing prediction model, and the icing probability at the current moment t is calculated as follows:
Figure FDA0003650243170000011
wherein TE t Is the temperature value, S t Is the wind speed value, R t Is the amount of rainfall, TR t Is the traffic flow, omega 1 、ω 2 、ω 3 And omega 4 The weight coefficients corresponding to the temperature, the wind speed, the rainfall and the traffic flow are obtained by sample data training.
4. The method for predicting the icing state of the highway pavement in real time according to claim 1, wherein radar ice measuring instruments are arranged on the highway at intervals, when primary early warning is started, the central control system sends a command to the radar ice measuring instruments on corresponding road sections to monitor a primary early warning area in time, and once icing is monitored, icing thickness data are uploaded to the central control system and secondary early warning is carried out;
and an active infrared ice monitor is installed at the icing frequency generation road section, a primary early warning result is monitored more accurately, icing is monitored, and icing thickness data are uploaded to a central control system and secondary early warning is carried out.
5. The method for predicting the icing condition of the highway pavement in real time according to claim 4, wherein when the millimeter wave radar is adopted to monitor the pavement in real time, the method comprises the following steps: the radar transmits a high-frequency millimeter wave signal, and the echo is subjected to signal processing; judging the icing condition and the icing thickness based on the difference of the echoes of the ground, ice or water objects; and if icing is monitored, uploading data in real time and giving an early warning.
6. The method for predicting the icing state of the highway pavement in real time according to claim 4, wherein when the icing frequent section adopts active infrared ice monitoring:
the infrared laser is directly irradiated on the icing surface of the object, the energy of the laser reflected by the icing surface of the object is received through the photoelectric detector, the reflection coefficients of the icing surface under different incident angles and observation angles are obtained through calculation, and the icing condition of the surface of the object is deduced according to the icing coefficient.
7. The method for predicting the icing state of the expressway road in real time as claimed in claim 4 or 6, wherein a real-time display screen is installed on a section with frequent icing, the display screen is connected to a central control system, when a secondary early warning is sent out on the section, the icing state of the expressway road is displayed in real time, and the driver driving on the section is informed of the real-time early warning.
CN202210539941.7A 2022-05-18 2022-05-18 Real-time prediction method for icing state of highway pavement Withdrawn CN114999113A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116052371A (en) * 2023-01-03 2023-05-02 广州市市政工程试验检测有限公司 Inhaul cable ice falling risk monitoring and early warning method and system
CN116740935A (en) * 2023-06-26 2023-09-12 河北高速公路集团有限公司 Expressway environment prediction method, device, equipment and storage medium

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116052371A (en) * 2023-01-03 2023-05-02 广州市市政工程试验检测有限公司 Inhaul cable ice falling risk monitoring and early warning method and system
CN116740935A (en) * 2023-06-26 2023-09-12 河北高速公路集团有限公司 Expressway environment prediction method, device, equipment and storage medium
CN116740935B (en) * 2023-06-26 2024-04-30 河北高速公路集团有限公司 Expressway environment prediction method, device, equipment and storage medium

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