Vehicle scheduling method and system for unmanned driving system of surface mine

Abstract

The invention provides a vehicle scheduling method and system for an unmanned driving system of a surface mine, and the method comprises the steps: obtaining a vehicle state in real time through a global scheduling layer, and dividing a loading region and an unloading region into independent resource pools through pooling scheduling; the loading area scheduling layer distributes tasks based on the principle that the number of to-be-loaded vehicles is minimum, and scheduling is optimized in combination with dynamic path planning and a task adjustment mechanism. The system supports unloading area synchronous scheduling logic, integrates strategies such as road load optimization and road right priority, and can be manually intervened and adjusted. The method solves the problem of insufficient flexibility of traditional scheduling, dynamically adapts to emergencies, improves the utilization rate of vehicles and equipment, and remarkably improves the overall production efficiency of the unmanned driving system of the surface mine.

Description

Technical Field

[0001] This invention relates to the field of unmanned driving technology in open-pit mines, and in particular to a vehicle scheduling method and system for an unmanned driving system in open-pit mines. Background Technology

[0002] As open-pit mines place increasing demands on safety and efficiency, driverless dump trucks are gradually replacing manual drivers in material transportation. Their core operational processes are as follows: Figure 1 As shown, this is a "loading-transporting-unloading" cycle, where the loading equipment loads materials into dump trucks in the loading area, the vehicles travel along the transport road to the unloading area to unload, and then return to the loading area to repeat the operation.

[0003] In existing technologies, the scheduling of unmanned mining systems is mostly "point-to-point manual scheduling," meaning that loading and unloading points and fixed transportation routes are manually designated. Because the operational flexibility of autonomous driving systems is lower than that of manual driving, fixed scheduling cannot dynamically adapt to unexpected situations such as vehicle malfunctions and road congestion, making it difficult to maximize production efficiency. Therefore, there is an urgent need for a strategy that can optimize vehicle scheduling in real time between loading and unloading areas and transportation routes to improve the overall production capacity of unmanned driving systems. Summary of the Invention

[0004] The purpose of this invention is to provide a vehicle scheduling method and system for an unmanned driving system in an open-pit mine, which dynamically schedules vehicles from a global perspective, optimizes the task allocation between loading and unloading areas, and improves the overall production efficiency of the system.

[0005] According to one objective of the present invention, the present invention provides a vehicle scheduling method for an unmanned driving system in an open-pit mine, comprising the following steps: S1. The global scheduling layer obtains the real-time operating status of all unmanned dump trucks through the unmanned driving platform. S2. The vehicle pooling scheduling method is adopted to divide multiple loading and unloading areas into independently operating resource pools, and to allocate work tasks to empty vehicles based on the loading area, unloading area and transportation road information in the resource pool. S3. The loading area scheduling layer assigns a target loading area to empty vehicles based on the principle of minimizing the number of vehicles waiting to be loaded in the loading area; the number of vehicles waiting to be loaded in the loading area is the difference between the total number of all vehicles ready to be loaded in the same loading area and the number of loading positions. S4. Dynamically adjust task assignment based on real-time status during vehicle operation.

[0006] Furthermore, the number of vehicles to be loaded in the loading area is calculated as follows: The same loading area contains at least one loading device and a corresponding loading position, and the total number of vehicles ready to be loaded includes vehicles at the loading positions and vehicles waiting in the loading area; Number of vehicles waiting to be loaded in the loading area = Total number of vehicles ready to be loaded - Number of loading positions.

[0007] Furthermore, the loading area scheduling layer also includes a vehicle allocation weight coefficient adjustment mechanism: Each loading zone is assigned a weight coefficient for its vehicles. The adjusted number of vehicles waiting to be loaded in the loading zone = the actual number of vehicles waiting to be loaded × the vehicle weight coefficient. Empty vehicles are given priority to the loading zone with the fewest vehicles waiting to be loaded after the adjustment.

[0008] Furthermore, the loading area scheduling layer also includes a dynamic path planning step: When the number of vehicles waiting to be loaded is the same in multiple loading areas, calculate the path length between the current position of the empty vehicle and each target loading area, and select the target loading area according to the preset priority. The preset priority includes shortest path priority, longest path priority, or random assignment. If a vehicle has the ability to calculate travel time in real time, the path length can be replaced with the estimated travel time.

[0009] Furthermore, the loading area scheduling layer also includes a dynamic task adjustment mechanism: As an empty vehicle travels toward the target loading area, it re-queries the real-time number of vehicles waiting to be loaded in each loading area at each intersection and reallocates the target loading area based on the latest data. When reassigning tasks, routes that have already been traveled must be excluded to avoid path loops.

[0010] Furthermore, it also includes an unloading area scheduling layer, which adopts the same scheduling logic as the loading area scheduling layer, replacing the loading area with the unloading area, and assigning a target unloading area to the heavy-load vehicle based on the principle of minimizing the number of vehicles to be unloaded in the unloading area.

[0011] Furthermore, it also includes road load factor optimization strategies: When multiple paths lead to the same target loading or unloading area, the path with the lowest road load rate is selected, where the road load rate = the number of vehicles currently traveling on the road ÷ the road length.

[0012] Furthermore, it also includes right-of-way priority scheduling strategies: When multiple vehicles collide on the same road or at the same intersection, they should be allowed to pass in the following order: (1) Heavy-duty vehicles have priority over unloaded vehicles; (2) Operating vehicles have priority over temporarily parked vehicles; (3) High-speed vehicles have priority over low-speed vehicles; (4) Vehicles going uphill have priority over vehicles going downhill; (5) Vehicles going straight have priority over vehicles turning.

[0013] Furthermore, it also includes the scheduling steps for the truck bed cleaning task: When the loaded material is sticky or at risk of freezing, after the vehicle completes the unloading task, it will automatically go to the truck bed cleaning equipment to perform the cleaning task according to the preset frequency or material residue threshold, and return to the loading area after the cleaning is completed.

[0014] According to another objective of the present invention, the present invention provides an unmanned driving system for open-pit mines based on the vehicle scheduling method described above, comprising: The autonomous driving platform monitors vehicle status in real time and dynamically assigns tasks. Multiple driverless dump trucks; Multiple loading and unloading areas; The communication module is used for data interaction between the vehicle and the platform; The task replanning module is used to dynamically adjust task assignments while the vehicle is in motion. Truck bed cleaning equipment is used to perform truck bed cleaning tasks.

[0015] This invention's technical solution acquires vehicle status in real time through a global scheduling layer and employs pooled scheduling to divide independent resource pools, achieving efficient matching between loading and unloading areas. The loading area scheduling layer allocates tasks based on the principle of minimizing the number of vehicles to be loaded, balancing the load of each loading area. This solves the problems of poor flexibility and difficulty in handling emergencies in traditional manual scheduling, dynamically adapting to scenarios such as vehicle malfunctions and road congestion, reducing vehicle waiting time, improving the utilization rate of loading equipment, and optimizing the overall transportation efficiency and production capacity of the open-pit mine unmanned driving system. Attached Figure Description

[0016] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0017] Figure 1 A schematic diagram of the traditional open-pit mine vehicle operation process; Figure 2 This is a schematic diagram illustrating the calculation of the number of vehicles to be loaded in the loading area according to an embodiment of the present invention; Figure 3 This is a schematic diagram of multi-loading area scheduling according to an embodiment of the present invention; Figure 4 This is a schematic diagram of task replanning in an embodiment of the present invention. Detailed Implementation

[0018] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," and "counterclockwise," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limiting this invention.

[0020] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the stated features. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified. Furthermore, the terms "installed," "connected," and "linked" should be interpreted broadly; for example, they may refer to a fixed connection, a detachable connection, or an integral connection; they may refer to a mechanical connection or an electrical connection; they may refer to a direct connection or an indirect connection through an intermediate medium; and they may refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0021] Example 1 A vehicle dispatching method for an unmanned driving system in an open-pit mine includes the following steps: S1. Obtain the real-time operating status of all vehicles through the autonomous driving platform; S2. Divide multiple loading and unloading areas into several resource pools, with each resource pool operating independently; S3. Dynamically allocate empty vehicles to the optimal loading area based on the number of vehicles waiting to be loaded in each loading area; S4. Dynamically adjust task assignment based on real-time status during vehicle operation.

[0022] In this embodiment, the number of vehicles to be loaded in the loading area in S3 is calculated as follows: The total number of vehicles waiting in front of all loading equipment in the same loading area minus the number of loading positions in that loading area; Optionally, a vehicle allocation weighting coefficient can be introduced for weighted calculation. The vehicle allocation weighting coefficient can be manually set to adjust the vehicle allocation priority of each loading area.

[0023] The vehicle scheduling method in this embodiment also includes a manual intervention mechanism, which allows manual designation of vehicles to perform specific tasks and synchronous updates of the number of vehicles waiting to be loaded in the relevant loading areas.

[0024] In this embodiment, the dynamic allocation strategy in S4 includes: When a vehicle receives a loading task, select the loading area with the fewest vehicles to be loaded; During the vehicle's journey, it is reassessed and may be reassigned at each intersection it passes.

[0025] In this embodiment, when the number of vehicles to be loaded is the same in multiple loading areas, the target loading area is selected based on the path length or the estimated travel time. The path selection strategy includes: shortest path priority, longest path priority, or random assignment.

[0026] The vehicle scheduling method in this embodiment also includes a task group binding mechanism, which binds a specific loading area to an unloading area, so that after a vehicle completes loading, it can only go to the bound unloading area to unload.

[0027] The vehicle scheduling method in this embodiment also includes a scheduling mechanism within the loading area, which allocates vehicles to idle loading equipment for loading.

[0028] The vehicle scheduling method in this embodiment also includes an unloading area scheduling mechanism, whose scheduling logic is consistent with that of the loading area scheduling mechanism.

[0029] The vehicle dispatching method in this embodiment also includes a general dispatching strategy, including: Set a maximum capacity limit for the loading area to avoid traffic congestion at intersections; Choose a driving route based on road load factor; Supports vehicle grouping and region binding; Supports triggering and scheduling of truck bed cleaning tasks; Supports enabling and disabling sub-partitions; Set road right-of-way priority rules; Supports multi-lane vehicle allocation settings.

[0030] In this embodiment, the right-of-way priority rules include: Heavy-duty vehicles take priority over unloaded vehicles; Operating vehicles have priority over temporarily parked vehicles; Faster vehicles have priority over slower vehicles; Vehicles going uphill have priority over vehicles going downhill. Vehicles going straight have priority over vehicles turning.

[0031] Example 2 An unmanned driving system for open-pit mines includes: An unmanned driving platform is used to execute the vehicle scheduling method of the unmanned driving system in the open-pit mine in Example 1. Multiple driverless dump trucks; Multiple loading and unloading areas; The communication module is used for data interaction between the vehicle and the platform.

[0032] In this embodiment, the autonomous driving platform also includes a task replanning module, which is used to dynamically adjust task assignments during vehicle operation.

[0033] The unmanned driving system in this embodiment also includes a truck bed cleaning device for performing truck bed cleaning tasks.

[0034] In this embodiment, the autonomous driving platform monitors the vehicle status in real time and dynamically allocates tasks.

[0035] The scheduling process is as follows: Initialize resource pools: Divide the loading and unloading areas into multiple resource pools; Calculate the number of vehicles to be loaded: Calculate the number of vehicles to be loaded in each loading area based on the real-time vehicle location; Task allocation: Empty vehicles are assigned to the target loading area based on the principle of minimizing the number of vehicles to be loaded; Dynamic replanning: Vehicles reassess tasks at intersections and reassign them if necessary; Manual intervention: Supports manual task assignment and system status updates; Unloading and Cleaning: After unloading, perform the truck bed cleaning task as needed.

[0036] Example 3 A vehicle dispatching method for an unmanned driving system in an open-pit mine includes the following steps: The global scheduling layer obtains the real-time operating status of all unmanned dump trucks through the unmanned driving platform. It adopts a vehicle pooling scheduling method to divide multiple loading and unloading areas into independently operating resource pools. Based on the loading area, unloading area and transportation road information in the resource pool, it assigns operation tasks to empty vehicles. The loading area scheduling layer assigns target loading areas to empty vehicles based on the principle of "minimum number of vehicles waiting to be loaded in the loading area". The "number of vehicles waiting to be loaded in the loading area" is the difference between the total number of vehicles ready to be loaded in the same loading area and the number of loading positions.

[0037] In this embodiment, in vehicle pooling scheduling, the division of resource pools is based on the type of operation or the characteristics of materials. The loading area, unloading area and transportation road in each resource pool form an independent scheduling unit, and the division of resource pools can be adjusted by manual configuration.

[0038] In this embodiment, the "number of vehicles waiting to be loaded in the loading area" is calculated as follows: The same loading area contains at least one loading device and a corresponding loading position. The total number of vehicles ready to be loaded includes vehicles on the loading positions and vehicles waiting in the loading area. The number of vehicles waiting to be loaded in the loading area = the total number of vehicles ready to be loaded - the number of loading positions.

[0039] In this embodiment, the loading area scheduling layer also includes a vehicle allocation weight coefficient adjustment mechanism: Each loading zone is assigned a weight coefficient for its vehicles. The adjusted number of vehicles waiting to be loaded in the loading zone = the actual number of vehicles waiting to be loaded × the vehicle weight coefficient. Empty vehicles are given priority to the loading zone with the fewest vehicles waiting to be loaded after the adjustment.

[0040] In this embodiment, the loading area scheduling layer further includes a dynamic path planning step: When the number of vehicles waiting to be loaded in multiple loading areas is the same, the path length between the current position of the empty vehicle and each target loading area is calculated based on the A algorithm, and the target loading area is selected according to the preset priority (shortest path priority, longest path priority, or random assignment); if the vehicle has the ability to calculate the travel time in real time, the path length can be replaced with the estimated travel time.

[0041] In this embodiment, the loading area scheduling layer also includes a dynamic task adjustment mechanism: When an empty vehicle is en route to the target loading area, it re-checks the real-time number of vehicles waiting to be loaded in each loading area at each intersection and reassigns the target loading area based on the latest data. When reassigning tasks, it is necessary to exclude roads that have already been traveled to avoid path loops.

[0042] The vehicle scheduling method in this embodiment also includes an unloading area scheduling layer. The unloading area scheduling layer adopts the same scheduling logic as the loading area scheduling layer, but replaces "loading area" with "unloading area". Based on the principle of "minimum number of vehicles to be unloaded in the unloading area", a target unloading area is assigned to the heavy-duty vehicle.

[0043] The vehicle dispatching method in this embodiment also includes a manual intervention mechanism: It supports manually specifying the operation tasks of vehicles during the automatic scheduling process, and simultaneously updates the number of vehicles waiting to be loaded in the loading area or the number of vehicles waiting to be unloaded in the unloading area corresponding to the original task and the new task.

[0044] The vehicle dispatching method in this embodiment also includes a dispatching step within the loading area: Once a vehicle enters the target loading area, it will be assigned to an available loading position first; if all loading positions are occupied, the vehicle will wait in line in the waiting area.

[0045] The vehicle dispatching method in this embodiment also includes a road load factor optimization strategy: When multiple paths lead to the same target loading or unloading area, the path with the lowest road load rate is selected, where the road load rate = the number of vehicles currently traveling on the road ÷ the road length.

[0046] The vehicle dispatching method in this embodiment also includes a task group binding mechanism: By binding a designated loading area and unloading area into a task group, a vehicle can only go to the bound unloading area to unload after completing the loading task in that loading area.

[0047] The vehicle scheduling method in this embodiment also includes a right-of-way priority scheduling strategy: When multiple vehicles collide on the same road or at the same intersection, they should be allowed to pass in the following order: (1) Heavy-duty vehicles have priority over unloaded vehicles; (2) Operating vehicles have priority over temporarily parked vehicles; (3) High-speed vehicles have priority over low-speed vehicles; (4) Vehicles going uphill have priority over vehicles going downhill; (5) Vehicles going straight have priority over vehicles turning.

[0048] The vehicle dispatching method in this embodiment also includes a truck bed cleaning task dispatching step: When the loaded material is sticky or at risk of freezing, after the vehicle completes the unloading task, it will automatically go to the truck bed cleaning equipment to perform the cleaning task according to the preset frequency or material residue threshold, and return to the loading area after the cleaning is completed.

[0049] The vehicle dispatching method in this embodiment also includes a sub-zone management mechanism: The loading or unloading area can be further divided into multiple sub-zones. When a sub-zone does not meet the traffic requirements due to road conditions, it can be manually closed. The scheduling system will automatically avoid the closed sub-zone during route planning.

[0050] The vehicle scheduling method in this embodiment also includes a vehicle grouping and binding mechanism: Vehicles are manually grouped into specific loading and unloading areas, and the vehicles in the group only perform scheduling tasks between the bound loading and unloading areas.

[0051] In this embodiment of the vehicle dispatching method, the global dispatching layer also includes an exception handling mechanism: When a vehicle malfunctions, the road is blocked, or the target loading / unloading area is unavailable, the corresponding vehicle's task is immediately marked as canceled, the number of vehicles waiting to be loaded / unloaded in the relevant loading / unloading area is updated, and the vehicle is reassigned a task.

[0052] Example 4 This embodiment provides a detailed description of the vehicle dispatching method of an unmanned driving system for open-pit mines according to the present invention from a specific application perspective: Firstly, a global scheduling strategy can be implemented using vehicle pooling. During operation, vehicles may experience unpredictable downtime due to malfunctions, site maintenance, or other unforeseen factors, all of which affect scheduling results. Individual vehicles cannot know the operational status of other vehicles. Therefore, a global perspective is needed to view the operational status of all vehicles—this is the autonomous driving platform—to allocate tasks to each vehicle in real time. Pooling scheduling involves manually assigning multiple loading and unloading areas into multiple resource pools based on factors such as task or material characteristics, with each resource pool operating independently.

[0053] Loading area scheduling strategy: The overall scheduling principle is "the loading area with the fewest vehicles waiting to be loaded will be the loading position where the currently unmanned dump truck is assigned," such as... Figure 2 As shown: The definition of "number of vehicles waiting to be loaded in the loading area" is as follows: When multiple "loading devices" share the same "loading area", the area where these loading devices and their corresponding loading positions are located is considered as one "loading area". Starting from each loading device in the same "loading area", the total number of vehicles that are ready to be loaded into that "loading area" (including the number of vehicles at the loading positions) minus the "number of loading positions" is the "number of vehicles waiting to be loaded in the loading area".

[0054] like Figure 2 As shown, after unloading materials from the unloading area or joining the transportation operation, empty vehicles will have loading tasks assigned after the task is assigned. At "Loading Area 1," there is one loading device with two loading positions, and two vehicles are on those positions. There is one vehicle waiting to be loaded behind one of the loading positions. Therefore, the number of vehicles waiting to be loaded at "Loading Area 1" (3) minus the number of loading positions (2) equals 1. Similarly, at "Loading Area 2," there are two loading devices with two loading positions. Only one loading position has a vehicle on it, and there are no vehicles waiting behind that position. Therefore, the number of vehicles waiting to be loaded at "Loading Area 2" (1) minus the number of loading positions (2) equals -1. At this point, vehicles assigned loading tasks at the intersection should proceed to "Loading Area 2" for loading operations because the number of vehicles waiting to be loaded at "Loading Area 2" is less than that at "Loading Area 1."

[0055] In production, vehicle distribution is sometimes uneven. Depending on the production design, it may be necessary to force certain loading areas to speed up or slow down their loading. This necessitates manual intervention in the number of vehicles dispatched to each loading area. This can be achieved by setting a "vehicle allocation weight coefficient" for each loading area, such that "number of vehicles waiting to be loaded in the loading area" = actual number of vehicles waiting to be loaded × "vehicle allocation weight coefficient." By adjusting the "vehicle allocation weight coefficient," manual intervention in the number of vehicles dispatched can be implemented. Figure 2As shown, if I set the "vehicle allocation weight coefficient" for "loading area 1" to 0.5 and the "vehicle allocation weight coefficient" for "loading area 2" to 2, then the "number of vehicles waiting to be loaded in loading area 1" will be 3 × 0.5 = 1.5, while the "number of vehicles waiting to be loaded in loading area 2" will be 1 × 2 = 2. Since the number of vehicles waiting to be loaded in loading area 2 is greater than that in loading area 1, vehicles assigned loading tasks at the intersection should go to loading area 1 for loading operations.

[0056] In addition, a manual scheduling function should be set up so that manual intervention can be carried out at any time during all automatically scheduled tasks, forcing designated vehicles to perform designated tasks. While manually assigning tasks, the "number of vehicles waiting to be loaded in the loading area" corresponding to the original task and the new task should be modified.

[0057] For different scenarios, the following sections will describe several scheduling strategies in detail. The specific strategies are as follows: like Figure 3 As shown: Strategy 1: When an empty vehicle receives a loading task, assign the task to the loading area with the fewest "loaders waiting to be loaded". Upon receiving a loading task from a vehicle, immediately increment the "loader waiting to be loaded" count for that loading area by 1. After completing a loading operation in each loading area, decrement the "loader waiting to be loaded" count for that loading area by 1 as the vehicle leaves the loading position. If a vehicle cancels a loading task en route to a loading area, immediately decrement the "loader waiting to be loaded" count for that loading area by 1. If a loading area is determined to be unsuitable for loading, it should be immediately removed from the resource pool to prevent subsequent vehicles from receiving instructions to load in that area. When multiple loading areas have the same "loader waiting to be loaded", various selection methods can be used. For example, an algorithm such as A can be used to calculate the path length between the vehicle's current location and each target loading area on the system map. Users can set different priorities based on the actual situation, such as "shortest path priority", "longest path priority", or "random assignment". If the vehicle chassis and autonomous driving system are capable enough, the estimated travel time between the vehicle's current location and each target loading interval can be calculated in real time, and the path length can be replaced with the estimated travel time.

[0058] like Figure 3As shown, assuming the "vehicle allocation weight coefficient" for all loading areas is 1, when "empty vehicle 1" receives a loading task and selects a loading area at "intersection 4", the number of vehicles waiting to be loaded in "loading area 1" is 2, in "loading area 2" it is -1, in "loading area 3" it is 0, in "loading area 4" it is 0, in "loading area 5" it is 0, and in "loading area 6" it is 1. At this time, "loading area 2" has the fewest vehicles waiting to be loaded, so "empty vehicle 1" should be assigned to "loading area 2" for loading. When assigning the task to "loading area 2" for "empty vehicle 1", the number of vehicles waiting to be loaded in "loading area 2" should be increased by 1. When "empty vehicle 2" selects a loading area at this time, the number of vehicles waiting to be loaded in loading areas 2, 3, 4, and 5 is all 0. If the system selection strategy is manually configured to "shortest path priority" at this time, then the vehicle is closest to "loading area 2" among loading areas 2, 3, 4, and 5. Therefore, the loading task of the vehicle should be assigned to "loading area 2".

[0059] If a vehicle experiences a malfunction during its journey and is unable to reach its assigned loading area, the "Number of Vehicles Awaiting Loading in the Loading Area" for that loading area should be immediately decremented by 1. If the road ahead is impassable or the target loading area is removed from the resource pool, the vehicle can be reassigned to another "loading area" from its current location following the same logic. In this case, the "Number of Vehicles Awaiting Loading in the Loading Area" for the area whose loading task was terminated should be immediately decremented by 1.

[0060] Strategy Two: When an empty vehicle receives a loading task, it is assigned to the loading area with the fewest pending loading vehicles. While traveling to this loading area, the vehicle re-queries the real-time pending loading vehicle count for each loading area at each intersection, and then re-issues the latest loading task at each intersection. Whenever a vehicle receives a new loading task, the pending loading vehicle count for the corresponding loading area is incremented by 1. Whenever a vehicle cancels a loading task, the pending loading vehicle count for the corresponding loading area is decremented by 1. When multiple loading areas have the same pending loading vehicle count, multiple selection methods can be used. For example, an algorithm like A can be used to calculate the path length between the vehicle's current location and each target loading area on the system map. Users can set different priorities based on the actual situation, such as shortest path priority, longest path priority, or random assignment. If the vehicle chassis and autonomous driving system are capable enough, the estimated travel time between the vehicle's current location and each target loading area can be calculated in real time, and the path length can be replaced with the estimated travel time. In each work cycle, the roads and directions traveled by the vehicle during each trip should be recorded. When replanning the loading area task at each intersection, roads that have already been traveled should be excluded to avoid the situation where the vehicle keeps wandering between two loading areas and cannot work due to replanning.

[0061] like Figure 3 As shown, if the "vehicle allocation weight coefficient" for all loading areas is 1, when "empty vehicle 1" receives a loading task and selects a loading area at "intersection 4", the "number of vehicles waiting to be loaded" in "loading area 2" is the lowest. Therefore, "empty vehicle 1" should be assigned to "loading area 2" for loading, and the "number of vehicles waiting to be loaded" in "loading area 2" will increment by 1. When "empty vehicle 1" reaches "intersection 3", the system should re-query which loading area has the lowest "number of vehicles waiting to be loaded". If the "number of vehicles waiting to be loaded" in each loading area has not changed, then "loading area 2" still has the lowest "number of vehicles waiting to be loaded", so "empty vehicle 1" will still be assigned to "loading area 2" for loading, and the "number of vehicles waiting to be loaded" in "loading area 2" will remain unchanged. If "empty vehicle 2" receives a loading task at this time, and the number of vehicles waiting to be loaded in loading areas 2, 3, 4, and 5 is all 0, assuming that the current system selection strategy is manually configured as "longest path priority", then the vehicle is farthest from "loading area 5" among loading areas 2, 3, 4, and 5. Therefore, the loading task of "empty vehicle 2" should be assigned to "loading area 5".

[0062] like Figure 4 As shown: When "empty vehicle 2" reaches "intersection 2", if at this time the vehicle in "loading area 3" has just finished loading and driven out of the loading position, such as Figure 4As shown. At this time, the number of vehicles waiting to be loaded in "Loading Area 3" is -1, which is the lowest in the entire area. Therefore, when "Empty Vehicle 2" replans its loading task at "Intersection 2", it should select "Loading Area 3" for operation, and at the same time, increase the number of vehicles waiting to be loaded in "Loading Area 3" by 1, and decrease the number of vehicles waiting to be loaded in the original task "Loading Area 5" by 1.

[0063] Strategy 3: Bind the designated loading and unloading areas into a task group. When an empty vehicle receives a loading task, assign the task to the loading area with the fewest pending loading vehicles. However, after completing the loading task, the vehicle can only go to the unloading area within the same task group of that loading area to perform unloading operations. Other scheduling strategies can be combined with Strategy 1 or Strategy 2.

[0064] Loading area strategy: Multiple loading machines may exist in the same loading area. When a vehicle enters the loading area, it will be assigned to the loading machine with available loading positions. When all loading positions are full, the vehicle should wait in the waiting area.

[0065] Offloading area scheduling strategy: The unloading zone strategy is basically the same as the loading zone scheduling strategy. Simply replace "loading zone" with "unloading zone" in the loading zone scheduling strategy.

[0066] General strategy: The general strategy can be used simultaneously in all of the above scheduling strategies.

[0067] General Strategy 1: To avoid an excessive number of vehicles waiting to be loaded in a particular loading area, causing traffic congestion at intersections and subsequently blocking vehicles heading to other areas, a maximum capacity should be set for the number of vehicles waiting to be loaded in a loading area. This maximum capacity is the maximum number of vehicles queuing between the loading positions in the loading area and the intersection. When the number of vehicles waiting to be loaded in a certain loading area exceeds the maximum capacity, vehicles should be dispatched to other loading areas whose maximum capacity is not yet full, even if that loading area has the smallest number of vehicles waiting to be loaded. If the number of vehicles waiting to be loaded in all loading areas exceeds the maximum capacity, then vehicles should be dispatched to the loading area with the smallest number of vehicles waiting to be loaded.

[0068] General Strategy Two: Road load factor can be calculated for each route. "Road load factor" = number of vehicles currently on the road ÷ road length. When a vehicle is heading towards a loading area and multiple roads lead to the same designated loading area, the route with the lower "road load factor" should be selected. Each road should be configurable with priority and road source selection.

[0069] General Strategy 3: Specified vehicles can be manually grouped, and then the grouped vehicles, loading area, and unloading area can be bound together, so that vehicles in the group can only be selected and dispatched in the loading and unloading areas of the same group.

[0070] General Strategy 4: Loading and unloading areas can be grouped together, but vehicles are not bound. When assigning loading tasks, the group with the fewest total vehicles to be loaded is selected for scheduling among multiple groups. When performing unloading tasks, scheduling can only be performed from the list of unloading areas bound to the loading area.

[0071] General Strategy 5: The follow-up task after the mandatory task can be specified. After a vehicle is manually designated to perform a task, the operation can continue according to the follow-up task after the mandatory task is completed.

[0072] General Strategy Six: A cargo bed cleaning task can be set. When the loaded material is highly viscous or frozen, it may stick to the bottom of the cargo bed during unloading and cannot be completely removed. In this case, the cargo bed cleaning function can be manually activated based on loading area, vehicle group, or individual vehicle. When the cargo bed cleaning function is activated, the vehicle will be dispatched to the cargo bed cleaning equipment after unloading. Once the vehicle arrives at the cleaning equipment and stops, the cargo bed will be raised to perform the cleaning work. After the cleaning is completed, the cleaning equipment will issue a task completion signal. Upon receiving the signal, the vehicle will lower the cargo bed and continue to the loading area to perform the next loading cycle. The cargo bed cleaning task can be set with a cleaning frequency. After each unloading task, the current task cycle can be selected to perform a cargo bed cleaning task at the set frequency. If a cargo bed material residue judgment system is available, a material residue threshold for the cargo bed cleaning task can be set. If the material residue exceeds the set threshold after unloading, the cargo bed cleaning task will be automatically executed.

[0073] General Strategy Seven: Loading and unloading areas can be subdivided into multiple sub-zones. When a sub-zone is unsuitable for travel due to road conditions or other factors, it can be manually closed. When assigning and generating travel routes for vehicles in the loading or unloading area, all closed sub-zones should be avoided.

[0074] General Strategy Eight: Priority traffic rules can be set. When multiple vehicles conflict on the same road or at an intersection, they should be dispatched and released according to the following principles: 1. Heavy-duty vehicles take priority over empty vehicles.

[0075] 2. Vehicles going to work sites have priority over vehicles going to temporary parking sites.

[0076] 3. Faster vehicles have priority over slower vehicles.

[0077] 4. Vehicles going uphill have priority over vehicles going downhill.

[0078] 5. Vehicles going straight have priority over vehicles turning.

[0079] General Strategy Nine: When multiple lanes exist in the same direction on the same road, vehicles should be dispatched according to the principle of average allocation by default. However, there should be a capability to manually set the allocation ratio. Dispatchers can manually adjust the vehicle allocation ratio of each road according to the on-site situation, and the priority of the manually set ratio should be higher than the default setting.

[0080] This invention solves the problem of low scheduling efficiency of unmanned vehicles in open-pit mines by using global pooling scheduling, dynamic calculation of the number of vehicles to be loaded, weight adjustment, and a general strategy for multiple scenarios. It can significantly improve production capacity and is applicable to unmanned transportation systems in various types of open-pit mines.

[0081] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A vehicle dispatching method for an unmanned driving system in an open-pit mine, characterized in that, Includes the following steps: S1. The global scheduling layer obtains the real-time operating status of all unmanned dump trucks through the unmanned driving platform. S2. The vehicle pooling scheduling method is adopted to divide multiple loading and unloading areas into independently operating resource pools, and to allocate work tasks to empty vehicles based on the loading area, unloading area and transportation road information in the resource pool. S3. The loading area scheduling layer assigns a target loading area to empty vehicles based on the principle of minimizing the number of vehicles waiting to be loaded in the loading area; the number of vehicles waiting to be loaded in the loading area is the difference between the total number of all vehicles ready to be loaded in the same loading area and the number of loading positions. S4. Dynamically adjust task assignment based on real-time status during vehicle operation.

2. The vehicle dispatching method for an unmanned driving system in an open-pit mine according to claim 1, characterized in that, The number of vehicles to be loaded in the loading area is calculated as follows: The same loading area contains at least one loading device and a corresponding loading position, and the total number of vehicles ready to be loaded includes the vehicles at the loading positions and the vehicles waiting in the loading area; Number of vehicles waiting to be loaded in the loading area = Total number of vehicles ready to be loaded - Number of loading positions.

3. The vehicle dispatching method for an unmanned driving system in an open-pit mine according to claim 1, characterized in that, The loading area scheduling layer also includes a vehicle allocation weight coefficient adjustment mechanism: Each loading zone is assigned a weight coefficient for its vehicles. The adjusted number of vehicles waiting to be loaded in the loading zone = the actual number of vehicles waiting to be loaded × the vehicle weight coefficient. Empty vehicles are given priority to the loading zone with the fewest vehicles waiting to be loaded after the adjustment.

4. The vehicle dispatching method for an unmanned driving system in an open-pit mine according to claim 1, characterized in that, The loading area scheduling layer also includes a dynamic path planning step: When the number of vehicles waiting to be loaded is the same in multiple loading areas, calculate the path length between the current position of the empty vehicle and each target loading area, and select the target loading area according to the preset priority. The preset priority includes shortest path priority, longest path priority, or random assignment. If a vehicle has the ability to calculate travel time in real time, the path length can be replaced with the estimated travel time.

5. The vehicle dispatching method for an unmanned driving system in an open-pit mine according to claim 1, characterized in that, The loading area scheduling layer also includes a dynamic task adjustment mechanism: As an empty vehicle travels toward the target loading area, it re-queries the real-time number of vehicles waiting to be loaded in each loading area at each intersection and reallocates the target loading area based on the latest data. When reassigning tasks, routes that have already been traveled must be excluded to avoid path loops.

6. The vehicle dispatching method for an unmanned driving system in an open-pit mine according to claim 1, characterized in that, It also includes an unloading area scheduling layer, which uses the same scheduling logic as the loading area scheduling layer, replacing the loading area with an unloading area, and assigning a target unloading area to the heavy-load vehicle based on the principle of minimizing the number of vehicles to be unloaded in the unloading area.

7. The vehicle dispatching method for an unmanned driving system in an open-pit mine according to claim 1, characterized in that, It also includes road load factor optimization strategies: When multiple paths lead to the same target loading or unloading area, the path with the lowest road load rate is selected, where the road load rate = the number of vehicles currently traveling on the road ÷ the road length.

8. The vehicle dispatching method for an unmanned driving system in an open-pit mine according to claim 1, characterized in that, It also includes right-of-way priority scheduling strategies: When multiple vehicles collide on the same road or at the same intersection, they should be allowed to pass in the following order: (1) Heavy-duty vehicles have priority over unloaded vehicles; (2) Operating vehicles have priority over temporarily parked vehicles; (3) High-speed vehicles have priority over low-speed vehicles; (4) Vehicles going uphill have priority over vehicles going downhill; (5) Vehicles going straight have priority over vehicles turning.

9. The vehicle dispatching method for an unmanned driving system in an open-pit mine according to claim 1, characterized in that, It also includes the scheduling steps for the truck bed cleaning task: When the loaded material is sticky or at risk of freezing, after the vehicle completes the unloading task, it will automatically go to the truck bed cleaning equipment to perform the cleaning task according to the preset frequency or material residue threshold, and return to the loading area after the cleaning is completed.

10. An unmanned driving system for open-pit mines based on the vehicle scheduling method of any one of claims 1-9, characterized in that, include: The autonomous driving platform monitors vehicle status in real time and dynamically assigns tasks. Multiple driverless dump trucks; Multiple loading and unloading areas; The communication module is used for data interaction between the vehicle and the platform; The task replanning module is used to dynamically adjust task assignments while the vehicle is in motion. Truck bed cleaning equipment is used to perform truck bed cleaning tasks.

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