Moving body operation management device

Abstract

To provide a moving body operation management device that makes safe and efficient take-off and landing possible when a plurality of drones are approaching one take-off and landing port.SOLUTION: A moving body operation management device 411 manages operation of a plurality of first moving bodies 105 that are each loaded with a conveyance target 305 which is an article or a person, and that each move from a departure location to an arrival location in accordance with an instructed route. The moving body operation management device 411 comprises: a movement time prediction calculation unit 706 that calculates movement times of the first moving bodies 105; an occupation probability calculation unit 707 that calculates a probability that a take-off and landing port 306 which the first moving bodies 105 take off from and land at will be occupied by the first moving bodies 105 on the basis of movement time uncertainty, which is calculated using information that affects the operation of each of the plurality of first moving bodies 105; and a usage plan optimization unit 708 that plans so that the take-off and landing port 306 will be occupied by the first moving bodies 105 at all times.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present invention relates to a mobile object traffic control device that moves and transports using an aircraft, and in particular to a mobile object traffic control device that uses a VTOL (Vertical take-off and landing aircraft) capable of vertical take-off and landing as the aircraft. [Background technology]

[0002] Recently, a system has been proposed to transport luggage to a destination using unmanned aerial vehicles called drones that take off and land vertically to the landing surface. Multi-rotor drones with multiple rotor blades are commonly used for these drones.

[0003] This drone-based transportation system inputs data representing the drone's planned flight path on the horizontal plane, obtains height reference values ​​representing the elevation of the surface below each of a plurality of positions on the planned flight path, and uses the value obtained by adding the flight altitude corresponding to each position to the height reference value as altitude data for the planned flight path.

[0004] This allows the aircraft to fly the planned route without colliding with any obstacles.

[0005] In such a drone-based transportation system, it is important that a large number of drones can efficiently arrive and land at their destinations. For this reason, a method described in Patent Document 1, for example, has been proposed as a drone landing control device.

[0006] This patent document 1 discloses a flight management system that manages reservations for each takeoff and landing port where autonomous drones take off and land, and also manages the flight plans and flight positions of multiple drones that fly autonomously between takeoff and landing ports. When multiple drones share a takeoff and landing port, reservation management for the takeoff and landing port enables multiple drones to approach one takeoff and landing port.

[0007] In this way, when managing reservations for takeoff and landing ports, it is necessary to take into account factors such as when the drones will land and take off, and whether or not time is needed to power and perform maintenance on the drone, in order to ensure efficiency.

[0008] Patent Document 2 discloses a method for a drone equipped with a battery to acquire information about the aircraft and its location, and indicate the power supply start time and standby period by taking into consideration the shortest arrival time to a power supply facility, the average flight time, and the avoidance of areas with bad weather, thereby enabling efficient power supply. [Prior art documents] [Patent documents]

[0009] [Patent Document 1] WO2018 / 155700 publication [Patent Document 2] WO2021 / 245836 publication Summary of the Invention [Problem to be solved by the invention]

[0010] Incidentally, the methods described in Patent Documents 1 and 2 do not take into account the fact that multiple drones will take off and land at the same takeoff and landing port, so when making a reservation, it is necessary to make sure that the takeoff and landing port used by each drone does not overlap with that of other drones.

[0011] However, taking into account that each drone's takeoff and landing circumstances and route conditions may result in it arriving early or late at the port, it is necessary to make redundant reservations with ample time before and after the original occupancy time.

[0012] If this reservation method is used at a single takeoff and landing port where multiple drones approach, the port's usage efficiency will decrease if all drones operate on schedule. Even if the port becomes available at certain times, drones that have not reserved the port will not be able to use it, resulting in a problem of reduced efficiency for the system as a whole.

[0013] In consideration of these problems, an object of the present invention is to provide a mobile object traffic management device and a mobile object traffic management method that enable safe and efficient takeoff and landing when multiple drones approach a single takeoff and landing port. [Means for solving the problem]

[0014] In order to achieve the above object, the present invention is configured as follows.

[0015] A mobile object operation management device that manages the operation of multiple mobile objects that carry transport objects, such as goods or people, and move along an instructed route from a departure point to a destination point includes a travel time prediction calculation unit that calculates the travel time of the mobile objects, an occupancy probability calculation unit that calculates the probability that multiple mobile objects will occupy a takeoff / arrival port from which the mobile objects take off and arrive, based on the uncertainty of the travel time calculated using information that affects the operation of each of the multiple mobile objects, and a usage plan optimization unit that plans to have the takeoff / arrival port occupied by the multiple mobile objects at all times.

[0016] In addition, in a mobile object operation pipeline method of a mobile object operation management device that manages the operation of multiple mobile objects that carry transport objects such as goods or people and move along an instructed route from a departure point to a destination, the travel time of the mobile objects is calculated, and based on the uncertainty of the travel time calculated from information that affects the operation of each of the multiple mobile objects, the occupancy probability that multiple mobile objects will occupy the take-off and landing ports from which the mobile objects take off and land is calculated, and it is planned so that the take-off and landing ports are occupied by the mobile objects at all times. Effect of the Invention

[0017] According to the present invention, it is possible to provide a mobile object operation management device and a mobile object management method that enable safe and efficient takeoff and landing when multiple drones approach a single takeoff and landing port. [Brief description of the drawings]

[0018] [Figure 1] FIG. 1 is a diagram for explaining an overview of a mobile transportation system in which a plurality of mobile objects are coordinated according to a first embodiment of the present invention. [Diagram 2] FIG. 2 is a diagram showing an image of a mobile object connection hub that connects mobile objects together according to the first embodiment of the present invention. [Diagram 3] 1 is an overall overview of a mobile transportation system using drones and rail vehicles according to a first embodiment of the present invention. [Figure 4] FIG. 2 is a diagram showing an image of the right to use each facility of the mobile transportation system in the first embodiment of the present invention. [Diagram 5] This is an overall overview diagram of the system that manages and controls the operation of a first mobile drone. [Figure 6] 1 is a flowchart showing the processing flow of a drone traffic management system. [Figure 7] FIG. 13 is a diagram showing an image of calculating the port occupancy probability of a single aircraft. [Figure 8] FIG. 13 is a diagram showing an image of the port occupancy probability of multiple aircraft aggregated together. [Figure 9] FIG. 13 is a diagram showing an image of adjusting the port occupancy probability. [Figure 10] 13 is a flowchart showing a process flow for adjusting a port occupancy probability. [Figure 11] 1 is a flowchart showing a general process flow of the transportation phase of a mobile transportation system. [Figure 12] FIG. 11 is a diagram for explaining an overview of a mobile transportation system in which a plurality of mobile objects are coordinated according to a second embodiment of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0019] Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings.

[0020] It should be noted that the present invention is not limited to the following embodiments, but includes within its scope various modifications and applications within the technical concept of the present invention. EXAMPLES

[0021] Example 1 FIG. 1 is a schematic configuration diagram of a mobile transportation system (mobile object traffic control system) 1 having a mobile object traffic control device in which a plurality of mobile objects are linked together according to a first embodiment of the present invention.

[0022] FIG. 1 shows a mobile transportation system 1 in which a user 100 purchases and pays for products on sale and transportation fares over the Internet or the like, and the products are automatically transported using multiple mobile bodies (a first mobile body 105, a second mobile body 107).

[0023] In Fig. 1, first, a user 100 selects and purchases a product or the like using a matching / buying and selling service system 102, and an order notification and permission to move are notified to a seller / movers 103. These products or the like are objects of transportation 305, which may be goods or people, and these objects of transportation are moved to a distribution base departure point 104, moved by a first mobile object 105 to an inter-mobile object connection hub 106 along the way, transferred or changed to a second mobile object 107 such as a railroad car 320, and arrive at a destination or a product storage facility 108.

[0024] The inter-mobile connection hub 106 has a take-off and landing port 306 where a first mobile body 105 such as a drone 300 takes off and lands.

[0025] The operation from the delivery base / departure point 104 to the arrival point 108 is managed by an integrated operation management system 109, and if the schedule needs to be revised, the operation of each mobile body (first mobile body 105, second mobile body 107) is adjusted. In addition, each mobile body (first mobile body 105, second mobile body 107) receives information and energy for movement from infrastructure 110 as necessary.

[0026] As a specific example of such a mobile transportation system 1, a description will be given of an example of logistics transportation using a drone as the first mobile body 105 and a railroad car as the second mobile body 107. Note that the second mobile body 107 is not limited to a railroad car, and may be a vehicle such as an automobile.

[0027] Drones offer a high degree of freedom in terms of where they can be delivered, and they are often used to transport small amounts of cargo over relatively short distances on demand.

[0028] On the other hand, railways are limited to locations where there are stations, but are often used to transport large amounts of cargo over long distances and on a regular schedule.

[0029] When considering a scenario in which these two vehicles are connected to transport goods, etc., a mismatch occurs between drones with a small payload and rail vehicles with a very large payload. To solve this problem, by operating multiple drones to arrive at the same time as regular train departure times, it is possible to utilize the strengths of the two vehicles and compensate for their weaknesses.

[0030] The operation of the mobile transportation system 1 will be described using drones and railroad trains as examples. The description here is for the transportation of goods, but the same applies to the transportation of people.

[0031] The mobile transportation system 1 can be broadly divided into an operation planning phase in which the route and time of mobile transportation are determined and reservations are made for each mobile vehicle and facility, etc., and a transportation phase in which items are actually loaded onto mobile vehicles such as drones and railway trains and transported.

[0032] First, a user 100 decides to order from among products that have been registered in advance by a seller / mobile person 103 in the matching / buying and selling service system 102. When the user 100 purchases a product, the matching / buying and selling service 102 transmits a request for delivery of the product to the seller / mobile person 103 and also notifies the integrated operation management system 109.

[0033] Next, an integrated operation management system 109 adjusts and arranges the operation times and the vehicles to be used for transporting goods at the delivery base / departure point 104, the vehicle connection hub 106, and the storage location / arrival point 108.

[0034] Next, the operation times of the drone and train to be used are coordinated and determined with other vehicles that use the delivery base / departure point 104, inter-vehicle connection hub 106, and storage location / arrival point 108 at the same time, and then payment is completed in the matching / buying and selling service system 102.

[0035] At this point, the operation plan phase is complete, and we move on to the transportation phase. However, the operation plan decided for one transportation may be changed due to adjustments in other transportations.

[0036] In the transportation phase, the seller / traveler 103 transports the goods to the distribution base / origin 104. This transportation may be performed by the seller himself or by other means.

[0037] Next, the goods are transported from the delivery base / departure point 104 to the inter-mobile connection hub 106 using a drone, which is the first mobile object 105, along the determined route, with the determined mobile object, and at the determined time. Next, at the inter-mobile connection hub 106, the goods are transferred from the first mobile body 105, which is a drone, to the second mobile body 107, which is a railroad train.

[0038] Fig. 2 shows an image of connecting a drone, which is a first mobile body 105 loaded with multiple packages, and a railroad car, which is a second mobile body 107. The connection between the drone, which is the first mobile body 105, and the railroad car, which is the second mobile body 107, shown in Fig. 2, is a specific example of the mobile body connection hub 106, but it is not necessarily limited to this form, and any system can be used as long as people and things contained in multiple types of mobile bodies are handed over by some means.

[0039] 2, the drone 300 has four blade rotors 302 provided at symmetrical positions on a rectangular housing body 301, and each blade rotor 302 is driven by an electric motor (not shown). Note that the flying object of the first embodiment is not limited to this, and any flying object that can take off and land vertically may be used.

[0040] The housing body 301 is provided with an aircraft control device 303 including a position and orientation sensor, and further provided with a communication device 304 that communicates with a drone control system 307 the position of the aircraft, drone 300, and the route it will take. A well-known GNSS sensor and inertial measurement unit are installed to detect the position and orientation of the housing body 301.

[0041] In addition, the aircraft control device 303 uses route information representing the horizontal flight plan route of the drone 300 (the aircraft) and a height reference value representing the elevation of the ground surface below each of the multiple positions on the flight plan route, and adds the flight altitude corresponding to that flight position to the height reference value, and uses this value as altitude information for the flight plan route, thereby enabling the drone 300 to fly along the flight plan route without colliding with other aircraft or obstacles.

[0042] Furthermore, a transportation object 305 is installed on the outside or inside of the housing body 301, and this transportation object 305 is removable.

[0043] On the other hand, the control system 307 that instructs the route of the drone 300, which is an air vehicle, is shown as being separate from the takeoff and landing port 306 in Fig. 2, but may be integrated with it. Also, although only one takeoff and landing port 306 from which a moving object such as the drone 300 takes off and lands is shown in Fig. 3, there may be multiple takeoff and landing ports.

[0044] However, the control system 307 is intended to instruct the route of the drone 300, which is an air vehicle, approaching at least one takeoff and landing port 306, and multiple control systems 307 will not instruct the drone 300, which is an air vehicle, on multiple routes.

[0045] When multiple drones 300 arrive at the takeoff and landing port 306, the control system 307 instructs the landing order, and each drone 300 lands, transfers the transport object 305 to a mobile transport aircraft 310, takes off, and the next drone 300 instructed to land lands and repeats the same operation.

[0046] The mobile transport aircraft 310 carrying the object 305 moves from the takeoff / landing port 306 to the terminal 321 where the railcar 320 is waiting by the departure time, and after loading the object 305 onto the railcar 320, it repeats the process of moving back to the takeoff / landing port 306.

[0047] The railroad car 320 arrives at the terminal 321 at the scheduled time according to instructions from the railroad control system 322, and waits until the departure time. During that time, the transportation object 305 is loaded from the mobile transport aircraft 310 onto the railroad car 320.

[0048] Next, the goods are transported from the inter-mobile connection hub 106 to the storage location / destination 108 by a railroad car 320, which is the second mobile unit 107, and upon arrival, the goods are stored and the user 100 is notified of their arrival.

[0049] Finally, the user 100 who has been notified of the arrival of the product receives the product at the storage location / arrival point 108, and the processing of the mobile transportation system 1 for this product is completed.

[0050] Detailed operations of each system of the mobile transportation system 1 using drones 300 and rail cars 320 will be explained using the overall overview of the mobile transportation system 1 using drones 300 and rail cars 320 in Fig. 3 and the processing flow of each system. In Fig. 3, thick arrows indicate the flow of goods, and thin arrows indicate the flow of information.

[0051] First, in order to explain the operation in the operation planning phase, the processing of the matching / buying and selling service 401 and the integrated operation management system 409 will be explained.

[0052] First, a seller 402 registers a product, a delivery base 407 where the product can be transported, and a time, etc., in an inventory / reservation management system 403. The inventory / reservation management system 403 is linked to an order management system 404, and the registered information can be referenced in the order management system 404 regarding inventory and reservation availability.

[0053] In addition, an ID is assigned to the registered product, and the product is registered in the delivery request system 406 together with the delivery base 407 where the product can be delivered, the time, and the like.

[0054] Next, the user 400 places an order for the product indicated by the inventory / reservation management system 403 through the order management system 404 .

[0055] Next, the order management system 404 confirms where the product is stored, and notifies the delivery matching platform 405 of the location and order details.

[0056] From the possession destination and order details acquired by the delivery matching platform 405, the route from the delivery base 407 to the storage location 408 designated by the user 400 is searched for, the route is listed, the maximum time required for each route is calculated, and a provisional decision is made.

[0057] Here, each required time includes at least the transportation time to the delivery base set by the seller 402, the transportation time by each mobile object, and the transportation time required for transferring the product.

[0058] Next, the delivery matching platform 405 transmits the ID of the ordered item, the list of stopovers, and each required time to the integrated operation control system 409.

[0059] Next, based on the route and required time received in the integrated traffic control system 409, an application is made to the drone traffic control system (mobile object traffic control device) 411 for the right to use the takeoff / landing port 412 on the takeoff side and the takeoff / landing port 306 on the landing side. This application for the right to use is made for multiple types of mobile objects in order of the likelihood of the set time being met.

[0060] In this embodiment 1, it is assumed that there is a low probability that the drone will keep to its scheduled time, and an application for usage rights is first made to the drone operation management system (mobile object operation management device) 411.

[0061] Here, the above-mentioned right of use will be explained. The right of use is the right to use each facility including the landing and takeoff ports (412, 306) and aircraft, and is a facility use reservation set on a time basis.

[0062] The concept of usage rights is shown on a time axis in Fig. 4. Time flows downward in Fig. 4, and the areas where usage rights are set in each facility are shown in white frames. The method of setting usage rights shown in this embodiment 1 is only one example, and the setting method may be changed depending on the type of business.

[0063] The reservation and setting of the right to use each facility must be set with a margin between the time when the facility is actually used. The following is an example of setting the right to use the takeoff and landing port 412 on the delivery base side, the drone 300, and the port 306 on the delivery connection system 410 side.

[0064] The right of use of the takeoff / landing port 412 on the delivery base side is set to start before the available transport time 601 registered by the seller 402 in the inventory / reservation management system 403. Also, taking into consideration the possibility of delays to the time 602 when the drone 300 is scheduled to arrive at the takeoff / landing port 412 on the delivery base side, the planned flight time 603 is calculated by adding the air margin time that the drone 300 can stay in the air, the time for maintenance and refueling, or the loading time, whichever is longer, and the right of use is set to the time 604 by adding the time to leave the port control area to the planned flight time 603.

[0065] During this port control zone departure time, a predetermined airspace around the takeoff and landing port 412 is set as a port control zone, and only one aircraft is allowed to be in the control zone at the same time. This is to prevent unexpected proximity or collision between aircraft due to multiple aircraft descending or taking off at the same time.

[0066] In addition, the right to use the drone 300 is set starting from the scheduled time 602 of arrival at the take-off and landing port 412 on the delivery base side, and ending at a time 606 which is the sum of the arrival time 605 at the take-off and landing port 306 on the delivery connection system 410 side and the remaining flight time.

[0067] In addition, the right to use the take-off and landing port 306 on the delivery connection system 410 side is set starting from the arrival time 605 at the take-off and landing port 306 on the delivery connection system 410 side, and is set up to a time 607 that is the sum of the flight time for the drone 300 on its route, plus the longer of the time for maintenance and refueling or the time required for loading, and if the drone 300 takes off for the next destination, the time to leave the port control area.

[0068] In the same manner, usage rights for other facilities are also established.

[0069] Next, based on the time requested from the integrated traffic control system 409, the drone traffic control system (mobile traffic control device) 411 selects the available times for the takeoff / landing port 412 and the landing port 306, as well as an aircraft that can be used for transporting goods, and grants the respective usage rights for the transportation of the product ID, and notifies the integrated traffic control system 109 and the drone control system 307.

[0070] Here, the operation of the drone traffic management system (mobile object traffic management device) 411 will be described according to the system configuration of FIG. 5 and the processing flow of FIG.

[0071] In step S801, the take-off and landing port 412 on the delivery base side, which is the departure point of the drone 300, and the take-off and landing port 306 on the delivery connection system side, which is the arrival point, and the provisionally determined use time calculated by the facility use time calculation unit 701 of the integrated operation management system 409 are received.

[0072] Next, in step S802, the aircraft / route selection unit 702 determines a flight route from the departure point and destination acquired in step S801 using the route DB 703. The route DB 703 contains a topological map shown as a sequence of waypoints indicating flight positions, and the route is set using the Dijkstra algorithm or the like. The links connecting these waypoints are assumed to have standard speeds stipulated for flying in that section.

[0073] In addition, an aircraft (drone 300) that can fly along the determined route is selected using an aircraft usage plan 704. The aircraft usage plan 704 includes the right to use the aircraft at the relevant time, the expected flight distance at the relevant time, the aircraft type, wind resistance, and the degree of punctuality based on charges, etc.

[0074] Next, in step S803, the aircraft performance of the drone 300 selected in step S802 is obtained from the aircraft usage plan 704, and at the same time, the uncertainty parameter calculation unit 705 obtains wind and weather information from the wind and environment information system 413. The uncertainty parameter calculation unit 705 calculates and determines the occurrence probability of factors that affect uncertain flight, such as wind conditions.

[0075] Next, in step S804, a standard flight time is calculated for the flight route selected by the aircraft from the flight route and aircraft selected in step S802, and environmental information such as wind conditions and aircraft performance acquired in step S803. The flight time calculation varies depending on the occurrence of wind conditions and other uncertain factors that affect flight, but in step S804, only the most likely information is selected and used for the flight time calculation.

[0076] Next, in step S805, it is confirmed that the standard flight time calculated in step S804 falls within the range of the use time at the departure point and the use time at the arrival point acquired in step S801. This can be confirmed by the following calculation.

[0077] (End time of use at destination) – (Start time of use at departure destination) > standard flight time, and (Start time of use at destination) – (End time of use at departure destination) < standard flight time.

[0078] If the standard flight time does not fall within the range of the use time, a different route or a different aircraft is selected, and the processes from step S802 to step S804 are repeated until the standard flight time falls within the use time.

[0079] Next, in step S806, the body and flight route of the selected drone 300 are fixed, and the uncertainty parameter calculation unit 705 acquires the uncertainty factors. The uncertainty of the travel time of the drone 300, which is a moving body, is calculated by calculating the range of variation in the travel time from the type of the drone 300, which is a moving body, and the effect on the movement performance.

[0080] As an example of an uncertain factor, wind conditions will be described. A wind vector is given in a certain area on the route. This wind vector is expressed by the magnitude of wind force and the wind direction. For this wind vector, the error in wind force and the error in wind direction are given as variance values. In addition, the occurrence probability of this uncertain factor may be given directly.

[0081] Next, in step S807, the port occupancy probability calculation unit 707 calculates the expected arrival time and the range of the time using the uncertainties acquired in step S806. The expected arrival time can be calculated by the following calculation formula (1). (Arrival time) = (Route distance / Standard speed) + (Uncertainty delay) + (Departure time) (1)

[0082] In the above formula (1), the route distance and standard speed are deterministic and are calculated uniquely. The uncertainty delay is the delay time caused by each uncertainty factor, and is treated as a random event and is calculated according to the events occurring in the section of the flight route.

[0083] For example, in the case of wind conditions, the flight speed for a certain section is calculated from the wind vector and aircraft maneuvering performance in that section. Using this speed, if the time to pass through that section at the original standard speed is faster, it is expressed as a negative value, and if the time to pass through that section is slower, it is expressed as a positive value. Since the occurrence of uncertainty differs for each section, the final uncertainty delay is calculated by adding up the delay times in each section.

[0084] If it were possible to classify the occurrence of uncertainty in each section into patterns, the number of layers of final uncertainty delay would equal the number of combinations of the number of sections and occurrence patterns. As a result of calculating the uncertainty delay for a certain set of patterns Si, the probability that drone 300 will arrive at the desired arrival time T is the occurrence probability of that pattern, and can be calculated as the joint probability of each event as follows using the following equation (2).

[0085] Probability that drone 300 will arrive at time T Pr(Si, T) = Probability that no trouble will occur, such as aircraft trouble Pr(N) × Probability that wind conditions (first uncertainty) are correct Pr(E) × Probability that second uncertainty is correct Pr(M) × × Probability that adjustment will occur Pr(A) (2)

[0086] Assuming that there is no uncertainty between the time when this drone 300 arrives and the time when it takes off, the port will be occupied with the same probability for the time from arrival at the port to the completion of takeoff. The probability that the takeoff and landing port of this arrival destination will be occupied by this drone 300 is calculated.

[0087] The occupancy probability is the probability that the target aircraft will be at the target port (approaching (descending)) at the target time. The probability distribution obtained by summing up the probability of arrival at this port Pr(Si, T) for all patterns is shown in Figure 9, and can be expressed as the probability distribution function F(t) based on the time from the earliest scheduled port arrival time TS to the latest scheduled takeoff completion time TE.

[0088] In addition, the usage plan optimization unit 708 can calculate the probability from arrival to takeoff in the same way as above, even when there is uncertainty between arrival at the port and completion of takeoff, such as charging time due to remaining fuel, remaining battery level, etc. In other words, the usage plan optimization unit 708 can increase the occupancy probability of the takeoff / landing port 306 of the mobile body by limiting the time that the mobile body drone 300 uses the takeoff / landing port 306 depending on the remaining energy of the mobile body drone 300, thereby allowing the mobile body to use the takeoff / landing port 306 preferentially.

[0089] In addition, the usage plan optimization unit 708 can change the occupancy probability of the takeoff and landing port 306 depending on the remaining flight time of the drone 300, which is an air vehicle.

[0090] The probability function F(t) of the probability of port occupancy by drone n obtained as above is recalculated so that the sum of all time periods during which drone n may arrive is 1, and this is taken as the probability function Fn(t).

[0091] If the takeoff / landing port itself is unavailable, the entire time period during which arrivals are possible will not be continuous, but will be divided by unavailable time periods. In that case, the maximum time span will not change, so the probability of port occupancy will increase within the range in which the port is available. For example, this applies when an intrusion detection sensor is installed at the takeoff / landing port and there is an intrusion on the port, or when there is an aircraft still present on the port despite the right of use having expired due to emergency maintenance, etc.

[0092] When drone 300, an aircraft (mobile body) making an emergency landing at takeoff and landing port 306, is approaching takeoff and landing port 306, the port occupancy probability calculation unit 707 calculates the port occupancy probability for a time period excluding the time period of the emergency landing.

[0093] In addition, a drone detector (mobile object detector) 112 that detects drones 300, which are flying objects (moving objects) occupying the takeoff and landing port 306, is placed at the takeoff and landing port 306, and a port occupancy probability calculation unit 707 calculates the occupancy probability based on the detection signal from the drone detector 112, excluding the time period when the takeoff and landing port 306 is occupied by the drone 300.

[0094] Similarly, when an aircraft requiring an emergency landing has priority to occupy a port, this can be handled by locking the available time period for the takeoff and landing port.

[0095] Next, in step S808, the port usage plan optimization unit 708 aggregates, from the port usage plan 709, the port occupancy probability of the arrival / departure port of the destination for which the usage right has already been set.

[0096] The port usage plan 709 stores the setting state of the usage rights of the target departure and arrival ports at each time.

[0097] The setting state of the right of use is set for each aircraft, including the time, aircraft ID, occupancy probability, and maximum flight time. The aggregated port occupancy probability is, for example, as shown in FIG.

[0098] In Figure 8, the port occupancy probability Pr(C1) 1001 of aircraft C1 and the port occupancy probability Pr(C2) 1002 of aircraft C2, for which usage rights have already been set and which were stored in the port usage plan 709, are superimposed on the port occupancy probability Pr(C3) 1003 of the aircraft calculated in step S807.

[0099] Each port occupancy probability does not reach a certain value, and the sum of port occupancy probabilities 1001 and 1002, Pr(C) = Σ 2 n=1Pr(Cn) is also assumed to be equal to or less than this value. This value is treated as the threshold for the port occupancy probability. This threshold is set in order to take into consideration unpredictable events in advance. For example, the route of the drone 300 may be obstructed by a bird or other flying object, causing a detour, or a disaster such as a fire may occur on the route, causing a delay due to the detour. By providing these as probabilities in advance, it becomes possible to take into consideration unpredictable events.

[0100] Next, in step S809, the port occupancy probability is optimized by the port usage plan optimization unit 708. The optimization of the port occupancy probability will be explained with reference to the conceptual diagram shown in FIG. 11 and the processing flow in FIG.

[0101] In step S1201 of FIG. 10, the sum of the occupancy probabilities 1001 and 1002 of the devices for which the usage rights have already been set and stored in the port usage plan 709, and the port occupancy probability 1003 calculated in step S807 is calculated.

[0102] In step S1202, the sum of the port occupancy probabilities calculated in step S1201 is compared with a threshold, and if the sum of the port occupancy probabilities is smaller than the threshold, it is determined that optimization is unnecessary and the process ends. If the sum of the port occupancy probabilities is equal to or greater than the threshold, the process proceeds to step S1203.

[0103] Step S1203 selects the drone 300 with the minimum occupancy probability and time expansion margin. In Fig. 9, the time expansion margin 1101 of the drone 300 with the right to use the occupancy probability 1001 and the time expansion margin 1102 of the drone 300 with the right to use the occupancy probability 1002 are compared, and the occupancy probability 1002 with the longest time expansion margin is selected.

[0104] In step S1204, the remaining flight time of the drone 300 selected in step S1203 is extended by a set amount of time, and the occupancy probability is recalculated. Since the port occupancy probability is recalculated so that the sum of the time periods is 1, it will decrease by the amount of time that the time period is extended.

[0105] 9, if it is extended to the flight margin time 1101, the probability will decrease to port occupancy probability 1110. Similarly, if the port occupancy probability 1002 is extended to time 1102, the probability will decrease to port occupancy probability 1120.

[0106] Next, in step S1205, the difference between the occupancy probability of the selected aircraft recalculated in step S1204, the sum of the occupancy probabilities calculated in step S1202, and a threshold value is compared, and if the sum of the occupancy probabilities including the occupancy probability of the selected aircraft recalculated in step S1204 is greater than or equal to the threshold value, the processing from steps S1203 to S1204 is repeated.

[0107] In step S1205, if the sum of the occupancy probabilities including the occupancy probability of the selected aircraft recalculated in step S1204 is smaller than the threshold value, the process proceeds to step S1206.

[0108] In step S1206, the occupancy probability is recalculated, and the adjustment process ends.

[0109] Next, in step S810 of FIG. 6, based on the port arrival time set in step S809, the time setting for granting port usage rights to each drone 300 in the port usage plan 709 is updated, and the plan is sent to the aircraft / facility usage plan determination unit 710 of the integrated operation management system 409, and the facility usage plan 711 is updated.

[0110] In addition, the port arrival time set in step S809 is transmitted to the aircraft / route selection unit 702, and based on the range of arrival times, the takeoff time is recalculated by the flight time prediction calculation unit (travel time prediction calculation unit) 706, and the aircraft usage plan 704 is updated.

[0111] In other words, the usage plan optimization unit 708 sets the probability that a mobile unit 105 will occupy the takeoff and landing port 306 by allowing multiple mobile units 105 to overlappingly use the takeoff and landing port 306, and updates the occupancy probability when the mobile unit 105 is operating, thereby calculating the order of occupancy and determining the order in which the mobile units 105 will use the takeoff and landing ports 306.

[0112] As a result of the above process, the integrated operation control system 409 is notified of the time adjustment of the drone 300's takeoff and landing port usage rights, and an application is made for railway vehicle usage rights for a departure time that is later than the drone 300's maximum delay time 606 (shown in Figure 4).

[0113] The railway traffic control system (second mobile traffic control device) 416 secures the right to use the railway vehicle from the time 608 when the railway vehicle 320 arrives at the platform 421 on the distribution connection system side to the time 609 when the railway vehicle 320 arrives at the platform 414 on the storage location side, after the time requested by the integrated traffic control system 409, and notifies the integrated traffic control system 409 of the result.

[0114] Next, the integrated operation control system 409 applies for the right to use the storage location 408 to store the goods from the time the railcar 320 arrives at the platform 414 at the storage location, receives the storage available time 610 from the storage location 408, and notifies the delivery matching platform 405.

[0115] Next, the delivery matching platform 405 notifies the order management system 404 of the confirmation of the order contents, and notifies the delivery request system 406 of the product delivery details.

[0116] Next, the delivery request system 406 notifies the seller 402 of the drone arrival time 602, which is the deadline for preparing the product with the corresponding ID at the delivery base 407.

[0117] At the end of the operation planning phase, the order management system 404 cooperates with the payment service 415 to carry out the customer's payment.

[0118] This completes the operation planning phase and transitions to the transportation phase.

[0119] In the transportation phase, goods are transported in the order of the bold arrows in Figure 3, and the time schedule is carried out according to the usage rights of each facility shown in Figure 4, which were planned in the operation planning phase. In the following, the operation of the system when changing and updating the usage rights will be described using as an example transportation by the first moving body (drone 300), which has many uncertainties and in which changes to the usage rights are made successively. In the following, the change of the usage rights in the transportation phase will be explained using the processing flow in Figure 11.

[0120] First, in step S1301, the seller 402 receives an order notification from the delivery request system 406.

[0121] Next, in step S1302, it is confirmed whether the product is in stock / due to arrive, and if it is out of stock, the process proceeds to step S1305 to execute a cancellation process. If it is in stock in step S1302, the process proceeds to step S1303.

[0122] In step S 1303 , the seller 402 transports the product to the delivery base 407 .

[0123] Next, in step S1304, it is confirmed whether the product has arrived by the designated registration time. If the product has not arrived, the process proceeds to step S1305, where a cancellation process is executed. If the product has arrived in step S1304, the process proceeds to step S1306.

[0124] In step S1306, the arrival of the goods to be transported is notified to the drone operation management system 411, and in step S1307, the status of the drone 300 scheduled to transport the goods as planned in step S507 is confirmed.

[0125] In step S1308, if the planned aircraft has arrived at the takeoff / landing port 412 on the delivery base side, the process proceeds to step S1310. In step S1308, if the planned aircraft has not yet arrived, the facility usage plan 711 is checked in step S1309 to see if there is an alternative aircraft or a change in the plan, and if there is a change in the plan, the process returns to step S1307.

[0126] In step S1309, if there is no change in the plan, the process waits until the target aircraft arrives at the takeoff / landing port 412 (step S1308).

[0127] Next, in step S1310, the goods are transported to the takeoff and landing port 412 at the distribution base and loaded onto the drone 300.

[0128] In step S1311, after confirming that the product is loaded onto the aircraft, the drone traffic management system 411 is notified that it is ready for takeoff, and in step S1312, a flight readiness flag for the aircraft is set in the aircraft usage plan 704 of the drone traffic management system 411.

[0129] Next, the drone control system 307 issues a flight command to the drone 300 that is ready for flight, and causes it to take off from the takeoff and landing port 412. Operation after takeoff is performed according to the command of the drone control system 307.

[0130] Next, in step 1314, the drone control system 307 is notified of the estimated arrival time based on the progress at the checkpoint. The drone 300 flies according to the target position (waypoint) and operation speed specified by the drone control system 307. The output from the position and orientation sensor 712 incorporated in the aircraft control device 303 mounted on the drone 300 is notified to the aircraft position management unit 713 of the drone control system 307 by the communication device 304.

[0131] The drone position management unit 713 manages the drone positions of all drones under its control, and transmits the acquired positions of each drone 300 to the estimated arrival time calculation unit 714, which calculates the estimated arrival time. The estimated arrival time is calculated by dividing the remaining route distance by the standard speed.

[0132] Furthermore, the calculated estimated arrival time is sent to the port occupancy probability update unit 715 of the drone operation management system 411, and the port occupancy probability is calculated based on the position of the drone 300 and the time. The port occupancy probability can be updated in a manner similar to that of step S807, and the range of estimated arrival times is calculated using uncertainties on the route from the current position to the takeoff and landing port on the delivery connection system 411 side, as shown in the following formula (3). (Estimated arrival time) = (remaining route distance / standard speed) + (uncertainty delay on remaining route) + (position acquisition time) (3)

[0133] Since only the uncertainty on the remaining route from the time the drone 300's position was acquired is taken into consideration, the range of the expected arrival time is narrower than in step S807. Furthermore, narrowing the range increases the kurtosis of the port occupancy probability, increasing certainty. As in step S808, the port usage plan optimization unit 708 aggregates the updated port occupancy probabilities of other drones 300 in operation from the port usage plan 709, optimizes the port occupancy probability in the same manner as in step S809, and updates the port usage plan 709.

[0134] The port occupancy probabilities obtained from all drones 300 in operation all have higher kurtosis than in the planning phase, there is less overlap with the port occupancy probabilities of other drones, and each port occupancy probability is high enough to almost satisfy the threshold value, so that as the takeoff and landing port 306 approaches, the occupancy probabilities become independent, and safety is maintained by taking off and landing in the order determined here during landing, as described below.

[0135] Next, in step S1315, if the change in the estimated arrival time obtained in step S1314 is greater than or equal to a threshold value compared to the time of planning, the port usage plan optimization unit 708 of the drone traffic management system 411 updates the plan based on information with higher certainty.

[0136] If the estimated arrival time is almost the same as in the planning phase, and there is no change by more than the threshold, the process proceeds to step S1322. If there is a change by more than the threshold and the change is in the direction of an advance in step S1315, the process proceeds to step S1316. If there is a delay in step S1315, the process proceeds to step S1318.

[0137] In step S1316, the port usage plan optimization unit 708 of the drone traffic management system 411 notifies the aircraft / facility usage plan determination unit 710 of the integrated traffic management system 409 of the new arrival time.

[0138] In step S1317, if the new arrival time is available in the delivery connection system 410 side for the use of the takeoff / arrival port, the integrated operation control system 409 advances the port arrival time 605 and proceeds to step S1322.

[0139] If the estimated arrival time is delayed, in step S1318, the port usage plan optimization unit 708 of the drone traffic management system 411 notifies the aircraft / facility usage plan determination unit 710 of the integrated traffic management system 409 of the new arrival time.

[0140] Next, in step S1319, if the new arrival time is available in the port usage rights on the distribution connection system 410 side, the integrated operation control system 409 determines whether or not the port control area departure time 606 needs to be extended, and proceeds to step S1320. This is a measure to deal with the case where more energy than expected is consumed due to a delay in operation, and therefore a charge time is required immediately before the port control area departure time.

[0141] In step S1320, it is determined whether or not the port use right needs to be extended in step 1319. If the port use right does not need to be extended, the process proceeds to step S1322. If the port use right needs to be extended, there is a risk that loading onto a railroad car cannot be completed, so the user is notified of the need to change the loading destination to an alternative means of transport, and the user 400 is notified of the arrival delay.

[0142] Next, in step S1322, it is determined whether the drone 300 has arrived in the port control area where it will prepare to land. If it has arrived in the port control area, the process proceeds to step S1323, and if it has not yet arrived in the port control area, the process returns to step S1314 and subsequent steps.

[0143] In step S1323, after receiving port landing permission from the drone control system 307, the drone lands at the takeoff and landing port 306. The operation design unit 716 of the drone control system 307 receives the estimated arrival time of the drone 300 from the estimated arrival time calculation unit 714, acquires the port usage plan 709 of the drone traffic management system 411, sets landing permission in the aircraft position management unit 713 in the order of priority between the arriving drone 300 and other drones 300, and communicates a landing instruction from the aircraft position management unit 713 to the drone 300.

[0144] Next, in step S1324, after the drone 300 lands at the takeoff and landing port 306, the goods are transported to the platform 421 by the inter-vehicle transport vehicle 310 in accordance with instructions from the delivery connection system 410, and are loaded onto the railcar 320 by the departure time.

[0145] Next, in step S1325, the railcar 320 follows safety instructions from the railroad control system 322 and operation instructions from the railroad traffic control system 416 to transport the railcar 320 to the platform 414 where the target storage location 408 is located.

[0146] Finally, in step S1326, the goods are transported from the railcar 320 to the storage location 408, and the goods are received by the user 400, completing the transport of the goods.

[0147] The above is a rough outline of the processing flow of the mobile transportation system 1.

[0148] By implementing the takeoff and landing control described above, it becomes possible to allow multiple aircraft to approach a single takeoff and landing port simultaneously from the planning stage onwards, thereby enabling the takeoff and landing port to be used safely and efficiently.

[0149] According to embodiment 1 of the present invention, when multiple drones 300 approach a single take-off and landing port 412, it is possible to provide a mobile object traffic management device, a mobile object traffic management system, and a mobile object traffic management method that enable safe and efficient take-off and landing during all available time periods at the take-off and landing port 412.

[0150] Example 2 Next, a second embodiment of the present invention will be described.

[0151] FIG. 12 is a schematic configuration diagram of a mobile transportation system (mobile object traffic control system) 1A in which a plurality of mobile objects are linked together according to the second embodiment.

[0152] In the mobile transport system 1 in the first embodiment shown in Fig. 1, the delivery base / departure point 104 and the storage location / arrival point 108 are located separately, but in the second embodiment shown in Fig. 12, the delivery base / departure point 104 and the delivery base / storage location 130, which also serves as the storage location / arrival point 108, are located at two locations. In other words, it is possible to deliver goods and the like from both directions using the first mobile unit 105 and the second mobile unit 107.

[0153] That is, goods or the like travel from one distribution base / storage location 130 via the first mobile object 105, the inter-mobile object connection hub 106, and the second mobile object 107 to arrive at the other distribution base / storage location 130.

[0154] The example shown in Fig. 1 and the example shown in Fig. 12 differ in whether or not the product etc. can be moved in both directions, but the actions and operations are the same. Therefore, the explanation of the actions and operations of the example shown in Fig. 12 will be omitted.

[0155] In the second embodiment, the same effects as those in the first embodiment can be obtained, and the present invention can be applied to a mobile object operation control system capable of transporting goods and the like in both directions from distant areas.

[0156] Although the aircraft for transporting luggage is unmanned, development is underway to expand it to a manned aircraft (so-called flying car) in the future. Therefore, the present invention proposes a takeoff and landing system that can be applied not only to unmanned aircraft but also to manned aircraft.

[0157] Furthermore, the aircraft is not limited to the multi-rotor type, but also includes other autonomously flying aircraft.

[0158] The present invention is not limited to the above-mentioned embodiment, but includes various modified examples. For example, the above-mentioned embodiment has been described in detail to easily explain the present invention, and is not necessarily limited to those including all of the configurations described. Also, it is possible to replace a part of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add the configuration of another embodiment to the configuration of one embodiment. Also, it is possible to add, delete, or replace a part of the configuration of each embodiment with another configuration. [Explanation of symbols]

[0159] 1, 1A... Mobile transport system (mobile operation management system), 100... User, 102... Matching / buying and selling service system, 103... Seller / mobile person, 104... Delivery base / departure point, 105... First mobile object, 106... Mobile object connection hub, 107... Second mobile object, 108... Storage location / arrival point, 109... Integrated operation management system, 110... Infrastructure, 111... User / seller, 112... Drone detector, 130... Delivery base / storage location, 300... ··Drone, 301···Main body, 302···Rotor, 303···Flight control device, 304···Communication device, 305···Transportation object, 306···Takeoff and landing port, 307, 322···Control system, 310···Mobile transport aircraft, 320···Railway vehicle, 321···Terminal, 322···Railway control system, 400···User, 401···Matching / buying and selling service, 402···Seller, 403···Inventory / reservation management system, 404···Order management system, 405·· ·Delivery matching platform, 406···Delivery request system, 407···Delivery base, 408···Storage location, 409···Integrated operation management system, 410···Delivery linking system, 411···Drone operation management system, 412···Take-off and landing port, 413···Wind condition and environmental information system, 414, 421···Platform, 415···Payment service, 416···Railway operation management system (second mobile object operation management device), 701···Facility use time calculation unit, 702·· ·Aircraft / route selection unit, 703···Route DB, 704···Aircraft utilization plan, 705···Uncertainty parameter calculation unit, 706···Flight time prediction calculation unit, 707···Port occupancy probability calculation unit, 708···Port utilization plan optimization unit, 709···Port utilization plan, 710···Aircraft / facility utilization plan determination unit, 711···Facility utilization plan, 712···Position and attitude sensor, 713···Aircraft position management unit, 714···Predicted arrival time calculation unit, 715···Port occupancy probability update unit, 716···Operation design unit

Claims

1. A mobile object operation management device for managing the operation of a plurality of mobile objects that carry objects to be transported, which are goods or people, and move from a departure point to a destination point, A travel time prediction calculation unit that calculates a travel time of the moving object; an occupancy probability calculation unit that calculates an occupancy probability that a plurality of moving bodies occupy a takeoff / arrival port at which the moving bodies take off and land, based on the uncertainty of the travel time calculated using information affecting the operation of each of the plurality of moving bodies; a usage plan optimization unit that plans the port so that it is occupied by a plurality of the mobile objects at all times; A mobile object operation control device comprising:

2. The mobile object traffic control device according to claim 1, The usage plan optimization unit is characterized in that it allows multiple mobile bodies to use the take-off and landing port overlappingly based on the probability that multiple mobile bodies will occupy the take-off and landing port, and updates the occupancy probability when the mobile bodies are operating, thereby calculating the order of occupancy and determining the usage priority of the take-off and landing ports for the multiple mobile bodies.

3. The mobile object traffic control device according to claim 1, A mobile object operation management device, characterized in that the uncertainty of the travel time is calculated by calculating a fluctuation range of the travel time based on the type of the mobile object and its effect on motion performance.

4. The mobile object traffic control device according to claim 1, The mobile object operation management device is characterized in that the usage plan optimization unit increases the probability of the mobile object occupying the take-off and landing port by limiting the time that the mobile object uses the take-off and landing port based on the remaining energy of the mobile object, thereby allowing the mobile object to use the take-off and landing port on a priority basis.

5. The mobile object traffic control device according to claim 1, A mobile object operation management device characterized in that the mobile object is an aircraft, and the usage plan optimization unit changes the occupancy probability of the takeoff and landing port depending on the remaining flight time of the aircraft.

6. The mobile object traffic control device according to claim 1, A mobile object operation management device characterized in that the occupancy probability calculation unit calculates the port occupancy probability for a time period excluding the time period during which the mobile object making an emergency landing at the takeoff / landing port is approaching the takeoff / landing port.

7. 7. The mobile object traffic control device according to claim 6, A mobile object operation management device characterized in that the mobile object is an airborne object, a mobile object detector for detecting the airborne object is arranged at the takeoff and landing port, and the occupancy probability calculation unit calculates the occupancy probability based on the detection signal from the mobile object detector, excluding the time period when the takeoff and landing port is occupied by the airborne object.

8. 2. The mobile object traffic control device according to claim 1, The plurality of moving bodies include a first moving body which is an aircraft, and a second moving body which moves the transportation object moved to a takeoff and landing port where the first moving body takes off and lands, to a storage location or a destination; A mobile object traffic control device characterized in that it is used in a mobile object traffic control system having a second mobile object traffic control device that manages the operation of the second mobile object.

9. The mobile object traffic control device according to claim 8, The mobile object traffic management system includes: A mobile object operation control device comprising an integrated operation control system that manages the operation of the first mobile object and the second mobile object in an integrated manner.

10. In a mobile object operation management device, a mobile object operation pipeline method is provided for managing the operation of a plurality of mobile objects that carry objects to be transported, which are goods or people, and move along a designated route from a departure point to a destination point, Calculate a travel time of the moving object; calculating an occupancy probability that a plurality of the moving bodies will occupy a port from which the moving bodies depart and arrive based on the uncertainty of the travel time calculated using information affecting the operation of each of the plurality of the moving bodies; scheduling said port to be occupied by said mobile unit at all times; A mobile object operation management method comprising:

11. The mobile object operation control method according to claim 10, A mobile object operation management method characterized by setting an occupancy probability for the mobile object to occupy the take-off and landing port by allowing multiple mobile objects to overlap in using the take-off and landing port, and updating the occupancy probability when the mobile object is operating, thereby calculating the order of occupancy and determining the order of use of the take-off and landing ports for the multiple mobile objects.

12. The mobile object operation control method according to claim 10, A mobile object operation management method, characterized in that the uncertainty of the travel time is calculated by calculating a fluctuation range of the travel time based on the type of the mobile object and its effect on motion performance.

13. The mobile object operation control method according to claim 10, A mobile object operation management method characterized by increasing the probability of the mobile object occupying the take-off and landing port by limiting the time the mobile object uses the take-off and landing port based on the remaining energy of the mobile object, thereby allowing the mobile object to use the take-off and landing port on a priority basis.

14. The mobile object operation control method according to claim 10, A mobile object operation management method, characterized in that the mobile object is an aircraft, and the occupancy probability of the takeoff and landing port is changed depending on the remaining flight time of the aircraft.

15. The mobile object operation control method according to claim 10, A mobile object operation management method characterized in that, when a mobile object making an emergency landing at the takeoff / landing port is approaching the takeoff / landing port, the port occupancy probability is calculated for a time period excluding the time period during which the emergency landing is made.

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