Operation management device, operation management method, and computer program

Abstract

This operation management device comprises: a satellite data acquisition unit which acquires satellite data obtained by observing a prescribed area; a vehicle location acquisition unit which acquires the locations of vehicles in the area on the basis of the satellite data; a congestion state identification unit which identifies, on the basis of the locations of the vehicles in the area, a congestion state of vehicles in the area; and a predicted waiting time calculation unit which calculates a predicted waiting time of an object vehicle in the area on the basis of the location of the object vehicle and the congestion state.

Description

Traffic management device, traffic management method, and computer program

[0001] This disclosure relates to a traffic management device, a traffic management method, and a computer program. This application claims priority to Japanese Patent Application No. 2022-203062 filed on December 20, 2022, and incorporates by reference all of the contents of that application.

[0002] Conventionally, there has been proposed a device for creating an efficient delivery plan when a large number of packages are delivered to a plurality of delivery points by vehicle (see, for example, Patent Document 1).

[0003] These delivery plans are created using predicted travel times between delivery points, and the accuracy of travel time predictions is improving with advances in vehicle detection technology and more accurate probe information showing vehicle location and time.

[0004] Japanese Patent Application Laid-Open No. 2001-109983

[0005] An operation management device according to one aspect of the present disclosure includes a satellite data acquisition unit that acquires satellite data observing an entry / exit area where vehicles can enter and exit; a vehicle position acquisition unit that acquires probe information of a target vehicle that is a probe vehicle, acquires the position of the target vehicle based on the probe information, and acquires the position of the vehicle within the entry / exit area based on the satellite data; a congestion status identification unit that identifies the congestion status of vehicles within the entry / exit area based on the position of the vehicle within the entry / exit area; and an estimated waiting time calculation unit that calculates a estimated waiting time of the target vehicle within the entry / exit area based on the position and congestion status of the target vehicle.

[0006] The present invention can be realized not only as a traffic management device having such a characteristic processing unit, but also as a traffic management method having such characteristic processing steps, or as a computer program for causing a computer to function as such a characteristic processing unit, or as a semiconductor integrated circuit that realizes part or all of the traffic management device, or as a traffic management system including the traffic management device.

[0007] FIG. 1 is a diagram illustrating an overall configuration of a traffic management system according to an embodiment of the present disclosure. FIG. 2 is a block diagram illustrating a configuration of an in-vehicle device. FIG. 3 is a block diagram illustrating a configuration of the traffic management device. FIG. 4 is a diagram illustrating an example of satellite data generated by a satellite data acquisition unit. FIG. 5 is a diagram illustrating an example of video data. FIG. 6 is a block diagram illustrating a configuration of an administrator terminal. FIG. 7 is a flowchart illustrating an example of a processing procedure for generating vehicle position information executed by the traffic management device. FIG. 8 is a flowchart illustrating an example of a processing procedure for generating target vehicle position information executed by the traffic management device. FIG. 9 is a flowchart illustrating an example of a processing procedure for updating a operation plan of a target vehicle executed by the traffic management device. FIG. 10 is a diagram illustrating an operation plan of a target vehicle created before the target vehicle departs from a base, and the operation record of the target vehicle. FIG. 11 is a diagram illustrating an operation plan of a target vehicle created before the target vehicle departs from a base, and the operation record of the target vehicle. FIG. 12 is a diagram illustrating an updated operation plan of a target vehicle and the operation record of the target vehicle. FIG. 13 is a diagram illustrating an updated operation plan of a target vehicle and the operation record of the target vehicle. Fig. 14 is a diagram showing an updated operation plan for a target vehicle and an operation record of the target vehicle Fig. 15 is a flowchart showing an example of a processing procedure for displaying video data executed by the operation management device.

[0008] [Problem to be Solved by the Present Disclosure] Although the predicted travel time indicates the predicted value of the travel time between delivery points on public roads, it does not include the waiting time of the vehicle within the delivery point area, such as a factory. Therefore, for example, the waiting time within the area was set to a predetermined fixed time when creating a delivery plan. This made it difficult to create an accurate delivery plan.

[0009] In order to create an accurate delivery plan, it is desirable to accurately predict the waiting time of vehicles within the area of ​​the delivery point. Note that there is a need to accurately predict the waiting time of vehicles within a specified area, in addition to the use of parcel delivery. For example, there is a need to predict the waiting time of container-loaded vehicles transporting containers to be loaded onto or unloaded from a ship within a port facility, and the waiting time of vehicles in large parking lots at event venues, etc.

[0010] The present disclosure has been made in consideration of the above circumstances, and aims to provide an operation management device, an operation management method, and a computer program that can accurately calculate the predicted waiting time of a target vehicle within a specified area.

[0011] Effect of the Present Disclosure According to the present disclosure, it is possible to accurately calculate the predicted waiting time of a target vehicle within a predetermined area.

[0012] [Outline of Embodiments of the Present Disclosure] First, an outline of an embodiment of the present disclosure will be listed and described. (1) A traffic management device according to one embodiment of the present disclosure includes a satellite data acquisition unit that acquires satellite data observing a predetermined area, a vehicle position acquisition unit that acquires positions of vehicles within the area based on the satellite data, a congestion status identification unit that identifies a congestion status of vehicles within the area based on the positions of the vehicles within the area, and an estimated waiting time calculation unit that calculates a estimated waiting time of the target vehicle within the area based on the position of the target vehicle and the congestion status.

[0013] By using satellite data, for example, the number of vehicles can be accurately determined as an indicator of vehicle congestion. Therefore, by calculating the predicted waiting time based on the location and congestion of the target vehicle, the predicted waiting time of the target vehicle within the area can be accurately calculated.

[0014] (2) In the above (1), the satellite data may include images of the area captured by a synthetic aperture radar or an optical sensor.

[0015] By using synthetic aperture radar or optical sensors, it is possible to identify the vehicle congestion situation in areas not covered by traffic information generation, and therefore to accurately calculate the predicted waiting time of target vehicles in areas not covered by traffic information generation.

[0016] (3) In (1) or (2) above, the congestion status identification unit calculates the number of waiting vehicles, including the target vehicle, that are located between the position of the target vehicle and a specified unloading point within the area based on the position of the target vehicle and the positions of vehicles within the area, and the predicted waiting time calculation unit calculates the predicted waiting time as the product of the number of waiting vehicles and a specified standard waiting time, and the standard waiting time may be a predetermined time based on the actual measured time from a specified time point to the time when unloading by the target vehicle at the unloading point is completed, collected for each of the multiple target vehicles, and the number of waiting vehicles at the specified time point.

[0017] According to this configuration, the predicted waiting time is calculated based on the waiting reference time measured in advance and the number of waiting vehicles, which indicates the congestion status of the vehicles. Therefore, the predicted waiting time can be calculated accurately.

[0018] (4) In the above (3), the waiting reference time may be determined based on a value obtained by dividing the actual measurement time collected for each of the target vehicles by the number of waiting vehicles.

[0019] According to this configuration, the waiting reference time represents the waiting time per waiting vehicle.

[0020] (5) In (3) or (4) above, the waiting reference time may be associated with a vehicle load classification, and the vehicle position acquisition unit may further calculate the load classification of the vehicles in the area based on the satellite data, and the predicted waiting time calculation unit may classify the number of waiting vehicles into the classifications calculated by the vehicle position acquisition unit, and calculate the predicted waiting time based on the number of vehicles for each classification after classification and the waiting reference time associated with the classification.

[0021] With this configuration, the predicted waiting time can be calculated based on the number of waiting vehicles for each load category and the waiting reference time corresponding to that category. Because the time required for unloading, etc. varies depending on the load, by classifying the waiting vehicles according to the load category, the predicted waiting time can be calculated with high accuracy.

[0022] (6) In any of (1) to (5) above, the operation management device may further include a display control unit that displays video data on a map showing the area in a manner that allows the position of the target vehicle to be distinguished from the positions of vehicles other than the target vehicle.

[0023] By viewing the video data, the user can see vehicles waiting ahead of the target vehicle in the area, allowing the user to intuitively understand how long they should wait until they reach their destination.

[0024] (7) In (6) above, the display control unit may display the video data in an emphasized manner showing a specified unloading point within the area and a route from the entrance of the area to the unloading point.

[0025] The user can view the video data and check which vehicles are waiting on the route to the unloading point, allowing the user to intuitively understand how long they should wait until the unloading point.

[0026] (8) In any of (1) to (7) above, the operation management device may further include an operation plan creation unit that determines whether or not a constraint on the delivery time of the package is satisfied based on a predetermined operation plan of the target vehicle and the calculated predicted waiting time, and re-creates the operation plan if it is determined that the constraint is not satisfied.

[0027] For example, if the calculated predicted waiting time is longer than the operation plan and the package cannot be delivered to the delivery point after the current location within the specified delivery time, the operation plan can be re-created, thereby increasing the probability of successfully delivering the package while meeting the delivery time constraints.

[0028] (9) In the above (8), the constraints may include at least one of a constraint on the arrival time of the target vehicle at the unloading point and a constraint on the departure time of the target vehicle from the unloading point.

[0029] This configuration can increase the probability of successful delivery of cargo that satisfies at least one of the constraints on the arrival time of the target vehicle at the unloading point and the constraints on the departure time of the target vehicle from the unloading point.

[0030] (10) An operation management method according to another embodiment of the present disclosure includes the steps of: an operation management device acquiring satellite data observing a specified area; the operation management device acquiring the positions of vehicles within the area based on the satellite data; the operation management device identifying a vehicle congestion status within the area based on the positions of the vehicles within the area; and the operation management device calculating a predicted waiting time for the target vehicle within the area based on the position and the congestion status of the target vehicle.

[0031] This configuration includes the characteristic processing steps of the above-described traffic management device, and therefore can achieve the same effects and advantages as the above-described traffic management device.

[0032] (11) A computer program according to another embodiment of the present disclosure causes a computer to function as a satellite data acquisition unit that acquires satellite data observing a specified area, a vehicle position acquisition unit that acquires the positions of vehicles within the area based on the satellite data, a congestion status identification unit that identifies the congestion status of vehicles within the area based on the positions of vehicles within the area, and a predicted waiting time calculation unit that calculates the predicted waiting time of the target vehicle within the area based on the position of the target vehicle and the congestion status.

[0033] According to this configuration, the computer can function as the above-described traffic management device, and therefore, the same functions and effects as those of the above-described traffic management device can be achieved.

[0034] [Details of the Embodiments of the Present Disclosure] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. Note that each of the embodiments described below represents a specific example of the present disclosure. The numerical values, shapes, materials, components, component placement and connection configurations, steps, and step order shown in the following embodiments are examples and do not limit the present disclosure. Furthermore, among the components in the following embodiments, components not recited in independent claims are components that can be added arbitrarily. Furthermore, each figure is a schematic diagram and is not necessarily a precise illustration.

[0035] The same components are denoted by the same reference numerals, and their functions and names are also the same, so their explanations will be omitted where appropriate.

[0036] [Overall Configuration of Traffic Management System] FIG. 1 is a diagram illustrating the overall configuration of a traffic management system according to an embodiment of the present disclosure. The traffic management system 100 is a system that manages the traffic of vehicles 3, and includes a traffic management device 1, an on-board device 4 mounted on the vehicle 3, and an administrator terminal 5. In this embodiment, the vehicle 3 is described as a delivery vehicle such as a truck that delivers luggage. However, the use of the vehicle 3 is not limited to luggage delivery, and the traffic management system 100 may also manage the traffic of vehicles 3 for other uses. For example, the vehicle 3 may be a container-carrying vehicle that transports containers to a port facility or the like, a general vehicle that transports people to a parking lot at an event venue, or a dedicated vehicle such as a bus or taxi.

[0037] The in-vehicle device 4 is mounted on a vehicle 3 (hereinafter also referred to as a "target vehicle") owned or managed by the manager, and acquires location information of the vehicle 3. The in-vehicle device 4 transmits probe information including the location of the vehicle 3 and the time when the location was measured to the traffic management device 1 via the network 6.

[0038] The traffic management device 1 creates a traffic plan for a target vehicle. The traffic management device 1 acquires probe information from the on-board device 4 of the target vehicle. The traffic management device 1 generates satellite data based on observation data acquired from an artificial satellite 7. The satellite data is data indicating the results of observation of the ground by the artificial satellite 7, and includes captured images of the ground, etc.

[0039] The artificial satellite 7 flying in the sky is, for example, a commercial satellite. The artificial satellite 7 has functions such as synthetic aperture radar. The artificial satellite 7 is equipped with an antenna. The artificial satellite 7 observes the ground by receiving reflected waves from the ground of microwaves irradiated onto the ground by the antenna. The artificial satellite 7 observes the ground at regular time intervals (for example, every 10 minutes to 1 hour). The artificial satellite 7 outputs the observation results of the ground as observation data (snapshots at the time of observation). The observation data indicates, for example, the backscattering intensity and phase of the microwaves irradiated toward the ground. The observation data also includes information such as the microwave irradiation direction and observation time related to the observation position.

[0040] The satellite data includes not only the captured image, but also the location information of the captured image and the image capture time information. The captured image is an image of the ground captured by the artificial satellite 7. The captured image can be generated based on observation data. The satellite data may also include complex data before being converted into the captured image. The complex data is data obtained based on the observation data.

[0041] The resolution of the captured images included in the satellite data is several tens of centimeters. Therefore, vehicles on the ground are clearly recognizable in the captured images of the satellite data. Furthermore, the position of the captured vehicle can be recognized from the position information in the captured image.

[0042] The traffic management device 1 creates a traffic plan for the target vehicle based on the probe information and satellite data. Note that the traffic management device 1 may also acquire traffic information such as congestion information from another server such as a traffic control server and create a traffic plan taking the traffic information into consideration.

[0043] The manager terminal 5 is a terminal device used by the manager, and receives and displays the video data transmitted from the operation management device 1. Examples of the video data will be described later.

[0044] 2 is a block diagram showing the configuration of the in-vehicle device 4. The in-vehicle device 4 includes a communication unit 41, a Global Navigation Satellite System (GNSS) receiver 42, a clock 43, a storage device 44, and a processor 46.

[0045] The communication unit 41, the GNSS receiver 42, the clock 43, the storage device 44, and the computer program 45 are connected to an in-vehicle network or an internal bus such as a Controller Area Network (CAN) or Ethernet (registered trademark).

[0046] The communication unit 41 includes a communication module for wirelessly connecting the in-vehicle device 4 to the network 6. The communication unit 41 transmits and receives data to and from other devices via the network 6. The communication unit 41 may be provided in a device separate from the in-vehicle device 4.

[0047] The GNSS receiver 42 determines the position of the vehicle 3 using satellite navigation. For example, the GNSS receiver 42 determines the position of the vehicle 3 based on radio waves received from multiple GPS (Global Positioning System) satellites. The position of the vehicle 3 can be determined, for example, by latitude and longitude. Satellite navigation uses a satellite positioning system such as GPS, but is not limited to GPS. For example, a quasi-zenith satellite system may also be used. The GNSS receiver 42 may be provided in a device separate from the in-vehicle device 4. The clock 43 calculates and outputs the current time. The clock 43 may be provided in a device separate from the in-vehicle device 4.

[0048] The storage device 44 is composed of a volatile memory element such as an SRAM (Static Random Access Memory) or a DRAM (Dynamic Random Access Memory), a non-volatile memory element such as a flash memory or an EEPROM (Electrically Erasable Programmable Read Only Memory), or a magnetic storage device such as a hard disk.

[0049] The storage device 44 stores a computer program 45 that is executed by the processor 46. The storage device 44 also stores data that is used or generated when the computer program 45 is executed.

[0050] The processor 46 is configured by a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), etc. The processor 46 includes a probe information providing unit 47 as a functional processing unit realized by reading and executing the computer program 45 stored in the storage device 44.

[0051] The probe information providing unit 47 provides probe information of the vehicle 3 to the traffic management device 1. The probe information is information indicating the position of the vehicle 3 and the time when the vehicle 3 is present at that position. For example, the probe information providing unit 47 acquires the position of the vehicle 3 from the GNSS receiver 42. The probe information providing unit 47 acquires the time when the position of the vehicle 3 was acquired from the clock 43. The probe information providing unit 47 generates probe information indicating the position of the vehicle 3 and the time acquired from the GNSS receiver 42 and the clock 43, respectively. The probe information providing unit 47 transmits the generated probe information to the traffic management device 1 via the communication unit 41.

[0052] 3 is a block diagram showing the configuration of the traffic management device 1. The traffic management device 1 includes a communication unit 11, a storage device 12, and a processor 25. The communication unit 11, the storage device 12, and the processor 25 are connected to each other via an internal bus.

[0053] The communication unit 11 includes a communication module for connecting the traffic management device 1 to the network 6 wirelessly or via a cable. The communication unit 11 transmits and receives data to and from other devices via the network 6. The communication unit 11 also includes a function for communicating with the artificial satellite 7. However, instead of the traffic management device 1 directly communicating with the artificial satellite 7, another server may communicate with the artificial satellite 7, and the communication unit 11 may receive the observation data received from the artificial satellite 7 from the other server.

[0054] The storage device 12 is configured by a volatile memory element such as an SRAM or a DRAM, a non-volatile memory element such as a flash memory or an EEPROM, or a magnetic storage device such as a hard disk.

[0055] The storage device 12 stores a computer program 13 executed by the processor 25. The storage device 12 also stores data used or generated during execution of the computer program 45. The data includes baggage information 14, vehicle information 15, location information 16, driver information 17, operation plan information 18, background image 19, vehicle position information 20, target vehicle position information 21, waiting reference time information 22, waiting time information 23, and map data 24.

[0056] The package information 14 is information about packages to be delivered, and includes, for example, package contents, number of packages, weight, delivery point, and information about work to be performed at the delivery point. Furthermore, if a delivery time for the package is specified, the package information 14 also includes the specified delivery time. The specified delivery time includes at least one of the arrival time of the target vehicle at the package unloading point located within the package delivery point and the departure time of the target vehicle from the unloading point.

[0057] The vehicle information 15 is information about the vehicle 3 used to deliver the package, and includes, for example, identification information of the vehicle 3 and a delivery time period during which the vehicle 3 can deliver the package. The location information 16 is information about a delivery location of the package, and indicates, for example, the location of the delivery location of the package.

[0058] The driver information 17 is information about the driver of the vehicle 3, and includes, for example, the driver's identification information and name.

[0059] The operation plan information 18 is information related to an operation plan for the vehicle 3. For example, the operation plan information 18 indicates actions (work, travel, waiting, rest) that the driver will take from the time the vehicle 3 departs from the base to the time it returns to the base via various points, in association with time.

[0060] The background image 19 is a captured image of the ground generated based on observation data acquired from the artificial satellite 7, and is a captured image that does not include vehicles. More specifically, the background image 19 is a background image of a predetermined area where the target vehicle can enter and exit (hereinafter referred to as the "entry / exit permitted area"). Here, the entry / exit permitted area is an area that is demarcated by predetermined dividing lines. The entry / exit permitted area generally refers to private or public land, and is an area with defined entrances and exits that is separated from external roads or areas. For this reason, public roads and expressways are not included in the entry / exit permitted area. Specifically, the premises of a delivery point, such as a factory, are considered to be the entry / exit permitted area.

[0061] The background image 19 is created in advance based on a known method. For example, the background image may be an image captured during a time when no vehicles are present, such as at night, or may be an image obtained by statistically processing (e.g., averaging) a plurality of captured images.

[0062] The vehicle position information 20 indicates the position of the vehicle identified based on satellite data. The vehicle position information 20 indicates not only the position information of the target vehicle but also the positions of other vehicles. The target vehicle position information 21 indicates the position of the target vehicle obtained from the probe information of the target vehicle.

[0063] The waiting reference time information 22 indicates the waiting time (hereinafter referred to as the "waiting reference time") for each vehicle in a line of vehicles lining up at a baggage unloading point set up within a baggage delivery point. The waiting reference time information 22 is set for each unloading point.

[0064] The waiting time information 23 indicates the actual waiting time of the target vehicle when it is lined up at the unloading point (actually measured waiting time), and the number of vehicles (hereinafter referred to as "waiting vehicles"), including the target vehicle, that are present between the position of the target vehicle and the unloading point within the entry / exit area (hereinafter referred to as "number of waiting vehicles"). In other words, the waiting time indicates the actual measured time from a predetermined point in time to the point at which the target vehicle completes unloading at the unloading point. The number of waiting vehicles indicates the number of waiting vehicles at that predetermined point in time. The waiting time information 23 is provided for each unloading point.

[0065] The map data 24 includes a map showing at least the accessible entry / exit area, the unloading points within the accessible entry / exit area, and the entrances.

[0066] The processor 25 is configured with a CPU, a GPU, etc. The processor 25 reads and executes the computer program 13 stored in the storage device 12. The processor 25 includes, as functional processing units realized by executing the computer program 13, an operation plan creation unit 26, a satellite data acquisition unit 27, a vehicle position acquisition unit 28, a congestion status identification unit 29, a predicted waiting time calculation unit 30, and a display control unit 31.

[0067] The operation plan creation unit 26 creates an operation plan for the target vehicle based on the baggage information 14, vehicle information 15, location information 16, and driver information 17 stored in the storage device 12. For example, the operation plan creation unit 26 sets the specified delivery time indicated by the baggage information 14 as a constraint and sets an equation indicating the baggage delivery time as an objective function. The operation plan creation unit 26 creates an operation plan for the target vehicle by minimizing the objective function within a range that satisfies the constraints using a predetermined optimization method. The operation plan creation unit 26 stores operation plan information 18 indicating the created operation plan in the storage device 12.

[0068] Furthermore, the operation plan creation unit 26 determines whether the constraints on the delivery time of the package are satisfied based on the operation plan of the target vehicle indicated in the operation plan information 18 and the predicted waiting time of the target vehicle within the entry / exit permitted area calculated by the predicted waiting time calculation unit 30, which will be described later. In other words, the operation plan creation unit 26 determines whether the package can be delivered to the current and subsequent delivery points within the specified delivery time. If the operation plan creation unit 26 determines that the constraints on the delivery time of the package are not satisfied, it re-creates an operation plan for the target vehicle from its current location onwards. The re-creation of the operation plan is performed by minimizing the objective function within a range that satisfies the constraints, as described above.

[0069] The satellite data acquisition unit 27 receives observation data of the entry / exit permitted area from the artificial satellite 7 via the communication unit 11. Here, the satellite data acquisition unit 27 determines whether the observation data is of the entry / exit permitted area by referring to the map data 24. The satellite data acquisition unit 27 acquires the satellite data by generating satellite data that shows a captured image of the entry / exit permitted area from the observation data.

[0070] 4 is a diagram showing an example of satellite data generated by the satellite data acquisition unit 27. The satellite data includes a captured image of the inside of an entry / exit area 80. There are multiple vehicles 83 within the entry / exit area 80. There is also a line of seven vehicles 83 on the route from an entrance 81 of the entry / exit area 80 to an unloading point 82. Note that the figures indicating the entrance 81 and the unloading point 82 are not actually included in the captured image.

[0071] The vehicle position acquisition unit 28 identifies the position of the vehicle within the entry / exit area based on the captured image generated by the satellite data acquisition unit 27 and the background image 19 stored in the storage device 12. Specifically, the vehicle position acquisition unit 28 generates a difference image between the captured image and the background image, extracts the vehicle area by binarizing the difference image, and determines the position of the vehicle on the captured image. Because the satellite data includes the position of the captured image, the vehicle position acquisition unit 28 identifies the position of the vehicle by converting the position of the vehicle on the captured image into the position of the vehicle in three-dimensional space. The vehicle position acquisition unit 28 writes the identified vehicle position into the storage device 12 as vehicle position information 20.

[0072] Note that if the vehicle area can be extracted from the captured image alone, the background image does not need to be used. For example, the vehicle position acquisition unit 28 may extract the vehicle area by inputting the captured image into a predetermined learning model. The learning model is configured, for example, with a convolution neural network (CNN), a recurrent neural network (RNN), an autoencoder, or the like, and each parameter of the learning model is determined in advance using a machine learning method such as deep learning. In other words, machine learning is performed using the captured image and the vehicle area in the captured image as training data, and each parameter of the learning model is determined in advance.

[0073] Furthermore, the vehicle position acquisition unit 28 acquires probe information from the in-vehicle device 4 via the communication unit 11. The vehicle position acquisition unit 28 acquires the position information of the target vehicle from the probe information and writes it to the storage device 12 as target vehicle position information 21. However, the in-vehicle position acquisition unit 28 may acquire the position information of the target vehicle by other methods. For example, the vehicle position acquisition unit 28 may acquire the position information of the target vehicle by recognizing an image captured by a camera installed within the entry / exit area and identifying the position of the target vehicle.

[0074] The congestion status identification unit 29 identifies the vehicle congestion status within the entry / exit area. Specifically, the congestion status identification unit 29 reads, from the storage device 12, vehicle position information 20 identified based on satellite data and target vehicle position information 21 identified based on probe information. Based on the positions of vehicles on the route from the entrance of the entry / exit area to the baggage unloading point and the position of the target vehicle, the congestion status identification unit 29 calculates the number of waiting vehicles between the target vehicle and the unloading point as a value indicating the vehicle congestion status. For example, based on the position of the target vehicle, the congestion status identification unit 29 identifies the fifth vehicle from the beginning of the route in the captured image shown in FIG. 4 as the target vehicle. In this case, the congestion status identification unit 29 calculates the number of waiting vehicles as five. In addition, if the target vehicle is not lined up in the line of vehicles at the unloading point because it is outside the entry / exit area, the congestion status identification unit 29 calculates the number of waiting vehicles as the number (8 vehicles) obtained by adding the number of vehicles lined up at the unloading point (7 vehicles in the example of Figure 4) to the number of target vehicles (1 vehicle).

[0075] The predicted waiting time calculation unit 30 calculates a predicted waiting time for the target vehicle by multiplying the number of waiting vehicles calculated by the congestion status identification unit 29 by the reference waiting time indicated by the reference waiting time information 22 corresponding to the unloading point. Here, the predicted waiting time corresponds to the time from the current time until the target vehicle leaves the unloading point after unloading or loading at the unloading point.

[0076] Furthermore, the predicted waiting time calculation unit 30 creates reference waiting time information 22 for each unloading point based on the waiting time information 23. For example, for each unloading point, the predicted waiting time calculation unit 30 calculates a value by dividing the actual waiting time at the unloading point by the number of waiting vehicles for each piece of waiting time information 23 associated with the unloading point. The predicted waiting time calculation unit 30 calculates the reference waiting time for the unloading point by averaging the calculated values. The predicted waiting time calculation unit 30 writes the reference waiting time information 22 indicating the calculated reference waiting time into the storage device 12.

[0077] The display control unit 31 generates video data showing the position of the target vehicle and the positions of vehicles other than the target vehicle on a map showing the entry / exit area in a manner that makes it possible to distinguish between them. The display control unit 31 transmits the generated video data to the manager terminal 5 via the communication unit 11 and causes the manager terminal 5 to display the video data.

[0078] FIG. 5 is a diagram illustrating an example of video data. The video data includes a map including an entry / exit permitted area 70, on which a target vehicle 74 and a vehicle other than the target vehicle 75 are displayed as icons. By displaying the target vehicle 74 and the vehicle 75 in different ways, a user can distinguish between the locations of the target vehicle 74 and the vehicle 75. For example, the icons may be displayed in different colors, shapes, patterns, or sizes, or only one of the icons may be displayed flashing. The video data also highlights the unloading point within the entry / exit permitted area and the route from the entrance of the entry / exit permitted area to the unloading point. For example, the unloading point 72 and the entrance 71 are highlighted by icons. The route 73 from the entrance 71 to the unloading point 72 is also highlighted by a thick dashed line.

[0079] 6 is a block diagram showing the configuration of the administrator terminal 5. The administrator terminal 5 includes a communication unit 51, a storage device 52, a display unit 54, and a processor 55. The communication unit 51, the storage device 52, the display unit 54, and the processor 55 are interconnected via an internal bus.

[0080] The communication unit 51 includes a communication module for connecting the administrator terminal 5 to the network 6 wirelessly or via a wired connection. The communication unit 51 transmits and receives data to and from other devices via the network 6.

[0081] The storage device 52 is configured by a volatile memory element such as an SRAM or a DRAM, a non-volatile memory element such as a flash memory or an EEPROM, or a magnetic storage device such as a hard disk. The storage device 52 stores the computer program 53 executed by the processor 55. The storage device 52 also stores data used or generated when the computer program 53 is executed.

[0082] The display unit 54 is configured to include a liquid crystal display or an organic EL (electroluminescence) display, etc., and displays video data. The display unit 54 may be configured to be installed outside the administrator terminal 5 and connected to the administrator terminal 5.

[0083] The processor 55 is configured by a CPU, a GPU, etc. The processor 55 reads and executes a computer program 53 stored in the storage device 52. The processor 55 includes a display control unit 56 as a functional processing unit realized by executing the computer program 53.

[0084] The display control unit 56 receives the video data from the traffic management device 1 via the communication unit 51. The display control unit 56 displays the received video data on the display unit 54. As a result, the display unit 54 displays the video data as shown in FIG.

[0085] The following describes the processing executed by the traffic management system 100. [Method for generating vehicle position information] Fig. 7 is a flowchart showing an example of the processing procedure for generating vehicle position information 20 executed by the traffic management device 1. The processing shown in Fig. 7 is executed every time observation data is received from a satellite 7.

[0086] The satellite data acquisition unit 27 refers to the operation plan information 18 to identify an entry / exit permitted area that includes a point that the target vehicle is scheduled to visit, and receives observation data of the entry / exit permitted area from the artificial satellite 7 via the communication unit 11 (step S11). The satellite data acquisition unit 27 receives the observation data at each time interval that the artificial satellite 7 observes the ground.

[0087] The satellite data acquisition unit 27 generates image data including a captured image as satellite data from the received observation data (step S12). For example, the satellite data acquisition unit 27 generates image data including a captured image made up of pixel values ​​that digitize the backscattering intensity indicated by the observation data. Although image data will be described below as satellite data, the observation data itself may be used as satellite data instead of image data, or data generated from the observation data may be used as satellite data. For example, the phase difference or intensity difference of radio waves received by the artificial satellite 7 may be used as satellite data.

[0088] The vehicle position acquisition unit 28 identifies the position of the vehicle within the entry / exit area based on the image data generated in step S12 and the background image 19 stored in the storage device 12 (step S13).

[0089] The vehicle position acquisition unit 28 writes the identified vehicle position into the storage device 12 as vehicle position information 20 (step S14).

[0090] 8 is a flowchart showing an example of a processing procedure for generating the target vehicle position information 21 executed by the traffic management device 1. The processing shown in FIG. 8 is executed every time probe information is received from the in-vehicle device 4.

[0091] The vehicle position acquisition unit 28 receives probe information transmitted from the vehicle-mounted device 4 at predetermined intervals from the vehicle-mounted device 4 via the communication unit 11 (step S21).

[0092] The vehicle position acquisition unit 28 identifies the current position of the target vehicle by reading the position information of the target vehicle from the probe information (step S22).

[0093] The vehicle position acquisition unit 28 writes the current position of the target vehicle as target vehicle position information 21 in the storage device 12 (step S23).

[0094] 9 is a flowchart showing an example of the processing steps of updating the operation plan of a target vehicle executed by the operation management device 1. The processing shown in FIG. 9 is executed at a predetermined cycle (for example, every 10 minutes) or whenever a predetermined event occurs (for example, when the satellite data acquisition unit 27 generates new image data).

[0095] The operation plan creation unit 26 reads out the target vehicle position information 21 and the map data 24 from the storage device 12. The operation plan creation unit 26 determines whether the target vehicle is within an entry / exit permitted area based on the read target vehicle position information 21 and map data 24 (Step S31). That is, the operation plan creation unit 26 specifies the range of the entry / exit permitted area based on the map data 24. The operation plan creation unit 26 determines whether the target vehicle is within that range based on the target vehicle position information 21.

[0096] If it is determined that the target vehicle is within the entry / exit permitted area (YES in step S31), the congestion status identification unit 29 reads out the vehicle position information 20 and the target vehicle position information 21 from the storage device 12. The congestion status identification unit 29 calculates the number of waiting vehicles between the target vehicle and the unloading point based on the read out vehicle position information 20 and the target vehicle position information 21 (step S32). The congestion status identification unit 29 also refers to the output of a clock (not shown) and stores the time at which it was determined that the target vehicle is within the entry / exit permitted area in the storage device 12.

[0097] The congestion status identification unit 29 repeatedly refers to the target vehicle position information 21 and waits until the target vehicle departs from the unloading point (step S33).

[0098] When the target vehicle departs from the unloading point (YES in step S33), the congestion status identification unit 29 refers to the time when the target vehicle was determined to be within the entry / exit area stored in the memory device 12 and the clock output, and calculates the waiting time, which is the time from when the target vehicle was determined to be within the entry / exit area to when it departs from the unloading point (step S34).

[0099] The congestion status identification unit 29 stores the waiting time information 23 indicating the number of waiting vehicles and the waiting time in the storage device 12 in association with the unloading point (step S35). The waiting time information 23 stored in the storage device 12 is used when creating the waiting reference time information 22.

[0100] If it is determined that the target vehicle is not within the entry / exit area (NO in step S31), the congestion status identification unit 29 reads out vehicle position information 20 of the next location (entrance / exit area) that the target vehicle will visit from the storage device 12. Based on the read vehicle position information 20, the congestion status identification unit 29 calculates the number of waiting vehicles lined up at the unloading point within the entry / exit area that the target vehicle will visit next (step S36). In other words, the congestion status identification unit 29 calculates the number of waiting vehicles by adding the number of target vehicles (1) to the number of vehicles lined up at the unloading point.

[0101] The predicted waiting time calculation unit 30 reads out the waiting reference time information 22 corresponding to the unloading point from the storage device 12. The predicted waiting time calculation unit 30 calculates the predicted waiting time of the target vehicle at the unloading point by multiplying the number of waiting vehicles calculated in step S36 by the waiting time indicated by the read waiting reference time information 22 (step S37).

[0102] The operation plan creation unit 26 predicts the departure time from the next unloading point based on the calculated predicted waiting time (step S38). For example, the operation plan creation unit 26 calculates the predicted arrival time at the next unloading point based on the distance to the next unloading point and a predetermined traveling speed. The operation plan creation unit 26 adds the predicted waiting time to the calculated predicted arrival time to calculate the predicted departure time from the next unloading point.

[0103] The operation plan creation unit 26 determines whether the target vehicle can operate according to the operation plan, assuming that the target vehicle departs from the next unloading point at the expected departure time (step S39). In other words, the operation plan creation unit 26 determines whether the target vehicle can deliver packages to the current and subsequent delivery points within the specified delivery time, assuming that the target vehicle departs from the next unloading point at the expected departure time.

[0104] If it is determined that the target vehicle can be operated according to the operation plan (YES in step S39), the operation plan creation unit 26 ends the processing.

[0105] If it is determined that the target vehicle cannot be operated according to the operation plan (NO in step S39), the operation plan creation unit 26 updates the operation plan of the target vehicle (step S40). That is, the operation plan creation unit 26 creates an operation plan for the target vehicle from the current location onwards by minimizing an objective function that indicates the delivery time of the package under the constraint, using the specified delivery time indicated by the package information 14 as a constraint.

[0106] The operation plan creation unit 26 stores the operation plan information 18 indicating the updated operation plan for the target vehicle in the storage device 12 (Step S41).

[0107] [Operation Plan Update Processing] A specific example of the operation plan update processing (step S40 in FIG. 9) will be described below. Movement of target vehicles when the operation plan is not updated will be described with reference to FIGS.

[0108] 10 is a diagram showing an operation plan for a target vehicle that was created before the target vehicle departed from the base, and the operation record of the target vehicle. The upper part shows the operation plan, and the lower part shows the operation record. The horizontal axis represents time. The same applies to FIGS. 11 to 14 described below.

[0109] As shown in FIG. 10 , according to the operation plan, the target vehicle will perform work at a base from 9:00 to 9:30, and depart from the base at 9:30 to travel toward Company A, which is the delivery point. The target vehicle will wait at Company A's unloading point from 10:00 to 10:15, and perform work (unloading or loading) at Company A from 10:15 to 10:45. The target vehicle will depart from Company A at 10:45 to travel toward Company B. The target vehicle will take a break from 12:00 to 13:00, and perform work at Company B from 13:00 to 13:45. The target vehicle will depart from Company B at 13:45 to travel toward Company C. The target vehicle will wait at Company C's unloading point from 14:30 to 14:45, and perform work at Company C from 14:45 to 15:30. The target vehicle will depart from Company C at 15:30 to travel toward Company D. The target vehicle will wait at Company D's unloading point from 16:00 to 16:15, and will perform work at Company D from 16:15 to 17:15. The target vehicle will depart Company D at 17:15 and travel toward the base. The target vehicle will perform work at the base from 17:45 to 18:15.

[0110] The operation results up to the current time of 13:30 are almost as planned. At this point, the congestion status identification unit 29 and the predicted waiting time calculation unit 30 calculate that the number of waiting vehicles at Company C's unloading point where the target vehicle is heading is 10, and the predicted waiting time is 75 minutes. On the other hand, the congestion status identification unit 29 and the predicted waiting time calculation unit 30 calculate that the number of waiting vehicles at Company D's unloading point where the target vehicle is heading is 1, and the predicted waiting time is 4 minutes.

[0111] 11 is a diagram showing an operation plan for a target vehicle created before the target vehicle departs from the base, and the operation record of the target vehicle. The upper part shows the same operation plan as shown in FIG. 10. The lower part shows the operation record until the target vehicle returns to the base when the operation plan is not changed.

[0112] As mentioned above, the predicted waiting time at the unloading point of Company C is 75 minutes, which is 60 minutes longer than the waiting time of 15 minutes (14:30 to 14:45) in the operation plan. This may cause delays in work at Company C and Company D, resulting in situations where the package delivery time constraints are not met.

[0113] According to Figure 11, the plan was to depart from company C at 15:30, but the actual departure time was 16:45. Also, the plan was to depart from company D at 17:15, but the actual departure time was 18:30.

[0114] Next, the movement of target vehicles when an operation plan is updated will be described with reference to FIG. 10 and FIG. 12 to FIG.

[0115] 10 , the predicted waiting time calculation unit 30 calculates that the predicted waiting time at the unloading point of Company C at the current time of 13:30 is 75 minutes, so if the target vehicle is operated according to the operation plan, it will not be able to make the delivery time specified by Company D, and it is determined that the vehicle cannot be operated according to the operation plan. Therefore, the operation plan creation unit 26 updates the operation plan.

[0116] 12 is a diagram showing an updated operation plan for a target vehicle and the operation record of the target vehicle. The upper part shows the updated operation plan, and the lower part shows the operation record of the target vehicle as of 13:30. As shown in the upper part, the operation plan creation unit 26 updates the operation plan by switching the order of visits to Company C and Company D. As a result, the constraints on the designated delivery times of Company C and Company D are satisfied.

[0117] 13 is a diagram showing an updated operation plan for a target vehicle and the operation record of the target vehicle. The upper part is the same as the updated operation plan shown in FIG. 12. The lower part shows the operation record as of 16:15.

[0118] As described above, the predicted waiting time at Company D's unloading point calculated by the predicted waiting time calculation unit 30 at 13:30 is 4 minutes. Therefore, the actual operation results indicate that the vehicle was able to depart from Company D as planned. Furthermore, at this time, the number of waiting vehicles at Company C's unloading point is 2, and the predicted waiting time is 15 minutes. By moving Company C's visit later than Company D's, the number of waiting vehicles at Company C's unloading point is reduced from 10 to 2, and the predicted waiting time is reduced to 15 minutes. The predicted waiting time of 15 minutes for Company C calculated by the predicted waiting time calculation unit 30 is the same as the predicted waiting time of 15 minutes (16:30 to 16:45) indicated in the operation plan. Therefore, the operation plan creation unit 26 determines that the target vehicle can operate according to the operation plan and does not create an operation plan.

[0119] 14 is a diagram showing the updated operation plan for the target vehicle and the operation record of the target vehicle. The upper part is the same as the updated operation plan shown in FIG. 12. The lower part shows the operation record as of 18:30. It shows that the target vehicle was able to operate according to the updated operation plan as of 18:30.

[0120] 15 is a flowchart showing an example of the processing procedure for displaying video data executed by the traffic management device 1. The displaying process for video data is executed, for example, in response to a request to transmit video data from the manager terminal 5. The display control unit 31 reads out the target vehicle position information 21 from the storage device 12 (step S51).

[0121] The display control unit 31 identifies the position of the target vehicle based on the target vehicle position information 21, and reads vehicle position information 20 indicating the positions of vehicles around the target vehicle from the storage device 12 (step S52). The display control unit 31 reads map data 24 from the storage device 12 (step S53).

[0122] The display control unit 31 creates video data based on the read target vehicle position information 21, vehicle position information 20, and map data 24 (step S54). An example of the video data is as shown in Fig. 5. The position of the target vehicle 74 is obtained from the target vehicle position information 21. The positions of vehicles 75 other than the target vehicle 74 are obtained by subtracting the position of the target vehicle indicated by the target vehicle position information 21 from the positions of the vehicles indicated by the vehicle position information 20.

[0123] The display control unit 31 transmits the created video data to the manager terminal 5 via the communication unit 11 (step S55). The manager terminal 5 displays the received video data. This allows the manager using the manager terminal 5 to confirm the position of the target vehicle 74 within the entry / exit permitted area 70. In addition, the manager can confirm the vehicles lined up at the unloading point 72.

[0124] According to an embodiment of the present disclosure, it is possible to accurately identify, for example, the number of vehicles as an indication of the vehicle congestion status by using image data obtained by observing the entry / exit area from an artificial satellite 7. Therefore, it is possible to accurately calculate the predicted waiting time of the target vehicle within the entry / exit area by calculating the predicted waiting time based on the position and congestion status of the target vehicle.

[0125] Furthermore, by using synthetic aperture radar, it is possible to identify the vehicle congestion status in areas where entry and exit are permitted but not subject to the generation of traffic information, and therefore it is possible to accurately calculate the predicted waiting time of a target vehicle in an area where entry and exit are permitted but not subject to the generation of traffic information.

[0126] The predicted waiting time calculation unit 30 of the traffic management device 1 calculates the predicted waiting time from the waiting reference time actually measured in advance and the number of waiting vehicles indicating the vehicle congestion state, so that the predicted waiting time can be calculated accurately.

[0127] The waiting reference time is determined based on the value obtained by dividing the actual measured time until unloading is completed at the unloading point, collected for each target vehicle, by the number of waiting vehicles. Thus, the waiting reference time can represent the waiting time per waiting vehicle.

[0128] The display control unit 31 of the traffic management device 1 displays video data on a map showing the entry / exit permitted area, in a manner that allows the position of the target vehicle to be distinguished from the positions of vehicles other than the target vehicle. A user viewing the video data can see vehicles waiting ahead of the target vehicle within the entry / exit permitted area. This allows the user to intuitively understand how long they should wait until they reach their destination.

[0129] The display control unit 31 of the operation management device 1 displays video data that highlights a predetermined unloading point within the entry / exit area and the route from the entrance of the entry / exit area to the unloading point. A user who views the video data can check vehicles waiting on the route to the unloading point. This allows the user to intuitively understand how long they should wait until the unloading point.

[0130] The operation plan creation unit 26 of the operation management device 1 determines whether the package delivery time constraint is met based on a predetermined operation plan for the target vehicle and the calculated predicted waiting time. If the operation plan creation unit 26 determines that the constraint is not met, it creates a new operation plan. For example, if the calculated predicted waiting time is longer than the operation plan and the package cannot be delivered to a delivery point after the current location within the specified delivery time, the operation plan can be created again. This increases the probability of successful delivery of packages that meet the delivery time constraint.

[0131] The constraint on the delivery time of the package includes at least one of a constraint on the arrival time of the target vehicle at the unloading point and a constraint on the departure time of the target vehicle from the unloading point, thereby increasing the probability of successful delivery of the package that satisfies at least one of the constraint on the arrival time of the target vehicle at the unloading point and the constraint on the departure time of the target vehicle from the unloading point.

[0132] [Variation 1] In the above-described embodiment, the reference waiting time indicated by the reference waiting time information 22 for each unloading point is not differentiated by vehicle type. However, the reference waiting time may be different for each vehicle type. For example, the reference waiting time information 22 for each unloading point may indicate a reference waiting time for each vehicle load category.

[0133] When identifying the position of the vehicle within the entry / exit area, the vehicle position acquisition unit 28 identifies the vehicle's load category. For example, the vehicle position acquisition unit 28 calculates the vehicle size based on the vehicle area extracted from the captured image. The vehicle position acquisition unit 28 identifies the load category based on the vehicle size and writes it into the vehicle position information 20. Note that for a target vehicle, the vehicle position acquisition unit 28 identifies the load category based on probe information acquired from the in-vehicle device 4 of the target vehicle and writes it into the target vehicle position information 21. In this case, it is assumed that the probe information includes load information.

[0134] When calculating the number of waiting vehicles at the unloading point within the entry / exit area, the congestion status identification unit 29 classifies the number of waiting vehicles by load capacity category based on the vehicle position information 20 and the target vehicle position information 21. For example, if the number of waiting vehicles is six, the congestion status identification unit 29 classifies the number of waiting vehicles as follows: two vehicles with a "large" load capacity, one vehicle with a "medium" load capacity, and three vehicles with a "small" load capacity.

[0135] The predicted waiting time calculation unit 30 calculates a predicted waiting time based on the number of waiting vehicles classified by the congestion status identification unit 29 and the standard waiting time for each load category. For example, the predicted waiting time calculation unit 30 calculates the predicted waiting time according to the following formula 1. Predicted waiting time = TL x NL + TM x NM + TS x NS ... (Formula 1) Where, TL: standard waiting time for a "heavy" load TM: standard waiting time for a "medium" load TS: standard waiting time for a "light" load NL: number of vehicles with a "heavy" load NM: number of vehicles with a "medium" load NS: number of vehicles with a "light" load

[0136] According to the first modification, the predicted waiting time can be calculated based on the number of waiting vehicles for each load weight category and the reference waiting time corresponding to that category. The time required for unloading or loading varies depending on the load weight. For example, the larger the load weight, the longer the time required for unloading or loading. Therefore, by classifying the waiting vehicles according to the load weight category, the predicted waiting time can be calculated with high accuracy.

[0137] [Variation 2] In the above-described embodiment, the predicted waiting time calculation unit 30 calculated the predicted waiting time of the target vehicle by multiplying the number of waiting vehicles by the waiting reference time, but the method of calculating the predicted waiting time is not limited to this.

[0138] For example, the predicted waiting time calculation unit 30 may derive the predicted waiting time by inputting the captured image into a predetermined learning model. The learning model is configured, for example, by a CNN, an RNN, an autoencoder, or the like, and each parameter of the learning model is determined in advance by a machine learning method such as deep learning. In other words, machine learning is performed using the captured image and the actual measured value of the waiting time as training data, and each parameter of the learning model is determined in advance.

[0139] [Modification 3] In the above-described embodiment, the satellite 7 has the function of a synthetic aperture radar, but the satellite 7 may also have an optical sensor in addition to or instead of the synthetic aperture radar. The optical sensor is, for example, a two-dimensional image sensor that captures images of the ground to generate captured images.

[0140] The satellite data acquisition unit 27 of the traffic management device 1 receives captured images of the entry / exit area, location information of the captured images, and information on the time of capture from the artificial satellite 7 via the communication unit 11. The image data acquisition unit 27 generates satellite data from the received information.

[0141] By using an optical sensor, it is possible to identify the vehicle congestion status in an entry / exit permitted area that is not subject to the generation of traffic information, and therefore to accurately calculate the predicted waiting time of a target vehicle in an entry / exit permitted area that is not subject to the generation of traffic information.

[0142] [Note] Each process (each function) in the above-described embodiments is realized by a processing circuit including one or more processors. The processing circuit may be configured as an integrated circuit or the like that combines one or more memories, various analog circuits, and various digital circuits in addition to the one or more processors. The one or more memories store programs (instructions) that cause the one or more processors to execute each of the processes. The one or more processors may execute each of the processes according to the program read from the one or more memories, or according to a logic circuit designed in advance to execute each of the processes. The processor may be a CPU, GPU, DSP (Digital Signal Processor), FPGA (Field Programmable Gate Array), ASIC (Application Specific Integrated Circuit), or any other processor suitable for computer control. Note that the physically separated processors may cooperate with each other to execute each of the processes. For example, the processors mounted on a plurality of physically separated computers may cooperate with each other to execute the processes via a network such as a local area network (LAN), a wide area network (WAN), the Internet, etc. The program may be installed into the memory from an external server device or the like via the network, or may be distributed in a state stored on a recording medium such as a CD-ROM (Compact Disc Read Only Memory), a DVD-ROM (Digital Versatile Disc Read Only Memory), or a semiconductor memory, and installed into the memory from the recording medium.

[0143] Furthermore, some or all of the functions of each device in the above-described embodiments may be provided by cloud computing. That is, some or all of the functions of each device may be realized by a cloud server. Furthermore, at least some of the above-described embodiments and variations may be combined in any manner.

[0144] The embodiments disclosed herein should be considered to be illustrative in all respects and not restrictive. The scope of the present invention is defined by the claims, not by the above meaning, and is intended to include all modifications within the meaning and scope of the claims.

[0145] REFERENCE SIGNS LIST 1 Operation management device 3 Vehicle 4 In-vehicle device 5 Administrator terminal 6 Network 7 Artificial satellite 11 Communication unit 12 Storage device 13 Computer program 14 Baggage information 15 Vehicle information 16 Location information 17 Driver information 18 Operation plan information 19 Background image 20 Vehicle position information 21 Target vehicle position information 22 Waiting reference time information 23 Waiting time information 24 Processor 25 Operation plan creation unit 26 Satellite data acquisition unit 27 Vehicle position acquisition unit 28 Congestion status identification unit 29 Estimated waiting time calculation unit 30 Display control unit 41 Communication unit 42 GNSS receiver 43 Clock 44 Storage device 45 Computer program 46 Processor 47 Probe information provision unit 51 Communication unit 52 Storage device 53 Computer program 54 Display unit 55 Processor 56 Display control unit 70 Entry / exit permitted area 71 Entrance 72 Location 73 Route 74 Target vehicle 75 Vehicle 80 Entry / exit permitted area 81 Entrance 82 Location 83 Vehicle 100 Operation management system

Claims

1. a satellite data acquisition unit that acquires satellite data that observes a predetermined area; a vehicle position acquisition unit that acquires the position of the vehicle within the area based on the satellite data; a congestion status determination unit that determines a vehicle congestion status within the area based on the positions of vehicles within the area; an estimated waiting time calculation unit that calculates an estimated waiting time of the target vehicle within the area based on the position of the target vehicle and the congestion state.

2. The traffic control device according to claim 1 , wherein the satellite data includes an image of the area captured by a synthetic aperture radar or an optical sensor.

3. the congestion status identification unit calculates the number of waiting vehicles, including the target vehicle, that are present between the position of the target vehicle and a predetermined unloading point within the area, based on the position of the target vehicle and the positions of vehicles within the area; the predicted waiting time calculation unit calculates the product of the number of waiting vehicles and a predetermined waiting reference time as the predicted waiting time; The operation management device described in claim 1 or claim 2, wherein the waiting standard time is a predetermined time based on the actual measured time collected for each of the multiple target vehicles from a predetermined point in time to the point at which unloading by the target vehicle at the unloading point is completed and the number of waiting vehicles at the predetermined point in time.

4. The traffic management device according to claim 3 , wherein the reference waiting time is determined based on a value obtained by dividing the actual measurement time collected for each of the target vehicles by the number of waiting vehicles.

5. the waiting reference time is associated with a vehicle load category, The vehicle position acquisition unit further calculates a classification of the load capacity of the vehicle in the area based on the satellite data, The operation management device of claim 3, wherein the predicted waiting time calculation unit classifies the number of waiting vehicles into the categories calculated by the vehicle position acquisition unit, and calculates the predicted waiting time based on the number of vehicles for each category after classification and the waiting reference time associated with the category.

6. 3. The traffic management device according to claim 1, further comprising a display control unit that displays video data showing the position of the target vehicle and the positions of vehicles other than the target vehicle in a manner that allows them to be distinguished on a map showing the area.

7. The operation management device according to claim 6, wherein the display control unit displays the video data in an emphasized manner showing a predetermined unloading point within the area and a route from an entrance of the area to the unloading point.

8. 3. The operation management device according to claim 1, further comprising an operation plan creation unit that determines whether a constraint on the delivery time of a package is satisfied based on a predetermined operation plan of the target vehicle and the calculated predicted waiting time, and re-creates the operation plan if it is determined that the constraint is not satisfied.

9. The traffic management device according to claim 8 , wherein the constraints include at least one of a constraint on an arrival time of the target vehicle at an unloading point and a constraint on a departure time of the target vehicle from the unloading point.

10. A step in which an operation management device acquires satellite data observing a predetermined area; the traffic management device acquiring a position of the vehicle within the area based on the satellite data; The traffic management device specifies a vehicle congestion state in the area based on a position of the vehicle in the area; The traffic management device calculates a predicted waiting time of the target vehicle within the area based on the position of the target vehicle and the congestion status.

11. Computer, a satellite data acquisition unit that acquires satellite data that observes a predetermined area; a vehicle position acquisition unit that acquires the position of the vehicle within the area based on the satellite data; a congestion status determination unit that determines a vehicle congestion status within the area based on the positions of vehicles within the area; and A computer program for causing the computer to function as an estimated waiting time calculation unit that calculates an estimated waiting time of the target vehicle within the area based on the position of the target vehicle and the congestion status.