Route generation device, route generation method, and program

Abstract

This contributes to planning package collection routes that reflect the constantly changing weight of the packages. [Solution] The route generation device comprises one or more processors and generates a route that includes one or more patrol groups, each of which is a collection device that collects cargo up to or less than the maximum load capacity, and each collection device collects one or more collection points that it patrols to collect cargo. The one or more processors collect measured weights of cargo collected at each of the multiple collection points, and select a first collection point other than the collection points included in the patrol route, and a second collection point other than the collection points included in the patrol route, such that the cumulative sum of the measured values ​​of the first collection point and the measured values ​​of the second collection point is less than or equal to the maximum cumulative amount, thereby generating one or more patrol groups, and is configured to generate a patrol route that is a collection of the one or more generated patrol groups, each of which contains only one of the multiple collection points.

Description

Technical Field

[0001] The present disclosure relates to a route generation device, a route generation method, and a program.

Background Art

[0002] When a vehicle for transporting goods efficiently circulates through a plurality of locations where goods are accumulated to collect the goods, the efficiency of logistics can be improved. For example, Patent Document 1 discloses a method for generating a route for collecting garbage based on the weight (mass) of the garbage collected at a plurality of garbage collection sites.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Each disclosure of the above prior art documents is incorporated herein by reference. The following analysis was made by the present inventor.

[0005] Here, at a plurality of garbage collection sites (goods collection sites), the weight of the collected garbage (goods) changes moment by moment, for example, on a weekly or daily basis. However, with the method disclosed in Citation Document 1, it is difficult to generate a goods collection route that reflects the moment-by-moment changing weight of the goods.

[0006] An object of the present disclosure is to contribute to the planning of a goods collection route that reflects the moment-by-moment changing weight of the goods in view of the above problems.

Means for Solving the Problems

[0007] In a first aspect of this disclosure, a route generating device is provided which comprises one or more processors and generates a route that includes one or more patrol groups, each of which is a collection device that collects packages up to or less than a maximum load capacity, and each collection device collects one or more packages that patrol to collect packages. The one or more processors are configured to collect measured weights of the packages collected at each of the multiple collection locations, and to generate one or more patrol groups by selecting a first collection location other than the collection locations included in the patrol route and a second collection location other than the first collection location included in the patrol route such that the cumulative sum of the measured weights of the first collection location and the measured weights of the second collection location is less than or equal to the maximum cumulative amount, and to generate a patrol route which is a collection of the one or more generated patrol groups that includes exactly one of each of the multiple collection locations.

[0008] A second aspect of this disclosure provides a route generation method for generating a route that includes one or more patrol groups, each of which a plurality of collection devices that collect cargo up to or less than a maximum load capacity have one or more collection points to patrol in order to collect cargo. The route generation method includes the steps of: collecting measured weights of the cargo collected at each of the plurality of collection points; generating one or more patrol groups by selecting a first collection point other than the collection points included in the patrol route, and a second collection point other than the collection points included in the patrol route, such that the cumulative sum of the measured values ​​of the first collection point and the measured values ​​of the second collection point is less than or equal to the maximum cumulative amount; and generating a patrol route which is a collection of the one or more generated patrol groups, each of which has only one of the plurality of collection points.

[0009] In a third aspect of this disclosure, a route generating device is provided, comprising one or more processors, for a plurality of collection devices that collect packages up to or less than a maximum load capacity, each generating a route that includes one or more patrol groups, each including one or more collection points on which to patrol to collect packages, wherein the one or more processors are instructed to execute a process of collecting measured weights of the packages collected at each of the plurality of collection points; a process of selecting a first collection point other than the collection points included in the patrol route, and a second collection point other than the first collection point included in the patrol route, such that the cumulative sum of the measured values ​​of the first collection point and the measured values ​​of the second collection point is less than or equal to the maximum cumulative amount, to generate one or more patrol groups; and a process of generating a patrol route which is a collection of the one or more generated patrol groups, each including exactly one of the plurality of collection points. This program can be recorded on a computer-readable storage medium. The storage medium may be non-transitory, such as semiconductor memory, hard disks, magnetic recording media, or optical recording media. This disclosure can be embodied as a computer program product. [Effects of the Invention]

[0010] Each perspective of this disclosure can contribute to planning package collection routes that reflect the constantly changing weight of packages. [Brief explanation of the drawing]

[0011] [Figure 1] Figure 1 is a diagram illustrating a correspondence between the route generation device for the first viewpoint, the collection system according to the embodiment, and the route generation device for the first viewpoint. [Figure 2] Figure 2 illustrates an example of the arrangement of collection points within the collection area targeted for creating a collection route using the collection system shown in Figure 1. [Figure 3]Figure 3 illustrates one configuration of a collection system that generates route planning information indicating routes for collecting packages gathered at multiple collection points located within the collection area shown in Figure 2. [Figure 4] Figure 4 is a flowchart illustrating an example of the process of creating route planning information using the route generation device shown in Figure 3 and other figures. [Figure 5] Figure 5 illustrates an example of an information table stored in the database during the process shown in Figure 4. [Figure 6A] Figure 6A illustrates an example of a group that uses the first collection point as the reference collection point. [Figure 6B] Figure 6B illustrates an example of a group that uses the second collection point as the base collection point. [Figure 6C] Figure 6C illustrates an example of a group that uses the third collection point as the base collection point. [Figure 7A] Figure 7A illustrates an example of an information table obtained when the processor first performs the processing shown in Figure 4. [Figure 7B] Figure 7B illustrates an example of an information table obtained by performing a sorting process based on weight on the information table shown in Figure 7A. [Figure 8A] Figure 8A illustrates an example of an information table obtained when the processor performs the processing shown in Figure 4 for the second time. [Figure 8B] Figure 8B illustrates an example of an information table obtained by performing a sorting process based on weight on the information table shown in Figure 8A. [Figure 9A] Figure 9A illustrates an example of a confirmed table obtained when the processor performs the processing shown in Figure 4 for the third time. [Figure 9B] Figure 9B illustrates an example of an information table obtained by performing a sorting process based on weight on the information table shown in Figure 9A. [Figure 10] Figure 10 illustrates an example of a confirmed group obtained as a result of the route planning information creation process by the route generation device shown in Figure 3, etc. [Figure 11] FIG. 11 is a sequence diagram illustrating an operation of the collection system shown in FIG. 3 and the like. Embodiments for Carrying Out the Invention

[0012] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. However, the present disclosure is not limited to the embodiments described below. Also, in each drawing, the same or corresponding elements are appropriately assigned the same reference numerals, and the same or corresponding processes and communications are also appropriately assigned the same reference numerals. Further, it should be noted that the drawings are schematic, and the quantities and positional relationships of each element may be different from reality. Also, the positional relationships and numbers of each element may be different between the drawings. Also, the connection lines between the blocks in the drawings and the like referred to in the following description include both bidirectional and unidirectional. The one-way arrow schematically shows the flow of the main signal (data) and does not exclude bidirectionality. Also, in the following description, information and data are not strictly distinguished. Further, for convenience of description, "less than or equal to" and "less than" are distinguished for the threshold value, and "greater than or equal to" and "greater than (including "longer", "heavier", etc.)" are distinguished, but there is no substantial difference between "less than or equal to" and "less than", and between "greater than or equal to" and "greater than".

[0013] First, the relationship between the route generation device from the first perspective and the collection system according to the present disclosure will be described. FIG. 1 is a diagram illustrating a correspondence relationship between the route generation device from the first perspective, the collection system 2 according to the embodiment, and the route generation device 3 from the first perspective. FIG. 2 is a diagram illustrating an example of the arrangement of the collection points 120A to 120J in the collection range 12 that is the target of creating the luggage collection route by the collection system 2 shown in FIG. 1. Note that the numbers shown for each collection point 120 in FIG. 2 indicate the weight of the garbage (luggage) collected at each collection point 120 in kg.

[0014] FIG. 3 is a diagram illustrating a configuration of a collection system 2 that generates route planning information indicating a route for collecting luggage collected at a plurality of collection points 120 existing within the collection range 12 shown in FIG. 2. The correspondence between the route generation device 3 from the first perspective and the collection system 2 is as shown in FIG. 1. That is, as shown in FIG. 1, the collection system 2 and the route generation device 3 are in a relationship in which the collection system 2 includes the route generation device 3.

[0015] For the purpose of concretizing and clarifying the description, the following matters are given as specific examples. First, as shown in FIG. 2, ten collection points 120A to 120J are scattered within the collection range 12. Next, garbage is carried into each of the collection points 120A to 120J as luggage from households and restaurants. The route generation device 3 generates a route (tour route) including one or more groups (tour groups) including one or more of the collection points 120A to 120J that each of the cleaning vehicles 26-1 to 26-m tours. Each of the cleaning vehicles (transport devices) 26-1 to 26-m with a maximum load capacity of 1,000 kg tours one or more of the collection points 120A to 120J according to the route to collect garbage. The positions of the collection points 120A to 120J can be specified by, for example, latitude and longitude. Hereinafter, unless particularly necessary, the phrase "each" in the description is omitted for simplification. Also, when indicating any of a plurality of possible components without specifying them, such as the collection points 120A to 120J, the subscript of the reference numeral may be omitted and it may be simply described as the collection point 120 or the like.

[0016] Next, the configuration of the collection system 2 will be described. As shown in FIG. 3, the collection system 2 includes a route generation device 3, collection point devices 20A to 20J, an input / output device 22, and cleaning vehicles (collection devices) 26-1 to 26-m. The input / output device 22 includes an output device (not shown) such as a display and an input device (not shown) such as a keyboard and a mouse, outputs information input to the input device by an operator of the collection system 2 to the route generation device 3, and outputs route planning information and the like output from the route generation device 3 to the operator via the output device.

[0017] Collection station devices 20A to 20J are installed in collection stations 120A to 120J and are equipped with a transmitter 200, an image / weight processing device 202, a weight sensor 204, and a camera 206. They are connected to the route generation device 3 via communication lines 210A to 210J, such as a mobile phone line or a wired telephone line. The cleaning vehicles 26-1 to 26-m are equipped with route display devices 28-1 to 28-m. The route display devices 28-1 to 28-J are equipped with a display 280, a receiver 282, and a GPS (Global Positioning System) device 284. The route display devices 28-1 to 28-m are connected to the route generation device 3 via communication lines 24-1 to 24-m, such as a mobile phone line. Note that the configuration of the collection system 2 shown in Figure 2 is illustrative, and the collection system 2 may further include configurations other than those shown in Figure 3.

[0018] Collection points 120A to 120J and collection point devices 20A to 20J are pre-set with identification information A to J, including location information, which can uniquely identify them, before the collection system 2 is activated. The cameras 206 of the collection point devices 20A to 20J are, for example, positioned near the collection points 120A to 120J in locations suitable for their imaging. The cameras 206, for example, image the waste collection containers and their surroundings in the collection points 120A to 120J, generate image signals showing these images, and output them to the image / weight processing device 202 (weight measuring device). The weight sensor 204 is, for example, positioned between the waste collection containers that hold the waste and the ground or floor, and detects the weight of the waste contained in the waste collection containers. The weight sensor 204 outputs a weight signal indicating the measured weight of the garbage (package) (hereinafter simply referred to as "garbage weight") to the image / weight processing device 202 via the communication lines 210A to 210J.

[0019] The image / weight processing device 202 processes the image signal input from the camera 206, generates image information representing the images of collection points 120A to 120J, and outputs it to the transmission device 200. The image / weight processing device 202 also processes the weight signal value input from the weight sensor 204, generates weight information representing the weight of the waste, and outputs it to the transmission device 200. The transmission devices 200 of collection point devices 20A to 20J add identification information A to J for collection point devices 20A to 20J to the image information and weight information input from the image / weight processing device 202, and transmit it to the route generation device 3 via communication lines 210A to 210J, respectively.

[0020] In the route display devices 28-1 to 28-m, the GPS device 284 detects the positions (latitude and longitude) of the garbage trucks 26-1 to 26-m and outputs them to the display 280. The receiving device 282 receives the route planning information generated by the route generation device 3 and image information of collection points 120A to 120J and outputs them to the display 280. The display 280 overlays the route planning information and image information received by the receiving device 282, the image information showing collection points 120A to 120J within the collection range 12, and the positions of the garbage trucks 26-1 to 26-m detected by the GPS device 284 and displays them on its screen (not shown). Furthermore, the display 280 displays the image information of collection points 120A to 120J on its screen.

[0021] The collection system 2 uses these components to generate route planning information, for example using Dijkstra's algorithm, which indicates the order in which the garbage trucks 26-1 to 26-m should visit each of the collection points 120A to 120J in order to efficiently collect the garbage accumulated at those points. The workers in the garbage trucks 26-1 to 26-m visit one or more of the collection points 120A to 120J according to the route planning information displayed on the display 280 of the route display device 28 and collect the garbage.

[0022] The route generation device 3 comprises one or more processors 300, a main memory 302, an auxiliary memory 304, a user interface (IF) device 306, a database (DB) 308, an input IF device 310, and a communication device 312, all connected to each other via buses and signal lines to send and receive data and information. In other words, the route generation device 3 comprises components of a computer capable of executing programs. Using these components, the route generation device 3 processes the weight information of the garbage accumulated in collection points 120A to 120J, which is input from the collection point devices 20A to 20J, and location information indicating the location of collection points 120A to 120J, and generates route planning information for the garbage trucks 26-1 to 26-m to efficiently collect the garbage accumulated in collection points 120A to 120J, as described above.

[0023] Route generation device 3 processes identification information, image information, and weight information input from collection station devices 20A to 20J of collection stations 120A to 120J, along with location information indicating the locations of collection stations 120A to 120J within the collection range 12 shown in Figure 2, to generate route planning information. Route generation device 3 outputs the generated route planning information to route display devices 28-1 to 28-m installed on the garbage trucks 26-1 to 26-m via communication lines 24-1 to 24-m. Route display devices 28-1 to 28-m receive the route planning information from route generation device 3, display the received route planning information on the display 280 of the route display devices 28-1 to 28-m, and show it to the workers riding in the garbage trucks 26-1 to 26-m. The workers will drive the sanitation vehicle 26-1 to 26-m according to the displayed route plan information, patrol collection points 120A to 120J, and collect the waste accumulated there.

[0024] The functions of the root generation device 3 can be realized not only by dedicated hardware, or a combination of dedicated hardware and its firmware, but also by a root generation device 3 having components of a general-purpose computer executing one or more programs. In the root generation device 3, an OS (Operating System; not shown) is executed, which mediates between the hardware of the root generation device 3 and the programs executed by the root generation device 3, such as Windows®, UNIX®, or TRON (The Real-time Operating system Nucleus). The programs that perform the various functions of the root generation device 3 run on the OS. Note that the root generation device 3 does not necessarily need to have components of a general-purpose computer; it may also have components of an embedded computer.

[0025] Next, the hardware operation of each component of the root generation device 3 will be described. The processor 300 includes one or more CPUs (Central Processing Units), or at least two combinations of one or more CPUs, one or more DSPs (Digital Signal Processors), and one or more GPUs (Graphics Processing Units). The processor 300 executes instructions contained in one or more programs stored in at least one of the main memory 302 and the auxiliary memory 304. The main memory 302 includes storage devices such as one or more RAMs (Random Access Memory) and one or more ROMs (Read Only Memory), and temporarily stores one or more programs executed by the root generation device 3, as well as information and data required for the execution of the programs.

[0026] The auxiliary storage device 304 includes, for example, a non-volatile computer-readable storage device such as an HDD (Hard Disk Drive), an SSD (Solid State Drive), and flash memory, or one or more of these. The auxiliary storage device 304 stores the program executed by the root generation device 3 and the information and data required for its execution for the medium to long term. In addition, information indicating the collection range 12 (Figure 2) and data and information required for various processes are pre-stored in at least one of the main storage device 302 and the auxiliary storage device 304 before the root generation device 3 is started.

[0027] The user interface device 306 is connected to the input / output device 22 and receives information indicating the operator's operation on the input devices of the input / output device 22 and outputs it to the processor 300. The user interface device 306 also outputs route planning information created by the route generation device 3 to the input / output device 22. The database 308 stores image information and weight information input from the storage devices 20A to 20J, and also stores table-format information required for generating route planning information in the route generation device 3. In addition to being implemented as dedicated hardware, the database 308 can also be implemented as software as a program that stores and manages information in the main memory 302.

[0028] The input IF device 310 receives image information and weight information from the collection station devices 20A to 20J via communication lines 210A to 210J and outputs it to the processor 300. The communication device 312 transmits the route plan information, weight information, and information indicating the collection range 12, which have been processed by the route generation device 3, to the route display devices 28-1 to 28-m via communication lines 24-1 to 24-m.

[0029] Furthermore, one or more programs stored in the main memory 302 of the root generation device 3 and executed by the processor 300 may be provided as program products recorded on a non-transitory computer-readable storage medium. In addition to one or more programs, such program products may include information and data essential for the execution of one or more programs.

[0030] Next, the operation of the collection system 2 will be explained. Figure 4 is a flowchart illustrating an example of the process (S10) for creating route planning information by the route generation device 3 shown in Figure 3, etc. Note that changing the order or dividing the processes shown in the flowchart in Figure 4 is included within the scope of this disclosure, as long as the process of the route generation device 3 is not altered. Figure 5 is a diagram illustrating an example of an information table stored in DB 308 in S100 shown in Figure 4.

[0031] Figures 6A to 6C illustrate an example of a group where the storage locations 120A, 120B, and 120E are designated as the reference storage location (first storage location). Figure 7A illustrates an example of an information table obtained when the processor 300 first performs the processing shown in Figure 4 (S102 to S118). Figure 8A illustrates an example of an information table obtained when the processor 300 performs the processing shown in Figure 4 (S102 to S118) for the second time.

[0032] Figure 9A illustrates an example of a confirmed table obtained when the processor 300 performs the processing shown in Figure 4 (S102-S118) for the third time. Figures 7B, 8B, and 9B illustrate examples of information tables obtained when the processor 300 performs sorting processing based on weight (S114) on the information tables shown in Figures 7A, 8A, and 9A, respectively. Figure 10 illustrates an example of a confirmed group obtained as a result of the route planning information creation process (S10) by the route generation device 3 (Figure 3).

[0033] In S100, the processor 300 of the route generation device 3 executes a program that implements the functions of the collection system 2, and collects identification information including location information of collection points 120A to 120J, weight information, and image information from collection point devices 20A to 20J. Furthermore, as shown in Figure 5, the processor 300 associates this information and stores it in DB 308. In S102, the processor 300 selects one or more of the collection point devices 20A to 20J that are not included in the group that has been confirmed to be included in the route (confirmed group) at this point. Note that whether a group is included in the route is confirmed in the process of S116. When the process of S102 is performed for the first time, all of the collection points 120A to 120J are selected.

[0034] In S104, the processor 300 sets one of the storage locations 120 selected in the S102 process as the reference storage location 120. In S106, the processor 300 calculates the distance between the reference storage location and the other storage locations 120. Furthermore, in the S106 process, the processor 300 adds (cumulatively adds) the weight (unadded weight) indicated by the weight information of the storage location 120 that is closest to the reference storage location among the storage locations 120 other than the storage location 120 set as the reference storage location 120 and not included in the confirmed group at this point.

[0035] In S108, the processor 300 determines whether the cumulative sum obtained by accumulating the weights indicated by the weight information of the collection point 120 selected as the reference collection point is less than or equal to the maximum load capacity of the cleaning vehicle 26 (1,000 kg). If the weight indicated by the cumulative sum is less than or equal to the maximum load capacity (Y in the process of S108), the processor 300 returns to the process of S106, and if it is heavier than the maximum load capacity (N in the same process), it proceeds to the process of S110.

[0036] In the processing of S110, the processor 300 performs grouping of the reference storage location and the storage locations 120 located in its vicinity. Specifically, for example, when storage location 120A is selected as the reference storage location in the processing of S104, as shown in Figure 6A, storage locations 120B, 120C, and 120D (second storage locations) are located in the vicinity of storage location 120A in order from closest to furthest away. In the case shown in Figure 6A, the weights indicated by the weight information of storage locations 120A, 120B, 120C, and 120D are 200kg, 250kg, 310kg, and 180kg, and the cumulative sum of the weights indicated by the weight information of storage locations 120A, 120B, 120C, and 120D is 940kg.

[0037] If we add the weight of 200 kg indicated by the weight information of collection point 120E, which is the next closest collection point to collection point 120A after collection points 120B, 120C, and 120D, to this 940 kg, it will exceed the maximum load capacity of the sanitation truck 26 (1,000 kg). Therefore, through processing S104 to S110, the processor 300 classifies (groups) collection points 120A, 120B, 120C, and 120D into one group. Furthermore, the processor 300 calculates the straight-line distance (500 m) between collection points 120A and 120D based on the location of the reference collection point (collection point 120A) of this group and the location of collection point 120D, which is the furthest from the reference collection point.

[0038] Similarly, when storage area 120B is selected as the reference storage area in processing S104, the processor 300 classifies storage areas 120A, 120B, and 120E into one group through processing S104 to S110, as shown in Figure 6B. Furthermore, the processor 300 calculates the straight-line distance (450m) between storage areas 120B and 120A based on the location of the reference storage area (storage area 120B) of this group and the location of storage area 120A, which is furthest from the reference storage area.

[0039] Similarly, when storage area 120E is selected as the reference storage area in processing S104, the processor 300 classifies storage areas 120A, 120B, 120E, and 120G into one group through processing S104 to S110, as shown in Figure 6C. Furthermore, the processor 300 calculates the straight-line distance (660m) between storage areas 120E and 120A based on the location of the reference storage area (storage area 120E) of this group and the location of storage area 120A, which is furthest from the reference storage area.

[0040] In S112, the processor 300 determines whether or not it has performed the processing in S104 to S110 with all of the storage locations 120A to 120J as the reference storage location. If the processor 300 has performed the processing in S104 to S110 with all of the storage locations 120A to 120J as the reference storage location (Y in the processing of S112), it proceeds to the processing of S114. If it has not performed the processing in S104 to S110 with all of them as the reference storage location (N in the same process), it returns to the processing of S102. When the processor 300 performs the processing in S104 to S110 with all of the storage locations 120A to 120J as the reference storage location, an information table is generated as shown in Figure 7A, which includes the identification information of the storage locations 120 included in the group obtained by the processing of S110, the sum of the weights indicated by the weight information of the storage locations 120 included in the group, and the distance between the reference storage location and the storage location 120 that is furthest away.

[0041] In S114, the processor 300 sorts the rows in the information table generated in the S112 process. In the first sort, the heavier the weight, the higher the row (heavier weights go up) and the lighter the row, the lower the row (lighter weights go down) (descending order according to weight). In the second sort, the closer the row, the higher the row (closer distances go up) and the farther the row, the lower the row (farther distances go down) (ascending order according to distance). When the sorting in the S114 process is performed on each row of the information table shown in Figure 7A, the information table illustrated in Figure 7B is obtained. As illustrated in Figure 7B, the top row of the information table is obtained with storage location 120H as the base storage location and contains information on a group that includes storage locations 120B, 120C, 120F, and 120H.

[0042] However, whether the rows in the information table are sorted in descending or ascending order according to weight, or whether the top row or the bottom row is selected, is a matter of design. The rows in the information table are sorted according to some predetermined rule, and one of the rows sorted according to the predetermined rule is selected. In S116, the processor 300 confirms the collection point 120 included in the top row of the sorted information table as the confirmed group. In other words, in S116, the processor 300 confirms the group being processed as the group included in the root information.

[0043] In S118, the processor 300 determines whether all of the integrators 120A to 120J are included in one or more groups that have been designated as confirmed groups in the processing of S114 up to this point. If all of the integrators 120A to 120J are included in one or more groups designated as confirmed groups (Y in S118), the processor 300 proceeds to the processing of S120; otherwise, it returns to the processing of S102. Note that integrator 120, which is already included in one or more groups designated as confirmed groups, is not subject to selection in the processing of S102.

[0044] Let's explain this further with a specific example. In the first (1st) S102 process, all storage locations 120A to 120J are subject to processing. On the other hand, in the second S102 process, storage locations 120B, 120C, 120F, and 120H, which are at the top of the information table shown in Figure 7B and included in the group with storage location 120H as the reference storage location, have already been selected as a confirmed group when the second S102 is executed, as indicated by the arrows in Figure 7B. Therefore, storage locations 120B, 120C, 120F, and 120H are not subject to processing in the second S102. When processor 300 performs the S102 process for the second time, as shown in Figure 8A, from the accumulation points 120A to 120J, accumulation points 120A, 120D, 120E, 120G, 120I, and 120J, other than the accumulation points 120B, 120C, 120F, and 120H included in the confirmed group, are selected for the S102 process.

[0045] As a result, the processor 300 generates the information table shown in Figure 8A through the processing in S102 to S112. Furthermore, the processor 300 performs a second sort on the information table shown in Figure 8A in S114 to generate the information table shown in Figure 8B, and identifies the collection point 120 included in the top row of the sorted information table as a confirmed group.

[0046] Furthermore, in the third S102 process, storage locations 120D, 120I, and 120J, which are at the top of the information table shown in Figure 8B and are included in the group with storage location 120J as the reference storage location, are not selected in the S102 process. When the processor 300 performs the S102 process for the third time, storage locations 120A, 120E, and 120G, other than storage locations 120B, 120C, 120D, 120F, 120H, 120I, and 120J included in the confirmed group, are selected from storage locations 120A to 120J in the S102 process, as shown in Figure 9A.

[0047] As a result, the processor 300 generates the information table shown in Figure 9A through the processing in S102 to S112. Furthermore, the processor 300 performs a third sort on the information table shown in Figure 9A in S114 to generate the information table shown in Figure 9B, and identifies the collection point 120 included in the top row of the sorted information table as a confirmed group.

[0048] In S120, the processor 300 generates a table of one or more confirmed groups that encompass all of the collection points 120A to 120J as a whole. The confirmed groups shown in Figure 10 include three groups with collection points 120H, 120J, and 120E as base collection points, and these three groups each contain all of the collection points 120A to 120J exactly once without any overlap. For example, as shown in Figure 10, the processor 300 sorts the groups included in the confirmed groups so that the longer the distance, the higher it is located (ascending order according to distance). Furthermore, the processor 300 generates route information (not shown) that allows for the shortest possible travel between the one or more collection points 120 included in each group included in the confirmed group, and adds this to each of these groups to generate route planning information.

[0049] When a confirmed group includes route planning information for m, each of the garbage trucks 26-1 to 26-m receives route planning information for m from the route generation device 3. Each of the garbage trucks 26-1 to 26-m circulates between one or more of the collection station devices 20A to 20J according to the received route planning information and collects the garbage accumulated at each of the collection station devices 20A to 20J.

[0050] Next, the overall operation of the collection system 2 will be explained with reference to Figure 11 and other figures. Figure 11 is a sequence diagram illustrating one operation (S20) of the collection system 2 shown in Figure 3 and other figures. As shown in Figure 11, in S200, each of the collection station devices 20A to 20J (Figure 3) of the collection system 2 transmits weight information and image information to the route generation device 3. The route generation device 3 receives weight information and image information from the collection station devices 20A to 20J. In S202, the route generation device 3 performs processing (S10) as explained with reference to Figure 4 and other figures, and generates route planning information.

[0051] In S204, the route generation device 3 transmits the generated route plan information and the received image information to the route display devices 28-1 to 28-m installed in the garbage trucks 26-1 to 26-m. The route plan information and image information received by the receiving device 282, along with image information showing the collection points 120A to 120J within the collection area 12 and the positions of the garbage trucks 26-1 to 26-m detected by the GPS device 284, are superimposed and displayed on the screen (not shown). The workers in the garbage trucks 26-1 to 26-m patrol one or more of the collection point devices 20A to 20J according to the displayed information and collect garbage.

[0052] Next, the technical effects obtained by the collection system 2 will be explained. As explained above, with the collection system 2, the route display device 28 can efficiently collect garbage by circulating the collection station devices 20 based on the weight of garbage measured at the collection station device 20. Generally, garbage trucks 26 circulate among multiple collection station devices 20 to collect garbage, but if the collected garbage exceeds the load capacity of the garbage truck 26, the collected garbage needs to be transported to a waste disposal site or similar facility for disposal. In contrast, with the collection system 2, route planning information is created so as not to exceed the weight of garbage that the collection station device 20 can carry, thus reducing the number of times the garbage truck 26 has to transport garbage to the collection site.

[0053] Furthermore, according to collection system 2, the optimal route planning information is created based on the weight of the garbage measured by the weight sensor 204 installed in the collection station device 20, rather than on predictions made from factors such as the area, population, season, day of the week, and time of day, thus shortening the travel distance and travel time of the garbage trucks 26. Also, according to collection system 2, route planning information is created so that many garbage trucks 26 patrol areas where garbage is concentrated, allowing for efficient collection of garbage in such areas. In addition, according to collection system 2, analysis of various factors such as area, population, season, day of the week, and time of day becomes unnecessary, allowing for garbage collection in accordance with the actual distribution of garbage volume.

[0054] Some or all of the above embodiments may also be described as follows, but are not limited to the following: [Note 1] (See Perspective 1 of this Disclosure) [Note 2] The route generation device according to Appendix 1, wherein when multiple patrol groups are generated, the multiple patrol groups are arranged vertically in a table according to a rule based on a predetermined cumulative sum, and the patrol group at a predetermined position in the table is added to the patrol route. [Note 3] The route generation device according to Appendix 2, wherein multiple patrol groups are arranged in a table in descending order according to the cumulative sum, and the highest patrol group in the table is added to the patrol route. [Note 4] The route generation device according to Appendix 1, wherein when the aforementioned travel group includes multiple such travel groups, the multiple such travel groups are sorted in the aforementioned travel group according to a predetermined rule. [Note 5] The route generation device according to Appendix 1, wherein the one or more processors are configured to calculate the distance between the first collection point and the second collection point furthest from the first collection point, and when the circulating group includes a plurality of circulating groups, the plurality of circulating groups are sorted in ascending order according to the calculated distance. [Note 6] The route generation device described in Appendix 1 displays the aforementioned patrol route and one or more of the aforementioned patrol groups together with images of one or more of the aforementioned collection points included in one or more of the aforementioned patrol groups. [Note 7] The route generation device described in Appendix 1 displays the aforementioned patrol route and one or more of the aforementioned patrol groups together with the locations of one or more of the aforementioned collection points included in one or more of the aforementioned patrol groups. [Note 8] The route generation device according to Appendix 1, which displays the patrol group and the order in which to visit the multiple patrol groups included in the patrol group, when the patrol group includes multiple collection points. [Note 9] (See Perspective 2 of this Disclosure) [Note 10] (See Perspective 3 of this Disclosure) It goes without saying that any combination of the forms described in the appendices of this disclosure, or any combination of the elements described in each perspective and embodiment (including the non-selection of some elements), can be made from time to time by those skilled in the art, in accordance with the basic concepts of this disclosure.

[0055] Furthermore, each disclosure of the above-mentioned patent documents and other materials cited is incorporated into this publication by reference. Within the framework of this disclosure (including the claims), further modifications and adjustments to the embodiments or examples are possible based on their fundamental technical concept. Also, within the framework of this disclosure, various combinations or selections (including partial deletions) of various disclosed elements (including each element of each claim, each element of each embodiment or example, each element of each drawing, etc.) are possible. In other words, this disclosure naturally includes various modifications and changes that a person skilled in the art could make in accordance with the entire disclosure, including the claims, and the technical concept. In particular, the numerical ranges described in this publication should be interpreted as specifically describing any numerical value or sub-range included within that range, even if not specifically noted. Furthermore, each disclosure of the above-mentioned cited documents is deemed to be included in the disclosures of this application, which may be used in part or in whole as part of this disclosure, in accordance with the spirit of this disclosure, as necessary. [Explanation of Symbols]

[0056] 12. Collection Scope 120 Collection points 2. Collection System 20 Collection station equipment 200 Transmitter 202 Image and weight processing equipment 204 Weight Sensor 206 Camera 210 Communication Circuit 22 Input / Output Devices 24 Communication lines 26 Cleaning truck 28 Route display device 280 displays 282 Receiving device 284 GPS device 3. Root generation device 300 processors 302 Main storage 304 Auxiliary storage 306 User Interface Device 308 DB 310 Input IF device 312 Communication equipment

Claims

1. A route generation device comprising one or more processors, wherein each of the multiple collection devices that collect packages up to or less than the maximum load capacity generates a route that includes one or more patrol groups, each including one or more collection points that patrol to collect packages, The one or more processors mentioned above are: The measured weight of the packages accumulated at each of the aforementioned multiple collection points is collected. One or more patrol groups are generated by selecting a first collection point other than the collection point included in the patrol route, and a second collection point other than the first collection point included in the patrol route, such that the cumulative sum of the measured values ​​of the first collection point and the measured values ​​of the second collection point is less than or equal to the maximum cumulative amount. A collection of one or more patrol groups generated, which generates a patrol route that includes exactly one of each of the multiple collection points. A route generation device configured as follows.

2. When multiple such tour groups are generated, the tour groups are arranged vertically within a table according to a rule based on a predetermined cumulative sum, and the tour group at a predetermined position within the table is added to the tour route. Route generation device according to claim 1.

3. Multiple tour groups are arranged in a table in descending order according to the cumulative sum, and the top-ranked tour group in the table is added to the tour route. Route generation device according to claim 2.

4. When the aforementioned travel group includes multiple such travel groups, the multiple such travel groups are sorted within the travel group according to a predetermined rule. Route generation device according to claim 1.

5. The one or more processors are configured to calculate the distance between the first collection point and the second collection point that is furthest from the first collection point. When the patrol group includes multiple patrol groups, the multiple patrol groups are sorted in ascending order according to the calculated distance. Route generation device according to claim 1.

6. The aforementioned patrol route and one or more of the aforementioned patrol groups are displayed together with images of one or more of the aforementioned collection points included in the one or more aforementioned patrol groups. Route generation device according to claim 1.

7. The aforementioned patrol route and one or more of the aforementioned patrol groups are displayed together with the location of one or more of the aforementioned collection points included in one or more of the aforementioned patrol groups. Route generation device according to claim 1.

8. When the patrol group includes multiple collection points, the patrol group and the order in which the patrol group is visited are displayed. Route generation device according to claim 1.

9. A route generation method for generating a patrol route that includes one or more patrol groups, each of which is a collection device that collects cargo up to or below its maximum load capacity, and each collection device collects cargo up to or below its maximum load capacity, and each patrol route includes one or more collection points that it visits to collect cargo, The steps include: collecting measured weights of the packages accumulated at each of the aforementioned multiple collection points; A step of generating one or more patrol groups by selecting a first collection point other than the collection point included in the patrol route, and a second collection point other than the first collection point included in the patrol route, such that the cumulative sum of the measured values ​​of the first collection point and the measured values ​​of the second collection point is less than or equal to the maximum cumulative amount, The steps include generating a set of one or more patrol groups, each of which contains exactly one of the multiple collection points, and generating a patrol route. Route generation method including

10. A route generation device comprising one or more processors, wherein each of multiple collection devices that collect packages up to or less than the maximum load capacity generates a route that includes one or more patrol groups, each including one or more collection points that it patrols to collect packages, In the above one or more processors, A process for collecting measured weights of the packages accumulated at each of the aforementioned multiple collection points, A process for generating one or more patrol groups by selecting a first collection point other than the collection point included in the patrol route, and a second collection point other than the first collection point included in the patrol route, such that the cumulative sum of the measured values ​​of the first collection point and the measured values ​​of the second collection point is less than or equal to the maximum cumulative amount, A process for generating a set of one or more patrol groups, each of which includes exactly one of the multiple collection points, and a patrol route. A program that executes the command.

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