Air traffic control device, control system, and control method

Abstract

We provide control systems and other equipment that enable safe operation management in a variety of situations. [Solution] The memory unit 601 stores the position of the aircraft. The decision unit (flight plan decision unit 603) uses the communication difficulty distance, which indicates the length of the self-position estimation difficulty region, which is a region in the flight path where it is difficult for an individual aircraft to estimate its own position, to determine the number of aircraft that can estimate their own position. The creation unit (flight plan decision unit 603) uses the number of aircraft, the flight path, and the position of the aircraft to determine the aircraft that will travel along the flight path and create a flight plan for each aircraft. The output unit 604 outputs the flight plan and information about the aircraft that will travel along the flight path.

Description

[Technical Field]

[0001] The present invention relates to a control device, a control system, and a control method. [Background technology]

[0002] The use of drones and other aircraft for railway inspection and maintenance is increasing. To ensure safety, it is necessary for control stations to be able to determine the position of aircraft even in areas where communication is difficult, such as tunnels. Regarding technologies related to areas where communication is difficult, there are, for example, Patent Documents 1 and 2.

[0003] Patent Document 1 states that "If the flight plan generation unit determines that the planned flight path included in the target information is inappropriate, it generates a recommended flight path different from the input flight path. For example, the flight plan generation unit generates a flight plan that includes a recommended flight path that allows imaging of the target identified from the acquired target information and transmits the image image that satisfies the required image quality via wireless communication."

[0004] Patent Document 2 states that, "In areas with high mountains, a base station can transmit and receive radio waves to and from a terminal drone flying on the opposite side of the mountain by relaying signals from a relay drone." [Prior art documents] [Patent Documents]

[0005] [Patent Document 1] Patent No. 7055926 [Patent Document 2] Japanese Patent Publication No. 2021-169304 [Overview of the project] [Problems that the invention aims to solve]

[0006] The technologies described in Patent Documents 1 and 2 do not take into account situations where multiple aircraft pass through communication-difficult areas. Therefore, there is a risk that safe flight management may not be possible in various situations, including when multiple aircraft pass through communication-difficult areas.

[0007] In view of the above problems, the object of the present invention is to provide a control device, a control system, and a control method that enable safe operation management in a variety of situations. [Means for solving the problem]

[0008] To achieve the above objective, an example of the control device of the present invention includes: a storage unit for storing the position of an aircraft; a determination unit for determining the number of aircraft capable of self-position estimation of the aircraft, using a communication difficulty distance which indicates the length of a self-position estimation difficulty region, which is a region in the flight path where self-position estimation of an individual aircraft is difficult; a creation unit for determining the aircraft passing through the flight path and creating a flight plan for each aircraft, using the number of aircraft, the flight path, and the position of the aircraft; and an output unit for outputting the flight plan and information relating to the aircraft passing through the flight path. [Effects of the Invention]

[0009] According to the present invention, safe operation management becomes possible even in a variety of situations. Other issues, configurations, and effects will be clarified by the following description of embodiments. [Brief explanation of the drawing]

[0010] [Figure 1] An example of an application scenario for the present invention. [Figure 2] Control system hardware configuration [Figure 3] Station terminal hardware configuration [Figure 4] Aircraft hardware configuration [Figure 5] Concepts of drone flight methods [Figure 6] Control system software configuration [Figure 7]Software Configuration of the Aircraft [Figure 8] Processing Flow in the Control System [Figure 9] Flight Plan Screen on the Station Terminal [Figure 10] Contents of the Flight Plan [Figure 11] Cooperation Processing Flow between Drones [Figure 12] Processing Flow for Calculating Areas Difficult to Estimate Self-Position [Figure 13] Positional Relationship among the Positioning Satellite, Tunnel, and Drone [Figure 14] Areas with Difficult Communication [Figure 15] Drone Position Display Screen on the Station Terminal [Figure 16] Drone Position Magnified Display Screen on the Station Terminal

Modes for Carrying Out the Invention

[0011] Hereinafter, embodiments of the present invention will be described with reference to the drawings. Various components of the present invention do not necessarily have to exist independently of each other. It is allowed that one component is composed of a plurality of members, a plurality of components are composed of one member, a certain component is part of another component, and a part of a certain component overlaps with a part of another component, etc. Also, in each figure, the same reference numerals are given to equivalent elements, and repeated descriptions are omitted as appropriate.

[0012] [Embodiment 1] Embodiment 1 shows the basic operation of the control device.

[0013] FIG. 1 is an example of an application scenario of the present invention. It is assumed a scene where drones 103 to 105 are inspecting while flying over the railway line 101. At that time, a tunnel 102 exists in the traveling direction of each drone. Also, a control device 111 is installed to make a flight plan, give flight instructions to each drone, and grasp the positions of each drone.

[0014] The control device 111 does not necessarily need to be installed near the tracks being inspected; for example, it can be installed inside the railway company's facilities or at a station. Also, the number of drones does not need to be three; any number can be used.

[0015] Figure 2 shows the hardware configuration of the control system. The control system is connected to a control device 111 and a network 230, and includes station terminals 210, 211, and 212 installed at each station. Station terminals 210, 211, and 212 are used by users 220, 221, and 222, respectively. The control device 111 includes a processor (CPU) 201, memory 202, communication device 203, and storage device 204. The processor 201 also receives inquiries and commands from each station terminal via the communication device 203.

[0016] Furthermore, the number of station terminals is not limited to the three shown in Figure 2; multiple terminals may be installed at each station, and the number of stations with terminals can be any number. The number of users is not limited to three; it is also acceptable for multiple people to share one station terminal, or for one person to use multiple station terminals. Network 230 may be an intranet installed by the railway operating company, or it may be the internet.

[0017] Figure 3 shows the hardware configuration of station terminals 210-212. Station terminals 210-212 consist of a processor (CPU) 301, memory 302, communication device 303, storage device 304, input device 305, and display device 306. Users 220-222 connect the station terminal to the control device 111 using the communication device 303 to call up the necessary screen and display it on the display device 306. Users 220-222 then operate the user interface displayed on the display device 306 using the input device 305. A keyboard, mouse, or stylus pen is preferred as the input device.

[0018] Figure 4 shows the hardware configuration of drones 103 to 105. Each drone is equipped with a processor (CPU) 405, memory 406, communication device 407, and storage device 404. The processor 405 is connected to the memory 406, communication device 407, and storage device 404. The processor 405 is also connected to a beacon 401, a camera 402, and a GNSS (Global Navigation Satellite System) 403.

[0019] The beacon 401 is a device used by each drone to determine its position relative to another and to communicate the results to each other. The camera 402 is used by the drone to perceive its surroundings while in flight, and in particular to recognize the railway tracks 101. By using the results, the drone can fly in a way that does not deviate from the railway tracks 101. LiDAR (Light Detection and Ranging) may be used instead of camera 402.

[0020] GNSS403 is a device that measures its own position using satellite radio waves such as GPS (Global Positioning System). Processor 405 transmits the position of each drone to the control unit 111 via communication device 407. This includes not only the self-positioning result from GNSS403 but also the positioning result of other aircraft from beacon 401. This information is then communicated at regular intervals.

[0021] Figure 5 is a conceptual diagram of the flight method of each drone in this embodiment. Drones 103 to 105 fly through tunnel 102 for inspection. First, drone 104 waits without entering tunnel 102, and drones 105 and 103 enter the tunnel first. Drones 105 and 103 fly through tunnel 102 while maintaining a certain distance from each other, and drones 105 and 103 determine each other's positions using the beacons 401 they each hold.

[0022] Drone 103, which is closest to the entrance, uses the communication device 407 or beacon 401 to transmit its own position and the position of drone 105 to drone 104. In other words, drone 103 inside tunnel 102 acts as a relay for drone 104 just before tunnel 102. Then, drone 104 uses the communication device 407 to transmit the positions of all three drones to the control device 111.

[0023] While repeating the above process, drones 105 and 103 fly through tunnel 102. After drone 105 exits tunnel 102, drone 104 enters tunnel 102, and drone 105 waits at the exit of tunnel 102. At this time, drone 105 takes on the role previously played by drone 104, and drones 104 and 103 determine each other's positions using beacons. Drone 103, being closer to the exit, uses communication device 407 or beacon 401 to transmit its own position and the position of drone 104 to drone 105. Then, drone 105 uses communication device 407 to transmit the positions of all three drones to the control device 111.

[0024] After drones 103 and 104 exit tunnel 102, the above process ends, and the three drones resume flying together. Although this embodiment shows an example with three drones, the number of drones is arbitrary and will be determined according to the process described below.

[0025] Figure 6 shows the software configuration of the control device 111. The memory unit 601 is implemented in the memory device 204 and holds information necessary for performing track inspections by drones, such as information on drones managed at each station and information on routes managed by the operating company. The OD receiver unit 605 receives the starting point for the inspection and the destination set at station terminals 210-212.

[0026] The flight path setting unit 606 sets a flight path based on the received departure point and destination. Note that the flight path is limited to railway lines, and each drone does not fly over roads or houses. The self-position estimation difficulty area identification unit 602 identifies areas on the flight path where it is difficult for each drone to estimate its own position. These are areas where it is difficult for the aircraft to estimate its own position on its own, such as areas where standalone positioning by GNSS 403 is difficult, or areas where self-position estimation by SLAM using camera 402 is difficult.

[0027] Information (location, dimensions, etc.) about areas where self-position estimation is difficult (e.g., tunnels) is included in the route information stored in the memory unit 601, for example. If the control device 111 is equipped with an input device, the information about areas where self-position estimation is difficult may be input using that input device, or the information about areas where self-position estimation is difficult may be input using a terminal (station terminal, tablet, smartphone, etc.) connected to the control device 111 via the network 230.

[0028] The flight plan determination unit 603 determines the number of drones and / or a method of cooperation for the drones to enable self-position estimation, based on the self-position estimation difficulty area identification unit 602. The cooperation method means that, when flying multiple drones, a master drone is determined and an ad-hoc network is formed by the multiple drones.

[0029] Furthermore, the flight plan determination unit 603 determines a flight plan based on the number of aircraft and / or the cooperation method, the flight path, and the drone information managed at each station. The output unit 604 then sends the information determined by the flight plan determination unit 603 back to the station terminal that transmitted the departure and destination information.

[0030] Figure 7 shows the software configuration of drones 103-105. First, the communication device 407 receives the flight plan 705 from the control device 111 and stores it in the memory device 404.

[0031] The track recognition unit 701 recognizes the track 101 based on the image obtained by the camera 402. The method for recognizing the track 101 can be, for example, the method disclosed in Japanese Patent Application Publication No. 2019-209734, and the drone flies along the recognized track. In other words, the flight width setting unit 702 and the flight altitude setting unit 703 each have the function of setting the flight position of the drone.

[0032] The flight width setting unit 702 is set to be in the middle of the two rails in the lateral direction, and the flight altitude setting unit 703 is set to be in the vertical direction so as to keep the altitude within a predetermined range. Since the installation width of the two rails is constant, the height of the drone can be determined by knowing how far apart the two rails recognized by the track recognition unit 701 are in the camera image.

[0033] The other aircraft position calculation unit 706 determines the positions of other aircraft based on the results measured by the beacon 401. In the case of drone 103 in this embodiment, it determines the positions of drone 104 and / or drone 105. The results of determining these positions are then transmitted to the control unit 111 via the communication device 407.

[0034] The flight control unit 704 then controls the flight path based on the set width and height, the flight plan 705, and the results from the other aircraft position calculation unit 706. The reason the flight control unit 704 uses the results from the other aircraft position calculation unit 706 is to maintain a certain distance from other aircraft.

[0035] Figure 8 shows the processing flow in the control system. First, in step 801, one of the users 220 to 222 inputs the destination at one of the station terminals 210 to 212. This destination information is transmitted to the control unit 111 via the communication device 303 of the station terminal, and steps 802 and below are processed by the processor 201 of the control unit 111. Next, in step 802, the flight path is determined.

[0036] The processor 201 can calculate the flight path by applying Dijkstra's algorithm to the track information stored in the memory unit 601, for example, as a set of nodes and links. At the same time, the processor 201 can also calculate the estimated time of passage through each node, which may be used as waypoint information (coordinates, estimated time of passage).

[0037] In this embodiment, it is assumed that the tunnel 102 is an area where communication with the GNSS 403 positioning satellites and / or with the control device 111 is difficult, and therefore it is an area where self-position estimation is difficult. For this reason, in the next step 803, the processor 201 determines whether or not there is a tunnel on the calculated path. If there is no tunnel, one drone is sufficient for inspection, and the processor 201 proceeds to step 807 and sets the number of drones to 1.

[0038] If a tunnel exists, the processor 201 proceeds to step 804 or later. First, in step 804, it obtains the longest tunnel length along the path. Next, in step 805, the processor 201 obtains the communication range specification of the beacon 401. This is included in the equipment specifications (not shown) stored in the memory unit 601. Next, in step 806, the processor 201 calculates the number of drones required for inspection. The number is set to, for example, roundup(longest tunnel length / beacon communication distance) + 1, so that when one drone exits the tunnel, a drone waiting at the entrance can enter the tunnel. Here, roundup is a function that rounds up its argument and returns an integer.

[0039] In the next step 808, the processor 201 determines whether the required number of drones is greater than the number of drones managed at the station. If the required number of drones is less than the number of drones managed at the station, the drones managed at the station can be used, and the processor 201 proceeds to step 810 to output the number of drones, the source of the drones, and the flight path to the station terminal.

[0040] If the number of drones required is greater than the number of drones managed, it is necessary to procure drones managed by other stations. In this case, the process proceeds to step 809, where processor 201 determines that the station from which to procure the missing drones is the station closest to the destination. After that, processor 201 proceeds to step 810 and outputs the number of drones, the drone procurement destination, and the flight path to the station terminal.

[0041] Furthermore, the master drone will be a drone under the management of the station where the station terminal for which the flight plan is being developed is located.

[0042] In this explanation, we assumed that communication was impossible throughout the entire tunnel. However, while communication may be possible within a certain distance from the tunnel entrance and exit, if we interpret the longest tunnel length as the communication-difficult distance, it becomes possible to create a flight plan that takes into account the communication-enabled area near the tunnel entrance and exit. Details of this will be explained in Example 2.

[0043] Figure 9 shows the flight planning screen 901 at the station terminal. Figure 9 will be explained in comparison with the flow chart in Figure 8.

[0044] When the station terminal connects to the control unit 111, the flight plan screen 901 is displayed, and the route information 909 stored in the memory unit 601 is displayed. The flight plan screen 901 also displays a flight plan button 920 and a flight status button 921. The flight plan button 920 is selected by the user when creating a flight plan, and is grayed out and cannot be selected when the flight plan screen 901 is displayed. The flight status button 921 is selected to display the position of the drone in flight.

[0045] First, the user operates the mouse, which is the input device 305, to position the mouse pointer 902 at the destination, and right-clicks to open the destination menu 903. Selecting "Set Destination" from the menu with a left-click sets point 904 as the destination. This corresponds to step 801. To clear the setting, select "Clear Destination". After the destination is set, the control device 111 calculates the route from station 930 to point 904. This corresponds to step 802.

[0046] Subsequently, route 905 is displayed on the flight plan screen 901. Tunnel 102 exists along the route, and its total length is displayed in the speech bubble 907. Furthermore, the number of drones to be procured at stations 930 and 931 is calculated in steps 806-809 and displayed in speech bubbles 908 and 910, respectively.

[0047] Once the above processes are complete, the user clicks the command transmission button 911, at which point the drones procured at stations 930 and 931 begin flight, and track inspection starts. The drones preferably begin flight either simultaneously with the master drone or when the master drone passes the station where each drone is procured. In the former case, each drone flies independently toward its destination but temporarily waits before tunnel 102. In the latter case, each drone flies toward its destination while joining the drone group, but waits before tunnel 102 if present. In either case, the processing after waiting is as shown in Figure 11.

[0048] Figure 10 shows the contents of the flight plan 705. Aircraft information 1002 is stored for each aircraft number 1001. Aircraft information 1002 consists of a departure point 1010, a destination point 1020, a departure time 1030, a number of waypoints 1040, waypoint information 1050, a station to which the aircraft belongs 1060, and a master flag 1070. The waypoint information 1050 is stored for each waypoint number 1040. The waypoint information 1050 consists of a waypoint 1051 and its passage time 1052. The departure point 1010, the destination point 1020, and the waypoint 1051 are expressed in terms of latitude, longitude, and altitude. The departure time 1030 and the passage time 1052 are expressed in terms of year, month, day, hour, minute, and second. The station to which the aircraft belongs 1060 indicates the station from which the drone was procured.

[0049] The master flag 1070 indicates whether the drone is the master or not. If it is the master, when the drone group approaches the tunnel, the drone will wait before the tunnel entrance and be responsible for informing the control unit 111 of the positions of the other drones via communication.

[0050] Figure 11 shows the processing flow for coordinated operations between drones in a tunnel. This is explained as a processing flow viewed from the perspective of a single drone (referred to as the "own drone").

[0051] First, in step 1101, the drone receives a command from the control unit 111 and begins flight. This is done by the user clicking the command transmission button 911. Next, in step 1102, the drone flies to the front of the tunnel 102 and waits for the other drones to arrive. Steps 1102 and 1103 are repeated until all drones have arrived.

[0052] Once all drones have arrived, step 1104 confirms whether you are the master or not. If you are the master, proceed to step 1109 and wait in front of tunnel 102. While waiting in front of tunnel 102, step 1110 transmits the positions of the other drones to the control unit 111. Step 1111 determines whether the other drone has left tunnel 102. If it has, step 1112 causes your drone to enter tunnel 102. If the other drone has not left tunnel 102, continue waiting in front of tunnel 102.

[0053] When the player aircraft enters tunnel 102, the other aircraft that has exited tunnel 102 becomes the master, and the process proceeds to the flow for when the player aircraft is not the master. In step 1105, the player aircraft, having entered tunnel 102, flies while recognizing the railway track 101 using camera 402. The method for recognizing the railway track 101 is as described above. Next, in step 1106, the player aircraft determines the position of the other aircraft using beacon 401. The player aircraft's position is also determined by the other aircraft, and they transmit their positions to each other. At this time, transmission is not possible to other aircraft that cannot receive radio waves. Therefore, transmission inevitably occurs to other aircraft that are close to the player aircraft.

[0054] If step 1107 determines that the player's ship has exited tunnel 102, the ship proceeds to step 1108 and first waits at the exit of tunnel 102. At that time, step 1113 determines whether any other ships are already waiting at the exit of tunnel 102. If no other ships are waiting, the game proceeds to step 1115 and the player's ship becomes the master.

[0055] If the aircraft becomes the master, it proceeds to step 1116 to monitor the positions of other aircraft in tunnel 102, and transmits the positions of other aircraft to the control unit 111 in step 1117. If, in step 1113, another aircraft is already waiting, that other aircraft becomes the master. In this case, if it is determined in step 1114 that there is another aircraft in the tunnel, it remains waiting at the exit of tunnel 102, and when the other aircraft leaves tunnel 102, it proceeds to step 1118 to resume flight.

[0056] The main features of Example 1 are as follows:

[0057] As shown in Figure 6, the memory unit 601 stores the location of the aircraft (for example, its storage location). The decision unit (flight plan decision unit 603) uses the communication difficulty distance, which indicates the length of the self-position estimation difficulty region, which is a region in the flight path where it is difficult for an individual aircraft to estimate its own position, to determine the number of aircraft that can estimate their own position. The creation unit (flight plan decision unit 603) uses the number of aircraft, the flight path, and the positions of the aircraft to determine which aircraft will travel along the flight path and create a flight plan for each aircraft. The output unit 604 outputs information about the flight plan and the aircraft that will travel along the flight path.

[0058] By having a number of aircraft corresponding to the length of the region where self-position estimation is difficult communicate the positions of other aircraft measured by each other, self-position estimation can be performed in the region where self-position estimation is difficult. As a result, safe flight management becomes possible even in diverse situations.

[0059] The decision unit (flight plan decision unit 603), if there are multiple aircraft, uses the positions of the entrance and exit of the self-position estimation difficult region to determine how the multiple aircraft will cooperate in the self-position estimation difficult region (Figure 5).

[0060] This allows multiple aircraft to coordinate effectively from the entrance to the exit of the region where self-localization is difficult.

[0061] In detail, the decision unit (flight plan decision unit 603) determines the number of aircraft and the method of cooperation using the communication distance (beacon communication distance) between two adjacent aircraft in the self-position estimation difficult area.

[0062] This enables positioning and communication of aircraft in areas where self-position estimation is difficult. The number of aircraft is, for example, roundup(communication difficulty distance / beacon communication distance) + 1. The cooperation method is, for example, a master aircraft waits at the entrance of the area where self-position estimation is difficult, and other aircraft enter the area sequentially at intervals that do not exceed the beacon communication distance. When the leading aircraft reaches the exit, the leading aircraft waits as a master (substitute), and the aircraft that was waiting at the entrance enters the area where self-position estimation is difficult. Each aircraft in the area where self-position estimation is difficult relays its relative position to the master via an ad-hoc network using beacons, and the master converts the relative positions of the other aircraft into absolute positions and transmits the absolute positions of all aircraft to the control unit 111.

[0063] The creation unit (flight plan determination unit 603) selects aircraft to be managed at the departure point of the flight path. If the number of aircraft to be managed at the departure point is less than the number of aircraft determined by the determination unit (flight plan determination unit 603), the creation unit selects aircraft to be managed at a management location closer to the destination than the departure point (for example, a train station) (Figure 8).

[0064] This reduces the energy consumption of aircraft procured from management locations other than the departure point. In this embodiment, any missing aircraft are selected from those managed at the management location closest to the destination before the region where self-position estimation is difficult.

[0065] If there are multiple aircraft, the control device 111 designates at least one of them as the master. As shown in Figure 5, the master (drone 104) waits before the area where self-position estimation is difficult. Other aircraft enter the area where self-position estimation is difficult and transmit their positions to the master directly or indirectly. The master transmits its own position and the positions of the other aircraft to the control device 111.

[0066] This allows the control device 111 to utilize the master's position and the positions of other aircraft in areas where self-position estimation is difficult. In this embodiment, the other aircraft transmit their relative positions, which are determined using beacons, to the master. The master converts the relative positions of the other aircraft to absolute positions using its own absolute position, determined using GNSS, and the relative positions of the other aircraft. However, the control device 111 or each aircraft may convert the relative positions to absolute positions.

[0067] As mentioned above, in areas where self-localization is difficult, the positions of other aircraft are measured using beacons equipped on each aircraft. The positions of other aircraft are transmitted to the master via an ad-hoc network formed by the beacons.

[0068] This allows the master to receive the positions of other aircraft in areas where self-localization is difficult.

[0069] If there are multiple aircraft, the control system 111 designates at least one of them as the master. If the master's control location and the other aircraft's control locations are different, the other aircraft take off at the same time as the master, or take off when the master passes over the other aircraft's control location (Figure 9).

[0070] By having other aircraft take off simultaneously with the master, the size of the aircraft swarm or the length of the formation can be reduced. By having other aircraft take off when the master passes over their management area, the energy consumption of the other aircraft is reduced.

[0071] As shown in Figure 1, the control system comprises a control device 111 and aircraft (drones 103-105) that fly based on the flight plan created by the control device 111.

[0072] This enables self-localization in areas where self-localization is difficult.

[0073] [Example 2] In Example 1, the basic operation was shown, and all areas within the tunnel 102 were treated as difficult to estimate. In Example 2, however, a different method is shown for calculating the difficult-to-estimate-situate-region area, which is processed by the difficult-to-estimate-situate-region identification unit 602.

[0074] Figure 12 shows the processing flow for calculating the self-localization difficulty region. Step 1201 is processing using cellular communication quality, step 1202 is processing using GNSS communication quality, and step 1203 is processing using the number of visible GNSS satellites. The order of processing steps 1201 to 1203 is arbitrary. Then, in step 1204, the region with the largest size among the processing results of steps 1201 to 1203 is designated as the self-localization difficulty region. The details of the processing in steps 1201 to 1203 are described below.

[0075] In step 1201, a communication difficulty area is defined as an area where the communication quality of cellular communications such as LTE (Long Term Evolution) is below a threshold.

[0076] One known indicator of cellular communication quality is the SINR (Signal-to-Interference-plus-Noise Ratio). A SINR greater than a threshold indicates good communication quality, while a SINR less than a threshold indicates poor communication quality. The SINR is expressed by Equation 1.

[0077]

number

[0078] However, in formula 1, P Tx is the transmitted signal strength, PL(d) is the propagation loss at distance d, I is the interference strength (interference from adjacent base stations or other users), and N is the noise strength (system noise such as thermal noise).

[0079] The aforementioned PL(d) is a value calculated using the basic propagation loss formula in the ITU-R (International Telecommunication Union Radiocommunication Sector) model, which is shown in Equation 2.

[0080]

number

[0081] However, in equation 2, PL0 is the basic loss at the reference distance (usually considered to be 1m), n is the propagation loss index which depends on the tunnel shape and material, d is the distance, and X is the random loss.

[0082] As described above, it is possible to define SINR as communication quality, set a threshold, and consider communication difficult if the value falls below that threshold. Here, if we consider d to be the distance from the tunnel entrance / exit, it is possible to use SINR as the communication quality at any location within the tunnel.

[0083] In step 1202, the communication difficulty region is defined as the region where the communication quality with positioning satellites in GNSS403 is below a threshold. Specifically, the received signal strength shown in equation 3 can be used.

[0084]

number

[0085] However, in equation 3, Pr(d) is the received signal strength at distance d, Pt is the transmitted signal strength, n is the attenuation coefficient, and L is the loss.

[0086] For GNSS signal communication to be possible, the aforementioned Pr(d) must exceed the minimum level required for communication.

[0087] As described above, it is possible to define the received signal strength at distance d as communication quality, set a threshold, and consider communication difficult if the signal strength falls below this threshold. Here, if d is considered to be the distance from the tunnel entrance / exit, it is possible to use the received signal strength as the communication quality at any position within the tunnel. For example, the typical transmission strength of a GNSS satellite signal is -130 dBm, and the minimum receivable strength is -135 dBm, so it is possible to set the threshold for Pr(d) to -135 dBm and consider communication difficult if the signal strength falls below this threshold.

[0088] In step 1203, a communication difficulty area is defined as an area where the number of visible GNSS403 satellites is less than the required number. Generally, four or more visible satellites are required for GNSS positioning. Therefore, an area with fewer than four visible satellites is defined as a self-position estimation difficulty area. In this embodiment, a satellite is considered a visible satellite if there are no obstructions in the direction of the satellite from the user's position.

[0089] The elevation angle θ of a positioning satellite at a given observation point can be expressed by equation 4.

[0090]

number

[0091] However, in equation 4, the vector r r The geocentric vector of the observation point, vector r sr This is the relative vector between the satellite and the observation point.

[0092] Based on this, the elevation angle θ relative to all positioning satellites is determined at various points within the tunnel 102. By counting the number of satellites whose elevation angle θ is greater than the minimum elevation angle and whose direction is not obstructed, the number of visible satellites can be determined. If the number of visible satellites is less than 4, it is a region where self-position estimation is difficult. This will be further explained using Figure 13. The minimum elevation angle is the minimum elevation angle at which radio waves from GNSS403 can be received.

[0093] Figure 13 shows the positional relationship among the positioning satellite 1301, the tunnel 102, and the drone 104. At this time, let the height of the tunnel 102 be h t , the height of the drone 104 from the ground be h d , the distance of the drone 104 from the entrance of the tunnel 102 be d, the elevation angle of the positioning satellite 1301 at the position of the drone 104 be θ, and the visible angle at the position of the drone 104 be θ'. Note that the visible angle is the angle within the range where there is no obstacle. At this time, the visible angle θ' can be calculated by Equation 5.

[0094]

Equation

[0095] At this time, if θ < θ', the positioning satellite 1301 can be regarded as a visible satellite, but if θ > θ', the positioning satellite 1301 is not a visible satellite. Therefore, by obtaining the distance d at which the number of visible satellites is 4 or more, it is possible to obtain the self-position estimation difficult area. s

[0096] However, executing the above processing for every distance d will consume a large amount of computer resources. Therefore, in terms of implementation, it is also preferable to execute the above processing at regular intervals inside the tunnel 102.

[0097] Regarding the identification of the self-position estimation difficult area using cellular communication quality, GNSS communication quality, and the number of visible satellites, it will be further described while referring to FIG. 14. FIG. 14 shows an area where communication is difficult in cellular communication and GNSS communication, and an area where the number of visible satellites for GNSS positioning is insufficient. In the cellular communication, it is assumed that the communication is good up to the distance d from the entrance and exit of the tunnel 102, and the communication is difficult in the area 1401. Similarly, in the GNSS communication, it is assumed that the communication is good up to the distance d from the entrance and exit, and the communication is difficult in the area 1402. Similarly, in terms of the number of visible satellites, it is assumed that the communication is good up to the distance d from the entrance and exit c until, and the communication is difficult in the area 1401. Similarly, in the GNSS communication, it is assumed that the communication is good up to the distance d g from the entrance and exit, and the communication is difficult in the area 1402. Similarly, in terms of the number of visible satellites, it is assumed that the communication is good up to the distance d s ​Communication was good up to a certain point, but communication was difficult in area 1403.

[0098] In this embodiment, the largest area of ​​the region where communication is deemed difficult is defined as the region where self-position estimation is difficult. That is, d c d g d s The minimum value among them indicates the distance from the entrance / exit to the area where communication is difficult. In the case of Figure 14, d g Since this is the minimum value, area 1402 becomes a region where self-localization is difficult. The length of the communication difficulty region is given by the length of the tunnel, i.e., difficulty region length = ld g It becomes ×2. Note that d g Even if a value other than the minimum is obtained, the same process can be used to find the region where self-localization is difficult.

[0099] Then, by performing the same calculation for all tunnels along the route to determine the maximum length of the difficult area, and using this value instead of the longest tunnel length in step 806, it is possible to more accurately determine the required number of drones.

[0100] After the above process, if the user wishes to check the drone's flight status, they reconnect to the control unit 111 and access the flight plan screen 901. Next, when the user clicks the flight status button 921, the positions of drones 103-105 transmitted to the control unit 111 are displayed on the station terminal screen 1501, as shown in Figure 15. At this point, the flight status button 921 becomes gray and cannot be selected.

[0101] Furthermore, if you select area 1502 using the mouse pointer 902 in this state, an enlarged view of area 1502 will be displayed as shown in Figure 16. Alternatively, it is also preferable to change the screen's magnification by operating the mouse wheel.

[0102] The main features of Example 2 are as follows:

[0103] The calculation unit (self-position estimation difficulty area identification unit 602) calculates an index of communication quality along the flight path (for example, equations 1 to 3). The identification unit (self-position estimation difficulty area identification unit 602) identifies an area where the communication quality index is below an arbitrary threshold as a self-position estimation difficulty area (Figure 14).

[0104] This makes it easy to identify areas where self-localization is difficult.

[0105] The calculation unit (self-position estimation difficulty area identification unit 602) calculates the communication difficulty distance (for example, l-dg × 2, Figure 14) using an index of communication quality.

[0106] This makes it easy to calculate the distance at which communication is difficult.

[0107] The region where self-localization is difficult is, for example, a communication difficulty region where communication between the aircraft alone and the base station is difficult (Step 1201, Figure 12). The communication quality index is a value that indicates the quality of communication between the aircraft alone and the base station (e.g., Equations 1 and 2).

[0108] As a result, areas with poor communication quality between the aircraft and the base station become areas where self-position estimation is difficult.

[0109] The region where self-position estimation is difficult is, for example, a communication difficulty region where communication between the aircraft alone and positioning satellites is difficult (Step 1202, Figure 12). The communication quality index is a value that indicates the quality of communication between the aircraft alone and positioning satellites (e.g., Equation 3).

[0110] As a result, areas where the quality of communication between the aircraft and positioning satellites is low become areas where self-position estimation is difficult.

[0111] An indicator of communication quality is, for example, the number of positioning satellites that a single aircraft can communicate with (Step 1203, Figure 12).

[0112] This makes it easy to calculate an indicator of the quality of communication between the aircraft itself and the positioning satellite.

[0113] An indicator of communication quality is, for example, the strength of the received signal in communication (e.g., Equation 3, Figure 14).

[0114] This makes it easy to calculate various indicators of communication quality.

[0115] It should be noted that the present invention is not limited to the embodiments described above, and various modifications are included. For example, the embodiments described above are explained in detail to make the present invention easier to understand, and are not necessarily limited to those having all the configurations described. Furthermore, it is possible to replace parts of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add configurations from other embodiments to the configuration of one embodiment. In addition, it is possible to add, delete, or replace parts of the configuration of each embodiment with other configurations. For example, the present invention is applicable not only to the area around the takeoff and landing port, but also to the entire flight area over a wide area.

[0116] Furthermore, each of the above configurations, functions, processing units, and processing means may be implemented in hardware, either partially or entirely, by designing them as integrated circuits, for example. Alternatively, each of the above configurations and functions may be implemented in software by having the processor interpret and execute programs that implement each function. Information such as programs, tables, and files that implement each function can be stored in memory, a recording device such as a hard disk or SSD (Solid State Drive), or a recording medium such as an IC card, SD card, or DVD.

[0117] Furthermore, the control lines and information lines shown are those deemed necessary for explanatory purposes, and not all control lines and information lines are necessarily shown in the actual product. In reality, it can be assumed that almost all components are interconnected.

[0118] According to this embodiment, it is possible to determine the aircraft's position even inside a tunnel and transmit the result to air traffic control, thereby contributing to ensuring the aircraft's safety by allowing air traffic control to know the aircraft's position. [Explanation of Symbols]

[0119] 101…Railway tracks, 102…Tunnel, 103-105…Drone, 111…Control equipment, 201…Processor (CPU), 202…Memory, 203…Communication equipment, 204…Storage device, 210-212…Station terminals, 220-222…User, 230…Network, 301…Processor (CPU), 302…Memory, 303…Communication equipment, 304…Storage device, 305…Input device, 306…Display device, 401…Beacon, 402…Camera, 403…GNSS, 404…Storage device, 405…Processor (CPU), 406…Memory, 407…Communication equipment

Claims

1. A memory unit that stores the position of the flying object, A determination unit that determines the number of aircraft capable of self-position estimation of the aircraft, using a communication difficulty distance which indicates the length of the self-position estimation difficulty region, which is a region in the flight path where it is difficult for an aircraft to estimate its own position, A creation unit that determines the aircraft passing through the flight path and creates a flight plan for each aircraft, using the number of aircraft, the flight path, and the position of the aircraft. An output unit that outputs the flight plan and information regarding the aircraft traveling along the flight path, A control device equipped with the following features.

2. In the control device according to claim 1, The aforementioned determination unit, If there are multiple aircraft, the positions of the entrance and exit of the self-position estimation difficult area are used to determine how the multiple aircraft will cooperate within the self-position estimation difficult area. A control device characterized by the following features.

3. In the control device according to claim 2, The aforementioned determination unit, The number of aircraft and the method of cooperation are determined using the communication distance between two adjacent aircraft in the aforementioned region where self-position estimation is difficult. A control device characterized by the following features.

4. In the control device according to claim 1, A calculation unit that calculates an index of communication quality along the aforementioned flight path, A designation unit that identifies a region where the communication quality indicator falls below an arbitrary threshold as a region where self-position estimation is difficult, A control device characterized by being equipped with the following features.

5. In the control device according to claim 4, The calculation unit described above, The communication difficulty distance is calculated using the aforementioned communication quality indicator. A control device characterized by the following features.

6. In the control device according to claim 1, The aforementioned creation unit, Select the aircraft that is managed at the departure point of the aforementioned flight path, If the number of aircraft managed at the departure point is less than the number of aircraft determined by the determination unit, the aircraft managed at a management location closer to the destination than the departure point will be selected. A control device characterized by the following features.

7. In the control device according to claim 1, If there are multiple aircraft, at least one of them is designated as the master. The master waits before the region where self-localization is difficult, The other aircraft enters the region where self-position estimation is difficult and transmits the position of the other aircraft directly or indirectly to the master. The master transmits its own position and the positions of other aircraft to the control device. A control device characterized by the following features.

8. In the control device according to claim 1, If there are multiple aircraft, at least one of them is designated as the master. If the management location of the master and the management locations of the other aircraft are different, the other aircraft will take off at the same time as the master, or take off when the master passes over the management location of the other aircraft. A control device characterized by the following features.

9. In the control device according to claim 4, The aforementioned region where self-position estimation is difficult is a communication difficulty region, which is a region where communication between the aircraft and the base station is difficult. The aforementioned communication quality index is a value that indicates the quality of communication between the aircraft itself and the base station. A control device characterized by the following features.

10. In the control device according to claim 4, The aforementioned region where self-position estimation is difficult is a region where communication between the aircraft alone and positioning satellites is difficult, and The aforementioned communication quality index is a value that indicates the quality of communication between the aircraft itself and the positioning satellite. A control device characterized by the following features.

11. In the control device according to claim 10, The aforementioned indicator of communication quality is the number of positioning satellites with which the aircraft can communicate. A control device characterized by the following features.

12. In the control device according to claim 4, The aforementioned indicator of communication quality is the strength of the received signal during communication. A control device characterized by the following features.

13. In the control device according to claim 7, In the aforementioned region where self-position estimation is difficult, the positions of other aircraft are measured using beacons provided by each aircraft. The positions of other aircraft are transmitted to the master via the ad hoc network formed by the beacons. A control device characterized by the following features.

14. A control system comprising: a control device according to claim 1; and an aircraft that flies based on the flight plan created by the control device.

15. A process to determine the number of aircraft that can perform self-position estimation, using the communication difficulty distance in the self-position estimation difficult region, which is a region in the flight path where it is difficult for an individual aircraft to estimate its own position, A step of determining which aircraft will travel along the flight path and creating a flight plan for each aircraft, using the number of aircraft, the flight path, and the position of the aircraft. A step of outputting the flight plan and information relating to the aircraft passing through the flight path, A control method that causes the processor to execute a command.

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