Gate guidance system and gate guidance program
The gate guidance system optimizes vehicle routing at nuclear power plants by using drone-monitored traffic conditions and past data to select appropriate gates for vehicles with restricted access, addressing the limitations of existing systems and improving entry and exit efficiency.
Patent Information
- Authority / Receiving Office
- JP · JP
- Patent Type
- Patents
- Current Assignee / Owner
- THE CHUGOKU ELECTRIC POWER CO INC
- Filing Date
- 2022-08-09
- Publication Date
- 2026-06-23
AI Technical Summary
Existing gate guidance systems, such as those described in Patent Document 1, are inadequate for nuclear power plants where certain vehicles are restricted to specific gates, and they fail to consider surrounding traffic conditions or gate congestion when guiding vehicles.
A gate guidance system and program that utilizes traffic monitoring via drones with cameras, combined with a guidance computer, to select appropriate gates for vehicles based on traffic conditions, regulated vehicle information, and past traffic data, using a machine-learned gate selection model to optimize entry and exit routes.
Effectively guides vehicles to less congested gates, considering restricted vehicle access and real-time traffic conditions, reducing entry and exit delays by distributing vehicles evenly and predicting loading/unloading times.
Smart Images
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Abstract
Description
Technical Field
[0001] The present invention relates to a gate guidance system and a gate guidance program for guiding which gate to use among a plurality of gates.
Background Art
[0002] A nuclear power plant is provided with a plurality of gates. When entering the nuclear power plant by vehicle, the gates through which the vehicle can enter are determined. For example, for commuter buses, construction vehicles that enter regularly, or vehicles that enter temporarily, the gates through which they can enter are determined. However, for company-owned vehicles of power companies and ordinary vehicles that enter regularly, entry is permitted through any gate.
[0003] And conventionally, the drivers of vehicles (free vehicles) that are permitted to enter through any gate have decided which gate to enter by themselves regardless of the surrounding traffic conditions or the congestion status of the gates. Therefore, when identity verification by security guards or verification of carried-in items is carried out at a specific gate during the morning commuting time, traffic jams occur and smooth entry cannot be achieved.
[0004] On the other hand, in a parking lot having a plurality of entrance gates, a parking lot guidance device that can smoothly guide a vehicle to an entrance gate is known (see, for example, Patent Document 1). This device groups vehicles based on the scheduled arrival time or the time when they enter within a predetermined range and then determines an entrance gate, sets congestion criteria for nodes around the parking lot to predict the occurrence of congested nodes, and sends congestion prediction information only to user terminals that want to bypass the congested nodes.
Prior Art Documents
Patent Documents
[0005]
Patent Document 1
Summary of the Invention
[0006] However, the device described in Patent Document 1 assumes that all vehicles can enter through any gate, whereas, as mentioned above, the gates through which certain vehicles can enter are restricted at nuclear power plants, making the device described in Patent Document 1 unsuitable for nuclear power plants. Furthermore, the device described in Patent Document 1 only determines the entry gate based on the scheduled arrival time or the time spent within a predetermined range, and cannot guide vehicles to the appropriate gate based on surrounding traffic conditions or gate congestion.
[0007] Therefore, the present invention aims to provide a gate guidance system and gate guidance program that can guide vehicles to the appropriate gate even when the gates that can be used for certain vehicles are restricted. [Means for solving the problem]
[0008] To solve the above problems, the invention of claim 1 is a gate guidance system for guiding a free vehicle to a gate when a facility is provided with multiple gates, and a regulated vehicle is a vehicle that is permitted to use only certain gates, and a free vehicle is a vehicle that is permitted to use any gate, when the free vehicle enters or exits the facility, the system comprising: traffic monitoring means for monitoring traffic conditions around the facility; vehicle information storage means for storing regulated vehicle information including the gates permitted for use by the regulated vehicle and the scheduled date and time of entry into the facility; location acquisition means for acquiring the location of the free vehicle; and gate selection means for selecting a gate that allows the free vehicle to enter or exit the facility smoothly, based on the traffic conditions around the facility, the regulated vehicle information, and the location of the free vehicle.
[0009] The invention of claim 2 is characterized in that, in the gate guidance system described in claim 1, the regulated vehicle information includes information relating to the loading and unloading of goods from the regulated vehicle.
[0010] The invention of claim 3 is characterized in that, in the gate guidance system described in claim 1, it comprises a past information storage means for storing past information including past traffic conditions around the facility, and the gate selection means selects the gate based on the past information.
[0011] The invention of claim 4 is characterized in that, in the gate guidance system described in claim 3, the past information includes weather information for the traffic conditions.
[0012] The invention of claim 5 is characterized in that, in the gate guidance system described in claim 1, the traffic monitoring means is composed of a camera installed on an aircraft, and monitors the traffic condition based on images captured by the camera.
[0013] The invention of claim 6 is characterized in that, in the gate guidance system described in claim 1, the gate selection means uses a gate selection learning model that has been machine-learned based on past performance data, so that when the traffic conditions around the facility, the regulated vehicle information, and the location of the free vehicle are input, a gate that allows the free vehicle to smoothly enter and exit the facility is output.
[0014] The invention of claim 7 is a gate guidance program for guiding a free vehicle to a gate when a facility is provided with multiple gates, and a regulated vehicle is a vehicle that is permitted to use only certain gates, and a free vehicle is a vehicle that is permitted to use any gate, to enter or exit the facility, characterized in that a computer functions as a vehicle information storage means for storing regulated vehicle information including the gates permitted to be used by the regulated vehicle and the scheduled date and time of entry into the facility, and a gate selection means for selecting a gate that allows the free vehicle to enter or exit the facility smoothly, based on the traffic conditions around the facility, the regulated vehicle information, and the location of the free vehicle.
[0015] The invention of claim 8 is characterized in that, in the gate guidance system described in claim 7, the regulated vehicle information includes information relating to the loading and unloading of goods from the regulated vehicle.
[0016] The invention of claim 9 is characterized in that, in the gate guidance system described in claim 7, the computer functions as a past information storage means for storing past information including past traffic conditions around the facility, and the gate selection means selects the gate based on the past information.
[0017] The invention of claim 10 is characterized in that, in the gate guidance system described in claim 9, the past information includes weather information for the traffic conditions.
[0018] The invention of claim 11 is characterized in that, in the gate guidance system described in claim 7, the gate selection means uses a gate selection learning model that has been machine-learned based on past performance data, so that when the traffic conditions around the facility, the regulated vehicle information, and the location of the free vehicle are input, a gate that allows the free vehicle to smoothly enter and exit the facility is output. [Effects of the Invention]
[0019] According to the inventions described in claims 1 and 7, a gate is selected that allows unrestricted vehicles to smoothly enter and exit the facility, based on traffic conditions such as where congestion is occurring around the facility and which gates are congested, information on restricted vehicles such as which gates they can use and when they will enter the facility, and the location of unrestricted vehicles. Therefore, when restricted vehicles and unrestricted vehicles enter and exit the facility, that is, even when the gates that can be used are restricted for some vehicles, it is possible to guide them to the appropriate gate.
[0020] According to the inventions described in claims 2 and 8, since the regulated vehicle information includes information regarding the loading and unloading of goods from the regulated vehicle, it becomes possible to predict the departure time from the facility by taking into account the time required for loading and unloading goods. As a result, it becomes possible to guide unoccupied vehicles to the appropriate gate at the predicted departure time.
[0021] According to the inventions described in claim 3 and claim 9, since the gate is selected based on past information including traffic conditions such as where traffic jams occurred around the facility in the past and which gate was congested, it is possible to guide an appropriate gate considering past traffic conditions and the like.
[0022] According to the inventions described in claim 4 and claim 10, since weather information in the traffic conditions is included as past information, it is possible to grasp such as in what weather situation, when and where traffic jams occur, and guide an appropriate gate based on the weather situation.
[0023] According to the invention described in claim 5, since the traffic condition is monitored based on the captured image by the camera disposed on the aircraft, it is possible to appropriately monitor and grasp the traffic jam situation and the like from above, and monitor snow accumulation and freezing on the road, etc., and guide a safe and appropriate gate.
[0024] According to the inventions described in claim 6 and claim 11, since a learned learning model for gate selection is used to output a gate through which free vehicles can smoothly enter and exit the facility, it is possible to guide a more appropriate gate.
Brief Description of the Drawings
[0025] [Figure 1] It is a schematic configuration diagram showing a gate guidance system according to an embodiment of this invention. [Figure 2] It is a schematic configuration block diagram showing the guidance computer of the gate guidance system in FIG. 1. [Figure 3] It is a diagram showing the data configuration of the vehicle information database of the guidance computer in FIG. 2. [Figure 4] It is a functional block diagram showing the schematic configuration of the gate selection learning model of the guidance computer in FIG. 2.
Modes for Carrying Out the Invention
[0026] Hereinafter, this invention will be described based on the illustrated embodiments.
[0027] Figure 1 is a schematic diagram showing a gate guidance system 1 according to an embodiment of the present invention. This gate guidance system 1 is a system that guides regulated vehicles, which are vehicles authorized to use only certain gates, and free vehicles, which are vehicles authorized to use any gate, to the gates when they enter or exit a facility where multiple gates are provided. In this embodiment, the case in which the facility is a nuclear power plant P and the power company operating the nuclear power plant P operates the gate guidance system 1 will be mainly described.
[0028] Specifically, the nuclear power plant P is equipped with two gates, G1 and G2. Commuter buses, construction vehicles that enter the plant on a daily basis, and vehicles that enter temporarily are limited to using only the second gate, G2, as restricted vehicles (C2). On the other hand, company vehicles of the power company and ordinary vehicles that enter the plant on a daily basis (commuter vehicles, etc.) are permitted to use either gate, G1 or G2, as free vehicles (C1). Furthermore, among the restricted vehicles (C2), commuter buses and construction vehicles that enter the plant on a daily basis have predetermined times for entering and exiting the nuclear power plant P. Vehicles that enter the plant temporarily must apply to the nuclear power plant P in advance, specifying the planned date and time of entry and whether or not goods will be loaded or unloaded.
[0029] Thus, this embodiment describes a case where the nuclear power plant P is equipped with two gates G1 and G2, but it may also have three or more gates. Furthermore, although this embodiment describes a case where all regulated vehicles C2 can use only the second gate G2, it may be possible to allow each regulated vehicle C2 to use a different gate.
[0030] The gate guidance system 1 primarily consists of a drone (flying vehicle) 2 equipped with a camera (traffic monitoring means) 21 and a guidance computer 3 installed at the nuclear power plant P, with the drone 2 and the guidance computer 3 being freely connected to each other. Furthermore, the guidance computer 3 is freely able to communicate with each free vehicle C1.
[0031] In other words, each free-roaming vehicle C1 is equipped with a communication device and a GPS (Global Positioning System), allowing the guidance computer 3 to acquire and know the current position of each free-roaming vehicle C1 in real time. Furthermore, as will be described later, gates G1 and G2 selected by the guidance computer 3 are transmitted to each free-roaming vehicle C1, and the selected gates G1 and G2 are displayed on the display mounted on each free-roaming vehicle C1, or announced by voice output from the speaker, providing guidance. Note that such communication devices, GPS, displays, etc., may be configured using existing car navigation systems.
[0032] Drone 2 is an unmanned aerial vehicle that flies over the area surrounding the nuclear power plant P. In this embodiment, it repeatedly flies a predetermined flight route / path automatically, but it may also be remotely controlled by a person. Furthermore, it constantly photographs the area around the nuclear power plant P with its mounted camera 21 and transmits the captured images to the guidance computer 3 in real time, so that the guidance computer 3 can acquire and monitor the traffic conditions around the nuclear power plant P. In this way, the camera 21 mounted on the drone 2 constitutes the traffic monitoring means. Here, depending on the size of the nuclear power plant P and the number of gates, multiple drones 2 may be flown.
[0033] The guidance computer 3 is a computer that selects and guides each free vehicle C1 on which gates G1 and G2 to use. As shown in Figure 2, it mainly comprises an input unit 31, a display unit 32, a communication unit 33, a storage unit 34, a gate selection task (gate selection means) 35, a learning task 36, and a central processing unit 37 that controls these.
[0034] The input unit 31 is an interface for inputting various information and commands, specifically for inputting regulated vehicle information into the vehicle information database 341 (described later) and inputting the activation command for the gate selection task 35. The display unit 32 is a display for displaying various data and information, specifically for displaying images taken from the drone 2 and displaying regulated vehicle information for the regulated vehicle C2 specified by the input unit 31. The communication unit 33 is an interface for communicating with the outside world via the internet or telephone network, specifically for receiving images taken from the drone 2, receiving location information from each free vehicle C1, and transmitting the gates G1 and G2 selected as described later to each free vehicle C1. The communication unit 33 is also configured to acquire weather information from an external source (such as a weather information system).
[0035] The memory unit 34 mainly comprises a vehicle information database (vehicle information storage means) 341, a past information database (past information storage means) 342, a gate selection learning model 343, and a gate selection performance database 344. Here, the vehicle information database 341 and the past information database 342 will be described, and the gate selection learning model 343 and the gate selection performance database 344 will be described later.
[0036] The vehicle information database 341 is a database that stores information about regulated vehicles, including the gates G1 and G2 that the regulated vehicle C2 is authorized to use, and the scheduled date and time of entry into the nuclear power plant P. In other words, it stores information about the regulated vehicle C2, and in this embodiment, as described above, for commuter buses and construction vehicles that enter the premises on a daily basis, the time of entry and exit (scheduled date and time of entry) and the gates G1 and G2 that they are authorized to use are predetermined, and this scheduled date and time of entry and gates G1 and G2 are stored together with the vehicle's identification information (license plate, etc.). On the other hand, for vehicles that enter the premises temporarily, as described above, they apply to the entry and exit management system of the nuclear power plant P in advance, and the regulated vehicle information is stored based on the information at the time of this application.
[0037] Specifically, as shown in Figure 3, for each vehicle ID 3411, the following information is stored: vehicle type 3412, affiliation 3413, scheduled entry 3414, gate 3415, and other information 3416. Vehicle ID 3411 stores vehicle identification information, such as license plate number and vehicle registration number. Vehicle type 3412 stores the type of vehicle, such as a passenger car or heavy machinery. Affiliation 3413 stores the name of the business or organization that owns or uses the vehicle. Scheduled entry 3414 stores the scheduled date and time of entry into the nuclear power plant P. Gate 3415 stores identification information of the gate authorized for use by this vehicle, such as whether it is the first gate G1 or the second gate G2. Other information 3416 stores information regarding the loading and unloading of goods from this vehicle, such as what goods are being loaded and unloaded, and how long the loading and unloading will take.
[0038] The historical information database 342 is a database that stores historical information, including past traffic conditions around the nuclear power plant P, such as where and when congestion occurred around the nuclear power plant P in the past, and when congestion occurred at each gate G1 and G2. In other words, it stores historical information on traffic conditions and congestion around the nuclear power plant P, as well as congestion at each gate G1 and G2, on a monthly, daily, and weather / weather information basis. For example, it stores historical information based on past performance, such as the fact that there are particularly many construction vehicles entering the site on a daily basis and construction vehicles entering temporarily at the beginning of the week, that there are fewer regulated work vehicles C2 and more free vehicles C1 during rainy or snowy weather, and that people commute earlier than during the morning rush hour on sunny days, that vehicles from cooperating companies often leave at a fixed time (e.g., 5pm), but the return times of commuter vehicles vary, and that congestion often occurs when heavy machinery vehicles pass through.
[0039] The gate selection task 35 is a task program that selects gates G1 and G2 that allow free vehicle C1 to smoothly enter or exit the nuclear power plant P, based on traffic conditions around the nuclear power plant P, information on regulated vehicles, and the current location of free vehicle C1. It selects gates G1 and G2 by referring to past information. Specifically, it selects gates G1 and G2 that allow free vehicle C1 to smoothly enter or exit the nuclear power plant P, based on traffic conditions such as where congestion is occurring or is expected to occur around the nuclear power plant P, which gates are congested or are expected to be congested, information on regulated vehicles such as which regulated vehicles C2 can use which gates G1 and G2 and when they enter the nuclear power plant P, the current location of free vehicle C1, and past information such as where and when congestion occurred around the nuclear power plant P in the past, which gates G1 and G2 were congested and when, and where and under what weather conditions congestion occurred.
[0040] This gate selection task 35 may be activated at all times, activated at predetermined times each day (for example, during commuting and departure times), or activated when an activation command is entered in the input unit 31. Furthermore, all free vehicles C1 may be selected and guided to gates G1 and G2, or only some free vehicles C1 may be selected and guided, for example, only free vehicles C1 that have requested to receive gate guidance services from the gate guidance system 1.
[0041] The gate selection task 35 first analyzes images of the area around the nuclear power plant P received from drone 2 to acquire and monitor traffic conditions around the nuclear power plant P. For example, it identifies where congestion is occurring around the nuclear power plant P, which gates G1 and G2 are congested, what types of vehicles are traveling, and whether the roads are frozen or covered in snow. It also determines the current location of each free vehicle C1 based on the location information received from each free vehicle C1.
[0042] Then, based on the acquired traffic conditions, the current location of each free vehicle C1, and information about the regulated vehicle C2, the gates G1 and G2 to which each free vehicle C1 should be guided are selected. For example, they may be selected as follows:
[0043] a) If a free vehicle C1 is currently located near the second gate G2, but there are many vehicles C1 and C2 heading towards the second gate G2, or if, according to the scheduled entry time of the regulated vehicle information, there will be many regulated vehicles C2 entering the nuclear power plant P during this time, or if, according to past information, the second gate G2 is congested during this time on the day of the week, then the first gate G1 will be selected for this free vehicle C1.
[0044] b) In case of rain, based on past information that there are fewer regulated work vehicles C2 and more free vehicles C1, commuting earlier than usual, gates G1 and G2 will be selected so that many free vehicles C1 are evenly distributed between both gates G1 and G2. In this case, if past information indicates that many free vehicles C1 will use the first gate G1, which is closer to the parking lot, the second gate G2 will be selected to accommodate as many free vehicles C1 as possible.
[0045] c) Currently, there are few vehicles C1 and C2 heading towards the second gate G2. However, based on past information that traffic congestion often occurs when multiple heavy machinery vehicles C2 enter later, the first gate G1 will be selected for the free vehicle C1.
[0046] d) If there is a concrete mixer truck among the regulated vehicles C2 heading towards the second gate G2, the first gate G1 will be selected for as many free vehicles C1 as possible, even if the second gate G2 is not currently congested, in order to avoid congestion at the second gate G2.
[0047] e) If traffic conditions indicate that an emergency vehicle is heading towards the first gate G1, select the second gate G2 for as many free vehicles C1 as possible.
[0048] f) If there is a slope on the road leading to the first gate G1 and the road is frozen or covered in snow, even if there are currently only a few free vehicles C1 heading towards the first gate G1, the second gate G2 will be selected for as many free vehicles C1 as possible to prevent slip accidents, etc.
[0049] g) When exiting, if many regulated vehicles C2 from partner companies have entered, based on past information that partner company vehicles often leave on time, the first gate G1 will be selected for free vehicles C1 that will exit during the scheduled time.
[0050] h) Based on the information regarding the loading and unloading of goods in the regulated vehicle information, the departure time is predicted taking into account the time required for loading and unloading goods. For free vehicles C1 that depart during that departure time, the first gate G1 is selected, and for free vehicles C1 that depart outside of that departure time, they are evenly allocated to both gates G1 and G2.
[0051] This gate selection task 35 takes the traffic conditions around the nuclear power plant P, information on regulated vehicles, and the current location of a free vehicle C1 as input, and uses a gate selection learning model 343 that has been machine-learned based on past performance data to output gates G1 and G2 that allow the free vehicle C1 to smoothly enter and exit the nuclear power plant P. This gate selection learning model 343 is created by the learning task 36.
[0052] In other words, the learning task 36 creates a gate selection learning model 343 using a known machine learning algorithm such as a neural network, based on past performance data recorded and stored in the gate selection performance database 344. This gate selection performance database 344 is a database in which performance data is recorded and stored, including the traffic conditions around the nuclear power plant P, information on regulated vehicles, the current location of free vehicles C1 as input information, and the results of verification (post-confirmation) that gates G1 and G2 allowed free vehicles C1 to enter and exit the nuclear power plant P smoothly, based on actual congestion and the degree of congestion at gates G1 and G2. The past performance data includes data created based on actual traffic conditions and information on regulated vehicles, as well as gates G1 and G2 verified from actual congestion, and data created through pre-training (gates G1 and G2 determined to allow smooth entry and exit by veteran employees of the nuclear power plant P and experts and specialists in congestion prediction).
[0053] As shown in Figure 4, this learning task 36 uses machine learning and deep learning with a neural network to create a neural network based on actual data recorded in the gate selection performance database 344. For example, the input layer contains traffic conditions around the nuclear power plant P, information on regulated vehicles, and the current position of free vehicle C1. The output layer contains gates G1 and G2, which have been verified to allow free vehicle C1 to enter and exit smoothly. The hidden layer is used for the analysis process from the input layer to the output layer. Then, learning task 36 uses the actual data of the gate selection learning model 343 as training data to learn various parameters in the hidden layer. In other words, learning task 36 learns various parameters in the hidden layer so that gates G1 and G2, which allow smooth entry and exit, are appropriately output based on traffic conditions around the nuclear power plant P, information on regulated vehicles, and the current position of free vehicle C1.
[0054] As described above, according to this gate guidance system 1, when a free vehicle C1 is attempting to enter or exit the nuclear power plant P, the system selects which gates G1 and G2 the free vehicle C1 should use and transmits this information to the free vehicle C1. At this time, based on traffic conditions such as where congestion is occurring around the nuclear power plant P and which gates G1 and G2 are congested, as well as information on regulated vehicles such as which gates G1 and G2 regulated vehicles C2 can use and when they will enter the nuclear power plant P, and the location of the free vehicle C1, the system selects the gates G1 and G2 that will allow the free vehicle C1 to enter and exit the nuclear power plant P smoothly. Therefore, even when regulated vehicles C2 and free vehicles C1 are entering and exiting the nuclear power plant P, that is, when gates G1 and G2 that can be used by some vehicles are restricted, the system can guide them to the appropriate gates G1 and G2.
[0055] Furthermore, since the regulated vehicle information includes information on the loading and unloading of goods from regulated vehicle C2, it becomes possible to predict the departure time from nuclear power plant P by taking into account the time required for loading and unloading goods. As a result, it becomes possible to guide the free vehicle C1 to the appropriate gates G1 and G2 at the predicted departure time.
[0056] Furthermore, gates G1 and G2 are selected based on past traffic information, including where congestion occurred around the nuclear power plant P in the past and which gates G1 and G2 were congested. This makes it possible to guide passengers to the appropriate gates G1 and G2, taking into account past traffic conditions.
[0057] Furthermore, since historical data includes weather information related to traffic conditions, it becomes possible to understand what kind of weather conditions cause congestion, when and where, and guide users to the appropriate gates G1 and G2 based on the weather conditions.
[0058] Furthermore, since traffic conditions are monitored based on images captured by the camera 21 installed on drone 2, congestion and other conditions can be properly monitored and understood from above. In addition, road conditions such as snow and ice can be monitored, enabling safe and appropriate guidance to gates G1 and G2.
[0059] Furthermore, by using the machine learning-developed gate selection model 343, gates G1 and G2 that allow the free vehicle C1 to smoothly enter and exit the nuclear power plant P are output, making it possible to guide the vehicle to more appropriate gates G1 and G2.
[0060] Although embodiments of this invention have been described in detail above, the specific configuration is not limited to these embodiments, and any design changes, etc., that do not depart from the gist of this invention are also included. For example, in the above embodiment, the traffic monitoring means is configured by a camera 21 mounted on the drone 2, but the traffic monitoring means may also be configured by a traffic volume measuring device / camera installed on the road. Furthermore, although the case where the facility is a nuclear power plant P has been described, it goes without saying that the invention can be applied to other facilities as well.
[0061] On the other hand, the gate guidance system 1 and guidance computer 3 described above may be configured by installing the following gate guidance program on a general-purpose computer. That is, the computer is configured as a gate guidance program for guiding a free vehicle C1 to a gate when a regulated vehicle C2, which is a vehicle that is permitted to use only a limited number of gates when multiple gates are provided at the facility, and a free vehicle C1, which is a vehicle that is permitted to use any gate, enters or exits the facility. The computer is configured as a vehicle information storage means (vehicle information database 341) that stores regulated vehicle information including the gates permitted to be used by the regulated vehicle C2 and the scheduled date and time of entry into the facility, and as a past information storage means (past information database 342) that stores past information including past traffic conditions around the facility, and the traffic conditions around the facility and the regulated vehicle Based on both pieces of information and the location of the free vehicle C1, the system functions as a gate selection means (gate selection task 35) that selects a gate that allows the free vehicle C1 to enter and exit the facility smoothly. The regulated vehicle information includes information on the loading and unloading of goods from the regulated vehicle C2, and the historical information includes weather information for past traffic conditions. The gate selection means selects a gate based on the historical information, and when the traffic conditions around the facility, the regulated vehicle information, and the location of the free vehicle C1 are input, it outputs a gate that allows the free vehicle C1 to enter and exit the facility smoothly. This is achieved by using a gate selection learning model 343 that has been machine-learned based on past performance data. [Explanation of Symbols]
[0062] 1. Gate guidance system 2. Drone (flying object) 21. Cameras (traffic monitoring tools) 3. Information Computer 341 Vehicle Information Database (Vehicle Information Storage Means) 342 Historical Information Database (Historical Information Storage Means) 343 Learning Model for Gate Selection 344 Gate Selection Performance Database 35. Gate Selection Task (Gate Selection Method) P Nuclear power plant (facility) C1 Free Vehicle C2 regulated vehicles G1 First Gate G2 Second Gate
Claims
1. A gate guidance system for guiding a free vehicle to a gate when a facility has multiple gates, and regulated vehicles are permitted to use only certain gates, and free vehicles are permitted to use any gate, when the free vehicle enters or exits the facility. Traffic monitoring means for monitoring traffic conditions around the aforementioned facility, A vehicle information storage means that stores information about the regulated vehicle, including the gate on which the regulated vehicle is permitted to use and the scheduled date and time of entry into the facility. A position acquisition means for acquiring the position of the aforementioned free vehicle, A gate selection means that selects a gate that allows the free vehicle to enter and exit the facility smoothly, based on the traffic conditions around the facility, the regulated vehicle information, and the location of the free vehicle. A gate guidance system characterized by comprising the following features.
2. The aforementioned restricted vehicle information includes information regarding the loading and unloading of goods from the restricted vehicle, The gate guidance system according to claim 1.
3. The facility is equipped with a past information storage means that stores past information, including past traffic conditions around the facility, The gate selection means selects the gate based on the past information. The gate guidance system according to claim 1.
4. The aforementioned past information includes weather information for the aforementioned traffic conditions, The gate guidance system according to claim 3.
5. The traffic monitoring means consists of a camera mounted on the aircraft, and monitors the traffic conditions based on images captured by the camera. The gate guidance system according to item 1, characterized by the feature.
6. The gate selection means, upon receiving the traffic conditions around the facility, the regulated vehicle information, and the location of the unattended vehicle, uses a gate selection learning model that has been machine-trained based on past performance data, so as to output a gate that allows the unattended vehicle to smoothly enter and exit the facility. The gate guidance system according to item 1, characterized by the feature.
7. In a facility with multiple gates, where regulated vehicles are permitted to use only certain gates and unregulated vehicles are permitted to use any gate, a gate guidance program for guiding unregulated vehicles to the appropriate gates is provided, and a computer is used to provide this program. A vehicle information storage means that stores information about the regulated vehicle, including the gate on which the regulated vehicle is permitted to use and the scheduled date and time of entry into the facility. A gate selection means that selects a gate that allows the free vehicle to enter and exit the facility smoothly, based on the traffic conditions around the facility, the regulated vehicle information, and the location of the free vehicle. A gate guidance program characterized by functioning as such.
8. The aforementioned restricted vehicle information includes information regarding the loading and unloading of goods from the restricted vehicle, The gate guidance program according to feature 7.
9. The computer is configured to function as a historical information storage means for storing historical information, including past traffic conditions around the facility. The gate selection means selects the gate based on the past information. The gate guidance program according to feature 7.
10. The aforementioned past information includes weather information for the aforementioned traffic conditions, The gate guidance program according to feature 9.
11. The gate selection means, upon receiving the traffic conditions around the facility, the regulated vehicle information, and the location of the unattended vehicle, uses a gate selection learning model that has been machine-trained based on past performance data, so as to output a gate that allows the unattended vehicle to smoothly enter and exit the facility. The gate guidance program according to item 7, characterized by the feature.