JP3364021B2 - Operation management control apparatus and method - Google Patents

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an operation management control device and method for managing the operation of an automatic guided vehicle and determining the transfer route in an unmanned transfer system for factories and the like.

[0002]

2. Description of the Related Art FIG. 37 is a system configuration diagram of an automatic carrying system having a plurality of unmanned vehicles. In this figure, 1
00 is an operation management control device for managing the unmanned transportation system, 101 is a ladder-type traveling path, # 1, # 2, ..., #
5 is an unmanned vehicle. 28 are nodes scattered on the traveling path 101, and the unmanned vehicles # 1 to # 5 stop, change the direction of the unmanned vehicles, and load and unload work. . Further, each of the unmanned vehicles # 1 to # 5 has a function of determining a traveling route to a target point (hereinafter, a target node), and the operation management control device 100
Move to the target node given by The determination of this route is described in the optimum route determination device (Japanese Patent Application No. 5-77244).

An example of the operation of this unmanned transport system will be described below. First, from the operation management control device 100, the unmanned vehicle #
It is assumed that the movement instructions shown in FIG. 37 are sent to 1 to # 5. Then, the unmanned vehicles # 1 to # 5 create an optimum travel route to the instructed movement target. The cost of each traveling section (arc) connecting adjacent nodes is used to determine the optimum route, and the route having the smallest integrated value of the costs is selected. However, in the creation of this travel route, the travel routes of other unmanned vehicles are not considered, and the optimal travel route is obtained only when no other unmanned vehicle exists. The cost here is an index such as the time required to pass each arc. FIG. 38 is a diagram showing the cost on the traveling path 101. In this diagram, the cost of each arc is shown in parentheses.

FIG. 39 shows each unmanned vehicle # 1 created at this time.
FIG. 3A is an operation diagram showing the travel routes of the unmanned vehicles # 1 to # 5, and the travel routes of the unmanned vehicles # 1 to # 5 are shown by solid lines, dotted lines, broken lines, one-dot chain lines, and two-dot broken lines, respectively. The operation diagram, (b) of the figure, is a diagram showing those routes in a node sequence. Next, the unmanned vehicles # 1 to # 5 send the node numbers on their own travel routes to the operation management control device 100 in the order of movement, and reserve the nodes. Operation management control device 100
Examines the requested node sequence (FIG. 39 (b)) in order from the beginning and permits the reservation if no other unmanned vehicle has made a reservation. Then, the unmanned vehicles # 1 to # 5 move to the permitted node. These controls prevent collisions between unmanned vehicles.

Now, for example, it is assumed that the unmanned vehicles # 1 to # 5 have reached the nodes 4, 6, 20, 22, and 3, respectively. FIG. 40 is an operation diagram showing the current position of each of the unmanned vehicles # 1 to # 5 and the traveling route after that at this time. When the next movement is performed while keeping this route, the unmanned vehicles # 1 and # 2 move in the opposite directions on the same traveling route, which causes competition of the traveling routes. In such a case, the destination cannot be reached unless either one changes the route. At this time, the unmanned vehicles # 1 and # 2 are not permitted to reserve the next destination node.

Therefore, the unmanned vehicle # 1 makes a detour (node 4 → 1).
8 → 19 → 20 → 21 → ...) is found and the node 18 is reserved. As a result, the unmanned vehicle # 2 can move along the original route, but this time, a competition for the traveling path occurs between the unmanned vehicles # 1 and # 3. Figure 41 shows each unmanned vehicle # 1 at this time
It is an operation diagram showing the routes from to # 5. Now, unmanned vehicle # 3 finds a detour (nodes 20 → 6 → 5 → 4 → 3 → 16 → 15), reserves node 6, and then moves to that node. In this way, repeating the competition of the driving route and the detour search,
Each unmanned vehicle # 1 to # 5 moves to the destination.

[0007]

However, since the above method changes the moving route after the competition of the traveling paths occurs,
There are cases where unnecessary movements and waiting such as repeated detours occur, and as the number of unmanned vehicles increases, there is a problem that the transport efficiency decreases significantly. The present invention has been made under such a background, and an object of the present invention is to provide an operation management control device and a method thereof in which a plurality of unmanned vehicles can efficiently move to a target point.

[0008]

According to a first aspect of the present invention, an operation for controlling the operation of a plurality of unmanned vehicles traveling on a traveling path including a plurality of nodes at stop positions and a connecting path connecting the nodes. In the management control device, a first means for searching a traveling route of each unmanned vehicle so that each unmanned vehicle does not travel in the opposite direction on the same connecting path, and each unmanned vehicle searched by the first means. Simulate the temporal movement of each unmanned vehicle based on the traveling route, and when any unmanned vehicle is detected to be unprogressable, change the node passage order, detour route search, or escape route search and a second means for releasing the non progression of the unmanned vehicle, wherein the
1 means connects the starting and destination nodes of each unmanned vehicle.
All the routes, calculate the cost of each route,
If an unmanned vehicle is competing in the opposite direction,
Add the cost of the direction section for the number of times that conflict has occurred,
Unmanned guided vehicles are sequentially selected in descending order of cost
However, the reverse running section of this automatic guided vehicle is
As a one-way street, it is necessary to re-acquire routes for all unmanned vehicles.
Characterize .

The invention according to claim 2 is an operation management control method for controlling the operation of a plurality of unmanned vehicles traveling on a traveling path consisting of a plurality of nodes at stop positions and a connection path connecting the nodes, A first step of searching a traveling route of each unmanned vehicle so that each unmanned vehicle does not travel in the opposite direction on the same connection route, and the time of each unmanned vehicle based on the traveling route obtained by the first step. And check the movement
A second step of adding a shunting route to the route of the unmanned vehicle that has already finished traveling when any unmanned vehicle is detected to be unrunnable, and an unmanned vehicle if the unstoppable state cannot be resolved in the second step. A third step of changing the traveling order of the vehicles, a fourth step of adding a detour route to the route of the unmanned vehicle when the unstoppable state cannot be resolved in the third step, and a non-progressable state that cannot be resolved in the fourth step And a fifth step of adding a shunt route to the route of the unmanned vehicle , and in each of the first step,
Find all the routes that connect the starting and target nodes of
The cost of each route of
If there is a conflict, the cost of this backward section is
The number of times that the
Select unmanned guided vehicles in ascending order and reverse the unmanned guided vehicle.
The traveling section is defined as one-way traffic of this automated guided vehicle,
The feature is that the route of the unmanned vehicle is recalculated .

According to a third aspect of the present invention, in the operation management control device according to the first aspect, a plan instruction storage means for storing the determined travel route of the plurality of unmanned vehicles at a predetermined time and the given work content, First processing for monitoring the state of each unmanned vehicle, and each time an unmanned vehicle that has completed a given work occurs, a new work is set in the plan instruction storage means, and the first means and the By performing the second process for activating the second means to search the travel route and the third process for giving an operation instruction to each of the unmanned vehicles based on the result of the search in parallel and periodically, It is characterized by comprising an operation control means for controlling the operation of a plurality of unmanned vehicles.

[0011]

According to the invention described in claim 1, the second means is the first
Based on the travel route obtained by the means, it simulates the time movement of each unmanned vehicle, and when it detects that the unmanned vehicle cannot move in the process, it changes the traveling order, detour route search, escape route search. As described above, the impassability is released, so that it is possible to obtain a travel route and a travel order in which the travel is not delayed, and thus it is possible to improve the travel efficiency.

According to the second aspect of the present invention, when it is detected that the unmanned vehicle cannot move, it is impossible to proceed in the order of adding the evacuation route, changing the traveling order, adding the bypass route, and adding the evacuation route. Since the above is canceled, it is possible to obtain the route and the traveling order in which the movement of all the unmanned vehicles is not delayed, and thus it is possible to improve the movement efficiency.

According to the third aspect of the invention, the operation control means periodically monitors the state of each unmanned vehicle, and when an unmanned vehicle that has completed the work occurs, a new instruction is stored in the plan instruction storage means of the unmanned vehicle. Set the work. After that, the first and second means perform the travel route search in consideration of the states of other unmanned vehicles. Therefore, new work can be immediately given to the unmanned vehicles that have completed the work, without waiting for the completion of the work of all the unmanned vehicles.

[0014]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The first and second embodiments of the present invention will be described below with reference to the drawings. FIG. 1 is a block diagram showing the configuration of the operation management control device 102 according to the first embodiment. In this figure, 103 is an operation control data memory, which stores the travel route of each unmanned vehicle, a node reservation sequence described later, and the like. Reference numeral 104 denotes a conveyance instruction table memory, which stores a position of a conveyed object, a conveyance destination, and the like. 10
Reference numeral 5 denotes an unmanned vehicle data memory, which stores the current position of each unmanned vehicle, the state of movement, and the like. Reference numeral 106 denotes a traveling road data memory, which stores the coordinates of each node on the traveling road, their connection relations and costs (FIG. 38). Also, 107 is a planning unit that determines the optimum travel route and operation sequence of the unmanned vehicle. The planning unit 107 includes a CPU and the like, and can be functionally divided into an operation planning unit 108, a route planning unit 109, and a route searching unit 110. The operation planning unit 108, the route planning unit 109, and the route searching unit 110 will be described in detail below.

Route Search Unit 110: First, the route search unit 11
According to the route search instruction supplied from the route planning unit 109, 0 obtains all the routes connecting the starting node and the target node of each unmanned vehicle. Next, the cost of each route is added up from the cost (FIG. 38) stored in the travel route data memory 106, and the route having the minimum cost is selected as the optimum route. However, when the route search instruction includes direction information for orientation, which will be described later, the route that travels the oriented arc in the opposite direction is not selected. Similarly, when the route search instruction includes lane-prohibited direction information, which will be described later, a route that passes the lane-prohibited arc is not selected. The route obtained by the above method and its cost are the route planning unit 1
It is output to 09. However, the route created here is
The driving routes of other unmanned vehicles are not taken into consideration, and the route becomes the optimum route only when there is no competition of the driving routes.

Route planning unit 109: The route planning unit 109
A travel route having no reverse travel section is obtained using a tree search method, and the result is output to the operation planning unit 108. The "tree" referred to here has a configuration of branching downward as shown in FIG. Here, N1, N2, ... Are branch points containing branch conditions, and among these, the branch point N1 is a root branch point for starting branching. Further, for example, when the branch point N2 is the current branch point, the branch point N1 is the parent branch point of the branch point N2, and the branch points N3 and N4 are the child branch points of the branch point N2. The search is basically performed from the upper branch point to the lower branch point, but when the search is impossible, the parent branch point is temporarily returned (hereinafter referred to as backtrack), and the branch is made to another branch point.

FIG. 3 is a flow chart showing the route planning process performed by the route planning unit 109, which will be described below with reference to this figure. When the processing is started (step SP1),
In step SP2, a search instruction is issued to the route search unit 110 to obtain the travel route of each unmanned vehicle. Here, the route search unit 110 that has received the search instruction searches for a route by the above-described method, and the initial route that is the result is searched for by the route planning unit 10.
Output to 9. The search instruction includes the target node of the unmanned vehicle determined by the data stored in the transport instruction table memory 104.

At step SP3, the root branch point of the tree is emptied. In step SP4, a section in which any two unmanned vehicles move in opposite directions (reverse section) is obtained based on the travel route of each unmanned vehicle supplied from the route search unit 110, and this is calculated as the section of the unmanned vehicle. Do this for all combinations. In step SP5, if there is no backward section in the result of step SP4, the process ends (step S
P17), if there is a backward section, the next step SP
Go to 6. Further, when there is no reverse direction section, the traveling route at that time is the final traveling route.

At step SP6, the costs of the backward sections of the route of each unmanned vehicle are added up. Here, the cost of the reverse direction section is read from the travel path data memory 105. In addition, when there is a competition in the opposite direction with the routes of a plurality of other unmanned vehicles in a certain reverse direction section, the cost is added up for the number of times of the competition. However, if there is no other route connecting two adjacent points on the traveling road, the section is not included in the backward section. In step SP7, competing unmanned vehicle sets are created by arranging the symbols attached to the unmanned vehicles in descending order of cost in the reverse traveling section. In step SP8,
A branch point with this competing unmanned vehicle set is added below the parent branch point. However, when this step SP8 is processed for the first time, the above-mentioned competing unmanned vehicle set is set at the route branch point.

At step SP9, the focused unmanned vehicle is determined from the competing unmanned vehicle set. This unmanned vehicle of interest is sequentially selected from the first unmanned vehicle in the competing unmanned vehicle group arranged in descending order of cost. If there is no next unmanned vehicle, there is no focused unmanned vehicle. In step SP10, if there is no unmanned vehicle of interest in the process of the previous step SP9, the process proceeds to next step SP11, and if there is an unmanned vehicle of interest, the process branches to step SP13. In step SP11, it is checked whether or not the current branch point is before the root branch point, and if it is not the root branch point, the next step SP12.
In the case of a route branch point, that is, when the route rearrangement fails in all of the competing unmanned vehicle sets of the route branch point,
All processes are terminated due to failure of route arrangement (step SP1)
7).

At step SP12, the process at the current branch point is moved to the parent branch point (backtrack), and the process returns to step SP9. In addition, the orientation made when branching to the current branch point is canceled at this time. Step S
In P13, the reverse section of the route of the target unmanned vehicle in the traveling path is oriented in the direction opposite to the moving direction of the unmanned vehicle (one-way) and added to the direction information. In step SP14, a search instruction is issued to the route search unit 110, and routes of all unmanned vehicles are recalculated on the oriented traveling route.

In step SP15, the previous step SP1
It is checked whether or not there is a route that cannot be obtained in the route search of No. 4, and if it exists, the process proceeds to the next step SP16, and if it does not exist, the process returns to step SP4. In step SP16, after the orientation of the traveling road performed in step SP13 is canceled, the process returns to step SP9. By the processing described above, a plurality of routes for unmanned vehicles (hereinafter, basic routes) with a small cost and no reverse traveling section can be obtained.

Operation Planning Unit 108: The operation planning unit 108
Based on the basic route supplied from the route planning unit 109, the movement of each unmanned vehicle is temporally checked, the movement order is adjusted,
Plan the movement of all unmanned vehicles to the target node by changing or adding routes as necessary. Moreover, the plan is carried out by simulation using a Petri net. Before describing the operation planning process performed by the operation planning unit 108, various processes included in the Petri net and the operation plan will be described using specific examples.

(1) Petri Net FIG. 4 (a) is an operation diagram used to explain the Petri net. In this figure, unmanned vehicles # 1 and # 2 are on standby on nodes 2 and 6 of the road 111, respectively. is doing. Also, FIG.
(B) shows the departure nodes of unmanned vehicles # 1 and # 2,
FIG. 3 is a diagram showing a target node and a route to the target node, and the inside of [] shows a moving time (second) between the nodes. That is, the unmanned vehicle # 1 moves from the node 2 to the nodes 3 and 4 in this order, and the moving time of each is from the node 2 to the node 3.
Is 1 second, and between nodes 3 and 4 is 3 seconds. The same applies to the unmanned vehicle # 2.

FIG. 5 is a diagram obtained by modeling the above operation diagram (FIG. 4A) with a Petri net. In the figure, P1, P2, ..., P8 are places, respectively, which correspond to the nodes 1 to 8 of the traveling path 111 and indicate the occupied states of the nodes. In addition, in these places P1 to P8, black tokens (black circles) are placed in circles when there are unmanned vehicles at the corresponding nodes, and white tokens (white circles) are shown when nodes are reserved. ) Is placed. In the initial state, the unmanned vehicle # 1 is set to the node 2 and the unmanned vehicle #
Since 2 is at node 6, black tokens are placed at places P2 and P6, respectively.

Further, T12, T23, ... Are transitions and indicate the moving state of the unmanned vehicle. Further, the transition has an input arc entering the transition and an output arc exiting from the transition, and these arcs connect two adjacent places. For example, the transition of the input node 5 and the output node 6 is T56,
Conversely, the transition corresponding to the move from node 6 to node 5 is T65. Also, when moving from node 5 to node 6, this transition T56 is fired to indicate that the unmanned vehicle is moving. Moreover, once the transition fires, it keeps firing for a finite time based on the moving time of the corresponding arc.

Further, a sequence of transitions on the route to be moved from now on is called an ignition scheduled transition series. In the case of the basic route of FIG. 4 (b), the scheduled transitions of unmanned vehicles # 1 and # 2. The series is as follows. Ignition scheduled transition series (unmanned vehicle # 1) = {T23,
T34} Ignition scheduled transition series (unmanned vehicle # 2) = {T67,
T73, T34}

Next, the processing relating to the ignition of the transition Tst will be described. The ignitable condition transition Tst can be ignited when the input side place Ps has a black token, the output side place Pt has no black token, and all preceding transitions (described later) are fired prior to this.

Ignition process Node Ns when the transition Tst that can be ignited is ignited
The moving time from the node to the node Nt is added to the current time, and is set to the completion time of the unmanned vehicle together with the transition number. When working at the node Nt, the working time is further added to the completion time. Then, a white token is placed in the output place Pt.

Ignition Completion Process A black token is removed from the input place Ps and a white token is removed from the output place Pt of the transition Tst during firing, and a black token is placed in the place Pt. When the unmanned vehicle passes through a single-track section (section without detour) under the above-described ignition possible conditions, it is checked whether the transitions can be collectively ignited. For example, if the transition sequence to be fired is {T1, T2, ..., Tn} and the transitions Ti, Ti + 1, ..., Tj among them are single-line sections, the transition Ti-1 is the transition T-1.
Can fire only if i, ..., Tj are all fireable. This is to prevent the exit of other unmanned vehicles existing in the single track section from being blocked by the ignition of the transition Ti-1.

(2) Planned Evacuation Operation In the evacuation operation, when there is another unmanned vehicle in the waiting state after the work is completed at the destination of the moving unmanned vehicle, the unmanned vehicle in the waiting state is removed. This is an operation to move (retract) to the node. FIG. 6 is a flowchart of the evacuation route search processing for finding the evacuation route, which will be described below.

When the evacuation operation is started, step Sa2
Check the nodes around you and find all the nodes that can be saved. Here, a node that can be saved is a node that satisfies the following conditions. Moving to that node is not prohibited. Not occupied by an unmanned vehicle that is not on standby.

Next, in step Sa3, basic costs such as travel time are added to the nodes that can be saved. However, for a node with an unmanned vehicle in a standby state, the cost is multiplied by 100, for example, so that the node is not selected as much as possible. In step Sa4, step S
Among the results of a3, the node with the lowest cost is set as the evacuation node, and the section from the current node to the evacuation node is added to the travel route of the unmanned vehicle.

FIG. 7 is an operation diagram showing an example of the above evacuation route search. In this figure, unmanned vehicles # 1 and # 3
Is on standby (no move planned), and unmanned vehicle # 2 is about to move to node 3. In this case, the unmanned vehicle # 1 that interferes with the unmanned vehicle # 2 is the target of evacuation. This drone #
The nodes that can be saved are node 2 and node 7, and the cost of the save path to both nodes is checked. The travel time to node 2 is 1 second, but since the unmanned vehicle # 3 is waiting at node 2, the basic cost is 100 of that travel time.
It will be doubled to 100. The travel time to the node 7 is 4, and the basic cost is 4. Therefore, the node 7 having a low cost is selected as the evacuation node, and the nodes 3 → 7 are added to the route of the unmanned vehicle # 1.

(3) Deadlock In the case where a plurality of unmanned vehicles are crowded in a narrow area and a deadlock situation occurs in which the vehicle cannot proceed on the planned route even if the evacuation operation is performed, The firing order adjustment, the detour route search, and the escape route search, which will be described later, are performed. Here, the method of grasping the state of deadlock is described. FIG. 8 is a flowchart showing this deadlock grasping process, which will be described below.

First, in step Sb2, an unmanned vehicle that has not been subjected to the following processing is selected and it is checked whether or not the unmanned vehicle is on standby. If the driver's vehicle is not on standby, the process proceeds to step Sb3, and if it is on standby, the process branches to step Sb4. In step Sb3, the closest unmanned vehicle on the travel route of the target unmanned vehicle is set as an unmanned unmanned vehicle, and the process proceeds to step Sb5. In step Sb4, all unmanned vehicles around the target unmanned vehicle are set as disturbing unmanned vehicles, and the process proceeds to the next step Sb5. In step Sb5, it is checked whether or not the above processing has been completed for all unmanned vehicles, and if there are unprocessed unmanned vehicles, the process returns to step Sb2.

In step Sb6, an unmanned vehicle not properly waiting is selected, and the unmanned vehicle is disturbed by the unmanned vehicle, the unmanned vehicle is disturbed by the unmanned vehicle being disturbed, ...
・ Following that, find two or more loops. Then, this is performed for all combinations. In step Sb7, a loop including the largest number of unmanned vehicles among the obtained loops is selected as a competitive loop.
In step Sb8, if the contention loop is not obtained in the process of step Sb7, this process ends due to deadlock grasp failure (step Sb10). In step Sb9, for each unmanned vehicle in the competition loop, an adjacent node to which the unmanned vehicle can move, that is, a node in which no other unmanned vehicle is present, is obtained, and this processing ends (step Sb10).

FIG. 9 is a diagram showing an example of deadlock on the traveling path 101. FIG. 9A shows an operation diagram in its initial state, and FIG. 9B shows an operation diagram in a deadlock state. Further, in this figure, unmanned vehicles that are not on standby are shown in black and unmanned vehicles that are on standby are shown in white. here,
The travel routes of the unmanned vehicles # 1 to # 6 are as follows. Unmanned Vehicle # 1: 6 → 5 → 4 Unmanned Vehicle # 2: 5 → 4 Unmanned Vehicle # 3: 17 → 18 → 4 Unmanned Vehicle # 4: 2 → 3 → 16 Unmanned Vehicle # 5: 16 → 17 Unmanned Vehicle # 6 : 15 → 16 → 17

According to the above route, the unmanned vehicles # 1 to #
When 6 moves from the initial route of FIG. 9 (a) by one section,
A deadlock state as shown in FIG. Here, although the unmanned vehicles # 2 and # 5 are in the standby state, the evacuation route described above cannot be found. Then, each of the unmanned vehicles # 1 to # 6 examines the unmanned unmanned vehicle in the way, and obtains the result as shown in FIG. 9 (c). In this figure, for example, the unmanned vehicle # 1 interferes with the unmanned vehicle # 2, and the unoccupied free node of the unmanned vehicle # 1 at the time of deadlock is the node 6. Based on this result, when searching for a loop of an unmanned vehicle that disturbs or an unmanned vehicle that interferes, Loop 1: Unmanned vehicle # 1 (5) → # 2 (4) Loop 2: Unmanned vehicle # 3 (18) → # 2 (4) Loop 3: Unmanned Vehicle # 6 (16) → # 5 (17) Loop 4: Unmanned Vehicle # 3 (18) → # 2 (4) → # 4 (3) → # 6 (1
4 loops of 6) → # 5 (17) → # 3 are obtained. Then, the loop 4 including the largest number of unmanned vehicles among these is selected as the competing loop. Note that the values in parentheses are the current positions (nodes) of each unmanned vehicle at the time of deadlock.

(4) Firing order adjustment When the deadlock described above is encountered, first, the firing order of transitions is adjusted and an attempt is made to eliminate it. In other words, we investigate whether deadlock can be avoided by changing the reservation order of nodes. FIG. 10 is a flowchart showing this firing order adjustment processing, which will be described below.
First, in step Sc2, the number of times another unmanned vehicle passes through the current node of each unstandby unmanned vehicle belonging to the competition loop is counted. In step Sc3, it is checked whether or not the number of times of passing is "0". If "0", this process is ended (step Sc9), and if it is not "0", the process proceeds to the next step Sc4.

In step Sc4, it is checked whether or not the number of passages of each node is a new state different from that in the previous firing order adjustment processing, and if it is a new state, the next step Sc
If the state is the same as the last time, the process ends (step Sc9). This is because if the state becomes complicated, the firing order may be changed many times and eventually the state may return to the previous state. In step Sc5, the unmanned vehicle there is checked to see if it has passed the current node of the unmanned vehicle that is disturbing itself, and if not, the next step S5.
The process proceeds to c6, and if it passes, the process ends (step Sc9). This is because the unmanned vehicle that has passed through the same section cannot check the unmanned vehicle that comes later, so that the joining point (node) is checked.

At step Sc6, the number of passages as a result of step Sc2 is used as an evaluation value. However, if the unmanned vehicle that is disturbing you is in the standby state, increase the evaluation value. In addition, the above-described processing of steps Sc2 to Sc6 is performed for all the nodes including the non-standby unmanned vehicles belonging to the competition loop. In Step Sc7, Step Sc6
The node having the smallest evaluation value of each node obtained in step 1 is selected as the competitive node. At step Sc8, the transition ignition control data is added so that the unmanned vehicle that interferes with the unmanned vehicle at the competing node will pass first. The transition firing control data regulates the moving order of the unmanned vehicle at the specific node, and the firing of the transition is regulated by this.

The process of adjusting the firing order described above will be described with reference to the operation diagram of FIG. 9 described above. First, node 1 with unattended unmanned vehicles # 3, # 4, and # 6 in a contention loop
The number of passages is calculated for each of 8, 3, and 16 (FIG. 9B). As a result, since the node 16 is once and the other nodes are 0 times, the node 16 is selected as the competition node. The transitions having this node 16 as the output destination are transitions T15.multidot.16 and T3.multidot.16, and the firing order of these is reversed. In other words, transition T3 / 16 is set as the preceding transition, and it is fired before transition T15 / 16. As a result, before the unmanned vehicle # 6 is moved to the node 16, the unmanned vehicle # 4 is moved to the node 16 and the unmanned vehicle # 2 on standby can be evacuated to the node 3 because the node 3 is vacant. In this way, deadlock may be eliminated by adjusting the firing order of transitions.

FIG. 11 is a diagram showing the final result of this specific example. FIG. 11 (a) shows the routes from the departure nodes to the target nodes of the unmanned vehicles # 1 to # 6, and FIG. 11 (b) shows The node reservation sequence is shown. The target node is shown in the parentheses in (a) of the figure, and the route after this node is the evacuation route described above. Also, the node reservation sequence ((b) in the figure)
Represents the order in which an unmanned vehicle reserves each node. In this figure, for example, node 5 reserves unmanned vehicles # 2 and # 1 in this order.

(5) Planning of detour operation If the deadlock situation cannot be resolved according to the basic route, a suitable unmanned vehicle is planned to take the detour route. FIG. 12 is a flowchart showing this detour route search processing, which will be described below.

First, in step Sd2, it is checked whether or not there is a movable adjacent node with respect to a non-standby unmanned vehicle that belongs to the competition loop. If there is, the process proceeds to the next step Sd3, and if not, the detour route search fails and the process is finished (step Sd9). In step Sd3, the following arcs are temporarily prohibited for the unmanned vehicle selected in the previous step. An arc from the current node of the unmanned vehicle to the next node

In step Sd4, the current node is set as the starting node and the next node is set as the target node. Step S
In d5, the route search process (step Sa1) is performed based on the settings in steps Sd3 and 4. Step Sd6
Then, the arc passage prohibition performed in step Sd3 is released. In step Sd7, it is checked whether or not the detour route is obtained in the route search process of step Sd5. If there is a detour route, the process proceeds to the next step Sd8. If there is no detour route, the detour route search fails and this process is executed. It ends (step Sd9). In step Sd8, the route of the target section is replaced with the detour route, and this process ends (step Sd9).

FIG. 13 is a diagram illustrating a deadlock situation, and FIG. 13A is an operation diagram showing a deadlock situation. The above-mentioned detour route search process will be described below with reference to this figure. First, when the unmanned vehicle # 1 is selected first, the arcs of the nodes 4 → 3, 4 → 18 are forbidden to try to obtain a detour route. Unmanned car in this case #
The detour route of 1 is node 5 → 6 → 20 → 19 → 18
→ 17 ... Route is considered, but node 18 → 17
Is reverse to the route of unmanned vehicle # 4, so basically this route is not selected. However, the operation plan described later (Fig. 16)
In the second trial of, the reverse running section may not be closed and may be selected. Next, unmanned vehicle # 2
If you make a detour route search with node 3 → 2 → 1 → 15 → 16
Is obtained. Then, this route becomes a bypass route and is inserted between the routes (3 → 16) of the unmanned vehicle # 2 (see FIG. 1).
3 (b)).

(6) Reservation operation plan When a detour operation cannot be taken in a deadlock situation, an appropriate unmanned vehicle temporarily retreats to another node (retracts), gives way to another unmanned vehicle, and then again. Move along the original route.
FIG. 14 is an evacuation route search showing this evacuation operation, which will be described below. First, in step Se1, it is checked whether or not there is an adjoining node that can be moved in an unmanned vehicle (non-standby unmanned vehicle) that belongs to a competition loop and has not yet arrived at the target node, and if there is, it proceeds to the next step Se3. If there is no evacuation route search, this process ends (step Se10).

In step Se3, the arc from the current node of the unmanned vehicle to the next node is temporarily prohibited. In step Se4, the current node is set as the departure node,
Set all other nodes as target nodes. Step S
In e5, the route search process (step Sa1) is performed under the conditions set in steps Se3 and 4. In step Se6, the route with the lowest cost is selected from all the routes obtained in step Se5, and the target node is set as the save node. However, when selecting the save node, the nodes existing in the single line section are excluded.

At step Se7, the prohibition of traffic performed at step Se3 is released. In step Se8, if there is no evacuation node as a result of step Se6, this process ends due to failure of evacuation route search (step Se10), and if there is an evacuation node, the process proceeds to the next step Se9. In step Se9, the route from the current node to the shunt node and the route from that node to the current node (the shunt route) are inserted into the route currently held, and this processing ends.

FIG. 15A is an operation diagram exemplifying a deadlock situation, and the escape route search processing will be described based on this operation diagram. First, assuming that the unmanned vehicle # 1 is selected first, the nodes 4 to 3 are temporarily prohibited and a route search is performed, and the node 5 is selected as the save node having the lowest cost. Here, the movable adjacent node of the unmanned vehicle # 1 includes the node 18 in addition to the node 5, but the cost (see FIG.
The node 5 with the smaller reference (reference) is selected as the save node. Next, the route from the node 5 to the node 4 is searched, and the node 4
→ 5 → 4 can be obtained as the escape route. Finally, this escape route is inserted into the original route and the route of unmanned vehicle # 1 (nodes 4 → 5 →
4 → 3 → 2) is obtained (FIG. 15B).

(7) Operation Planning The operation planning unit 108 determines the routes of all unmanned vehicles and plans the moving order by using the above-mentioned various processes (1) to (6). 16, 17, and 18 are flowcharts showing this operation planning process, which will be described below. First, in step Sf1 (FIG. 16), the running path is modeled using a Petri net. In step Sf2,
Set 1 to the number of trials. In step Sf3, the route of each unmanned vehicle is set to the basic route obtained by the route planning. In step Sf4, the number of trials is checked and the number of trials is "1".
If so, the process proceeds to the next step Sf5, and if the value is other than "1", the process proceeds to step Sf6.

In step Sf5, all arcs that are reverse to the above-mentioned basic routes are prohibited. As a result, the backward section does not occur in the following processing. Further, when the process returns due to the loop and the number of trials becomes 2 (FIG. 18, step Sf31), this step Sf5 is not executed, and this restriction of passage prohibition is not added in the route search process. In step Sf6, the current time is initialized to 0. In step Sf7, each unmanned vehicle is placed at the starting point, and the ignition scheduled transition series is obtained from each of the routes. In step Sf8, the completion time of each unmanned vehicle is initialized to -1.

In step Sf9, the ignition transition sequence is initialized to empty. This firing transition series is a series of transitions that actually fires, and does not necessarily match the scheduled firing series. In step Sf10, it is checked whether or not the completion time is the same as the current time for each unmanned vehicle. If they are the same, the process proceeds to the next step Sf11, and if they are not the same, the process branches to step Sf12. In step Sf11, the leading transition is extracted from the transitions scheduled to be fired of all unmanned vehicles that satisfy the condition of step Sf10, and the ignition completion process is performed.

In step Sf12 (FIG. 17), it is checked whether or not the completion time is before the current time for each unmanned vehicle, and if it is before, the process proceeds to next step Sf13,
If not, the process branches to step Sf20. In step Sf13, it is checked whether or not the transition at the head of the scheduled firing transition can be fired. If it can fire, the process proceeds to step Sf14, and if it cannot fire, the process branches to step Sf17. In step Sf14, all the transitions that are allowed to be fired in step Sf13 are taken out and the firing process is performed.

In step Sf15, the moving time of the transition fired at the completion time is added to update the completion time. In step Sf16, the transitions fired in step Sf14 are registered (added) to the corresponding firing transition series, and the process proceeds to step Sf20. On the other hand, in step Sf17, it is checked whether or not there is a movable adjacent node in the unmanned vehicle that disturbs the transition that cannot fire. In other words, check if you can drive the unmanned unmanned vehicle to another node. As a result, if the ejection is possible, the process proceeds to the next step Sf18, and if not, the process branches to step Sf20.

In step Sf18, it is checked whether or not the unmanned vehicle allowed to be ejected in step Sf17 is on standby, and if it is on standby, the process proceeds to the next step Sf19,
If not waiting, the process branches to step Sf20. In step Sf19, the evacuation route processing (FIG. 6, step Sa1) is performed on the unmanned vehicle that satisfies the conditions of steps Sf17 and S18 to obtain the evacuation route. Step Sf20
Then, it is checked whether or not the completion time of the ignition transition corresponding to all the unmanned vehicles is before the current time, and if it is before, the process branches to step 22, and if not, the step Sf.
Proceed to 21.

In step Sf21, an unmanned vehicle having the closest future completion time is found from all the unmanned vehicles, and the completion time is set to the current time. Then, step Sf1
Return to 0 (FIG. 16). In step Sf22, it is checked whether or not the transition sequences scheduled to fire all unmanned vehicles are empty. If it is empty, the process branches to step Sf32 (FIG. 18), and if it is not empty, the process proceeds to next step Sf23. In step Sf23, the deadlock situation is checked by the above-described deadlock grasping process (FIG. 8, step Sb1). In step Sf24, the firing order of each transition is adjusted by the firing order adjustment processing (FIG. 10, step Sc1) described above, based on the competition loop obtained in the processing of step Sf23.

In step Sf25, it is checked whether or not the adjustment of the firing order in the previous step Sf is successful. If the adjustment is unsuccessful, the process proceeds to the next step Sf26, and if it is successful, that is, if the deadlock is eliminated, step Sf6. (Fig. 1
Return to 6). In step Sf26, the detour route is searched by the detour route search process (FIG. 12, step Sd1). In step Sf27, it is checked whether or not the bypass route search in the previous step has succeeded.
Return to f6 (FIG. 16). In step Sf28, the escape route is searched by the escape route search (FIG. 14, step Se1).

In step Sf29, it is checked whether or not the escape route search in the previous step has succeeded.
Return to f6 (FIG. 16). In step Sf30, the current number of trials is checked, and if it is "1", the next step Sf is performed.
If it is not "1", the operation plan is unsuccessful and the entire process is terminated (step Sf34). Step Sf31
Then, after increasing the number of trials to 2, the process returns to step Sf3 (FIG. 16). Step Sf32 is executed when the operation plan of the unmanned vehicle is successful, and sets the current route to the final route of the unmanned vehicle. In step Sf33, an order of unmanned vehicles occupying each node (node reservation sequence) is created based on the ignition transition sequence, and the whole process is terminated (step Sf34).

(8) Processing Example of Petri Net Simulation Next, a specific example of the above Petri net simulation will be described under the conditions of the operation diagram (a) and route (b) in FIG. 4 described above. FIG. 19 is a Petri net diagram showing a simulation process. First, the initial state (Fig. 19)
In (a)), first, the transition T23 corresponding to the unmanned vehicle # 1 is changed to the unmanned vehicle # by the ignition process (step Sf14).
Transition T67 corresponding to 2 fires respectively.
Their completion time is 1 or 2 seconds, respectively. Then, white tokens are placed in the places P3 and P4.

Next, in step Sf21, the current time is updated to the completion time of the unmanned vehicle # 1, that is, 1 second, and the process returns to step Sf10. By the firing completion process of step Sf11, the black token appears in the place P2 and the white token appears in the place P3, and the black token appears in the place P3 (FIG. 19B). This state means that the unmanned vehicle # 1 has arrived at the node 3. Here, the transition T67 during ignition is surrounded by a rectangle. Next, step Sf
14, the transition T34 corresponding to the unmanned vehicle # 1 is fired, and the completion time of the unmanned vehicle # 1 is 4 in step Sf15.
Set to seconds. Next, in step Sf21, the current time is updated to 3 seconds which is the completion time of the unmanned vehicle # 2,
The ignition completion process of the transition T67 is performed in step Sf11 which returns again via f10.

At step Sf13, the transition T73 of the unmanned vehicle # 2 is checked, but it cannot be fired because there is a black token in the output place P3. This is because the unmanned vehicle # 1 occupies the node 3. Unmanned vehicle # 1 is currently moving from node 3 to 4 and cannot be ejected. Therefore, the unmanned vehicle # 2 waits at the node 7. At step Sf21, the current time is updated to the completion time of the unmanned vehicle # 1, that is, 4 seconds. The ignition process of the transition T34 is performed in step Sf14, and the unmanned vehicle # 1 arrives at the target node 4. Next, since the unmanned vehicle # 1 has opened the node 3, the ignition process of the transition T73 is performed in step Sf14 (FIG. 19 (d)). At the time when the ignition process of the transition T73 is completed (FIG. 20 (a)), step S
At f14, it tries to ignite the last transition T34, but cannot ignite, so it drives out unmanned vehicle # 1.

By the evacuation route search processing (step Sf19), the evacuation route (node 4 → 8) of the unmanned vehicle # 1 is obtained, and the corresponding transition T48 is added to the transitions to be fired and fired. Thereafter, the simulation proceeds in the same process, and when the process proceeds to FIG. 20C, there is no transition to be fired, and the process of step Sf32 starts. Transition firing sequence = {T23 (# 1), T6
7 (# 2), T34 (# 1), T73 (# 2), T48 (# 1), T34 (#
2)}, the preceding relationship of the unmanned vehicle occupying each node is examined, and a node reservation sequence as shown in FIG. 21A is created. Further, from this node reservation sequence, an operation plan diagram as shown in FIG. In this figure, unmanned vehicles # 1 and # 2 correspond to the solid line and the broken line, respectively. Also, arrows indicate the movement of each unmanned vehicle, and horizontal lines indicate the period during which the node is reserved. For example, the unmanned vehicle # 1 moves from the node 2 to the node 3 in 1 second, and further moves to the node 4 in 3 seconds. During this time, node 3
Reserved for unmanned vehicle # 1 from time 0 to 4.

Overall Operation Example 1: Below, the operation management control device 102 (FIG. 1) in the conveyance path 101 shown in FIG. 37.
The operation of will be described. In the following figures, parts corresponding to those in FIG. 37 are assigned the same reference numerals and explanations thereof are omitted. In addition, the starting point and the target point in this operation example are shown in FIG.
It shows in (a). First, the route planning unit 109 outputs a search instruction (FIG. 22A) to the route searching unit 110. The route search unit 110 follows each unmanned vehicle # 1 according to this search instruction.
The transport route (initial route) of # 5 to # 5 is searched, and the initial route resulting from the search is output to the route planning unit 109. FIG. 23
(A) is an operation diagram showing this initial route, in which the routes of the unmanned vehicles # 1 to # 7 are respectively indicated by dotted lines and
It is shown by a long dash-dot line, a two-dot chain line, a dash-dot line, a broken line, a solid line, and a long broken line.

In this initial route, the route planning unit 109 connects the nodes 2 and 3, the nodes 4 to 6, and the node 8 to each other.
Since the section between 10 and 10 is the reverse direction section, the specific section of the traveling path is oriented according to the cost, and the search instruction is output to the route search unit 110 again. The above operation is performed until there is no reverse direction section, and FIG.
A basic route as shown in (b) is obtained. Route Planning Department 1
09 outputs this basic route to the operation planning unit 108.
The motion planning unit 108 performs the above-described motion planning process (FIGS. 16, 17, and 18) based on this basic route. In addition, a route search such as a detour route performed during this process is performed by the route search unit 110 via the route planning unit 109. In addition, the departure node, the target node, and the prohibited section in this case are output from the operation planning unit 108. Through the above processing, the final route as shown in FIGS. 22 (c) and 23 (c) is obtained. In this final route, an evacuation route (node 20 → 6) for unmanned vehicle # 1 is added to the basic route (FIG. 22B). Further, FIG. 24 is an operation plan diagram temporally showing the movement of each of the unmanned vehicles # 1 to # 7 at this time.

Overall operation example 2: Next, the above-mentioned transport path 1
An operation example when the traffic between the nodes 20 and 21 of 01 is prohibited will be described. However, the present location and the target location of each unmanned vehicle # 1 to # 7 in this operation example are the same as those in the operation example 1 described above (FIG. 22A). In this case, between the nodes 6 and 7, between the nodes 7 and 8, and between the nodes 21 and 2.
Since there is no detouring route other than the route connecting the two, it is not included in the backward section. Here, the same processing as in the operation example 1 is performed, and first, the route searching unit 110 obtains an initial route as shown in the operation diagram of FIG.
Next, the route planning unit 109 creates basic routes as shown in FIGS. 25 (b) and 26 (b). In these figures, the reverse traveling section on the initial route (FIG. 26A) is eliminated.

Then, in the operation planning unit 108, FIG.
The final route as shown in FIG. 5 (c) and FIG. 26 (c) is created. In this final route, the basic route (see FIG. 26)
For (b)), the evacuation route of unmanned vehicle # 1 (node 20
→ 6) and the evacuation route for unmanned vehicle # 5 (node 8 → 22 →
23 → 24 → 10 → 9) is added. Also, FIG.
7 is an operation plan diagram at this time. In this diagram, node reservations for unmanned vehicles # 1 to # 7 are shown by the same line type as in FIG.

As described above, according to the first embodiment, the traveling routes and traveling sequences of all unmanned vehicles can be obtained before traveling in consideration of interference between unmanned vehicles. In other words, the operation of the entire unmanned transportation system is a regular repetition of travel route determination and movement of all unmanned vehicles, so each unmanned vehicle waits for all unmanned vehicles to move and complete work, and then simultaneously The movement has started. Therefore, in the second embodiment described below, an unmanned vehicle that has reached the target node and completed work receives the next instruction immediately without waiting for the other unmanned vehicles to complete work, It will be configured so that the travel route can be given in consideration of the position of the unmanned vehicle and the fixed route. This improves the processing capacity of the entire unmanned transportation system.

FIG. 28 is a block diagram showing the configuration of the operation management control device 202 according to the second embodiment. In this figure, a portion common to the respective portions shown in FIG. 1 is a traveling road data memory 106, and its explanation is omitted.

In FIG. 28, reference numeral 200 denotes an operation control unit, which is a processing device including a CPU (central processing unit), ROM (read only memory), RAM (random access memory) and the like. The operation control unit 200 activates the planning unit 207 and controls the operation of the unmanned vehicle based on the travel route of each unmanned vehicle obtained by the planning unit 207. The planning unit 207 includes a route searching unit 210, a route planning unit 209, and an operation planning unit 208, and its configuration is basically the same as that of the planning unit 107 of the first embodiment. The transfer execution table memory 201 is a storage area for pooling jobs given to the unmanned transfer system. At the time of being stored in the transport execution table memory 201, each job has not been assigned to the unmanned vehicle. Reference numeral 203 denotes a plan result storage memory, which is the first
The operation control data memory 103 in the embodiment of FIG. That is, the plan result storage memory 2
03 stores the fixed route of each unmanned vehicle planned by the planning unit 207, the node reservation sequence, and the like. However, in the first embodiment, the contents of the operation control data memory 103 become the operation command to each unmanned vehicle as it is, but in the present embodiment, the operation control unit 200 checks and refers to the data in the plan result storage memory 203. Since the travel instruction to each unmanned vehicle is output by the travel instruction processing described later, the content of the operation control data memory 103 does not become an operation instruction as it is.

Reference numeral 204 is a plan instruction table memory,
Data is stored that instructs how the planning unit 207 handles each unmanned vehicle when making a route plan and an operation plan. FIG. 29 is an example of the configuration of the plan instruction table memory 204. The plan instruction table memory 204 stores each data of the route determination level, the target node, and the working time for each unmanned vehicle. Each data will be described below.

Route determination level: The route determination level is data indicating the determination status of the travel route of each unmanned vehicle, and has three types: "undetermined", "determined to destination node", and "determined to save destination node". In this embodiment, the operation planning unit 2
The addition of the evacuation route in 08 is performed only after reaching the destination node if necessary. That is, the evacuation route is not inserted in the route before reaching the target node as in the first embodiment. Similarly, when the route to the save destination node is determined, a new save destination node and route are not inserted before the save destination node. By this,
It is necessary to always grasp to what extent the travel route of each unmanned vehicle is established, and this data (route confirmation level)
Is used.

"Undecided" indicates that the route from the current node to the target node has not been determined yet, and therefore the route needs to be obtained. “Determine to destination node” means that the route from the current node to the destination node is established. For the route after the target node, the operation planning unit 20
By adding the save destination node in 8, there is a possibility that a route to it will be added. “Definition to save destination node” means that the route from the current node to the save destination node via the target node is fixed. For the route after the save destination node, the operation planning unit 2
There is a possibility that a route to the evacuation destination node will be added by adding the evacuation destination node in 08.

Target node: This item stores a target node that executes the work of each unmanned vehicle. Working time: This item stores the working time at the target node of each unmanned vehicle. For example, when the work at the target node is loading and unloading of luggage, the real time required for the work is given. When there is no work at the target node, the work time is set to 0.

When a certain unmanned vehicle reaches the target node and completes the work, and there is no work stock in the transfer execution table memory 201 even though it is about to receive the next work, the unmanned car is currently running. There is no work in. In this case, an instruction is given to the column of the unmanned vehicle in the plan instruction table memory 204 as follows. Route confirmation level: Undetermined target node: Current node work time: 0

Further, in FIG. 28, reference numeral 211 denotes an unmanned vehicle interface, which is a wireless communication means for exchanging data between the operation control unit 200 and each unmanned vehicle. The unmanned vehicle interface 211 sends a traveling instruction from the operation control unit 200 to each unmanned vehicle, receives the state and position of each unmanned vehicle that changes from moment to moment, and the operation control unit 20.
Send to 0.

Next, the operation of the operation control unit 200 will be described. The operation control unit 200 has a plurality of CPUs and performs the following three processes in parallel. 1) Unmanned vehicle data memory 205 update 2) Planning unit 207 activation 3) Unmanned vehicle control The details of each process will be described below.

1) Update of unmanned vehicle data memory 205 The operation control unit 200 sequentially receives the state of each unmanned vehicle from the unmanned vehicle interface 211, and updates the contents of the unmanned vehicle data memory 205 based on the contents thereof. In addition, the operation control unit 2
Each time 00 updates the unmanned vehicle data memory 205, the new phase flag is set to 1 to indicate that the positional relationship between the unmanned vehicles has changed. The new phase flag is a judgment when the planning unit 207 is started again in the expectation that the next planning execution will be successful because the position of any unmanned vehicle changes after the planning unit fails in the planning unit 207. Used for. Specifically, the new phase flag is set to 1 every time the operation control unit 200 updates the contents of the unmanned vehicle data memory 205, and is set to 0 when the planning unit 207 fails to execute the plan. In addition, the planning section 2 described here
The plan execution failure due to 07 refers to the case where the planning unit 207 cannot add any new fixed route to all unmanned vehicles.

2) When the planning unit 207 start-up operation control unit 200 refers to the transfer execution table memory 201 and the unmanned vehicle data memory 205 and confirms the existence of unassigned jobs and the existence of unmanned vehicles without jobs. Based on the two data, the route determination level, the target node, and the working time are set in the plan instruction table memory 204, and the planning unit 207 is activated. The plan execution by the planning unit 207 is completed, and the data is stored in the plan result storage memory 20.
3 is stored in the operation control unit 200, the operation control unit 200 checks the contents, and if the plan is successful, the operation control data memory 206
Copy to.

The activation process of the planning unit 207 of the operation control unit 200 will be described below with reference to the flowchart shown in FIG. In this flowchart, two flags, "failure flag" and "new phase flag" are used. The failure flag indicates whether or not the plan execution is successful in the planning unit 207, where 0 means plan execution success and 1 means plan execution failure. The new phase flag indicates that the position of at least one unmanned vehicle has changed,
The new phase flag is set to 1 every time the operation control unit 200 updates the contents of the unmanned vehicle data memory 205, and to 0 when the planning unit 207 fails to execute the plan.

When the process is started, both flags are initialized (the failure flag is set to 0 and the new phase flag is set to 1) in step Sg2. In step Sg3, the unmanned vehicle data memory 205 is checked to see if there is an unmanned vehicle ready for the next operation. Here, the unmanned vehicle that can move to the next work refers to an unmanned vehicle to which an operation for the unassigned job is not assigned even though there is an unassigned job in the transport execution table memory 201. Step Sg3
When there is no unmanned vehicle that can move to the next work, the operation control unit 200 cannot activate the planning unit 207, and therefore continues to monitor the unmanned vehicle data data memory 205 until an unmanned car that can move to the next work appears. A loop (Sg3 and Sg4) will be entered.

When an unmanned vehicle ready for the next work is found in step Sg3, steps Sg5 and Sg6 are executed.
Check the failure flag and new phase flag. Here, if the failure flag is 0 or the new phase flag is 1, the planned activation (step Sg7)
However, if not, the procedure returns to step Sg4, and the unmanned vehicle data memory 20 until the new phase flag becomes 1.
We will enter a loop that continues to monitor 5.

In step Sg7, the planning instruction table memory 204 is set for each unmanned vehicle, and the planning unit 207 is activated. The settings are as follows. If there is an unassigned job in the transfer execution table memory 201, set as follows for an unmanned vehicle that can move to the next operation,
Assign a job. Route confirmation level: Undetermined purpose node: Work execution node of assigned work Work time: Work time of assigned work Transport execution table For unmanned vehicles that can move to the next work when there is no work to be assigned in the memory 201 Set as follows. Route confirmation level: undecided Objective node: Current node work time: 0 Work assignment has been completed, the route to the objective node is confirmed,
For unmanned vehicles currently heading for that destination node,
Set as follows. Route confirmation level: Confirmation to the destination node Destination node: Working time of the destination node currently working: Working time at the destination node For unmanned vehicles that have completed work at the destination node and are currently heading to the evacuation destination node , Set as follows. Route confirmation level: Confirmation destination node up to the evacuation destination node Objective node: Evacuation destination node currently working: 0

In step Sg8, the planning unit 207 executes the plan. When the plan execution by the planning unit 207 is completed, the contents of the plan storage memory 203 are checked in step Sg9 to check whether the plan execution is successful. The success of the plan execution described here means that the planning unit 20
7 indicates a case in which a confirmed route can be newly added to at least one unmanned vehicle. If the plan execution is unsuccessful, the process proceeds to step Sg10, the failure flag is set to 1, the new phase flag is set to 0, and the process proceeds to step Sg4 to start a new plan starting process. If the planned execution is successful, the process proceeds to step Sg11, and the failure flag and the new phase flag are set to 0.

In step Sg12, the fixed route and node reservation sequence of each unmanned vehicle are stored in the plan result storage memory 2
03 to the operation control data memory 206. With the update of the operation control data memory 206 in step Sh12, the series of processes for starting the planning unit 207 is completed. Since the operation control unit 200 enters the next planning unit 207 activation process, the process proceeds to step Sg3.

3) Unmanned Vehicle Control The operation control unit 200 issues an actual operation command to the unmanned vehicle based on the contents of the unmanned vehicle data memory 205 and the operation control data memory 206. This operation command is given to the unmanned vehicle via the unmanned vehicle interface 211. Operation control unit 200
There are various types of operation commands output to the unmanned vehicle depending on the configuration of the target unmanned transfer system such as the work content at the target node and the standby instruction. From the viewpoint of management, I will focus on the driving instruction processing.

The running instruction processing of the operation control unit 200 will be described below with reference to the flowchart shown in FIG. First, before describing the flowchart, various lists used in this processing will be described. Each unmanned vehicle has the following three types of node lists, and the operation control unit 200 performs traveling instruction processing based on the contents. The first is a fixed route node list in which the nodes on the fixed route of each unmanned vehicle are arranged in the order of passage. The second is a reserved node list, which is a list of nodes in the fixed route node list that are permitted to pass by the operation control unit 200, arranged in the order of permission. The third is an unreserved node list, which is a list of nodes in the definite route node list that are not permitted to pass, arranged in order in the definite route node list. From the above, the relationship between the three node lists is that the definite route node list minus the reserved node list is the unreserved node list.

Each node has a node reservation sequence. This is shown in FIG. 11 in the first embodiment.
Similar to that shown in (b), an unmanned vehicle that is scheduled to reserve the node is arranged in order for each node, and is created and output when the planning unit 207 executes the plan.

In FIG. 31, when the travel instruction process is started, the parameter CAR is set to 1 in step Sh2. Here, the parameter CAR indicates the unmanned vehicle number of the unmanned vehicle currently undergoing the travel instruction process. Next, step Sh
In step 3, the difference between the fixed route node list of the unmanned vehicle number CAR and the reserved node list of the unmanned vehicle is calculated, and step Sh4
Then, all the nodes that are confirmed to pass in the fixed route node list but are not reserved in the reserved node list are moved to the unreserved node list in the order described in the fixed route node list. Unmanned vehicle number CA in step Sh4
When the preparation of the unreserved node list for the unmanned vehicle of R is completed, the head node of the unreserved node list is taken out and this node is set in the parameter N in step Sh5.

Next, in step Sh6, the head unmanned vehicle of the node reservation sequence of the node N is compared with the unmanned vehicle of the unmanned vehicle number CAR currently being processed. Here, if they are equal, the process proceeds to step Sh7, and if they are different, the process proceeds to step Sh11. In step Sh7, the node N is added to the reservation node list of the unmanned vehicle with the unmanned vehicle number CAR. Then, in step Sh8, node N is deleted from the unreserved node list of the unmanned vehicle with the unmanned vehicle number CAR.
By these steps Sh7 and Sh8, the node N completes the reservation by the unmanned vehicle with the unmanned vehicle number CAR and is added to the reservation node list of the unmanned vehicle. In step Sh9,
Check if there is another unreserved node for the unmanned vehicle with the unmanned vehicle number CAR. If the unreserved node list is empty, the reservation work ends, and the process proceeds to step Sh11.

At step Sh10, the unmanned vehicle number CAR
Check whether or not the node reservation up to the target node is completed for the unmanned vehicle. This means that even if the route to the evacuation destination node is fixed after the destination node and the reservation to the evacuation destination node is possible,
This is because the movement is stopped once at the target node and the work is performed.
In step Sh11, a running instruction is issued from the current node to the last node in the reserved node list for the unmanned vehicle with the unmanned vehicle number CAR. In step Sh12, the unmanned vehicle with the unmanned vehicle number CAR described at the head of each node is deleted from the node reservation sequence of the node (including the current node at the time of step Sh9) passed by the traveling instruction of step Sh11. This step Sh11
And 12, the unmanned vehicle with the unmanned vehicle number CAR moves according to the contents of the reservation node list.

At step Sh13, 1 is added to the value of the unmanned vehicle number CAR in order to move the unmanned vehicle to be the subject of the traveling instruction to the unmanned vehicle having the next unmanned vehicle number. In step Sh14, it is checked whether or not a series of processes has been completed for all unmanned vehicles. The value of the incremented unmanned vehicle number CAR is compared with the total number of unmanned vehicles included in the unmanned transportation system. If the total number of unmanned vehicles is larger, the process is returned to step Sh3, and the same process is performed again for the unmanned vehicle with the unmanned vehicle number CAR obtained in step Sh13. CA
If R is larger, it means that the node reservation and the travel instruction have been completed for all the unmanned vehicles, and the process is terminated.

Next, the operation of the planning unit 207 of the second embodiment will be described, focusing on the differences from the planning unit 107 of the first embodiment. Route search unit 210: Like the route search unit 110 of the first embodiment, it is activated by the route planning unit 209 described later. In addition, the route search unit 210, when activated,
It is also possible to instruct the information about the direction and the prohibition of traffic on the specific route as the search condition. Second
The route search unit 210 of this embodiment differs from the route search unit 110 of the first embodiment in that the latter seeks an initial route (minimum cost route that does not consider competition between unmanned vehicles) for all unmanned vehicles. On the other hand, the former is that the initial route is obtained only for the unmanned vehicle whose route confirmation level in the plan instruction table memory 204 is “undecided”. This is because an unmanned vehicle whose route confirmation level in the plan instruction table memory 204 is "confirm to target node" or "confirm to save destination node" has already confirmed the route to the target node or save destination node. This is because the fixed route has a fixed condition.

Route planning unit 209: In the second embodiment, since the travel route for each unmanned vehicle is created without waiting for the completion of the work of the other unmanned vehicles, the unmanned vehicles that have completed the work are immediately processed. When the route planning unit 209 calculates a basic route (minimum cost route without a reverse direction section), it means that there are already some routes whose travels are fixed. Further, since the operation control unit 200 issues a traveling instruction to each unmanned vehicle in parallel with the process of the route planning unit 209, the route planning unit 209 obtains the current position information of each unmanned vehicle before starting the process. There is a need. From the above two points, the route planning unit 20
Before starting the process, it is necessary for 9 to initialize the fixed travel path and the current position of each unmanned vehicle.

FIG. 32 is a flowchart showing the route planning process performed by the route planning unit 209, which is obtained by adding some processing to the flowchart (FIG. 3) of the route planning unit 109 of the first embodiment. When the process starts, step SP
In 1 (a), the fixed travel route is initialized. The route confirmation level of the plan instruction table memory 204 is checked, and an unmanned vehicle having a route confirmation level of "determine to destination node" or "determine to evacuation destination node" is picked up. Next, the unmanned vehicle data memory 205 is searched to find out all the confirmed routes including the traveling direction of the picked-up unmanned vehicle. Then, with respect to these determined routes, traveling in the direction opposite to the traveling direction is temporarily prohibited and one-way travel is performed. That is, for the route search processing of the route search unit 210 in subsequent steps SP2 ′ and SP14 ′, the travelable direction is conditioned by the determined route.

Next, in step SP1 (b), the current position of each unmanned vehicle is initialized. Since the operation control of this embodiment is started irrespective of the position of each unmanned vehicle, each unmanned vehicle is not necessarily located on a node and may be moving between nodes. Therefore, the route planning unit 20
At the time point when the process of 9 moves to step SP1 (b), the node is set as the current position for the unmanned vehicle located on the node, and the unmanned vehicle moving between the nodes is passed immediately before. Set the node as the current position. Step S
When the initial settings in P1 (a) and SP1 (b) are completed, the subsequent processing is the same as the processing after step SP2 in FIG. 3 shown in the first embodiment. However, in steps SP2 ′ and SP14 ′, the initial route search by the route search unit 210 is performed only for the unmanned vehicle whose route determination level in the plan instruction table memory 204 is “undecided”.

Operation planning unit 208: The process of the operation planning unit 208 of the second embodiment is the same as the operation planning unit 108 of the first embodiment.
The process is basically the same as the process (FIGS. 16, 17, and 18). The difference between the two is that in the case of the operation planning unit 208, FIG.
Step Sf24 of 7 (detailed view is FIG. 10), step Sf26 of FIG. 18 (detailed view is FIG. 12) and step Sf
In each step of FIG. 28 (detailed view is FIG. 14), only the unmanned vehicles whose route confirmation level in the plan instruction table memory 204 is “undecided” are subject to ignition sequence adjustment, detour route search, and escape route search. Is. Further, in the second embodiment, since the once determined route is not changed, the evacuation route search (step Sf19 shown in FIG. 17).
When an evacuation route is added in, the unmanned vehicle whose route confirmation level in the plan instruction table memory 204 is "undecided" or "determined to the destination node" is unmanned after "destination node" after the destination node. For vehicles, the evacuation route will be added after the currently determined evacuation destination node.

Overall Operation Example 3: Next, the operation of the operation management control device 202 having the above configuration will be described. As described above, in the second embodiment, the operation control unit 200 sequentially assigns a new job from an unmanned vehicle with no hands available, without waiting for the completion of the operation of another unmanned vehicle. Therefore, the following situation is set as the start point of the operation example. As shown in FIG. 33 (a), the unmanned vehicle # 1 has just completed its assigned work, and is waiting at the node 2. The unmanned vehicle # 2 is traveling between the nodes 5 and 4 to carry out the loading work (working time is 35 seconds) at the node 3, and the unmanned vehicle # 3 is loading work at the node 9 (working time is 25 seconds). Suppose that node 7 is on the verge of departure.

The operation control unit 200 monitors the state of the unmanned vehicle at regular intervals and writes the above-mentioned state of each unmanned vehicle in the unmanned vehicle data memory 205. Since the operation control unit 200 repeats the planning unit 207 activation process shown in FIG. 30 in parallel with the updating of the unmanned vehicle data memory 205, the planning unit 207 is activated accordingly.

When the operation control unit 200 confirms the presence of the waiting unmanned vehicle (unmanned vehicle # 1), it retrieves one job from the jobs stored in the transport execution table memory 201 and sets it in the unmanned vehicle # 1. assign. Here, it is assumed that the loading work (working time is 30 seconds) at the node 9 is assigned to the unmanned vehicle # 1. Since the destination nodes and the routes to the unmanned vehicles # 2 and # 3 have already been determined, the contents of the plan instruction table memory 204 are as shown in FIG.

When the plan instruction table memory 204 is set, the planning unit 207 starts the plan execution. First, the route planning unit 209 initializes the fixed travel route before creating the basic route (step SP1 shown in FIG. 32).
(See (a)). The confirmed travel route of the unmanned vehicle # 2 is the node 5 → 4 → 3 in the order of passing nodes, and therefore the movement of the node 3 → 4 → 5, which goes in the opposite direction, is prohibited. Similarly, the movement of nodes 9 → 8 → 7, which runs in the opposite direction to the fixed route of unmanned vehicle # 3, is also prohibited.

Next, the current position of the unmanned vehicle is initialized (see step SP1 (b) shown in FIG. 32). Drone #
Since 1 is waiting in node 2, its current position is set to node 2. Since the unmanned vehicle # 2 is traveling between the node 5 and the node 4, its current position is set to the node 5 which has just passed. Since the unmanned vehicle # 3 is stopped at the node 7, its current position is set to the node 7.
After the above initial setting is completed, the route planning unit 209 performs the same processing as the route planning unit 109 described in the first embodiment to search for a basic route (minimum cost route with no backward period) (see FIG. 32). (Refer to the processing after step SP2 ′ shown). However, in steps SP2 ′ and SP14 ′, the target of the process for obtaining the traveling route is only the unmanned vehicle whose route confirmation level is “undecided” in the plan instruction table memory 204. As a result, the basic route of the unmanned vehicle # 1 is calculated as node 2 → 1 → 6 → 7 → 8 → 9. Further, the unmanned vehicles # 2 and # 3 have the current fixed travel route as the basic route. When the basic route search of the route planning unit 209 is completed, the operation planning unit 208 then makes an operation plan. Here, the evacuation route from the node 9 to the node 10 is added to the unmanned vehicle # 3.

When the plan execution is completed, the fixed route of each unmanned vehicle becomes as shown in FIG. 34 (a), and the planning unit 207 makes the node reservation sequence shown in FIG. 34 (b) and FIG.
The fixed route node list shown in (c) is stored in the plan result storage memory 203. When the operation control unit 200 confirms the success of the plan execution, it copies the node reservation sequence and the confirmed node list to the operation control data memory 206.

In parallel with the start-up process of the planning unit 207 described above, the operation control unit 200 repeats the traveling instruction process shown in FIG. 31 with reference to the operation control data memory 206. Therefore, when the operation control data memory 206 is updated by the processing of FIG. 30, the content is immediately reflected in the running instruction to each unmanned vehicle. First, all the node strings in the fixed route node list of the unmanned vehicle # 1 are moved to the unreserved node list of the unmanned vehicle.

The head node (node 2) of the unreserved node list of unmanned vehicle # 1 is taken out and it is determined whether the head unmanned vehicle of the node reservation sequence of node 2 is unmanned vehicle # 1. In FIG. 34 (b), since the unmanned vehicle # 1 is at the head of the node reservation sequence of the node 2, node 2 is entered in the reservation node list of the unmanned vehicle # 1 from the top of the unreserved node list of the unmanned car. delete. After this, node 1
For 6 and 6, the same process as in node 2 is performed. As a result, nodes 7, 8, and 9 are arranged in the unreserved node list of unmanned vehicle # 1, and nodes 2, 1, and 6 are arranged in the reserved node list of the unmanned vehicle.

The operation control unit 200, for the unmanned vehicle # 1, outputs the nodes 2, 1 and 2 listed in the reserved node list.
A travel instruction from node 2 to node 6 is given along line 6. After that, the unmanned vehicle # 1 is deleted from the head of each node reservation sequence of the nodes (the nodes 2 and 1 in this case) through which the unmanned vehicle # 1 has passed.

Next, the operation control unit 200 performs the same process as the unmanned vehicle # 1 on the unmanned vehicle # 2 to move the unmanned vehicle # 2 from the node 5 to the node 3. This makes node 4
Unmanned vehicle # 2 from the beginning of the node reservation sequence for 5 and 5
Is deleted. When the processing of the unmanned vehicle # 2 ends, the processing target moves to the unmanned vehicle # 3, and the operation control unit 200 transfers the unmanned vehicle # 3 from the node 7 to the node 9 again by the same processing as the unmanned vehicles # 1 and # 2. To move. As a result, the unmanned vehicle # 3 is deleted from the beginning of the node reservation sequence of the nodes 7 and 8. In addition, driverless car # 3 is node 1 here.
Although the route is fixed up to 0, only node 9 is reserved.
The reason why the unmanned vehicle # 3 cannot be moved is that the unmanned vehicle # 3 must be loaded at the node 9.

Since the processing has been completed for all the unmanned vehicles as described above, the traveling instruction processing by the operation control unit 200 is once ended. Since the unmanned vehicles # 2 and # 3 have reached the target node due to the above movement, the operation control unit 200 issues a work instruction to both unmanned vehicles. When the work instruction to the unmanned vehicles # 2 and # 3 is completed, the unmanned vehicle control function of the operation control unit 200 shifts to the traveling instruction process again.

Since the unmanned vehicle # 3 was described at the beginning of the node reservation sequence of the node 7 in the previous travel instruction processing to the unmanned vehicle # 1, the unmanned vehicle # 1 adds the node 7 to the reservation node list. However, since the unmanned vehicle # 3 moved to the node 9 in the traveling instruction processing of the unmanned vehicle # 3 performed thereafter, the nodes 7 and 8
The unmanned vehicle # 3 has been deleted from the beginning of the node reservation sequence.

As a result, in this travel instruction process, the unmanned vehicle # 1 can add the node 7 to the reserved node list. The node 8 is also added to the reserved node list of the unmanned vehicle # 1 by the same process. However, since the current node of the unmanned vehicle # 3 is the node 9 and therefore the unmanned vehicle # 3 has not been deleted from the beginning of the node reservation sequence of the node 9, the node 9 is added to the reserved node list of the unmanned vehicle # 1. It is not possible. Driverless car # 1 is from node 6 to node 8
And deletes the unmanned vehicle # 1 from the head of the node reservation sequence of both nodes.

Further, after the traveling instruction processing of the unmanned vehicle # 2, the traveling instruction processing of the unmanned vehicle # 3 is started. Driverless car # 3
Although the travel route to the evacuation destination node 10 has been determined by the planning unit 207, since the work instruction has been set in the node 9, only the node 9 can be reserved in the reserved node list in the previous process, and the unreserved node list Node 10 was left in the. Therefore, node 10
To the reserved node list and node 9 for driverless vehicle # 3
From the node to the node 10 is instructed. As a result, the unmanned vehicle # 3 is deleted from the beginning of the node reservation sequence of the node 9.

When the unmanned vehicle # 1 travels again, the unmanned vehicle # 3 is deleted from the beginning of the node reservation sequence of the node 9, so the node 9 is added to the reservation node list of the unmanned vehicle # 1. Can be added. Now that the unreserved node list for unmanned vehicle # 1 is empty, unmanned vehicle # 1 moves from node 8 to node 9 and unmanned vehicle # 1 is deleted from the beginning of the node reservation sequence for node 8. Through the above processing, each unmanned vehicle can reach the target node and complete the given work.

Overall Operation Example 4: In the overall operation example 3 described above, an example in which the planning by the planning unit 207 succeeds in the first execution is shown. Therefore, in this operation example, the planning unit 207
An example of processing of the operation control unit 200 in the case where the plan according to is unsuccessful is shown. The following situation is set as the start time of the operation example. As shown in FIG. 35 (a), unmanned vehicle # 1
Has just completed its previously assigned job and is waiting at node 2. The unmanned vehicle # 2 is traveling between the nodes 5 and 4 in order to carry out the loading work (working time is 35 seconds) at the node 3, and the unmanned vehicle # 3
Is supposed to be passing through the node 8 in order to unload the node 7 (working time is 28 seconds). The flow of the entire process is the same as that of the first operation example described above. The operation control unit 200 confirms the existence of the waiting unmanned vehicle (unmanned vehicle # 1), extracts one job from the jobs stored in the transfer execution table memory 201, and assigns it to the unmanned vehicle # 1. It is assumed here that the unmanned vehicle # 1 is assigned the loading work (working time is 30 seconds) at the node 9.

Since the destination nodes and the routes to the unmanned vehicles # 2 and # 3 have already been determined, the contents of the plan instruction table memory 204 are as shown in FIG. When the plan instruction table memory 204 is set, the planning unit 207 starts the plan execution. In the route planning unit 209, the initial setting of the fixed running path is performed, and the current fixed running paths of the unmanned vehicles # 2 and # 3 (the running path from the node 5 to the node 3 and the running path from the node 8 to the node 7) are set. Traveling in the opposite direction is prohibited. As described above, in the second embodiment, the once determined travel route is not the target of route planning by the route planning unit 209 (more accurately, the route searching unit 210 called in the route planning unit 209). So unmanned vehicles # 2 and # 3
The fixed route of will not be changed.

For this reason, all routes along which the unmanned vehicle # 1 travels from the node 2 to the node 9 which is the target node are prohibited from travelling, and the planning unit 207 sets a new fixed route (unmanned vehicle # 2).
Since the travel routes of # and # 3 have already been determined, in this case, the determined route for unmanned vehicle # 1 cannot be obtained. That is, the plan execution by the planning unit 207 ends in failure. Since the plan was unsuccessful, the fixed route of each unmanned vehicle did not change as compared with that before the start of the plan, and remains as shown in FIG. 35 (a). Therefore, the operation control unit 200 operates from the plan result storage memory 203 to the operation control data memory 206.
The plan reservation result is not copied to the node reservation sequence and the confirmed node list in the operation control data memory 206, and the contents before the plan activation are saved.

Since the operation control unit 200 failed in the planning for the unmanned vehicle # 1, it does not issue a driving instruction to the unmanned vehicles # 2 and # 3 and follows the fixed traveling path before the planning. And issue a driving instruction. As a result, the unmanned vehicles # 2 and # 3 move to their destination nodes. When the unmanned vehicles # 2 and # 3 move, the operation control unit 20
0 updates the unmanned vehicle data memory 205, and again the planning unit 2
Start the plan according to 07.

In this plan, since the unmanned vehicles # 2 and # 3 do not have a fixed travel route, the reverse direction section is set in the initial setting of the fixed route of the route planning unit 209 (see step SP1 (a) shown in FIG. 32). Is not set, the plan succeeds,
A determined route as shown in FIG. 36A is required for each unmanned vehicle. The planning unit 207 stores the node reservation sequence shown in FIG. 36B and the fixed route node list shown in FIG. 36C in the planning result storage memory 203. The operation control unit 200 copies the node reservation sequence and the confirmed node list to the operation control data memory 206.
When the unmanned vehicle control function of the operation control unit 200 is included in the traveling instruction process (FIG. 31), all the node strings in the fixed route node list of the unmanned vehicle # 1 are moved to the unreserved node list of the unmanned vehicle.

The head node (node 2) of the unreserved node list of the unmanned vehicle # 1 is taken out and entered in the reserved node list of the unmanned vehicle # 1 and deleted from the head of the unreserved node list of the unmanned vehicle. Similarly, the nodes 1 and 6 in the unreserved node list of the unmanned vehicle # 1 are entered in the reserved node list of the unmanned vehicle and deleted from the unreserved node list. As a result, in the unreserved node list of unmanned vehicle # 1, node 7,
8 and 9 are node 2 in the reservation node list of the unmanned vehicle,
1 and 6 are lined up.

The operation control unit 200, for the unmanned vehicle # 1, outputs the nodes 2, 1 and 2 listed in the reserved node list.
A travel instruction from node 2 to node 6 is given along line 6. After that, the unmanned vehicle # 1 is deleted from the head of each node reservation sequence of the nodes (the nodes 2 and 1 in this case) through which the unmanned vehicle # 1 has passed. Next, the processing target moves to the unmanned vehicle # 3 through the traveling instruction processing of the unmanned vehicle # 2. The operation control unit 200 evacuates the unmanned vehicle # 3 from the node 7 to the node 4 by the same processing as the unmanned vehicle # 1. As a result, the unmanned vehicle # 3 is deleted from the beginning of the node reservation sequence of the nodes 7 and 8.

When the unmanned vehicle control function of the operation control unit 200 shifts to the traveling instruction processing again, the unmanned vehicle # 1 can add the nodes 7, 8 and 9 to the reserved node list. The unmanned vehicle # 1 moves from the node 6 to the node 9, and deletes the unmanned vehicle # 1 from the head of the node reservation sequence of the nodes 6, 7 and 8.

Through the above processing, each unmanned vehicle can reach the target node and complete the given work.
In addition, in the operation examples 3 and 4 of the whole operation, the operation control unit 200 immediately assigns the work from the unmanned unmanned vehicle without waiting for the completion of the work of the other unmanned unmanned vehicles. As soon as the work is finished, the following work is actually assigned to both unmanned vehicles, but the description about it is omitted here to focus on the operation of unmanned vehicle # 1.

Although the embodiments of the inventions described in claims 1 to 3 have been described in detail with reference to the drawings, the concrete structure is not limited to this embodiment, and the inventions described in claims 1 to 3 are not limited thereto. Even if there is a design change or the like within the scope of the invention, it is included in the invention.

[0125]

As described above, according to the first and second aspects.
According to the invention described above, before the unmanned vehicle starts to move, it is possible to obtain the traveling routes and the traveling order of all the unmanned vehicles in advance in consideration of the interference between the unmanned vehicles. Even if there is a possibility of frequent interference on the road, it is possible to move smoothly, and thus it is possible to improve the transport efficiency of the unmanned vehicle. According to the third aspect of the invention, the operation control means periodically monitors the state of each unmanned vehicle, and when an unmanned vehicle that has completed the work occurs, a new work is stored in the plan instruction storage means of the unmanned vehicle. To set. After that, the first and second means perform the travel route search in consideration of the states of other unmanned vehicles. Therefore, under the condition of each unmanned vehicle that changes from moment to moment, it is possible to immediately give a new work and operation instruction to the unmanned vehicle that has completed the work, and thus it is possible to improve the transportation efficiency of the unmanned vehicle. Is obtained.

[Brief description of drawings]

FIG. 1 is a block diagram of an operation management control device according to an embodiment of the present invention.

FIG. 2 is a diagram showing a tree used for path planning.

FIG. 3 is a flowchart showing a route planning process of a route planning unit 109.

FIG. 4 is an operation diagram showing an operation example of an operation plan process.

5 is a Petri net diagram modeling the operation diagram of FIG. 4. FIG.

FIG. 6 is a flowchart showing an evacuation route search process of the operation planning unit 108.

FIG. 7 is an operation diagram showing an operation example of an evacuation route search process.

8 is a flowchart showing a deadlock grasping process of the operation planning unit 108. FIG.

FIG. 9 is an operation diagram showing an operation example of deadlock grasping processing.

10 is a flowchart showing a firing order adjustment process of the operation planning unit 108. FIG.

FIG. 11 is an operation diagram (a) and a node reservation sequence (b) showing an operation example of a firing order adjustment process.

12 is a flowchart showing a bypass route search process of the operation planning unit 108. FIG.

FIG. 13 is an operation diagram showing an operation example of detour route search processing.

FIG. 14 is a flowchart showing a shunt route search process of the operation planning unit.

FIG. 15 is an operation diagram showing an operation example of a refuge route search process.

16 is a flowchart showing an operation planning process (main process) of the operation planning unit 108. FIG.

FIG. 17 is a flowchart showing an operation planning process (main process).

FIG. 18 is a flowchart showing an operation planning process (main process).

19 is a Petri net diagram showing an operation example of the operation planning unit 108. FIG.

20 is a Petri net diagram showing an operation example of the operation planning unit 108. FIG.

FIG. 21 is a node reservation sequence (a) and an operation plan showing the operation result of the same operation example.

FIG. 22 shows an initial setting (a), a basic route (b), and a final route (c) in the operation example 1 of the operation management control device 102.

FIG. 23 is an operation diagram showing an initial route (a), a basic route (b), and a final route (c) in the same operation example 1.

FIG. 24 is an operation plan diagram in the same operation example 1.

FIG. 25 shows a basic route (a) and a final route (b) in the operation example 2 of the operation management control device 102.

FIG. 26 is an operation diagram showing an initial route (a), a basic route (b), and a final route (c) in the second operation example.

FIG. 27 is an operation plan diagram in the second operation example.

FIG. 28 is a block diagram of an operation management control device according to a second embodiment of the present invention.

FIG. 29 is an explanatory diagram showing an example of a plan instruction table memory 204.

FIG. 30 is a flowchart showing a planning unit starting process of the operation control unit 200.

31 is a flowchart showing a travel instruction process of the operation control unit 200. FIG.

FIG. 32 is a flowchart showing a route planning process of the route planning unit 209.

FIG. 33 is an operation diagram (a) showing the initial setting in the overall operation example 3 and an explanatory diagram (b) showing the contents of the plan instruction table memory 204.

FIG. 34 is an operation diagram (a) after a route is determined, a node reservation sequence (b), and a determined route node list (c) in the overall operation example 3.

FIG. 35 is an operation diagram (a) showing the initial setting in the overall operation example 4 and an explanatory diagram (b) showing the contents of the plan instruction table memory 204.

FIG. 36 is an operation diagram (a) after a route is determined, a node reservation sequence (b), and a determined route node list (c) in the overall operation example 4.

FIG. 37 is a system configuration diagram of an unmanned conveyance system.

FIG. 38 is a diagram showing costs on the road 101 in the conventional example (FIG. 37).

FIG. 39 is an operation diagram showing a travel route in a conventional example.

FIG. 40 is an operation diagram showing a travel route in a conventional example.

FIG. 41 is an operation diagram showing a travel route in a conventional example.

[Explanation of symbols]

101 ……………… Conveyor path 102, 202 ... Operation management control device 103, 206 ... Operation control data memory 104 ……………… Transport instruction table memory 105, 205 ... unmanned vehicle data memory 106 ……………… Runway data memory 107, 207 ... Planning Department 108, 208 ... Operation planning section 109, 209 ... Path Planning Department 110, 210 ... Route search unit 200 ……………… Operation control unit 201 ……………… Transport execution table memory 203 ……………… Plan result storage memory 204 ……………… Planning instruction table memory 211 ……………… Unmanned vehicle interface

   ─────────────────────────────────────────────────── ─── Continued front page       (56) References JP-A-5-165520 (JP, A)                 JP-A-2-77808 (JP, A)                 JP-A-4-23108 (JP, A)                 JP-A-4-81905 (JP, A)

Claims (3)

(57) [Claims] 1. An operation management control device for controlling the operation of a plurality of unmanned vehicles traveling on a traveling path consisting of a plurality of nodes at a stop position and a connecting path connecting the nodes, and each unmanned vehicle is connected to the same. First means for searching a traveling route of each unmanned vehicle so as not to travel in opposite directions on the road, and time of each unmanned vehicle based on the traveling route of each unmanned vehicle searched by the first means If the unmovable state of any unmanned vehicle is detected by simulating various movements, the unmovable state of the unmanned vehicle is canceled by any of the methods of changing the order of node passage, detour route search, and escape route search. Means, wherein the first means comprises a starting node and a target node for each unmanned vehicle.
Find all the routes that connect the routes, find the cost of each route,
If multiple unmanned vehicles are competing in the opposite direction,
The cost of this backward section is added by the number of times
The unmanned vehicles are sequentially selected in descending order of cost
However, one-way traffic of this unmanned
As a feature, the route of all unmanned vehicles is recalculated.
That operation management control device. 2. An operation management control method for controlling the operation of a plurality of unmanned vehicles traveling on a traveling path consisting of a plurality of nodes at a stop position and a connection path connecting the nodes, and each unmanned vehicle is connected to the same. A first step of searching a traveling route of each unmanned vehicle so as not to travel in opposite directions on the road, and a temporal movement of each unmanned vehicle based on the traveling route obtained in the first step are investigated. If the unavailability of the unmanned vehicle is detected, a second step of adding a shunt route to the route of the unmanned vehicle that has already finished traveling, and an unmanned vehicle if the uninitiable state cannot be resolved in the second step A third step of changing the traveling order of the vehicle, a fourth step of adding a detour route to the route of the unmanned vehicle when the unprohibited state cannot be resolved in the third step, and the fourth step. Anda fifth step of adding the retracting path in the path of the unmanned vehicle if the row impossible can not be solved, in the first step, and starting node of each unmanned vehicle
Find all the routes connecting the target nodes, and the cost of each route
And multiple unmanned vehicles are competing in the opposite direction.
If you are competing for the cost of this backward section
Add up the number of times and place unmanned vehicles in descending order of cost
Sequentially select the reverse running section of this unmanned vehicle
As a one-way street, it is necessary to re-acquire routes for all unmanned vehicles.
A characteristic operation management control method. 3. The operation management control device according to claim 1, wherein a plan instruction storage unit that stores the determined travel route of the plurality of unmanned vehicles and given work contents at a predetermined time, and the state of each unmanned vehicle And a first process for monitoring the operation, and each time an unmanned vehicle that has completed a given work is generated, a new work is set in the plan instruction storage means, and the first means and the second means are activated. By performing a second process for searching a travel route by parallel and a third process for giving an operation instruction to each unmanned vehicle based on the result of the search in parallel and periodically,
An operation management control device comprising an operation control means for controlling the operation of the plurality of unmanned vehicles.