A Remote Control Method and System for Highway Construction Equipment

Abstract

The present invention relates to the technical field of remote control, and specifically to a method and system for remotely controlling road construction equipment, which includes the following steps: For road construction equipment, the tilt angle of the equipment is collected through an on-vehicle tilt sensor, the change in tilt angle is calculated, the grounding area of the crawler or tire is recorded, the data of the load sensor is called, and the change in tilt angle is calculated. In the present invention, through the comprehensive evaluation of the tilt angle, the grounding area of the crawler or tire, and the load data, the driving stability is guaranteed. The terrain adaptability calculation covers the analysis of slope gradient, terrain undulation, and obstacle height, optimizing the path selection of the equipment in complex construction environments. The path planning combines the data of friction force, traction force, and slip angle, optimizing the distribution of running resistance, improving construction efficiency, reducing energy consumption. The remote control instruction is calculated based on the positioning data and coordinate offset, ensuring the accurate execution of path adjustment, reducing error accumulation, and making the remote control response more stable.

Description

Technical Field

[0001] The present invention relates to the technical field of remote control, and particularly to a method and system for remotely controlling highway construction equipment. Background Art

[0002] The technical field of remote control involves the remote operation and monitoring of equipment, systems, or processes. Its core content involves transmitting control instructions through wired or wireless communication methods to achieve precise control of target objects. This technical field covers multiple aspects such as industrial automation, intelligent manufacturing, intelligent transportation, unmanned driving, and remote monitoring, and usually relies on key technical means such as computer control, communication networks, sensors, and actuators. The overall development trend of remote control technology includes improving control accuracy, optimizing data transmission efficiency, and enhancing system stability to meet the requirements of remote operation in different application scenarios.

[0003] Among them, the method for remotely controlling highway construction equipment refers to the operation of highway construction machinery and equipment, and realizes functions such as adjusting the working state, controlling the movement trajectory, and executing construction tasks through remote instructions. This method usually relies on wireless communication technology for data transmission, and combines position detection and feedback control to ensure that the equipment executes construction tasks according to preset requirements under remote operation. In addition, this method also covers the real-time monitoring of the equipment operation state, by obtaining the working parameters of the construction equipment, and combining computer control technology for instruction parsing and equipment driving to achieve precise control of remote construction machinery.

[0004] The prior art only relies on single tilt angle monitoring for equipment attitude adjustment, without combining the grounding area and load data, resulting in inaccurate stability evaluation. The terrain adaptability analysis lacks comprehensive judgment of slope gradient, undulation amplitude, and obstacles, and the adaptability of the equipment on complex terrain is limited. The path planning does not fully consider the real-time friction and traction force, the path adjustment method is lagging, affecting the operation stability of the equipment. The remote control instruction has a large deviation during the adjustment process due to insufficient positioning accuracy, and the path execution is prone to deviation, reducing the construction accuracy. Summary of the Invention

[0005] The purpose of the present invention is to solve the disadvantages existing in the prior art, and to propose a method and system for remotely controlling highway construction equipment.

[0006] To achieve the above purpose, the present invention adopts the following technical scheme: A method for remotely controlling highway construction equipment, comprising the following steps:

[0007] S1: For highway construction equipment, collect the equipment tilt angle through an on-vehicle tilt sensor, calculate the change amount of the tilt angle, record the grounding area of the crawler or tire, call the load sensor data, and generate a stability state value of the highway construction equipment;

[0008] S2: Based on the stable state value of the highway construction equipment, calculate the slope gradient change rate through lidar point cloud data, record the undulation amplitude obtained by the ground unevenness sensor, call the obstacle detection radar to record the obstacle height, calculate the slope gradient change rate, ground undulation index, and obstacle impact factor, and generate the terrain adaptability coefficient of the construction area through weighted fusion;

[0009] S3: Based on the terrain adaptability coefficient of the construction area, collect friction measurement data, read the values of the traction sensors, call the slip angle readings, calculate the resistance gradient, and generate the path resistance distribution rate of the highway construction equipment;

[0010] S4: Based on the path resistance distribution rate of the highway construction equipment, collect target route data, read the slope gradient data, calculate the path adjustment plan, and generate the optimized path coordinate set of the highway construction equipment;

[0011] S5: Based on the optimized path coordinate set of the highway construction equipment, collect equipment positioning data, call the coordinates of the remote control system, read the offset angle, calculate the adjustment angle, and generate the remote path control instruction of the highway construction equipment.

[0012] As a further solution of the present invention, the stable state value of the highway construction equipment is specifically the inclination change amount, the grounding area of the crawler or tire, and the load sensor data. The terrain adaptability coefficient of the construction area includes the slope gradient, undulation amplitude, obstacle height, slope curvature, and contour gradient. The path resistance distribution rate of the highway construction equipment is specifically the friction measurement data, the values of the traction sensors, the slip angle readings, and the resistance gradient. The optimized path coordinate set of the highway construction equipment includes the target route data, the slope gradient data, and the path adjustment plan. The remote path control instruction of the highway construction equipment specifically refers to the equipment positioning data, the coordinates of the remote control system, the offset angle, and the adjustment angle.

[0013] As a further solution of the present invention, the steps for obtaining the stable state value of the highway construction equipment are specifically as follows:

[0014] S101: Based on the highway construction equipment, collect the equipment tilt angle through the vehicle-mounted tilt sensor, calculate the inclination change amount, record the grounding area of the crawler or tire, call the load sensor data, and obtain the original inclination data;

[0015] S102: Call the original inclination data, calculate the inclination change amount, and according to the grounding area of the crawler or tire and the load sensor data, use the formula:

[0016] ;

[0017] Calculate and obtain the inclination change value per unit grounding area to get the inclination change amount;

[0018] Wherein, Represent the variation value of the inclination angle per unit grounding area, Represent the current inclination angle, Represent the inclination angle at the previous moment, Represent the grounding area of the crawler or tire, Represent the data of the load sensor;

[0019] S103: Based on the variation amount of the inclination angle, compare with the stable threshold range of the inclination angle, judge the stable state of the road construction equipment, and obtain the stable state value of the road construction equipment.

[0020] As a further solution of the present invention, the obtaining steps of the terrain adaptability coefficient of the construction area are specifically as follows:

[0021] S201: Based on the stable state value of the road construction equipment, calculate the slope gradient change rate through the lidar point cloud data, record the undulation amplitude obtained by the ground unevenness sensor, call the obstacle detection radar to record the obstacle height, compare the slope gradient with the undulation amplitude, calculate the slope curvature, and conduct a joint analysis of the slope curvature and the obstacle height to obtain the slope curvature adjustment value;

[0022] S202: Call the slope curvature adjustment value and compare it with the contour gradient, and use the formula:

[0023] ;

[0024] Calculate the deviation of the slope curvature gradient through operation, and combine with the slope gradient to calculate the initial terrain adaptability coefficient, and generate the slope adaptation gradient coefficient;

[0025] Among them, Represent the slope adaptation gradient coefficient, Represent the slope curvature adjustment value, Represent the contour gradient, Represent the obstacle height weight coefficient, Represent the sum of the slope curvature data set, Represent the sum of the contour gradient data set, Represent the total number of obstacles in the obstacle height data set, Represent the group of obstacle height data;

[0026] S203: Call the slope adaptation gradient coefficient, combine with the slope curvature adjustment value and the contour gradient, screen the differences of multiple parameters, eliminate the data outside the adaptability threshold, and summarize the adaptability range of the terrain to obtain the terrain adaptability coefficient of the construction area.

[0027] As a further solution of the present invention, the obtaining steps of the path resistance distribution rate of the road construction equipment are specifically as follows:

[0028] S301: Based on the terrain adaptability coefficient of the construction area, collect friction measurement data, record the measured values of the friction data under different traction forces, read the values of the traction sensors, combine the friction data under the action of the traction force, compare the change trends of the friction coefficients at multiple traction force levels, and obtain the friction coefficient distribution values;

[0029] S302: Call the slip angle readings, combine the values of the traction sensors, calculate the changes in the slip angle under the action of different traction forces, and based on the friction coefficient distribution values, analyze the increments of the slip angle under the action of the traction force. Use the formula:

[0030] ;

[0031] Perform operations to obtain the resistance gradient values and get the change trend of the traction resistance;

[0032] where, represents the resistance gradient value, represents the traction force measured by the th group of traction sensors, represents the friction coefficient distribution value of the th group, represents the total number of measurement samples, represents the slip angle reading of the th group, represents the increment of the slip angle measured by the th group of traction sensors;

[0033] S303: Based on the change trend of the traction resistance, combine the friction coefficient distribution values, establish a path resistance distribution matrix, calculate the resistance levels under multiple path units, obtain the resistance characteristic data of different path units, and generate the path resistance distribution rate of the road construction equipment by integrating the resistance characteristics of multiple units.

[0034] As a further solution of the present invention, the steps for obtaining the optimized path coordinate set of the road construction equipment are specifically as follows:

[0035] S401: Based on the path resistance distribution rate of the road construction equipment, collect the target route data, extract the parameters of the spatial coordinates, road surface type, and curvature radius of the route, read the slope gradient data, calculate the slope change rate at multiple points and the distribution of the slope continuous intervals, and obtain the slope gradient distribution data;

[0036] S402: Call the slope gradient distribution data, calculate the path adjustment plan, and at the same time, based on the comprehensive calculated value of the slope change rate, curvature radius, and resistance distribution rate, use the formula:

[0037] ;

[0038] Calculate to obtain the path optimization adjustment parameters and generate a path optimization adjustment matrix;

[0039] Among them, represents the new path adjustment parameter, represents the slope change rate data value, represents the radius of curvature data value, represents the resistance distribution rate data value, represents the adjustment additional value, represents the slope continuity data value, represents the slope continuity additional value, represents the number of path segments;

[0040] S403: Call the path optimization adjustment matrix, and recalculate the original path data according to the adjustment weight, and screen the path coordinate set that meets the optimization conditions to obtain the optimized path coordinate set of the road construction equipment.

[0041] As a further solution of the present invention, the obtaining step of the remote path control instruction of the road construction equipment is specifically:

[0042] S501: Based on the optimized path coordinate set of the road construction equipment, collect the equipment positioning data, obtain the current spatial coordinates and motion state information of the equipment, and at the same time call the coordinates of the remote control system to obtain the target path coordinates stored in the remote control system, and compare the deviation between the current coordinates and the target path coordinates to calculate the equipment offset trajectory data;

[0043] S502: Call the equipment offset trajectory data, read the offset angle, compare it with the direction angle of the target path coordinates, calculate the adjustment angle, and combine the current motion speed and steering inertia of the equipment, and use the formula:

[0044] ;

[0045] Calculate to obtain the equipment adjustment angle parameter to obtain the equipment angle adjustment matrix;

[0046] Among them, represents the adjustment angle parameter, represents the current angle of the equipment, represents the target direction angle, represents the current speed of the equipment, represents the steering inertia factor, represents the angle error, represents the correction coefficient, represents the number of time steps, represents the number of inertia data points, represents the number of correction data points;

[0047] S503: Invoke the device angle adjustment matrix, combine it with the control instruction structure of the device remote control system, convert the adjustment matrix into the instruction format of the remote control system, and generate the remote path control instruction for the road construction equipment.

[0048] A remote control system for road construction equipment, which is used to execute the above-mentioned remote control method for road construction equipment. The system includes:

[0049] The equipment stability monitoring module obtains the tilt angle of the vehicle-mounted tilt sensor, detects the grounding area of the crawler or tire, invokes the load sensor data, calculates the change in tilt angle, screens the maximum value among the tilt angle, the grounding area of the crawler or tire, and the change in load data, calculates the equipment tilt state coefficient, screens and compares the equipment tilt state coefficient with the set stability reference value, calculates the stable state offset, and establishes the stable state value of the road construction equipment.

[0050] The construction area terrain adaptability evaluation module, based on the stable state value of the road construction equipment, obtains the lidar slope gradient, invokes the ground unevenness sensor data to calculate the undulation amplitude, reads the obstacle detection radar data to calculate the obstacle height, calculates the slope curvature, screens and compares the slope curvature with the contour gradient, and generates the construction area terrain adaptability coefficient.

[0051] The path resistance distribution calculation module, based on the construction area terrain adaptability coefficient, obtains the friction measurement data, invokes the traction sensor value, reads the slip angle reading, calculates the resistance gradient, screens and compares the maximum value of the resistance gradient with the friction measurement data, and establishes the path resistance distribution rate of the road construction equipment.

[0052] The construction equipment path optimization module, based on the path resistance distribution rate of the road construction equipment, obtains the target route data, invokes the slope gradient data, calculates the path adjustment plan, screens the difference value between the target route data and the path adjustment plan, and establishes the optimized path coordinate set of the road construction equipment.

[0053] The remote path control instruction generation module, based on the optimized path coordinate set of the road construction equipment, obtains the equipment positioning data, invokes the remote control system coordinates, reads the offset angle, calculates the adjustment angle, and establishes the remote path control instruction for the road construction equipment.

[0054] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0055] In the present invention, based on multi-dimensional data fusion calculation, the remote control accuracy is improved. The attitude of the device is comprehensively evaluated through the tilt angle, the grounding area of the crawler or tire, and the load data, ensuring the driving stability. The terrain adaptability calculation covers the analysis of slope gradient, terrain undulation, and obstacle height, optimizing the path selection of the device in complex construction environments. The path planning combines the data of friction force, traction force, and slip angle, optimizing the distribution of running resistance, improving the construction efficiency, and reducing the energy consumption. The remote control instruction is based on the positioning data and coordinate offset calculation, ensuring the precise execution of path adjustment, reducing the error accumulation, and making the remote control response more stable. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 It is a schematic diagram of the working process of the present invention;

[0057] Figure 2 It is a flowchart of the steps for obtaining the stable state value of the road construction equipment of the present invention;

[0058] Figure 3 It is a flowchart of the steps for obtaining the terrain adaptability coefficient of the construction area of the present invention;

[0059] Figure 4 It is a flowchart of the steps for obtaining the path resistance distribution rate of the road construction equipment of the present invention;

[0060] Figure 5 It is a flowchart of the steps for obtaining the optimized path coordinate set of the road construction equipment of the present invention;

[0061] Figure 6 It is a flowchart of the steps for obtaining the remote path control instruction of the road construction equipment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0062] In order to make the objectives, technical solutions, and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to 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 used to limit the present invention.

[0063] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. is based on the orientation or positional relationship shown in the accompanying drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention. In addition, in the description of the present invention, "a plurality of" means two or more unless otherwise specifically defined.

[0064] Embodiment 1: Please refer to Figure 1 , the present invention provides a technical solution: a remote control method for highway construction equipment, including the following steps:

[0065] S1: Obtain the operating parameters of the highway construction equipment, collect the equipment tilt angle measured by the vehicle-mounted tilt sensor, the grounding area obtained by the crawler or wheel grounding pressure sensor, the load distribution data recorded by the load sensor, call the drive torque and speed data of the equipment drive system, calculate the change amount of the tilt angle, judge the stable state of the equipment during traveling on the slope, and obtain the stable state value of the highway construction equipment based on the change amount of the tilt angle;

[0066] S2: Based on the stable state value of the highway construction equipment, obtain the terrain data of the construction area, collect the surface slope gradient measured by the lidar, the surface undulation degree obtained by the ground unevenness sensor, the obstacle height recorded by the obstacle detection radar, call the slope curvature calculation unit to calculate the surface slope change rate, combine the contour gradient analysis module to calculate the continuous undulation degree of the slope, calculate the influence of the slope gradient on the equipment operation, screen the equipment adaptation area based on the slope gradient influence rate, and generate the terrain adaptability coefficient of the construction area;

[0067] S3: Based on the terrain adaptability coefficient of the construction area, obtain the construction path resistance parameters, collect the surface friction coefficient recorded by the surface friction measurement device, the driving torque measured by the equipment traction force sensor, the driving load calculated by the driving load monitoring device, call the slip angle measured by the crawler slip angle measurement module, the slope change amount calculated by the path slope change measurement module, calculate the path resistance gradient, judge the resistance distribution area, screen the low-resistance traveling area, and obtain the path resistance distribution rate of the highway construction equipment;

[0068] S4: Based on the path resistance distribution rate of the highway construction equipment, obtain the target traveling route of the equipment, call the path point coordinates set in the construction path planning, the slope gradient change amount calculated by the slope gradient optimization module, the obstacle influence data recorded by the obstacle bypass judgment module, calculate the path point adjustment scheme, judge the influence of the path point adjustment on the equipment operation state, screen the stable traveling path points, and establish the optimized path coordinate set of the highway construction equipment;

[0069] S5: Based on the optimized path coordinate set of the highway construction equipment, obtain the traveling deviation angle of the equipment, call the current position of the equipment recorded by the GPS positioning system, the target path point coordinates set by the remote control system, calculate the traveling direction adjustment angle, judge whether the adjustment angle exceeds the stable range of the equipment, screen the control instructions within the adjustment range, and generate the remote path control instruction of the highway construction equipment.

[0070] The stable state values of highway construction equipment specifically include the inclination change amount, the grounding area of the crawler or tire, and the load sensor data. The terrain adaptability coefficient of the construction area includes the slope gradient, the undulation amplitude, the obstacle height, the slope curvature, and the contour gradient. The path resistance distribution rate of highway construction equipment specifically includes the friction measurement data, the traction sensor value, the slip angle reading, and the resistance gradient. The optimized path coordinate set of highway construction equipment includes the target route data, the slope gradient data, and the path adjustment plan. The remote path control instruction of highway construction equipment specifically refers to the equipment positioning data, the remote control system coordinates, the offset angle, and the adjustment angle.

[0071] Please refer to Figure 2 , and the steps for obtaining the stable state values of highway construction equipment are specifically as follows:

[0072] S101: Based on the highway construction equipment, collect the equipment tilt angle through the vehicle-mounted tilt sensor, calculate the inclination change amount, record the grounding area of the crawler or tire, call the load sensor data, and obtain the original inclination data;

[0073] First, install the vehicle-mounted tilt sensor at a suitable position on the equipment body structure to ensure that the real-time tilt angle of the equipment can be accurately measured. The data format collected by the sensor is in angle units (°) and is transmitted to the data processing system. At the same time, the grounding area of the crawler or tire is calculated from the geometric dimensions of the equipment chassis and the contact situation with the ground. For example, for the total length of the crawler and the crawler width , the formula for calculating the grounding area of the crawler or tire is . Taking a certain model of equipment as an example, assuming the crawler length is 3.5 m and the width is 0.8 m, then its grounding area is calculated as square meters. The load sensor is installed at the key load-bearing parts of the equipment chassis to monitor the equipment load force in real time . The output unit of the sensor is kN, and the data is transmitted to the data processing system through the acquisition system. For example, in a specific working condition of a certain equipment, the data measured by the load sensor . At the same time, the tilt sensor collects the current tilt angle value and the tilt angle value at the previous moment . For example . . All the data is input into the data processing system for calculation and storage.

[0074] S102: Call the original inclination data, calculate the inclination change amount, and based on the grounding area of the crawler or tire and the load sensor data, use the formula:

[0075] ;

[0076] Calculate and obtain the inclination change value per unit grounding area to get the inclination change amount;

[0077] Among them, represents the change value of the inclination angle per unit grounding area, represents the current inclination angle, represents the inclination angle at the previous moment, represents the grounding area of the crawler or tire, represents the load sensor data;

[0078] Formula:

[0079] ;

[0080] First, calculate the change value of the inclination angle, that is , and after taking the absolute value, we get , taking the previous example, , secondly, calculate the change value of the inclination angle per unit grounding area , and the formula is , substitute the data , where , finally , this value is stored in the system for subsequent stable state judgment, as shown in Table 1.

[0081] Table 1 Data table for calculating the change amount of the inclination angle:

[0082] ;

[0083] As shown in Table 1, the change value of the inclination angle under different devices and working conditions can be calculated based on the inclination angle, load and grounding area, and this data is used to judge the stable state of the device.

[0084] S103: Based on the change amount of the inclination angle, compare it with the stable threshold range of the inclination angle, judge the stable state of the road construction equipment, and obtain the stable state value of the road construction equipment.

[0085] Based on the calculation result, the system is compared with the preset stable threshold range of the inclination angle, and the threshold interval is set. When falls within this range, the device is in a stable state, otherwise it enters the abnormal state judgment. For example, in this example, the calculated is within the threshold range, and it is determined that the device is stable. If then it is determined that the device is unstable, and the relevant data is further recorded and analyzed, as shown in Table 2.

[0086] Table 2 Device stable state determination table:

[0087] ;

[0088] Refer to Table 2. The system determines the current stable state of the device based on the calculation results and the set threshold, and stores the relevant data for subsequent analysis and optimization adjustment.

[0089] Please refer to Figure 3 , and the steps for obtaining the terrain adaptability coefficient of the construction area are specifically as follows:

[0090] S201: Based on the stable state value of the highway construction equipment, calculate the slope gradient change rate through the lidar point cloud data, record the undulation amplitude obtained by the ground unevenness sensor, call the obstacle detection radar to record the obstacle height, compare the slope gradient with the undulation amplitude, calculate the slope curvature, and conduct a joint analysis of the slope curvature and the obstacle height to obtain the slope curvature adjustment value;

[0091] First, call the lidar to scan the current construction area to collect slope gradient data. Specifically, the lidar measures the heights of multiple points and calculates the slope gradient based on the height differences between adjacent points. For example, in a construction area, if the height of point A is 120m, the height of point B is 124m, and the horizontal distance between them is 5m, then the slope gradient is calculated as ; At the same time, record the undulation amplitude obtained by the ground unevenness sensor. This sensor detects the minute height changes on the construction ground, and the data can be calculated through the height changes of multiple points. For example, if the heights of five points measured in a certain construction area are 120m, 121.5m, 123m, 122m, and 124m respectively, then the undulation amplitude can be expressed as the difference between the maximum and minimum values, that is ; Subsequently, call the obstacle detection radar to detect the obstacle height in the construction area. The radar returns the data of the highest point of the obstacle. For example, if the highest point height of a certain obstacle is measured as 130m, and the reference ground height at the location of this obstacle is 122m, then the obstacle height is calculated as ; Compare the slope gradient with the undulation amplitude to analyze the overall change trend of the slope surface. For example, when the slope gradient is high and the undulation amplitude is small, it indicates that the change of the slope surface tends to be smooth, otherwise it means that the slope surface is relatively rugged. For example, if the slope gradient of a certain construction area is 0.9 and the undulation amplitude is 2, it can be considered that the slope surface is relatively steep but overall flat, while if the slope gradient is 0.3 and the undulation amplitude is 6, it can be judged that the slope surface has many undulations; Based on the calculation results of the slope gradient and the undulation amplitude, further calculate the slope curvature, that is, consider the overall undulation situation of the slope surface. For example, if multiple slope gradient values in a certain area are 0.8, 1.0, 0.6, and 0.7 respectively, the slope curvature can be calculated through the second derivative to reflect the continuity of the slope surface; Finally, conduct a joint analysis of the slope curvature and the obstacle height to judge whether the overall slope surface is suitable for construction. For example, if the slope curvature is large and the obstacle height exceeds the set threshold, such as higher than 5m, the construction equipment may be difficult to operate stably. Therefore, calculate the slope curvature adjustment value for subsequent adjustment of the construction plan.

[0092] S202: Call the slope curvature adjustment value and compare it with the contour gradient. Use the formula:

[0093] ;

[0094] Calculate the slope curvature gradient deviation through operation, and combine the slope gradient to calculate the initial coefficient of terrain adaptability to generate the slope adaptation gradient coefficient.

[0095] Among them, represents the slope adaptation gradient coefficient, represents the slope curvature adjustment value, represents the contour gradient, represents the obstacle height weight coefficient, represents the sum of the slope curvature data set, represents the sum of the contour gradient data set, represents the total number of obstacles in the obstacle height data set, represents the group of obstacle height data;

[0096] For example, if the contour interval of a certain area is 10m and the contour height difference is 2m, then its contour gradient is calculated as ; When calculating the slope adaptation gradient coefficient, use the formula:

[0097] ;

[0098] Among them, represents the slope curvature adjustment value, let its value be 0.5, and represents the contour gradient, and the previously calculated value is 0.2, then ; Denote the total number of obstacles. Suppose 3 obstacles are detected, with heights of 6m, 4m, and 5m respectively. Let the obstacle height weight coefficients take values of 0.8, 0.7, and 0.9 respectively. Then the summation term is calculated as follows:

[0099] ;

[0100] Denote the sum of the slope curvature data set. Suppose the slope curvature values of five slopes in a certain area are 0.4, 0.5, 0.3, 0.6, and 0.7. Then their sum ; Denote the sum of the contour gradient data set. Suppose the contour gradient data set contains five values: 0.2, 0.3, 0.25, 0.15, and 0.35. Then their sum ; Finally, calculate the denominator part:

[0101] ;

[0102] Finally, calculate the slope adaptation gradient coefficient :

[0103] ;

[0104] Table 3 Slope adaptation gradient coefficient calculation parameter table:

[0105] ;

[0106] As shown in Table 3, this table shows each parameter and calculation result involved in the calculation process of the slope adaptation gradient coefficient.

[0107] S203: Call the slope adaptation gradient coefficient, combine the slope curvature adjustment value and the contour gradient, screen the differences of multiple parameters, eliminate the data outside the adaptation threshold, and summarize the adaptation range of the terrain to obtain the terrain adaptation coefficient of the construction area.

[0108] First, set the adaptation threshold range. For example, set the data of the slope adaptation gradient coefficient between 4.0 and 7.0 as the adaptation range. Then, if the calculated , it meets the adaptation range; for the slope curvature adjustment value, if this value is within the set range (such as 0.3 to 0.7), the data is retained, otherwise it is eliminated. For example, if the calculated slope curvature adjustment value in a certain area is 0.2, it should be eliminated; finally, summarize the adaptation range of the terrain, calculate the terrain adaptation coefficient of the construction area. If the calculated adaptation coefficient of a certain area is 0.75, it is determined that this area is suitable for construction, otherwise adjust the construction plan or improve the slope parameters to meet the adaptation requirements.

[0109] Please refer toFigure 4 , the steps for obtaining the path resistance distribution rate of highway construction equipment are specifically as follows:

[0110] S301: Based on the terrain adaptability coefficient of the construction area, collect friction measurement data, record the measured values of the friction data under different traction forces, read the values of the traction sensors, combine the friction data under the action of the traction force, and compare the change trends of the friction coefficients at multiple traction force levels to obtain the friction coefficient distribution value;

[0111] First, divide the construction area into zones. Each zone is numbered according to its terrain characteristics (such as slope, soil hardness, humidity, etc.), and the adaptability coefficient of each zone is recorded (the range is set from 0.1 to 1.0, and the higher the adaptability, the larger the value). Then, deploy friction measurement devices in each zone to collect friction measurement data, which includes the friction force of the construction equipment at different traction force levels and the pressure at the ground contact points , use the formula to calculate the friction coefficient. At least three data of different traction force levels should be collected at each measurement point , and record their corresponding friction coefficients , then read the values of the traction sensors. The sensors measure the instantaneous traction force value and the stability of the traction force, and combine the friction data under the action of the traction force. By comparing the friction coefficients at multiple traction force levels calculate the change rate The friction coefficient distribution value is calculated by region, that is, the measured friction data is weighted and calculated according to the terrain adaptability coefficient , as shown in Table 4. As shown in Table 4, the friction data shows a trend that the friction coefficient decreases with the increase of the traction force. This result indicates that there are differences in the influence of the friction coefficient change in different terrain regions on the traction force. This numerical result can be used for subsequent traction resistance calculation to judge the traction force adaptability of different regions.

[0112] Table 4 Friction Coefficient Distribution Data Table:

[0113] ;

[0114] As shown in Table 4, the friction data shows a trend that the friction coefficient decreases with the increase of the traction force. This result indicates that there are differences in the influence of the friction coefficient change in different terrain regions on the traction force. This numerical result can be used for subsequent traction resistance calculation to judge the traction force adaptability of different regions.

[0115] S302: Call the slip angle readings, combine the values of the traction sensors, calculate the change of the slip angle under the action of different traction forces, and based on the friction coefficient distribution value, analyze the increment of the slip angle under the action of the traction force, using the formula:

[0116] ;

[0117] Calculate the resistance gradient value through operation to obtain the change trend of the traction resistance;

[0118] Among them, represents the resistance gradient value, represents the traction force measured by the th group of traction sensors, represents the th group of friction coefficient distribution values, represents the total number of measurement samples, represents the th group of slip angle readings, represents the th group of slip angle increments measured by the traction sensors;

[0119] This sensor captures the angular changes caused by ground resistance during traction, calculates the changes in the slip angle at different traction force levels, sets different traction force levels, such as 600N, 1200N, 1800N, and records the slip angle , calculates the slip angle increment at each traction force level , calculates the frictional force based on the friction coefficient distribution value, calculates the cumulative value of the traction resistance change trend, according to the formula:

[0120] ;

[0121] The following test data is used for calculation:

[0122] ;

[0123] Calculation result:

[0124] ;

[0125] This result shows the resistance gradient value of the current construction area at different traction force levels. This value can be used to evaluate the resistance trend of the traction equipment and further for the calculation of the path resistance distribution.

[0126] S303: Based on the traction resistance change trend, combined with the friction coefficient distribution value, establish a path resistance distribution matrix, calculate the resistance levels under multiple path units, obtain the resistance characteristic data of different path units, and generate the path resistance distribution rate of the highway construction equipment by synthesizing the resistance characteristics of multiple units.

[0127] The construction area is divided into multiple path units. Each path unit is numerically valued according to its friction coefficient, traction resistance, and slip angle, and a matrix is formed:

[0128] ;

[0129] Calculate the resistance levels under each path unit, analyze the resistance characteristic data of each path unit according to the path resistance matrix, form resistance grades, which are divided into three grades from low to high: 0 - 300N, 301 - 600N, and 601 - 900N. Finally, comprehensively integrate the resistance characteristics of multiple units to generate the path resistance distribution rate of highway construction equipment, as shown in Table 5.

[0130] Table 5 Path Resistance Distribution Table of Construction Equipment:

[0131] ;

[0132] As shown in Table 5, the resistance distribution rate changes with the path resistance gradient. This result indicates that the resistance characteristics of different path units can be classified through the resistance distribution matrix, and based on this, the driving paths of construction equipment can be optimized to enable the equipment to operate in areas with lower resistance and improve the traction efficiency.

[0133] Please refer to Figure 5 , the specific steps for obtaining the optimized path coordinate set of highway construction equipment are as follows:

[0134] S401: Based on the path resistance distribution rate of highway construction equipment, collect the target route data, extract the parameters of the spatial coordinates, road surface type, and curvature radius of the route, read the slope gradient data, calculate the slope change rate of multiple points and the distribution of slope continuous intervals, and obtain the slope gradient distribution data;

[0135] First, it is necessary to determine the geographical information data of the target route. Collect the longitude and latitude information of the target route through high-precision GPS equipment, and combine with GIS (Geographic Information System) to extract the spatial coordinates. When obtaining the road surface type data, it is necessary to conduct on-site surveys of the road and confirm different types of road surface structures such as asphalt, concrete, and gravel in combination with the database of the traffic management department. Further, for the measurement of the curvature radius of the route, unmanned aerial vehicle aerial survey or road surveying equipment can be used to calculate the corresponding curvature radius through continuous point coordinates. For the reading of the slope gradient data, a three-dimensional laser scanner or an electronic level is used to measure the slope angle at equal intervals along the line, and the slope change rate is calculated in combination with the elevation data. For the calculation of the slope change rate of multiple points, the difference in slope angles between adjacent measurement points is divided by the corresponding horizontal distance to obtain the slope change rate. For example, the slope angles of adjacent measurement points on a certain section of the road are and , and the distance between the two points is 10 meters, then the slope change rate is calculated as follows: , and the distribution of the slope continuous interval can be obtained by setting a threshold, and the continuous area where the slope change rate is within the range of ±0.2° / m is regarded as the slope stable area, as shown in Table 6. Finally, the complete slope gradient distribution data is obtained. This result indicates that the collection of the slope gradient data has been completed and can provide data support for subsequent path optimization and adjustment, and is further used for path optimization calculation.

[0136] Table 6 Gradient Distribution Data Table:

[0137] ;

[0138] As shown in Table 6, if the gradient change rate of multiple consecutive measurement points on a certain section is lower than the set threshold (0.2° / m), then it is marked as a continuous gradient interval.

[0139] S402: Call the gradient distribution data, calculate the path adjustment plan, and at the same time, based on the comprehensive calculation value of the gradient change rate, curvature radius, and resistance distribution rate, use the formula:

[0140] ;

[0141] Perform operations to obtain the path optimization adjustment parameters and generate the path optimization adjustment matrix;

[0142] Among them, represents the new path adjustment parameter, represents the gradient change rate data value, represents the curvature radius data value, represents the resistance distribution rate data value, represents the adjustment additional value, represents the continuous gradient data value, represents the continuous gradient additional value, represents the number of path segments;

[0143] First, read the gradient change rate, curvature radius, and resistance distribution rate data in Table 6. When calculating the path adjustment plan, comprehensive analysis needs to be carried out based on these data. Assume that on a certain section, the gradient change rate is 0.3° / m, the curvature radius is 200m, and the resistance distribution rate is 0.7. Then, operations need to be performed on these data. When calculating the path optimization adjustment parameters, according to the formula:

[0144] ;

[0145] Set the parameter values: the adjustment additional value is 0.5, the continuous gradient data value is 1.2, and the continuous gradient additional value is 0.8. Then the calculation is as follows:

[0146] ;

[0147] This result indicates that the current combination of the gradient change rate, curvature radius, and resistance distribution rate on this section does not meet the optimization conditions. The calculated value is less than the set threshold (-50), so optimization adjustments are needed. By reducing the slope change rate or increasing the curvature radius, make fall within a reasonable range, and finally form a path optimization adjustment matrix, as shown in Table 7.

[0148] Table 7 Path optimization adjustment matrix:

[0149] ;

[0150] As shown in Table 7, the new slope change rate and resistance distribution rate after adjustment can make the adjustment parameters fall within the acceptable range (>-50).

[0151] S403: Call the path optimization adjustment matrix, and according to the adjustment weight, recalculate the original path data, screen the path coordinate set that meets the optimization conditions, and obtain the optimized path coordinate set of the road construction equipment.

[0152] Specifically when executing, traverse the slope change rate and resistance distribution rate values after adjustment in Table 7, perform matching calculations with the original path data, and compare the change values before and after adjustment If the of the adjusted path meets the optimization conditions (>-50), then add the spatial coordinates corresponding to this path to the optimized path coordinate set. As shown in Table 8, this result shows that the path after optimization adjustment meets the operation requirements of the construction equipment and can be used as part of the optimized path coordinate set.

[0153] Table 8 Optimized path coordinate set of road construction equipment:

[0154] ;

[0155] As shown in Table 8, the finally obtained optimized path coordinate set contains the path coordinate information that meets the optimization requirements after calculation and screening. This result shows that the optimized path already meets the requirements of the smoothness and passability of the construction equipment operation and can be used for the equipment path planning during the construction process.

[0156] Please refer to Figure 6 , the steps for obtaining the remote path control instruction of the road construction equipment are specifically as follows:

[0157] S501: Based on the optimized path coordinate set of the road construction equipment, collect the equipment positioning data, obtain the current spatial coordinates and motion state information of the equipment, and at the same time call the coordinates of the remote control system to obtain the target path coordinates stored in the remote control system, compare the deviation between the current coordinates and the target path coordinates, and calculate the equipment offset trajectory data;

[0158] First, you need to call the device's built-in positioning system, such as GPS or inertial navigation system (INS), to collect the device's positioning data in real time, including latitude, longitude, elevation, and azimuth, and convert it into spatial coordinates. Specifically, assuming that the device's current GPS coordinates are (34.12345°N, 117.98765°E, elevation 50m), you first need to convert it to UTM (Universal Transverse Mercator) coordinates to obtain plane coordinates. At the same time, the device's motion status information needs to be obtained through a speed sensor or wheel speedometer, including instantaneous speed (Unit: m / s) and current angle (Unit: °), assuming the current device speed is m / s, current angle , while the target path coordinates stored in the remote control system should be a set of discrete points, such as , and obtain the target path space coordinates through coordinate transformation , then compare the device's current location With the target path coordinates The deviation is calculated by the Euclidean distance formula Calculate the offset distance, for example if m, m, then m, and at the same time, calculate the current direction angle of the device Angle with target path The angle between ,like ,but , thereby obtaining the device's offset trajectory data, including position offset and angular offset And other parameters, as shown in Table 9.

[0159] Table 9 Equipment deviation trajectory data table:

[0160] ;

[0161] As shown in Table 9, the results show that there is a deviation between the current position of the device and the target path point, where the position offset m, which indicates the distance that the device trajectory deviates from the target path, and the angle deviation , indicating that there is an angle deviation of 5° between the current direction of the device and the target path direction. These data will be used in subsequent steps to calculate and adjust the angle parameters to achieve trajectory correction.

[0162] S502: Call the device offset trajectory data, read the offset angle, compare the direction angle of the target path coordinates, calculate the adjustment angle, and combine the current movement speed and steering inertia of the device, using the formula:

[0163] ;

[0164] Obtain the device adjustment angle parameter through calculation to get the device angle adjustment matrix;

[0165] Among them, represents the adjustment angle parameter, represents the current angle of the device, represents the target direction angle, represents the current speed of the device, represents the steering inertia factor, represents the angle error, represents the correction coefficient, represents the number of time steps, represents the number of inertia data points, represents the number of correction data points;

[0166] First, it is necessary to extract (angle offset) and (target direction angle), compare with the target path coordinate direction angle , calculate the adjustment angle , combined with the current motion speed of the device and steering inertia , adopt the following calculation formula:

[0167] ;

[0168] Assume that the time step of the device is , the number of inertia data points , the number of correction data points , calculate as follows:

[0169] ;

[0170] ;

[0171] ;

[0172] ;

[0173] ;

[0174] Therefore, the adjustment angle parameter of the device angle adjustment matrix is calculated, and this value will be converted into the remote control system instruction format in the next step and used to control the steering system of the device to perform trajectory correction.

[0175] S503: Invoke the device angle adjustment matrix, combine it with the control instruction structure of the device remote control system, convert the adjustment matrix into the instruction format of the remote control system, and generate the remote path control instruction for the road construction equipment.

[0176] According to the remote control system protocol, the adjustment angle data should be converted into a numerical instruction code, for example, represented in the 16-bit integer format. Set the minimum adjustment unit to 0.01°. Then It is converted to an integer value, which is sent to the remote control system through the remote communication protocol (such as CAN bus or wireless network protocol). The remote control system parses the instruction and executes the corresponding steering control. At the same time, it is linked with the device steering mechanism to adjust the steering angle of the device's steering wheel or track to the specified angle. If the device is a wheeled vehicle, the steering angle is controlled by the motor. If it is a tracked device, the steering is achieved by adjusting the track speed difference. In this way, the generation of the remote path control instruction for the road construction equipment is completed. This result indicates that the adjustment angle of the device has been converted into an instruction recognizable by the remote control system and can drive the device to perform the corresponding adjustment to correct its driving trajectory and return to the target path.

[0177] A remote control system for road construction equipment. The remote control system for road construction equipment is used to execute the above-mentioned remote control method for road construction equipment. The system includes:

[0178] The device stability monitoring module obtains the tilt angle of the vehicle-mounted tilt sensor, detects the grounding area of the track or tire, calls the load sensor data, calculates the change in tilt angle, screens the maximum value among the tilt angle, the grounding area of the track or tire, and the change in load data, calculates the device tilt state coefficient, screens and compares the device tilt state coefficient with the set stability reference value, calculates the stable state offset, and establishes the stable state value of the road construction equipment;

[0179] The construction area terrain adaptability evaluation module, based on the stable state value of the road construction equipment, obtains the lidar slope gradient, calls the ground unevenness sensor data to calculate the undulation amplitude, reads the obstacle detection radar data to calculate the obstacle height, calculates the slope curvature, screens and compares the slope curvature with the contour gradient, and generates the construction area terrain adaptability coefficient;

[0180] The path resistance distribution calculation module, based on the construction area terrain adaptability coefficient, obtains the friction measurement data, calls the traction sensor value, reads the slip angle reading, calculates the resistance gradient, screens and compares the maximum value of the resistance gradient with the friction measurement data, and establishes the path resistance distribution rate of the road construction equipment;

[0181] Based on the path resistance distribution rate of highway construction equipment, the construction equipment path optimization module obtains the target route data, calls the slope gradient data, calculates the path adjustment plan, screens the difference value between the target route data and the path adjustment plan, and establishes the optimized path coordinate set of highway construction equipment;

[0182] Based on the optimized path coordinate set of highway construction equipment, the remote path control instruction generation module obtains the equipment positioning data, calls the coordinates of the remote control system, reads the offset angle, calculates the adjustment angle, and establishes the remote path control instruction of highway construction equipment.

[0183] The above is only a preferred embodiment of the present invention, and does not limit the present invention in other forms. Any person skilled in the art may use the disclosed technical content to make changes or modifications into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change, and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution content of the present invention still belong to the protection scope of the technical solution of the present invention.

Claims

1. A method for remote control of highway construction equipment, characterized in that: The following steps are involved: S1: For highway construction equipment, the inclination angle of the equipment is collected through the vehicle-mounted inclination sensor, the inclination angle change is calculated, the track or tire contact area is recorded, the load sensor data is called, and the stable state value of the highway construction equipment is generated; S2: Based on the stable state value of the highway construction equipment, the slope change rate of the slope is calculated through the laser radar point cloud data, the ground concave and convex sensor is recorded to obtain the undulation amplitude, the obstacle detection radar is called to record the obstacle height, the slope change rate, the ground undulation index and the obstacle influence factor are calculated, and the terrain adaptability coefficient of the construction area is generated through weighted fusion; S3: Based on the terrain adaptability coefficient of the construction area, collect friction measurement data, read the traction sensor value, call the slip angle reading, calculate the resistance gradient, and generate the road construction equipment path resistance distribution rate; S4: Based on the road construction equipment path resistance distribution rate, collecting target route data, reading slope gradient data, calculating a path adjustment plan, and generating a road construction equipment optimized path coordinate set; S5: Based on the optimized path coordinate set of the highway construction equipment, collect equipment positioning data, call the remote control system coordinates, read the offset angle, calculate the adjustment angle, and generate a remote path control instruction for the highway construction equipment; The stable state value of the highway construction equipment specifically includes the inclination angle change, the track or tire contact area, and the load sensor data. The terrain adaptability coefficient of the construction area includes the slope gradient, undulation amplitude, obstacle height, slope curvature, and contour gradient. The path resistance distribution rate of the highway construction equipment specifically includes friction measurement data, traction sensor value, slip angle reading, and resistance gradient. The highway construction equipment optimized path coordinate set includes target route data, slope gradient data, and path adjustment plan. The highway construction equipment remote path control instruction specifically refers to equipment positioning data, remote control system coordinates, offset angle, and adjustment angle.

2. The highway construction equipment remote control method according to claim 1, characterized in that: The steps for obtaining the stable state value of the highway construction equipment are specifically as follows: S101: Based on the highway construction equipment, the inclination angle of the equipment is collected through the vehicle-mounted inclination sensor, the inclination change is calculated, the contact area of ​​the track or tire is recorded, the load sensor data is called, and the original inclination data is obtained; S102: calling the original inclination data to calculate the inclination change, using the formula: ； Calculate and obtain the inclination angle change value per unit ground contact area to obtain the inclination angle change amount; in, Represents the change in inclination per unit ground contact area, represents the current inclination angle, represents the inclination angle at the previous moment, Represents the contact area of ​​the track or tire, Represents load sensor data; S103: Based on the inclination angle variation, the inclination angle stability threshold range is compared to determine the stability state of the highway construction equipment and obtain a stability state value of the highway construction equipment.

3. The highway construction equipment remote control method according to claim 2, characterized in that: The steps for obtaining the terrain adaptability coefficient of the construction area are specifically as follows: S201: Based on the stable state value of the highway construction equipment, the slope change rate of the slope is calculated through the laser radar point cloud data, and the fluctuation amplitude obtained by the ground concave-convex sensor is recorded, the obstacle detection radar is called to record the obstacle height, the slope gradient is compared with the fluctuation amplitude, the slope curvature is calculated, and the slope curvature and the obstacle height are jointly analyzed to obtain the slope curvature adjustment value; S202: calling the slope curvature adjustment value and comparing it with the contour gradient, using the formula: ； The slope curvature gradient deviation is obtained by operation, and the initial coefficient of terrain adaptability is calculated in combination with the slope gradient to generate the slope adaptability gradient coefficient; in, represents the slope adaptation gradient coefficient, Represents the slope curvature adjustment value, represents the contour gradient, represents the obstacle height weight coefficient, represents the sum of the slope curvature dataset, represents the sum of the contour gradient data set, Represents the total number of obstacles in the obstacle height dataset, Representative Group obstacle height data; S203: calling the slope adaptation gradient coefficient, combining the slope curvature adjustment value and the contour gradient, screening the differences in multiple parameters, eliminating data outside the adaptability threshold, and summarizing the adaptability range of the terrain to obtain the terrain adaptability coefficient of the construction area.

4. The highway construction equipment remote control method according to claim 3, characterized in that: The steps for obtaining the path resistance distribution rate of the highway construction equipment are specifically as follows: S301: Based on the terrain adaptability coefficient of the construction area, collect friction measurement data, record the measured values ​​of the friction data under differentiated traction, read the traction sensor value, combine the friction data under the traction, compare the friction coefficient change trend under multiple traction levels, and obtain the friction coefficient distribution value; S302: Call the slip angle reading, combine the traction sensor value, calculate the change of the slip angle under the action of the differentiated traction force, and analyze the increment of the slip angle under the action of the traction force based on the friction coefficient distribution value, using the formula: ； Obtain the resistance gradient value through calculation and obtain the changing trend of the traction resistance; in, Represents the resistance gradient value, Representative The traction force measured by the traction sensor of the group, Representative Group friction coefficient distribution value, Represents the total number of samples measured, Representative Group slip angle readings, Representative The slip angle increment measured by the group traction sensor; S303: Based on the traction resistance change trend and in combination with the friction coefficient distribution value, a path resistance distribution matrix is ​​established, the resistance level under multiple path units is calculated, the resistance characteristic data of differentiated path units are obtained, and the resistance characteristics of multiple units are integrated to generate a path resistance distribution rate of highway construction equipment.

5. The highway construction equipment remote control method according to claim 4, characterized in that: The steps for obtaining the optimized path coordinate set of the highway construction equipment are specifically as follows: S401: Based on the road construction equipment path resistance distribution rate, target route data is collected, spatial coordinates, road surface type, and curvature radius parameters of the route are extracted, slope gradient data is read, and slope change rates and distribution of slope continuous intervals at multiple points are calculated to obtain slope gradient distribution data; S402: Call the slope gradient distribution data to calculate the path adjustment plan, and use the formula based on the comprehensive calculation value of the slope change rate, curvature radius and resistance distribution rate: ； Calculate and obtain path optimization adjustment parameters, and generate a path optimization adjustment matrix; in, Represents the new adjustment parameters of the path, Represents the slope change rate data value, Represents the curvature radius data value, Represents the resistance distribution rate data value, stands for adjusted value added, represents the continuous data value of slope, represents the continuous additional value of slope, Represents the number of path segments; S403: calling the path optimization adjustment matrix, recalculating the original path data according to the adjustment weight, screening the path coordinate set that meets the optimization conditions, and obtaining the optimized path coordinate set of the highway construction equipment.

6. The highway construction equipment remote control method according to claim 5, characterized in that: The steps for obtaining the remote path control instructions of the highway construction equipment are specifically as follows: S501: Based on the optimized path coordinate set of the highway construction equipment, the equipment positioning data is collected to obtain the current spatial coordinates and motion state information of the equipment, and the remote control system coordinates are called to obtain the target path coordinates stored in the remote control system, and the deviation between the current coordinates and the target path coordinates is compared to calculate the equipment offset trajectory data; S502: Call the device offset trajectory data, read the offset angle, compare the direction angle of the target path coordinates, calculate the adjustment angle, and combine the current movement speed and steering inertia of the device to use the formula: ； Obtain the device angle adjustment parameters through calculation to obtain the device angle adjustment matrix; in, Represents the adjustment angle parameter, Represents the current angle of the device. represents the target direction angle, Represents the current speed of the device. represents the steering inertia factor, represents the angle error, represents the correction factor, represents the number of time steps, represents the number of inertia data points, represents the number of calibration data points; S503: calling the device angle adjustment matrix, combining the control instruction structure of the device remote control system, converting the adjustment matrix into the remote control system instruction format, and generating a highway construction equipment remote path control instruction.

7. A highway construction equipment remote control system, characterized in that: According to the highway construction equipment remote control method according to any one of claims 1 to 6, the system comprises: The equipment stability monitoring module obtains the inclination angle of the vehicle-mounted inclination sensor, detects the contact area of ​​the track or tire, calls the load sensor data, calculates the inclination angle change, selects the maximum value among the inclination angle, contact area of ​​the track or tire and the load data change, calculates the equipment inclination state coefficient, selects the equipment inclination state coefficient and compares it with the set stability reference value, calculates the stable state offset, and establishes the stable state value of the highway construction equipment; The construction area terrain adaptability assessment module obtains the laser radar slope gradient based on the stable state value of the highway construction equipment, calls the ground concave and convex sensor data to calculate the undulation amplitude, reads the obstacle detection radar data to calculate the obstacle height, calculates the slope curvature, screens the slope curvature and compares it with the contour gradient, and generates the construction area terrain adaptability coefficient; The path resistance distribution calculation module obtains friction measurement data based on the terrain adaptability coefficient of the construction area, calls the traction sensor value, reads the slip angle reading, calculates the resistance gradient, screens the maximum value of the resistance gradient and compares it with the friction measurement data, and establishes the path resistance distribution rate of the highway construction equipment; The construction equipment path optimization module obtains the target route data based on the highway construction equipment path resistance distribution rate, calls the slope gradient data, calculates the path adjustment plan, screens the difference between the target route data and the path adjustment plan, and establishes the highway construction equipment optimized path coordinate set; The remote path control instruction generation module obtains equipment positioning data, calls the remote control system coordinates, reads the offset angle, calculates the adjustment angle, and establishes the remote path control instruction for the highway construction equipment based on the highway construction equipment optimized path coordinate set.

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