Urban updated unmanned asphalt pavement compaction system and intelligent control construction method

Abstract

The invention relates to an urban updated unmanned asphalt pavement compaction system and an intelligent control construction method. The unmanned asphalt pavement compaction system comprises an unmanned road roller, a server, infrared temperature acquisition equipment, environment temperature detection equipment, steel wheel temperature monitoring equipment, compaction degree monitoring equipment, vehicle-mounted laser radar equipment and a control and signal processing module. Multi-source sensing of a construction site is achieved, it is guaranteed that the pavement compaction quality can be monitored, and on the basis of multi-source sensing data obtained in real time, running and working parameters of an unmanned road roller are dynamically adjusted through the intelligent control construction method of the urban updating unmanned asphalt pavement compaction system, so that the pavement compaction quality is improved. The adaptability of asphalt pavement compaction of the unmanned road roller under different working conditions is improved, and the construction quality is further guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of pavement engineering, and in particular to an unmanned asphalt pavement compaction system and an intelligent control construction method for urban renewal. Background Art

[0002] Traditional asphalt pavement compaction equipment, rollers, require manual operation. The asphalt pavement rolling process is often performed on freshly laid asphalt mixtures, with temperatures reaching around 160 degrees Celsius. Operators must withstand these high temperatures. Furthermore, the toxic gases and dust produced by asphalt volatilization pose a significant health risk to operators. Unmanned rollers can reduce labor costs and operate in all-weather conditions. Therefore, the development of unmanned rollers is necessary. Pavement compaction, a crucial step in asphalt pavement construction, is crucial for ensuring its quality. Due to variations in construction environment, weather, and working conditions, controlling the roller's movement according to a fixed strategy can easily lead to variations in compaction quality. Therefore, a dynamic control method is needed to adjust the roller's motion and operating parameters based on the surrounding environment and construction conditions. Monitoring the construction process is essential to improving pavement construction quality and preventing insufficient, excessive, or uneven compaction.

[0003] Currently, unmanned roller compaction systems have completed experimental development. Existing unmanned roller onboard systems collect data while working and upload it in real time, enabling real-time monitoring of construction site conditions. However, when currently unmanned rollers dynamically adjust based on real-time monitoring data from the construction site, they often pre-set normal ranges for parameters such as speed and temperature. These dynamic adjustments are achieved by comparing real-time data with pre-set ranges. However, the construction environment for unmanned rollers is often complex, and this oversimplified adjustment method makes it difficult to guarantee the quality of unmanned roller compaction.

[0004] Therefore, it is urgent to design an unmanned asphalt pavement compaction system and an intelligent control construction method for urban renewal to solve the problems existing in the above-mentioned existing technologies. Summary of the Invention

[0005] Based on the above objectives, the present invention provides an unmanned asphalt pavement compaction system, which adopts the following technical solutions: an unmanned asphalt pavement compaction system, including an unmanned roller, a server, an infrared temperature acquisition device, an ambient temperature detection device, a steel wheel temperature monitoring device, a compaction degree monitoring device, an on-board laser radar device, and a control and signal processing module, wherein:

[0006] The control and signal processing module is used to receive driving and working instructions sent by the server and control the unmanned roller to roll the construction area. At the same time, the control and signal processing module is used to receive data collected by infrared temperature collection equipment, ambient temperature detection equipment, steel wheel temperature monitoring equipment, compaction monitoring equipment and vehicle-mounted laser radar equipment, and upload the data to the server.

[0007] The server is used to generate driving and working instructions for the unmanned roller and send the instructions to the unmanned roller. At the same time, the server is used to receive data uploaded by the control and signal processing module, decode and organize the data, and generate the next stage of driving and working instructions for the unmanned roller based on the data.

[0008] Furthermore, infrared temperature acquisition equipment, ambient temperature detection equipment, steel wheel temperature monitoring equipment, compaction degree monitoring equipment, vehicle-mounted laser radar equipment, and control and signal processing modules are installed on the unmanned roller;

[0009] The infrared temperature acquisition device is used to obtain the road surface temperature at the construction site and transmit the collected data to the control and signal processing module;

[0010] The ambient temperature detection equipment is used to obtain the ambient temperature of the construction site and transmit the collected data to the control and signal processing module;

[0011] The steel wheel temperature monitoring equipment is used to obtain the steel wheel temperature during construction and transmit the collected data to the control and signal processing module;

[0012] The compaction monitoring equipment is used to measure the actual compaction degree of the asphalt concrete pavement during the compaction process and transmit the collected data to the control and signal processing module;

[0013] The vehicle-mounted LiDAR device is used to obtain the elevation information of the asphalt concrete pavement after compaction by the unmanned roller and transmit the collected data to the control and signal processing module;

[0014] The control and signal processing module is used to receive instructions sent by the server and control the unmanned roller to work according to the instructions. At the same time, the control and signal processing module is used to receive data collected by infrared temperature acquisition equipment, ambient temperature detection equipment, steel wheel temperature monitoring equipment, compaction monitoring equipment, and vehicle-mounted lidar equipment, and package the data information and location information into structured data, and then upload it to the server.

[0015] Furthermore, the unmanned roller is a vibratory roller, including a single steel wheel roller, a double steel wheel roller, a single wheel drive roller, a double wheel drive roller, a light roller, a small roller, a medium roller or a heavy roller.

[0016] Furthermore, the program deployed on the server records the driving trajectory of the unmanned roller, the number of compaction passes in the construction area, and processes the information uploaded by multiple unmanned rollers. It records the road surface temperature information, ambient temperature information, and steel wheel temperature information separately, and splices them into the asphalt pavement construction temperature field according to the time and space dimensions; organizes and splices the actual compaction information of asphalt concrete into the compaction field; and organizes and splices the elevation information of the asphalt concrete pavement into the flatness field.

[0017] Furthermore, the control and signal processing module includes a Beidou positioning submodule, an information receiving submodule, an information sending submodule, an AI processor submodule, and a control submodule, wherein:

[0018] The Beidou positioning submodule is used to obtain the location information of the unmanned roller;

[0019] The information receiving submodule is used to receive information sent by the server;

[0020] The information sending submodule is used to upload information to the server;

[0021] The AI ​​processor submodule is used to process and encode the received road surface temperature information, ambient temperature information, steel wheel temperature information, compaction information, and road surface elevation information, and package the data and location information into structured data. At the same time, it decodes the received server instructions and generates corresponding control instructions to transmit to the control submodule;

[0022] The control submodule is used to control the driving direction, driving speed and excitation frequency of the unmanned roller.

[0023] The present invention also provides an intelligent construction control method based on the unmanned asphalt pavement compaction system, comprising the following steps:

[0024] Step S1: Generate a fixed strategy to control the operation of the unmanned roller based on the on-site construction conditions. The monitoring equipment on the unmanned roller is used to obtain actual monitoring data, including road surface temperature, ambient temperature, steel wheel temperature, road surface compaction, and road surface smoothness.

[0025] Step S2: Select a test section and obtain comprehensive test data of the test section. The comprehensive test data includes the unmanned roller under ideal working conditions at the standard rolling speed v s The road surface temperature, ambient temperature and steel wheel temperature collected during driving are used to establish a standard state matrix of temperature data And establish its mapping association with the standard rolling progress, and establish the actual temperature state matrix according to the monitoring data during the actual rolling operation Associated with the mapping of real-time rolling progress, calculate the current rolling progress corresponding and Dynamically adjust the rolling speed based on the real-time status difference;

[0026] Step S3: Select a test section and obtain the compaction test data of the test section. The compaction test data includes the standard rolling excitation force F of the unmanned roller under ideal working conditions. S The road surface compaction degree under the current rolling number collected by rolling is used to establish the standard state vector of compaction degree data And establish its mapping association with the standard rolling progress. During the actual rolling operation, the actual compaction state vector is established based on the monitoring data. Associated with the mapping of real-time rolling progress, calculate the current progress corresponding and Dynamically adjust the rolling excitation force based on the real-time status difference;

[0027] Step S4: adjusting the rolling path of the unmanned roller according to the flatness of the asphalt concrete pavement in the flatness field to obtain a dynamically adjusted rolling path;

[0028] Step S5: Generate dynamic driving guidance information for the unmanned roller based on the dynamically adjusted rolling speed, the dynamically adjusted exciting force, and the dynamically adjusted rolling path, so that the unmanned roller can adjust its working parameters and perform construction.

[0029] Furthermore, the step S2 specifically includes:

[0030] Establishing a standard state matrix of temperature data under ideal working conditions in Including standard road surface temperature T P ' , Standard ambient temperature T e ' , Standard steel wheel temperature T ' W ; When the unmanned roller is working on site, the actual temperature state matrix is ​​obtained in Including actual road surface temperature T P , actual ambient temperature T e , actual steel wheel temperature T W ; Then according to the standard state matrix The difference between the actual temperature state matrix The rolling speed v is adjusted using the following formula:

[0031] V=V S +k1(T P -T P ' )+k2(T e -T e ')+k3(T w -T w ' )

[0032] Among them, k1 is the adjustment coefficient of the difference between the actual value and the standard value of the speed and the road surface temperature, k2 is the adjustment coefficient of the difference between the actual value and the standard value of the speed and the ambient temperature, and k3 is the adjustment coefficient of the difference between the actual value and the standard value of the speed and the steel wheel temperature.

[0033] Furthermore, the step S3 specifically includes:

[0034] Establishing the standard state vector of pavement compaction under ideal working conditions Unmanned roller (1) during on-site construction Get the actual compaction state vector, and then according to the standard state vector and the actual compaction state vector The excitation force F is adjusted according to the difference in the excitation force, using the following formula:

[0035]

[0036] Where a is the adjustment coefficient of the difference between the exciting force and the actual and standard values ​​of the pavement compaction.

[0037] Furthermore, the step S4 specifically includes:

[0038] For locally uneven road sections, adjacent unmanned rollers are dispatched to repeatedly roll the locally uneven sections until the height difference in the locally uneven sections is eliminated; for regular unevenness on road sections caused by segregation of paver materials, the paths of all unmanned rollers are replanned, and the unevenness of the road sections is eliminated by reasonably designing the driving paths of the unmanned rollers.

[0039] Furthermore, the step S5 specifically includes:

[0040] The dynamically adjusted rolling path is converted into discrete position points at fixed time intervals. The offset angle of the unmanned roller's steering wheel is calculated based on the orientation of the unmanned roller's steel wheel center and the path position point, thereby controlling the driving direction of the unmanned roller. The relevant parameters of the unmanned roller's speed clutch are set according to the dynamically adjusted rolling speed, thereby controlling the driving speed of the unmanned roller. The excitation frequency of the unmanned roller is set according to the dynamically adjusted excitation force.

[0041] Beneficial effects of the present invention: The present invention realizes multi-source perception of the construction site by setting up a variety of temperature acquisition equipment, compaction monitoring equipment, and vehicle-mounted laser radar equipment, and records the road surface temperature information, ambient temperature information, and steel wheel temperature information separately, and splices them into an asphalt pavement construction temperature field according to the time and space dimensions; organizes and splices the actual compaction information of asphalt concrete into a compaction field; and organizes and splices the elevation information of asphalt concrete pavement into a flatness field, ensuring that the road surface compaction quality can be monitored in real time. At the same time, through the processing of the above data, effective data support is provided for the dynamic adjustment of various parameters of the unmanned roller. In addition, through the dynamic intelligent construction control method of the unmanned roller, based on the multi-source perception data acquired in real time, by establishing a mapping association between the operating temperature information and the operating progress, and a mapping association between the compaction degree and the operating progress, the difference between the actual operating temperature and the ideal operating temperature, and the difference between the actual compaction degree and the ideal compaction degree are calculated, and the speed and exciting force parameters that need to be adjusted are obtained to improve the degree of consistency between the actual working conditions and the ideal working conditions, and avoid construction quality problems caused by parameter errors. By dynamically adjusting the driving and working parameters of the unmanned roller through the above method, the adaptability of the unmanned roller in asphalt pavement compaction under different working conditions is improved, and the construction quality is further guaranteed. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 This is a schematic diagram of the principle of an unmanned asphalt pavement compaction system according to an embodiment of the present invention;

[0043] Figure 2 This is a schematic diagram of the locations where the infrared temperature acquisition device, ambient temperature detection device, steel wheel temperature monitoring device, compaction degree monitoring device, vehicle-mounted laser radar device, and control and signal processing module are installed on a road roller according to an embodiment of the present invention;

[0044] Figure 3 Schematic diagram of the control and signal processing module according to an embodiment of the present invention;

[0045] Figure 4 Schematic diagram of the control method flow in an embodiment of the present invention. DETAILED DESCRIPTION

[0046] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0047] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to specific embodiments.

[0048] like Figures 1 to 3As shown, an unmanned asphalt pavement compaction system includes an unmanned roller 1, a server 2, an infrared temperature acquisition device 11, an ambient temperature detection device 12, a steel wheel temperature monitoring device 13, a compaction degree monitoring device 14, an on-board laser radar device 15, and a control and signal processing module 16, wherein: the control and signal processing module 16 is used to receive driving and working instructions sent by the server 2, and control the unmanned roller 1 to compact the construction area; at the same time, the control and signal processing module 16 is used to receive data collected by the infrared temperature acquisition device 11, the ambient temperature detection device 12, the steel wheel temperature monitoring device 13, the compaction degree monitoring device 14, and the on-board laser radar device 15, and upload the data to the server 2;

[0049] Server 2 is used to generate driving and working instructions for the unmanned roller 1 and send the instructions to the unmanned roller 1. At the same time, server 2 is used to receive data uploaded by the control and signal processing module 16, decode and organize the data, and generate driving and working instructions for the unmanned roller 1 in the next stage based on the data.

[0050] As a preferred embodiment, Figure 2 As shown, an infrared temperature acquisition device 11, an ambient temperature detection device 12, a steel wheel temperature monitoring device 13, a compaction degree monitoring device 14, an on-board laser radar device 15, and a control and signal processing module 16 are installed on the unmanned roller 1;

[0051] The infrared temperature acquisition device 11 is used to obtain the road surface temperature at the construction site and transmit the collected data to the control and signal processing module 16;

[0052] The ambient temperature detection device 12 is used to obtain the ambient temperature of the construction site and transmit the collected data to the control and signal processing module 16;

[0053] The steel wheel temperature monitoring device 13 is used to obtain the steel wheel temperature during the construction process and transmit the collected data to the control and signal processing module 16;

[0054] The compaction monitoring device 14 is used to measure the actual compaction degree of the asphalt concrete pavement during the compaction process and transmit the collected data to the control and signal processing module 16;

[0055] The vehicle-mounted laser radar device 15 is used to obtain the elevation information of the asphalt concrete pavement after compaction by the unmanned roller 1 and transmit the collected data to the control and signal processing module 16;

[0056] The control and signal processing module 16 is used to receive instructions sent by the server 2, and control the unmanned roller 1 to work according to the instructions. At the same time, the control and signal processing module 16 is used to receive data collected by the infrared temperature acquisition device 11, the ambient temperature detection device 12, the steel wheel temperature monitoring device 13, the compaction monitoring device 14, and the vehicle-mounted lidar device 15, and package the data information and location information into structured data, and then upload it to the server 2.

[0057] As a preferred embodiment, the unmanned roller 1 is a vibratory roller, including a single steel wheel roller, a double steel wheel roller, a single wheel drive roller, a double wheel drive roller, a light roller, a small roller, a medium roller or a heavy roller.

[0058] As a preferred embodiment, the program deployed on server 2 records the driving trajectory of the unmanned roller 1 and the number of compaction passes in the construction area. It also processes the information uploaded by multiple unmanned rollers 1. It records road surface temperature, ambient temperature, and steel drum temperature separately and splices them into an asphalt pavement construction temperature field based on time and space. It then organizes the actual asphalt concrete compaction degree information into a compaction degree field, and organizes the asphalt concrete pavement elevation information into a flatness field.

[0059] As a preferred embodiment, Figure 3 As shown, the control and signal processing module 16 includes a Beidou positioning submodule 161, an information receiving submodule 162, an information sending submodule 163, an AI processor submodule 164 and a control submodule 165, wherein:

[0060] The Beidou positioning submodule 161 is used to obtain the location information of the unmanned roller 1;

[0061] The information receiving submodule 162 is used to receive information sent by the server 2;

[0062] The information sending submodule 163 is used to upload information to the server 2;

[0063] The AI ​​processor submodule 164 is used to process and encode the received road surface temperature information, ambient temperature information, steel wheel temperature information, compaction information, and road surface elevation information, and package the data and location information into structured data. At the same time, it decodes the instructions received from the server 2 and generates corresponding control instructions to transmit to the control submodule 165;

[0064] The control submodule 165 is used to control the driving direction, driving speed and excitation frequency of the unmanned roller 1 .

[0065] As a preferred embodiment, multiple infrared temperature acquisition devices 11, compaction monitoring devices 14, and vehicle-mounted LiDAR devices 15 are deployed to achieve multi-source sensing of the construction site. Road surface temperature, ambient temperature, and steel wheel temperature information are recorded separately and spliced ​​together according to time and space to form an asphalt pavement construction temperature field. Actual asphalt concrete compaction information is collated and spliced ​​into a compaction field. Elevation information on the asphalt concrete pavement is collated and spliced ​​into a flatness field. This ensures real-time monitoring of pavement compaction quality and provides effective data support for dynamic adjustment of various parameters of the unmanned roller through the processing of this data.

[0066] like Figure 4 As shown, a dynamic intelligent construction control method for controlling the above-mentioned unmanned roller includes the following steps:

[0067] Step S1: Generate a fixed strategy to control the driving of the unmanned roller 1 according to the on-site construction conditions. The monitoring equipment mounted on the unmanned roller 1 is used to obtain actual monitoring data, which includes road surface temperature, ambient temperature, steel wheel temperature, road surface compaction, and road surface flatness.

[0068] Step S2: Select a test section and obtain comprehensive test data of the test section. The comprehensive test data includes the unmanned roller 1 under ideal working conditions at the standard rolling speed v s The road surface temperature, ambient temperature and steel wheel temperature collected during driving are used to establish a standard state matrix of temperature data And establish its mapping association with the standard rolling progress, and establish the actual temperature state matrix according to the monitoring data during the actual rolling operation Associated with the mapping of real-time rolling progress, calculate the current rolling progress corresponding and The rolling speed is dynamically adjusted based on the real-time state difference to improve the consistency between the state vector of the current rolling progress and the ideal working condition corresponding rolling progress, thus avoiding construction quality problems caused by temperature deviation;

[0069] Step S3: Select a test section and obtain the compaction test data of the test section. The compaction test data includes the standard rolling excitation force F of the unmanned roller under ideal working conditions. S The road surface compaction degree under the current rolling number collected by rolling is used to establish the standard state vector of compaction degree data And establish its mapping association with the standard rolling progress. During the actual rolling operation, the actual compaction state vector is established based on the monitoring data. Associated with the mapping of real-time rolling progress, calculate the current progress corresponding and Dynamically adjust the rolling excitation force based on the real-time status difference;

[0070] Step S4: adjusting the rolling path of the unmanned roller according to the flatness of the asphalt concrete pavement in the flatness field to obtain a dynamically adjusted rolling path;

[0071] Step S5: Generate dynamic driving guidance information for the unmanned roller based on the dynamically adjusted rolling speed, the dynamically adjusted exciting force, and the dynamically adjusted rolling path, so that the unmanned roller can adjust its working parameters and perform construction.

[0072] In this embodiment, the above step S2 specifically includes the following contents:

[0073] Establishing a standard state matrix of temperature data under ideal working conditions in Including standard road surface temperature T P ' , Standard ambient temperature T e ' , Standard steel wheel temperature T ' W ; When the unmanned roller is working on site, the actual temperature state matrix is ​​obtained in Including actual road surface temperature T P , actual ambient temperature T e , actual steel wheel temperature T W ; Then according to the standard state matrix The difference between the actual temperature state matrix The rolling speed v is adjusted using the following formula:

[0074] V=V S +k1(T P -T P ' )+k2(T e -T e ' )+k3(T w -T w ' )

[0075] Among them, k1 is the adjustment coefficient of the difference between the actual value and the standard value of the speed and the road surface temperature, k2 is the adjustment coefficient of the difference between the actual value and the standard value of the speed and the ambient temperature, and k3 is the adjustment coefficient of the difference between the actual value and the standard value of the speed and the steel wheel temperature.

[0076] Furthermore, the step S3 specifically includes:

[0077] Establishing the standard state vector of pavement compaction under ideal working conditions Unmanned roller (1) during on-site construction Get the actual compaction state vector, and then according to the standard state vector and the actual compaction state vector The excitation force F is adjusted according to the difference in the excitation force, using the following formula:

[0078]

[0079] Where a is the adjustment coefficient of the difference between the exciting force and the actual and standard values ​​of the pavement compaction.

[0080] In this embodiment, the above step S4 specifically includes the following contents:

[0081] For locally uneven sections, adjacent unmanned rollers 1 are dispatched to prioritize and repeatedly roll the uneven areas until the elevation difference is eliminated. For regular unevenness caused by paver material segregation, the paths of all unmanned rollers 1 are replanned, and the unevenness is eliminated through the rational design of their travel paths.

[0082] In this embodiment, the above step S5 specifically includes the following contents:

[0083] The dynamically adjusted rolling path is converted into discrete locations at fixed time intervals. The steering wheel offset angle of the unmanned roller 1 is calculated based on the orientation of the center of the unmanned roller's steel drum relative to the path location points, thereby controlling the roller's travel direction. The relevant parameters of the unmanned roller's speed clutch are set based on the dynamically adjusted rolling speed, thereby controlling the roller's travel speed. The excitation frequency of the unmanned roller 1 is set based on the dynamically adjusted excitation force. Through the intelligent control construction method for an unmanned asphalt pavement compaction system for urban renewal, based on real-time multi-source sensor data, mappings are established between operating temperature information and operating progress, and between compaction degree and operating progress. The differences between the actual and ideal operating temperatures, as well as the actual and ideal compaction degrees, are calculated to determine the speed and excitation force parameters that require adjustment. This improves the consistency between actual and ideal operating conditions and avoids construction quality issues caused by parameter errors. By dynamically adjusting the driving and operating parameters of the unmanned roller, the unmanned roller's adaptability to asphalt pavement compaction under different operating conditions is improved, further ensuring construction quality.

[0084] Those skilled in the art should understand that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of the present invention is limited to these examples. Within the scope of the present invention, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of the different aspects of the present invention as described above. The present invention is intended to cover all such substitutions, modifications, and variations that fall within the broad scope of the claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. An intelligent control construction method for an unmanned asphalt pavement compaction system for urban renewal, characterized in that: The following steps are involved: Step S1: generating a fixed strategy to control the driving of the unmanned roller (1) according to the on-site construction conditions, wherein the monitoring equipment mounted on the unmanned roller (1) is used to obtain actual monitoring data, the actual monitoring data including road surface temperature, ambient temperature, steel wheel temperature, road surface compaction degree, and road surface flatness; Step S2: Select a test section and obtain comprehensive test data of the test section. The comprehensive test data includes the unmanned roller (1) under ideal working conditions at the standard rolling speed v s The road surface temperature, ambient temperature and steel wheel temperature collected during driving are used to establish a standard state matrix of temperature data And establish its mapping association with the standard rolling progress, and establish the actual temperature state matrix according to the monitoring data during the actual rolling operation Associated with the mapping of real-time rolling progress, calculate the current rolling progress corresponding and Dynamically adjust the rolling speed based on the real-time status difference; Step S3: Select a test section and obtain the compaction test data of the test section. The compaction test data includes the compaction force F of the unmanned roller (1) under ideal working conditions according to the standard rolling excitation force F. S The road surface compaction degree under the current rolling number collected by rolling is used to establish the standard state vector of compaction degree data And establish its mapping association with the standard rolling progress. During the actual rolling operation, the actual compaction state vector is established based on the monitoring data. Associated with the mapping of real-time rolling progress, calculate the current progress corresponding and Dynamically adjust the rolling excitation force based on the real-time status difference; Step S4: adjusting the rolling path of the unmanned roller (1) according to the flatness of the asphalt concrete pavement in the flatness field to obtain a dynamically adjusted rolling path; Step S5: generating dynamic driving guidance information for the unmanned roller (1) based on the dynamically adjusted rolling speed, the dynamically adjusted exciting force, and the dynamically adjusted rolling path, so as to enable the unmanned roller (1) to adjust working parameters and perform construction.

2. The intelligent control construction method of the unmanned asphalt pavement compaction system for urban renewal according to claim 1 is characterized in that: The step S2 specifically includes: establishing a standard state matrix of temperature data under ideal working conditions in Including standard road surface temperature T P ' , Standard ambient temperature T e ' , Standard steel wheel temperature T ' W ; When the unmanned roller (1) is working on site, the actual temperature state matrix is ​​obtained in Including actual road surface temperature T P , actual ambient temperature T e , actual steel wheel temperature T W ; Then according to the standard state matrix The difference between the actual temperature state matrix The rolling speed v is adjusted using the following formula: V=V S +k1(T P -T P ' )+k2(T e -T e ' )+k3(T w -T w ' ) Among them, k1 is the adjustment coefficient of the difference between the actual value and the standard value of the speed and the road surface temperature, k2 is the adjustment coefficient of the difference between the actual value and the standard value of the speed and the ambient temperature, and k3 is the adjustment coefficient of the difference between the actual value and the standard value of the speed and the steel wheel temperature.

3. The intelligent control construction method of the unmanned asphalt pavement compaction system for urban renewal according to claim 1 is characterized in that: The step S3 specifically includes: Establishing the standard state vector of pavement compaction under ideal working conditions Unmanned roller (1) during on-site construction Get the actual compaction state vector, and then according to the standard state vector and the actual compaction state vector The excitation force F is adjusted according to the difference in the excitation force, using the following formula: Where a is the adjustment coefficient of the difference between the exciting force and the actual and standard values ​​of the pavement compaction.

4. The intelligent control construction method of the unmanned asphalt pavement compaction system for urban renewal according to claim 1 is characterized in that: The step S4 specifically includes: For a locally uneven road section, the adjacent unmanned roller (1) is dispatched to preferentially perform repeated rolling on the locally uneven section until the height difference of the locally uneven section is eliminated; In case of regular unevenness of road sections caused by segregation of materials used in paving machines, the paths of all unmanned rollers (1) are replanned, and the unevenness of road sections is eliminated by rationally designing the driving paths of the unmanned rollers (1).

5. The intelligent control construction method of the unmanned asphalt pavement compaction system for urban renewal according to claim 1 is characterized in that: The step S5 specifically includes: converting the dynamically adjusted rolling path into discrete position points at fixed time intervals; calculating the offset angle of the steering wheel of the unmanned roller (1) according to the position of the center of the steel wheel of the unmanned roller (1) and the position point on the path, thereby controlling the driving direction of the unmanned roller (1); setting the relevant parameters of the speed clutch of the unmanned roller (1) according to the dynamically adjusted rolling speed, thereby controlling the driving speed of the unmanned roller (1); and setting the excitation frequency of the unmanned roller (1) according to the dynamically adjusted excitation force.

6. An unmanned asphalt pavement compaction system for executing the intelligent control construction method of the urban renewal unmanned asphalt pavement compaction system according to any one of claims 1 to 5, characterized in that: The invention comprises an unmanned roller (1), a server (2), an infrared temperature acquisition device (11), an ambient temperature detection device (12), a steel wheel temperature monitoring device (13), a compaction degree monitoring device (14), an on-board laser radar device (15), and a control and signal processing module (16), wherein: The control and signal processing module (16) is used to receive the driving and working instructions sent by the server (2), and control the unmanned roller (1) to roll the construction area; at the same time, the control and signal processing module (16) is used to receive data collected by the infrared temperature acquisition device (11), the ambient temperature detection device (12), the steel wheel temperature monitoring device (13), the compaction degree monitoring device (14) and the vehicle-mounted laser radar device (15), and upload the data to the server (2); The server (2) is used to generate driving and working instructions for the unmanned roller (1) and send the instructions to the unmanned roller (1). At the same time, the server (2) is used to receive data uploaded by the control and signal processing module (16), decode and organize the data, and generate driving and working instructions for the unmanned roller (1) in the next stage based on the data.

7. The unmanned asphalt pavement compaction system according to claim 6, characterized in that: An infrared temperature acquisition device (11), an ambient temperature detection device (12), a steel wheel temperature monitoring device (13), a compaction degree monitoring device (14), an on-board laser radar device 15), and a control and signal processing module (16) are installed on the unmanned roller (1); The infrared temperature acquisition device (11) is used to obtain the road surface temperature at the construction site and transmit the acquired data to the control and signal processing module (16); The ambient temperature detection device (12) is used to obtain the ambient temperature of the construction site and transmit the collected data to the control and signal processing module (16); The steel wheel temperature monitoring device (13) is used to obtain the steel wheel temperature during the construction process and transmit the collected data to the control and signal processing module (16); The compaction monitoring device (14) is used to measure the actual compaction degree of the asphalt concrete pavement during the compaction process and transmit the collected data to the control and signal processing module (16); The vehicle-mounted laser radar device (15) is used to obtain elevation information of the asphalt concrete pavement after compaction by the unmanned roller (1), and transmit the collected data to the control and signal processing module (16); The control and signal processing module (16) is used to receive instructions sent by the server (2) and control the unmanned roller (1) to operate according to the instructions. At the same time, the control and signal processing module (16) is used to receive data collected by the infrared temperature acquisition device (11), the ambient temperature detection device (12), the steel wheel temperature monitoring device (13), the compaction degree monitoring device (14), and the vehicle-mounted laser radar device (15), and package the data information and position information into structured data, and then upload it to the server (2).

8. The unmanned asphalt pavement compaction system according to claim 7, characterized in that: The control and signal processing module (16) includes a Beidou positioning submodule (161), an information receiving submodule (162), an information sending submodule (163), an AI processor submodule (164) and a control submodule (165), wherein; The Beidou positioning submodule (161) is used to obtain the position information of the unmanned roller (1); The information receiving submodule (162) is used to receive information sent by the server (2); The information sending submodule (163) is used to upload information to the server (2); The AI ​​processor submodule (164) is used to process and encode the received road surface temperature information, ambient temperature information, steel wheel temperature information, compaction information, and road surface elevation information, and package the data and position information into structured data, and decode the received instructions from the server (2), generate corresponding control instructions, and transmit them to the control submodule (165); The control submodule (165) is used to control the driving direction, driving speed and excitation frequency of the unmanned roller (1).

9. The unmanned asphalt pavement compaction system according to claim 7, characterized in that: The program deployed on the server (2) records the driving trajectory of the unmanned roller (1), records the number of compaction passes in the construction area, and processes the information uploaded by multiple unmanned rollers (1), records the road surface temperature information, the ambient temperature information, and the steel wheel temperature information respectively, and splices them into an asphalt pavement construction temperature field according to the time and space dimensions; organizes and splices the actual compaction degree information of the asphalt concrete into a compaction degree field; and organizes and splices the elevation information of the asphalt concrete pavement into a flatness field.

10. The unmanned asphalt pavement compaction system according to claim 6, characterized in that: The unmanned roller (1) is a vibratory roller, including a single steel wheel roller, a double steel wheel roller, a single wheel drive roller, a double wheel drive roller, a light roller, a small roller, a medium roller or a heavy roller.

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