Multi-moving vehicle control method

Abstract

This case discloses a multi-vehicle control system and method. It calculates a plurality of transport costs for all standby mobile vehicles to reach a target point. From the standby mobile vehicles determined to have a path, it selects a target standby mobile vehicle with the lowest transport cost. It assigns a task to the target standby mobile vehicle with the lowest transport cost and controls the target standby mobile vehicle to travel to the target point.

Description

[Technical Field]

[0001] This invention relates to a multi-vehicle control system and method. [Previous Technology]

[0002] In automated environments requiring mobile vehicles (e.g., but not limited to mobile machinery, Automated Guided Vehicles (AGVs), AMRs, AGFs, etc.) (e.g., but not limited to semiconductor factories, machine processing plants, logistics warehouses, industrial and commercial assembly plants, etc.), current industry demands include improving transport efficiency and avoiding traffic congestion. In these applications, effectively assigning and coordinating the operational tasks of multiple mobile vehicles is crucial to ensuring smooth traffic flow and efficient operation. However, as the number of mobile vehicles in the system increases, the complexity of scheduling and coordination also increases. The key lies in how to rationally allocate transport tasks to each mobile vehicle and coordinate multiple mobile vehicles to reduce conflicts between them, thereby avoiding traffic deadlocks and maximizing overall transport efficiency while meeting the rated transport capacity.

[0003] Generally, multi-vehicle management systems can be divided into centralized management and decentralized management.

[0004] The advantage of centralized management is its simple architecture and ease of deployment; the disadvantage is that information exchange between mobile vehicles must be bridged through the central controller, and the dispatching and path planning of mobile vehicles must first be calculated by the central controller before transmitting task commands and corresponding running paths to the mobile vehicles. Therefore, when the number of mobile vehicles increases, the central controller is prone to system delays due to excessive computation, and may even cause system problems.

[0005] The advantage of distributed management is that it can effectively solve the system latency problem caused by centralized management. Because each mobile vehicle and the central controller are independent entities (Agents), they can exchange information independently. In addition to performing task assignment calculations, the central controller also performs path planning independently after the mobile vehicle receives the assigned tasks from the central controller. This distributed architecture, in which each individual shares the system workload, can greatly reduce the computational load on the central controller. However, the disadvantage of this architecture is that it is relatively complex and has higher construction and maintenance costs.

[0006] Moreover, in terms of current mobile vehicle control, there are roughly the following shortcomings that need to be overcome.

[0007] Disadvantage of the prior art: After the optimal path is planned for the mobile vehicle, the mobile vehicle will occupy the running path. If the subsequent mobile vehicle plans the same path or repeats the path, the subsequent mobile vehicle needs to wait for the preceding mobile vehicle to leave before it can occupy the path, which causes the subsequent mobile vehicle to wait for a long time.

[0008] Second drawback of conventional technology: It does not consider the possibility of multiple moving vehicles meeting during the path planning process, so it only plans the shortest distance path, which is more likely to cause time-consuming waiting situations.

[0009] The third drawback of the conventional technology is that when assigning tasks, the task is directly assigned to the mobile vehicle closest to the target point. If the transportation cost is not considered, it is easy to cause conflicts between multiple mobile vehicles, resulting in a decrease in transportation efficiency.

[0010] The fourth drawback of the conventional technology is that when dealing with multiple opposing tasks, if the system only plans the shortest distance path, it is easy to cause traffic congestion or even system deadlock.

[0011] Therefore, the industry currently needs a multi-vehicle control system and method to improve the above-mentioned shortcomings, enhance transportation efficiency and avoid traffic congestion. [Summary of the Invention]

[0012] The present invention relates to a multi-vehicle control system and method. Through path planning for multi-vehicle timing optimization, the traffic operation sequence can be optimized to improve the disadvantage of the prior art (if the subsequent vehicle plans the same or repeated path, the subsequent vehicle needs to wait for the preceding vehicle to leave before it can occupy the path, causing the subsequent vehicle to wait for a long time).

[0013] This invention relates to a multi-vehicle control system and method, which proposes a multi-vehicle traffic management path planning algorithm with the lowest transportation cost to obtain the optimal path with the lowest transportation cost, thereby improving the second drawback of the prior art (in the process of path planning, the possibility of multiple vehicles meeting is not considered, so only the shortest distance path is planned, which is more likely to cause time-consuming waiting situations).

[0014] This invention relates to a multi-mobile vehicle control system and method, and proposes a multi-mobile vehicle optimal dispatch algorithm, which can assign tasks to the mobile vehicle with the lowest transportation cost. The transportation cost includes the comprehensive cost of the running path distance, the number of times the multiple mobile vehicles meet during the operation, and the time spent on conflict resolution, etc., in order to improve the third drawback of the prior art (assigning tasks to the mobile vehicle closest to the target point, if the transportation cost is not considered, is prone to multi-mobile vehicle conflicts, resulting in a decrease in transportation efficiency).

[0015] This invention relates to a multi-vehicle control system and method, which combines optimal multi-vehicle dispatch, multi-vehicle timing scheduling optimization and traffic management path planning with the lowest transportation cost, and multi-vehicle traffic management path operation, to optimize system transportation cost (reduce traffic complexity) and avoid traffic congestion, thereby improving the fourth drawback of the prior art (planning only the shortest distance path, which can easily cause traffic congestion or even system deadlock when handling multiple opposing tasks).

[0016] According to a first aspect of the present invention, a multi-vehicle control method is provided, comprising: calculating a plurality of transport costs for all standby mobile vehicles to reach a target point; selecting a target standby mobile vehicle with the minimum transport cost from the standby mobile vehicles that are determined to have a path; and assigning a task to the target standby mobile vehicle with the minimum transport cost, and controlling the target standby mobile vehicle to run to the target point.

[0017] According to a second aspect of the present invention, a multi-vehicle control method is provided, comprising: updating the actual departure time of a mobile vehicle from one of the current path units, and compensating the time difference between the actual departure time and a planned departure time in an unrun planned path timing of the mobile vehicle in a path server; determining whether the unrun planned path timing of the mobile vehicle conflicts with at least one other mobile vehicle in a multi-vehicle conflict or a path unit occupancy conflict; re-planning the path for the path unit in which the multi-vehicle conflict or the path unit occupancy conflict occurs; and controlling the mobile vehicle to run to a target node according to a planned path.

[0018] According to a third aspect of the present invention, a multi-vehicle control system is provided, comprising: a path server; a control unit communicating with the path server; and a plurality of mobile vehicles communicating with the path server and the control unit. The path server stores a plurality of entry and exit times for each of the mobile vehicles in each path unit. The control unit performs the following actions: calculating a plurality of transport costs for all standby mobile vehicles to reach a target point; selecting a target standby mobile vehicle with the minimum transport cost from the standby mobile vehicles that are determined to have a path; assigning a task to the target standby mobile vehicle with the minimum transport cost; and controlling the target standby mobile vehicle to run to the target point.

[0019] In order to better understand the above and other aspects of the present invention, specific embodiments are described below in conjunction with the accompanying drawings:

Implementation Method

[0021] The technical terms used in this specification are based on common terminology in the field. Where this specification provides explanations or definitions for certain terms, the interpretation of those terms shall be based on the explanations or definitions provided in this specification. Each embodiment disclosed herein has one or more technical features. Where feasible, those skilled in the art may selectively implement some or all of the technical features in any embodiment, or selectively combine some or all of the technical features in these embodiments.

[0022] Figure 1 shows a schematic diagram of a multi-vehicle control method according to an embodiment of the present invention. The multi-vehicle control method includes the following steps: optimal multi-vehicle dispatch 110, multi-vehicle timing scheduling optimization and traffic control route planning with minimum transportation cost 120, and multi-vehicle traffic control route operation 130. Therefore, the multi-vehicle control method of the present invention can optimize system transportation cost (reduce traffic complexity) and avoid traffic congestion. Details of the optimal multi-vehicle dispatch step 110, the multi-vehicle timing scheduling optimization and traffic control route planning with minimum transportation cost 120, and the multi-vehicle traffic control route operation 130 will be described below.

[0023] Figures 2A to 2C respectively show functional block diagrams of a multi-vehicle control system according to different embodiments of the present invention. The multi-vehicle control system 200A includes: a path server 210A, a control unit 220A, and a plurality of mobile vehicles 230A. The path server 210A, the control unit 220A, and the mobile vehicles 230A communicate with each other.

[0024] Similarly, as shown in Figure 2B, the multi-vehicle control system 200B includes a path server 210B and a plurality of mobile vehicles 230B. The path server 210B includes a control unit 220B. The path server 210B, the control unit 220B, and the mobile vehicles 230B communicate with each other.

[0025] Similarly, as shown in Figure 2C, the multi-vehicle control system 200C includes a path server 210C and a plurality of mobile vehicles 230C. The path server 210C has the function of a control unit. The path server 210C and the mobile vehicles 230C communicate with each other.

[0026] Path servers 210A, 210B, and 210C are, for example, but not limited to, cloud servers with databases. Path servers 210A, 210B, and 210C store the entry and exit times (i.e., entry and exit times) of each mobile vehicle 230A, 230B, and 230C at each path unit and starting node (or destination node). Path units include road segments and nodes.

[0027] Control units 220A and 220B can be implemented, for example, by using a chip, a circuit block within the chip, a firmware circuit, or a circuit board containing several electronic components and wires. Alternatively, control units 220A and 220B can be implemented by related software or programs executable in a computer system or server. All of this is within the spirit of this case.

[0028] That is, in one embodiment of this case, the control unit may be independent of the path server, or the control unit may be integrated into the path server, both of which are within the spirit of this case.

[0029] Mobile vehicles 230A, 230B, and 230C are, for example but not limited to, mobile machines, automated guided vehicles (AGVs), etc. Mobile vehicles 230A, 230B, and 230C are hardware devices. In other embodiments, mobile vehicles 230A, 230B, and 230C can learn the running paths and timings of other mobile vehicles from path servers 210A, 210B, and 210C.

[0030] In one embodiment of this invention, route servers 210A to 210C (and control unit 220A or control unit 220B) perform any of the following or any combination thereof in one embodiment of this invention: (1) traffic control route planning with multi-vehicle timing scheduling optimization, (2) traffic control route planning with minimum transportation cost, (3) optimal multi-vehicle dispatch, and (4) multi-vehicle traffic control route operation.

[0031] In another embodiment of the present invention, route servers 210A to 210C (and control unit 220A or control unit 220B) perform (3) optimal multi-vehicle dispatching of an embodiment of the present invention; and mobile vehicle 230A or 230B or 230C performs any of the following or any combination thereof of an embodiment of the present invention: (1) traffic control route planning with multi-vehicle timing scheduling optimization, (2) traffic control route planning with minimum transportation cost, and (4) multi-vehicle traffic control route operation.

[0032] In this embodiment, when implementing the above-mentioned features, a field map is constructed. The field map includes a plurality of nodes and a plurality of road segments (edges), and the connection points between road segments are nodes. Below, a path includes at least one path unit and at least one node (which may be a starting node or a target node). A path unit includes one road segment and one node.

[0033] Figure 3 shows a site map according to an embodiment of the present invention. In Figure 3, the site map includes nodes n1 to n8 and road segments e1 to e10. For example, road segment e1 connects nodes n1 and n3, and so on.

[0034] The following will explain how the present invention performs (1) traffic control route planning with optimized timing of multiple mobile vehicles, (2) traffic control route planning with the lowest transportation cost, (3) optimal allocation of multiple mobile vehicles, and (4) operation of traffic control routes for multiple mobile vehicles.

[0035] (1) Traffic control route planning based on multi-vehicle timing scheduling optimization

[0036] Figures 4A to 4G show traffic control route planning for multi-vehicle timing scheduling optimization according to an embodiment of this case.

[0037] Figures 4A and 4B show the entry time (s_time) and exit time (e_time) of the path unit planning sequence according to an embodiment of this case. In Figure 4A, the path unit includes path e1 and node n2. In Figure 4B, the path unit includes node n2 and path e1. Alternatively, taking Figure 3 as an example, assume that the starting node of the planned path is n1 and the target node is n8. In Figure 4A, the planned path includes: (starting) node n1 and three path units, wherein the first path unit includes road segment e1 and node n3, the second path unit includes road segment e4 and node n5, and the third path unit includes road segment e8 and node n8. In Figure 4B, the planned path includes: three path units and (target) node n8, wherein the first path unit includes node n1 and road segment e1, the second path unit includes node n3 and road segment e4, and the third path unit includes node n5 and road segment e8.

[0038] In Figures 4A and 4B, the time point when the mobile vehicle MRc enters the path unit is taken as the path unit planning timing entry time point (s_time), and the time point when the mobile vehicle MRc leaves the path unit is taken as the path unit planning timing departure time point (e_time).

[0039] Figures 4C and 4D show the determination of timing overlap of multiple mobile vehicles (i.e., determination of conflict of multiple mobile vehicles) according to an embodiment of the present case.

[0040] In Figures 4C and 4D, sc represents the entry time of the mobile vehicle MRc into this path unit, ec represents the departure time of the mobile vehicle MRc from this path unit, si represents the entry time of other mobile vehicles MRi into this path unit, and ei represents the departure time of other mobile vehicles MRi from this path unit. If the mobile vehicle is present in the path unit, other mobile vehicles cannot enter. Conversely, if other mobile vehicles are present in the path unit, the mobile vehicle cannot enter. In Figure 4C, mobile vehicles MRj and MRc are in opposing directions, while mobile vehicles MRk and MRc are in the same direction. Below, mobile vehicle MRi encompasses mobile vehicles MRj and MRk.

[0041] In one embodiment of this case, when (sc≦ei) and (si≦ec), it indicates that multiple mobile vehicles are clashing in the same path unit, that is, a multi-vehicle conflict is established. That is, when "the entry time sc of this mobile vehicle MRc entering this path unit is less than or equal to the departure time ei of other mobile vehicles MRi leaving this path unit" and "the entry time si of other mobile vehicles MRi entering this path unit is less than or equal to the departure time ec of this mobile vehicle MRc leaving this path unit", it is determined that a multi-vehicle path unit conflict is established.

[0042] Figure 4C shows conflict scenarios 410-450'. Taking conflict scenario 410 as an example, in the original plan, when other mobile vehicles MRi have not yet left the path unit, this mobile vehicle MRc intends to enter the path unit, thus resulting in a multi-vehicle path unit conflict. Taking conflict scenario 420 as an example, in the original plan, when this mobile vehicle MRc has not yet left the path unit, other mobile vehicles MRi intend to enter the path unit, thus resulting in a multi-vehicle path unit conflict. Taking conflict scenario 430 as an example, the entry and exit times of this mobile vehicle MRc and other mobile vehicles MRi are exactly the same (si=sc and ei and ec), thus resulting in a multi-vehicle path unit conflict. The rest can be deduced similarly. That is, in conflict scenarios 430-450', it is possible that the mobile vehicle MRc and other mobile vehicles MRi enter the path unit at exactly the same time, or it is possible that the mobile vehicle MRc and other mobile vehicles MRi leave the path unit at exactly the same time. All of this is within the spirit of this case.

[0043] Figure 4D shows conflict scenarios 430-470. The mobile vehicle MRc moves from node n6 to node n8, while other mobile vehicles MRi move from node n6 to node n9. Taking conflict scenarios 430, 440, and 440' as examples, in the original plan, the entry time of the mobile vehicle MRc and other mobile vehicles MRi to node n6 is exactly the same (si=sc), thus resulting in a multi-vehicle path element conflict. Taking conflict scenarios 450 and 450' as examples, in the original plan, the departure time of the mobile vehicle MRc and other mobile vehicles MRi to node n6 is exactly the same (ei=ec), thus resulting in a multi-vehicle path element conflict. Taking conflict scenario 460 as an example, in the original plan, the entry time of the mobile vehicle MRc to node n6 is the same as the departure time of other mobile vehicles MRi to node n6 (sc=ei), thus resulting in a multi-vehicle path element conflict. Taking conflict scenario 470 as an example, in the original plan, the departure time of this mobile vehicle MRc from node n6 is the same as the entry time of other mobile vehicles MRi to node n6 (ec=si), thus causing a conflict of multiple mobile vehicle path units.

[0044] Therefore, in one embodiment of this case, when multiple mobile vehicles conflict in the same path unit, the timing of the overlapping of multiple mobile vehicles will be adjusted to eliminate the conflict of multiple mobile vehicle path units. When the timing of the overlapping of multiple mobile vehicles is to be adjusted, the timing of all relevant mobile vehicles that have reserved the path will be sorted.

[0045] Figure 4E illustrates how to adjust the timing of overlapping multiple mobile vehicles to eliminate path unit conflicts. In Figure 4E, the time point sc when the mobile vehicle MRc enters the path unit is adjusted by an adjustment time AT1 to become sc' (the adjustment method can be deceleration or allowing the mobile vehicle to stay in the previous path unit) to eliminate path unit conflicts. When [(si-e1)≧(ec-sc+TT)] is true, the entry time of the mobile vehicle MRc is adjusted by an adjustment time AT1 before entering the path unit to eliminate path unit conflicts. The adjustment time AT1 of the mobile vehicle MRc is set as AT1=sc'-sc=abs(e1-sc)+TT. Where, abs(e1-sc) represents the absolute value of (e1-sc), and TT represents the tolerance time.

[0046] Figure 4F shows how to adjust the timing of multiple overlapping mobile vehicles to eliminate conflicts in multiple mobile vehicle path units. In Figure 4F, the time point sc when the mobile vehicle MRc enters the path unit is adjusted by an adjustment time AT2 to become sc' (the adjustment method can be deceleration or allowing the mobile vehicle to stay in the previous path unit) to eliminate conflicts in multiple mobile vehicle path units. When [(si-e(i-1)<(ec-sc+TT)] is true, the entry time of the mobile vehicle MRc is adjusted by an adjustment time AT2 before entering the path unit to eliminate conflicts in multiple mobile vehicle path units. The adjustment time AT2 of the mobile vehicle MRc is set as AT2=sc'-sc=abs(ei-sc)+TT.

[0047] Figure 4G shows how to adjust the timing of multiple overlapping mobile vehicles to eliminate conflicts in multiple mobile vehicle path units. In Figure 4G, the time point sc when the mobile vehicle MRc enters the path unit is adjusted by an adjustment time AT3 to become sc' (the adjustment method can be acceleration) to eliminate conflicts in multiple mobile vehicle path units. When [(s1-ei)>(ec-sc+TT)] is true, the entry time of the mobile vehicle MRc is adjusted by an adjustment time AT3 before entering the path unit to eliminate conflicts in multiple mobile vehicle path units. The adjustment time AT3 of the mobile vehicle MRc is set as AT3=sc-sc'=abs(ei-sc)+TT.

[0048] That is to say, in one embodiment of this case, when the mobile vehicle has a path unit conflict with other mobile vehicles, the planning sequence (entry time point) of the mobile vehicle is adjusted to resolve the path unit conflict.

[0049] In one embodiment of this case, traffic management route planning through multi-vehicle timing scheduling optimization helps to solve the first drawback of the prior art (time-consuming waiting of subsequent vehicles) and the fourth drawback of the prior art (traffic congestion or even system deadlock).

[0050] In one embodiment of this invention, the multi-vehicle conflict determination and multi-vehicle timing adjustment in Figures 4A to 4G can be performed by the control unit 220A or the control unit 220B of the path server 210B. In another embodiment of this invention, the multi-vehicle conflict determination and multi-vehicle timing adjustment in Figures 4A to 4G can be performed by the mobile vehicles 230A, 230B, or 230C.

[0051] (2) Traffic management route planning with the lowest transportation cost

[0052] Figures 5A to 5E show schematic diagrams of traffic control route planning with minimum transportation cost according to an embodiment of this case, wherein AC represents a node. Transportation cost includes: the total cost of the route distance, the number of times multiple mobile vehicles meet during the operation, and the time spent on conflict resolution.

[0053] Figure 5A shows that the mobile vehicle MR1 has a forward collision with another mobile vehicle MR2. The path cell that the mobile vehicle MR1 wants to take is in the same direction as the path cell that the other mobile vehicle MR2 wants to take. When a forward collision occurs, the mobile vehicle MR1 will wait for the other mobile vehicle MR2 to leave the path cell before entering the path cell.

[0054] When a forward conflict occurs, the adjustment time of the mobile vehicle MR1 is AT4=s1'-s1=abs(e2-s1)+TT, and the transportation cost of the mobile vehicle MR1 is AT4*V+D, where V represents the speed of the mobile vehicle MR1 and D represents the distance between the two nodes.

[0055] Figure 5B shows that the mobile vehicle MR1 and other mobile vehicles MR2 have a fork conflict. The path unit to be taken by the mobile vehicle MR1 and the path unit to be taken by other mobile vehicles MR2 will reach the same node C. When a fork conflict occurs, the mobile vehicle MR1 will wait for the other mobile vehicle MR2 to leave the path unit before it can proceed with the path unit.

[0056] When a fork conflict occurs, the adjustment time of the mobile vehicle MR1 is AT5=s1'-s1=abs(e2-s1)+TT, and the transportation cost of the mobile vehicle MR1 is AT5*V+D.

[0057] Figure 5C shows a head-on conflict between the mobile vehicle MR1 and another mobile vehicle MR2, wherein the path unit to be taken by the mobile vehicle MR1 is in the opposite direction to the path unit to be taken by the other mobile vehicle MR2. When a head-on conflict occurs, the adjustment time of the mobile vehicle MR1 is such that the transportation cost of the mobile vehicle MR1 running the path unit is relatively greater than the transportation cost of the mobile vehicle MR1 running the adjacent path unit (thus avoiding the mobile vehicle MR1 running the conflicting route), or the adjustment time of the mobile vehicle MR1 is made infinitely long. When a head-on conflict occurs, an alternative route is selected for the mobile vehicle MR1.

[0058] Figure 5D shows no conflict. When there is no conflict, the transport cost of this mobile vehicle MR1 is D.

[0059] Figure 5E shows the transportation cost of an embodiment of this case and the transportation cost of the prior art. Node n1 represents the starting node and node n8 represents the target node. In this case, the speed v of the mobile vehicle MRc is 3. Since other mobile vehicles MR1 ​​appear on the road segment from node n3 to node n5, the settling time (AT) of the mobile vehicle MRc is 5 and the speed v is 3.

[0060] In one embodiment of this case, the path P1 obtained through traffic control route planning with the lowest transportation cost is from node n1, through nodes n2 and n5 to reach node n8. The transportation cost of path P1 in this embodiment is 11+13+6=30, and there are no multiple vehicles meeting on path P1.

[0061] Conversely, in the conventional technique, the path P2 is obtained by using the shortest distance for path planning, which is from node n1, through nodes n3 and n5 to reach node n8. The transportation cost of path P2 in the conventional technique is 10 + 8 + 3*5 + 6 = 39.

[0062] By comparing the transportation costs of paths P1 and P2, it can be seen that the traffic management route planning in this embodiment can achieve the lowest transportation cost. This helps to solve the second drawback of the prior art (time-consuming waiting of the moving vehicle) and the fourth drawback of the prior art (traffic congestion or even system deadlock).

[0063] In one embodiment of this invention, the lowest transportation cost traffic control route planning for Figures 5A to 5E can be performed by the control unit 220A or the control unit 220B of the route server 210B. In another embodiment of this invention, the lowest transportation cost traffic control route planning for Figures 5A to 5E can be performed by the mobile vehicle 230A, 230B, or 230C.

[0064] Figures 6A to 6C show flowcharts of a traffic management route planning method according to an embodiment of this case. In step 602, the starting point data is placed into the path diffusion set table (OPEN list) of this mobile vehicle. In step 604, the node with the minimum objective function (cost function) is selected from the path diffusion set table of this mobile vehicle, and the node with the minimum objective function is moved from the path diffusion set table to the path convergence set table (CLOSED list) of this mobile vehicle, and at the same time, this node (the node with the minimum objective function) is defined as the current node.

[0065] In step 606, determine whether the current node is the endpoint. If yes, proceed to step 608; otherwise, proceed to step 610.

[0066] In step 608, the set of endpoints connected to parent nodes is retrieved from the path convergence set table of this mobile vehicle (also referred to as the "path convergence set table") to obtain the timing plan of the optimal path nodes for multiple mobile vehicles. The path cost is obtained by summing all objective functions on the optimal path, and the relevant data is updated in the path server. Step 608 belongs to the traffic control path planning of multi-mobile vehicle timing scheduling optimization. Below, "path convergence set table" and "path diffusion set table" have the same meaning; and "path diffusion set table" and "path diffusion set table" have the same meaning.

[0067] In step 610, determine whether the path diffusion set table has no nodes. If step 610 is yes, the process proceeds to step 612. If step 610 is no, the process proceeds to step 614.

[0068] In step 612, it is determined that the mobile vehicle has no path.

[0069] In step 614, all adjacent nodes of the current node of this mobile vehicle are identified, and the timing data of other mobile vehicles on the current node and adjacent node set are obtained from the path server. Step 614 can be executed by the path server and the control unit.

[0070] In step 616, as described in the traffic management route planning for minimum transportation cost of multiple mobile vehicles, it is determined whether a set of path units from the current node to the adjacent node of this mobile vehicle will cause timing conflicts or path unit occupancy conflicts with other mobile vehicles. If step 616 is yes, the process proceeds to step 618. If step 616 is no, the process proceeds to step 620. Step 616 belongs to the traffic management route planning for minimum transportation cost of multiple mobile vehicles. A set of path units refers to a set formed by multiple path units.

[0071] In step 618, as described in the traffic control route planning for multi-vehicle timing optimization, it is determined whether there is a conflict between opposing vehicles. Step 618 pertains to traffic control route planning for multi-vehicle timing optimization. If step 618 is yes, the process proceeds to step 622. If step 618 is no, the process proceeds to step 624.

[0072] In step 620, as described in the traffic route planning for minimum transportation cost of multiple mobile vehicles, all objective functions of the set of path units from the current node to adjacent nodes of this mobile vehicle are calculated. Step 620 belongs to the traffic route planning for minimum transportation cost of multiple mobile vehicles.

[0073] In step 622, the cost (adjustment time) of the conflicting path is adjusted so that the transportation cost of this mobile vehicle running the conflicting path unit is relatively greater than the transportation cost of this mobile vehicle running the adjacent path unit, or the adjustment time of this mobile vehicle is made infinitely large to avoid planning the path to that road segment. Step 622 belongs to traffic management path planning in multi-mobile vehicle time-series scheduling optimization.

[0074] In step 624, as described in the traffic route planning for minimum transportation cost of multiple mobile vehicles, the objective function for adjusting the conflicting road segment based on the adjustment time of this mobile vehicle is calculated. Step 624 pertains to the traffic route planning for minimum transportation cost of multiple mobile vehicles.

[0075] In step 626, determine whether the set of adjacent nodes already exists in the path diffusion set table. If step 626 is yes, the process proceeds to step 628. If step 626 is no, the process proceeds to step 632.

[0076] In step 628, it is determined whether the new objective function value of the adjacent node set is smaller than the old objective function value. If step 628 is yes, the process proceeds to step 630. If step 628 is no, the process proceeds to step 604.

[0077] In step 630, the data of adjacent nodes is updated and the data of adjacent nodes is moved back to the path diffusion set table of this mobile vehicle.

[0078] In step 632, determine whether the set of adjacent nodes already exists in the path convergence set table. If step 632 is yes, the process proceeds to step 634. If step 632 is no, the process proceeds to step 636.

[0079] In step 634, it is determined whether the new objective function value of the adjacent node set is smaller than the old objective function value. If step 634 is yes, the process proceeds to step 638. If step 634 is no, the process proceeds to step 604.

[0080] In step 636, it is determined that the adjacent node is not in the path diffusion set table and the path convergence set table of this mobile vehicle, and the adjacent node is added to the path diffusion set table.

[0081] In step 638, update the adjacent node data of the path diffusion set table of this mobile vehicle.

[0082] (3) Optimal dispatch of multiple mobile vehicles

[0083] Figure 7 shows a flowchart of a multi-vehicle optimal dispatch method according to an embodiment of the present invention. The multi-vehicle optimal dispatch method in Figure 7 is executed by control unit 220A or 220B or path server 210C.

[0084] In step 705, the task is received and placed in the task queue.

[0085] In step 710, check if there are any tasks in the task queue. If there are no tasks in the task queue, the process returns to step 705. If there are tasks in the task queue, the process proceeds to step 715.

[0086] In step 715, the first task is taken from the task queue.

[0087] In step 720, check if there are any standby mobile vehicles. If so, the process proceeds to step 725.

[0088] In step 725, traffic control route planning with the lowest transportation cost is performed to calculate the respective transportation costs of all standby mobile vehicles to the target point (i.e., the mission start point). Step 725 is Figures 6A to 6C of this case.

[0089] In step 730, determine whether all standby mobile vehicles have no path. If step 730 is yes, the process proceeds to step 735. If step 730 is no, the process proceeds to step 740.

[0090] In step 735, wait, and then execute step 725 again.

[0091] In step 740, the mobile vehicle with the lowest transportation cost is selected from the standby mobile vehicles with a path.

[0092] In step 745, the task is assigned to the mobile vehicle with the lowest transportation cost.

[0093] Figure 8 shows an example of optimal multi-vehicle dispatch according to an embodiment of the present invention. In Figure 8, mobile vehicles MR1 ​​and MR5 are performing tasks, while mobile vehicles MR2 to MR4 are in standby. In Figure 8, the target point refers to the task starting point from which the task is to be dispatched. After performing optimal multi-vehicle dispatch according to an embodiment of the present invention, mobile vehicle MR3 is selected. Conversely, in the prior art, mobile vehicle MR2, which is closest to the target point, is selected, but such a selection incurs high transportation costs, possibly due to path conflicts with other mobile vehicles. However, the transportation cost calculation of the embodiment of the present invention shows that the transportation cost of mobile vehicle MR3 is lower than that of mobile vehicle MR2. Therefore, mobile vehicle MR3 is a better choice. In the embodiment of the present invention, after selecting mobile vehicle MR3, the above-mentioned multi-vehicle timing scheduling optimization, lowest transportation cost traffic control path planning, and traffic control path operation method are used to move mobile vehicle MR3 to the target point.

[0094] The optimal dispatch method for multiple mobile vehicles in this embodiment can solve the third drawback of the prior art (if transportation costs are not considered, multiple mobile vehicles are prone to conflict, resulting in reduced transportation efficiency).

[0095] (4) Multi-vehicle traffic control route operation

[0096] Figures 9A and 9B show schematic diagrams of traffic control routes for multiple mobile vehicles according to an embodiment of this case.

[0097] Figure 9A shows a schematic diagram of a mobile vehicle MR1 starting to leave the current path unit (including road segment e0 and node n1). When the mobile vehicle starts to leave the current path unit, the following steps are performed.

[0098] Step 1: Update the actual departure time of the mobile vehicle leaving the current path unit, and compensate the difference between the actual departure time and the planned departure time for the planned path timing.

[0099] Step 2: If a conflict occurs in the current path unit of the compensation timing, then replan the current path unit in the conflict.

[0100] Step 3: Occupy the next path unit T (including road segment e1 and node n2).

[0101] Step 4: Release the current path unit (including road segment e0 and node n1), and update the data of the occupied next path unit T (road segment (e1) data and node (n2) data) and the data of the released current path unit (road segment (e0) data and node (n1)) in the path server.

[0102] Figure 9B shows a schematic diagram of the mobile vehicle MR1 entering the current path unit. When the mobile vehicle enters the current path unit, the following steps are performed.

[0103] Step 1: Release the previous path unit (segment e0 and node n0).

[0104] Step 2: Update the actual entry time of the mobile vehicle into the current path unit, and compensate the difference between the actual entry time and the planned entry time into the planned path timing.

[0105] Step 3. If a conflict occurs in the current path unit of the compensation timing, then replan the current path unit in the conflict.

[0106] Step 4. Occupy the current path unit T (including road segment e1 and node n1), and update the path server with the data of the released previous path unit (road segment (e0) data, node (n0) data) and the data of the occupied current path unit (road segment (e1) data and node (n1) data).

[0107] In addition, in other possible embodiments of this case, the entry and exit path units of Figure 8A and Figure 8B can be combined in combination, which is also within the spirit of this case.

[0108] Figures 10A and 10B show flowcharts of a multi-vehicle traffic control path operation method according to an embodiment of the present invention.

[0109] In step 1005, the current path unit is set as the current path unit and the path unit is occupied.

[0110] In step 1010, determine whether the mobile vehicle is ready to start. If step 1010 is yes, the process proceeds to step 1015. If step 1010 is no, the process returns to step 1005.

[0111] In step 1015, the actual departure time of the mobile vehicle from the current path unit is updated, and the time difference between the actual departure time and the planned departure time is compensated in the unrunned planned path timing of the mobile vehicle in the path server. For details of step 1015, please refer to Figures 9A and 9B.

[0112] In step 1020, it is determined whether the timing of the unplanned path of this mobile vehicle will conflict with the timing of path units or the occupation of path units with other mobile vehicles. If step 1020 is yes, the process proceeds to step 1025. If step 1020 is no, the process proceeds to step 1045.

[0113] In step 1025, path planning is re-performed for path units that have path unit timing conflicts or path unit occupancy conflicts.

[0114] In step 1045, determine whether the conflict occurs in the planned next path unit. If step 1045 is yes, the process proceeds to steps 1046 and 1047. If step 1045 is no, the process returns to step 1030.

[0115] In step 1046, the adjustment time of the conflicting path unit is set such that the transportation cost of the mobile vehicle running the conflicting path unit is relatively greater than the transportation cost of the mobile vehicle running the adjacent path unit, or the adjustment time of the mobile vehicle is set to indefinite. In step 1047, the mobile vehicle is stopped.

[0116] In step 1030, for the planned path, the adjacent path units occupying the current path unit.

[0117] In step 1035, the previously occupied path unit is released, and the occupied path unit data, released path unit data, and the adjusted planned path timing are updated on the path server.

[0118] After step 1035, the process proceeds to step 1050 to allow the mobile vehicle to operate.

[0119] In step 1055, it is determined whether the mobile vehicle has reached the target node. If step 1055 is yes, the process ends. If step 1055 is no, the process proceeds to step 1060.

[0120] In step 1060, it is determined whether the mobile vehicle has reached the adjacent node. If step 1060 is yes, the process returns to step 1005. If step 1060 is no, the process returns to step 1055.

[0121] In one embodiment of this case, the operation of multi-vehicle traffic management routes helps to solve the following disadvantages of the prior art (time-consuming waiting of subsequent vehicles), the following disadvantages of the prior art (time-consuming waiting of subsequent vehicles), the following disadvantages of the prior art (if transportation costs are not considered, it is easy to cause conflicts among multiple vehicles, resulting in reduced transportation efficiency) and the following disadvantages of the prior art (traffic congestion or even system deadlock).

[0122] In one embodiment of this invention, the multi-vehicle traffic control path operation of Figures 9A, 9B, 10A, and 10B can be executed by the control unit 220B or the path server 210C of the control unit 220A or the path server 210B. In another embodiment of this invention, the multi-vehicle traffic control path operation of Figures 9A, 9B, 10A, and 10B can be executed by the mobile vehicles 230A, 230B, or 230C.

[0123] An embodiment of the present invention provides a multi-vehicle control system that combines multi-vehicle optimal dispatch, multi-vehicle timing scheduling optimization and traffic management path planning with the lowest transportation cost, and a multi-vehicle traffic management path operation control method to solve known problems such as multi-vehicle system operation path unit occupancy, meeting waiting waste and multi-vehicle meeting deadlock, so as to achieve the effects of avoiding traffic congestion and improving transportation efficiency.

[0124] While this application may describe many specific details, these should not be construed as limiting the scope of the claimed invention, but rather as a description of the characteristics of a particular embodiment. In this description, certain features described in the context of a single embodiment may also be implemented in combination in that single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments. Furthermore, while features may initially be described as functioning in certain combinations, or even initially described as such combinations, in some cases one or more features may be removed from that combination, and the illustrated combination may be for a sub-combination or a variation of the sub-combination. Similarly, while operations are depicted in the illustrations as being performed in a specific order, this should not be construed as requiring these operations to be performed in the specific order or sequence shown, or that all depicted operations must be performed to achieve the desired result.

[0125] Although the above embodiments of this case only disclose some examples and implementation methods, the examples, implementation methods and other implementation methods can be changed, modified and enhanced based on the disclosed content.

[0126] In summary, although the present invention has been disclosed above by way of embodiments, it is not intended to limit the present invention. Those skilled in the art to which this invention pertains can make various modifications and refinements without departing from the spirit and scope of the present invention. Therefore, the scope of protection of this invention shall be determined by the appended claims. [Simplified Explanation of the Diagram]

[0020] Figure 1 shows a schematic diagram of a multi-vehicle control method according to an embodiment of the present invention. Figures 2A to 2C show functional block diagrams of a multi-vehicle control system according to different embodiments of the present invention. Figure 3 shows a field map according to an embodiment of the present invention. Figures 4A to 4G show traffic control route planning for multi-vehicle timing scheduling optimization according to an embodiment of the present invention. Figures 5A to 5E show schematic diagrams of traffic control route planning for minimum transportation cost according to an embodiment of the present invention. Figures 6A to 6C show flowcharts of a traffic control route planning method according to an embodiment of the present invention. Figure 7 shows a flowchart of a multi-vehicle optimal dispatch method according to an embodiment of the present invention. Figure 8 shows an example of optimal dispatch of multi-vehicles according to an embodiment of the present invention. Figures 9A and 9B show schematic diagrams of multi-vehicle traffic control route operation according to an embodiment of the present invention. Figures 10A and 10B show flowcharts of a multi-vehicle traffic control route operation method according to an embodiment of the present invention.

Claims

1. A method for controlling multiple mobile vehicles, comprising: Update the actual departure time of a mobile vehicle from one of the current path units, and compensate the mobile vehicle's unrun planned path timing in a path server with a time difference between the actual departure time and a planned departure time; and control the mobile vehicle to run to a target node according to a planned path.

2. The multi-vehicle control method as described in claim 1 further includes: Determine whether the timing of the unplanned path of the mobile vehicle conflicts with at least one other mobile vehicle or a path unit occupancy conflict; and replan the path for the path unit where the conflict occurs.

3. The multi-vehicle control method as described in claim 2, wherein, The path unit occupancy conflict includes a forward conflict, a fork conflict, or a pair of forward conflicts.

4. The multi-vehicle control method as described in claim 2, wherein, When the mobile vehicle starts to leave the current path unit, update the actual departure time of the mobile vehicle leaving the current path unit, and compensate the difference between the actual departure time and a planned departure time in a planned path timing; if the current path unit in the compensation timing conflicts, re-plan the current path unit in the conflicting current path unit; occupy the next path unit; and release the current path unit, and update the data of the occupied next path unit and the data of the released current path unit in the path server.

5. The multi-vehicle control method as described in claim 2, wherein, When the mobile vehicle enters a current path unit, it releases a previous path unit; updates the actual entry time of the mobile vehicle into the current path unit, and compensates the difference between the actual entry time and a planned entry time in a planned path timing; if the current path unit in the compensated timing conflicts, it re-plans the current path unit in the conflicting current path unit; and occupies the current path unit, updating the path server with the data of the released previous path unit and the data of the occupied current path unit.

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