In-place heat regeneration machine group control method, control system and readable storage medium

Abstract

The invention discloses a hot in-place recycling cluster control method, which comprises the following steps of: importing a global task plan of a cluster into a central control unit, and distributing a refined single-machine task strategy to a plurality of single-machine control units; performing global task planning and time synchronous scheduling on the plurality of unmanned machines in the machine group by using the central control unit according to the global task planning, wherein the global task planning comprises the following steps: allocating an optimal path for the plurality of unmanned machines; a starting instruction, a speed adjusting instruction, a vehicle distance adjusting instruction and a track adjusting instruction are sent to the designated unmanned machine through the corresponding single machine control unit; and in response to a fault of the central control unit, independently carrying out emergency path planning and scheduling on the unmanned machines to which the single-machine control units belong according to the corresponding single-machine task strategies by utilizing the single-machine control units. According to the invention, efficient, safe and unmanned control of the in-place heat regeneration machine group is realized, the working efficiency and quality of road maintenance construction can be improved, and the safety risk can also be reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of road maintenance construction, and particularly relates to a control method, a control system and a readable storage medium for an in-situ hot recycling machine fleet. Background Art

[0002] With the continuous development of automation and intelligent technologies, the application of driverless machines in fields such as road maintenance construction is becoming increasingly widespread. Especially in complex construction processes such as in-situ hot recycling, the traditional manual driving operation mode has problems such as low work efficiency and high safety risks, and can no longer meet the requirements of modern road maintenance construction.

[0003] In the prior art, although there have been some studies on the control of driverless machines and the scheduling of machine fleets, these studies often only focus on a specific aspect, such as path planning, collision avoidance, etc., and lack comprehensive consideration of the overall control system. In addition, the driverless machine control systems in the prior art often have problems such as slow response speed and poor coordination ability, and cannot meet the real-time control and coordinated operation requirements in complex construction environments. Summary of the Invention

[0004] The purpose of the present invention is to provide a control method, a control system and a readable storage medium for an in-situ hot recycling machine fleet, to achieve efficient, safe and unmanned control of the in-situ hot recycling machine fleet, which can improve the work efficiency and quality of road maintenance construction, and can also reduce safety risks, providing strong support for the automation and intelligent development in the field of road maintenance construction.

[0005] To achieve the above purpose, the present invention provides a control method for an in-situ hot recycling machine fleet, including:

[0006] Importing the global task plan of the machine fleet into the central control unit, and allocating the refined single-machine task strategy to multiple single-machine control units, wherein the central control unit is configured in the main control center, the single-machine control units are dispersedly configured in multiple sub-control centers, and the central control unit and the multiple single-machine control units form a task scheduling system;

[0007] Using the central control unit to perform global task planning and time synchronization scheduling on multiple driverless machines in the machine fleet according to the global task plan, wherein the global task plan includes:

[0008] Allocating the optimal path for multiple driverless machines;

[0009] Using the corresponding single-machine control unit to send a start instruction, a speed adjustment instruction, a vehicle spacing adjustment instruction and a trajectory adjustment instruction to the specified driverless machine to drive the specified driverless machine to run according to the established path;

[0010] In response to a failure of the central control unit, each stand-alone control unit independently performs emergency path planning and scheduling for the affiliated driverless machine according to the corresponding stand-alone task strategy.

[0011] As a further solution of the present invention: before global task planning and time synchronization scheduling, system testing is performed, including:

[0012] Performing status detection on the driverless machines configured in each stand-alone unit to confirm whether they meet the operation conditions;

[0013] Performing status detection on the stand-alone control units configured in each stand-alone unit to confirm whether they can normally execute control instructions;

[0014] Performing status detection on the power supply systems configured in each stand-alone unit to confirm whether they can normally supply power;

[0015] If any driverless machine failure, control system failure, or power supply system does not meet the operation conditions is detected, the corresponding stand-alone unit is marked as a failure area, and the path planning for the driverless machine in the failure area is cancelled;

[0016] For non-failure areas, activate the corresponding power supply system according to the global task planning to ensure that the driverless machine can run along the established path.

[0017] As a further solution of the present invention: the steps for the driverless machine to run along the specified path:

[0018] Send a running command to the corresponding driverless machine according to the optimal path to control the driverless machine to run at the established speed and direction;

[0019] Send a running command to the corresponding stand-alone control unit according to the optimal path, and control the corresponding stand-alone control unit to make corresponding judgments and control outputs according to the formulated requirements;

[0020] The specific steps are as follows:

[0021] Use the corresponding stand-alone control unit to determine the initial position of the driverless machine through preliminary positioning;

[0022] According to the expected running direction, control the driverless machine to pass through an absolute positioning mark to obtain its actual position;

[0023] Judge the actual driving direction of the driverless machine according to the initial position and the actual position;

[0024] In response to the actual driving direction being inconsistent with the direction indicated by the running command, force the driverless machine to stop, and send a running command containing a new direction to the stand-alone control unit;

[0025] Output a new control command to the driverless machine at the corresponding position according to the new direction and the actual position, so as to control it to run in the new direction.

[0026] As a further solution of the present invention: when the driverless machine is running, use the corresponding single-machine control unit to correct the position information of the driverless machine according to the ground markings;

[0027] Control the driverless machine to run on the established path according to the corrected position information;

[0028] A plurality of virtual position markings are arranged on the established trajectory, and the driverless machines in each single machine update their optimal driving postures in real time by reading the information of the virtual position markings.

[0029] As a further solution of the present invention: the steps for the driverless machine to run on the established trajectory:

[0030] Obtain the real-time position and driving speed of the driverless machine;

[0031] According to the real-time position and driving speed, calculate the expected time and the optimal driving posture for the driverless machine to reach the next virtual position marking;

[0032] Send the calculated optimal driving posture information to the control system of the corresponding driverless machine to drive the driverless machine to run along the established trajectory and in the optimal driving posture.

[0033] As a further solution of the present invention: when the driverless machine reaches the target point or the end point of the established trajectory, perform the following steps:

[0034] Use the self-checking system of the driverless machine to control it to enter the standby state and perform maintenance operations;

[0035] At the same time, before the driverless machine enters the standby state, record its current position as a new virtual position marking, so as to optimize the driving path and attitude control in subsequent tasks;

[0036] Send the information of the new virtual position marking to the fleet control system to update the operation strategy and path planning of the entire fleet.

[0037] As a further solution of the present invention: the main control center is configured with a construction management system, and uses the construction management system to collect the status information of all ground equipment and all vehicle-mounted equipment of the fleet, display the status information on the display interface of the main control center, and adjust the global path planning and time synchronization scheduling formulated by the central control unit according to the management instructions input by the management personnel through the man-machine interaction interface.

[0038] As a further solution of the present invention: when the job end instruction is triggered:

[0039] The single - machine control unit sends an instruction to exit the autonomous driving state to the driverless machines within all single - machines;

[0040] The task scheduling system detects whether each driverless machine has successfully exited the autonomous driving state;

[0041] If it is detected that any driverless machine fails to successfully exit the autonomous driving state, the single - machine control unit will send an emergency stop instruction to ensure that the driverless machine stops moving immediately.

[0042] To achieve the above object, the present invention also provides a fleet control system, including a processor and its connected positioning and orientation device, communication device, display, and memory; the processor is configured to execute the above - mentioned fleet control method.

[0043] To achieve the above object, the present invention also provides a readable storage medium, on which computer instructions are stored, and when the computer instructions are executed by a processor, the above - mentioned fleet control method is implemented

[0044] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0045] By integrating autonomous driving technology, fleet scheduling and control, and network communication and data transmission technology, efficient, safe, and unmanned control of in - place hot recycling fleets is achieved. The present invention not only improves the work efficiency and quality of road maintenance construction, but also reduces safety risks, providing strong support for the automation and intelligent development in the field of road maintenance construction.

[0046] The present invention not only has advantages such as fast response speed and strong coordination ability, but also can be flexibly adjusted and optimized according to actual construction requirements, improving the operation efficiency and safety of the entire fleet. At the same time, the present invention also realizes real - time monitoring and management of the entire fleet through technical means such as introducing a construction management system and a human - machine interaction interface, providing a more convenient and efficient management means for road maintenance construction. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a schematic diagram of the execution path of the driverless operation of the in - place hot recycling fleet of the present invention;

[0048] Figure 2 It is a schematic diagram of the display interface of the central control unit of the present invention;

[0049] Figure 3 It is a schematic diagram of the display interface of the single - machine control unit of the present invention.

[0050] Figure 4 It is a schematic diagram of the speed membership degree of the present invention.

[0051] Figure 5Schematic diagram of the membership degree of the vehicle distance for the present invention.

[0052] Figure 6 Schematic diagram of the membership degree of the lateral deviation for the present invention. Specific embodiments

[0053] The present invention will be further described below through embodiments.

[0054] A control method for an in-situ hot recycling machine fleet includes:

[0055] Importing the global task plan of the machine fleet into the central control unit and allocating the refined single-machine task strategies to multiple single-machine control units. Among them, the central control unit is configured in the main control center, and the single-machine control units are dispersedly configured in multiple sub-control centers. The central control unit and multiple single-machine control units form a task scheduling system;

[0056] Using the central control unit to perform global task planning and time synchronization scheduling on multiple unmanned machines in the machine fleet. Among them, the global task planning includes:

[0057] Allocating the optimal path for multiple unmanned machines;

[0058] Using the corresponding single-machine control unit to send start commands, speed adjustment commands, vehicle distance adjustment commands, and trajectory adjustment commands to the specified unmanned machine to drive the specified unmanned machine to run along the established path;

[0059] In response to a failure of the central control unit, using each single-machine control unit to independently perform emergency path planning and scheduling on the affiliated unmanned machine according to the corresponding single-machine task strategy;

[0060] The time synchronization scheduling includes:

[0061] Real-time monitoring of the control commands received by each device controller for each of the unmanned machines;

[0062] Judging whether the received control commands have time consistency, that is, whether they meet the predetermined time synchronization requirements;

[0063] If the control commands do not have time consistency, set a protection period, and adjust the control of the unmanned machine within this protection period to ensure that the control instructions are strictly issued according to the cycle period;

[0064] Monitor and track the time synchronization of each unmanned machine according to its position, driving speed, and control adjustment situation within the cycle period;

[0065] Based on the results of monitoring and tracking, determine the time deviation of each unmanned machine and perform time adjustment to formulate an automatically adjusted time scheduling instruction, so as to ensure the synchronous operation of the entire fleet in terms of time.

[0066] Furthermore, conduct system testing before global task planning and time synchronization scheduling, including:

[0067] Detect the status of the unmanned machines configured on each individual unit to confirm whether they meet the operating conditions;

[0068] Detect the status of the single-unit control unit configured on each individual unit to confirm whether it can execute control instructions normally;

[0069] Detect the status of the power supply system configured on each individual unit to confirm whether it can supply power normally;

[0070] Specifically, the steps for detecting the status of the power supply system include:

[0071] Perform preliminary activation on the power supply system;

[0072] Use the task scheduling system to send a status conversion command to the power supply system to convert the power supply system to the test mode;

[0073] Test whether each power output point of the power supply system is normal through the power circulation link, and test whether each power switch is in normal contact;

[0074] Feed back the test results to the corresponding single-unit control unit for the task scheduling system to evaluate the performance of the power supply system of the corresponding single unit according to the test results;

[0075] In response to the performance of the power supply system of any single unit being lower than the preset standard, determine that the status of the power supply system of that single unit does not meet the operating conditions;

[0076] If any unmanned machine failure, control system failure, or power supply system not meeting the operating conditions is detected, mark the corresponding single unit as a failure area and cancel the path planning for the unmanned machine within the failure area;

[0077] For non-failure areas, activate the corresponding power supply system according to the global task planning to ensure that the unmanned machine can operate along the established path.

[0078] Before operating along the established path, first conduct single-unit testing of the unmanned machine. The steps of single-unit testing include:

[0079] In response to the start instruction, wake up the corresponding unmanned machine for self-check;

[0080] Obtain the self-check information of the driverless machine using its self-check system;

[0081] Send the self-check information to the corresponding single-machine control unit for the task scheduling system to decide whether replacement is needed according to the status of the driverless machine.

[0082] Further, the steps for the driverless machine to run along a specified path:

[0083] Send a running command to the corresponding driverless machine according to the optimal path to control the driverless machine to run at a set speed and direction;

[0084] Send a running command to the control system of the corresponding single machine according to the optimal path, and control the corresponding single-machine control unit to make corresponding judgments and control outputs according to the formulated requirements;

[0085] The specific steps are as follows:

[0086] Use the corresponding single-machine control unit to determine the initial position of the driverless machine through preliminary positioning;

[0087] According to the expected running direction, control the driverless machine to pass through an absolute positioning mark to obtain its actual position;

[0088] Judge the actual driving direction of the driverless machine according to the initial position and the actual position;

[0089] In response to the actual driving direction being inconsistent with the direction indicated by the running command, force the driverless machine to stop and send a running command containing a new direction to the single-machine control unit;

[0090] Output a new control command to the driverless machine at the corresponding position according to the new direction and the actual position to control it to run in the new direction.

[0091] When the driverless machine is running, use its self-check system to monitor the running environment;

[0092] In response to the abnormal result of the running environment monitoring, use the self-check system to cut off the power output of the power supply system and start emergency braking to control the driverless machine to dock nearby.

[0093] Further, when the driverless machine is running, use the corresponding single-machine control unit to correct the position information of the driverless machine according to the ground marks;

[0094] Control the driverless machine to run on the established path according to the corrected position information;

[0095] Multiple virtual position marks are configured on the established trajectory, and the driverless machines in each single machine update their best driving postures in real time by reading the information of the virtual position marks.

[0096] Further, the steps for the driverless machine to run on the established trajectory:

[0097] Obtain the real-time position and driving speed of the driverless machine;

[0098] According to the real-time position and driving speed, calculate the expected time and the optimal driving attitude for the driverless machine to reach the next virtual position mark;

[0099] Send the calculated optimal driving attitude information to the control system of the corresponding driverless machine to drive the driverless machine to run along the established trajectory and in the optimal driving attitude.

[0100] Further, when the driverless machine reaches the target point or the end of the established trajectory, perform the following steps:

[0101] Use the self-check system of the driverless machine to control it to enter the standby state and perform maintenance operations;

[0102] Meanwhile, before the driverless machine enters the standby state, record its current position as a new virtual position mark to optimize the driving path and attitude control in subsequent tasks;

[0103] Send the information of the new virtual position mark to the fleet control system to update the operation strategy and path planning of the entire fleet.

[0104] Further, the main control center is equipped with a construction management system, and uses the construction management system to collect the status information of all ground equipment and all vehicle-mounted equipment of the fleet, display the status information on the display interface of the main control center, and adjust the global path planning and time synchronization scheduling formulated by the central control unit according to the management instructions input by the management personnel through the man-machine interaction interface.

[0105] Further, when the job end instruction is triggered:

[0106] The single-machine control unit sends an instruction to all driverless machines in the single machine to exit the autopilot state;

[0107] The task scheduling system detects whether each driverless machine has successfully exited the autopilot state;

[0108] If it is detected that any driverless machine fails to successfully exit the autopilot state, the single-machine control unit will send an emergency stop instruction to ensure that the driverless machine stops moving immediately.

[0109] A fleet control system includes a processor and its connected positioning and orientation device, communication device, display, and memory; the processor is configured to execute the above-mentioned fleet control method.

[0110] A readable storage medium stores computer instructions thereon, and when the computer instructions are executed by a processor, the above-mentioned cluster control method is implemented.

[0111] In the present invention, the central control unit, the single-vehicle control unit, the road surface positioning system and the communication transmission network cooperate with each other to jointly achieve the driverless control of the in-situ hot recycling machine cluster.

[0112] The central control unit is the core of the entire machine cluster control system, responsible for task planning, operation scheduling, time arrangement, as well as machine cluster monitoring and tracking. The central control unit sorts and binds tasks to the vehicles according to the daily operation plan and the status of the machine cluster, and at the same time, the path trajectory information is sent to the single-vehicle control unit of each vehicle. When a single vehicle fails, the central control unit removes the automatic driving permission of the vehicle and changes it to manual driving, and the remaining vehicles continue to maintain the automatic driving state.

[0113] The single-vehicle control unit is placed in each vehicle of the hot recycling unit group, mainly used for positioning and orienting the vehicle itself, sending the vehicle status information to the central control unit, and controlling the vehicle to drive automatically according to the path trajectory sent by the central control unit combined with the current status information of the vehicle. At the same time, the single-vehicle control unit of each vehicle calibrates the model size of the vehicle through the display, and checks whether the vehicle status information of itself is complete and correct through the display interface.

[0114] The road surface positioning system includes a reference station and a mobile RTK device. The reference station is installed at a fixed position before each construction and cannot be moved during the construction process. The RTK device is mainly used for path collection, helping the system generate task trajectory information and inputting this information into the central control unit, and finally sent by the central control unit to each single-vehicle control unit.

[0115] The complete set of machine cluster control system forms a local area network through the communication transmission network. The communication network in this embodiment includes radio communication, wifi communication, etc. Among them, the base station corrects the positioning information with the positioning and orienting device of each vehicle through radio communication, and the corrected positioning and orienting information of each vehicle and the status information of each vehicle itself are transmitted to the central control unit through wifi. The central control unit calculates the inter-vehicle distance based on the positioning information of each vehicle, and outputs the target speed of each vehicle according to the pre-established rules and sends it to each vehicle through wifi.

[0116] In the present invention, through the integration of the central control unit, the single-vehicle control unit, the road surface positioning system, and the communication transmission network, the collaborative automatic driving control of the in-situ hot recycling machine cluster is realized. This not only improves the efficiency and quality of road maintenance operations, but also lays a foundation for the intelligent development of future road maintenance. At the same time, the present invention has good redundancy and reliability, ensuring the stable operation and safety of the system.

[0117] The schematic diagram of the execution path of the unmanned operation of the vehicle fleet is as Figure 1 shown, and the specific embodiments are as follows:

[0118] First, set up a fixed base station at a suitable location and adjust the parameters of the base station to ensure that the base station can send and receive signals stably and accurately. The fixed base station is an important part of the unmanned driving system. It provides precise positioning and navigation services and lays the foundation for subsequent unmanned driving operations.

[0119] Next, power on the RTK system and set up the RTK. The RTK system is the core device for achieving high-precision positioning. It calculates the position and speed information of the vehicle in real time by receiving signals from the fixed base station and satellites. The settings for the RTK system include selecting a suitable positioning mode, setting the data output frequency, and the coordinate system, etc., to ensure that the RTK system can provide positioning information accurately and in real time.

[0120] Then, the staff holds the RTK device to collect the path and generate the task trajectory. Path collection is an important part of unmanned driving technology. It provides basic data for subsequent automatic driving by recording the trajectory information of the vehicle's travel. During the collection process, the staff needs to walk along the predetermined construction path to ensure that the RTK device can accurately record the path information. After the collection is completed, the generated task trajectory data is imported into the central control unit.

[0121] Next, power on each device of the vehicle fleet, connect the central control unit to the local area network, and connect each device to the central control unit. This process is a key step in realizing communication and data sharing between devices. Through the local area network connection, each device can transmit status information in real time and receive control instructions, so as to achieve collaborative work. At the same time, connecting each device to the central control unit can realize the unified management and control of each device by the central control unit.

[0122] After the device connection is completed, issue the collected construction tasks to each device and set the requirements for the vehicle spacing. The construction task is the core element in unmanned driving technology. It stipulates the construction path trajectory, vehicle spacing, vehicle speed, and vehicle sequence relationship of the vehicle fleet. By issuing the construction tasks, each device can clarify its own responsibilities and goals. At the same time, setting the requirements for the vehicle spacing is to ensure that the vehicle fleet can maintain a safe and stable spacing during construction and avoid safety accidents such as collisions.

[0123] Subsequently, check each single-machine control unit, and calibrate the vehicle model through the display module of the single-machine control unit. The display interface of the single-machine control unit is as Figure 3As shown. The single - machine control unit is a key component in unmanned driving technology. It is responsible for controlling the trajectory tracking control and anti - collision strategy of a single vehicle. By checking its working status and input / output signals, etc., it can be ensured that it can respond to control instructions normally and execute actions accurately. At the same time, by calibrating the vehicle model, it can be ensured that control instructions can be accurately mapped to the actual actions of the vehicle, thereby improving the accuracy and stability of unmanned driving.

[0124] During the inspection process, it is also necessary to check whether the network status of the vehicle is normal. The network status is one of the important factors affecting the performance of unmanned driving technology. If the network connection is unstable or the data transmission rate is insufficient, it may lead to the loss or delay of control instructions, thus affecting the safety and efficiency of unmanned driving. Therefore, during the inspection process, it should be ensured that the network connection is stable and reliable and the data transmission rate meets the requirements.

[0125] Finally, by issuing a task start instruction through the central control unit and observing the display interface of the central control unit, the display interface of the central control unit is as Figure 2 shown. Confirm whether the status of each vehicle is normal. The task start instruction is a key signal to start unmanned driving technology, which triggers each device to start working collaboratively according to the preset construction tasks. Before issuing the instruction, it should be confirmed again whether the status of each device is normal and whether the construction tasks have been correctly loaded. At the same time, by observing the display interface of the central control unit, information such as the position, speed, and direction of each vehicle and the execution status of the construction tasks can be understood in real - time, so as to promptly discover abnormal situations and take necessary measures for handling.

[0126] Taking the data obtained from a certain test as an example, convert the exact values of the input variables into the membership functions of fuzzy sets. Define the fuzzy sets as:

[0127] Lateral deviation (p): near, medium, far;

[0128] Speed deviation (v): slow, medium, fast;

[0129] Inter - vehicle distance deviation (d): narrow, medium, wide; Define the membership function of lateral deviation:

[0130] Near: Use a triangular membership function;

[0131] Vertex: (- 10,1);

[0132] Left bottom point: (- 20,0);

[0133] Right bottom point: (0,0);

[0134] The membership function expression is as follows:

[0135]

[0136] Medium: Use a trapezoidal membership function; left bottom point: (-10, 0);

[0137] Left vertex: (-5, 1);

[0138] Right vertex: (5, 1);

[0139] Right bottom point: (10, 0);

[0140] Membership function expression:

[0141]

[0142] Far: Use a triangular membership function;

[0143] Vertex: (10, 1);

[0144] Left bottom point: (0, 0);

[0145] Right bottom point: (20, 0);

[0146] Membership function expression:

[0147]

[0148] Similarly, the speed deviation membership function is defined as follows; Slow: Use a triangular membership function;

[0149] Vertex: (-5, 1);

[0150] Left bottom point: (-10, 0);

[0151] Right bottom point: (0, 0);

[0152] Membership function expression:

[0153]

[0154] Medium: Use a trapezoidal membership function;

[0155] Left bottom point: (-5, 0);

[0156] Left vertex: (-2.5, 1);

[0157] Right vertex: (2.5, 1);

[0158] Right bottom point: (5, 0);

[0159] Membership function expression:

[0160]

[0161] Fast: Use triangular membership function;

[0162] Vertex: (5, 1);

[0163] Left bottom point: (0, 0);

[0164] Right bottom point: (10, 0);

[0165] Membership function expression:

[0166]

[0167] The same membership function for vehicle spacing deviation can be expressed as:

[0168] Assume that the fuzzy set of vehicle spacing deviation d is defined as: Narrow, Medium, Wide;

[0169] Narrow: Use triangular membership function;

[0170] Vertex: (-1, 1);

[0171] Left bottom point: (-2, 0);

[0172] Right bottom point: (0, 0);

[0173] Membership function expression:

[0174]

[0175] Medium: Use trapezoidal membership function;

[0176] Left bottom point: (-1, 0);

[0177] Left vertex: (-0.5, 1);

[0178] Right vertex: (0.5, 1);

[0179] Right bottom point: (1, 0);

[0180] Membership function expression:

[0181]

[0182] Wide: Use triangular membership function;

[0183] Vertex: (1, 1);

[0184] Left bottom point: (0, 0);

[0185] Right bottom point: (2, 0);

[0186] Membership function expression:

[0187]

[0188] Assume that when the distance deviation p = 3, speed deviation v = 2, and inter-vehicle distance deviation d = 1.5 for a certain vehicle in the unit (the unit and specific values here are determined according to the actual working conditions), then according to the membership calculation formula, we can get:

[0189] The membership of the distance deviation p belonging to moderate is 1, the probability of the speed deviation v belonging to moderate is 1, and the probability of the inter-vehicle distance deviation d belonging to wide is 0.5.

[0190] Input the key membership information of the unit into the controller, and the controller performs relevant reasoning and decision-making according to the vehicle membership information and predefined fuzzy rules.

[0191] 1 Speed adjustment rule:

[0192] If the distance deviation is large and positive (NB), and the speed deviation is positive (PB), then increase the speed adjustment amount (PB);

[0193] If the distance deviation is large and negative (PB), and the speed deviation is negative (NB), then decrease the speed adjustment amount (NB);

[0194] If the inter-vehicle distance deviation is small (ZO), then keep the speed adjustment amount unchanged (ZO);

[0195] 2 Trajectory adjustment rule:

[0196] If the distance deviation is large (NB or PB), then increase the trajectory adjustment amount to correct the deviation (PB);

[0197] If the distance deviation is small (ZO), then keep the trajectory adjustment amount unchanged (ZO);

[0198] 3 Inter-vehicle distance adjustment rule:

[0199] If the inter-vehicle distance deviation is large (NB or PB), then adjust the inter-vehicle distance to reduce the deviation (PB or NB, depending on the deviation direction);

[0200] If the inter-vehicle distance deviation is small (ZO), then keep the inter-vehicle distance adjustment amount unchanged (ZO).

[0201] In summary, through multiple steps including task generation (setting task name, speed setting, path collection, special point marking), task distribution (the central control unit accessing the local area network, completing the binding of each vehicle, distributing tasks to each vehicle, setting the inter-vehicle distance), status check (the central control unit checking the RTK solution status, checking the satellite data status of each vehicle control unit, checking vehicle model calibration, checking the vehicle task acceptance situation), turning off the manual driving mode, and starting the automatic driving mode, the present invention realizes the unmanned operation of the in-situ hot recycling machine fleet. The present invention has the advantages of high automation degree, high positioning accuracy, strong coordination ability, etc., and can significantly improve the construction efficiency and quality, and reduce the labor cost and safety risk.

Claims

1. A method for controlling an in-situ hot recycling machine fleet, characterized in that, Including: Import the global task plan of the fleet into the central control unit, and allocate the refined single-machine task strategy to multiple single-machine control units. Among them, the central control unit is configured in the main control center, and the single-machine control units are dispersedly configured in multiple sub-control centers. The central control unit and multiple single-machine control units form a task scheduling system; Use the central control unit to perform global task planning and time synchronization scheduling on multiple unmanned vehicles in the fleet. Among them, the global task planning includes: Allocate the optimal path for multiple unmanned vehicles; Use the corresponding single-machine control unit to send start commands, speed adjustment commands, inter-vehicle distance adjustment commands, and trajectory adjustment commands to the specified unmanned vehicle to drive the specified unmanned vehicle to run along the established path; In response to a failure of the central control unit, use each single-machine control unit to independently perform emergency path planning and scheduling on the affiliated unmanned vehicle according to the corresponding single-machine task strategy.

2. The in-situ hot recycling machine group control method according to claim 1, characterized in that Perform system testing before global task planning and time synchronization scheduling, including: Detect the status of the unmanned vehicles configured on each single machine to confirm whether they meet the operation conditions; Detect the status of the single-machine control units configured on each single machine to confirm whether they can normally execute control commands; Detect the status of the power supply system configured on each single machine to confirm whether it can normally provide power; If any unmanned vehicle failure, control system failure, or power supply system does not meet the operation conditions is detected, mark the corresponding single machine as a failure area, and cancel the path planning for the unmanned vehicle in the failure area; For non-failure areas, activate the corresponding power supply system according to the global task plan to ensure that the unmanned vehicle can run along the established path.

3. A method for controlling an in-situ hot recycling machine group according to claim 1 or 2, characterized in that, Steps for the unmanned vehicle to run along the specified path: Send a running command to the corresponding unmanned vehicle according to the optimal path to control the unmanned vehicle to run at the established speed and direction; Send a running command to the corresponding single-machine control unit according to the optimal path, and control the corresponding single-machine control unit to make corresponding judgments and control outputs according to the specified requirements; The specific steps are as follows: Use the corresponding single-machine control unit to determine the initial position of the unmanned vehicle through preliminary positioning; According to the expected running direction, control the unmanned vehicle to pass through an absolute positioning mark to obtain its actual position; Judge the actual driving direction of the unmanned vehicle according to the initial position and the actual position; In response to the actual driving direction being inconsistent with the direction indicated by the running command, force the unmanned vehicle to stop, and send a running command containing a new direction to the single-machine control unit; Output a new control command to the unmanned vehicle at the corresponding position according to the new direction and the actual position to control it to run in the new direction.

4. The on-site hot recycling machine group control method according to claim 3, characterized in that When the unmanned vehicle is running, use the corresponding single-machine control unit to correct the position information of the unmanned vehicle according to the ground mark; Control the unmanned vehicle to run on the established path according to the corrected position information; Multiple virtual position marks are configured on the established trajectory, and the unmanned vehicles in each single machine update their best driving postures in real time by reading the information of the virtual position marks.

5. The method for controlling an in-situ hot recycling machine group according to claim 4, wherein, Steps for an unmanned vehicle to operate on a predefined trajectory: Obtain the real-time position and traveling speed of the unmanned vehicle; Based on the real-time position and traveling speed, calculate the expected time for the unmanned vehicle to reach the next virtual position marker and the optimal traveling attitude; Send the calculated optimal traveling attitude information to the control system of the corresponding unmanned vehicle to drive the unmanned vehicle to operate along the predefined trajectory with the optimal traveling attitude.

6. A method for controlling an in-situ hot recycling machine group according to claim 4, characterized in that, When the unmanned vehicle reaches the target point or the end of the predefined trajectory, perform the following steps: Use the self-check system of the unmanned vehicle to control it to enter the standby state and perform maintenance operations; Meanwhile, before the unmanned vehicle enters the standby state, record its current position as a new virtual position marker to optimize the traveling path and attitude control in subsequent tasks; Send the information of the new virtual position marker to the fleet control system to update the operation strategy and path planning of the entire fleet.

7. A method for controlling an in-situ hot recycling machine group according to claim 1, characterized in that, The main control center is equipped with a construction management system, and uses the construction management system to collect the status information of all ground equipment and all on-vehicle equipment of the fleet, display the status information on the display interface of the main control center, and adjust the global path planning and time synchronization scheduling formulated by the central control unit according to the management instructions input by the management personnel through the man-machine interaction interface.

8. A method for controlling an in-situ hot recycling machine group according to claim 1, characterized in that, When the job end instruction is triggered: The single-vehicle control unit sends an instruction to all unmanned vehicles within the single vehicle to exit the autopilot state; The task scheduling system detects whether each unmanned vehicle has successfully exited the autopilot state; If it is detected that any unmanned vehicle fails to successfully exit the autopilot state, the single-vehicle control unit will send an emergency stop instruction to ensure that the unmanned vehicle stops moving immediately.

9. A cluster control system, characterized in that It includes a processor and its connected positioning and orientation device, communication device, display, and memory; the processor is configured to execute the fleet control method described in any one of claims 1 to 8.

10. A readable storage medium, characterized in that, Computer instructions are stored on a readable storage medium, and when the computer instructions are executed by the processor, the fleet control method described in any one of claims 1 to 8 is implemented.

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