CN118644053B

CN118644053B - Method, device, system and medium for mixed scheduling of unmanned mining truck and manned vehicle

Info

Publication number: CN118644053B
Application number: CN202411112376.1A
Authority: CN
Inventors: 刘良杰; 黄佳德; 尹超; 刘烨轩; 汤春林; 宁翔
Original assignee: Zhuzhou CRRC Times Electric Co Ltd
Current assignee: Zhuzhou CRRC Times Electric Co Ltd
Priority date: 2024-08-14
Filing date: 2024-08-14
Publication date: 2024-12-06
Anticipated expiration: 2044-08-14
Also published as: CN118644053A

Abstract

The invention discloses a method, a device, a system and a medium for mixed scheduling of unmanned mining trucks and unmanned vehicles, wherein the method comprises the steps of receiving positioning information and nearby obstacle information sent by each unmanned vehicle and unmanned mining truck in a target control area in real time; according to the positioning information of various vehicles in the target control area, scheduling each unmanned mining truck and each manned mining truck by taking the maximum loading operation efficiency, the minimum empty travel and the optimal number of the overall unmanned mining trucks and the manned mining trucks as targets, planning a running path for each scheduled mining truck, judging whether each vehicle can run in conflict or not in the process that each mining truck executes the operation according to the planned running path, and if so, controlling to send early warning information to the vehicles with running conflict. The invention can realize the mixed dispatching of the unmanned mining truck and the manned vehicle efficiently, safely and reliably.

Description

Method, device, system and medium for mixed scheduling of unmanned mining truck and manned vehicle

Technical Field

The invention relates to the technical field of mining area vehicle dispatching, in particular to a method, a device, a system and a medium for dispatching unmanned mining trucks and manned vehicles in a mixed mode.

Background

The unmanned system of the mining truck (mining dump truck) receives the operation scheduling instruction, makes a decision according to the state of the vehicle and environmental perception data, issues instructions to a vehicle driving system, a braking system, a steering system, a lifting system, a lighting system and the like, and can automatically control the vehicle to complete an operation task. The unmanned mining truck can greatly improve the operation efficiency and the intelligent degree of operation. To ensure operational safety, it is common in the prior art to only apply unmanned mining trucks in a particular area within an open air mine where only unmanned mining trucks are present, each unmanned mining truck being dispatched in accordance with the idle state of the unmanned mining truck within the mine.

However, if the unmanned mining truck is applied to the whole strip mine area, the mining truck which is driven by a person is required to simultaneously execute the operation in the mining area, and besides, the auxiliary production operation such as whole road surface, cleaning of the working surface, building of retaining walls and the like is required to be performed, so that the cooperative operation vehicles such as land levelers, water sprinklers, bulldozers and the like are also required to exist in the mining area, and are usually all the unmanned vehicles, namely, the unmanned mining truck and various types of unmanned vehicles are actually simultaneously present in the whole mining area. The traditional scheduling mode for the independent unmanned mining truck cannot realize cooperative operation between the unmanned mining truck and various types of manned vehicles, so that the operation efficiency of various types of vehicles can be influenced, the operation safety of the unmanned mining truck cannot be ensured, and the unmanned mining truck is greatly limited when the unmanned technology is applied to the full mining grade. Therefore, it is a current urgent problem to be solved to achieve safe and reliable hybrid marshalling between unmanned mining trucks and other manned vehicles in mining areas.

Disclosure of Invention

Aiming at the technical problems existing in the prior art, the invention provides the method, the device, the system and the medium for mixed scheduling of the unmanned mining truck and the manned vehicle, which are simple to realize, low in cost and safe and reliable in scheduling.

In order to solve the technical problems, the technical scheme provided by the invention is as follows:

a method for mixed scheduling of unmanned mining trucks and manned vehicles, the method comprising:

Receiving positioning information sent by various types of vehicles and nearby obstacle information sent by various unmanned mining trucks in a target control area in real time, wherein the types of vehicles comprise manned vehicles and unmanned mining trucks, and the manned vehicles comprise manned mining trucks and manned cooperative auxiliary vehicles;

according to positioning information of various vehicles in a target control area, taking the maximum loading operation efficiency, the minimum empty travel and the optimal number of the whole unmanned mining trucks and the manned mining trucks as targets, respectively distributing corresponding weight coefficients for each target to construct and form an objective function, dispatching each unmanned mining truck and each manned mining truck according to the constructed objective function, respectively planning a driving path for each dispatched unmanned mining truck, wherein the empty travel is the distance traveled by each unmanned mining truck and each unmanned mining truck when the unmanned mining truck is empty, the target with the maximum loading operation efficiency uses the total traffic of the unmanned mining trucks and the manned vehicles on each path in the target control area, and the waiting time required by each unmanned mining truck and the manned mining truck in each working area to construct a corresponding calculation model, and the targets with the optimal number of the whole unmanned mining trucks and the manned mining trucks use the traffic of the unmanned mining trucks and the traffic of the unmanned mining trucks on each path;

and in the process that each unmanned mining truck executes the operation according to the planned running path, judging whether each unmanned mining truck can generate running conflict with other vehicles or obstacles according to the received positioning information and the obstacle information of each vehicle, and if so, controlling to send early warning information to the vehicles with the running conflict.

Further, the target with the minimum idle travel distance uses the idle travel distance and the number of vehicles on each path in a target control area to construct a total distance calculation model of idle travel on all paths, and the target with the minimum idle travel distance corresponds to the target with the minimum idle travel distance when the target function of the total distance calculation model of idle travel on all paths is minimum.

Further, when the objective function is constructed, the objective for minimizing the idle time of the electric shovel is further included, an electric shovel idle time calculation model is constructed by using the efficiency and the total working time of each electric shovel and the idle time of each electric shovel, and the objective for minimizing the idle time of the electric shovel is corresponding to the objective for minimizing the idle time of the electric shovel when the objective function including the electric shovel idle time calculation model is minimum.

Further, the method further comprises the step of setting any one or more of loading and unloading area continuous operation constraint, electric shovel loading and unloading capacity constraint, ore yield constraint and mixed scheduling safety distance constraint, wherein the loading and unloading area continuous operation constraint is constraint conditions which are required to be met when an ore truck continuously works in a loading area and an unloading area, the electric shovel loading and unloading capacity constraint is constraint which is required to be met by each electric shovel loading and unloading capacity, the ore yield constraint is constraint conditions which are required to be met by the total yield of each electric shovel, and the mixed scheduling safety distance constraint is constraint conditions which are required to be met by the safety distance between the manned ore truck and the unmanned ore truck.

Further, the loading and unloading area continuous operation constraint is as follows:

;

Wherein N _ia represents the number of paths entering the ith electric shovel loading area, the crushing station coal unloading area and the dumping area, N _o represents the number of paths of the ore-sending trucks from the electric shovel loading area, the crushing station coal unloading area and the dumping area, Indicating the flow of the unmanned mining truck entering the ith electric shovel loading area, the coal unloading area of the crushing station and the soil discharging area,Indicating the flow of the manned mining truck entering the ith electric shovel loading area, the coal unloading area of the crushing station and the soil discharging area,Represents the unmanned mining truck traffic sent by the jth path,Indicating the flow of the manned mining truck from the jth path.

Further, the electric shovel loading capacity constraint is as follows:

;

wherein, The number of paths of the vehicle flow sent by the kth electric shovel is indicated,Represents the unmanned mining truck traffic sent by the jth path,Indicating the flow of the manned mining truck sent by the jth path,Indicating the maximum mining rate of the kth electric shovel.

Further, in the running process of the unmanned mining truck according to the planned path, detecting whether dangerous position points exist in the planned path, when the dangerous position points exist, retracting the dangerous position points along the planned path to obtain new safe track points, and continuing to run by taking the new safe track points as starting points, wherein the dangerous position points comprise position points where any one of a communication positioning vehicle, a communication fault vehicle, a blocking area and a safety track envelope of a current vehicle invades other controlled vehicle safety envelopes, and the safe distances are obtained according to vehicle positioning control errors, vehicle backward sliding distances and safety margins.

Further, when the communication positioning fault occurs in the front unmanned mining truck in the driving process, the last effective positioning information of the front fault vehicle is adopted to calculate the safety envelope of the front fault vehicle, and the safety track point of the rear vehicle is determined according to the safety envelope of the front fault vehicle, so that a safety distance exists between the safety track point of the rear vehicle and the safety envelope of the vehicle determined according to the last effective positioning information of the front fault vehicle.

Further, when the existence of the unmanned mining truck in the specified range around the manned vehicle is judged according to the vehicle positioning information, the running track of the unmanned mining truck is sent to the terminal of the corresponding manned vehicle for display.

Further, if it is determined that the unmanned mining truck is in collision with the obstacle, the method further comprises the step of rescheduling the path according to the current position, the safe parking position and the current speed of the unmanned mining truck in collision.

An unmanned mining truck and manned vehicle mixed scheduling device, comprising:

the information receiving module is used for receiving positioning information sent by various vehicles in the target control area and nearby barrier information sent by various unmanned mining trucks in real time, wherein the vehicle types comprise manned vehicles and unmanned mining trucks, and the manned vehicles comprise manned mining trucks and manned cooperative auxiliary vehicles;

The dispatching control module is used for constructing and forming an objective function by taking the maximum loading operation efficiency, the minimum empty travel and the optimal overall unmanned mining truck and the optimal number of the unmanned mining trucks as targets according to the positioning information of various vehicles in the target control area, respectively distributing corresponding weight coefficients for each target, dispatching each unmanned mining truck and each unmanned mining truck according to the constructed objective function, respectively planning a driving path for each dispatched unmanned mining truck, wherein the empty travel is the distance travelled by each unmanned mining truck and each unmanned mining truck when the unmanned mining trucks are empty, the target with the maximum loading operation efficiency uses the total traffic of the unmanned mining trucks and the unmanned mining trucks on each path in the target control area, and constructs a corresponding calculation model by using the traffic of the unmanned mining trucks and the required waiting time of the unmanned mining trucks and the unmanned mining trucks on each path in each working area;

And the early warning module is used for judging whether each unmanned mining truck can generate running conflict with other vehicles or obstacles according to the received positioning information and the received obstacle information of each mining truck in the process of executing the operation according to the planned running path, and controlling to send early warning information to the vehicles with the running conflict if the unmanned mining trucks can generate the running conflict with other vehicles or obstacles.

A computer device comprising a processor and a memory for storing a computer program, the processor being for executing the computer program to perform a method as described above.

An unmanned mining truck and manned vehicle hybrid scheduling system comprising:

A plurality of unmanned mining trucks, each of which is equipped with a vehicle-mounted positioning device, a communication device and an external environment detection sensor;

The system comprises a plurality of manned vehicles, a plurality of control units and a plurality of control units, wherein the manned vehicles comprise manned mining trucks and manned cooperative auxiliary vehicles, and each manned vehicle is provided with a vehicle-mounted positioning device and a communication device;

Scheduling means for scheduling each unmanned mining truck and the manned mining truck in the above-described method;

and a network communication system for enabling communication connection between the dispatcher and each of the unmanned mining trucks, each of the manned vehicles.

A computer readable storage medium storing a computer program which, when executed by a processor, implements a method as described above.

Compared with the prior art, the invention has the advantages that the mixed scheduling of the all-mine-level manned vehicle and the unmanned mining truck can be realized, the cooperative operation and mixed transportation operation of the unmanned mining truck and the multi-type vehicle can be realized, the unmanned mining truck and the unmanned mining truck of different types can be effectively managed and scheduled, the cross transportation problem of the multi-type vehicle in the mixed running mode can be solved, and the adaptability of the unmanned system in the all-mining area operation can be improved.

Drawings

FIG. 1 is a schematic diagram of a suitable system architecture for use in embodiments of the present invention.

Fig. 2 is a schematic diagram of the architecture of an unmanned mining truck for use in a specific application embodiment of the present invention.

Fig. 3 is a schematic diagram of the architecture of a manned mining truck used in a specific application embodiment of the present invention.

Fig. 4 is a schematic diagram of an intersystem data association relationship applicable to a specific application embodiment of the present invention.

Fig. 5 is a schematic diagram of an implementation flow of the hybrid scheduling method of the unmanned mining truck and the manned vehicle according to the embodiment.

Fig. 6 is a schematic diagram of the principle of determining the safe distance in the present embodiment.

Fig. 7 is a schematic diagram of the safety rights division of the vehicle hybrid operation in the embodiment of the application of the present invention.

Fig. 8 is a schematic diagram of a path collision occurring in a road crossing area in a specific application embodiment of the present invention.

Fig. 9 is a schematic diagram of the present invention in which a path conflict occurs in a soil discharge area in a specific application embodiment.

Fig. 10 is a schematic diagram of the invention in a specific application embodiment without reporting the intrusion of the vehicle.

Detailed Description

The invention is further described below in connection with the drawings and the specific preferred embodiments, but the scope of protection of the invention is not limited thereby.

Fig. 1 is a system architecture applicable to the present embodiment, where the system may include an unmanned mining truck, a manned cooperative auxiliary vehicle, a ground centralized control system, and a network communication system, where the network communication system establishes communication connection between the ground centralized control system and each unmanned mining truck, manned mining truck, and manned cooperative auxiliary vehicle, and the network communication system includes, but is not limited to, 4G, 5G, and other communication modes. And dispatching and controlling each unmanned mining truck by the ground centralized control system according to the state of each type of vehicle in the control area. The unmanned mining truck is a mining dump truck controlled by an unmanned driving system, the manned mining truck is a mining dump truck driven by a person, and the manned collaborative auxiliary vehicle is a vehicle which is mutually matched and collaborative with the dump truck in the transportation production process of the surface mine and comprises a bulldozer, an excavator, a land leveler, a watering cart, a command cart, a fuelling cart and the like.

The ground centralized control system can receive information uploaded by unmanned mining trucks, manned mining trucks and manned cooperative auxiliary vehicles through the network communication system, such as positioning information of each vehicle, vehicle state information, obstacle information near the unmanned mining trucks and the like. Because a driving path needs to be planned for the unmanned mining truck, in order to ensure driving safety, environmental information near the unmanned mining truck needs to be acquired, including whether obstacles exist around the unmanned mining truck. In the embodiment, the unmanned mining truck senses the surrounding environment in the driving process, and if the unmanned mining truck senses the obstacle information, the obstacle information is sent to the ground centralized control system, so that the ground centralized control system can plan a path again according to the obstacle information. The obstacle may be static or dynamic, and the real-time position of the obstacle is uploaded to the ground centralized control system after the obstacle is sensed, and the ground centralized control system performs path planning according to the real-time position of the obstacle so as to avoid the obstacle. Meanwhile, the ground centralized control system sends information to the unmanned mining truck, the manned mining truck and the manned cooperative auxiliary vehicle through the network communication system, for example, sends scheduling instructions and planned paths to the unmanned mining truck, and sends early warning information to the manned mining truck and the manned cooperative auxiliary vehicle.

The unmanned vehicle-mounted system is loaded in the unmanned mining truck, can receive the dispatching instruction and the path information from the ground centralized control system, makes a safety decision according to the state of the vehicle, gives corresponding control instructions to the vehicle, drives the mining truck to execute the operation tasks, can control the acceleration, braking and related actions of the vehicle according to the surrounding actual conditions, and can stop in time when an emergency occurs. Because of the need of generating a dispatching strategy for the unmanned mining truck according to the real-time position and the surrounding environment of the unmanned mining truck, in this embodiment, the unmanned mining truck may be additionally provided with a vehicle-mounted positioning device such as a GNSS (global navigation satellite system), a sensor capable of sensing the surrounding environment, and a communication unit capable of realizing communication with an external device, where the sensor may use a camera and a radar sensor (e.g., a laser radar, a millimeter wave radar), etc. In the task execution process, the unmanned vehicle-mounted system in the unmanned mining truck acquires high-precision positioning and attitude information of the unmanned vehicle-mounted system through vehicle-mounted positioning equipment, acquires surrounding terrain and obstacle information through vehicle-mounted sensors, dynamically adjusts the running state of the vehicle in real time according to the information, and simultaneously uploads the positioning information, the surrounding terrain and the obstacle information acquired in real time to a ground centralized control system.

Optionally, devices such as an HMI (human-machine interface), an AMS (automatic switching), an automatic/Manual switching Switch, a mode indicator light, and the like may be additionally installed in the unmanned mining truck. The AMS switch is used for realizing safe switching between unmanned driving and manual driving states. For example, the AMS switch has two gears for unmanned and manual driving, two sets of AMS switches may be configured in each unmanned mining truck, and the unmanned mining truck may enter an unmanned state only when both sets of AMS switches are in the unmanned gear, so as to ensure the safety and reliability of unmanned mining. The mode indicator light is a driving mode for displaying a mining truck by configuring different types of lights outside the vehicle, including but not limited to an unmanned mode, a manual driving mode, a remote driving mode, etc.

In a specific application embodiment, the architecture of the unmanned mining truck device is shown in fig. 2, and the architecture comprises a VAP (Virtual Access Point ) host and devices such as a vehicle-mounted GNSS device, a communication unit, a radar, an HMI and a camera, wherein each device is respectively connected with the VAP host, and the VAP host receives information collected by the devices such as the vehicle-mounted GNSS device, the radar and the camera or a control instruction accessed by the HMI, and after data processing, the AMS switch and the mode indicator lamp are correspondingly controlled to act.

The mining truck driven by someone is controlled by staff to accelerate, brake and related actions according to the surrounding actual conditions, and is stopped in time when emergency occurs. In a manned mining truck, a communication unit is required to realize the real-time communication function of a vehicle, and a vehicle-mounted positioning device such as a GNSS is required to be additionally arranged to position the position of the vehicle in real time and upload the position to a ground centralized control system. Optionally, HMI may be added to the manned mining truck to facilitate man-machine interaction. FIG. 3 is a schematic illustration of a manned vehicle equipment architecture for use in a specific embodiment of the application, including a host processing platform, which may be a computing, network and storage capable device based on hardware/software resources and services, and a communication unit, HMI and onboard GNSS devices respectively coupled to the host processing platform.

In a specific application embodiment, the ground centralized control system is used as an unmanned comprehensive operation system for the mining trucks of the surface mine, and can be used for providing mining area vehicle operation path management functions required by mining area operation, including receiving mining area vehicle information, collecting mining area equipment state, automatically maintaining mining area operation progress information in the operation process, providing a mining area information comprehensive display interface and a manual intervention control interface for users, providing automatic operation and obstacle avoidance strategies for vehicles and the like.

Optionally, the system of the embodiment may further include a remote driving system, so as to be used for controlling the system of the unmanned mining card by using the remote cockpit under special conditions. The remote driving system is in communication connection with the unmanned mining truck through the network communication system, and when the unmanned mining card needs to be remotely controlled, the remote driving system transmits a control instruction through the network communication system so as to control the unmanned mining card to act according to the specified instruction. The unmanned mining card can also be in communication connection with a vehicle outside the system, which is not connected with the mixed dispatching system. Unmanned collaborative operation system is needed to be installed in unmanned mining truck vehicles in the system, and if the unmanned collaborative operation system is not installed, the unmanned system can be accessed through installing a temporary positioning communication device when the unmanned collaborative operation system is in a mining area operation area.

Optionally, the system of the embodiment further comprises a primary crushing station, wherein the equipment for conveying the crushed coal blocks to the conveyor through the chute after the coal blocks are extruded, impacted and crushed is arranged in the crushing station, and the communication and signal processing components are deployed in the crushing station and are used for connecting the crushing station into the mixed scheduling system.

The data transmission relationship between the parts in the system to which the embodiment is applied is shown in fig. 4, where each part in the system performs data transmission through a route, and each number in the drawing represents a different route, and the functions of each route are specifically shown as follows:

the unmanned mining card sends information such as positioning, vehicle state and the like to a network transmission system;

the route 2 is that the manned rock transportation mining card sends the positioning information to the network transmission system;

the route 3 is that the manned coal mine transport card sends the positioning information to the network transmission system;

the route 4 is that the manned cooperative auxiliary vehicle sends the positioning information to the network transmission system;

the network transmission system forwards the information of the routes 1, 2, 3 and 4 to the mixed scheduling system in real time;

the mixed scheduling system formulates a corresponding scheduling strategy according to the information of the route 5 and transmits a corresponding instruction to the network transmission system;

the route 7 is that the unmanned mining card receives the dispatching instruction forwarded by the network transmission system, and the unmanned mining card operates according to the received instruction, and performs collision early warning prompt when collision risk exists between the unmanned mining card and the manned vehicle;

A route 8, namely receiving an alarm instruction forwarded by a network transmission system by a manned rock transportation mining card to perform collision early warning;

A route 9, wherein the manned coal mine card receives an alarm instruction forwarded by the network transmission system and performs collision early warning;

The route 10 is that the someone drives the cooperative auxiliary vehicle to receive the warning instruction forwarded by the network transmission system and perform collision early warning;

The route 11 is that a driver remotely operates the unmanned mining card through a remote driving system, and video stream and data stream through a network communication system;

the route 12 is that the unmanned mining card feeds back the state information data of the unmanned mining card to the remote driving system in real time through the network communication system;

The route 13 is that the unmanned mining card detects the vehicle outside the recognition system through the installed sensors (including radar and cameras) and feeds back to the ground centralized control system.

According to the system, the ground centralized control system is used as a control center, network data communication is used as a bridge, and mixed marshalling safety and efficient production operation of the existing/unmanned mining cards, the collaborative auxiliary vehicles and the unmanned trucks are realized based on mixed marshalling of the ground centralized control system, so that the unmanned mining trucks and the unmanned vehicles can operate in a mining area in a mixed mode.

It will be appreciated that the above-described devices that may be included in the system are not limiting but merely illustrative, and that the system may alternatively include other types of manned vehicles, unmanned vehicles, co-assist vehicles, workstations, etc. The ground centralized control system can be a terminal device arranged on the ground to be used as a centralized control system, or can be a system in other forms such as a cloud server, or even can be a system in which a module capable of realizing a mixed scheduling control function is integrally arranged on a certain controlled vehicle, and the controlled vehicle is in communication connection with other vehicles to realize scheduling control.

As shown in fig. 5, the method for dispatching the unmanned mining truck and the manned vehicle in a mixed mode according to the embodiment comprises the following steps:

and S01, receiving positioning information sent by various vehicles in the target control area and nearby obstacle information sent by various unmanned mining trucks in real time, wherein the vehicle types comprise manned vehicles and unmanned mining trucks, and the manned vehicles comprise manned mining trucks and manned cooperative auxiliary vehicles.

In this embodiment, the height precision positioning and attitude information is obtained in real time by the vehicle-mounted positioning device in the unmanned mining truck, and surrounding terrain and obstacle information are obtained by the vehicle-mounted sensor, and the positioning information and the surrounding terrain and obstacle information obtained in real time are uploaded to the ground centralized control system, and the real-time positioning information is also uploaded to the ground centralized control system in the running process of the manned mining truck and the manned vehicle with the manned collaborative auxiliary vehicle. The ground centralized control system receives positioning information, obstacle information and the like sent by each type of vehicle in a target control area in a mining area in real time, and can determine the positions of each type of vehicle, the running state of the vehicle, whether obstacles exist nearby or not and the like by utilizing the obtained information.

In this embodiment, the target control area may be the whole open-air mining area, or may be an area that is separately divided in the mining area and needs to be subjected to mixed scheduling control, and the size of the control area may be defined according to actual requirements.

And S02, constructing and forming an objective function by taking the maximum loading operation efficiency, the minimum empty travel and the optimal number of the whole unmanned mining trucks and the manned mining trucks as targets according to the positioning information of various vehicles in the target control area, respectively distributing corresponding weight coefficients for each target, dispatching each unmanned mining truck and each manned mining truck according to the constructed objective function, planning a driving path for each dispatched unmanned mining truck, respectively using the total traffic of the unmanned mining trucks and the manned mining trucks on each path in the target control area by the target with the maximum loading operation efficiency, and constructing a corresponding calculation model by the aid of waiting time of the unmanned mining trucks and the manned mining trucks in each working area by the target with the optimal number of the whole unmanned mining trucks and the manned mining trucks, and constructing a corresponding calculation model by using the unmanned mining truck traffic and the manned mining truck traffic on each path by the target with the optimal number of the whole unmanned mining trucks and the manned mining trucks.

Considering that unmanned mining trucks and manned mining trucks need to be scheduled simultaneously in the mining truck scheduling process, the overall input quantity of the unmanned mining trucks and the manned mining trucks determines the overall input cost and the utilization rate, and the manned cooperative auxiliary vehicles exist simultaneously in the mining area, the problems of collision in driving and overlarge traffic flow and the like between the unmanned mining trucks and the manned cooperative auxiliary vehicles need to be avoided simultaneously in the mining truck scheduling process are considered, waiting time is caused when a plurality of mining trucks work simultaneously, and in order to ensure that each mining truck works normally in sequence, each mining truck may need to wait for a certain time when entering the loading area, the coal unloading area, the soil discharging area and the like, and the overall working efficiency is lower when the waiting time is longer. In addition, in the operation process of the mining truck, after the mining truck is transported to the unloading area for unloading after the loading area is loaded, the vehicle can need to run for a period of time in an idle mode, if the idle time is long, the overall utilization rate can be reduced similarly, and the overall operation efficiency is further affected.

In view of the above problems, the present embodiment performs dispatching of each unmanned mining truck and each manned mining truck by comprehensively targeting the maximum loading operation efficiency, the minimum empty travel and the optimal number of the overall unmanned mining trucks and the manned mining trucks, and considers the total traffic of the unmanned mining trucks and the manned vehicles (including the manned mining trucks and the auxiliary vehicles) on each path and the waiting time of each mining truck on the basis of considering the optimal number of the overall unmanned mining trucks and the manned mining trucks, so that the overall mining truck loading operation efficiency can be maximized (only the mining trucks are considered when the auxiliary vehicles are considered in consideration of the traffic, so that the minimum mining truck waiting time can be ensured under the optimal overall traffic condition by comprehensively combining the total traffic and the waiting time), and meanwhile, the empty travel of the overall mining trucks enables the minimum empty travel when the empty travel of the mining trucks is combined, so that the overall equipment utilization rate and the operation efficiency are improved.

In order to achieve intelligent operation, in the embodiment, a ground centralized control system performs path planning for each unmanned mining truck according to the state of each vehicle in a target control area and loading operation, then sends the planned path to each unmanned mining truck, and each unmanned mining truck runs according to the planned path to complete the operation.

Optionally, the ground centralized control system can also plan the path for the manned mining truck at the same time, send the planned path to the HMI of the manned mining truck for display, and the staff of the manned mining truck can travel according to the received planned path, so that the staff can travel according to the real-time optimal path, and the operation efficiency is improved.

In this embodiment, when each unmanned mining truck and manned mining truck are scheduled with the maximum loading operation efficiency as a target, a calculation model of the waiting time of the mining truck on all paths is built by using the total traffic on each path in a target control area and the waiting time of the mining truck on each working area, an objective function is built by using the calculation model of the waiting time of the mining truck on all paths, and the objective function corresponds to the target with the maximum loading operation efficiency when the objective function is minimum, so as to determine the unmanned mining truck and the manned mining truck which need to be scheduled. For example, by constructing a calculation model of the loading operation efficiency using the state information (idle state, position information, etc.) of the unmanned mining truck and the manned mining truck as the objective function, the minimum value of the objective function corresponds to the maximum loading operation efficiency, and by solving the minimum value of the objective function, the number of unmanned mining trucks and the manned mining trucks required to be dispatched and which unmanned mining trucks and manned mining trucks required to be dispatched can be obtained, thereby forming a dispatching strategy.

According to the dispatching method, from the angles of the unmanned mining truck and the manned mining truck, the turnover efficiency of the whole mining truck is improved by minimizing the waiting time of the whole mining truck, and the waiting time of the unmanned mining truck and the manned mining truck and the delay in production are reduced, so that the use efficiency of the mining truck is improved.

For example, the waiting time required by the mining truck can include loading area waiting time, crushing station queuing time, dumping site queuing time and the like, a calculation model C of the waiting time required by the mining truck on all paths can be constructed according to the following formula, and the mining truck which needs to be scheduled when the waiting time of the mining truck is minimum can be determined when the C takes the minimum value.

(1)

Wherein, Indicating the mining truck waiting time on the ith path,The total traffic flow on the i-th path, i.e., the number of vehicles on each path, is represented.

Optionally, the objective with the smallest travel distance in the objective function is to construct a total distance calculation model of the empty car running on all paths by using the empty car travel distance on each path and the number of vehicles on the empty car path in the objective control area, and the objective with the smallest travel distance corresponding to the objective with the smallest travel distance when the objective function comprising the total distance calculation model of the empty car running on all paths is smallest can automatically plan the optimal running routes of the unmanned mining truck and the manned mining truck, so that the empty car travel distance is shortened. The empty path is the path of the mining truck in an empty state. For the loaded ore trucks in a heavy truck state, the ore trucks after unloading in the crushing station/dumping site are in an empty truck state, so that whether the ore trucks are in a heavy truck or an empty truck state can be judged through the load signals of the ore trucks. The empty travel is the travel distance of the vehicle when the vehicle is unloaded (not loaded with materials), the smaller the empty travel distance is, the higher the utilization rate of the vehicle is, and the empty travel time of the mining truck can be reduced and the utilization rate and the transportation efficiency of the whole mining truck can be improved by globally optimizing the total distance of the empty travel distance of the mining truck on all paths such as coal transportation, rock transportation and the like from mine transportation.

For example, a total distance calculation model A for the empty car running on all paths can be constructed according to the empty car travel distance and the empty car flow on each path and the following formula, and when A takes the minimum value, the mining truck which needs to be scheduled when the empty car travel is the minimum value can be determined.

(2)

Wherein, Indicating the empty travel distance of the ith path,And (5) indicating the empty traffic on the ith path, wherein the empty traffic is the number of vehicles on each empty path.

Optionally, the objective function may be constructed by further including a goal of minimizing the idle time of the electric shovel, and the efficiency, the total working time and the idle time of each electric shovel are used to construct an electric shovel idle time calculation model, where the objective function including the electric shovel idle time calculation model is the goal of minimizing the idle time of the electric shovel. The electric shovel is used as the mining equipment matched with the ore card loading operation, if the smaller the idle time is, the higher the utilization rate is, the higher the operation efficiency is, and the efficiency maximization can be realized by taking the minimum electric shovel idle time as the target from the angle of the electric shovel which is used for operating in cooperation with the unmanned ore card and the manned ore card, so that the whole production efficiency is improved.

For example, a calculation model B of the idle time of the electric shovel can be constructed according to the efficiency of each electric shovel, the total working time of the electric shovel and the idle time of each electric shovel, and when B takes the minimum value, the mining truck which needs to be scheduled when the idle time of the electric shovel is the minimum value can be determined.

(3)

Wherein, Indicating the efficiency of the kth electric shovel, T indicating the total working time of the electric shovel,Indicating the idle time of the kth electric shovel.

Optionally, the method comprises the steps that the method comprises the steps of constructing an ore truck integral flow calculation model by using the unmanned ore truck flow and the manned ore truck flow on each path, and the method comprises the step of corresponding to the method comprising the step of constructing the target with the optimal number of the integral unmanned ore trucks and the manned ore trucks when the objective function comprising the ore truck integral flow calculation model is minimum. An excessive number of mining trucks can result in high operating costs, while if too small, it can be difficult to efficiently complete a job task. By regulating the least unmanned and manned mining trucks according to the mine throughput plan from a mine transportation global perspective, an optimal number of overall unmanned and manned mining trucks can be ensured.

For example, a calculation model D for calculating the overall mining truck flow can be constructed according to the unmanned mining truck flow and the manned mining truck flow on each path, and when D takes the minimum value, the number of mining trucks to be dispatched when the number of the overall unmanned mining truck and the manned mining truck is optimal can be determined.

(4)

Wherein, Representing the unmanned mining truck traffic on the ith path,Indicating the manned mining truck traffic on the ith path.

Preferably, the objective function can be jointly constructed by integrating the above objectives, so as to determine an optimal mining truck dispatching strategy according to the objectives of maximizing the loading efficiency, minimizing the idle travel, optimizing the idle time of the electric shovel and optimizing the number of the whole mining trucks, respectively distributing corresponding weight coefficients for the objectives, and weighting the objectives to form a final objective function. For example, the established objective function may be expressed specifically as:

(5)

wherein, alpha, beta, gamma, delta and epsilon are weight coefficients for balancing the importance of different optimization targets, and can be specifically configured according to the importance degree of each target. N represents the total number of paths, M represents the number of electric shovels, Indicating the empty travel distance of the ith path,Indicating empty traffic on the ith path,Indicating the efficiency of the kth electric shovel, T indicating the total operating time,Indicating the idle time of the kth electric shovel,Indicating the mining truck waiting time on the ith path,Indicating the total traffic on the ith path, including unmanned mining trucks and manned mining trucks,Representing the unmanned mining truck traffic on the ith path,Indicating the manned mine truck flow on the ith path.

According to the mixed scheduling strategy of the manned mining truck and the unmanned mining truck, the optimal operation route can be automatically planned on the premise of meeting production tasks, the empty travel can be shortened, the efficiency of the electric shovel can be maximized, and the waiting time of the whole mining truck is reduced.

In order to achieve the above-mentioned mixed scheduling objective, this embodiment may further set constraint conditions such as loading and unloading area continuous operation constraint, electric shovel loading and unloading capability constraint, ore yield constraint, and mixed scheduling safety distance constraint, where the loading and unloading area continuous operation constraint is a constraint condition that needs to be met when an ore truck continuously works in a loading area and an unloading area, the electric shovel loading and unloading capability constraint is a constraint that needs to be met by each electric shovel excavating capability, the ore yield constraint is a constraint condition that needs to be met by the total yield of each electric shovel, and the mixed scheduling safety distance constraint is a constraint condition that needs to be met by a safety distance between a manned ore truck and an unmanned ore truck.

Optionally, in order to ensure that the mining truck can continuously run in the shovel loading area, the coal unloading area of the crushing station and the soil discharging area, the continuous operation requirement of the mining truck in the loading area and the unloading area and the flow balance of the unmanned mining truck and the unmanned mining truck can be met, and the continuous operation constraint of the loading area can be configured as follows:

(6)

Alternatively, the electric shovel capacity constraints may be configured to:

(7)

Alternatively, the ore yield constraint may be configured to:

(8)

Wherein M represents the number of electric shovels, Indicating the yield of the kth electric shovel,Representing the planned production.

Alternatively, the hybrid scheduling security distance constraint may be configured to:

(9)

wherein, Representing the distance between the manned mining truck on the ith path and the unmanned mining truck on the jth path,Representing the minimum of the safe distance.

According to the embodiment, by adopting the mixed-knitting dispatching strategy, safe and efficient mixed-knitting dispatching between the manned vehicle and the unmanned mining truck can be realized, different types of unmanned mining cards and the manned vehicle can be effectively managed and dispatched, so that the unmanned vehicle and the unmanned mining truck can cooperatively operate, and full-mining-level safe mixed-knitting transportation can be realized.

And S03, judging whether each unmanned mining truck can collide with other vehicles or obstacles according to the received positioning information and the received obstacle information of each vehicle in the process of executing the operation of each mining truck according to the planned running path, and if so, controlling to send early warning information to the vehicles with the running collisions.

In this embodiment, during hybrid scheduling, it is required to ensure that the vehicle does not collide and collide with a static or dynamic obstacle during the automatic running process, that is, has an obstacle protection function. If the ground centralized control system judges that the unmanned mining truck exists and has running conflict with the obstacle, the ground centralized control system further comprises the step of rescheduling a path according to the current position, the safe parking position and the current speed of the unmanned mining truck with the conflict. For example, after the unmanned mining truck detects the obstacle, the distance between the obstacle and the expected path is calculated, if the distance is smaller than the safety threshold, the obstacle is judged to conflict with the vehicle, and the unmanned mining truck is controlled to reprogram a speed curve from the current position to the safety parking position according to the current position, the safety parking position and the current speed, so that the safety parking is realized.

In this embodiment, in the process of executing the operation according to the planned driving path of each mining truck, the ground centralized control system may determine whether each unmanned mining truck may generate a driving conflict with other vehicles (unmanned mining truck, manned vehicle) or obstacles according to the received positioning information and the obstacle information of each vehicle, and if it is determined that the driving conflict may occur, send early warning information to the corresponding vehicle to perform early warning. For example, if there are two unmanned mining trucks, if there is a collision, the warning information is sent to the two unmanned mining trucks, respectively, if there are an unmanned mining truck and a manned vehicle (manned mining truck, assisting vehicle), the warning information is sent to the unmanned mining truck and the manned vehicle, and if there is an obstacle in front of the unmanned mining truck, the warning information is sent to the unmanned mining truck. It will be appreciated that the warning function of the obstacle in front of the unmanned mining truck may also be implemented by an unmanned system inside the unmanned mining truck.

In this embodiment, when it is determined that the unmanned mining truck exists in the specified range around the manned vehicle according to the vehicle positioning information, the method further includes sending the running track of the unmanned mining truck to the terminal of the corresponding manned vehicle for display. Specifically, in the running process of the manned vehicle, the ground centralized control system can detect the vehicle state around the manned vehicle, if the unmanned mining truck is detected to exist near the manned vehicle, the running track of the unmanned mining truck is sent to the cooperative operation terminal of the manned vehicle, and the running track of the unmanned mining truck is displayed on the cooperative operation terminal of the manned vehicle, so that a driver of the manned vehicle can conveniently observe whether the unmanned mining truck exists near the unmanned mining truck or not, and necessary evading measures can be taken in advance. Optionally, whether the manned vehicle approaches the intersection or not can be detected, if so, corresponding prompt information or intersection position information is sent to a collaborative terminal of the manned vehicle, so that the manned vehicle is prompted to conduct driving planning in advance.

In this embodiment, during the running of the unmanned mining truck according to the planned path, whether a dangerous position point exists in the planned path is detected, when the dangerous position point exists is detected, the dangerous position point is retracted along the planned path by a safety distance to obtain a new safety track point, so as to ensure the running safety of the unmanned mining truck, and after the safety distance is retracted, the unmanned mining truck continues to run with the new safety track point as a starting point. The dangerous position point comprises any one of a communication positioning vehicle, a communication fault vehicle, a blocking area, a safety track envelope of the current vehicle, a safety envelope of other controlled vehicles and the like, and the safety distance can be determined according to a vehicle positioning control error, a vehicle backward sliding distance and a safety margin.

Specifically, according to the path track calculated by vehicle planning and the obstacle information uploaded to the ground centralized control system by the unmanned vehicle-mounted system, the ground centralized control system periodically calculates whether dangerous points exist in the planned track, and when the dangerous points exist, the dangerous point coordinates retract a safety distance Ls along the planned track to obtain a new safety track endpoint Ps, as shown in fig. 6. Wherein, the safe distance Ls is calculated according to the following formula: The safety distance allowance can be configured according to specific situations to ensure enough safety space, lu represents control and positioning errors, ps represents a safety track end point, namely a new safety track end point after the safety distance Ls is retracted, lf represents the horizontal distance from the center of a rear axle of the mining truck to the forefront end of the vehicle, lr represents the horizontal distance from the center of the rear axle of the mining truck to the rearmost end of the vehicle, and Lrb represents the backward sliding distance, namely the backward sliding distance which can occur in the process of stopping or starting the mining truck on a ramp. In the continuous running process of the unmanned mining truck, the ground centralized control system can continuously monitor the running condition of the mining truck and dynamically adjust the running track of the mining truck according to the obstacle information and the planned path uploaded in real time.

Optionally, a priority principle in the case of conflict can be set, and the unmanned mining truck can avoid other controlled vehicles preferentially in the driving process, so that the safety envelopes of the unmanned mining truck and other vehicles are ensured not to overlap. For example, if it is determined that the manned vehicle collides with the unmanned mining truck in the intersection or the dumping region, the control prioritizes the passing of the manned vehicle. Because the unmanned mining truck cannot acquire the driving intention of the manned vehicle, when the road right has conflict, the principle of prioritizing the manned vehicle can be adopted. When there is a collision in driving, the unmanned vehicle parks and dodges, and when it is confirmed that the unmanned mining card has parked and dodges and there is no track that collides with the unmanned vehicle, the unmanned vehicle can pass through the collision area preferentially.

Alternatively, the safe distance of the manned vehicle from the vehicle in front (manned/unmanned vehicle) is ensured by the driver of the manned vehicle, as shown in section B, C of fig. 7. When the unmanned vehicle follows the manned vehicle, the GMS guarantees the safe distance between the unmanned vehicle and the front manned vehicle, as shown in the A, D section in fig. 7.

Specifically, when a path conflict occurs between a manned vehicle and an unmanned mining truck at an intersection, as shown in fig. 8, the unmanned mining truck is controlled to stop, the manned vehicle is actively allowed to pass, and only one trolley is allowed to pass through an intersection area. When a path conflict occurs between an unmanned mining truck and a manned mining truck in a soil discharge area, as shown in fig. 9, the unmanned mining truck (a) corresponds to the situation that the unmanned mining truck is in front and the manned vehicle is behind, and the unmanned mining truck (b) corresponds to the situation that the manned vehicle is in front and the unmanned vehicle is behind, the unmanned vehicle parks and avoids no matter the unmanned vehicle is in front or the unmanned vehicle is in front, and the unmanned vehicle preferentially passes through.

In this embodiment, when it is determined that a communication positioning fault occurs in a front unmanned mining truck (controlled vehicle) during running, the method further includes calculating a safety envelope of the front fault vehicle by using last valid positioning information of the front fault vehicle, that is, a maximum space range that the front fault vehicle may occupy, and determining a safety track point of the rear controlled vehicle according to the safety envelope of the front fault vehicle, that is, determining a safety track point of a vehicle behind the fault vehicle by using last valid positioning information of the front fault vehicle, so that a safety distance exists between the safety track point of the rear vehicle and the safety envelope of the vehicle determined according to the last valid positioning information of the front fault vehicle.

Specifically, the position of the fault vehicle can be determined according to the last effective positioning information of the fault vehicle, and the possible track range can be estimated by combining the last movement direction and the last speed of the fault vehicle, so that the safety envelope of the fault vehicle is determined. And if the safety track envelope of the unmanned mining truck invades the planned track envelope of other vehicles, withdrawing the safety track end point of the unmanned vehicle by the safety distance Ls as a conflict point. Thus, the distance between the front fault vehicle and the rear vehicle needs to be at least larger than the sum of the safety envelope radius and the safety distance of the front fault vehicle to ensure the running safety of the vehicle.

For example, assuming that the last valid locating point of the front controlled fault vehicle is (X _f,Y_f) and the safety envelope of the controlled fault vehicle is estimated to be radius r _f, the following condition is satisfied for the safety track point (X _s,Y_s) of the rear tracking vehicle:

(10)

wherein, Is the estimated safety envelope radius of the failed vehicle ahead.

Specifically, a safety protection function is realized by configuring a safety protection module, and a safety track point of the vehicle is calculated when the vehicle has communication faults. A vehicle (including an unmanned mining card and a manned vehicle) which is provided with communication and positioning equipment and has normal equipment operation is taken as a controlled vehicle, and a system external vehicle which is provided with the communication and positioning equipment but has no equipment failure and is not provided with the communication and positioning equipment is taken as an uncontrolled vehicle. The ground centralized control system monitors the communication state of all the controlled vehicles, and if no data of the vehicles or invalid positioning data of the vehicles are received for 3 seconds (configurable), the controlled vehicles are converted into non-controlled vehicles. The ground centralized control system stores the safety track or safety envelope of the uncontrolled vehicle until the envelope is deleted, when two vehicles are tracked, if the front controlled vehicle has communication positioning faults in the driving process, the safety protection module calculates the safety track dangerous point of the tracked vehicle and adopts the front controlled vehicle to effectively position the safety track point of the rear vehicle for the last time, if the safety track envelope of the controlled vehicle invades the planning track envelope of the normal controlled vehicle, the safety track end point of the unmanned vehicle is a conflict point withdrawing safety distance, as shown in fig. 10, wherein (a) correspondingly shows the effect schematic diagram of the safety track dangerous point X (track envelope intersection point) of the tracked vehicle B invaded the planning track envelope of the front controlled vehicle A, and (B) shows the effect schematic diagram of the safety track point Y of the tracked vehicle B according to the withdrawal safety track dangerous point X of the front controlled vehicle A.

Further, when the unmanned mining card runs, safety risks exist, besides the automatic emergency safety protection through the vehicle, the unmanned mining card can be guaranteed to safely stop through four layers of protection mechanisms of a cooperative vehicle emergency stop button, a remote cockpit emergency stop button and a ground centralized control system emergency stop button, and four layers of protection of a full mining-level vehicle, a cooperative vehicle, an emergency connection pipe and a ground can be realized, so that the safety protection under the condition of vehicle emergency is realized through the multiple safety protection of the mining card unmanned and the manned vehicle.

The invention can realize the mixed dispatching of all-mine-level manned vehicles and unmanned mining trucks, realize the cooperative operation and mixed transportation operation of the unmanned mining trucks and the multi-type vehicles, effectively manage and dispatch the unmanned mining cards and the manned vehicles of different types, solve the problem of cross transportation in the multi-type vehicle mixed running mode, realize the high-efficiency coal-rock mixed transportation of all-mine-level and improve the adaptability of an unmanned system.

The embodiment also provides a mixed scheduling device for unmanned mining trucks and manned vehicles, comprising:

the information receiving module is used for receiving positioning information sent by various types of vehicles in the target control area and nearby obstacle information sent by various unmanned mining trucks in real time, wherein the types of vehicles comprise manned vehicles and unmanned mining trucks, and the manned vehicles comprise manned mining trucks and manned cooperative auxiliary vehicles;

The dispatching control module is used for constructing and forming an objective function by taking the maximum loading operation efficiency, the minimum empty travel and the optimal total traffic flow of the unmanned mining trucks and the manned mining trucks on each path in the objective control area and respectively distributing corresponding weight coefficients for each objective according to the positioning information of various vehicles in the objective control area, dispatching each unmanned mining truck and each manned mining truck according to the constructed objective function, planning a driving path for each dispatched unmanned mining truck, wherein the empty travel is the distance travelled by the unmanned mining truck and the unmanned mining truck when the unmanned mining truck is empty, the objective with the maximum loading operation efficiency uses the total traffic flow of the unmanned mining trucks and the unmanned mining trucks on each path in the objective control area and the required waiting time of the unmanned mining trucks and the manned mining trucks in each working area, and constructing a corresponding calculation model by using the traffic flow of the unmanned mining trucks and the traffic flow of the unmanned mining trucks on each path by the objective with the optimal quantity of the unmanned mining trucks and the unmanned mining trucks;

The hybrid scheduling device for the unmanned mining truck and the manned vehicle in this embodiment corresponds to the hybrid scheduling method for the unmanned mining truck and the manned vehicle in a one-to-one manner, and will not be described in detail here.

The present embodiment also provides a computer device comprising a processor and a memory, the memory being for storing a computer program, the processor being for executing the computer program to perform a method as described above.

It will be understood that the method in this embodiment may be performed by a single device, for example, a computer or a server, or may be implemented by a plurality of devices in a distributed scenario, where one device of the plurality of devices may perform only one or more steps in the method in this embodiment, and the plurality of devices interact to implement the method. The processor may be implemented as a general-purpose CPU, a microprocessor, an application-specific integrated circuit, or one or more integrated circuits, etc. for executing the relevant program to implement the methods described in this embodiment. The memory may be implemented in the form of read-only memory ROM, random access memory RAM, static storage devices, dynamic storage devices, etc. The memory may store an operating system and other application programs, and when the methods of the present embodiments are implemented in software or firmware, the associated program code is stored in the memory and invoked for execution by the processor.

The embodiment also provides a mixed scheduling system of unmanned mining trucks and manned vehicles, comprising:

a plurality of unmanned mining trucks, each of which is provided with a vehicle-mounted positioning device, a communication device and an external environment detection sensor;

The dispatching device is used for dispatching each unmanned mining truck and the manned mining truck by adopting the dispatching method;

In a specific application embodiment, the hybrid dispatching system of the unmanned mining truck and the manned vehicle can adopt a framework as shown in fig. 1, wherein the dispatching device is arranged in a ground centralized control system, namely, a software module capable of realizing the dispatching method is loaded in the ground centralized control system, and the ground centralized control system realizes the hybrid dispatching of each unmanned mining truck and each manned mining truck.

The present embodiment further provides a computer readable storage medium storing a computer program which, when executed by a processor, implements a method as described above.

It will be appreciated by those skilled in the art that the above-described embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-readable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein. The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks. These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

The foregoing is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. While the invention has been described with reference to preferred embodiments, it is not intended to be limiting. Therefore, any simple modification, equivalent variation and modification of the above embodiments according to the technical substance of the present invention shall fall within the scope of the technical solution of the present invention.

Claims

1. The mixed scheduling method for the unmanned mining truck and the manned vehicle is characterized by comprising the following steps of:

According to the positioning information of various vehicles in a target control area received in real time, comprehensively taking the maximum loading operation efficiency, the minimum empty travel and the optimal total traffic flow of the unmanned mining trucks and the manned mining trucks on each path in the target control area, respectively distributing corresponding weight coefficients for each target, constructing and forming an objective function after weighting each target, dispatching each unmanned mining truck and the manned mining truck according to the constructed objective function, respectively planning a driving path for each dispatched unmanned mining truck, wherein the empty travel is the distance traveled by the unmanned mining truck and the unmanned mining truck when the unmanned mining truck is empty, the target with the maximum loading operation efficiency uses the total traffic flow of the unmanned mining trucks and the unmanned mining trucks on each path in the target control area, and the waiting time required by each unmanned mining truck in each working area, so that the waiting time of the whole mining truck is minimized, and the optimal target of the total unmanned mining trucks and the unmanned mining trucks uses the traffic flow of the unmanned mining trucks on each path, and the optimal calculation model is constructed by the corresponding traffic flow of the unmanned mining trucks and the unmanned mining trucks on each path;

The calculation model corresponding to the target with the maximum loading operation efficiency is as follows:

wherein, Indicating the mining truck waiting time on the ith path,The total traffic flow on the ith path is represented, the total traffic flow is the number of vehicles on each path, and N represents the total number of paths;

The target with the minimum empty travel distance builds a total distance calculation model of empty travel on all paths by using the empty travel distance and the number of vehicles on each path in a target control area, and the target with the minimum empty travel distance corresponding to the target with the minimum empty travel distance when the objective function of the total distance calculation model of empty travel on all paths is minimum comprises the following total distance calculation models of empty travel on all paths:

wherein, Indicating the empty travel distance of the ith path,The empty traffic flow on the ith path is represented, and the empty traffic flow is the number of vehicles on each empty path;

The calculation model corresponding to the optimal number of the integral unmanned mining trucks and the optimal number of the manned mining trucks is as follows:

wherein, Representing the unmanned mining truck traffic on the ith path,Representing the flow of the manned mining truck on the ith path;

In the process that each unmanned mining truck executes operation according to a planned running path, judging whether each unmanned mining truck can generate running conflict with other vehicles or obstacles according to the received positioning information and the received obstacle information of each vehicle, if so, controlling to send early warning information to the vehicles with the running conflict, and dynamically adjusting the running track of the mining truck according to the obstacle information and the planned path uploaded in real time;

The method comprises the steps of setting any one or more of loading and unloading area continuous operation constraint, electric shovel loading and unloading capacity constraint, ore yield constraint and mixed scheduling safety distance constraint, wherein the loading and unloading area continuous operation constraint is a constraint condition to be met when an ore truck continuously works in a loading area and an unloading area, the electric shovel loading and unloading capacity constraint is a constraint to be met by each electric shovel loading and unloading capacity, the ore yield constraint is a constraint condition to be met by the total yield of each electric shovel, and the mixed scheduling safety distance constraint is a constraint condition to be met by the safety distance between a manned ore truck and an unmanned ore truck;

the continuous operation constraint of the loading and unloading area is as follows:

;

wherein, Indicating the number of paths entering the p-th electric shovel loading area, the crushing station coal unloading area and the dumping area, N _o indicating the number of paths of the ore-sending trucks from the electric shovel loading area, the crushing station coal unloading area and the dumping area,Indicating the flow of the unmanned mining truck entering the p-th electric shovel loading area, the coal unloading area of the crushing station and the soil discharging area,Indicating the flow of the manned mining truck entering the p-th electric shovel loading area, the coal unloading area of the crushing station and the soil discharging area,Represents the unmanned mining truck traffic emitted by the q-th path,Representing the flow of the manned mining truck sent by the q-th path;

the electric shovel mining capacity constraint is as follows:

;

wherein, The number of paths of the vehicle flow sent by the kth electric shovel is indicated,Indicating the unmanned mining truck traffic sent by the first path,Indicating the manned mining truck traffic sent by the first path,Representing the maximum mining rate of the kth electric shovel;

The ore yield constraint is:

Wherein M represents the number of electric shovels, Indicating the yield of the kth electric shovel,Representing a planned production;

The mixed scheduling safety distance constraint is as follows:

2. The method for mixed scheduling of unmanned mining trucks and manned vehicles according to claim 1, wherein the objective function is constructed by further including an objective of minimizing the idle time of the electric shovel, wherein the efficiency of each electric shovel, the total operating time and the idle time of each electric shovel are used to construct an electric shovel idle time calculation model, and the objective of minimizing the idle time of the electric shovel is corresponding to the objective of minimizing the idle time of the electric shovel when the objective function including the electric shovel idle time calculation model is minimum.

3. The method for mixed scheduling of unmanned mining trucks and manned vehicles according to any one of claims 1-2, further comprising detecting whether dangerous position points exist in a planned path in the process of driving the unmanned mining trucks according to the planned path, and when the dangerous position points exist, retracting safety distances of the dangerous position points along the planned path to obtain new safety track points, wherein the unmanned mining trucks continue to drive with the new safety track points as starting points, the dangerous position points comprise position points where any one of communication positioning vehicles, communication fault vehicles, blocking areas and safety track envelopes of current vehicles invade other controlled vehicle safety envelopes, and the safety distances are determined according to vehicle positioning control errors, vehicle backward sliding distances and safety margins.

4. The method for mixed scheduling of unmanned mining trucks and manned vehicles according to any one of claims 1 to 2, wherein when it is determined that a communication positioning fault occurs in a front unmanned mining truck during traveling, the last valid positioning information of the front fault vehicle is used to calculate a safety envelope of the front fault vehicle, and a safety track point of a rear vehicle is determined according to the safety envelope of the front fault vehicle, so that a safety distance exists between the safety track point of the rear vehicle and the safety envelope of the vehicle determined according to the last valid positioning information of the front fault vehicle.

5. The method for mixed dispatching of the unmanned mining truck and the manned vehicle according to any one of claims 1 to 2, further comprising sending the running track of the unmanned mining truck to a terminal of the corresponding manned vehicle for display when it is judged that the unmanned mining truck exists in a specified range around the manned vehicle according to the vehicle positioning information.

6. The method for mixed scheduling of unmanned mining trucks and manned vehicles according to any one of claims 1 to 2, wherein if it is determined that there is a collision between the unmanned mining truck and an obstacle, the method further comprises rescheduling a route according to the current position, safe parking position and current speed of the unmanned mining truck having the collision.

7. An unmanned mining truck and manned vehicle mixed scheduling device for implementing the unmanned mining truck and manned vehicle mixed scheduling method according to any one of claims 1 to 6, characterized by comprising:

8. A computer device comprising a processor and a memory for storing a computer program, wherein the processor is configured to execute the computer program to perform the method of any of claims 1-6.

9. An unmanned mining truck and manned vehicle hybrid scheduling system, comprising:

Scheduling means for scheduling each unmanned mining truck, manned mining truck using the method of any one of claims 1 to 6;

10. A computer readable storage medium storing a computer program, wherein the computer program when executed by a processor implements the method of any one of claims 1-6.