Trailer posture detection method and system

Abstract

The present invention relates to the technical field of vehicle posture detection, and specifically to a trailer posture detection method and system, comprising: using a sensor to monitor the posture parameters of a trailer in real time, wherein the posture parameters include angular velocity, acceleration and vertical height; classifying the road surface state according to the historical vertical height data of the left and right sides of the trailer; confirming the current road surface state according to the vertical height data collected in real time; calculating the recommended steering speed and maximum steering angle according to the angular velocity, acceleration and load of the trailer under the current road surface state; and issuing an alarm when the steering speed and the maximum steering angle exceed a preset value. Thus, the trailer posture detection system can provide real-time and accurate data support for drivers, helping them to better control the trailer under complex road conditions and reduce the risk of traffic accidents.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle posture detection, and in particular to a trailer posture detection method and system. Background Art

[0002] The risk of trailer rollover mainly refers to the risk of overturning caused by the trailer tilting laterally and exceeding its stability limit during transportation due to reasons such as excessive turning speed, improper cargo loading, poor road conditions, insufficient vehicle stability or unexpected situations. This phenomenon will not only seriously damage the cargo and vehicle, but may also endanger the safety of the driver and other road users, causing traffic jams and significant economic losses.

[0003] The existing trailer rollover prevention method mainly relies on the driver's own judgment, which is too subjective and has low reliability. Summary of the invention

[0004] The purpose of the present invention is to provide a trailer posture detection method and system, which aims to detect the running posture of the trailer and give driving suggestions, so as to provide real-time and accurate data support for drivers, help them better control the trailer under complex road conditions and reduce the risk of traffic accidents.

[0005] To achieve the above-mentioned object, in a first aspect, the present invention provides a method for detecting the posture of a trailer, comprising using a sensor to monitor the posture parameters of the trailer in real time, wherein the posture parameters include angular velocity, acceleration and vertical height;

[0006] The road surface conditions are classified based on the historical vertical height data of the left and right sides of the trailer;

[0007] Confirm the current road surface status based on the vertical height data collected in real time;

[0008] Calculate the recommended steering speed and maximum steering angle based on the trailer's angular velocity, acceleration and load under the current road conditions;

[0009] An alarm will be issued when the steering speed and maximum steering angle exceed the preset values.

[0010] The specific steps of using sensors to monitor the posture parameters of the trailer in real time include:

[0011] Select the corresponding sensor group according to monitoring requirements;

[0012] Fix the sensor group at the corresponding position of the trailer according to the design layout;

[0013] Wirelessly connect all sensors to the central processing unit and calibrate the sensors;

[0014] A sensor group is used to collect the posture parameters of the trailer.

[0015] The specific steps of classifying the road surface conditions according to the historical vertical height data of the left and right sides of the trailer include:

[0016] The historical vertical height data is annotated with road surface labels, wherein the road surface labels include flatness, potholes, and slopes;

[0017] Extracting classification features from the annotated historical vertical height data, wherein the classification features include the difference between the heights of the left and right sides, the average height, the standard deviation, and the skewness;

[0018] Divide the labeled data set into a training set and a validation set;

[0019] The linear support vector machine model is trained using the training set to obtain a road surface judgment model.

[0020] The specific steps of confirming the current road surface state according to the vertical height data collected in real time include:

[0021] Get the vertical height data collected by the sensor;

[0022] Preprocessing the vertical height data;

[0023] The road surface judgment model is applied to the real-time collected data to identify the current road surface status.

[0024] The specific steps of preprocessing the vertical height data include:

[0025] Check whether there are abnormal height values ​​in the vertical height data, and if so, delete the abnormal height values;

[0026] If there are missing values ​​in the vertical height data, they are filled using interpolation.

[0027] The specific steps of calculating the recommended steering speed and maximum steering angle according to the angular velocity, acceleration and load of the trailer under the current road condition include:

[0028] Set up a dynamic model based on the trailer's angular velocity, acceleration, load, and road conditions;

[0029] The dynamic model is used to calculate the speed at which the trailer can turn safely under the current road conditions;

[0030] The corresponding safe steering angle is calculated based on the safe steering speed.

[0031] The specific steps of setting the dynamic model according to the angular velocity, acceleration and load of the trailer and the road surface state include:

[0032] Define basic parameters and coordinate system;

[0033] Establish dynamic equations based on angular velocity, acceleration, load and road conditions;

[0034] The accelerations on the x- and y-axes are corrected by the rotational dynamics equations.

[0035] In a second aspect, the present invention further provides a trailer posture detection system, including a parameter acquisition module, a road surface classification module, a road surface detection module, a speed calculation module and an alarm module;

[0036] The parameter acquisition module is used to use sensors to monitor the posture parameters of the trailer in real time, and the posture parameters include angular velocity, acceleration and vertical height;

[0037] The road surface classification module is used to classify the road surface state according to the historical vertical height data of the left and right sides of the trailer;

[0038] The road surface detection module is used to confirm the current road surface state based on the vertical height data collected in real time;

[0039] The speed calculation module is used to calculate the recommended steering speed and maximum steering angle according to the angular velocity, acceleration and load of the trailer under the current road condition;

[0040] The alarm module is used to issue an alarm when the steering vehicle speed and the maximum steering angle exceed preset values.

[0041] A trailer posture detection method and system of the present invention uses a high-precision sensor to monitor the posture parameters of the trailer in real time. These posture parameters mainly include the angular velocity, acceleration and vertical height of the trailer. The angular velocity is used to measure the speed of the trailer rotating around its axis, the acceleration is used to measure the acceleration of the trailer, and the vertical height is used to monitor the change in the distance between the trailer and the ground. The historical vertical height data on the left and right sides of the trailer are collected and analyzed to classify the road surface conditions. Through this method, different road conditions can be identified, such as flat road surface, slope road surface or rugged road surface. According to the vertical height data collected in real time, the current road surface condition is further confirmed. Combining historical data and real-time data, the road condition can be judged more accurately and corresponding driving suggestions can be provided. On the basis of confirming the current road surface condition, the recommended steering speed and maximum steering angle are calculated according to the angular velocity, acceleration and load of the trailer. These parameters are crucial to ensure the safe driving of the trailer. The recommended steering speed can help the driver understand the maximum speed at which the trailer can be safely driven under the current road conditions. The maximum steering angle helps the driver avoid oversteering when turning, which causes the trailer to lose control. The steering speed and maximum steering angle are monitored in real time. Once their values ​​exceed the preset safety threshold, the system will immediately issue an alarm. In this way, the driver can take timely measures to ensure the safe driving of the trailer. In this way, the trailer posture detection system can provide drivers with real-time and accurate data support, helping them better control the trailer under complex road conditions and reduce the risk of traffic accidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0043] Figure 1 It is a flow chart of a trailer posture detection method according to the first embodiment of the present invention.

[0044] Figure 2 This is a flow chart of the first embodiment of the present invention for using sensors to monitor the posture parameters of a trailer in real time, wherein the posture parameters include angular velocity, acceleration and vertical height.

[0045] Figure 3 It is a flow chart of classifying the road surface conditions according to the historical vertical height data of the left and right sides of the trailer according to the first embodiment of the present invention.

[0046] Figure 4This is a flow chart of confirming the current road surface state based on vertical height data collected in real time according to the first embodiment of the present invention.

[0047] Figure 5 4 is a flowchart of preprocessing vertical height data according to the first embodiment of the present invention.

[0048] Figure 6 It is a flow chart of calculating the recommended steering speed and the maximum steering angle according to the angular velocity, acceleration and load of the trailer under the current road condition according to the first embodiment of the present invention.

[0049] Figure 7 It is a flow chart of setting a dynamic model according to the angular velocity, acceleration and load of the trailer and the road surface conditions in the first embodiment of the present invention. DETAILED DESCRIPTION

[0050] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0051] For the first embodiment, please refer to Figure 1 to Figure 7 The present invention provides a method for detecting a trailer posture, comprising:

[0052] S101 uses sensors to monitor the posture parameters of the trailer in real time, including angular velocity, acceleration and vertical height;

[0053] The specific steps include:

[0054] S201 selects a corresponding sensor group according to monitoring requirements;

[0055] Carefully select the appropriate sensor combination based on actual monitoring needs. This process involves evaluating the performance of different types of sensors (such as MEMS gyroscopes, accelerometers, and precision lidar or ultrasonic sensors) to ensure that the selected sensors can capture subtle changes in the trailer's posture and adapt to various complex road environments and weather conditions. For example, in areas with frequent rain or fog, the sensor's waterproof and dustproof level and anti-interference ability will become important considerations.

[0056] S202 fixes the sensor group to the corresponding position of the trailer according to the design layout;

[0057] The professional team will accurately install the selected sensor group to the predetermined position of the trailer according to the previous system design drawings. These positions usually include the front, middle and rear of the trailer, as well as the left and right bottoms of special concern, to fully cover the posture changes of the trailer. During the installation process, it is necessary to ensure that the sensor is both stable and does not hinder the normal operation of the trailer, while considering its durability and ease of maintenance.

[0058] S203 connects all sensors to the central processing unit wirelessly and calibrates the sensors;

[0059] All deployed sensors establish a stable data transmission link with the central processing unit (CPU) through a reliable wireless communication protocol (such as Wi-Fi, Bluetooth or LoRaWAN). This connection not only allows seamless transmission of real-time data streams, but also provides security for remote monitoring and fault diagnosis. After the connection is completed, a detailed sensor calibration is performed to ensure that the data output by all sensors is accurate and eliminate errors introduced by installation position, angle or individual differences.

[0060] S204 uses a sensor group to collect posture parameters of the trailer.

[0061] With the full activation of the sensor group, the posture parameters of the trailer begin to be collected in real time and continuously. These parameters include but are not limited to the angular velocity of the trailer around three axes, acceleration along three directions, and the vertical height change of the bottom of the trailer relative to the ground. These data not only provide real-time road condition feedback to the driving assistance system, but can also be used to analyze the dynamic balance state of the trailer, predict potential suspension system problems, and provide valuable information for subsequent road maintenance and traffic planning. Through continuous data collection and analysis, the entire system lays a solid foundation for improving transportation efficiency and safety.

[0062] S102 classifies the road surface conditions according to the historical vertical height data of the left and right sides of the trailer;

[0063] The specific steps include:

[0064] S301 annotates the historical vertical height data using road surface labels, where the road surface labels include flatness, potholes, and slopes;

[0065] This step requires professional knowledge or manual review. Based on the actual experience of the trailer driving or the subsequent road inspection report, each section of driving data is added with road label data, such as "flat", "potholes" or "slope". Such annotations provide target variables for subsequent machine learning models and are the basis for building effective models.

[0066] S302 extracts classification features from the annotated historical vertical height data, where the classification features include the difference between the heights of the left and right sides, the average height, the standard deviation, and the skewness;

[0067] Height difference between the left and right sides: intuitively reflects whether the road surface is flat.

[0068] Average height: can be used to identify the horizontal position of the entire road surface.

[0069] Standard Deviation: A measure of the differences between data points, which helps identify irregularities in the road surface.

[0070] Skewness: Assessing the asymmetry of data distribution helps identify road tilt or special morphology. By extracting these features, the system can describe different road conditions in a quantitative way.

[0071] S303 divides the labeled data set into a training set and a validation set;

[0072] In order to verify the effectiveness of the model and avoid overfitting, the original annotated data set is divided into two parts: training set and validation set. The training set is used for model learning and parameter adjustment, and the validation set is used to evaluate the performance of the model on unseen data. A reasonable data division ratio (such as 80% training and 20% validation) is the key to ensuring the generalization ability of the model.

[0073] S304 uses the training set to train the linear support vector machine model to obtain a road surface judgment model.

[0074] Support vector machines are a powerful supervised learning method that is particularly suitable for solving classification problems, especially when there are clear boundaries between data categories. By training the model using a training set, the system can learn the complex relationship between different features and road conditions, and ultimately output a judgment model that can predict road conditions based on new vertical height data. The training process involves tuning the model parameters to achieve the best classification effect.

[0075] S103 confirms the current road surface state according to the vertical height data collected in real time;

[0076] The specific steps include:

[0077] S401 obtains vertical height data collected by the sensor;

[0078] The vertical height data is received in real time from the sensors on the trailer through wireless communication technologies (such as Bluetooth, Wi-Fi or cellular networks). These data reflect the real-time relative height changes between the trailer and the ground during driving, which is the basic information for evaluating the road surface condition.

[0079] S402 pre-processes the vertical height data;

[0080] The specific steps include:

[0081] S501 checks whether there is an abnormal height value in the vertical height data, and if so, deletes the abnormal height value;

[0082] Statistical methods (such as Z-score or IQR) are used to identify and remove outliers in the data. Outliers are caused by sensor misreading, extreme road events or external interference, which distort the judgment of the model. Once the vertical height value outside the normal range is found, the system will automatically delete it to reduce the negative impact on the analysis results.

[0083] S502: If there are missing values ​​in the vertical height data, fill them using interpolation.

[0084] When faced with gaps or missing data, interpolation methods (such as linear interpolation, nearest neighbor interpolation, or time series prediction methods) are used to fill in the missing values. This not only maintains the continuity of the data, but also avoids the loss of information caused by directly ignoring the missing data.

[0085] S403 applies the road surface judgment model to the real-time collected data to identify the current road surface status.

[0086] After data preprocessing, the real-time data is input into the previously trained road surface judgment model. The model quickly classifies the current state of the road surface based on the characteristics of the real-time vertical height data (such as difference, average height, etc.) to facilitate subsequent speed control.

[0087] S104 calculates a recommended steering speed and a maximum steering angle according to the angular velocity, acceleration and load of the trailer under the current road condition;

[0088] The specific steps include:

[0089] S601 sets a dynamic model according to the angular velocity, acceleration and load of the trailer and the road surface condition;

[0090] The specific steps include:

[0091] S701 defines basic parameters and coordinate system;

[0092] The basic parameters of the trailer's dynamic model need to be clarified, including but not limited to mass, center of mass position, friction coefficient between tires and the ground, etc. At the same time, an appropriate coordinate system (usually a world coordinate system fixed to the ground or a body coordinate system that rotates with the vehicle body) is defined to accurately describe the displacement, velocity and acceleration of the trailer.

[0093] The mass of the trailer is m;

[0094] The load of the trailer M;

[0095] The mass of each wheel of the trailer is m w ;

[0096] The friction coefficient f between the road surface and the wheels;

[0097] Angular velocity of the trailer ω;

[0098] The acceleration of the trailer is a.

[0099] S702 establishes a dynamic equation based on angular velocity, acceleration, load and road surface conditions;

[0100] In the x-axis direction, the forces acting on the trailer include the friction force fm w g (downward) and the driving force (if any), where g is the acceleration due to gravity. Therefore, the dynamic equation is: ma = fm w gT, where T is the driving force on the trailer.

[0101] In the y-axis direction, the forces acting on the trailer are mainly gravity mg and road support force N. Therefore, the dynamic equation is: N=mg+Mg.

[0102] In the z-axis direction, the force on each wheel of the trailer is the same, mainly the component of the trailer's weight mg on the z-axis. Therefore, the dynamic equation is: m w g = Nz, where z is the height of the trailer relative to the road surface.

[0103] S703 corrects the acceleration on the x-axis and the y-axis by using the rotational dynamics equation.

[0104] The acceleration calculations on the x-axis (lateral) and y-axis (longitudinal) are corrected by rotating the dynamic equations to ensure that the model can accurately reflect the vehicle response to uneven road surfaces or specific conditions.

[0105] The specific implementation steps include:

[0106] Obtain the vehicle's initial state (speed, direction, suspension state, etc.) and road roughness data.

[0107] Suspension and tire forces are calculated based on the current vehicle state and road conditions.

[0108] The suspension force mainly depends on the displacement, velocity, stiffness and damping of the suspension system. The following are the calculation steps:

[0109] Determine the suspension displacement:

[0110] The relative motion between the wheels and the body of the vehicle determines the amount of compression (or extension) of the suspension.

[0111] s=s wheel -sbody Where s is the suspension displacement, s wheel is the wheel displacement, s body is the displacement of the vehicle body.

[0112] Calculate the suspension speed:

[0113] The suspension velocity is the time derivative of the suspension displacement, v s =ds / dt

[0114] Calculate the suspension force:

[0115] The suspension forces are calculated using the stiffness (k) and damping (c) coefficients of the suspension.

[0116] Fs=-k·sc·v s Where Fs is the suspension force, and the negative sign indicates that the direction of the force is always opposite to the direction of displacement.

[0117] Tire force calculations usually involve the longitudinal force, lateral force, and side force of the tire. The following are the calculation steps:

[0118] Determine the tire's slip rate and sideslip angle;

[0119] Slip ratio (λ): It is the ratio of the difference between the longitudinal speed of the tire and the rotational speed of the wheel to the rotational speed of the wheel.

[0120] Slip angle (α): It is the angle between the speed direction of the tire contact point and the longitudinal axis of the tire.

[0121] Using the tire model:

[0122] Select a tire model (such as MagicFormula, brush model, etc.) to describe the mechanical behavior of the tire.

[0123] Calculate the longitudinal force (Fx):

[0124] The longitudinal force is calculated based on the slip ratio and the tire model.

[0125] Fx=F(λ) where F(λ) is the relationship between longitudinal force and slip rate given by the tire model.

[0126] Calculate the lateral force (Fy):

[0127] Calculates lateral forces based on the slip angle and tire model.

[0128] Fy=F(α) where F(α) is the relationship between lateral force and sideslip angle given by the tire model.

[0129] Substituting the suspension and tire forces into the rotational dynamics equations, the acceleration and angular acceleration of the vehicle body are calculated.

[0130] Linear equations of motion:

[0131] Horizontal (x-axis):

[0132] Vertical (y-axis):

[0133] Angular motion equations:

[0134] Around the z axis (vehicle pitch):

[0135] Around the x-axis (vehicle yaw):

[0136] About the y-axis (vehicle roll):

[0137] Where m is the vehicle mass, and are the lateral and longitudinal accelerations, Fx and Fy are the corresponding forces, I is the moment of inertia, are the pitch, yaw and roll angular accelerations respectively, and M is the moment.

[0138] Update the vehicle's position, velocity, and orientation based on the calculated acceleration and angular acceleration.

[0139] S602 calculates, through a dynamics model, a speed at which the trailer can turn safely under current road conditions;

[0140] On the basis of establishing a sound dynamic model, the steering speed that the trailer can safely maintain under the current road conditions is calculated through numerical solution or simulation analysis. This step takes into account the physical limits of the vehicle, the stability requirements, and the grip limitations of the road surface to ensure that there will be no side slip or loss of control. Specifically, it includes setting initial conditions: such as initial speed, steering angle, etc. Assume that the road friction coefficient is 0.7 (dry asphalt road surface). Use the fourth-order Runge-Kutta method for numerical integration. Given different vehicle speeds, solve the vehicle motion equations through numerical integration.

[0141] S603 calculates a corresponding safe steering angle based on the safe steering vehicle speed.

[0142] Based on the calculated safe steering speed, the maximum steering angle that the trailer can safely perform is further determined. This calculation needs to take into account the direct impact of vehicle speed on vehicle handling stability, as well as factors such as the trailer's own size and wheelbase, to ensure that the vehicle can maintain sufficient lateral stability when turning at the recommended speed to avoid excessive yaw or overturning risks. Specifically, a series of different steering angles θi can be given, and the vehicle motion equation can be solved by numerical integration. For each steering angle θi, check whether it exceeds the lateral acceleration limit (for example, 0.4g). Find the maximum steering angle θmax that just meets the safety conditions.

[0143] S105 issues an alarm when the steering speed and the maximum steering angle exceed preset values.

[0144] The specific steps are as follows:

[0145] At this stage, the trailer's real-time driving data, especially speed, steering angle and acceleration, is continuously collected and transmitted to the central processing unit through the sensor network. The data is initially cleaned and formatted to ensure the accuracy and timeliness of the information.

[0146] After receiving the real-time data, the central processing unit immediately compares it with the previously calculated safe steering speed and maximum steering angle. This process involves complex algorithms that are used to calculate the vehicle's actual steering rate and angle in real time to ensure an accurate match with the preset safety values.

[0147] Once the system detects that the actual steering speed of the trailer exceeds the preset safety value, or the actual steering angle exceeds the calculated maximum safe steering angle, the risk assessment logic is immediately triggered. This logic not only considers the excess of a single parameter, but also comprehensively evaluates the impact of these two factors on vehicle stability and safety.

[0148] When the risk assessment confirms that there is a safety hazard, the system immediately triggers the alarm mechanism. The alarm can be an audible warning, issued through the speakers inside the vehicle; a visual warning, such as a flashing warning light on the dashboard; or even tactile feedback, such as the vibration of the steering wheel, to ensure that the driver can quickly pay attention. In addition, in an emergency, the system also sends an alarm message to the fleet manager or emergency service center through the on-board communication device so that further action can be taken.

[0149] Each time the alarm is triggered, the system will automatically record relevant driving data and alarm details, including time, location, vehicle speed, steering angle, etc.

[0150] In a second embodiment, the present invention further provides a trailer posture detection system, comprising a parameter acquisition module, a road surface classification module, a road surface detection module, a speed calculation module and an alarm module; the parameter acquisition module is used to use sensors to monitor the posture parameters of the trailer in real time, and the posture parameters include angular velocity, acceleration and vertical height; the road surface classification module is used to classify the road surface state according to the historical vertical height data on the left and right sides of the trailer; the road surface detection module is used to confirm the current road surface state according to the vertical height data collected in real time; the speed calculation module is used to calculate the recommended steering speed and maximum steering angle according to the angular velocity, acceleration and load of the trailer under the current road surface state; the alarm module is used to issue an alarm when the steering speed and the maximum steering angle exceed the preset values.

[0151] The parameter acquisition module uses sensor technology (such as gyroscopes, accelerometers and height sensors) to monitor the posture parameters of the trailer in real time. These parameters include the angular velocity of the trailer around three axes, the acceleration along three directions, and the real-time vertical height change of the bottom of the trailer relative to the ground. The high frequency and high precision of sensor data ensure the reliability and real-time nature of the monitoring data. The road classification module uses machine learning algorithms to conduct in-depth analysis of the vertical height data on the left and right sides, and then classify different types of road conditions. Through data annotation, feature extraction, model training and other steps, the system can identify various states of the road surface, such as flatness, potholes, and slopes, providing a basis for subsequent decision-making. The road detection module receives and processes the latest vertical height data from the sensor in real time, and combines historical data with real-time environmental information to accurately determine the road surface state where the trailer is currently located. Through data preprocessing, outlier removal and missing value filling, the accuracy of the current road condition judgment is ensured, providing the driver with instant road feedback. The speed calculation module uses a dynamic model to comprehensively consider the angular velocity, acceleration and actual load of the trailer to calculate the recommended safest steering speed and maximum safe steering angle. This calculation process is highly dependent on accurate physical models and real-time data processing capabilities, and is designed to help drivers make optimal driving decisions under various road conditions and reduce risks caused by improper operation. The alarm module is responsible for monitoring the actual driving parameters of the trailer. Once it detects that the steering speed or steering angle exceeds the pre-set safety threshold, it immediately warns the driver through sound, vision or touch, prompting the driver to adjust driving behavior in time to avoid potential dangerous situations. At the same time, the system records detailed information for each alarm to provide data support for subsequent driving behavior analysis and system optimization.

[0152] In summary, the trailer posture detection system provides all-round safety protection for the daily operation of trailers through integrated monitoring, analysis, calculation and early warning functions, and significantly improves the safety and efficiency of road transportation.

[0153] What is disclosed above is only a preferred embodiment of the present invention, and it certainly cannot be used to limit the scope of rights of the present invention. Ordinary technicians in this field can understand that all or part of the processes of the above embodiment and equivalent changes made according to the claims of the present invention still fall within the scope of the invention.

Claims

1. A trailer posture detection method, It is characterized in that The method comprises: using sensors to monitor the posture parameters of the trailer in real time, wherein the posture parameters include angular velocity, acceleration and vertical height; The road surface conditions are classified based on the historical vertical height data of the left and right sides of the trailer; Confirm the current road surface status based on the vertical height data collected in real time; Calculate the recommended steering speed and maximum steering angle based on the trailer's angular velocity, acceleration and load under the current road conditions; When the steering speed and maximum steering angle exceed the preset value, an alarm is issued; The specific steps of classifying the road surface conditions according to the historical vertical height data of the left and right sides of the trailer include: The historical vertical height data is annotated with road surface labels, wherein the road surface labels include flatness, potholes, and slopes; Extracting classification features from the annotated historical vertical height data, wherein the classification features include the difference between the heights of the left and right sides, the average height, the standard deviation, and the skewness; Divide the labeled data set into a training set and a validation set; The linear support vector machine model is trained using the training set to obtain a road surface judgment model.

2. A method for detecting a trailer posture as claimed in claim 1, characterized in that: The specific steps of using sensors to monitor the posture parameters of the trailer in real time include: Select the corresponding sensor group according to monitoring requirements; Fix the sensor group at the corresponding position of the trailer according to the design layout; Wirelessly connect all sensors to the central processing unit and calibrate the sensors; A sensor group is used to collect the posture parameters of the trailer.

3. A method for detecting a trailer posture as claimed in claim 2, characterized in that: The specific steps of confirming the current road surface state according to the vertical height data collected in real time include: Get the vertical height data collected by the sensor; Preprocessing the vertical height data; The road surface judgment model is applied to the real-time collected data to identify the current road surface status.

4. A method for detecting a trailer posture as claimed in claim 3, characterized in that: The specific steps of preprocessing the vertical height data include: Check whether there are abnormal height values ​​in the vertical height data, and if so, delete the abnormal height values; If there are missing values ​​in the vertical height data, they are filled using interpolation.

5. A method for detecting a trailer posture as claimed in claim 4, characterized in that: The specific steps of calculating the recommended steering speed and the maximum steering angle according to the angular velocity, acceleration and load of the trailer under the current road condition include: Set up a dynamic model based on the trailer's angular velocity, acceleration, load, and road conditions; The dynamic model is used to calculate the speed at which the trailer can turn safely under the current road conditions; The corresponding safe steering angle is calculated based on the safe steering speed.

6. A method for detecting a trailer posture as claimed in claim 5, characterized in that: The specific steps of setting the dynamic model according to the angular velocity, acceleration and load of the trailer and the road surface state include: Define basic parameters and coordinate system; Establish dynamic equations based on angular velocity, acceleration, load and road conditions; The accelerations on the x- and y-axes are corrected by the rotational dynamics equations.

7. A trailer posture detection system, applied to the trailer posture detection method according to claim 1, characterized in that: It includes parameter acquisition module, road surface classification module, road surface detection module, speed calculation module and alarm module; The parameter acquisition module is used to use sensors to monitor the posture parameters of the trailer in real time, and the posture parameters include angular velocity, acceleration and vertical height; The road surface classification module is used to classify the road surface state according to the historical vertical height data of the left and right sides of the trailer; The road surface detection module is used to confirm the current road surface state based on the vertical height data collected in real time; The speed calculation module is used to calculate the recommended steering speed and maximum steering angle according to the angular velocity, acceleration and load of the trailer under the current road condition; The alarm module is used to issue an alarm when the steering vehicle speed and the maximum steering angle exceed preset values.

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