Collision alarm system for highway guardrail plate

Abstract

The invention relates to the technical field of highway guardrail plate on-line monitoring, in particular to a highway guardrail plate collision alarm system, which comprises a collision data acquisition module which is mounted on a highway guardrail plate based on an acceleration sensor, acquires real-time acceleration data during collision, measures an acceleration value at the moment of collision, and transmits the acceleration value to the highway guardrail plate; and recording acceleration values along a plurality of axial directions, capturing acceleration components in X, Y and Z directions, calculating the product of the acceleration values and the mass of the guardrail plate to obtain collision force, accumulating the measured collision force, and generating the collision level of the guardrail plate. According to the invention, the dynamic adjustment of the volume and the flicker frequency enhances the adaptability of the alarm, and the alarm can keep sufficient visibility and audibility in a high-noise or low-light environment. By means of the self-learning ability of historical data, the self reaction mechanism can be optimized, it is ensured that accurate safety response is provided in a constantly changing environment, and therefore the overall driving safety is improved.

Description

Technical Field

[0001] The invention relates to the technical field of online monitoring of highway guardrails, and in particular to a collision alarm system for highway guardrails. Background Art

[0002] The collision alarm system of highway guardrail is to monitor the situation of highway guardrail in real time when a collision occurs. By installing sensors on the guardrail, it can detect the collision event and issue an alarm immediately to ensure the driving safety of the highway.

[0003] However, the existing technology lacks detailed analysis of the event level in handling collision events, which makes it difficult for the alarm response to match the severity of the accident. The alarm signal often fails to reflect the actual situation of the collision, which makes the driver pay less attention to the alarm and may delay the opportunity to take effective measures. The fixed setting of environmental factors also limits the effectiveness of the alarm. In noisy or low-light environments, the recognizability of the alarm signal decreases, increasing the risk of accidents. Summary of the invention

[0004] The purpose of the present invention is to solve the shortcomings in the prior art and to propose a collision warning system for highway guardrails.

[0005] In order to achieve the above-mentioned purpose, the present invention adopts the following technical scheme: A collision warning system for a highway guardrail comprises: The collision data acquisition module is based on an acceleration sensor installed on the guardrail of a highway. It collects real-time acceleration data during a collision, measures the acceleration value at the moment of collision, records the acceleration values ​​along multiple axes, captures the acceleration components in the X, Y and Z directions, calculates the product of the acceleration value and the mass of the guardrail to obtain the collision force, accumulates the measured collision force, and generates the guardrail collision level; The collision frequency analysis module records the timestamp of the collision event based on the guardrail collision level. When the collision level exceeds the threshold, the time is recorded, and the time interval between adjacent collisions is calculated. The time difference is obtained by subtracting the timestamp of the previous collision. The number of collisions and the accumulated collision events within the set time window are counted. The total number of collisions is calculated and divided by the length of the time window to obtain the collision frequency, and the guardrail collision frequency is obtained. A multi-level alarm generation module, based on the guardrail collision level and guardrail collision frequency, compares the collision level and frequency with a preset threshold, checks whether the value exceeds the threshold, matches the collision level and frequency combination to assign an alarm level, retrieves the settings for each alarm level to select the sound intensity and flashing frequency, and generates an alarm signal; The environmental adaptation adjustment module adjusts the volume of the alarm signal according to the environmental noise level and lighting conditions measured by the noise sensor and the light sensor. If the environmental noise is higher than the sound intensity, the sound intensity is increased. The flashing mode is also modified. High-frequency flashing is selected when the light is bright, and low-frequency flashing is selected when the light is dim. The self-learning mechanism module stores the collision events and the corresponding guardrail collision levels and guardrail collision frequencies in the database based on past collision data, compares the current collision data with the past data, uses statistical analysis methods to calculate the differences, adjusts the alarm threshold, updates the response parameters, and modifies the response strategy.

[0006] As a further solution of the present invention, the high-frequency flicker is four times per second, and the low-frequency flicker is two times per second.

[0007] As a further solution of the present invention, the collision data acquisition module includes: The real-time acceleration acquisition submodule is based on an acceleration sensor installed on the guardrail of a highway. The sensor detects the vibration of the guardrail, captures the acceleration change during a collision in real time, converts the analog signal into a digital signal, and performs sampling to generate real-time acceleration data. The multi-axis acceleration recording submodule extracts the acceleration value of each axis based on the real-time acceleration data, separates the acceleration components in the X, Y and Z directions, stores the data in each direction, and obtains the multi-axis acceleration components; The collision force calculation submodule, based on the multi-axis acceleration components, multiplies the acceleration in each direction by the guardrail mass, calculates the collision force in each direction, synthesizes the total collision force, accumulates the measured total collision force, and generates the guardrail collision level.

[0008] As a further solution of the present invention, the collision frequency analysis module includes: The collision event recording submodule is based on the guardrail collision level. When the collision level exceeds the threshold, the current time is recorded as the timestamp, and the timestamp is stored in the event log to generate a collision time series. The time interval calculation submodule calculates the difference between adjacent timestamps based on the collision time sequence, subtracts the previous time from the latter time, and obtains the time interval of each collision to form a collision time interval sequence; The collision frequency calculation submodule counts the number of collisions within a set time window based on the collision time interval sequence, divides the total number of collisions by the length of the time window, calculates the collision frequency, and obtains the guardrail collision frequency.

[0009] As a further solution of the present invention, the multi-level alarm generation module includes: The threshold comparison submodule compares the collision level with the preset level threshold based on the guardrail collision level and the guardrail collision frequency to check whether it exceeds the threshold, and compares the collision frequency with the preset frequency threshold to obtain the threshold comparison result; The alarm level assignment submodule matches the combination of collision level and frequency based on the threshold comparison result, searches for the corresponding alarm level, assigns the alarm level, and obtains the alarm level; The alarm signal generation submodule retrieves the preset alarm parameters based on the alarm level, selects the corresponding sound intensity and flashing frequency, and combines them into an alarm signal.

[0010] As a further solution of the present invention, the environmental adaptation adjustment module includes: The environmental parameter measurement submodule measures the environmental noise level and light intensity based on the noise sensor and light sensor, digitizes the measured values, and records the environmental parameters; The alarm signal adjustment submodule compares the ambient noise with the alarm volume based on the alarm signal and environmental parameters. If the ambient noise is higher than the alarm volume, the volume is increased; if it is lower, the volume is maintained or reduced. The flashing mode is then adjusted according to the light intensity, with high-frequency flashing set when the light is bright and low-frequency flashing set when the light is dim.

[0011] As a further solution of the present invention, the self-learning mechanism module includes: The historical data storage submodule stores the guardrail collision level and guardrail collision frequency of each collision and the timestamp into the database according to the past collision data to form a historical collision data set.

[0012] As a further solution of the present invention, it also includes: The difference analysis submodule compares the current collision data with the historical collision data set, uses statistical analysis methods to calculate the differences, adjusts the alarm threshold, updates the response parameters, and modifies the response strategy.

[0013] As a further embodiment of the present invention, the statistical analysis method is according to the formula: Calculating alert thresholds ;in, is the new alarm threshold, is the average value of historical collision levels, is the standard deviation of historical collision levels, is the current collision level, is the current collision frequency, is the historical collision frequency, , is the adjustment factor.

[0014] Compared with the prior art, the advantages and positive effects of the present invention are: In the present invention, by conducting in-depth analysis of collision events, it is possible to effectively identify collisions of different levels, record timestamps, and calculate the time intervals between adjacent events. This meticulous time management improves the control of collision frequency, allowing potential risks to be captured at an early stage. In addition, the dynamic adjustment of volume and flashing frequency enhances the adaptability of the alarm, and the alarm can maintain sufficient visibility and audibility in high-noise or low-light environments. With the self-learning ability of historical data, the response mechanism can be optimized to ensure accurate safety responses in a changing environment, thereby improving overall driving safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0016] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0017] See also Figure 1 The present invention provides a technical solution: a collision warning system for a highway guardrail comprises: The collision data acquisition module is based on an acceleration sensor installed on the guardrail of a highway. It collects real-time acceleration data during a collision, measures the acceleration value at the moment of collision, records the acceleration values ​​along multiple axes, captures the acceleration components in the X, Y and Z directions, calculates the product of the acceleration value and the mass of the guardrail to obtain the collision force, accumulates the measured collision force, and generates the guardrail collision level; The collision frequency analysis module records the timestamp of the collision event based on the guardrail collision level. When the collision level exceeds the threshold, the time is recorded, and the time interval between adjacent collisions is calculated. The time difference is obtained by subtracting the timestamp of the previous collision. The number of collisions and the accumulated collision events within the set time window are counted. The total number of collisions is calculated and divided by the length of the time window to obtain the collision frequency, and the guardrail collision frequency is obtained. A multi-level alarm generation module, based on the guardrail collision level and guardrail collision frequency, compares the collision level and frequency with a preset threshold, checks whether the value exceeds the threshold, matches the collision level and frequency combination to assign an alarm level, retrieves the settings for each alarm level to select the sound intensity and flashing frequency, and generates an alarm signal; The environmental adaptation adjustment module adjusts the volume of the alarm signal according to the environmental noise level and lighting conditions measured by the noise sensor and the light sensor. If the environmental noise is higher than the sound intensity, the sound intensity is increased. The flashing mode is also modified. When the light is bright, high-frequency flashing is selected. When the light is dim, low-frequency flashing is selected. The high-frequency flashing is four times per second, and the low-frequency flashing is two times per second. The self-learning mechanism module stores the collision events and the corresponding guardrail collision levels and guardrail collision frequencies in the database based on past collision data, compares the current collision data with the past data, uses statistical analysis methods to calculate the differences, adjusts the alarm threshold, updates the response parameters, and modifies the response strategy.

[0018] In this embodiment, the collision data collection module includes: The real-time acceleration acquisition submodule is based on an acceleration sensor installed on the guardrail of a highway. The sensor detects the vibration of the guardrail, captures the acceleration change during a collision in real time, converts the analog signal into a digital signal, and performs sampling to generate real-time acceleration data. The multi-axis acceleration recording submodule extracts the acceleration value of each axis based on the real-time acceleration data, separates the acceleration components in the X, Y and Z directions, stores the data in each direction, and obtains the multi-axis acceleration components; The collision force calculation submodule, based on the multi-axis acceleration components, multiplies the acceleration in each direction by the guardrail mass, calculates the collision force in each direction, synthesizes the total collision force, accumulates the measured total collision force, and generates the guardrail collision level.

[0019] Acceleration sensors are installed on highway guardrails to detect the vibration of the guardrails and capture the acceleration changes during collisions in real time. The analog signals are converted into digital signals and sampled to generate real-time acceleration data. This data can be used to analyze the specific characteristics of the impact on the guardrails in specific collision events. The analysis results help optimize the guardrail design to improve its ability to absorb and resist impacts.

[0020] Based on real-time acceleration data, the acceleration value of each axis is extracted, the acceleration components in the X, Y and Z directions are separated, and the data in each direction are stored to obtain multi-axis acceleration components. This data processing method allows researchers to understand in detail the changes in force in different directions during the collision process, which is crucial for analyzing the response behavior of the structure under impact at different angles.

[0021] In the above content, based on the multi-axis acceleration components, the acceleration in each direction is multiplied by the mass of the guardrail, according to the formula , calculate the collision force in each direction. Where, Represents the quality of the guardrail, Represents acceleration.

[0022] Detailed explanation of the formula and the process of formula calculation and derivation: Taking into account the quality of the actual guardrail It may be determined by its material and design, e.g. , and in an actual collision event, the acceleration in the X direction obtained by the sensor for , then the collision force Can be Similarly, if the accelerations in the Y and Z directions are and , then the corresponding collision force is and The total collision force can be calculated by vector sum, that is, .

[0023] This calculation method can provide a quantitative analysis of the forces in all directions during a collision.

[0024] In this embodiment, the collision frequency analysis module includes: The collision event recording submodule is based on the guardrail collision level. When the collision level exceeds the threshold, the current time is recorded as the timestamp, and the timestamp is stored in the event log to generate a collision time series. The time interval calculation submodule calculates the difference between adjacent timestamps based on the collision time sequence, subtracts the previous time from the latter time, and obtains the time interval of each collision to form a collision time interval sequence; The collision frequency calculation submodule counts the number of collisions within a set time window based on the collision time interval sequence, divides the total number of collisions by the length of the time window, calculates the collision frequency, and obtains the guardrail collision frequency.

[0025] In the safety monitoring system of highway guardrails, the collision event recording submodule plays a vital role. This module is responsible for automatically recording the specific time point of the current collision based on whether the guardrail collision level exceeds the set safety threshold when a collision occurs, and storing this time information as a timestamp in the event log. This operation ensures the accurate time recording of the event, which is helpful for subsequent accident analysis and data backtracking, and ensures that every collision data is accurately recorded and saved.

[0026] In the above content, based on the collision time series, the difference between adjacent timestamps is calculated according to the formula: , calculate the time interval between each collision. In the formula, Representative The timestamp of the collision, Representative The timestamp of the collision.

[0027] Detailed explanation of the formula and the process of formula calculation and derivation: For example, in one monitoring cycle, a guardrail panel is and The collision occurs at the moment, according to the formula The available time interval is 15 minutes. This calculation method allows system administrators to evaluate the frequency of collisions and their time distribution, thereby conducting further data analysis and optimizing resource allocation.

[0028] The collision frequency calculation submodule converts time interval data into more operationally meaningful collision frequency information. Within a preset time window, such as an hour or a day, the number of collisions occurring within the time range is counted and the number is divided by the length of the time window. The calculated collision frequency can intuitively represent the safety status of the guardrail within a certain time range, providing important data support for traffic management departments, helping them to evaluate and adjust traffic operations and safety measures to reduce accident rates and improve road safety.

[0029] In this embodiment, the multi-level alarm generation module includes: The threshold comparison submodule compares the collision level with the preset level threshold based on the guardrail collision level and the guardrail collision frequency to check whether it exceeds the threshold, and compares the collision frequency with the preset frequency threshold to obtain the threshold comparison result; The alarm level assignment submodule matches the combination of collision level and frequency based on the threshold comparison result, searches for the corresponding alarm level, assigns the alarm level, and obtains the alarm level; The alarm signal generation submodule retrieves the preset alarm parameters based on the alarm level, selects the corresponding sound intensity and flashing frequency, and combines them into an alarm signal.

[0030] In the above content, the collision level is compared with the preset level threshold, according to the formula , check whether it exceeds the threshold. In the formula, Represents the current collision level, Represents the preset level threshold.

[0031] If a guardrail panel has a collision level is 3, and the preset level threshold is 2, according to the formula ,Right now , a true result indicates that the collision level exceeds a preset threshold. This calculation indicates that a specific response is required, such as escalating the alert status or conducting a scene inspection, to ensure road safety.

[0032] Based on the threshold comparison results, this module matches the combination of collision level and frequency, finds the corresponding alarm level, and assigns this alarm level. In this way, the system can adjust the response strategy according to the actual severity and frequency of the collision, which helps to improve the response efficiency and accuracy of the alarm system and ensure that the appropriate level of alarm is issued when necessary, thereby improving road safety.

[0033] The alarm signal generation submodule is responsible for retrieving preset alarm parameters based on the alarm level, selecting the corresponding sound intensity and flashing frequency, and combining them into the final alarm signal. This process ensures that each alarm can notify road users and managers in an appropriate manner, effectively convey alarm information and enhance the prominence of the alarm through a combination of sound and visual signals, prompting relevant personnel to take necessary safety measures.

[0034] In this embodiment, the environment adaptation adjustment module includes: The environmental parameter measurement submodule measures the environmental noise level and light intensity based on the noise sensor and light sensor, digitizes the measured values, and records the environmental parameters; The alarm signal adjustment submodule compares the ambient noise with the alarm volume based on the alarm signal and environmental parameters. If the ambient noise is higher than the alarm volume, the volume is increased; if it is lower, the volume is maintained or reduced. The flashing mode is then adjusted according to the light intensity, with high-frequency flashing set when the light is bright and low-frequency flashing set when the light is dim.

[0035] The environmental parameter measurement submodule uses noise sensors and light sensors to measure the noise level and light intensity in the environment. This process converts real-time environmental data into digital information through sensors for subsequent processing and analysis. The precise measurement of this module provides basic environmental data for the alarm system, ensuring that the alarm signal can be appropriately adjusted according to different environmental conditions to achieve the best alarm effect.

[0036] In the above content, the ambient noise is compared with the alarm volume, according to the formula , if the ambient noise is higher than the alarm volume, increase the volume. Represents the adjusted alarm volume, represents the ambient noise level, Represents the original alarm volume, Indicates the volume adjustment amount.

[0037] Detailed explanation of the formula and the process of formula calculation and derivation: For example, the ambient noise level The original alarm volume is 80dB The preset volume adjustment is 70dB. is 15dB. According to the formula , calculated This calculation shows that in order to rise above the ambient noise and ensure the effectiveness of the alarm, the alarm volume needs to be adjusted to 85dB.

[0038] The alarm signal generation submodule selects the appropriate sound intensity and flashing frequency according to the light intensity and alarm level, and combines them into the final alarm signal. This operation ensures that the alarm signal can be effectively conveyed under different lighting conditions. For example, high-frequency flashing is set in bright light to highlight the visibility of the alarm, while low-frequency flashing is used in dim environments to avoid excessive stimulation while maintaining the effectiveness of the alarm.

[0039] In this embodiment, the self-learning mechanism module includes: The historical data storage submodule stores the guardrail collision level and guardrail collision frequency of each collision and the timestamp into the database according to the past collision data to form a historical collision data set.

[0040] The historical data storage submodule focuses on collecting detailed data of each collision, including guardrail collision level, guardrail collision frequency, and timestamp of the collision. These data are effectively stored in the database to form a historical collision dataset, which provides basic data for future analysis and decision-making, ensuring the integrity and traceability of the data.

[0041] The difference analysis submodule compares the current collision data with the historical collision data set, uses statistical analysis methods to calculate the differences, adjusts the alarm threshold, updates the response parameters, and modifies the response strategy.

[0042] In this embodiment, the statistical analysis method is based on the formula: Calculating alert thresholds ;in, is the new alarm threshold, is the average value of historical collision levels, is the standard deviation of historical collision levels, is the current collision level, is the current collision frequency, is the historical collision frequency, , is the adjustment factor.

[0043] First, calculate the average of the historical collision levels , accumulate the historical collision level data and divide it by the number of data; then, calculate the standard deviation of the historical collision level , calculate the sum of the squares of the difference between each data and the average value, divide it by the number of data and take the square root; then calculate the absolute value of the difference between the current collision level and the historical average value, take the square root and multiply it by the weight coefficient ; Then, calculate the relative change between the current and historical collision frequencies , multiplied by the adjustment factor ; Finally, substitute the above results into the formula to calculate the new alarm threshold .

[0044] The relative change between the current and historical collision frequencies is added to reflect the trend change of the collision frequency, improve the dynamic adjustment capability of the alarm threshold, and make the response to abnormal situations more timely and accurate.

[0045] Calculate the average of historical collision levels : Collect historical collision level data, for example: [2.0, 2.5, 3.0, 2.8, 2.2, 2.7, 3.1, 2.9, 2.6, 2.4], substitute it into the formula to calculate :

[0046] Calculate the standard deviation of historical collision levels :

[0047] Calculate each : (2.0-2.62)²=0.3844; (2.5-2.62)²=0.0144; (3.0-2.62)²=0.1444; (2.8-2.62)²=0.0324; (2.2-2.62)²=0.1764; (2.7-2.62)²=0.0064; (3.1-2.62)²=0.2304; (2.9-2.62)²=0.0784; (2.6-2.62)²=0.0004; (2.4-2.62)²=0.0484; sum: .

[0048] so:

[0049] Determine the adjustment factor: :According to the system's requirements for standard deviation sensitivity, set ; Substituting the values:

[0050] : Calculated using the maximum absolute deviation of historical data, ; Maximum absolute deviation: .

[0051] so: .

[0052] :Based on the historical collision frequency, set ; Historical collision frequency times / hour; so: ; Get the current data: Current collision level (obtained through real-time monitoring by sensors) Current collision frequency Times / hour (calculated within the set time window) Calculate the parameters: calculate :

[0053] calculate :

[0054] calculate:

[0055]

[0056] Calculate new alert thresholds : Substitute the above calculation results into: The new alert threshold is 5.8837, reflecting the current increase in collision levels and frequency.

Claims

1. A collision warning system for a highway guardrail, characterized in that: The system comprises: The collision data acquisition module is based on an acceleration sensor installed on the guardrail of a highway. It collects real-time acceleration data during a collision, measures the acceleration value at the moment of collision, records the acceleration values ​​along multiple axes, captures the acceleration components in the X, Y and Z directions, calculates the product of the acceleration value and the mass of the guardrail to obtain the collision force, accumulates the measured collision force, and generates the guardrail collision level; The collision frequency analysis module records the timestamp of the collision event based on the guardrail collision level. When the collision level exceeds the threshold, the time is recorded, and the time interval between adjacent collisions is calculated. The time difference is obtained by subtracting the timestamp of the previous collision. The number of collisions and the accumulated collision events within the set time window are counted. The total number of collisions is calculated and divided by the length of the time window to obtain the collision frequency, and the guardrail collision frequency is obtained. A multi-level alarm generation module, based on the guardrail collision level and guardrail collision frequency, compares the collision level and frequency with a preset threshold, checks whether the value exceeds the threshold, matches the collision level and frequency combination to assign an alarm level, retrieves the settings for each alarm level to select the sound intensity and flashing frequency, and generates an alarm signal; The environmental adaptation adjustment module adjusts the volume of the alarm signal according to the environmental noise level and lighting conditions measured by the noise sensor and the light sensor. If the environmental noise is higher than the sound intensity, the sound intensity is increased. The flashing mode is also modified. High-frequency flashing is selected when the light is bright, and low-frequency flashing is selected when the light is dim. The self-learning mechanism module stores the collision events and the corresponding guardrail collision levels and guardrail collision frequencies in the database based on past collision data, compares the current collision data with the past data, uses statistical analysis methods to calculate the differences, adjusts the alarm threshold, updates the response parameters, and modifies the response strategy.

2. The collision warning system for highway guardrail according to claim 1 is characterized in that: The high-frequency flicker is four times per second, and the low-frequency flicker is two times per second.

3. The collision warning system for highway guardrail according to claim 1 is characterized in that: The collision data acquisition module comprises: The real-time acceleration acquisition submodule is based on an acceleration sensor installed on the guardrail of a highway. The sensor detects the vibration of the guardrail, captures the acceleration change during a collision in real time, converts the analog signal into a digital signal, and performs sampling to generate real-time acceleration data. The multi-axis acceleration recording submodule extracts the acceleration value of each axis based on the real-time acceleration data, separates the acceleration components in the X, Y and Z directions, stores the data in each direction, and obtains the multi-axis acceleration components; The collision force calculation submodule, based on the multi-axis acceleration components, multiplies the acceleration in each direction by the guardrail mass, calculates the collision force in each direction, synthesizes the total collision force, accumulates the measured total collision force, and generates the guardrail collision level.

4. The collision warning system for highway guardrail according to claim 1 is characterized in that: The collision frequency analysis module includes: The collision event recording submodule is based on the guardrail collision level. When the collision level exceeds the threshold, the current time is recorded as the timestamp, and the timestamp is stored in the event log to generate a collision time series. The time interval calculation submodule calculates the difference between adjacent timestamps based on the collision time sequence, subtracts the previous time from the latter time, and obtains the time interval of each collision to form a collision time interval sequence; The collision frequency calculation submodule counts the number of collisions within a set time window based on the collision time interval sequence, divides the total number of collisions by the length of the time window, calculates the collision frequency, and obtains the guardrail collision frequency.

5. The collision warning system for highway guardrail according to claim 1 is characterized in that: The multi-level alarm generation module comprises: The threshold comparison submodule compares the collision level with the preset level threshold based on the guardrail collision level and the guardrail collision frequency to check whether it exceeds the threshold, and compares the collision frequency with the preset frequency threshold to obtain the threshold comparison result; The alarm level assignment submodule matches the combination of collision level and frequency based on the threshold comparison result, searches for the corresponding alarm level, assigns the alarm level, and obtains the alarm level; The alarm signal generation submodule retrieves the preset alarm parameters based on the alarm level, selects the corresponding sound intensity and flashing frequency, and combines them into an alarm signal.

6. The collision warning system for highway guardrail according to claim 1, characterized in that: The environmental adaptation adjustment module includes: The environmental parameter measurement submodule measures the environmental noise level and light intensity based on the noise sensor and light sensor, digitizes the measured values, and records the environmental parameters; The alarm signal adjustment submodule compares the ambient noise with the alarm volume based on the alarm signal and environmental parameters. If the ambient noise is higher than the alarm volume, the volume is increased; if it is lower, the volume is maintained or reduced. The flashing mode is then adjusted according to the light intensity, with high-frequency flashing set when the light is bright and low-frequency flashing set when the light is dim.

7. The collision warning system for highway guardrail according to claim 1, characterized in that: The self-learning mechanism module includes: The historical data storage submodule stores the guardrail collision level and guardrail collision frequency of each collision and the timestamp into the database according to the past collision data to form a historical collision data set.

8. The collision warning system for highway guardrail according to claim 7 is characterized in that: Also includes: The difference analysis submodule compares the current collision data with the historical collision data set, uses statistical analysis methods to calculate the differences, adjusts the alarm threshold, updates the response parameters, and modifies the response strategy.

9. The collision warning system for highway guardrail according to claim 8, characterized in that: The statistical analysis method is according to the formula: Calculating alert thresholds ;in, is the new alarm threshold, is the average value of historical collision levels, is the standard deviation of historical collision levels, is the current collision level, is the current collision frequency, is the historical collision frequency, , is the adjustment factor.

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