JP7632037B2 - Information processing method, information processing device, and program - Google Patents

Description

This disclosure relates to an information processing method, an information processing device, and a program.

Patent Document 1 discloses a traffic condition estimation system. In the traffic condition estimation system disclosed in Patent Document 1, the number of vehicles that have passed a reference point on a road and the passing time, which is the time when a specific vehicle passes each point including the reference point, are acquired from a vehicle detection device installed at the reference point. In the traffic condition estimation system, the traffic condition of the road is estimated based on the number of vehicles that have passed the reference point and the passing time.

JP 2019-192148 A

The purpose of this disclosure is to understand the correlation between traffic volume and traffic speed on a road link.

An information processing method according to a first aspect of the present disclosure includes:
1. A computer-implemented information processing method, comprising:
Obtaining position and speed information for a plurality of vehicles;
calculating a traffic volume of the predetermined road link for each unit time within a predetermined period of time, the traffic volume indicating the number of all vehicles that have passed through the predetermined road link based on the position information of the plurality of vehicles;
calculating a traffic speed of the predetermined road link, which indicates a speed representative of a traffic flow of the predetermined road link, for each unit time within the predetermined period based on speed information of the plurality of vehicles;
calculating a correlation between the traffic volume and the traffic speed of the predetermined road link within the predetermined period based on the traffic volume and the traffic speed;
Includes.

An information processing device according to a second aspect of the present disclosure includes:
Obtaining position and speed information for a plurality of vehicles;
calculating a traffic volume of the predetermined road link for each unit time within a predetermined period of time, the traffic volume indicating the number of all vehicles that have passed through the predetermined road link based on the position information of the plurality of vehicles;
calculating a traffic speed of the predetermined road link, which indicates a speed representative of a traffic flow of the predetermined road link, for each unit time within the predetermined period based on speed information of the plurality of vehicles;
calculating a correlation between the traffic volume and the traffic speed of the predetermined road link within the predetermined period based on the traffic volume and the traffic speed;
The control unit executes the above.

A program according to a third aspect of the present disclosure includes:
A program for causing a computer to execute an information processing method,
The information processing method includes:
Obtaining position and speed information for a plurality of vehicles;
calculating a traffic volume of the predetermined road link for each unit time within a predetermined period of time, the traffic volume indicating the number of all vehicles that have passed through the predetermined road link based on the position information of the plurality of vehicles;
calculating a traffic speed of the predetermined road link, which indicates a speed representative of a traffic flow of the predetermined road link, for each unit time within the predetermined period based on speed information of the plurality of vehicles;
calculating a correlation between the traffic volume and the traffic speed of the predetermined road link within the predetermined period based on the traffic volume and the traffic speed;
Includes.

This disclosure makes it possible to understand the correlation between traffic volume and traffic speed on a road link.

FIG. 1 is a diagram showing a schematic configuration of an estimation system. FIG. 2 is a block diagram illustrating an example of a functional configuration of the server in the first embodiment. FIG. 3 shows an example of a table configuration of vehicle information stored in the vehicle information database. FIG. 4 is a diagram showing an example of a table configuration of the first area information stored in the first area information database in the first embodiment. FIG. 5 shows an example of a table configuration of the second area information stored in the second area information database. FIG. 6 is a flowchart of the estimation process. FIG. 7 is a flowchart of the correlation calculation process. FIG. 8 is a diagram showing an example of the correlation between traffic volume and traffic speed. FIG. 9 is a block diagram illustrating an example of a functional configuration of a server according to the second embodiment. FIG. 10 is a diagram showing an example of a table configuration of domestic information stored in the domestic information database. FIG. 11 is a diagram for explaining an example of a method for calculating the specific number of vehicles. FIG. 12 shows an example of a table configuration of the first area information stored in the first area information database in the third embodiment.

Assume that various vehicles pass through a specified road link. At this time, the number of vehicles passing through the specified road link changes. Furthermore, the flow of vehicles traveling on the specified road link also changes due to the change in the amount of vehicles passing through the specified road link. For example, the more vehicles passing through a specified road link, the worse the flow of vehicles traveling on the specified road link becomes. Therefore, the information processing method according to the first aspect of the present disclosure calculates the correlation between the number of vehicles passing through a specified road link and the flow of vehicles traveling on the specified road link.

An information processing method according to a first aspect of the present disclosure is an information processing method executed by a computer. In the information processing method, the computer acquires position information and speed information of a plurality of vehicles. The computer calculates a traffic volume of a predetermined road link for each unit time within a predetermined period based on the acquired position information of the plurality of vehicles. Here, the traffic volume of the predetermined road link is an amount indicating the number of vehicles that have passed through the predetermined road link (hereinafter, may be referred to as the "passing number"). Furthermore, the predetermined period is a period specified by an administrator who manages the computer. Furthermore, the unit time is a period specified by an administrator who manages the computer. The administrator who manages the computer appropriately sets a predetermined period and a unit time suitable for calculating a correlation between traffic volume and traffic speed described below.

At this time, if the computer is able to obtain the position information of all vehicles that have passed through a specified road link, it directly calculates the traffic volume by obtaining the number of all vehicles that have passed through the specified road link per unit time based on the position information. Also, there are cases where the computer is unable to obtain the position information of all vehicles that have passed through a specified road link. In such cases, the computer may calculate the traffic volume by estimating the number of all vehicles that have passed through a specified road link per unit time within a specified period from the number of passing vehicles for which position information was obtained.

The computer also calculates the traffic speed of a specific road link for each unit time within a specific period based on the acquired speed information. The traffic speed is a quantity indicating the speed representative of the traffic flow of a road link. Here, when the computer is able to acquire speed information of all vehicles that have passed through a specific road link, it calculates the traffic speed based on the speeds of all vehicles. In this case, the computer calculates the traffic speed, for example, by calculating the average speed of all vehicles. On the other hand, there are cases where the computer is unable to acquire speed information of all vehicles that have passed through a specific road link. In this case, when multiple vehicles are traveling on a road link, it is assumed that the multiple vehicles are traveling at a similar speed. The computer may acquire the traffic speed by estimating the speed of all vehicles traveling on a specific road link from the speed information of the multiple vehicles for which speed information has been acquired. The computer calculates the traffic speed, for example, by calculating the average speed of the multiple vehicles from the speed information of the multiple vehicles for which speed information has been acquired.

Then, the computer calculates the correlation between traffic volume and traffic speed on a specified road link within a specified period of time based on the calculated traffic volume and traffic speed.

As described above, the information processing method according to the first aspect of the present disclosure calculates the correlation between traffic volume and traffic speed of a specified road link within a specified time period. In this way, the information processing method according to the first aspect of the present disclosure makes it possible to calculate the correlation between traffic volume and traffic speed of a specified road link within a specified time period, for example, without installing a sensor or the like on the specified road link that measures the number and speed of vehicles passing through the specified road link. In this way, the correlation between traffic volume and traffic speed on a specified road link can be grasped.

Specific embodiments of the present disclosure are described below with reference to the drawings. The dimensions, materials, shapes, and relative positions of the components described in the present embodiment are not intended to limit the technical scope of the present disclosure unless otherwise specified.

First Embodiment
(System Overview)
An estimation system 1 in this embodiment will be described with reference to Fig. 1. Fig. 1 is a diagram showing a schematic configuration of the estimation system 1. The estimation system 1 includes an on-vehicle device 300 mounted on a plurality of vehicles and a server 400. In the estimation system 1, the on-vehicle devices 300 and the server 400 are connected to each other via a network N1. The network N1 may be, for example, a wide area network (WAN), which is a global public communication network such as the Internet, or a telephone communication network such as a mobile phone.

(In-vehicle device)
Assume that various vehicles pass through a predetermined road link. In FIG. 1, a vehicle of a predetermined manufacturer among a plurality of vehicles passing through a predetermined road link is defined as a first vehicle 10. Note that the predetermined manufacturer may include a plurality of manufacturers. The first vehicle 10, which is a vehicle of a predetermined manufacturer, includes a vehicle that can mount an on-board device 200, which is an on-board device having a communication function for communicating with the server 400, and a vehicle that cannot mount the on-board device 200. Among the first vehicles 10, a vehicle that can mount the on-board device 200 is defined as a second vehicle 20. Furthermore, the second vehicles 20 that can mount the on-board device 200 include a vehicle that has a contract (hereinafter, sometimes referred to as a "communication contract") to enable the communication function of the on-board device 200, and a vehicle that does not have a communication contract. Among the second vehicles 20, a vehicle that has a communication contract is defined as a third vehicle 30. Among the on-board devices 200, an on-board device mounted on the third vehicle 30 that has a communication contract is defined as an on-board device 300. In the estimation system 1, the in-vehicle device 300 transmits vehicle information including position information and speed information of the third vehicle 30 to the server 400 at a predetermined period via the network N1.

(server)
The server 400 estimates the number of vehicles that have passed through a predetermined road link (hereinafter, may be referred to as the "passing number of vehicles"). The server 400 estimates the number of vehicles of all manufacturers that have passed through the predetermined road link, including a vehicle of a predetermined manufacturer (first vehicle 10) and vehicles of all manufacturers other than the predetermined manufacturer (hereinafter, may be referred to as the "total passing number of vehicles").

At this time, the server 400 cannot obtain position information of any vehicle other than the third vehicle 30. In other words, it cannot obtain position information of the first vehicle 10 and the second vehicle that do not have the in-vehicle device 200, and the second vehicle 20 that has the in-vehicle device 200 but does not have a communication contract. The server 400 also cannot obtain position information of vehicles other than those of a specified manufacturer. Therefore, the server 400 cannot directly calculate the number of passing vehicles other than the third vehicle 30 based on the position information of vehicles other than the third vehicle 30.

The server 400 then identifies the third vehicle 30 that has passed through a specific road link based on the position information of the third vehicle 30 contained in the vehicle information received from the in-vehicle device 300. The server 400 then estimates the total number of passing vehicles based on the number of passing third vehicles 30. The method by which the server 400 estimates the total number of passing vehicles will be described in detail later.

The server 400 also calculates the correlation between traffic volume and traffic speed for a given road link. Here, traffic volume is the amount indicating the number of vehicles passing through a road link. The more vehicles that pass through a road link, the greater the traffic volume. Furthermore, traffic speed is a value indicating the speed that represents the traffic flow of the road link. The method of calculating the correlation between traffic volume and traffic speed for a given road link will be described in detail later.

The server 400 includes a computer having a processor 410, a main memory unit 420, an auxiliary memory unit 430, and a communication interface (communication I/F) 440. The processor 410 is, for example, a CPU (Central Processing Unit) or a DSP (Digital Signal Processor). The main memory unit 420 is, for example, a RAM (Random Access Memory). The auxiliary memory unit 430 is, for example, a ROM (Read Only Memory). The auxiliary memory unit 430 is, for example, a HDD (Hard Disk Drive), or a disk recording medium such as a CD-ROM, a DVD disk, or a Blu-ray disk. The auxiliary memory unit 430 may also be a removable medium (portable storage medium). Here, examples of the removable medium include a USB memory and an SD card. The communication I/F 440 is, for example, a LAN (Local Area Network) interface board or a wireless communication circuit for wireless communication.

In the server 400, the auxiliary memory unit 430 stores an operating system (OS), various programs, various information tables, and the like. In the server 400, the processor 410 can load the programs stored in the auxiliary memory unit 430 into the main memory unit 420 and execute them to realize various functions as described below. However, some or all of the functions of the server 400 may be realized by hardware circuits such as ASICs or FPGAs. The server 400 does not necessarily have to be realized by a single physical configuration, and may be composed of multiple computers that work together. The in-vehicle device 200 and the in-vehicle device 300 are also configured to include a computer, just like the server 400.

(Functional configuration)
Next, the functional configuration of the server 400 constituting the estimation system 1 according to the present embodiment will be described with reference to Fig. 2 to Fig. 5. Fig. 2 is a block diagram illustrating an example of the functional configuration of the server 400 in the present embodiment.

The server 400 includes a control unit 401, a communication unit 402, a vehicle information database 403 (vehicle information DB 403), a first area information database 404 (first area information DB 404), and a second area information database 405 (second area information DB 405). The control unit 401 has a function of performing calculation processing for controlling the server 400. The control unit 401 can be realized by a processor 410 in the server 400.

The communication unit 402 has a function of connecting the server 400 to the network N1. The communication unit 402 can be realized by the communication I/F 440 in the server 400. The control unit 401 receives vehicle information of each third vehicle 30 from the multiple in-vehicle devices 300 at a predetermined period by the communication unit 402. The control unit 401 stores the received vehicle information of the third vehicle 30 in the vehicle information DB 403. The control unit 401 may acquire vehicle information transmitted by the in-vehicle device 300 to a server device other than the server 400 from the server device. In this embodiment, the vehicle information received by the server 400 from the in-vehicle device 300 includes the speed information of the third vehicle 30. However, the vehicle information does not necessarily need to include the speed information. For example, the server 400 may acquire the speed of the third vehicle 30 by calculating the speed of the third vehicle 30 based on the position information included in the vehicle information.

The vehicle information DB 403 can be realized by the auxiliary storage unit 430 in the server 400. FIG. 3 is an example of a table configuration of vehicle information stored in the vehicle information DB 403. As shown in FIG. 3, the vehicle information of the third vehicle 30 stored in the vehicle information DB 403 has a vehicle ID field, a position field, a speed field, a date and time field, a vehicle type field, and a vehicle model field. An identifier (vehicle ID) for identifying a vehicle is inputted into the vehicle ID field. Here, the vehicle ID of the third vehicle 30 is inputted into the vehicle ID field. The position information of the third vehicle 30 is inputted into the position field. The position information of the third vehicle 30 inputted into the position field is, for example, latitude and longitude. Based on the position information inputted into the position field, it is possible to identify the road link that the third vehicle 30 has passed through. The speed information of the third vehicle 30 is inputted into the speed field. Based on the speed information inputted into the speed field, it is possible to identify the speed at which the third vehicle 30 passed through the road link. The date and time field is input with the date and time when the in-vehicle device 300 transmitted the vehicle information to the server 400. Based on the date and time input in the date and time field, the passing time when the third vehicle 30 passed a certain road link can be identified. The vehicle model field is input with the vehicle model of the third vehicle 30 corresponding to the vehicle ID input in the vehicle ID field. Here, the vehicle model field is input with the vehicle model determined by a specific manufacturer. The vehicle model field is input with the vehicle model of the third vehicle 30 corresponding to the vehicle ID input in the vehicle ID field.

The first area information DB 404 is a database for storing the first area information. The first area information DB 404 can be realized by the auxiliary memory unit 430 in the server 400. The first area information is information related to the number of registered second vehicles 20 in a specified area. Here, the specified area is an area that includes a specified road link. The specified area is, for example, an administrative region such as a prefecture that includes the specified road link. Note that the specified area does not have to be an administrative region such as a prefecture as long as it is an area that includes the specified road link. Furthermore, the number of registered vehicles in a specified area is the number of vehicles that are registered in advance as being present in the specified area. It is considered that the number of registered vehicles in a specified area is close to the number of vehicles operating in the specified area.

Figure 4 is a diagram showing an example of the table configuration of the first area information stored in the first area information DB 404 in this embodiment. As shown in Figure 4, the first area information has a vehicle type field, a third registered number field, and a second registered number field. The vehicle type defined by a specific manufacturer is entered in the vehicle type field.

The number of registered third vehicles (third registered number) in the specified area is entered for each vehicle type in the third registered number field. The number of registered second vehicles 20 (second registered number) in the specified area is entered for each vehicle type in the second registered number field. The number of registered vehicles in the specified area is the number of vehicles that have been pre-registered as being present in the specified area.

The second area information DB405 is a database for storing the second area information. Here, the second area information is information about the number of registered first vehicles 10 in a specified area and the number of registered vehicles of all manufacturers in the specified area. The second area information DB405 can be realized by the auxiliary storage unit 430 in the server 400. FIG. 5 is an example of a table configuration of the second area information stored in the second area information DB405. As shown in FIG. 5, it has a first registered number field and a total registered number field. The first registered number field is input with the number of registered first vehicles 10 in the specified area (first registered number). Note that the first registered number input in the first registered number field is the number of registered vehicles including vehicles of all models of a specified manufacturer. The total registered number field is input with the number of registered vehicles of all manufacturers in the specified area (total registered number).

(Calculation of the number of passing third vehicles)
The control unit 401 identifies the third vehicles 30 that have passed through the predetermined road link within each unit time in the predetermined period based on the vehicle information stored in the vehicle information DB 403. Specifically, the control unit 401 identifies the third vehicles 30 that have passed through the predetermined road link within each unit time in the predetermined period based on the position information of each third vehicle 30 input in the position field of the vehicle information and the date and time input in the date and time field. The control unit 401 also classifies the identified third vehicles 30 by vehicle type based on the vehicle type of each third vehicle 30 input in the vehicle type field of the vehicle information. Then, the control unit 401 calculates the number of passing third vehicles 30 for each vehicle type for each unit time. Hereinafter, the number of passing vehicles for each unit time may be simply referred to as the "number of passing vehicles". The predetermined period is a period set by the administrator of the server 400. For example, a period of one day or several days is set as the predetermined period. Furthermore, the unit time is a time set by the administrator of the server 400. For example, a period of one hour or several hours is set as the unit time. The administrator of the server 400 appropriately sets a predetermined period and a unit time suitable for calculating the correlation between traffic volume and traffic speed, which will be described later.

(Estimated number of passing second vehicles)
The predetermined road link is included in a predetermined area. Therefore, it is assumed that the ratio of the number of passing second vehicles 20 to the number of passing third vehicles 30 for each vehicle type is approximately equal to the ratio of the second registered number to the third registered number for each vehicle type. Then, the control unit 401 calculates an estimate of the number of passing second vehicles 20 including all vehicle types (hereinafter, may be referred to as the "second estimate") based on the ratio of the second registered number to the third registered number for each vehicle type and the number of passing third vehicles for each vehicle type.

Specifically, the control unit 401 calculates the second estimated value _N2 by the following formula. Here, the number N _i of passing third vehicles 30 belonging to each type i is the number of third vehicles 30 belonging to each type i that pass within a unit time. Therefore, the second estimated value _N2 obtained by multiplying the number of third vehicles 30 belonging to each type i that pass within a unit time by the ratio and taking the sum is also an estimate of the number of second vehicles 20 that pass within a unit time.

Here, T is a set of each vehicle type, N _i is the number of passing third vehicles 30 belonging to vehicle type i, b _i is the second registered number of vehicle type i, and a _i is the third registered number of vehicle type i. Therefore, N _i b _i /a _i in the above (Equation 1) is an estimated value of the number of passing second vehicles 20 belonging to vehicle type i. In this way, the control unit 401 calculates the second estimated value including all vehicle types by multiplying the ratio of the second registered number to the third registered number for each vehicle type by the number of passing third vehicles for each vehicle type and taking the sum for all vehicle types.

It is also possible to assume that the ratio of the number of passing second vehicles to the number of passing third vehicles, including all vehicle types, without classifying them by vehicle type, is roughly the same as the ratio of the number of passing second registered vehicles to the number of passing third registered vehicles, including all vehicle types. In this case, the second estimated value including all vehicle types is calculated based on the ratio of the number of passing second registered vehicles to the number of passing third vehicles 30, including all vehicle types. However, the proportion of vehicles with communication contracts may differ for each vehicle type. In other words, the ratio of the number of passing second registered vehicles to the number of passing third registered vehicles may differ depending on the vehicle type. Therefore, as in the above formula (1), the second estimated value including all vehicle types can be calculated with higher accuracy by taking the sum of the estimated values of the number of passing second vehicles 20 belonging to each vehicle type.

(Estimated number of vehicles passing through the first carriage)
It is also assumed that the ratio between the number of passing first vehicles and the number of passing second vehicles is approximately equal to the ratio between the first registered number and the second registered number including all vehicle types. Then, the control unit 401 calculates an estimate of the number of passing first vehicles 10 that have passed through a predetermined road link (hereinafter, may be referred to as the "first estimate") based on the ratio between the first registered number and the second registered number including all vehicle types and the second estimate including all vehicle types.

ここで、Ｒ_１は第１登録台数、Ｒ_２は第２登録台数である。 Specifically, the control unit 401 calculates the first estimated value N1 by multiplying the ratio between the first registered number and the second registered number by the second estimated value _N2 including all vehicle types, as in the following formula (2). Here, the second estimated value _N2 is an estimate of the number of passing vehicles of the second vehicle 20 per unit time. Therefore, the first estimated value _N1 obtained by multiplying the estimate of the number of passing vehicles of the second vehicle ₂₀ per unit time by the ratio is also an estimate of the number of passing vehicles of the first vehicle 10 per unit time.

Here, _R1 is the first registered number, and _R2 is the second registered number.

(Estimate of total number of passing vehicles)
It is further assumed that the ratio of the total number of passing vehicles to the number of passing vehicles of the first vehicle is approximately equal to the ratio of the total number of registered vehicles to the first number of registered vehicles. Then, the control unit 401 calculates an estimate of the total number of passing vehicles based on the ratio of the total number of registered vehicles to the first number of registered vehicles and the first estimate.

ここで、Ｒ_１は第１登録台数であり、Ｒ_ａｌｌは全登録台数である。 Specifically, the control unit 401 calculates the estimated value N all of the total number of passing vehicles by multiplying the ratio between the total number of registered vehicles and the first number of registered vehicles by the first estimated value N ₁ as in the following formula (3 ₎ . Here, the first estimated value N ₁ is an estimated value of the number of passing vehicles of the first vehicle 10 per unit time. Therefore, the estimated value N _all of the total number of passing vehicles obtained by multiplying the estimated value of the number of passing vehicles of the first vehicle 10 per unit time by the ratio is also an estimated value of the number of passing vehicles of all manufacturers per unit time.

Here, _R1 is the first registered number, and _Rall is the total registered number.

(Estimation process)
Next, the estimation process executed by the control unit 401 in the server 400 in the estimation system 1 will be described with reference to Fig. 6. The estimation process is a process for calculating an estimated value of the total number of passing vehicles. Fig. 6 is a flowchart of the estimation process. The estimation process is started, for example, when an administrator of the server 400 inputs information about a predetermined road link and instructs the server 400 to execute the estimation process.

In the estimation process, first, in S101, third vehicles 30 that have passed through a specified road link within each unit time are identified based on the vehicle information stored in the vehicle information DB 403. Here, the administrator of the server 400 specifies the specified period and the unit time. Specifically, the control unit 401 identifies third vehicles 30 that have passed through a specified road link within each unit time within a specified period based on the date and time and location information entered in the date and time field in the vehicle information stored in the vehicle information DB 403. Next, in S102, the number of third vehicles 30 that have passed through a specified road link for each type of vehicle is calculated for each unit time.

Next, in S103, the second estimated value including all vehicle types is calculated for each unit time. At this time, the control unit 401 acquires the second registered number and the third registered number for each vehicle type from the first area information DB 404. Then, the control unit 401 calculates the second estimated value for each vehicle type for each unit time based on the ratio between the second registered number and the third registered number for each vehicle type and the number of passing third vehicles for each vehicle type. Furthermore, the control unit 401 calculates the second estimated value including all vehicle types for each unit time by taking the sum of the second estimated values for each vehicle type. Next, in S104, the first estimated value is calculated for each unit time based on the ratio between the first registered number and the second registered number including all vehicle types and the second estimated value including all vehicle types. At this time, the control unit 401 calculates the second registered number including all vehicle types by taking the sum of the second registered numbers for each vehicle type stored in the first area information DB 404. Furthermore, the control unit 401 acquires the first registered number from the second area information DB 405. Next, in S105, an estimated value of the total number of passing vehicles is calculated for each unit time based on the ratio between the total registered number and the first registered number and the second estimated value. At this time, the control unit 401 acquires the total registered number from the second area information DB 405. Then, the estimation process is terminated.

(Correlation calculation process)
Next, the correlation calculation process executed by the control unit 401 in the server 400 in the estimation system 1 will be described with reference to Fig. 7. The correlation calculation process is a process for calculating the correlation between the traffic volume and the traffic speed of a predetermined road link within a predetermined period of time. Fig. 7 is a flowchart of the correlation calculation process. The correlation calculation process is started when the server 400 completes the estimation process.

In the correlation calculation process, first, in S201, the traffic volume within each unit time estimated in the estimation process is obtained. In addition, in S202, the traffic speed within each unit time is obtained. Here, the server 400 cannot obtain speed information other than that of the third vehicle 30. Therefore, when multiple vehicles are traveling on a road link, it is assumed that the multiple vehicles are traveling at the same speed. The control unit 401 obtains the speeds of multiple third vehicles 30 that have passed through a specified road link within each unit time from the passage information DB 403. Then, the control unit 401 calculates the harmonic average of the speeds of multiple third vehicles 30 that have passed through a specified road link within each unit time. The control unit 401 estimates the speeds of multiple vehicles, including vehicles other than the third vehicle 30, traveling on a specified road link by the harmonic average of the speeds of multiple third vehicles 30 that have passed through a specified road link within each unit time. That is, the control unit 401 calculates a speed (traffic speed) representative of the traffic flow of the road link by calculating the harmonic mean of the speeds of multiple third vehicles 30. In this way, the control unit 401 calculates the traffic speed of a specific road link for each unit time.

Next, in S203, the traffic volume for each unit time is associated with the traffic speed for each unit time to calculate the correlation between the traffic volume and the traffic speed. FIG. 8 is a diagram showing an example of the correlation between traffic volume and traffic speed. In FIG. 8, the horizontal axis indicates traffic volume, and the vertical axis indicates traffic speed. Also, in FIG. 8, plots showing the correspondence between traffic volume and traffic speed in each unit time are indicated by open circles. Also, in FIG. 8, an approximation curve based on each plot is indicated as a QV curve. In this way, the control unit 401 calculates the QV curve to calculate the correlation between traffic volume and traffic speed of a specified road link within a specified period.

Next, in S204, the maximum traffic volume of the specified road link is calculated. Here, the maximum traffic volume is a value indicating the maximum traffic volume of the road link. The maximum traffic volume of the specified road link is calculated by calculating the traffic volume corresponding to the maximum value in the horizontal axis direction of the QV curve. In this way, by calculating the maximum traffic volume, it becomes possible to grasp the maximum traffic volume of the specified road link.

In addition, in S205, the critical speed of the specified road link is calculated. Here, the critical speed is a value indicating the speed that is the boundary between congested and non-congested road links. The critical speed of the specified road link is calculated by calculating the traffic speed corresponding to the maximum value in the horizontal axis direction of the QV curve. As shown in FIG. 8, when the traffic speed in the specified road link is higher than the critical speed, the specified road link can be said to be in a non-congested state. Also, as shown in FIG. 8, when the traffic speed in the specified road link is lower than the critical speed, the specified road link can be said to be in a congested state. In this way, by calculating the critical speed, it becomes possible to know whether the specified road link is congested or not based on the speed of the vehicle traveling on the specified road link. When the processing of S205 is completed, the correlation calculation processing is terminated.

As described above, in the estimation system 1, the server 400 calculates an estimate of the total number of passing vehicles based on the number of passing third vehicles 30. In other words, in the estimation system 1, the number of passing vehicles of all manufacturers, including the number of passing vehicles other than the third vehicle 30 that have passed through a specified road link, can be calculated. Furthermore, the server 400 calculates the correlation between the traffic volume and traffic speed of a specified road link within a specified period based on the calculated estimate of the total number of passing vehicles. This makes it possible to grasp the correlation between the traffic volume and traffic speed of a specified road link. Note that in this embodiment, the multiple vehicle types defined by a specified manufacturer correspond to the "multiple groups" according to the present disclosure.

(Variation 1)
In this modified example, it is assumed that there is a vehicle type with a low ratio of vehicles with a communication contract (hereinafter, sometimes simply referred to as "contract rate"). In this case, the ratio between the second registered number and the third registered number of vehicles with a relatively low contract rate is larger than the ratio between the second registered number and the third registered number of vehicles with a relatively high contract rate. Therefore, when the same number of third vehicles 30 of a vehicle type with a low contract rate and a vehicle type with a high contract rate pass through a predetermined road link, the estimated number of passing vehicles of the second vehicle type with a low contract rate is larger than the estimated number of passing vehicles of the second vehicle type with a high contract rate. Therefore, when a vehicle type with a significantly low contract rate exists, there is a risk that the estimated number of passing vehicles of the vehicle type may be excessively affected by the second estimated value _N2 calculated by the above formula (1).

Therefore, in this modified example, the second estimated value is calculated by excluding the second vehicles 20 belonging to a vehicle type whose contract rate is equal to or lower than a predetermined first threshold (hereinafter, sometimes referred to as a "low contract rate vehicle type"). Specifically, the server 400 calculates the contract rate for each vehicle type based on the third registered number and the second registered number for each vehicle type in the first area information. Here, the contract rate for each vehicle type is calculated by dividing the third registered number for each vehicle type by the second registered number for each vehicle type. Then, the server 400 calculates the second estimated value _N2 by excluding the low contract rate vehicle type in the above formula (1). Specifically, the server 400 calculates the second estimated value _N2 by excluding the value of N _{i bi /a i of the low contract rate vehicle type in ΣN i bi / a i in} the above formula (1). However, the registered number of the low contract rate vehicle type is included in the first registered number. That is, the number of low contract rate vehicle models is included in the first registered number _R1 when calculating the first estimated value _N1 in the above formula (2). That is, the number of registered low contract rate vehicle models is considered to be included in the number of first vehicles 10 that are not equipped with the in-vehicle device 200, and the first estimated value _N1 is estimated.

In this way, by excluding the number of passing second vehicles 20 that belong to a vehicle type with a low contract rate when calculating an estimate of the number of passing second vehicles, it is possible to suppress the impact on the accuracy of the estimation of the second estimate. As a result, it is possible to calculate an estimate of the total number of passing vehicles with higher accuracy.

(Variation 2)
In this modified example, a case is assumed in which there is a vehicle type with a small number of registered third vehicles 30 in a specified area (the number of third vehicles 30 registered as existing in a specified area). In this case, there is a risk that a vehicle type with a significantly small number of registered third vehicles 30 in a specified area will pass through a specified road link with probabilistic uncertainty. Therefore, the server 400 calculates the second estimated value by excluding the second vehicle 20 of the vehicle type with a significantly small number of registered third vehicles 30 in the specified area. Specifically, the server 400 identifies a vehicle type (hereinafter, sometimes referred to as a "minority vehicle type") whose third registered number in the first area information is equal to or less than a predetermined second threshold. Then, the server 400 calculates the second estimated value _N2 by excluding the value of N _i b _i /a _i of the minority vehicle type in ΣN _i b _i /a _i in the above formula (1). However, the number of registered vehicles of the minority vehicle type is included in the first registered number. That is, the number of vehicles of the minority vehicle type is included in the first registered number _R1 when calculating the first estimated value _N1 in the above formula (2). That is, the first estimated value _N1 is estimated by regarding the number of registered vehicles of the minority vehicle type as being included in the number of first vehicles 10 that are not equipped with the in-vehicle device 200. In this way, when calculating an estimated value of the number of passing second vehicles, by excluding the number of passing second vehicles 20 belonging to the minority vehicle type that involves probabilistic uncertainty, it is possible to suppress the influence on the estimation accuracy of the second estimated value. As a result, it is possible to calculate an estimated value of the total number of passing vehicles with higher accuracy.

(Variation 3)
In this modified example, it is assumed that there exists a vehicle type in which the third registered number is different from the number of third vehicles 30 that are actually communicating with the server 400 in a specified area (hereinafter, sometimes referred to as the "communicating number"). For example, when there exist many third vehicles 30 whose on-board devices 300 are not actually used even though they have a communication contract, the third registered number is different from the communicating number. When there exists a vehicle type in which the difference between the third registered number and the communicating number is significantly large, there is a risk that the estimated value of the passing number of the vehicle type of the vehicle type has an excessively large influence on the second estimated value _N2 calculated by the above formula (1).

Therefore, the server 400 calculates the second estimated value by excluding vehicles belonging to vehicle types for which the difference between the third registered number and the communicating number is equal to or greater than a predetermined value (hereinafter, may be referred to as "divergent vehicle types"). At this time, the server 400 counts the communicating number for each vehicle type based on the vehicle information stored in the vehicle information DB 403. Note that the vehicle whose vehicle information is stored in the vehicle information DB 403 can be regarded as the third vehicle 30 communicating with the server 400. Furthermore, the server 400 identifies the divergent vehicle types based on the counted communicating number for each vehicle type and the third registered number for each vehicle type stored in the first area information DB.

Then, the server 400 calculates the second estimated value _N2 by excluding the value of N _{i bi} /a _i of the deviating vehicle type in ΣN _{i bi} /a _i in the above formula (1). However, the registered number of the deviating vehicle type is included in the first registered number. That is, the number of the deviating vehicle type is included in the first registered number R ₁ when calculating the first estimated value _N1 in the above formula (2). That is, the registered number of the deviating vehicle type is considered to be included in the number of the first vehicles 10 that do not have the in-vehicle device 200, and the first estimated value _N1 is estimated. In this way, by excluding the passing number of the second vehicles 20 belonging to the deviating vehicle type when calculating the estimated value of the passing number of the second vehicle, it is possible to suppress the influence on the estimation accuracy of the second estimated value. As a result, it is possible to calculate an estimated value of the total passing number with higher accuracy.

(Variation 4)
In this embodiment, the server 400 cannot obtain vehicle information on vehicles other than the third vehicle 30, and therefore estimates the total number of passing vehicles based on the number of passing third vehicles 30. However, if the server 400 can obtain vehicle information on all vehicles passing a specific road link, the correlation between traffic volume and traffic speed may be calculated by obtaining the number of passing vehicles and the speed of all vehicles per unit time within a specific period directly from the vehicle information.

Second Embodiment
In this embodiment, the server 400 calculates the uncertainty of the estimated value of the total number of passing vehicles in the first embodiment. Only the differences from the first embodiment will be described below. Fig. 9 is a block diagram showing an example of the functional configuration of the server 400 in this embodiment. In this embodiment, the server 400 includes a control unit 401, a communication unit 402, a vehicle information DB 403, a first area information DB 404, a second area information DB 405, and a domestic information database 406 (domestic information DB 406).

The domestic information DB 406 is a database for storing domestic information. Here, the domestic information is information relating to the number of vehicles in a country including a specified area. The domestic information DB 406 can be realized by the auxiliary storage unit 430 in the server 400. FIG. 10 is a diagram showing an example of a table configuration of the domestic information stored in the domestic information DB 406.

As shown in FIG. 10, the domestic information has a vehicle type field, a communication number field, a third registered number field, and a second registered number field. The vehicle type to which the third vehicle 30 belongs is input in the vehicle type field. The number of third vehicles 30 that are actually communicating with the server 400 in Japan (communicating number in Japan) is input in the communicating number field for each vehicle type input in the vehicle type field. The third registered number field is the registered number of third vehicles 30 in Japan (third registered number in Japan) for each vehicle type input in the vehicle type field. The second registered number field is the registered number of second vehicles 20 in Japan (second registered number in Japan) for each vehicle type input in the vehicle type field.

(Systematic error)
The server 400 calculates the estimated value of the total number of passing vehicles in the same manner as in the first embodiment. In this embodiment, the server 400 further calculates a systematic error, which is an error caused by the calculation method of the estimated value of the total number of passing vehicles. In this embodiment, the server 400 calculates the systematic error by the following method.

The control unit 401 calculates a third estimated value for each vehicle type based on the number of communicating vehicles in the country, the third registered number in the country, and the second registered number in the country, which are included in the domestic information. Here, the third estimated value is an estimated value of the number of second vehicles 20 present in the country. Specifically, the control unit 401 calculates the third estimated value for each vehicle type by multiplying the ratio of the second registered number to the third registered number in the country for each vehicle type by the number of communicating vehicles in the country. In other words, the third estimated value is calculated by a method similar to the method of calculating the second estimated value in the first embodiment.

The control unit 401 also calculates the ratio (hereinafter, sometimes referred to as the "predetermined ratio") between the second registered number in Japan of one of the multiple vehicle models and the total of the second registered numbers in Japan of each vehicle model other than the one vehicle model. The control unit 401 also calculates the total of the third estimated values of each vehicle model other than the one vehicle model.

The control unit 401 also calculates the product of the total value of the third estimated values of each vehicle type other than the one vehicle type and a predetermined ratio for the one vehicle type as the specific number of second vehicles 20 belonging to the one vehicle type. Then, it calculates the ratio of the difference between the third estimated value of the one vehicle type and the specific number of second vehicles 20 belonging to the one vehicle type to the third estimated value of the one vehicle type (hereinafter, sometimes simply referred to as the "difference ratio").

FIG. 11 is a diagram for explaining an example of a method for calculating the specific number of vehicles. In FIG. 11, the third estimated values of vehicle types A, B, and C are 1000, 2000, and 3000. The second registered numbers in Japan of vehicle types A, B, and C are 10000, 20000, and 30500. Here, assume that the specific number of vehicles 20 belonging to vehicle type C is calculated. In this case, the total of the third estimated values of each vehicle type (vehicle type A and vehicle type B) other than vehicle type C is 30000, which is the total of 10000 vehicles of vehicle type A and 20000 vehicles of vehicle type B. The predetermined ratio for vehicle type C, which is the ratio between the second registered number in Japan of vehicle type C and the total of the second registered numbers in Japan of each vehicle type other than vehicle type C, is 30500/(10000+20000). In addition, since the third estimated value of vehicle type A is 1000 vehicles and the third estimated value of vehicle type B is 2000 vehicles, the total of the third estimated values of each vehicle type other than vehicle type C is 3000. Therefore, the specific number related to the second vehicles 20 belonging to vehicle type C is 3050 vehicles, which is obtained by multiplying the predetermined ratio of 30500/30000 by 3000, which is the total of the third estimated values of each vehicle type other than vehicle type C.

In the above case, the control unit 401 calculates the ratio of the difference between the third estimated value for vehicle type C and the specific number of second vehicles 20 belonging to vehicle type C to the third estimated value for vehicle type C as the difference ratio for vehicle type C. Specifically, the difference ratio for vehicle type C is calculated by the following formula (4).

The control unit 401 also calculates the difference ratio for each of the multiple vehicle models other than the one vehicle model. For example, in the example shown in FIG. 9, the difference ratio is calculated for each of vehicle models A and B in the same manner as above. The control unit 401 then calculates the unbiased standard deviation of the difference ratio for each of the multiple vehicle models as the systematic error. Note that the control unit 401 may also calculate the square root of the unbiased variance of the difference ratio as the systematic error.

ここで、Ｘは、確率変数（第３車両３０の通過台数）であり、λはｋ台の第３車両３０が所定の道路リンクを通過する事象が起こる平均値であり、ｅはネイピア数である。 (Statistical error)
In this embodiment, the server 400 further calculates a statistical error, which is an error that appears due to a probabilistic event that the third vehicle passes through a predetermined road link. Here, the number of passing third vehicles that pass through the predetermined road link occurs discretely. Therefore, the occurrence probability of the number of passing third vehicles 30 follows a Poisson distribution. The probability mass function P of the Poisson distribution is expressed by the following equation (5).

Here, X is a random variable (the number of passing third vehicles 30), λ is the average value of the event that k third vehicles 30 pass through a given road link, and e is Napier's constant.

ここで、Ｎは、第３車両３０の通過台数である。第３車両３０の通過台数Ｎは、車両情報ＤＢに格納されている車両情報に基づいて算出することができる。 Therefore, the control unit 401 calculates the statistical error ΔN based on the following equation (6), using the number of third vehicles 30 that have passed through a specific road link as a random variable.

Here, N is the number of passing third vehicles 30. The number N of passing third vehicles 30 can be calculated based on the vehicle information stored in the vehicle information DB.

ここで、Ｅ_１は系統誤差であり、Ｅ_２は統計誤差である。 (Uncertainty calculation)
The control unit 401 calculates the uncertainty of the estimated value of the total number of passing vehicles based on the calculated systematic error and statistical error. Specifically, the control unit 401 calculates the uncertainty E based on the following formula (7).

where _E1 is the systematic error and _E2 is the statistical error.

As described above, the estimation system 1 calculates the uncertainty of the estimated value of the total number of passing vehicles, including both systematic error and statistical error. This makes it possible to estimate the uncertainty of the estimated value of the total number of passing vehicles calculated by the server 400.

(Variation 1)
As described above, in this embodiment, the server 400 calculates the systematic error based on the number of communicating vehicles, the second registered number, and the third registered number in the country. However, the server 400 does not necessarily have to calculate the systematic error based on these values. In other words, the server 400 can calculate the systematic error based on the number of communicating vehicles, the second registered number, and the third registered number in an area wider than the specified area including the specified road link.

ここで、Ｎ_ＡおよびＮ_Ｂはそれぞれ車両型式Ａの第３車両３０の通過台数および車両型式Ｂの第３車両３０の通過台数である。また、a_Ａおよびa_Ｂはそれぞれ車両型式Ａの第３登録台数および車両型式Ｂの第３登録台数である。また、b_Ａおよびb_Ｂはそれぞれ車両型式Ａの第３登録台数および車両型式Ｂの第２登録台数である。したがって、Ｎｉ＝Ｎ_Ａ＋Ｎ_Ｂ、ａ_ｉ＝ａ_Ａ＋ａ_Ｂ、ｂ_ｉ＝ｂ_Ａ＋ｂ_Ｂが成立する。 Third Embodiment
In the first embodiment, the second estimated value is calculated based on the ratio between the second registered number and the third registered number for each vehicle type and the number of passing third vehicles for each vehicle type. At this time, as shown in the above formula (1), the second estimated value of vehicle type i is given by _{Nibi /ai ( Ni} is the number of passing third vehicles 30 belonging to vehicle type i, _bi is the second registered number of vehicle type i, and _ai is the third registered number of vehicle type i). Here, one vehicle type may include multiple vehicle types. For example, when vehicle type i includes two types of vehicle types, vehicle type A and vehicle type B, the second estimated value _NAB of vehicle type i is given by the following (formula 8).

Here, N _A and N _B are the number of passing third vehicles 30 of vehicle type A and the number of passing third vehicles 30 of vehicle type B, respectively. Also, a _A and a _B are the third registered number of vehicle type A and the third registered number of vehicle type B, respectively. Also, b _A and b _B are the third registered number of vehicle type A and the second registered number of vehicle type B, respectively. Therefore, Ni = N _A + N _B , a _i = a _A + a _B , and _bi = b _A + b _B hold.

On the other hand, when the second estimated value of vehicle model i is calculated as the sum of the second estimated values of vehicle model A and vehicle model B, the second estimated value N _AB of vehicle model i is given by the following (Equation 9).

If equations (8) and (9) are taken as identities for N _A and N _B , the condition for the second estimates N _AB of both equations to match is to satisfy the following equation (10).

The left side of equation (10) is the contract rate for vehicle type A, and the right side of equation (10) is the contract rate for vehicle type B. Therefore, if the contract rate for each vehicle type in one vehicle model differs, if the second estimated value is calculated by grouping by vehicle model as in the first embodiment, there is a risk that the estimation accuracy of the second estimated value will be low.

Therefore, in this embodiment, the control unit 401 classifies vehicles (first vehicles 10) of a specified manufacturer into multiple groups based on the contract rate for each vehicle type. Here, each group is classified according to vehicle types with similar contract rates. The control unit 401 then calculates a second estimated value for each group based on the ratio between the second registered number and the third registered number for each group and the number of passing third vehicles for each group. Then, the control unit 401 calculates a second estimated value for the number of passing second vehicles 20 including all vehicle types by taking the sum of the second estimated values for all groups. Below, only the differences from the first embodiment will be explained.

Figure 12 is an example of a table configuration of the first area information stored in the first area information DB 404 in this embodiment. The first area information stored in the first area information DB 404 in this embodiment has a vehicle type field, a third registered number field, a second registered number field, and a contract rate field. The vehicle type of each vehicle model of a specified manufacturer is input in the vehicle type field. The third registered number field is input with the third registered number in a specified area for each vehicle type input in the vehicle type field. The second registered number field is input with the second registered number in a specified area for each vehicle type input in the vehicle type field. In addition, in the first area information DB 404, the vehicle type, the second registered number, and the third registered number are input for each group classified based on the contract rate. Then, the range of the contract rate in each group is input in the contract rate field. The control unit 401 calculates the contract rate of each vehicle type based on the third registered number and the second registered number. Then, each vehicle model is classified into groups based on the calculated contract rate. For example, each vehicle model is classified into five groups: a group with a contract rate of 80% or more, a group with a contract rate of 60% or more and less than 80%, a group with a contract rate of 40% or more and less than 60%, a group with a contract rate of 20% or more and less than 40%, and a group with a contract rate of 0% or more and less than 20%.

The control unit 401 then calculates the sum of the third registered numbers of each of the multiple vehicle types belonging to each group as the third registered number of each group in the specified area. The control unit 401 also calculates the sum of the second registered numbers of each of the multiple vehicle types belonging to each group as the second registered number of each group in the specified area. The control unit 401 also classifies the third vehicles 30 that have passed through the specified road link into groups based on the vehicle types of each third vehicle 30 entered in the vehicle type field in the vehicle information. The control unit 401 then calculates the number of passing third vehicles 30 for each group.

Then, the control unit 401 calculates a second estimated value N2 based on the ratio of the second registered number to the third registered number for each group and the number of passing third vehicles for each group. Specifically, the control unit 401 calculates the second estimated value _N2 by the following formula (11).

Here, G is a set of each group, N _i is the number of passing third vehicles in group i, b _i is the second registered number in group i, and a _i is the third registered number in group i. Therefore, N _i b _i /a _i in the above formula (11) is an estimated value of the number of passing second vehicles 20 belonging to group i. In this way, the control unit 401 calculates the second estimated value of the number of passing second vehicles 20 including all vehicle types by multiplying the ratio of the second registered number to the third registered number for each group by the number of passing third vehicles for each group and taking the sum for all groups.

As described above, in this embodiment, the second estimated value is calculated for each group classified based on the contract rate for each vehicle model. This makes it possible to calculate the second estimated value for each group classified by vehicle models with similar contract rates. Therefore, it becomes possible to calculate the second estimated value of the number of passing second vehicles 20 with higher accuracy. As a result, it becomes possible to calculate a more accurate estimate of the total number of passing vehicles.

The method of estimating the second estimated value in each modified example of the first embodiment can also be applied to estimating the second estimated value in the third embodiment. In addition, the method of calculating the systematic error, the method of calculating the statistical error, and the method of calculating the uncertainty of the estimated value of the total number of passing vehicles in the second embodiment can also be applied to calculating the estimated value of the total number of passing vehicles in the third embodiment.

<Other embodiments>
The above-described embodiment is merely an example, and the present disclosure may be modified as appropriate without departing from the spirit and scope of the present disclosure. Furthermore, the processes and means described in the present disclosure may be freely combined and implemented as long as no technical contradiction occurs.

In addition, a process described as being performed by one device may be shared and executed by multiple devices. Or, a process described as being performed by different devices may be executed by one device. In a computer system, the hardware configuration (server configuration) by which each function is realized can be flexibly changed.

The present disclosure can also be realized by supplying a computer program that implements the functions described in the above embodiments to a computer, and having one or more processors of the computer read and execute the program. Such a computer program may be provided to the computer by a non-transitory computer-readable storage medium that can be connected to the system bus of the computer, or may be provided to the computer via a network. Non-transitory computer-readable storage media include any type of medium suitable for storing electronic instructions, such as, for example, a magnetic disk (such as a floppy disk or a hard disk drive (HDD)), an optical disk (such as a CD-ROM, a DVD disk, or a Blu-ray disk), a read-only memory (ROM), a random access memory (RAM), an EPROM, an EEPROM, a magnetic card, a flash memory, or an optical card.

Reference Signs List 1: Estimation system 10: First vehicle 20: Second vehicle 30: Third vehicle 200: On-vehicle device 300: On-vehicle device 400: Server 401: Control unit 402: Communication unit 403: Vehicle information DB
404: First area information DB
405: Second area information DB

Claims (17)

1. A computer-implemented information processing method, comprising:
Obtaining position and speed information for a plurality of vehicles;
calculating a traffic volume of the predetermined road link for each unit time within a predetermined period of time, the traffic volume indicating the number of all vehicles that have passed through the predetermined road link based on the position information of the plurality of vehicles;
calculating a traffic speed of the predetermined road link, which indicates a speed representative of a traffic flow of the predetermined road link, for each unit time within the predetermined period based on speed information of the plurality of vehicles;
calculating a correlation between the traffic volume and the traffic speed of the predetermined road link within the predetermined period based on the traffic volume and the traffic speed;
Including ,
A vehicle of a specified manufacturer is designated as the first vehicle,
Among the vehicles of the specified manufacturer, a vehicle capable of mounting an on-board device having a communication function for communicating with a specified server device is designated as a second vehicle;
Among the vehicles of the specified manufacturer in which the in-vehicle device can be installed, a vehicle for which a contract has been made to enable the communication function of the in-vehicle device is defined as a third vehicle;
In the information processing method,
Identifying the third vehicles that have passed through the predetermined road link within each unit time based on position information of each third vehicle transmitted from the in-vehicle device mounted in each third vehicle to the predetermined server device;
acquiring a number of passing vehicles for each group among the third vehicles that pass through the predetermined road link within each unit time when the vehicles of the predetermined manufacturer are classified into a plurality of groups;
estimating the number of passing second vehicles for each group based on the number of passing third vehicles for each group and a ratio between the number of registered second vehicles and the number of registered third vehicles for each group in a specified area including the specified road link, and calculating an estimated value of the number of passing second vehicles that have passed through the specified road link as the sum of the number of passing second vehicles of each group;
calculating an estimated value of the number of passing vehicles of the first vehicles that have passed through the specified road link based on the estimated value of the number of passing vehicles of the second vehicles and a ratio of the number of registered vehicles of the first vehicles to the number of registered vehicles of the second vehicles in the specified area;
calculating an estimated number of passing vehicles of all vehicles that have passed through the specified road link based on an estimated number of passing vehicles of the first vehicles and a ratio of the registered number of vehicles of all manufacturers to the registered number of the first vehicles in the specified area;
Further comprising:
calculating a traffic volume of the predetermined road link for each unit time based on the estimated number of passing vehicles of all the vehicles;
Information processing methods. calculating a maximum traffic volume indicating a maximum traffic volume on the predetermined road link and a critical speed indicating a speed that is a boundary between congestion and non-congestion on the predetermined road link based on the correlation between the traffic volume and the traffic speed;
Further comprising:
The information processing method according to claim 1 . the plurality of groups are set based on vehicle models defined by the predetermined manufacturer,
3. The information processing method according to claim 1 or 2 . the plurality of groups are set based on a contract rate of a contract for communication between the predetermined server device and the in-vehicle device for each vehicle model;
3. The information processing method according to claim 1 or 2 . When calculating the estimated value of the number of passing vehicles of the second vehicles, the number of passing vehicles of the second vehicles of a group having a contract rate for a communication contract between the predetermined server device and the in-vehicle device equal to or less than a predetermined first threshold value among the plurality of groups is excluded.
The information processing method according to claim 1 . When calculating the estimated value of the number of passing vehicles of the second vehicles, the number of passing vehicles of the second vehicles of a group in which the number of the third vehicles registered in the specified area is equal to or less than a predetermined second threshold is excluded from the plurality of groups.
The information processing method according to claim 1 . When calculating an estimated value of the number of passing vehicles of the second vehicles, the number of passing vehicles of a group among the plurality of groups in which a difference between the number of registered vehicles of the third vehicles in the specified area and the number of the third vehicles in the specified area in which communication between the specified server device and the in-vehicle device is actually performed is equal to or greater than a specified value is excluded.
The information processing method according to claim 1 . calculating an estimated number of the second vehicles for each group in the wide area based on the number of the third vehicles for each group in a wide area that is wider than the specified area, in which communication between the specified server device and the in-vehicle device is actually being performed, and a ratio, for each group, between the number of the second vehicles registered in the wide area and the number of the third vehicles registered in the wide area;
calculating a specific number of the second vehicles of the one group by calculating a product of a ratio between the number of registered second vehicles in the wide area of one group among the plurality of groups and the number of registered second vehicles in the wide area of groups other than the one group and a sum of estimated values of the number of the second vehicles in the wide area of each group other than the one group;
Calculating a ratio of a difference between an estimated number of the second vehicles in the wide area of the one group and a specific number of the second vehicles in the one group to an estimated number of the second vehicles in the wide area;
Calculating a systematic error based on the proportions calculated for each group;
Further comprising:
The information processing method according to claim 1 . calculating a statistical error regarding the number of passing vehicles of all vehicles that have passed through the predetermined road link based on a Poisson distribution in which the sum of the number of passing vehicles of the third vehicles of each group is a random variable;
Further comprising:
The information processing method according to claim 8 . calculating an uncertainty regarding the number of all vehicles passing through the predetermined road link based on the systematic error and the statistical error;
Further comprising:
The information processing method according to claim 9 . Obtaining position and speed information for a plurality of vehicles;
calculating a traffic volume of the predetermined road link for each unit time within a predetermined period of time, the traffic volume indicating the number of all vehicles that have passed through the predetermined road link based on the position information of the plurality of vehicles;
calculating a traffic speed of the predetermined road link, which indicates a speed representative of a traffic flow of the predetermined road link, for each unit time within the predetermined period based on speed information of the plurality of vehicles;
calculating a correlation between the traffic volume and the traffic speed of the predetermined road link within the predetermined period based on the traffic volume and the traffic speed;
A control unit that executes
A vehicle of a specified manufacturer is designated as the first vehicle,
Among the vehicles of the specified manufacturer, a vehicle capable of mounting an on-board device having a communication function for communicating with a specified server device is designated as a second vehicle;
Among the vehicles of the specified manufacturer in which the in-vehicle device can be installed, a vehicle for which a contract has been made to enable the communication function of the in-vehicle device is defined as a third vehicle;
The control unit is
Identifying the third vehicles that have passed through the predetermined road link within each unit time based on position information of each third vehicle transmitted from the in-vehicle device mounted in each third vehicle to the predetermined server device;
acquiring a number of passing vehicles for each group among the third vehicles that pass through the predetermined road link within each unit time when the vehicles of the predetermined manufacturer are classified into a plurality of groups;
estimating the number of passing second vehicles for each group based on the number of passing third vehicles for each group and a ratio between the number of registered second vehicles and the number of registered third vehicles for each group in a specified area including the specified road link, and calculating an estimated value of the number of passing second vehicles that have passed through the specified road link as the sum of the number of passing second vehicles of each group;
calculating an estimated value of the number of passing vehicles of the first vehicles that have passed through the specified road link based on the estimated value of the number of passing vehicles of the second vehicles and a ratio of the number of registered vehicles of the first vehicles to the number of registered vehicles of the second vehicles in the specified area;
Based on an estimated value of the number of passing vehicles of the first vehicle and a ratio of the number of registered vehicles of all manufacturers to the number of registered vehicles of the first vehicle in the specified area, the number of vehicles passing the specified road link is calculated.
Calculate an estimate of the number of vehicles passing through the area;
Further execute
calculating a traffic volume of the predetermined road link for each unit time based on the estimated number of passing vehicles of all the vehicles;
Information processing device. The control unit is
calculating a maximum traffic volume indicating a maximum traffic volume on the predetermined road link and a critical speed indicating a speed that is a boundary between congestion and non-congestion on the predetermined road link based on the correlation between the traffic volume and the traffic speed;
Further execute
The information processing device according to claim 11 . the plurality of groups are set based on vehicle models defined by the predetermined manufacturer,
13. The information processing device according to claim 11 or 12 . the plurality of groups are set based on a contract rate of a contract for communication between the predetermined server device and the in-vehicle device for each vehicle model;
13. The information processing device according to claim 11 or 12 . The control unit is
When calculating the estimated value of the number of passing vehicles of the second vehicles, the number of passing vehicles of the second vehicles of a group having a contract rate for a communication contract between the predetermined server device and the in-vehicle device equal to or less than a predetermined first threshold value among the plurality of groups is excluded.
The information processing device according to claim 11 . The control unit is
When calculating the estimated value of the number of passing vehicles of the second vehicles, the number of passing vehicles of the second vehicles of a group in which the number of the third vehicles registered in the specified area is equal to or less than a predetermined second threshold is excluded from among the plurality of groups.
The information processing device according to claim 11 . A program for causing a computer to execute an information processing method,
The information processing method includes:
Obtaining position and speed information for a plurality of vehicles;
calculating a traffic volume of the predetermined road link for each unit time within a predetermined period of time, the traffic volume indicating the number of all vehicles that have passed through the predetermined road link based on the position information of the plurality of vehicles;
calculating a traffic speed of the predetermined road link, which indicates a speed representative of a traffic flow of the predetermined road link, for each unit time within the predetermined period based on speed information of the plurality of vehicles;
calculating a correlation between the traffic volume and the traffic speed of the predetermined road link within the predetermined period based on the traffic volume and the traffic speed;
Including ,
A vehicle of a specified manufacturer is designated as the first vehicle,
Among the vehicles of the specified manufacturer, a vehicle capable of mounting an on-board device having a communication function for communicating with a specified server device is designated as a second vehicle;
Among the vehicles of the specified manufacturer in which the in-vehicle device can be installed, a vehicle for which a contract has been made to enable the communication function of the in-vehicle device is defined as a third vehicle;
In the information processing method,
Identifying the third vehicles that have passed through the predetermined road link within each unit time based on position information of each third vehicle transmitted from the in-vehicle device mounted in each third vehicle to the predetermined server device;
acquiring a number of passing vehicles for each group among the third vehicles that pass through the predetermined road link within each unit time when the vehicles of the predetermined manufacturer are classified into a plurality of groups;
estimating the number of passing second vehicles for each group based on the number of passing third vehicles for each group and a ratio between the number of registered second vehicles and the number of registered third vehicles for each group in a specified area including the specified road link, and calculating an estimated value of the number of passing second vehicles that have passed through the specified road link as the sum of the number of passing second vehicles of each group;
calculating an estimated value of the number of passing vehicles of the first vehicles that have passed through the specified road link based on the estimated value of the number of passing vehicles of the second vehicles and a ratio of the number of registered vehicles of the first vehicles to the number of registered vehicles of the second vehicles in the specified area;
calculating an estimated number of passing vehicles of all vehicles that have passed through the specified road link based on an estimated number of passing vehicles of the first vehicles and a ratio of the registered number of vehicles of all manufacturers to the registered number of the first vehicles in the specified area;
Further comprising:
calculating a traffic volume of the predetermined road link for each unit time based on the estimated number of passing vehicles of all the vehicles;
program.

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