Communication bandwidth calculation device, communication bandwidth calculation method, and program

Abstract

A communication bandwidth calculation device according to the present invention calculates a communication bandwidth of a communication network that provides a communication service related to autonomous driving vehicles with appropriate communication service quality. The communication band calculation device includes an in-road-region communication amount prediction unit that predicts the number of autonomous driving vehicles at a future time point in a road region regarding a relevant area in which a communication facility is designed, estimates a communication amount per one autonomous driving vehicle generated in association the autonomous driving vehicles, and predicts a communication amount in the road region where the autonomous driving vehicles pass, and a communication bandwidth calculation unit that calculates the communication facility so as to satisfy the communication service quality in the relevant area with respect to the in-road region communication amount.

Description

Communication bandwidth calculation device, communication bandwidth calculation method, and program

[0001] This invention relates to a technique for calculating communication bandwidth in a communication network.

[0002] Traditionally, regardless of whether the communication is via fixed lines (wired) or wireless communication using mobile terminals, communication services provided over a communication network can be defined as the quality of communication services demanded by users, such as QoS (Quality of Service) or QoS (Quality of Experience). Communication service providers design, operate, and manage their communication networks to achieve such communication service quality.

[0003] To achieve the necessary communication service quality, communication networks regularly measure the traffic volume of the communication services they provide, and at the same time, analyze and evaluate the traffic characteristics unique to each communication service, thereby acquiring and accumulating knowledge about the traffic characteristics of those communication services. In order to provide communication services economically and to build communication resources in a timely manner without excess or deficiency, there is a need for technology that can utilize the knowledge thus obtained to predict future communication traffic volume and calculate the appropriate amount of communication equipment.

[0004] Prior art documents relating to communication bandwidth calculation technology include, for example, Patent Document 1.

[0005] Japanese Patent Publication No. 2018-157311

[0006] Research and development of technologies for the practical application of self-driving connected vehicles (Self-driving vehicles) are progressing rapidly, and they are expected to be implemented in society in the near future.

[0007] New communication services related to autonomous vehicles are expected to exhibit new traffic characteristics (spatial and temporal demand fluctuations and communication volume) that differ significantly from conventional mobile communication terminals (smartphones, tablets, laptops, etc.).

[0008] Therefore, in a communication network that provides communication services related to autonomous vehicles with appropriate service quality, the communication network will be required to secure communication bandwidth (communication capacity) of communication equipment that can provide the necessary service quality for the communication services related to autonomous vehicles in relation to the volume of communication for those services.

[0009] However, conventional technology did not include a method for calculating the communication bandwidth of a communication network that provides communication services related to autonomous vehicles with appropriate communication service quality.

[0010] This invention has been made in view of the above points, and aims to provide a technology that enables the calculation of the communication bandwidth of a communication network that provides communication services related to autonomous vehicles with appropriate communication service quality.

[0011] According to the disclosed technology, a communication bandwidth calculation device is provided for calculating the communication bandwidth of a communication network that provides communication services related to autonomous vehicles with appropriate communication service quality, comprising: a road area communication volume prediction unit that predicts the number of autonomous vehicles at a future point in time within the road area for a target area on which communication equipment is designed, estimates the amount of communication per vehicle related to autonomous vehicles, and predicts the amount of communication within the road area on which autonomous vehicles travel; and a communication bandwidth calculation unit that calculates communication equipment in the target area to satisfy the communication service quality with respect to the amount of communication within the road area.

[0012] The disclosed technology provides a method for calculating the communication bandwidth of a communication network that provides communication services related to autonomous vehicles with appropriate quality of service.

[0013] This is a diagram illustrating road traffic of autonomous vehicles and communications related to autonomous vehicles. This is a diagram illustrating communication categories (A) to (E) that occur in relation to autonomous vehicles. This is a diagram illustrating communications of communication categories (A) to (E) that occur in relation to autonomous vehicles (specific example). This is a diagram illustrating the correspondence between communications of communication categories (A) to (E) and communication service quality classes (specific example). This is an overall block diagram showing the configuration of a communication bandwidth calculation device according to one embodiment of the present invention. This is a block diagram showing the internal configuration of the arithmetic processing unit according to one embodiment of this invention. This is a flowchart (1) showing the processing of the arithmetic processing unit (2). This is a flowchart (3) showing the processing of the arithmetic processing unit (4). This is a diagram showing an example of the hardware configuration of the device.

[0014] Hereinafter, embodiments of the present invention (this embodiment) will be described with reference to the drawings. The embodiments described below are merely examples, and the embodiments to which the present invention is applied are not limited to the embodiments described below.

[0015] The following describes a technique for calculating the required communication bandwidth or equipment capacity by predicting the amount of communication traffic at a future design target period, in order to provide the communication service quality required by users of communication services, for communication equipment in a communication network where the amount of communication traffic fluctuates and increases (decreases).

[0016] Below, we will first explain the problem in more detail, and then describe the technology related to this embodiment in detail.

[0017] Research and development of technologies for the practical application of self-driving connected vehicles (Self-driving vehicles) are progressing rapidly, and they are expected to be implemented in society in the near future.

[0018] (New communication services related to autonomous vehicles) A ​​fully autonomous vehicle is said to be a car that can drive safely without external communication, or its control functions. However, in reality, autonomous vehicles will need to utilize new communication services, such as large-scale data communication.

[0019] Specifically, it is essential for an autonomous vehicle to perform timely downloads for updating the autonomous driving control program, communications for obtaining 3D road map data until reaching the destination, and the like.

[0020] In addition, in order to support safe road traffic for all motor vehicles including those not for autonomous driving, the development and construction of advanced road traffic systems (Intelligent Transport Systems: ITS) promoted by the Ministry of Land, Infrastructure, Transport and Tourism are underway. With the enhancement of the AI functions and performance mounted on autonomous vehicles, it is predicted that the communications with road infrastructure including traffic signal devices will be further advanced and activated. At the same time, it is also expected that the development of various vehicle-to-vehicle communications and the like based on the original / standard specifications by vehicle manufacturers will be studied and introduced.

[0021] In addition, since the control technology of autonomous vehicles is a technology under development, according to the (Revised) Road Traffic Act, for communications between an autonomous vehicle and an autonomous vehicle control room (remote monitoring / operation room), remote monitoring (real-time monitoring of the operation status and prompt response in case of abnormality), emergency response (remote operation for safe stop), operation management (instructions according to the operation plan and traffic conditions), data collection and analysis (for enhancing the safety and efficiency of operation), etc. are defined.

[0022] Furthermore, it is also assumed that the communications for entertainment during travel time such as video viewing and games will develop by using the communication functions, displays, and audio devices built in autonomous vehicles by the passengers in the autonomous vehicle and the drivers who are being released from driving.

[0023] In the present embodiment, regardless of whether the autonomous driving function is complete or incomplete, a motor vehicle as a communication terminal / information communication device that performs the communications including the above related to the autonomous vehicle is called an autonomous vehicle.

[0024] (New traffic characteristics of new communication services related to autonomous vehicles) Since the pedestrian sidewalk and the vehicle lane of motor vehicles including autonomous vehicles are separated, the space where communications by smartphones and the like held by pedestrians occur and the space where communications of autonomous vehicles occur are adjacent but different spaces.

[0025] The higher the frequency band enabling wideband communication services, the shorter the effective communication distance. Considering this, in order to provide wideband mobile communication services in response to the use of higher frequency bands due to the development of wireless technology and the spread of autonomous vehicles, it is clear that it is necessary to modify the design of the access space of mobile communication terminals and enhance communication resources so that the conventional base station coverage area designed mainly for communication terminals held by pedestrians can also support communication related to autonomous vehicles.

[0026] As described above, since the technology of autonomous vehicles is still in development, the (Revised) Road Traffic Law stipulates remote monitoring (real-time monitoring of the driving situation and prompt response in case of abnormalities), emergency response (remote operation for safe stop), operation management (instructions according to the operation plan and traffic situation), data collection and analysis (to improve the safety and efficiency of operation), etc. by the control room (remote monitoring / operation room) of autonomous vehicles for the safe operation of autonomous vehicles.

[0027] Specifically, communication for transmitting the video from the driving camera of an autonomous vehicle to the control room of the autonomous vehicle, or communication for sending an automatic driving control signal for safe stop by remote operation in the emergency response to an autonomous vehicle, etc. are carried out. It is also clear that these communications have different communication traffic characteristics compared to communication by conventional smartphones, etc., and the required quality of service for the required communication services is strict.

[0028] Alternatively, in the video viewing inside the aforementioned autonomous vehicle, compared to conventional smartphones, the in-vehicle display is larger and the acoustic environment inside the vehicle is better than when using a smartphone outdoors. Therefore, due to the requirement for higher definition video and higher quality audio, the communication data volume further increases and higher communication service quality is required. As a result, it is considered that further enhancement of the capacity of communication facilities is required. That is, even for the same communication services as before, it is considered that there are some cases where the communication traffic characteristics change depending on the environment of the vehicle.

[0029] Based on the above, it is believed that the new communication services related to autonomous vehicles will exhibit new traffic characteristics (spatial and temporal demand fluctuations and communication volume) that differ significantly from conventional mobile communication terminals (smartphones, tablets, laptops, etc.). Therefore, we believe it is important to approach autonomous vehicles as entirely new communication terminals / information and communication devices.

[0030] Therefore, in a communication network that provides communication services related to autonomous vehicles with appropriate service quality, the communication network will be required to secure communication bandwidth (communication capacity) of communication equipment that can provide the necessary service quality for the communication services related to autonomous vehicles in relation to the volume of communication for those services.

[0031] Moreover, as autonomous driving control functions evolve from imperfect to perfect, and as autonomous vehicles equipped with these functions become widely adopted in society from scratch, the communication network is required to be able to provide communication services economically while adapting to diverse and complex changes in circumstances over a long period of time.

[0032] However, conventional technology did not include a method for calculating the communication bandwidth of a communication network that provides communication services related to autonomous vehicles with appropriate communication service quality.

[0033] The technology according to this embodiment solves the above-mentioned problems. Specifically, the technology according to this embodiment aims to provide a technology that enables the calculation of the communication bandwidth of a communication network that provides communication services related to autonomous vehicles with appropriate communication service quality.

[0034] (Outline of the Embodiment) First, an outline of this embodiment will be described. In this embodiment, a communication bandwidth calculation device 10 is provided that calculates the communication bandwidth of a communication network that provides communication services related to autonomous vehicles with appropriate communication service quality.

[0035] The communication bandwidth calculation device 10 includes a road area communication volume prediction unit 16D, a non-road area communication volume prediction unit 16E, and a communication bandwidth calculation unit 16F.

[0036] The road area communication volume prediction unit 16D predicts the number of autonomous vehicles at a future point in time within the road area for the target area on which communication equipment is designed, estimates the amount of communication per vehicle related to autonomous vehicles, and predicts the amount of communication within the road area on which autonomous vehicles will travel.

[0037] The non-road area communication volume prediction unit 16E predicts the volume of non-road area communication, which is conventional communication by pedestrians, excluding communication with autonomous vehicles, within the non-road area of ​​the target area.

[0038] The communication bandwidth calculation unit 16F calculates the required bandwidth for communication equipment to satisfy the communication service quality within the target area, based on the sum of the communication volume within the road area and the communication volume within the non-road area.

[0039] (Regarding communication service quality classes) For example, in a 5G communication network, it can be assumed that four classes of communication service quality will be provided as a set, in addition to eMBB (enhanced mobile broadband), uRLLC (ultra-reliable and low-latency communications), mMTC (massive machine-type communications), and a best-effort communication service quality class.

[0040] In other words, every connection to a communication service is assigned to one of these four communication service quality classes. This ensures that, instead of assigning a communication service quality to each individual connection to a communication service, the communication service quality required for each of the four communication service quality classes mentioned above is reliably provided. The technology according to this embodiment is a technology that assumes the calculation of communication equipment capacity for each communication service quality class.

[0041] However, the above-described configuration of communication service quality classes is merely one example of a 5G communication network and is not limited to the above set. It may also apply to any set consisting of communication service quality classes defined by any communication service quality indicator (throughput, latency, packet loss rate, etc.). Furthermore, communication services may be provided individually, without being classified into communication service quality classes, each providing the communication service quality it requires.

[0042] The following describes a technology that enables the calculation of the communication bandwidth of a communication network that provides communication services related to autonomous vehicles with appropriate communication service quality. The communication bandwidth is calculated by a communication bandwidth calculation device 10.

[0043] (Regarding the method for calculating communication bandwidth by the communication bandwidth calculation device 10) In a communication network that provides communication services related to autonomous vehicles with appropriate communication service quality, for the reasons mentioned above, autonomous vehicles are considered as communication terminals with entirely new communication service demand characteristics.

[0044] As a first step, the communication bandwidth calculation device 10 predicts the amount of communication traffic generated as a communication service related to autonomous vehicles, and predicts the amount of communication traffic at a future design target time for each communication service quality class provided by the communication network.

[0045] Next, in the second step, the communication bandwidth calculation device 10 calculates the amount of communication equipment that can satisfy the communication service quality indicators (throughput, latency, packet loss rate, etc.) required for the communication service quality class of interest, based on the sum of the amount of communication from communication services related to autonomous vehicles calculated in the first step, which constitutes the load on each communication service quality class, and the amount of communication from conventional communication services for pedestrians, etc.

[0046] (Explanation of Step 1) Step 1 explains the prediction of the amount of data traffic generated as a communication service related to autonomous vehicles. This is calculated by multiplying the "prediction of the number of autonomous vehicles in the road traffic volume" calculated in Step 1-1 and the "prediction of the amount of data traffic for each communication service quality by one autonomous vehicle" calculated in Step 1-2.

[0047] Steps 1-1 and 1-2 will be explained in more detail.

[0048] <Step 1-1: Predicting the number of autonomous vehicles in road traffic> At a time when autonomous vehicles have not yet been put into operation or widespread use, we consider the following:

[0049] For major roads, there is existing database information on road traffic volume, such as the "National Road and Street Traffic Survey (Road Traffic Census)" conducted by the Ministry of Land, Infrastructure, Transport and Tourism. Since the spread of autonomous vehicles itself is not expected to affect the traffic volume (total number of vehicles) on each road, this database can be used to predict future time points. ＊ C(t) ＊ It can be predicted that the total number of automobiles = the number of autonomous vehicles + the number of non-autonomous vehicles. This prediction may also take into account conditions such as season, weather, and events.

[0050] Furthermore, regarding the adoption rate of autonomous vehicles, the actual value of the adoption rate α is calculated using the projected future number of autonomous vehicles shipped, and the projected value α(t) at any future point in time is calculated based on the trend forecast. ＊ It is also possible to calculate ( ).

[0051] The prediction of traffic volume (number of autonomous vehicles) on a specified road at a future point in time is calculated using (traffic volume C(t ＊ )) x (diffusion rate α(t ＊ ))

[0052] On roads other than major thoroughfares, where the number of vehicles is small and it would be inefficient to gradually increase the communication equipment for such communication, it is reasonable to assume that all vehicles have transitioned to autonomous vehicles. In other words, the penetration rate α(t ＊ ) = 1 is also acceptable.

[0053] <Steps 1-2: Predicting Communication Volume by Service Quality for a Single Self-Driving Vehicle> Self-driving connected vehicles (Self-driving vehicles) are equipped with an autonomous driving control system that enables autonomous driving, in addition to the vehicle control system of conventional non-autonomous vehicles. More precisely, the communication by a self-driving vehicle here refers to communication by the autonomous driving control system for autonomous driving.

[0054] Generally, the numerous new communications from autonomous vehicles can be classified as follows, based on the autonomous vehicle and its communication partners.

[0055] Communication Category (A): Communication between autonomous vehicles and traffic infrastructure. Communication Category (B): Communication between autonomous vehicles. Communication Category (C): Communication between autonomous vehicles and communication terminals held by pedestrians and cyclists. Communication Category (D): Communication between autonomous vehicles and base stations. Communication Category (E): Other communications related to autonomous vehicles. Below, we will explain road traffic involving autonomous vehicles and communications related to autonomous vehicles. Figure 1 is a diagram illustrating road traffic involving autonomous vehicles and communications related to autonomous vehicles. Figure 2 is a diagram illustrating communication categories (A) to (E) that occur in relation to autonomous vehicles. Figure 3 is a diagram illustrating communications in communication categories (A) to (E) that occur in relation to autonomous vehicles.

[0056] Using Figure 3, we will specifically explain each of the communications included in the above communication categories. As mentioned above, since technological development in standardization / proprietary specifications is ongoing, the following content includes assumptions and possibilities.

[0057] <Communication Category (A): Communication between Autonomous Vehicles and Transportation Infrastructure> As mentioned above, transportation infrastructure refers to information and communication systems for road traffic, such as the Intelligent Transport Systems (ITS) promoted by the Ministry of Land, Infrastructure, Transport and Tourism.

[0058] Traffic infrastructure specifically includes roads, traffic signals, external sensors such as cameras, ETC, VICS, communication spots, and car navigation systems, and supports traffic safety by providing road traffic information and congestion information to autonomous vehicles (or car drivers).

[0059] Information related to the movement of autonomous vehicles (including location, speed, direction of travel, and destination) is generated by each autonomous vehicle and uploaded to the traffic infrastructure. In addition, this information is collected from all vehicles passing in front of it by numerous cameras and external sensors on the road, which constitute the traffic infrastructure.

[0060] This information is collected at the road traffic control center, and through statistical processing, information useful for the safety of vehicle operation, such as road congestion information, is generated and provided to all vehicles from the traffic infrastructure.

[0061] Furthermore, aggregated traffic information transmitted from transportation infrastructure to vehicles is likely to often utilize broadcast communication on dedicated frequency bands. In this case, the amount of data transmitted does not depend on the number of autonomous vehicles. Therefore, there is no need to increase the amount of communication equipment even as the number of autonomous vehicles increases.

[0062] <Communication Category (B): Communication between Autonomous Vehicles> Communication between autonomous vehicles, similar to communication between autonomous vehicles and traffic infrastructure, involves the exchange of individual traffic information between vehicles, including the vehicle's road location, lane, speed, direction of travel, destination, and future autonomous vehicle control plans (lane changes, speed changes, direction changes), for the purpose of ensuring safe driving.

[0063] This makes it possible to use the traffic information of surrounding vehicles to identify approaching vehicles that could potentially collide with the vehicle, even in situations where the vehicle's cameras and sensors have blind spots or poor visibility, and to use this information for safer driving.

[0064] <Communication Category (C): Communication between autonomous vehicles and communication terminals held by pedestrians and cyclists> In order to ensure safe driving, it will become technically possible in the near future to detect and utilize not only autonomous vehicles, but also pedestrians, cyclists, and all other autonomous vehicles in advance.

[0065] Therefore, it is assumed that in communication between autonomous vehicles and communication terminals, including smartphones and mobile devices, carried by pedestrians, cyclists, and drivers of non-autonomous vehicles, individual traffic information (including information such as location, speed, direction of travel, and destination) will be exchanged between both parties. For example, even if a pedestrian does not explicitly input their current destination into their communication terminal, it will be possible for the terminal to predict and generate probabilistic individual traffic information for the pedestrian using the terminal's movement history (specifically, the movement history of the individual pedestrian currently carrying the terminal).

[0066] <Communication Category (D): Communication between Autonomous Vehicles and Base Stations> In order to ensure safe driving, diverse communication between autonomous vehicles and base stations that cover the roads they are traveling on may also play an important role.

[0067] For example, one could envision a communication service that utilizes the computing resources of MEC (Multi-access Edge Computing) within a base station for desired computational processing related to mobile communication terminals and notebook PCs carried by autonomous vehicles and their occupants.

[0068] <Communication Category (E): Other communications related to autonomous vehicles> The following describes communications related to autonomous vehicles that are not included above.

[0069] Autonomous vehicles are expected to require frequent updates to their autonomous driving control programs. Furthermore, data necessary for autonomous driving, such as 3D road map information of the surrounding area, must also be updated promptly and to the latest standards.

[0070] As mentioned above, the revised Road Traffic Act stipulates that, in order to ensure the safety of autonomous vehicle operation, the autonomous vehicle control room (remote monitoring and operation room) will be responsible for remote monitoring (real-time monitoring of operating status and rapid response in case of abnormalities), emergency response (remote control for safe stopping), operation management (operation plan and instructions according to traffic conditions), and data collection and analysis (to improve the safety and efficiency of operation). Specifically, this includes communication to transmit driving camera footage of the autonomous vehicle to the autonomous vehicle control room, and communication to send control signals for safe stopping via remote control in the event of an emergency with the autonomous vehicle.

[0071] Furthermore, it is necessary to anticipate that during travel in self-driving cars, both the passengers and, in the future, the drivers themselves will use video streaming services or game apps for entertainment.

[0072] As described above, communications related to autonomous vehicles occur for purposes such as updating the autonomous driving program, downloading 3D road map information, communication for controlling autonomous vehicles, and entertainment such as viewing video content for the driver and other occupants.

[0073] (Forecasting Communication Volume) Therefore, in order to ensure proper communication service quality, it is necessary to predict the amount of communication that will load the communication equipment and calculate the appropriate communication equipment bandwidth / capacity. However, it is necessary to calculate the amount of communication for each individual communication service related to autonomous vehicles, as classified into the above communication categories (A) to (E), by a single connection.

[0074] The information required for this purpose, such as communication throughput (average and variation), communication duration, and communication occurrence rate (call rate), can be calculated and evaluated as numerical values ​​or distributions, regardless of whether it is a standard specification or a proprietary specification. This can be clarified through measurements via prior verification experiments or theoretical estimations before an autonomous vehicle actually drives on public roads.

[0075] In detail, it is also possible to calculate and evaluate the above values ​​and distributions, conditioned on dependences on time of day, individual roads, and other environmental factors. Using these basic values ​​(i.e., communication throughput per single connection (average and variability), length of communication time, and communication occurrence rate (call rate) values ​​and distributions) as a basis, it is also possible to make future predictions regarding these basic values ​​using changes in demand and trends for each communication service.

[0076] (Classification by Communication Service Quality Class) Figure 4 shows a concrete example of assigning the many communications related to autonomous vehicles listed above to the communication service quality class provided by the communication network that each communication requires.

[0077] Figure 4 is a diagram (specific example) illustrating the correspondence between communication categories (A) to (E) and communication service quality classes.

[0078] The allocation shown in Figure 4 depends on the detailed design of the communication network, and therefore various implementations and realization forms are possible. In particular, in communication category (E), achieving the communication objective involves not only the functions of the communication network but also the functions of the distribution server and the applications on the communication terminal side, and there are various possibilities for functional division and quality / performance allocation.

[0079] In other words, depending on its implementation, the relaying communication network may choose a dedicated network to ensure / guarantee a certain level of communication service quality, or it may choose to use the internet, although the communication service quality will be best-effort. Therefore, in the drawings of this application, the terms "Internet" and "dedicated network" are used to clearly indicate that this choice is included.

[0080] In the communication network shown below as an example, assuming 5G, four communication service quality classes are provided: eMMB, uRLLC, mMTC, and best effort.

[0081] The eMMB class is assigned the aforementioned communication with the automated driving control program distribution server (e-1) and the communication with the 3D road map distribution server (e-2).

[0082] The uRLLC class is assigned to the aforementioned communication with the automated driving control room (e-3).

[0083] The mMTC class is assigned the following functions: communication with the aforementioned signal infrastructure (including traffic lights) (a-1), communication with autonomous vehicles (b-1), communication with mobile communication terminals (those carried by pedestrians, cyclists, and occupants of non-autonomous vehicles) (c-1), and communication with base stations (d-1).

[0084] The best-effort class is allocated communication with the video distribution server (e-4).

[0085] The prediction of communication volume for the above communication services using a single connection can be calculated by accumulating the data for one autonomous vehicle, which can then be used to calculate the communication equipment capacity described later. This process can be performed regardless of the level of automation of the autonomous vehicle's autonomous driving control function, from incomplete to complete, or its level of widespread adoption.

[0086] Using the prediction and calculation results described above, it is possible to predict the amount of data transmitted by one autonomous vehicle for each communication service quality in steps 1 and 2.

[0087] (Explanation of the second step) Next, an example of the implementation of the communication bandwidth calculation device 10 corresponding to the second step described above will be explained.

[0088] The communication bandwidth calculation device 10 of this embodiment can calculate the amount of communication equipment that can satisfy the communication service quality indicators (throughput, latency, packet loss rate, etc.) required for the communication service quality class of interest, based on the sum of the amount of communication from communication services related to autonomous vehicles calculated in the first step, which constitutes the load on each communication service quality class, and the amount of communication from communication services used by pedestrians, etc., which have existed in the past.

[0089] (Overall Configuration of the Communication System) Figure 5 is an overall block diagram showing the configuration of a communication system including the communication bandwidth calculation device 10 according to this embodiment. In this embodiment, a mobile communication network capable of providing data communication services is used as an example to describe the target communication network 20. However, the basic concept can also be partially applied to fixed communication networks (for example, between base stations and transportation infrastructure). Furthermore, in this embodiment, it is assumed that data communication is performed using the IP protocol, but data communication using the IP protocol is just one example, and the technology according to the present invention can be applied regardless of the type of protocol.

[0090] As shown in Figure 5, we assume a scenario in which four communication service quality classes (eMBB, uRLLC, mMTC, best effort) are provided as 5G communication services to user-owned communication terminals 411, 421, 431, and 441 via base stations 41, 42, 43, and 44 through the communication network 20.

[0091] In this embodiment of a communication network that provides communication services related to autonomous vehicles with appropriate communication service quality, the communication terminal will be described specifically under the following conditions.

[0092] Let the communication terminal 411 be referred to as the autonomous vehicle X0. The following will provide a detailed explanation of the communication related to the autonomous vehicle X0.

[0093] When the communication terminal 421 is associated with the traffic signal / traffic infrastructure Y1, the communication with the autonomous vehicle X0 corresponds to "Communication Category (A): Communication between autonomous vehicle and traffic infrastructure".

[0094] Similarly, when the communication terminal 431 is associated with the autonomous vehicle X1, the communication between it and the autonomous vehicle X0 corresponds to "Communication Category (B): Communication between autonomous vehicles".

[0095] When the communication terminal 441 is associated with the mobile communication terminal Z1, communication with the autonomous vehicle X0 corresponds to "Communication Category (C): Communication between an autonomous vehicle and a communication terminal held by a pedestrian or cyclist".

[0096] Furthermore, communication between the autonomous vehicle X0 and the base station corresponds to "Communication Category (D): Communication between autonomous vehicle and base station".

[0097] Finally, the updates to the autonomous driving control program of the autonomous vehicle X0, as well as communication for 3D road map information and video viewing, fall under "Communication Category (E): Other communications by autonomous vehicles."

[0098] The following provides a detailed explanation of each communication category (A) through (E).

[0099] In this communication system, when providing communication services to autonomous vehicles, only the communication traffic relayed by the base station is affected by the capacity of the communication equipment of the communication system. In other words, if the communication does not relay through the base station (for example, when autonomous vehicles communicate with each other without going through a base station), it does not need to be considered as part of the communication capacity of the communication system, but this depends on the implementation.

[0100] Therefore, the communication bandwidth will be calculated by considering only the communication traffic that passes through base stations from the above communication categories (A) to (E).

[0101] Here, it is assumed that autonomous vehicles X0, X1, and mobile communication terminal Z1 (communication terminals 411, 431, and 441, respectively) are functioning normally via wireless communication. Therefore, the following explanation remains unchanged regardless of how freely the communication terminals move or how the base stations they are connected to change from time to time. The same applies to traffic signals / traffic infrastructure Y1 (since it does not move, the base station it is connected to does not change).

[0102] Any user-owned data communication terminal using the communication network 20 can communicate with a desired server or any other data communication terminal via the internet and dedicated network 26, after passing through the bandwidth equipment 30-37, nodes 21, 22, access nodes 23, 24, and gateway router 25.

[0103] Note that nodes, access nodes, and bandwidth equipment are all examples of communication equipment. Specifically, nodes are mainly routers, and access nodes are mainly switches, etc. Bandwidth equipment refers to fixed transmission lines (communication lines) such as optical lines, or wireless transmission lines (communication lines).

[0104] The communication bandwidth calculation device 10 is composed of an information processing device using a computer, and performs calculation processing using the following information 61 to 70 as input.

[0105] ・Network equipment configuration information 61 ・Equipment unit traffic information 62 ・Communication terminal information 63 ・Road traffic volume information 64 ・Seasonal, weather, and event information 65 ・NW quality target value 66 ・Autonomous vehicle penetration rate forecast information 67 ・Communication settings information related to autonomous vehicles 68 ・Demand evaluation area configuration information 69 ・Map information 70 The following describes each piece of information.

[0106] The network equipment configuration information 61 is information about the configuration and interconnection relationships of network equipment that is maintained and updated within the operation system 51. The network equipment configuration information 61 includes all information about communication equipment in the communication network 20, such as information about nodes, access nodes, and line bandwidths accommodated in the communication network 20, and information about the connection relationships between nodes / access nodes and lines.

[0107] The equipment-unit traffic information 62 will now be explained. For example, the equipment-unit traffic information 62 related to the bandwidth equipment 30 is measurement data that measures the amount of traffic flowing out or coming in from the bandwidth equipment 30 at regular time intervals in relation to the connection with node 21. The equipment-unit traffic information 62 includes traffic information for all communication equipment constituting the communication network 20 and is stored within the operation system 51 for a certain period of time.

[0108] The communication terminal information 63 is information maintained and updated within the user / contract management system 52. It includes terminal ID information that identifies the communication terminal within the communication network 20, and information (including authentication information) for linking the communication terminal to the user who bears the charges and the contract details. Because the communication terminal can be identified, it is possible to determine what attributes and performance the communication terminal has. In other words, it is possible to determine whether it is a smartphone, an autonomous vehicle, or something else. This information can be used for the safe operation of autonomous vehicles.

[0109] I will now explain the road traffic volume information 64 (which can also be called the number of autonomous vehicles information 64). As mentioned above, for major roads, there is database information such as the "National Road and Street Traffic Survey (Road Traffic Census)" by the Ministry of Land, Infrastructure, Transport and Tourism. This allows us to find out the traffic volume for a specified time period.

[0110] This section explains the seasonal, weather, and event information (65). Regarding seasonal and weather data, the Japan Meteorological Agency accumulates and publishes historical data. For events, it is possible to create an event database by searching past web pages. Since road traffic volume and the traffic volume of various communication services are known to be affected by seasons, weather, and events, using the seasonal, weather, and event information (65) can be expected to improve prediction accuracy when forecasting future road traffic volume (number of autonomous vehicles) and traffic volume of various communication services.

[0111] Let me explain the NW quality target value 66. As mentioned above, in a communication network that provides communication services related to autonomous vehicles with appropriate communication service quality, autonomous vehicles perform communications that fall under communication categories (A) to (E). Each communication is based on various standard specifications (including 3GPP, ITU (ITU-R), IEEE, ITS, etc.), the automobile manufacturer's own specifications, and the government ordinances and guidance of the supervisory authority. Communication resources utilize the frequency bands, etc., designated based on the above. Therefore, under conditions where the amount / volume of communication traffic increases in proportion to the number of autonomous vehicles and the number of surrounding communication terminals that communicate with each other, the frequency band (or its communication capacity) as a communication resource may become strained, potentially leading to a deterioration in the quality of communication services.

[0112] The NW Quality Target Value 66 is defined as a list of target values ​​for quality indicators that define the communication service quality class required for each communication service quality class, which accommodates communication services that enable the safe driving of autonomous vehicles, the original purpose of the autonomous driving function, and other conventional communication services.

[0113] In actual operation, it is necessary to increase communication equipment capacity in a timely manner so that each quality indicator specified in the communication service quality class does not deteriorate below the value required by the NW quality target value 66.

[0114] Let me explain the autonomous vehicle penetration rate forecast information 67. As mentioned above, the autonomous vehicle penetration rate forecast information 67 is the predicted penetration rate of autonomous vehicles at a future point in time. This could be a penetration rate calculated from the projected number of autonomous vehicles to be shipped at a future point in time, as published / planned by autonomous vehicle manufacturers or organizations such as the Ministry of Land, Infrastructure, Transport and Tourism, or a small value such as 10% could be set as an initial provisional value for penetration.

[0115] Alternatively, as the adoption of autonomous vehicles increases, we could use predicted values ​​obtained by linear regression prediction using the least squares method based on time-series data of their adoption rate.

[0116] Examples of references describing analytical and predictive methods such as linear regression and multiple regression, which will be discussed later, include the following:

[0117] - "Konishi, Sadanori, Introduction to Multivariate Analysis, Iwanami Shoten, 2010" - "Sanford Weisberg, Linear Regression for Data Analysis [4th Edition], 2024, Kyoritsu Shuppan" The communication setting information 68 for autonomous vehicles will be explained. The communication setting information 68 for autonomous vehicles is setting information that specifies the amount of communication per autonomous vehicle that arises for new communication categories (A) to (E) in relation to autonomous vehicles, expressed as the amount of communication for each communication service quality class provided by the communication network.

[0118] By multiplying the communication volume per autonomous vehicle by the projected number of autonomous vehicles in the future, it is possible to calculate the communication load on specific wireless communication equipment resources (frequency resources) for each communication service quality class. Furthermore, the communication service quality for those wireless communication equipment resources can also be calculated through simulations, etc.

[0119] The basis for the numerical values ​​in this information may be measured from prior verification experiments, regardless of whether they are standardized or proprietary specifications, or they may be values ​​that have been theoretically evaluated.

[0120] The area configuration information 69 for demand evaluation will now be explained. In order to properly design the communication equipment capacity that will appropriately achieve the communication service quality of the communication network, it is necessary to correctly calculate (or predict, if in the future) the amount of communication corresponding to the demand and the amount of communication corresponding to the supply that will meet that demand.

[0121] In particular, in wireless communication services, there is no fixed relationship between the demand-side mobile communication terminals and the supply-side base stations. Therefore, defining the demand-side communication volume and the corresponding supply-side communication volume becomes a crucial point.

[0122] As one example of a definition, for a predetermined area, the amount of communication service traffic generated as demand within that area and the amount of communication service traffic that can be supplied within that area can be calculated separately, and the surplus or deficit can be evaluated by matching the former as the demand for that area and the latter as the supply for that area.

[0123] In this embodiment, the entire telecommunications service area that a telecommunications carrier's network should / is covering is referred to as "all of Japan." By using the aforementioned areas as elements and pre-setting a collection of numerous areas to cover all of Japan, and then achieving a supply that appropriately responds to the demand for communication volume within the domain of each individual area, it is possible to design a wireless communication network that covers telecommunications services throughout Japan.

[0124] In this embodiment, information used to clarify the information of individual areas (domains / boundaries, etc.) that can cover the entire country of Japan is called area configuration information.

[0125] Here, we have used the same area configuration to explain the matching of supply and demand, but it is sufficient for the set of individual areas as a whole to cover all of Japan, and it is possible to use different area configurations when calculating demand and when calculating supply. For this reason, in order to clearly indicate that it is an area used at the stage of evaluating the demand for communication traffic, we will specifically call it the "demand evaluation area," and the area configuration information will be called the "demand evaluation area configuration information."

[0126] On the supply side, it is possible to define a supply evaluation area that is different from the demand evaluation area, but in this embodiment, they will be described as being the same.

[0127] A simple example of area configuration information for demand assessment is a 1 / 10 subdivided mesh area (approximately 100 meters on each side) based on latitude and longitude (National Land Numerical Information) provided by the Geospatial Information Authority of Japan. Alternatively, a tertiary mesh area (approximately 1 kilometer on each side) may also be used.

[0128] By using the demand evaluation area configuration information 69, the area (on the map) of any demand evaluation area becomes clear. By using this in combination with the map information 70, the road area and the non-road area can be clearly separated within that demand evaluation area.

[0129] As mentioned above, in the road domain, as autonomous vehicles become more widespread in the future, communication related to autonomous vehicles will be generated and increase as a new communication traffic demand. The volume of this communication will be predicted based on the steps 1-1 and 1-2 described above.

[0130] Non-road areas refer to areas such as sidewalks or above-ground structures like buildings and apartment complexes. Since the communication traffic demand in these areas is the same as that of conventional mobile communication services, the volume of communication can be predicted with general accuracy based on the trends of conventional communication volumes.

[0131] As mentioned above, the map information 70 is used in combination with the demand evaluation area configuration information 69 to clearly distinguish between road areas and non-road areas on each individual demand evaluation area.

[0132] (Communication Bandwidth Calculation Device 10) The communication bandwidth calculation device 10 takes the above-mentioned various information and numerical values ​​as input and, through the processing described later, calculates the communication bandwidth of the communication network that satisfies the NW quality target value 66 for communication categories (A) to (E) in a communication network that provides the above-mentioned communication services related to autonomous vehicles with appropriate communication service quality.

[0133] (Internal configuration of the communication bandwidth calculation device 10) Next, the internal configuration of the communication bandwidth calculation device 10 according to this embodiment will be described in detail.

[0134] The configuration of the communication bandwidth calculation device 10 shown in Figure 5 is an example of a hardware configuration when implemented on a computer. This computer may be a physical machine or a virtual machine. When the communication bandwidth calculation device 10 is implemented on a virtual machine, the hardware configuration shown in Figure 5 becomes a virtual hardware configuration.

[0135] As shown in Figure 5, the communication bandwidth calculation device 10 has as its main components a communication interface unit 11 (hereinafter referred to as the communication I / F unit 11), an operation input unit 12, a screen display unit 13, an information database unit 14 (hereinafter referred to as the information DB unit 14), a storage unit 15, and an arithmetic processing unit 16. These components are connected via an internal communication bus and can send and receive information from each other.

[0136] The communication interface unit 11 consists of a dedicated data communication circuit and has the function of communicating with the operation system 51, the user / contract management system 52, and other systems.

[0137] The operation input unit 12 consists of an operation input device such as a keyboard or mouse, and has the function of detecting input operations from the operator and outputting operation information to the calculation processing unit 16.

[0138] The screen display unit 13 is a screen display device such as a display, and has the function of displaying various information such as operation menus and calculation results on the screen in response to instructions from the calculation processing unit 16.

[0139] The information database unit 14 consists of storage devices such as a hard disk and memory, and has the function of sending, receiving, and storing various data used in each process of the arithmetic processing unit 16. The information database unit 14 stores network equipment configuration information 61, equipment unit traffic information 62, communication terminal information 63, etc., and updates them in a timely manner.

[0140] The storage unit 15 consists of a storage device such as a hard disk or memory, and has the function of storing various programs and data used in each process of the arithmetic processing unit 16.

[0141] The arithmetic processing unit 16 has a microprocessor such as a CPU (Central Processing Unit) and its peripheral circuits. It reads programs and data from the storage unit 15 in response to operations from the information DB 14 or the operation input unit 12, and executes the program to obtain network equipment configuration information 61, equipment unit traffic information 62, communication terminal information 63, etc., necessary for arithmetic processing from the information DB unit 14, and stores the results of the arithmetic processing in the information DB unit 14.

[0142] The program that implements the processing in the communication bandwidth calculation device 10 is provided on a recording medium such as an SSD (solid-state drive), optical disc, or flash memory. The program read from the recording medium is stored in the storage unit 15, for example, and then read and executed by the arithmetic processing unit 16. Alternatively, the program may be downloaded from a server or the like via a communication network.

[0143] (Configuration of the arithmetic processing unit 16) Next, with reference to Figure 6, the internal functional configuration of the arithmetic processing unit 16 according to this embodiment will be described in detail.

[0144] Figure 6 is a block diagram showing the various processing units of the arithmetic processing unit 16. Each processing unit is a functional processing unit that is realized when a program is executed by the arithmetic processing unit 16. For the sake of convenience, in the drawings referred to in the following explanation, information (for example, network equipment configuration information 61) may be indicated only by a reference numeral (for example, 61).

[0145] As shown in Figure 6, the calculation processing unit 16 includes, as its main processing units, an information acquisition unit 16A, a road / non-road analysis unit 16B for demand design within the area, an automated driving vehicle number prediction unit 16C within the road area, a communication volume prediction unit 16D within the road area, a communication volume prediction unit 16E within the non-road area, a communication bandwidth calculation unit 16F, and an operation system setting unit 16G.

[0146] The information acquisition unit 16A acquires network equipment configuration information 61, equipment unit traffic information 62, communication terminal information 63, road traffic volume information 64, and seasonal / weather / event information 65 from an appropriate system or database that holds and stores this information. It also sets network quality target values ​​66 and autonomous vehicle penetration rate prediction information 67 and inputs them into the information acquisition unit 16A.

[0147] The road / non-road analysis unit 16B for demand evaluation within the area will now be explained. The road / non-road analysis unit 16B for demand evaluation within the area, in combination with map information 70, clarifies the road area and non-road area for each of the demand evaluation areas, and outputs road area information 81 and non-road area information 82.

[0148] The autonomous vehicle count prediction unit 16C within the road area will now be described. The autonomous vehicle count prediction unit 16C predicts and evaluates autonomous vehicle count prediction information 83, which is a prediction of the number of autonomous vehicles that will travel in each demand evaluation area at a future point in time, based on road traffic volume information 64 for the road of interest and autonomous vehicle penetration rate prediction information 67. Season, weather, and event information 65 may be used to further improve the accuracy of the autonomous vehicle count prediction information 83.

[0149] The road area communication volume prediction unit 16D will now be explained. Road area communication volume is defined as the amount of communication (communication traffic) newly generated in relation to autonomous vehicles within the road area included in the target demand evaluation area, categorized by communication service quality class.

[0150] The road area traffic volume prediction unit 16D predicts and evaluates future road area traffic volume prediction information 84 for the road area of ​​the target demand evaluation area, based on road area information 81 and the aforementioned communication setting information 68 related to the autonomous vehicle. Seasonal, weather, and event information 65 may be used to further improve the accuracy of the road area traffic volume prediction information 84.

[0151] The non-road area communication volume prediction unit 16E will now be explained. Non-road area communication volume does not include the road area of ​​the target demand evaluation area, and therefore does not include communication volume newly generated in relation to autonomous vehicles. It is defined as the amount of communication (communication traffic volume) by communication service quality class from communication terminals held by conventional pedestrians and occupants of non-autonomous vehicles in the non-road area.

[0152] The non-road area traffic volume prediction unit 16E predicts and evaluates future non-road area traffic volume prediction information 85 for the non-road area of ​​the target demand evaluation area, using network equipment configuration information 61 and equipment unit traffic information 62. Seasonal, weather, and event information 65 may be used to further improve the accuracy of the non-road area traffic volume prediction information 85.

[0153] Therefore, the total amount of communication traffic that will occur at a future point in time in each demand assessment area will be the sum of the communication traffic within the road area (84) and the communication traffic within the non-road area (85).

[0154] The communication bandwidth calculation unit 16F calculates the communication equipment capacity / bandwidth required to achieve a communication service quality that satisfies the NW quality target value 66, under the condition that the sum of the traffic volume within the road area and the traffic volume within the non-road area in the target demand evaluation area constitutes the traffic load. This calculated bandwidth is called the required bandwidth information 86. In this explanation, bandwidth has been used as a simple representative, but the specifications of communication equipment or communication resources vary. For example, regarding computing power, it is possible to similarly calculate the computing power required for supply in relation to the computing power in demand and the NW quality target value 66, which is the target quality.

[0155] The operation system setting unit 16D sets the necessary bandwidth information 86 in the operation system 51, which is required to achieve a communication service quality higher than the network quality target value 66 for all communication traffic that will occur at a future point in time that is to be predicted in the target demand evaluation area, as calculated by the communication bandwidth calculation unit 16F.

[0156] The functions of the operation system 51 enable equipment operation such that the amount of communication equipment in the demand evaluation area at a future point in time is greater than the required bandwidth information 86. The required bandwidth information 86 can also be reflected in plans for expanding communication equipment.

[0157] The operation of each processing unit will be explained in more detail below, referring to the flowchart.

[0158] (Information acquisition unit 16A) The operation of the information acquisition unit 16A will be explained with reference to the flowchart shown in Figure 7.

[0159] <S110 (Step 110)> In S110, the information acquisition unit 16A acquires network equipment configuration information 61 and equipment unit traffic information 62 from the operation system 51, which are necessary for the calculation processing described later. The information acquisition unit 16A also acquires communication terminal information 63 from the user / contract management system 52, road traffic volume information 64 from the road traffic volume database 53, and season / weather / event information 65 from the season / weather / event database 54. Furthermore, it inputs network quality target values ​​66, autonomous vehicle penetration rate prediction information 67, communication setting information 68 related to autonomous vehicles, demand evaluation area configuration information 69, and map information 70 from the information I / F acquisition unit 11 or the operation input unit 12, etc.

[0160] <S120> In S120, the information acquisition unit 16A stores network equipment configuration information 61, equipment unit traffic information 62, communication terminal information 63, road traffic volume information 64, seasonal / weather / event information 65, NW quality target value 66, autonomous vehicle penetration rate prediction information 67, communication setting information related to autonomous vehicles 68, demand evaluation area configuration information 69, and map information 70 in the information DB unit 14.

[0161] (Road / Non-Road Analysis Unit 16B for Demand Assessment) The operation of the Road / Non-Road Analysis Unit 16B for Demand Assessment will be explained with reference to the flowchart shown in Figure 7.

[0162] <S210> In S210, the road / non-road analysis unit 16B for demand evaluation area acquires demand evaluation area configuration information 69 and map information 70 from the information DB unit 14.

[0163] <S220> In S220, the demand evaluation area road / non-road analysis unit 16B generates road area information 81 and non-road area information 82 for each demand evaluation area to be analyzed, from the demand evaluation area configuration information 69 and map information 70, which clearly distinguish between road areas and non-road areas within the area.

[0164] <S230> In S230, the demand evaluation area road / non-road analysis unit 16B stores the road area information 81 and the non-road area information 82 in the information DB unit 14.

[0165] (Number of Autonomous Vehicles in Road Area Prediction Unit 16C) As described above, the Number of Autonomous Vehicles in Road Area Prediction Unit 16C predicts the number of autonomous vehicles passing at a future time point to be predicted, i.e., the autonomous vehicle number prediction information 83, from the road traffic volume information 64 and the autonomous vehicle penetration rate prediction information 67, in addition to the road area information 81 for the road. For the purpose of further improving the accuracy of the autonomous vehicle number prediction information 83, seasonal / weather / event information 65 may be used.

[0166] Refer to the flowchart shown in FIG. 8 to explain the operation of the Number of Autonomous Vehicles in Road Area Prediction Unit 16C.

[0167] <S310> In S310, the Number of Autonomous Vehicles in Road Area Prediction Unit 16C acquires the road area information 81, the road traffic volume information 64, the autonomous vehicle penetration rate prediction information 67 from the information DB unit 14, and, if it is desired to improve the accuracy more in a short-term prediction, the seasonal / weather / event information 65.

[0168] <S320> In S320, first, the Number of Autonomous Vehicles in Road Area Prediction Unit 16C specifies the road area in the target area for demand evaluation from the road area information 81, specifies the roads occupying the road area, and extracts the past road traffic volume for the roads in the road area from the road traffic volume information 64. The predicted value of the number of motor vehicles (including autonomous and non-autonomous vehicles) at a future time point may be obtained by linear regression prediction of the past road traffic volume. Let the predicted value of the number of autonomous vehicles in the road area at a future time point t be C(t ＊ ). ＊

[0169] At this time, in order to consider the short-term upward fluctuation of the road traffic volume, the seasonal / weather / event information 65 is added to the road traffic volume information 64 as input data, and the factors of season, weather, and event are added, and the predicted value C(t ＊ of the motor vehicle traffic volume at a future time point t is calculated using a multiple regression prediction model. Next, the Number of Autonomous Vehicles in Road Area Prediction Unit 16C calculates the autonomous vehicle number prediction information 83 from the road traffic volume information 64 and the autonomous vehicle penetration rate prediction information 67 as follows. ＊

[0170] The autonomous vehicle penetration rate forecast information 67, as mentioned above, is a forecast value of the penetration rate derived from the projected number of autonomous vehicles to be shipped in the future, as published / planned by autonomous vehicle manufacturers and organizations such as the Ministry of Land, Infrastructure, Transport and Tourism. A small value such as 10% may be set as an initial provisional value for penetration. As the penetration of autonomous vehicles progresses, the values ​​obtained by linear regression prediction using the least squares method are used.

[0171] Here, at a future time t ＊ The predicted penetration rate of self-driving cars is α(t ＊ )

[0172] At this point in time, the future time t of the autonomous vehicle ＊ The predicted value of the number of autonomous vehicles on the road in question, known as the predicted number of autonomous vehicles, is used to obtain the predicted number of autonomous vehicles information 83 from AC(t ＊ If we assume that, then it will be as follows:

[0173] <S330> In S330, the autonomous vehicle count prediction unit 16C in the road area stores the autonomous vehicle count prediction information 83 in the information DB unit 14.

[0174] (Road Area Communication Volume Prediction Unit 16D) As described above, the Road Area Communication Volume Prediction Unit 16D predicts and evaluates the communication volume of each of the communication categories (A) to (E) that will newly occur in relation to the autonomous vehicle within the road area. The predicted value of the road area communication volume at a future point in time to be predicted is defined as the Road Area Communication Volume Prediction Information 84.

[0175] As described above, the road area traffic volume prediction unit 16D predicts and evaluates road area traffic volume prediction information 84 at a future point in time to be predicted, based on the predicted number of autonomous vehicles in the road area information 83 and the communication setting information 68 related to autonomous vehicles. Seasonal, weather, and event information 65 may be used to further improve the accuracy of the road area traffic volume prediction information 84.

[0176] The operation of the road area communication volume prediction unit 16D will be explained with reference to the flowchart shown in Figure 8.

[0177] <S410> In S410, the road area communication volume prediction unit 16D obtains the number of autonomous vehicles prediction information 83 and the communication setting information 68 related to autonomous vehicles from the information DB unit 14, and if it is desired to improve accuracy for short-term predictions, it also obtains seasonal, weather, and event information 65.

[0178] <S420> In S420, the road area communication volume prediction unit 16D uses the autonomous vehicle number prediction information 83 to determine the target road and the future time point t to be predicted. ＊ AC(t) is the predicted number of autonomous vehicles. ＊ Extract the following:

[0179] Next, using the communication configuration information 68 related to the autonomous vehicle, we evaluate the amount of communication per autonomous vehicle generated for each of the communication categories (A) to (E), which are classifications of communications related to autonomous vehicles, for each frequency band corresponding to the communication bandwidth resource.

[0180] Communication Category (A): Communication between autonomous vehicles and traffic infrastructure. Communication Category (B): Communication between autonomous vehicles. Communication Category (C): Communication between autonomous vehicles and communication terminals held by pedestrians and cyclists. Communication Category (D): Communication between autonomous vehicles and base stations. Communication Category (E): Other communications related to autonomous vehicles. Specifically, this refers to future time point t generated by communication category (A) per autonomous vehicle to communication resource r. ＊ The predicted value of the communication volume is W ｒ，（Ａ） (t ＊ When expressed as shown above, the sum of the predicted communication volumes per autonomous vehicle for communication resource r, based on communication categories (A) to (E), is as follows:

[0181] Here, W ｒ，（Ａ） (t ＊ ), W ｒ，（Ｂ） (t ＊ ), W ｒ，（Ｃ） (t ＊ ), W ｒ，（Ｄ） (t ＊ ), W ｒ，（Ｅ） (t ＊Each value can be the optimal value determined through prior verification experiments, etc., in accordance with standardization and proprietary specifications.

[0182] Therefore, within the road area in question, and at the future time t that we intend to predict... ＊ The estimated amount of communication traffic to the communication resource r generated by all autonomous vehicles in the system is as follows, assuming it is proportional to the number of autonomous vehicles:

[0183] However, when multicast or broadcast communication is performed on the frequency of the communication resource in question, it is not proportional to the number of autonomous vehicles, so the following applies:

[0184] The above is referred to as road area traffic volume prediction information 84.

[0185] To account for short-term upward fluctuations in road traffic volume, seasonal, weather, and event information 65 may be added to the input data, and the factors of season, weather, and events may be added, and the road area communication volume prediction information 84 may be evaluated using a multiple regression prediction model.

[0186] <S430> In S430, the road area communication volume prediction unit 16D stores the road area communication volume prediction information 84 in the information DB unit 14.

[0187] (Non-road area communication volume prediction unit 16E) As described above, the non-road area communication volume prediction unit 16E predicts and evaluates non-road area communication volume prediction information 85, which is a prediction of the amount of communication by communication terminals held by conventional pedestrians and occupants of non-autonomous vehicles (not the amount of communication newly generated in relation to autonomous vehicles) at a future point in time to be predicted, using non-road area information 82 for non-road areas, as well as network equipment configuration information 61 and equipment unit traffic information 62. Season, weather, and event information 65 may be used to further improve the accuracy of the non-road area communication volume prediction information 85.

[0188] The operation of the non-road area communication volume prediction unit 16E will be explained with reference to the flowchart shown in Figure 9.

[0189] <S510> In S510, the non-road area communication volume prediction unit 16E acquires non-road area information 82, network equipment configuration information 61, and equipment unit traffic information 62 from the information DB unit 14, and if it is desired to improve accuracy for short-term predictions, it acquires seasonal, weather, and event information 65.

[0190] <S520> First, non-road areas in the target demand evaluation area are identified from the non-road area information 82, and the communication equipment that covered the said non-road area is identified using network equipment configuration information 61 which includes the past history of the communication equipment. Then, past time-series data of the traffic volume of conventional communication services, excluding communications related to autonomous vehicles, can be extracted from the equipment unit traffic information 62 of the communication equipment that covered the said non-road area.

[0191] The future point in time we want to predict t ＊ To obtain a predicted value for the traffic volume within the non-road area, past time-series data of the traffic volume can be used for linear regression prediction using the least squares method. This predicted value is referred to as the non-road area traffic volume prediction information 85.

[0192] <S530> In S530, the non-road area communication volume prediction unit 16E stores the non-road area communication volume prediction information 85 in the information DB unit 14.

[0193] (Communication Bandwidth Calculation Unit 16F) As described above, the communication bandwidth calculation unit 16F calculates the bandwidth / capacity of the communication equipment for the demand evaluation area required to achieve a communication service quality that satisfies the NW quality target value 66, in a situation where the sum of the traffic volume within the road area and the traffic volume within the non-road area in the target demand evaluation area becomes the communication traffic load. This calculated bandwidth is called the required bandwidth information 86.

[0194] The operation of the communication bandwidth calculation unit 16F will be explained with reference to the flowchart shown in Figure 10. The following operation is explained for a single communication device / communication resource, but generally, a communication network has many communication devices, so after evaluating each individual communication device / communication resource, the overall optimization is performed so that there is no surplus or shortage for any of the communication devices.

[0195] <S610> In S610, the communication bandwidth calculation unit 16F acquires from the information DB unit 14 network equipment configuration information 61, NW quality target value 66, as well as road area information 81, non-road area information 82, road area communication volume prediction information 84, and non-road area communication volume prediction information 85.

[0196] <S620> In S620, the communication bandwidth calculation unit 16F can identify base stations or communication equipment at the frequency level that cover the road area and non-road area of ​​the target demand evaluation area, using road area information 81, non-road area information 82, and network equipment configuration information 61.

[0197] Furthermore, since detailed setting conditions of the identified communication equipment can be obtained from the network equipment configuration information 61, the coverage area of ​​the base station / frequency as communication equipment can be estimated. Therefore, it is possible to estimate to what extent the communication equipment (base station / frequency) covers the road area and the non-road area, and to what extent it can transfer the communication volume generated in the road area and the non-road area, respectively. In other words, the communication volume generated in the demand evaluation area can be calculated as the sum of the road area communication volume prediction information 84 generated in the road area and the non-road area communication volume prediction information 85 generated in the non-road area.

[0198] Generally, the quality Q of a communication service quality class can be evaluated based on two conditions: communication bandwidth (capacity) W and the amount of data traffic T. From this relationship, the communication bandwidth W is used as a variable, and the data traffic T and the target communication service quality class Q can be evaluated. ｔａｒｇｅｔ Given this condition, the minimum communication equipment bandwidth / capacity W that satisfies it can be evaluated.

[0199] The following describes how to evaluate the quality of communication service quality classes using computer-based network simulation, based on technologies such as those described in the reference "ns-3 a discrete-event network simulator for internet systems, https: / / www.nsnam.org".

[0200] The future point in time at which you intend to calculate the communication bandwidth (capacity) of the communication equipment is t ＊ Let's assume that.

[0201] Communication bandwidth W(t ＊ ) (variable) and communication amount T(t ＊ Based on the two conditions of Q(t) and t, the results of a computer-based network simulation showed that the quality of communication services Q(t) ＊ ) is obtained. This correspondence can be defined as a function G as follows. Here, = is defined as the communication network quality of the (left side) and (right side) being equivalent.

[0202] Here, the NW quality target value is set to Q ｔａｒｇｅｔ Assuming that the indicator of communication service quality is expressed using the symbol < when the left side is relatively inferior to the right side (defined as the indicator of communication service quality being inferior to the left side of <), the variable W, which represents the communication bandwidth, is increased by the smallest unit of communication bandwidth expansion until the following equation is satisfied, thereby increasing the network quality target value of 66, Q ｔａｒｇｅｔ The variable W can be increased until the condition is met. W(t ＊ The following relationship is satisfied.

[0203] Furthermore, from the perspective of preventing overinvestment in communication equipment, it is desirable that the above relationship be satisfied and minimized at a future point in time, ＊ The optimal communication bandwidth W is the required bandwidth information 86 in this case. ｏｐｔ (t ＊ ) can be expressed as follows:

[0204] <S630> In S630, the communication bandwidth calculation unit 16F stores the required bandwidth information 86 in the information DB unit 14.

[0205] <Variations> In the above example, the amount of communication T generated in the target demand evaluation area is calculated as the sum of road area communication volume forecast information 84 generated in the road area and non-road area communication volume forecast information 85 generated in the non-road area, but is not limited to this.

[0206] The traffic volume T generated in the target demand evaluation area may be limited to only the road area traffic volume forecast information 84 generated in the road area. In this case, the required bandwidth information 86 for the traffic volume generated in the road area can be calculated by the above calculation.

[0207] (Operation System Setting Unit 16G) The operation system setting unit 16G sets the required bandwidth information 86 calculated by the communication bandwidth calculation unit 16F to the operation system 51. As described above, the required bandwidth information 86 is the bandwidth of the communication equipment necessary for the communication service quality of each communication service quality class to achieve a quality higher than the network quality target value 66 for the amount of communication that will occur at the future time set above.

[0208] This makes it possible to operate the communication equipment in such a way that the amount of equipment capacity set for the future point in time above is greater than the required bandwidth information 86. The required bandwidth information 86 can also be reflected in plans to expand the communication equipment.

[0209] The operation of the operation system setting unit 16G will be explained with reference to the flowchart shown in Figure 10.

[0210] <S710> In S710, the operation system setting unit 16G obtains network equipment configuration information 61 and required bandwidth information 86 from the information DB unit 14.

[0211] <S720> In S720, the operation system setting unit 16G refers to the network equipment configuration information 61 and generates communication equipment reservation information 91 for the communication equipment of interest, and inputs / sets it into the operation system 51. As a result, the bandwidth / capacity of the communication equipment in question is reserved / secured at a future point in time.

[0212] The communication equipment reservation information 91 is information registered and instructed to the operation system 51 in order to secure the required bandwidth information 86. The required bandwidth information 86 is the equipment capacity necessary to meet the network quality target value at a predicted future point in time for the communication equipment of interest.

[0213] <S730> In S730, the operation system setting unit 16G stores the communication equipment reservation information 91 in the information DB unit 14.

[0214] (Supplement) For the sake of explanation, the communication bandwidth calculation device 10 according to this embodiment is described using a functional block diagram, but the communication bandwidth calculation device 10 according to this embodiment may be implemented in hardware, software, or a combination thereof. Also, each functional part may be used in combination as necessary. Furthermore, the method according to this embodiment may be carried out in an order different from the order shown in the embodiment.

[0215] (Hardware Configuration Example) A more specific example of hardware configuration is described below. Any of the devices described in this embodiment (communication bandwidth calculation device 10, communication terminals 411, 421, 431, 441, etc.) can be realized, for example, by having a computer run a program. This computer may be a physical computer or a virtual machine on the cloud.

[0216] In other words, the device can be realized by using hardware resources such as the CPU and memory built into a computer to execute a program corresponding to the processing performed by the device. The program can be recorded on a computer-readable recording medium (such as portable memory), saved, and distributed. It can also be provided via a network, such as the Internet or email.

[0217] Figure 11 shows an example of the hardware configuration of the computer described above. The computer in Figure 11 has a drive device 1000, an auxiliary storage device 1002, a memory device 1003, a CPU 1004, an interface device 1005, a display device 1006, an input device 1007, an output device 1008, etc., all of which are interconnected by bus B. The computer may also be equipped with a GPU.

[0218] The program that enables processing on the computer is provided on a recording medium 1001, such as a CD-ROM or memory card. When the recording medium 1001 containing the program is set in the drive device 1000, the program is installed from the recording medium 1001 to the auxiliary storage device 1002 via the drive device 1000. However, the program does not necessarily have to be installed from the recording medium 1001; it may also be downloaded from another computer via a network. The auxiliary storage device 1002 stores the installed program as well as necessary files and data.

[0219] The memory device 1003 reads and stores a program from the auxiliary storage device 1002 when a program startup command is received. The CPU 1004 implements the functions related to the device 10 according to the program stored in the memory device 1003. The interface device 1005 is used as an interface for connecting to a network, etc. The display device 1006 displays a GUI (Graphical User Interface) etc. based on the program. The input device 1007 consists of a keyboard and mouse, buttons, or a touch panel etc., and is used to input various operation commands. The output device 1008 outputs the calculation results.

[0220] (Summary of Embodiments) As described above, the technology described in this embodiment provides a communication bandwidth calculation device 10 for calculating the communication bandwidth of a communication network that provides communication services related to autonomous vehicles with appropriate communication service quality.

[0221] The communication bandwidth calculation device 10 includes a road area communication volume prediction unit 16D, a non-road area communication volume prediction unit 16E, and a communication bandwidth calculation unit 16F.

[0222] The road area communication volume prediction unit 16D predicts the number of autonomous vehicles at a future point in time within the road area for the target area on which communication equipment is designed, estimates the amount of communication per vehicle related to autonomous vehicles, and predicts the amount of communication within the road area on which autonomous vehicles will travel.

[0223] The non-road area communication volume prediction unit 16E predicts the volume of non-road area communication, which is conventional communication by pedestrians, excluding communication with autonomous vehicles, within the non-road area of ​​the target area.

[0224] The communication bandwidth calculation unit 16F calculates the communication equipment to satisfy the communication service quality within the target area, based on the sum of the communication volume within the road area and the communication volume within the non-road area.

[0225] (Effects of the technology according to the embodiment) As described above, the communication bandwidth calculation device 10 in this embodiment makes it possible to calculate the communication bandwidth necessary to reliably provide the appropriate communication service quality class for each communication category (A) to (E) related to autonomous vehicles. As a result, it becomes possible to provide the appropriate communication service quality for each communication service related to autonomous vehicles.

[0226] The following additional information is disclosed regarding the embodiments described above.

[0227] <Note> (Note 1) A communication bandwidth calculation device for calculating the communication bandwidth of a communication network that provides communication services related to autonomous vehicles with appropriate communication service quality, comprising: a road area communication volume prediction unit that predicts the number of autonomous vehicles at a future point in time within the road area for a target area on which communication equipment is designed, estimates the amount of communication per vehicle related to autonomous vehicles, and predicts the amount of communication within the road area on which autonomous vehicles travel; and a communication bandwidth calculation unit that calculates communication equipment in the target area to satisfy the communication service quality with respect to the amount of communication within the road area. (Appendix 2) A communication bandwidth calculation device for calculating the communication bandwidth of a communication network that provides communication services related to autonomous vehicles with appropriate communication service quality, comprising: a road area communication volume prediction unit that predicts the number of autonomous vehicles at a future point in time within the road area for a target area on which communication equipment is designed, estimates the amount of communication per vehicle related to autonomous vehicles, and predicts the amount of communication within the road area on which autonomous vehicles travel; a non-road area communication volume prediction unit that predicts the amount of communication within the non-road area of ​​the target area, which is communication by pedestrians that does not include communication with autonomous vehicles; and a communication bandwidth calculation unit that calculates communication equipment in the target area so as to satisfy the communication service quality with respect to the sum of the road area communication volume and the non-road area communication volume.(Note 3) A communication bandwidth calculation method to be performed by a communication bandwidth calculation device for calculating the communication bandwidth of a communication network that provides communication services related to autonomous vehicles with appropriate communication service quality, comprising: a road area communication volume prediction step for a target area on which communication equipment is designed, in which the number of autonomous vehicles at a future point in time is predicted within the road area, the amount of communication per vehicle related to autonomous vehicles is estimated, and the amount of communication within the road area on which autonomous vehicles travel is predicted; a non-road area communication volume prediction step for a non-road area on which communication is by pedestrians, not including communication with autonomous vehicles, is predicted within the non-road area of ​​the target area; and a communication bandwidth calculation step for calculating communication equipment in the target area so as to satisfy the communication service quality with respect to the sum of the road area communication volume and the non-road area communication volume. (Note 4) A non-temporary storage medium storing a program for causing a computer to function as a communication bandwidth calculation device as described in Note 1 or 2.

[0228] Although this embodiment has been described above, the present invention is not limited to this specific embodiment, and various modifications and changes are possible within the scope of the gist of the invention as described in the claims.

[0229] 10 Communication bandwidth calculation device 11 Communication I / F unit 12 Operation input unit 13 Screen display unit 14 Information DB unit 15 Storage unit 16 Calculation processing unit 16A Information acquisition unit 16B Road / non-road analysis unit for demand evaluation area 16C Automated vehicle number prediction unit within road area 16D Communication volume prediction unit within road area 16E Communication volume prediction unit within non-road area 16F Communication bandwidth calculation unit 16G Operation system setting unit 20 Communication network 21, 22 Nodes 23, 24 Access node 25 Gateway router 26 Internet and dedicated network 31, 32, 33, 34, 35, 36, 37 Bandwidth equipment 41, 42, 43, 44 Base station 411 Automated vehicle X0 421 Traffic light / traffic infrastructure Y1 431 Automated vehicle X1 441 Mobile communication terminal Z1 51 Operation system 52 User / contract management system 53 Road traffic volume database 54 Season / weather / event database 61 Network equipment configuration information 62 Equipment unit traffic information 63 Communication terminal information 64 Road traffic volume information 65 Season / weather / event information 66 NW quality target value 67 Autonomous vehicle penetration rate forecast 68 Communication setting information related to autonomous vehicles 69 Demand evaluation area configuration information 70 Map information 81 Road area information 82 Non-road area information 83 Autonomous vehicle number forecast information 84 Road area communication volume forecast information 85 Non-road area communication volume forecast information 86 Required bandwidth information 91 Communication equipment reservation information 1000 Drive device 1001 Recording medium 1002 Auxiliary storage device 1003 Memory device 1004 CPU 1005 Interface device 1006 Display device 1007 Input device 1008 Output device

Claims

1. A communication bandwidth calculation device for calculating the communication bandwidth of a communication network that provides communication services related to autonomous vehicles with appropriate communication service quality, comprising: a road area communication volume prediction unit that predicts the number of autonomous vehicles at a future point in time within the road area for a target area on which communication equipment is designed, estimates the amount of communication per vehicle related to autonomous vehicles, and predicts the amount of communication within the road area on which autonomous vehicles travel; and a communication bandwidth calculation unit that calculates communication equipment in the target area to satisfy the communication service quality with respect to the amount of communication within the road area.

2. A communication bandwidth calculation device for calculating the communication bandwidth of a communication network that provides communication services related to autonomous vehicles with appropriate communication service quality, comprising: a road area communication volume prediction unit that predicts the number of autonomous vehicles at a future point in time within the road area for a target area on which communication equipment is designed, estimates the amount of communication per vehicle related to autonomous vehicles, and predicts the amount of communication within the road area on which autonomous vehicles travel; a non-road area communication volume prediction unit that predicts the amount of communication within the non-road area of ​​the target area, which is communication by pedestrians that does not include communication with autonomous vehicles; and a communication bandwidth calculation unit that calculates communication equipment in the target area so as to satisfy the communication service quality with respect to the sum of the road area communication volume and the non-road area communication volume.

3. A communication bandwidth calculation method performed by a communication bandwidth calculation device for calculating the communication bandwidth of a communication network that provides communication services related to autonomous vehicles with appropriate communication service quality, comprising: a road area communication volume prediction step for a target area on which communication equipment is designed, in which the number of autonomous vehicles at a future point in time is predicted within the road area, the amount of communication per vehicle related to autonomous vehicles is estimated, and the amount of communication within the road area on which autonomous vehicles travel is predicted; a non-road area communication volume prediction step for the non-road area of ​​the target area, in which the amount of communication within the non-road area is communication by pedestrians that does not include communication with autonomous vehicles; and a communication bandwidth calculation step for calculating communication equipment in the target area so as to satisfy the communication service quality with respect to the sum of the road area communication volume and the non-road area communication volume.

4. A program for causing a computer to function as a communication bandwidth calculation device according to claim 1 or 2.

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