Transportation planning device and transportation planning method

Abstract

This transportation planning device (3, 3a, 3b, 3c) comprises: a transportation route determination unit (31, 31a) that determines transportation routes of a mobile body (5) to a transportation destination on the basis of transportation information including at least the transportation destination; and a remote operation determination unit (32, 32a, 32b, 32c) that determines, among the transportation routes , a remote transportation route in which the mobile body (5) is operated remotely by a remote operator.

Description

Transportation planning device and transportation planning method

[0001] The present disclosure relates to a transportation planning device and a transportation planning method for transporting people or goods using a moving object.

[0002] With the revitalization of manufacturing and the spread of e-commerce sites, demand for logistics is increasing around the world. At the same time, the transportation industry, which plays a part in logistics, is facing a shortage of drivers.

[0003] Patent Document 1 discloses a delivery system and a processing server that delivers packages using unmanned mobile objects.

[0004] Japanese Patent Application Laid-Open No. 2020-83600

[0005] The conventional technology disclosed in Patent Document 1 had a problem in that it was not possible to deliver packages on routes other than those that the mobile object could automatically drive.

[0006] The present disclosure has been made to solve the above-mentioned problems, and aims to provide a transportation planning device and transportation planning method that are capable of transporting people and goods on routes other than those that can be automatically driven by a mobile vehicle.

[0007] The transportation planning device according to the present disclosure includes a transportation route determination unit that determines a transportation route for a mobile body to a destination based on transportation information including at least the destination, and a remote operation determination unit that determines a remote transportation route among the transportation routes along which the mobile body is remotely operated by a remote operator.

[0008] In addition, the transportation planning method disclosed herein includes a step of determining a transportation route of a mobile object to a destination based on transportation information including at least the destination, and a step of determining a remote transportation route among the transportation routes, in which the mobile object is remotely operated by a remote operator.

[0009] The transportation planning device and transportation planning method according to the present disclosure have the effect of enabling a moving body to transport people and goods on routes other than those that can be driven automatically.

[0010] FIG. 1 is an example of a configuration diagram of a transportation planning system according to a first embodiment. FIG. 2 is an example of a configuration diagram of a remote control device according to the first to fourth embodiments. FIG. 3 is an example of a configuration diagram of a moving body according to the first to fourth embodiments. FIG. 4 is a flowchart showing an example of an operation of the transportation planning device according to the first embodiment. FIG. 5 is an example of a configuration diagram of a transportation planning system according to a second embodiment. FIG. 6 is a flowchart showing an example of an operation of the transportation planning device according to the second embodiment. FIG. 7 is an example of a configuration diagram of a transportation planning system according to a third embodiment. FIG. 8 is a flowchart showing an example of an operation of the transportation planning device according to the third embodiment. FIG. 9 is an example of a configuration diagram of a transportation planning system according to a fourth embodiment. FIG. 10 is an example of a configuration diagram of a learning device according to the fourth embodiment. FIG. 11 is a flowchart showing an example of an operation of the transportation planning device according to the fourth embodiment. FIG. 12 is a diagram showing a hardware configuration of the transportation planning devices according to the first to fourth embodiments.

[0011] A transportation planning device and a transportation planning method according to an embodiment will be described in detail below with reference to the accompanying drawings.

[0012] In the following description, it is assumed that a mobile unit 5 transports people or goods from a departure point to a destination (delivery destination), and hands over the transportation to another mobile unit 5 at one or more points along the way. As an example, mobile unit 5-A transports people or goods along transportation route A from the departure point to handover point A, mobile unit 5-B transports people or goods along transportation route B from handover point A to handover point B, and mobile unit 5-C transports people or goods along transportation route C from handover point B to the delivery destination. Mobile units 5-A, 5-B, and 5-C are all different. For example, mobile unit 5-A is a truck, mobile unit 5-B is a passenger car, and mobile unit 5-C is a legged robot. A remote operator remotely operates the assigned mobile unit 5 along a remote transportation route determined by a transportation planning device (described later). For example, when transportation route B and transportation route C are determined as remote transportation routes, the remote operator remotely operates the mobile unit 5-B on transportation route B and remotely operates the mobile unit 5-C on transportation route C. The mobile unit 5-A is automatically controlled to operate on transportation route A.

[0013] As an example, the mobile units 5-A and 5-B may be the same. In this case, even if the mobile units 5 are the same in the above example, whether they are automatically controlled or remotely operated is determined depending on the transportation route.

[0014] In the above description, multiple moving bodies 5 travel along their respective transportation routes, taking over the transportation of people or goods along the way, but this is not limited to this. That is, one moving body 5 may transport people or goods from a departure point to a destination. In this case, the moving body 5 does not take over the transportation of people or goods to another moving body 5.

[0015] 1 is an example of a configuration diagram of a transportation planning system 1 according to a first embodiment. The transportation planning system 1 includes an input device 2, a transportation planning device 3, a remote control device 4, a mobile object 5, and a database 6. Each of the input device 2, the transportation planning device 3, the remote control device 4, the mobile object 5, and the database 6 transmits and receives information via a network (not shown).

[0016] The input device 2 is a device that accepts transportation information including at least a destination, and is, for example, a mobile terminal device such as a tablet, smartphone, or personal computer, but is not limited to a mobile terminal device. Here, the destination refers to, for example, a destination communicated to a taxi driver when the person gets into the taxi if the mobile object 5 is transporting a person, or to, for example, the address of the destination if the mobile object 5 is transporting goods. The user who inputs the transportation information to the input device 2 is, for example, a taxi driver or a person riding in the taxi if the mobile object 5 is transporting a person, or, for example, a transport company that manages the goods or a person requesting the goods to be transported if the mobile object 5 is transporting goods.

[0017] The input device 2 may receive transportation information including not only the transportation destination but also the desired transportation time and transportation volume.

[0018] The transportation planning device 3 determines a remote transportation route for remotely controlling the mobile object 5 based on the input information from the input device 2 and the mobile object information from the mobile object 5 .

[0019] The remote control device 4 is a device that allows a remote operator to remotely control the moving object 5 while viewing an image. The remote control device 4 will be described in detail later with reference to FIG.

[0020] The mobile object 5 is, for example, a taxi, a truck, a standard automobile, a drone, a legged robot, etc. The mobile object 5 will be described in detail later with reference to FIG.

[0021] The database 6 stores geographical data relating to road information, legal regulations regarding autonomous driving, and routes that can be driven autonomously, mobile body data relating to the type of mobile body 5 and the level of autonomous driving of the mobile body 5, remote operator data relating to the driving skill, nationality, evaluation, and location (workplace) of the remote operator, and destination data relating to the type of building at the delivery destination and a local map of the delivery destination.

[0022] The transportation planning device 3 includes a transportation route determination unit 31 and a remote operation determination unit 32 .

[0023] The transportation route determination unit 31 determines a transportation route of the mobile object 5 to the destination input to the input device 2. When the input device 2 accepts a desired transportation time, the transportation route determination unit 31 may determine a transportation route based on the desired transportation time. For example, the transportation route determination unit 31 determines a transportation route of the mobile object 5 so that the mobile object 5 arrives at the destination at the desired transportation time.

[0024] Furthermore, when the input device 2 receives the transportation volume, the transportation route determination unit 31 may determine the transportation route based on the transportation volume. For example, when the transportation volume is large, the transportation route determination unit 31 determines the transportation route of the mobile object 5 so that the mobile object 5 arrives at the destination in the shortest time, taking into consideration the load of people or goods being transported.

[0025] The remote operation determination unit 32 determines a remote transportation route along which the mobile object 5 is remotely operated by a remote operator from among the transportation routes determined by the transportation route determination unit 31. As an example, the remote operation determination unit 32 determines, from among the transportation routes determined by the transportation route determination unit 31, a route other than a route along which the mobile object 5 can be automatically driven, as the remote transportation route, based on the geographical data stored in the database 6.

[0026] The remote operation determination unit 32 may determine the remote transportation route based on the mobile object information indicating the state including the position of the mobile object 5 and the remaining travel distance. As an example, the remote operation determination unit 32 predicts a communication delay from the distance between the position of the mobile object 5 and the position of the remote control device 4, and determines, as the remote transportation route, a route within a range where the communication delay is less than a predetermined value.

[0027] The remote operation determination unit 32 may determine the remote transportation route based on the mobile object data regarding the mobile object 5 stored in the database 6. As an example, the remote operation determination unit 32 determines, as the remote transportation route, a route that satisfies the conditions related to legal regulations for autonomous driving based on the level of autonomous driving of the mobile object 5.

[0028] The remote operation determination unit 32 may determine the remote transportation route based on remote operator data related to the remote operator stored in the database 6. As an example, the remote operation determination unit 32 determines that if the remote operator has high driving skills, remote operation is possible even on narrow roads or roads with many curves, and determines a route including these roads as the remote transportation route.

[0029] The remote operation determination unit 32 may determine a remote transportation route based on the control success / failure information. The control success / failure information is information on whether the mobile object 5 is capable of traveling by autonomous driving. Cases in which autonomous driving is not possible include an abnormality in a sensor mounted on the mobile object 5. In such cases, the remote operation determination unit 32 stops controlling the autonomous driving of the mobile object 5 and switches to remote operation by a remote operator.

[0030] The remote operation determination unit 32 allocates the mobile units 5 along the remote transportation route based on the mobile unit information. As an example, when taking over transportation midway from the departure point to the transportation destination, the remote operation determination unit 32 allocates a mobile unit 5 near that location as the mobile unit 5 to be remotely operated. As another example, the remote operation determination unit 32 allocates, among multiple mobile units 5, a mobile unit 5 with a long remaining travel distance to travel along the remote route. Here, "allocation of a mobile unit 5" means allocating a mobile unit 5 to travel part or all of the route from the departure point to the transportation destination. In other words, "allocation of a mobile unit 5" includes not only the designation of the mobile unit 5 but also the designation of the route along which the mobile unit 5 will travel. This also applies to subsequent remote operator allocation, etc.

[0031] The remote operation determination unit 32 may allocate the mobile units 5 along the remote transportation route based on the mobile unit data relating to the mobile units 5 stored in the database 6. As an example, the remote operation determination unit 32 allocates a small type of mobile unit 5 that is easy to remotely operate to travel along the remote route.

[0032] The remote operation determination unit 32 assigns remote operators to remote transportation routes based on remote operator data related to the remote operators stored in the database 6. As one example, the remote operation determination unit 32 assigns a remote operator whose place of work is close to the location of the mobile object 5 at the time of starting remote operation. As another example, the remote operation determination unit 32 estimates whether the remote operator is accustomed to driving on the left or right side of the road based on the nationality of the remote operator, and assigns a remote operator whose driving rules match those based on road information when remotely operating. As yet another example, the remote operation determination unit 32 assigns a remote operator with a high evaluation. The evaluation of a remote operator depends on whether the remote operator transports people or goods on time.

[0033] The remote operation determination unit 32 presents the determined remote transportation route, the assigned mobile body 5, and the assigned remote operator to the remote operator. The remote operator starts remote operation of the mobile body 5 when notified by a means not shown that the person or object has been transported to the starting point of the remote transportation route. The remote operation determination unit 32 also outputs an automatic control flag to the mobile body 5. The automatic control flag is a flag indicating whether the mobile body 5 will travel by automatic driving. If the person or object is outside the remote operation route, the remote operation determination unit 32 sets the automatic control flag to ON to perform automatic driving of the mobile body 5. If the person or object is within the remote operation route, the remote operation determination unit 32 sets the automatic control flag to OFF to perform remote operation of the mobile body 5. Note that if the control success / failure information indicates that traveling by automatic driving is impossible, the automatic control flag is set to OFF.

[0034] 2 is a diagram showing an example of the configuration of the remote control device 4 according to the first embodiment. The remote control device 4 includes a receiving unit 41, an image generating unit 42, an operation detecting unit 43, and a transmitting unit 44.

[0035] The receiving unit 41 receives internal world information (part of the mobile body information), external world information, and control success / failure information from the mobile body 5 .

[0036] The image generation unit 42 outputs an image required for remote control to the image display device 8 based on the moving object information and external environment information from the receiving unit 41. The image generation unit 42 may output control success / failure information from the receiving unit 41 to the image display device 8 as necessary.

[0037] The operation detection unit 43 inputs remote operation information such as the amount of remote operation of the accelerator, brake, steering, etc. from the operation device 7, and the remote operator's switching operation to remote operation and shift operation (forward, reverse, and parking).

[0038] The transmitter 44 outputs the remote operation amount and remote operation information from the operation detector 43 to the mobile object 5 .

[0039] 3 is an example of a configuration diagram of a mobile object 5 according to the first embodiment. The mobile object 5 includes a mobile object control device 51, an internal sensor 52, an external sensor 53, and an actuator 54. Furthermore, the mobile object control device 51 includes a receiving unit 511, a command value converting unit 512, a switching unit 513, an internal information acquiring unit 514, an external information acquiring unit 515, an automatic driving control unit 516, and a transmitting unit 517.

[0040] The receiving unit 511 receives an automatic control flag from the transportation planning device 3. The receiving unit 511 also receives a remote operation amount and remote operation information from the remote operation device 4.

[0041] The command value converter 512 converts the remote control amount and remote control information into actuator command values ​​(current, voltage, etc.).

[0042] The switching unit 513 switches between the automatic driving mode and the remote control mode of the moving object 5 based on the automatic control flag from the receiving unit 511. That is, when the automatic control flag is ON, the switching unit 513 outputs the actuator command value from the automatic driving control unit 516 to the actuator 54. When the automatic control flag is OFF, the switching unit 513 outputs the actuator command value from the command value conversion unit 512 to the actuator 54.

[0043] The internal world information acquisition unit 514 acquires internal world information of the moving object 5 from the internal world sensor 52. The internal world information acquisition unit 514 outputs the internal world information to the transmission unit 517 as part of the moving object information.

[0044] The external environment information acquisition unit 515 acquires external environment information around the mobile object 5 from the external environment sensor 53. The external environment information acquisition unit 515 outputs the external environment information to the transmission unit 517.

[0045] The automatic driving control unit 516 generates actuator command values ​​for automatic driving control of the moving body 5 using the internal world information from the internal world information acquisition unit 514 and the external world information from the external world information acquisition unit 515.

[0046] The transmitting unit 517 transmits the internal world information from the internal world information acquiring unit 514 and the control success / failure information from the automatic driving control unit 516 to the transportation planning device 3. The transmitting unit 517 transmits the internal world information from the internal world information acquiring unit 514, the external world information from the external world information acquiring unit 515, and the control success / failure information from the automatic driving control unit 516 to the remote operation device 4.

[0047] The internal sensor 52 is a sensor for acquiring internal information of the mobile body 5. The internal sensor 52 is, for example, a position sensor of the mobile body 5, a steering angle sensor, a speed sensor, an inertia sensor, and the like.

[0048] The external sensor 53 is a sensor for acquiring external information of the mobile object 5. The external sensor 53 is, for example, a LiDAR (Light Detection and Ranging), a camera, or a radar.

[0049] The actuator 54 is a drive source for driving the moving mechanism of the moving body 5 based on the actuator command value from the switching unit 513. When the moving body 5 is an automobile, the actuator 54 is an electric motor, an automobile drive device, a brake control device, etc.

[0050] 4 is a flowchart showing an example of the operation of the transportation planning device 3 in the embodiment 1. That is, FIG. 4 is a flowchart showing an example of the transportation planning method in the embodiment 1.

[0051] As shown in FIG. 4, when the operation of the transportation planning device 3 is started by a means not shown, the transportation route determination unit 31 determines the transportation route of the moving object 5 to the destination input to the input device 2 (step ST1).

[0052] The remote operation determination unit 32 determines a remote transportation route along which the remote operator will remotely operate the mobile object 5 from among the transportation routes determined in step ST1 (step ST2).

[0053] The remote operation determination unit 32 allocates the moving object 5 to the remote transportation route (step ST3).

[0054] The remote operation determination unit 32 assigns a remote operator to the remote transportation route (step ST4).

[0055] The remote operation determination unit 32 presents the remote transportation route determined in step ST2, the mobile unit 5 assigned in step ST3, and the remote operator assigned in step ST4 to the remote operator (step ST5).

[0056] The remote operation determination unit 32 sets an automatic control flag and outputs it to the moving body 5 (step ST6). If a person or object is outside the remote operation route, the remote operation determination unit 32 sets the automatic control flag to ON so that the moving body 5 will perform automatic driving. If a person or object is within the remote operation route, the remote operation determination unit 32 sets the automatic control flag to OFF so that a remote operator will remotely operate the moving body 5. Thereafter, the operation of the transportation planning device 3 is terminated by means not shown.

[0057] According to the first embodiment described above, the transportation planning device 3 determines transportation routes to the destination of people or goods, and determines remote transportation routes among the transportation routes where the mobile body 5 is remotely operated by a remote operator, so that people or goods can be transported even on routes other than those that the mobile body 5 can operate automatically.

[0058] Second Embodiment In the first embodiment, the transportation planning device 3 assigns a remote operator to remotely operate the moving object 5, but in the second embodiment, the transportation planning device 3a also assigns a local operator to operate the moving object 5 on-site.

[0059] Fig. 5 is an example of a configuration diagram of a transportation planning system 1a according to a second embodiment. Fig. 5 differs from Fig. 1 in that the transportation planning system 1a includes a database 6a instead of the database 6 and a transportation planning device 3a instead of the transportation planning device 3. Since the components other than the database 6a and the transportation planning device 3a are the same as those shown in Fig. 1, a description thereof will be omitted.

[0060] In addition to the geographical data, mobile object data, remote operator data, and delivery destination data stored in the database 6, the database 6a stores local operator data relating to the driving skills, nationality, evaluation, and location (workplace) of the local operator. When the mobile object 5 cannot be operated both automatically and remotely, the local operator performs operations including actual operation and driving of the mobile object 5. It is desirable that the local operator be a person waiting near the mobile object 5.

[0061] The transportation planning device 3a includes a transportation route determination unit 31 and a remote operation determination unit 32a. The transportation route determination unit 31 determines a transportation route of the moving object 5 to the transportation destination input to the input device 2.

[0062] The remote operation determination unit 32a determines the remote transportation route, assigns the mobile unit 5, and assigns the remote operator, and also assigns the local operator based on the local operator data related to the local operator. As one example, the remote operation determination unit 32a assigns a local operator whose standby position is close to the location of the mobile unit 5. As another example, the remote operation determination unit 32a estimates whether the local operator is accustomed to driving on the left or right side of the road based on the nationality of the local operator, and assigns a local operator whose driving rules match those based on road information when remotely operating the local operator. As yet another example, the remote operation determination unit 32a assigns a local operator with a high evaluation. The evaluation of the local operator depends on whether the local operator transports people or goods on time.

[0063] The remote operation determination unit 32a presents the determined remote transportation route, the assigned mobile unit 5, and the assigned remote operator to the remote operator. The remote operation determination unit 32a presents the assigned mobile unit 5 and the assigned local operator to the local operator. The remote operation determination unit 32a also outputs an automatic control flag to the mobile unit 5.

[0064] Fig. 6 is a flowchart showing an example of the operation of the transportation planning device 3a in the second embodiment. That is, Fig. 6 is a flowchart showing an example of a transportation planning method in the second embodiment. Fig. 6 differs from Fig. 4 in that the processing of step ST7 is performed after the processing of step ST4, and the processing of step ST8 is performed after the processing of step ST5. Steps other than step ST7 and ST8 are the same as those shown in Fig. 4, and therefore description thereof will be omitted.

[0065] After the process of step ST4 is performed, the remote operation determining unit 32a assigns a local operator (step ST7).

[0066] After the process of step ST5 is performed, the remote operation determining unit 32a presents the moving object 5 assigned in step ST3 and the local operator assigned in step ST7 to the local operator (step ST8).

[0067] According to the second embodiment described above, the transportation planning device 3a assigns a local operator, and therefore can transport people and goods even when the mobile body 5 cannot be operated automatically or remotely.

[0068] Embodiment 3 In the first embodiment, the transportation planning device 3 determines the remote transportation route, the mobile object 5, and the remote operator, but in the third embodiment, the transportation planning device 3b determines these in consideration of information specified by the user.

[0069] Fig. 7 is an example of a configuration diagram of a transportation planning system 1b according to a third embodiment. Fig. 7 differs from Fig. 1 in that the transportation planning system 1b includes an input device 2a instead of the input device 2, a database 6b instead of the database 6, and a transportation planning device 3b instead of the transportation planning device 3. Components other than the input device 2a, the database 6b, and the transportation planning device 3b are the same as those shown in Fig. 1, and therefore will not be described again.

[0070] The input device 2a is a device that accepts transportation information including the transportation destination, desired transportation time, and transportation volume, as well as designation information regarding the mobile body 5 or remote operator designated by the user. Note that the input device 2a may also accept information regarding the local operator and transportation route, which may be included in the designation information. The input device 2a is, for example, a mobile terminal device such as a tablet, smartphone, or personal computer, but is not limited to a mobile terminal device.

[0071] The database 6b stores geographic data relating to the locations of gas stations or EV (Electric Vehicle) charging facilities corresponding to road information, in addition to the geographic data, mobile unit data, remote operator data, local operator data, and delivery destination data stored in the database 6a, and CO ２ Stores vehicle data including emissions.

[0072] The transportation planning device 3b includes a transportation route determination unit 31a and a remote operation determination unit 32b.

[0073] The transportation route determination unit 31a determines a transportation route based on the specified information specified by the user. As an example, when a transportation company as a user specifies a transportation route that passes many gas stations or EV vehicle charging facilities as specified information, the transportation route determination unit 31a refers to the geographic data in the database 6b and determines a transportation route that passes many gas stations or EV vehicle charging facilities. As another example, the transportation route determination unit 31a determines a transportation route that includes many routes that the mobile object 5 specified by the user can travel.

[0074] The remote operation determination unit 32b determines a remote transportation route based on the specified information specified by the user. For example, the remote operation determination unit 32b determines that if the remote operator specified by the user has high skill, remote operation is possible even on narrow roads or roads with many curves, and determines a route including such roads as the remote transportation route.

[0075] The remote operation determination unit 32b assigns the mobile body 5, the remote operator, or the local operator based on the designation information designated by the user. As an example, the remote operation determination unit 32b assigns the mobile body 5 designated by the user as the mobile body 5 on the remote transportation route, assigns the remote operator designated by the user as the remote operator on the remote transportation route, and assigns the local operator designated by the user as the local operator.

[0076] The remote operation determination unit 32b presents the determined remote transportation route, the assigned mobile unit 5, and the assigned remote operator to the remote operator. The remote operation determination unit 32b presents the assigned mobile unit 5 and the assigned local operator to the local operator. The remote operation determination unit 32b also outputs an automatic control flag to the mobile unit 5.

[0077] Fig. 8 is a flowchart showing an example of the operation of the transportation planning device 3b in the third embodiment. That is, Fig. 8 is a flowchart showing an example of a transportation planning method in the third embodiment. Fig. 8 differs from Fig. 4 in that instead of the processing of steps ST1 to ST4, the processing of steps ST9 to ST12 is performed. Steps other than steps ST9 to ST12 are the same as those shown in Fig. 4, and therefore description thereof will be omitted.

[0078] When the operation of the transportation planning device 3b is started by a means not shown, the transportation route determination unit 31a determines the transportation route of the mobile body 5 to the destination input to the input device 2a based on the specified information specified by the user (step ST9).

[0079] The remote operation determination unit 32b determines a remote transportation route based on the designation information designated by the user (step ST10).

[0080] The remote operation determining unit 32b assigns the moving object 5 based on the designation information designated by the user (step ST11).

[0081] The remote operation determining unit 32b assigns a remote operator based on the designation information designated by the user (step ST12).

[0082] After the process of step ST12, the remote operation determining unit 32b may assign a local operator based on the designation information specified by the user. In this case, after the process of step ST5, the remote operation determining unit 32b presents the moving object 5 assigned in step ST11 and the local operator assigned after step ST12 to the local operator.

[0083] According to the third embodiment described above, the transportation planning device 3b takes into consideration the specified information specified by the user, and therefore can transport people or goods using the route, mobile object 5, and remote operator desired by the user.

[0084] Fourth Embodiment In a fourth embodiment, the transportation planning device 3c determines a remote transportation route, a mobile object 5, and a remote operator, taking into consideration the operation time required to operate the mobile object 5.

[0085] Fig. 9 is an example of a configuration diagram of a transportation planning system 1c according to a fourth embodiment. Fig. 9 differs from Fig. 1 in that the transportation planning system 1c includes a transportation planning device 3c instead of the transportation planning device 3. Since the components other than the transportation planning device 3c are the same as those shown in Fig. 1, a description thereof will be omitted.

[0086] The transportation planning device 3c includes a transportation route determination unit 31, a remote operation determination unit 32c, a work time prediction unit 33, and a learning device 34. The transportation route determination unit 31 determines a transportation route of the moving object 5 to the destination input to the input device 2.

[0087] The remote operation determination unit 32c allocates the mobile units 5 based on the work time required to operate the mobile units 5. Here, the "work time required to operate the mobile units 5" refers to the time required for the remote operator or the local operator to travel the route for which they are responsible for operating the mobile units 5. As an example, the remote operation determination unit 32c allocates the mobile units 5 that take the shortest time to travel the specified route from the departure point to the delivery destination.

[0088] The remote operation determination unit 32c assigns a remote operator based on the operation time. As an example, the remote operation determination unit 32c assigns a remote operator who has performed remote operation of the mobile object 5 along a specified route from the departure point to the delivery destination and who has the shortest remote operation time.

[0089] The remote operation determination unit 32c assigns a local operator based on the operation time. As an example, the remote operation determination unit 32c assigns a local operator who has operated the mobile object 5 along a specified route from the departure point to the delivery destination and who has the shortest operation time.

[0090] The work time prediction unit 33 predicts the work time using a trained model 343 included in the learning device 34. Alternatively, the work time prediction unit 33 may predict the work time based on a database that stores past remote transportation routes, combinations of mobile objects 5 and remote operators, or past combinations of transportation routes, mobile objects 5 and local operators, without using the learning device 34. Note that the learning device 34 does not have to be included in the transportation planning device 3c.

[0091] 10 is a diagram illustrating an example of a configuration of a learning device 34 according to the fourth embodiment. The learning device 34 includes a preprocessing unit 341, a learning unit 342, and a trained model 343.

[0092] The pre-processing unit 341 calculates the work time based on a work completion report from a remote operator via a means not shown. The pre-processing unit 341 may also calculate the work time based on a work completion report from a local operator.

[0093] The learning unit 342 performs learning to generate a learning model that inputs transportation information and outputs work time, using at least the transportation information from the input device 2 and the work time from the preprocessing unit 341. In other words, when there is one remote operator and one mobile unit 5 allocated from the departure point to the destination, the information required to generate the learning model is only the transportation information and work time.

[0094] The learning unit 342 may perform learning using the transportation information, the mobile body data and remote operator data in database 6, and the work time to generate a learning model that takes the transportation information, the mobile body data, and the remote operator data as input and outputs the work time. Furthermore, the learning unit 342 may also use local operator data from database 6a or the like instead of database 6. In this case, the learning unit 342 may perform learning to generate a learning model that takes data including the local operator data as input and outputs the work time.

[0095] The learning unit 342 may also use traffic congestion information, time period, or weather data. In this case, the learning unit 342 may perform learning to generate a learning model that receives data including traffic congestion information, time period, or weather data as input and outputs work time.

[0096] The learning unit 342 generates a learning model by supervised machine learning. However, the learning model is not limited to supervised machine learning, and may be generated by unsupervised machine learning.

[0097] The trained model 343 is a trained model generated by the training unit 342 .

[0098] Fig. 11 is a flowchart showing an example of the operation of the transportation planning device 3c in the fourth embodiment. That is, Fig. 11 is a flowchart showing an example of a transportation planning method in the fourth embodiment. Fig. 11 differs from Fig. 4 in that processing of step ST13 is performed after processing of step ST1, and processing of steps ST14 to ST16 is performed instead of processing of steps ST2 to ST4. Steps other than step ST13 to ST16 are the same as those shown in Fig. 4, and therefore description thereof will be omitted.

[0099] After the process of step ST1 is performed, the operation time prediction unit 33 predicts the operation time required to operate the moving object 5 (step ST13).

[0100] The remote operation determination unit 32c determines a remote transportation route based on the operation time (step ST14).

[0101] The remote operation determining unit 32c assigns the moving object 5 based on the operation time (step ST15).

[0102] The remote operation determining unit 32c assigns a remote operator based on the operation time (step ST16).

[0103] After the process of step ST16, the remote operation determining unit 32c may assign a local operator based on the operation time. In this case, after the process of step ST5, the remote operation determining unit 32c presents the mobile object 5 assigned in step ST15 and the local operator assigned after step ST16 to the local operator.

[0104] According to the fourth embodiment described above, the transportation planning device 3c takes into consideration the operation time required to operate the moving object 5, and therefore can determine a more efficient remote transportation route, etc.

[0105] Here, a description will be given of the hardware configuration of the transportation planning devices 3, 3a, 3b, and 3c according to the first to fourth embodiments. Each function of the transportation planning devices 3, 3a, 3b, and 3c can be realized by a processing circuit. The processing circuit includes at least one processor and at least one memory.

[0106] 12 is a diagram showing the hardware configuration of the transportation planning devices 3, 3a, 3b, and 3c according to the first to fourth embodiments. The transportation planning devices 3, 3a, 3b, and 3c can be realized by a processor 10 and a memory 11 shown in FIG. 12(a). The processor 10 is, for example, a CPU (Central Processing Unit, also referred to as a central processing unit, processing device, arithmetic unit, microprocessor, microcomputer, processor, or DSP (Digital Signal Processor)) or a system LSI (Large Scale Integration).

[0107] The memory 11 may be, for example, a non-volatile or volatile semiconductor memory such as a RAM (Random Access Memory), a ROM (Read Only Memory), a flash memory, an EPROM (Erasable Programmable Read Only Memory), or an EEPROM (registered trademark) (Electrically Erasable Programmable Read-Only Memory), a HDD (Hard Disk Drive), a magnetic disk, a flexible disk, an optical disk, a compact disk, a mini disk, or a DVD (Digital Versatile Disk).

[0108] The functions of each part of the transportation planning devices 3, 3a, 3b, and 3c are realized by software or the like (software, firmware, or software and firmware). The software or the like is written as a program and stored in the memory 11. The processor 10 realizes the function of each part by reading and executing the program stored in the memory 11. In other words, it can be said that this program causes a computer to execute the procedure or method of the transportation planning devices 3, 3a, 3b, and 3c.

[0109] The program executed by the processor 10 may be provided as a computer program product stored in a computer-readable storage medium as an installable or executable file. Alternatively, the program executed by the processor 10 may be provided to the transportation planning devices 3, 3a, 3b, and 3c via a network such as the Internet.

[0110] Furthermore, the transportation planning devices 3, 3a, 3b, and 3c may be realized by a dedicated processing circuit 12 shown in Fig. 12(b). When the processing circuit 12 is dedicated hardware, the processing circuit 12 may be, for example, a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array), or a combination thereof.

[0111] The above describes a configuration in which the functions of each component of the transportation planning devices 3, 3a, 3b, and 3c are realized either by software or hardware. However, the present invention is not limited to this, and some of the components of the transportation planning devices 3, 3a, 3b, and 3c may be realized by software and other components may be realized by dedicated hardware.

[0112] The configurations shown in the first to fourth embodiments are merely examples, and may be combined with other known technologies. Furthermore, the first to fourth embodiments may be combined with each other. Furthermore, it is also possible to omit or change part of the configuration without departing from the spirit of the invention.

[0113] 1, 1a, 1b, 1c Transportation planning system, 2, 2a Input device, 3, 3a, 3b, 3c Transportation planning device, 31, 31a Transportation route determination unit, 32, 32a, 32b, 32c Remote operation determination unit, 33 Work time prediction unit, 34 Learning device, 341 Preprocessing unit, 342 Learning unit, 343 Learned model, 4 Remote operation device, 41 Receiving unit, 42 Image generation unit, 43 Operation detection unit, 44 Transmission unit, 5 Mobile body, 51 Mobile body control device, 511 Receiving unit, 512 Command value conversion unit, 513 Switching unit, 514 Internal world information acquisition unit, 515 External world information acquisition unit, 516 Automatic driving control unit, 517 Transmission unit, 52 Internal world sensor, 53 External world sensor, 54 Actuator, 6, 6a, 6b Database, 7 Operation device, 8 Image display device, 10 Processor, 11 Memory, 12 Processing circuit.

Claims

1. A transportation planning device comprising: a transportation route determination unit that determines a transportation route for a mobile object to a destination based on transportation information including at least the destination; and a remote operation determination unit that determines a remote transportation route among the transportation routes along which a remote operator remotely operates the mobile object.

2. A transportation planning device according to claim 1, wherein the remote operation determination unit determines the remote transportation route based on mobile object information indicating the state of the mobile object.

3. A transportation planning device according to claim 1 or 2, wherein the remote operation determination unit determines the remote transportation route based on mobile body data relating to the mobile body.

4. A transportation planning device according to any one of claims 1 to 3, wherein the remote operation determination unit determines the remote transportation route based on remote operator data relating to the remote operator.

5. A transportation planning device according to any one of claims 1 to 4, wherein the remote operation determination unit determines the remote transportation route based on control success / failure information.

6. A transportation planning device according to claim 2, wherein the remote operation determination unit allocates the mobile objects to the remote transportation route based on the mobile object information.

7. A transportation planning device according to claim 3, wherein the remote operation determination unit allocates the mobile objects to the remote transportation route based on the mobile object data.

8. A transportation planning device according to claim 4, wherein the remote operation determination unit allocates the remote operators to the remote transportation route based on the remote operator data.

9. A transportation planning device according to any one of claims 1 to 8, wherein the remote operation determination unit assigns the local operators based on local operator data relating to the local operators.

10. A transportation planning device according to any one of claims 1 to 9, wherein the remote operation determination unit determines the remote transportation route based on specified information relating to a mobile object, a remote operator, or a local operator specified by a user.

11. A transportation planning device according to claim 10, wherein the transportation route determination unit determines the transportation route based on the specified information.

12. A transportation planning device according to claim 10 or 11, wherein the remote operation determination unit assigns the mobile object, the remote operator, or the local operator based on the designation information.

13. A transportation planning device according to claim 6 or 7, comprising an operation time prediction unit that predicts the operation time required to operate the mobile object, and the remote operation determination unit allocates the mobile object based on the operation time.

14. A transportation planning device according to claim 8, further comprising a work time prediction unit that predicts the work time required to operate the mobile object, and the remote operation determination unit assigns the remote operator based on the work time.

15. A transportation planning device according to claim 9, further comprising a work time prediction unit that predicts the work time required to operate the mobile object, and the remote operation determination unit assigns the local operator based on the work time.

16. A transportation planning device according to any one of claims 13 to 15, wherein the work time prediction unit predicts the work time based on a learning model that receives at least the transportation information as input and outputs the work time.

17. A transportation planning method comprising: a step of determining a transportation route for a mobile object to a destination based on transportation information including at least the destination; and a step of determining, from among the transportation routes, a remote transportation route along which the mobile object is remotely operated by a remote operator.