JP7440616B2 - Abnormality detection device, onboard equipment, abnormality detection method, and program - Google Patents

Description

The present disclosure relates to an abnormality detection device, an on-vehicle device, an abnormality detection method, and a program.

It is known that an on-vehicle device mounted on a vehicle or the like receives a signal via an on-vehicle antenna and specifies the current driving route etc. from the actually measured positioning results.

On the other hand, as a technology related to communication terminals, for example, Patent Document 1 discloses a position information management system that manages the positions of communication terminals and the like.

Japanese Patent Application Publication No. 2014-217015

The location information management system disclosed in Patent Document 1 compares movement history information and failure pattern information to detect an abnormality in a distribution device that distributes location information to a communication terminal or the like.
However, in the abnormality detection method disclosed in Patent Document 1, the influence of the surrounding environment may be detected as an abnormality.

The present disclosure aims to provide an abnormality detection device, an on-vehicle device, an abnormality detection method, and a program in which the influence of the surrounding environment is difficult to detect as an abnormality in actually measured positioning results.

An anomaly detection device according to the present disclosure includes a statistical data acquisition unit that acquires statistical data of GNSS positioning results associated with a position, and an actual measured positioning unit that is the GNSS positioning result that is actually measured based on a GNSS signal and that includes position information. The apparatus includes a positioning result acquisition unit that acquires a result, and a determination unit that determines an abnormality in the actually measured positioning result based on the statistical data.

An anomaly detection method according to the present disclosure includes the steps of acquiring statistical data of GNSS positioning results associated with a position, and acquiring actual measured positioning results that are the GNSS positioning results that are actually measured based on GNSS signals and include position information. and determining an abnormality in the actually measured positioning result based on the statistical data.

A program according to the present disclosure includes a step of acquiring statistical data of a GNSS positioning result associated with a position in a computer of an abnormality detection device, and the GNSS positioning result is actually measured based on a GNSS signal and includes position information. A step of acquiring an actual positioning result, and a step of determining an abnormality in the actual positioning result based on the statistical data are executed.

According to the abnormality detection device, in-vehicle device, abnormality detection method, and program of the present disclosure, the influence of the surrounding environment is unlikely to be detected as an abnormality in the actually measured positioning result.

FIG. 1 is a block diagram of an abnormality detection device according to a first embodiment of the present disclosure. FIG. 2 is an explanatory diagram of a positioning result estimation model according to the first embodiment of the present disclosure. FIG. 3 is an explanatory diagram of position information according to the first embodiment of the present disclosure. 4 is an enlarged view of section IV in FIG. 3. FIG. FIG. 3 is a diagram showing a probability distribution according to the first embodiment of the present disclosure. 1 is a flowchart of an abnormality detection method according to a first embodiment of the present disclosure. FIG. 7 is an explanatory diagram of a positioning result estimation model according to a second embodiment of the present disclosure. FIG. 7 is an explanatory diagram of a positioning result estimation model according to a third embodiment of the present disclosure. FIG. 3 is a block diagram of an abnormality detection device according to a modification of the present disclosure. 1 is a diagram illustrating an example of a hardware configuration of a computer included in an abnormality detection device according to each embodiment of the present disclosure.

Embodiments according to the present disclosure will be described below with reference to the drawings. In all the drawings, the same or corresponding structures are given the same reference numerals, and common explanations are omitted.

<First embodiment>
A first embodiment of the abnormality detection device will be described with reference to FIGS. 1 to 6.

(In-vehicle system configuration)
The in-vehicle system 1 is a system for specifying the current position, travel route, etc. of a vehicle.
As shown in FIG. 1, the on-vehicle system 1 includes an on-vehicle antenna 2 and an on-vehicle device 3.
The in-vehicle system 1 is mounted on a vehicle.
For example, the in-vehicle system 1 may acquire the actual positioning result PRO based on a GNSS (Global Navigation Satellite System) signal SG received via the in-vehicle antenna 2.
Here, the actually measured positioning result PRO is a GNSS positioning result actually measured by the in-vehicle system 1 based on the GNSS signal SG, and includes position information IP indicating the actually measured position.
For example, the position information IP may indicate the reception position of the GNSS signal at the vehicle-mounted antenna 2.
For example, the actually measured positioning result PRO may further include a position error actually measured by the in-vehicle system 1, an actually measured reception strength of the GNSS signal, an actually measured number of captured satellites, and the like.
Moreover, these pieces of information included in the measured positioning result PRO may be calculated from GNSS signals received from a plurality of satellites.
The acquired actual positioning result PRO is used in the on-vehicle device 3 to specify the driving route of the vehicle and the like.

(Configuration of onboard equipment)
The onboard device 3 includes a reception section 4 and an abnormality detection device 5.
The receiving unit 4 receives GNSS signals SG received by the on-vehicle antenna 2 from a plurality of satellites.
For example, the onboard device 3 may be able to acquire the current position of the vehicle from the measured positioning result PRO, and display the travel route of the vehicle through processing such as map matching.

(Configuration of abnormality detection device)
The abnormality detection device 5 is a device for detecting an abnormality in the actually measured positioning result PRO.
The abnormality detection device 5 includes a statistical data acquisition section 51, a positioning result acquisition section 52, and a determination section 53.
For example, the abnormality detection device 5 may further include an output section 54.

The statistical data acquisition unit 51 acquires statistical data SDT of the GNSS positioning result PR1.
The statistical data SDT is associated with a position.
For example, the statistical data SDT may be associated with each of a plurality of locations.

For example, the statistical data SDT may be obtained in advance.
For example, the statistical data acquisition unit 51 may acquire the statistical data SDT in advance by storing it in the abnormality detection device 5 at the time of shipment of the on-vehicle device 3.
For example, the statistical data acquisition unit 51 may acquire the statistical data SDT stored inside the onboard device 3 in advance when the abnormality detection device 5 is activated.
For example, the statistical data acquisition unit 51 may acquire the latest statistical data SDT from outside the vehicle-mounted device 3 via communication in advance when the abnormality detection device 5 is activated.

For example, the GNSS positioning result PR1 indicated by the statistical data SDT may be the position, position error, reception strength of the GNSS signal, number of captured satellites, etc.
For example, the statistical data SDT may be a data set of probability distribution of the GNSS positioning result PR1.

For example, the statistical data SDT may be statistical data including a plurality of parameters.
Thereby, when each parameter is set, statistical data of the GNSS positioning result PR1 related to the set parameter is specified.
For example, the statistical data SDT may include 3D data, travel routes, camera images, satellite orbits, etc. as parameters.

For example, the statistical data SDT may be statistical data calculated in advance by a positioning result estimation model.
For example, when the statistical data SDT includes parameters such as 3D data, travel routes, camera images, and satellite orbits, as shown in Figure 2, the positioning result estimation model is used to automatically calculate the GNSS positioning results PR1 related to each parameter. The statistical data SDT may be calculated by learning.

Here, the 3D data is map data having three-dimensional information about roads on which vehicles can travel and their surroundings.
For example, the 3D data may include three-dimensional information of three-dimensional structures such as buildings, tunnels, walls, bridges, roads, mountains, trees, and signs around each location on the road.

Further, the travel route is a travel trajectory on a road on which the vehicle can travel, and includes position information IP1 at a position equivalent to the position indicated by the position information IP included in the measured positioning result PRO.
For example, as shown in FIGS. 3 and 4, the position indicated by the actually measured position information IP includes an error, whereas the position indicated by the position information IP1 does not need to include an error.

The positioning result acquisition unit 52 acquires the actually measured positioning result PRO.

The determining unit 53 determines an abnormality in the actually measured positioning result PRO based on the statistical data SDT.
For example, the determining unit 53 may determine whether there is an abnormality in the reception strength RI of the actually measured positioning result PRO.
For example, the determination unit 53 may include a comparison unit 531.

The comparison unit 531 compares the actually measured positioning result PRO with the statistical data SDT related to the position information IP included in the actually measured positioning result PRO.

For example, when a certain actual positioning result PRO is acquired, the determining unit 53 may identify statistical data SDO related to the actual positioning result PRO. At this time, the determination unit 53 sets each parameter based on the actual measured positioning result PRO, and obtains statistical data SDO related to the actual measured positioning result PRO based on each parameter from the statistical data SDT acquired by the statistical data acquisition unit 51. May be specified.

For example, when a certain actual positioning result PRO is acquired, the determination unit 53 selects the position information IP included in the actual positioning result PRO from among the statistical data SDT as the statistical data SDT related to the position information IP. Statistical data SDO in location information IP1 equivalent to IP may be specified. In this case, "location information IP1 equivalent to the location information IP" may be location information IP1 indicating a position within an error range included in the location indicated by the location information IP.
For example, the "error range included in the position indicated by the location information IP" corresponds to the size of the error in the position indicated by the location information IP, with the position indicated by the location information IP as the center, as shown in FIGS. 3 and 4. It may be a circular range with a radius.
Then, the comparison unit 531 compares the actual positioning result PRO at the position indicated by the position information IP and the statistical data SDO at the position indicated by the position information IP1.

For example, a case will be described in which the determining unit 53 determines an abnormality in the reception strength RI of the measured positioning result PRO.
In this case, the comparison unit 531 uses the statistical data SDO regarding the reception strength in the location information IP1 as a comparison standard among the statistical data SDT. At this time, as shown in FIG. 5, the statistical data SDO regarding the reception strength may be, for example, a probability distribution of the reception strength in the position information IP1.

For example, as shown in FIG. 5, the probability distribution of the received strength shows a distribution that decreases from a peak between the upper and lower limits of the received strength toward the lower and upper limits.
If the reception strength RI corresponds to the reception strength that indicates a peak in the probability distribution of reception strength, the in-vehicle system 1 is receiving the reception strength RI that is likely at the position indicated by the position information IP.
On the other hand, if the reception strength RI corresponds to a reception strength that does not show a peak in the probability distribution of reception strength, the in-vehicle system 1 is receiving an unlikely reception strength RI at the position indicated by the location information IP. become.
For this reason, in the probability distribution of reception strengths, if the reception strength RI is included in the reception strength that does not show a peak, there is a high possibility that the reception strength RI is abnormal.
Therefore, for example, as shown in FIG. 5, the reception strength RI at the position indicated by the location information IP is 0.01% from the lower limit of the probability distribution of the reception strength or 0.01% from the upper limit of the probability distribution of the reception strength. If included, the determining unit 53 may determine that the reception strength RI is abnormal.

When the determining unit 53 determines that the measured positioning result PRO is abnormal, the output unit 54 outputs that an abnormality has been detected.
For example, the output unit 54 may output an alarm, message, etc. to notify the user of an abnormality.
For example, in order to review the abnormality after it has been detected, the output unit 54 outputs various data, including the fact that the abnormality was detected, the time and position at which the abnormality was detected, to a recording medium, etc., and stores the data. Good too.

(motion)
The operation of the abnormality detection device 5 of this embodiment will be explained.
The operation of the abnormality detection device 5 corresponds to an embodiment of the abnormality detection method.
The abnormality detection device 5 implements each step shown in FIG.

First, the statistical data acquisition unit 51 acquires statistical data SDT associated with a position (step ST01).
For example, the statistical data acquisition unit 51 may acquire the statistical data SDT in advance.

Following the implementation of step ST01, the positioning result acquisition unit 52 acquires the actually measured positioning result PRO, which is a GNSS positioning result actually measured based on the GNSS signal SG and includes position information IP (step ST02).

Following the implementation of step ST02, the determination unit 53 determines whether there is an abnormality in the actual positioning result PRO based on the acquired statistical data SDT (step ST03).

If the determining unit 53 does not determine an abnormality (step ST03: No), step ST02 is performed again.
When the determining unit 53 determines that an abnormality is detected (step ST03: Yes), the output unit 54 outputs the fact that an abnormality has been detected through display or data output (step ST04).

(action and effect)
According to this embodiment, the abnormality detection device 5 detects an abnormality in the actually measured positioning result based on the statistical data SDT of the GNSS positioning result associated with the position.
Since the statistical data SDT of the GNSS positioning results includes the influence of the surrounding environment, the anomaly detection device 5 can suppress the influence of the surrounding environment at each position and detect anomalies in the actually measured positioning results. can.
Therefore, according to the abnormality detection device 5, the influence of the surrounding environment is unlikely to be detected as an abnormality in the actually measured positioning result.

For example, the radio wave communication status may vary depending on the influence of three-dimensional structures such as buildings, tunnels, walls, bridges, roads, mountains, trees, and signs around each location on the road.
On the other hand, since the statistical data SDT is statistical data acquired from the GNSS positioning results related to each position, it is statistical data that includes, for example, the influence of three-dimensional structures related to each position.
Therefore, since the abnormality detection device 5 can detect an abnormality based on statistical data including the influence of three-dimensional structures, the abnormality detection device 5 can suppress the influence of three-dimensional structures, regardless of the presence or absence of three-dimensional structures. Abnormalities in actually measured positioning results can be detected.

According to an example of the present embodiment, by comparing the actually measured positioning result PRO and the statistical data SDT related to the position information IP, the abnormality detection device 5 detects the surrounding environment of the position where the actually measured positioning result PRO was acquired. It is possible to detect an abnormality in the actually measured positioning result based on the statistical data SDT including the influence of

Further, according to an example of the present embodiment, the abnormality detection device 5 can detect an abnormality in the actually measured reception strength RI based on the statistical data SDT of the reception strength including the influence of the surrounding environment.
Therefore, according to the abnormality detection device 5, the influence of the surrounding environment on the reception strength RI is difficult to be detected as an abnormality in the actually measured positioning result.

<Second embodiment>
A second embodiment of the abnormality detection device will be described with reference to FIGS. 1, 6, and 7.

(composition)
The abnormality detection device 5 is configured as shown in FIG. 1 similarly to the first embodiment.
In this embodiment, for example, the statistical data SDT may be further associated with time.

For example, the statistical data SDT may include time in addition to 3D data, travel routes, camera images, satellite orbits, etc. as parameters.

For example, if the statistical data SDT includes time as a parameter in addition to 3D data, travel routes, camera images, satellite orbits, etc., as shown in Figure 7, the positioning result estimation model is used to calculate the GNSS positioning related to each parameter. The statistical data SDT may be calculated by machine learning the result PR1.

For example, the positioning result acquisition unit 52 may include in the actual positioning result PRO the time at which the actual positioning result PRO was actually measured.

For example, the determining unit 53 may specify statistical data related to the time when the measured positioning result PRO was actually measured as the statistical data SDO related to the measured positioning result PRO.

(motion)
The operation of the abnormality detection device 5 of this embodiment will be explained.
The operation of the abnormality detection device 5 corresponds to an embodiment of the abnormality detection method.
The abnormality detection device 5 performs each step shown in FIG. 6 similarly to the first embodiment.
First, the statistical data acquisition unit 51 acquires statistical data SDT associated with each of a plurality of positions (step ST01). At that time, for example, the statistical data SDT may be further associated with time.

Following the implementation of step ST01, the positioning result acquisition unit 52 acquires the actually measured positioning result PRO, which is a GNSS positioning result actually measured based on the GNSS signal SG and includes position information IP (step ST02). At that time, for example, the positioning result acquisition unit 52 may include in the actual positioning result PRO the time at which the actual positioning result PRO was actually measured.

Following the implementation of step ST02, the determination unit 53 determines whether there is an abnormality in the actual positioning result PRO based on the acquired statistical data SDT (step ST03). At this time, for example, the determining unit 53 may specify statistical data related to the time when the measured positioning result PRO was actually measured, as the statistical data SDO related to the measured positioning result PRO.

The subsequent operations are similar to those in the first embodiment.

(action and effect)
According to an example of the present embodiment, the abnormality detection device 5 detects an abnormality in the actually measured positioning results based on the statistical data SDT of the GNSS positioning results associated with each time.
Since the statistical data SDT of the GNSS positioning results includes the influence of the surrounding environment at each time, the anomaly detection device 5 suppresses the influence of the surrounding environment at each time and detects abnormalities in the actually measured positioning results. can do.

For example, radio wave communication conditions may differ between night and day even at the same location. On the other hand, according to an example of the present embodiment, the abnormality detection device 5 can suppress differences in the radio wave communication status due to differences in time, so that, for example, the abnormality detection device 5 can suppress differences in the radio wave communication status due to differences in time. Abnormalities in positioning results can be detected.

<Third embodiment>
A third embodiment of the abnormality detection device will be described with reference to FIGS. 1, 6, and 8.

(composition)
The abnormality detection device 5 is configured as shown in FIG. 1 similarly to the first embodiment.
In this embodiment, for example, the statistical data SDT may be further associated with the vehicle type.

For example, in the statistical data acquisition unit 51, the statistical data SDT may include vehicle type in addition to 3D data, driving route, camera image, satellite orbit, etc. as parameters.

For example, if the statistical data SDT includes vehicle type as a parameter in addition to 3D data, driving routes, camera images, satellite orbits, etc., as shown in Figure 8, the positioning result estimation model is used to perform GNSS positioning related to each parameter. The statistical data SDT may be calculated by machine learning the result PR1.

For example, the positioning result acquisition unit 52 may include, in the actual positioning result PRO, vehicle type information that is preset and indicates the type of vehicle in which the vehicle is mounted.

For example, the determining unit 53 may specify, as the statistical data SDO related to the actual positioning result PRO, statistical data related to the model of the vehicle in which the actual positioning result PRO was measured.

(motion)
The operation of the abnormality detection device 5 of this embodiment will be explained.
The operation of the abnormality detection device 5 corresponds to an embodiment of the abnormality detection method.
The abnormality detection device 5 performs each step shown in FIG. 6 similarly to the first embodiment.
First, the statistical data acquisition unit 51 acquires statistical data SDT associated with a position (step ST01). At that time, for example, the statistical data SDT may be further associated with the vehicle type.

Following the implementation of step ST01, the positioning result acquisition unit 52 acquires the actually measured positioning result PRO, which is a GNSS positioning result actually measured based on the GNSS signal SG and includes position information IP (step ST02). At this time, for example, the positioning result acquisition unit 52 may include, in the actual positioning result PRO, vehicle type information that is preset and indicates the type of vehicle in which the abnormality detection device 5 is installed.

Following the implementation of step ST02, the determination unit 53 determines whether there is an abnormality in the actual positioning result PRO based on the acquired statistical data SDT (step ST03). At this time, for example, the determining unit 53 may specify, as the statistical data SDO related to the actual positioning result PRO, statistical data related to the vehicle type of the vehicle in which the actual positioning result PRO was measured.

The subsequent operations are similar to those in the first embodiment.

(action and effect)
According to this embodiment, the abnormality detection device 5 detects abnormalities in the actually measured positioning results based on the statistical data SDT of the GNSS positioning results PR1 associated with each vehicle type.
Since the statistical data SDT of the GNSS positioning result PR1 includes the influence of the surrounding environment for each vehicle type, the abnormality detection device 5 suppresses the influence of the surrounding environment for each vehicle type and detects abnormalities in the actually measured positioning results. can be detected.

For example, the radio wave communication status may differ between a truck and a light vehicle, which have significantly different vehicle heights, even if they are in the same location. On the other hand, according to an example of the present embodiment, the abnormality detection device 5 can suppress the difference in the radio communication status due to the difference in vehicle type, so that the abnormality detection device 5 can suppress the difference in the communication status of radio waves due to the difference in vehicle type. Anomalies in results can be detected.

As a modification, the statistical data SDT may be associated with time and vehicle type.
For example, the statistical data SDT may include time and vehicle type in addition to 3D data, travel routes, camera images, satellite orbits, etc. as parameters.
In this case, the determination unit 53 may specify statistical data related to the time when the measured positioning result PRO was actually measured and the vehicle type as the statistical data SDO related to the measured positioning result PRO.

<Other variations>
In each of the embodiments described above, the abnormality detection device 5 detects an abnormality in the actually measured positioning result PRO, but may further specify an abnormality mode for the detected abnormality.
As a modification, as shown in FIG. 9, the abnormality detection device 5 may further include an abnormal mode identification unit 55 that identifies the abnormal mode of the actual measured positioning result PRO based on the statistical data SDT.
As described above, the actual positioning result PRO may include various positioning results such as the actually measured position, position error, reception strength, number of captured satellites, etc. Therefore, the abnormal mode identification unit 55 determines the positioning result based on the pattern of combinations of these positioning results. can identify the abnormal mode.
For example, by machine learning each pattern of the combination of GNSS positioning results PR1, the abnormal mode identification unit 55 can detect a dropped in-vehicle antenna, a software bug, interference radio waves inside or outside the vehicle to communication, and interference waves inside or outside the vehicle to communication. It may be possible to identify the abnormal mode to which the measured positioning result PRO belongs from among abnormal modes such as an interfering structure outside the vehicle or poor connection of various cables.
According to this modification, the abnormality detection device 5 can identify the abnormality mode of the actually measured positioning result PRO.
Therefore, the abnormal mode of the actually measured positioning result PRO can be grasped.

In each of the embodiments described above, the comparison unit 531 compares the actual positioning result PRO at the position indicated by the location information IP and the statistical data SDT at the position indicated by the location information IP1 information. Any comparison may be made with the statistical data SDT.
As a modification, the comparison unit 531 may calculate the degree of abnormality as the comparison result.
For example, the comparison unit 531 may calculate, as the degree of abnormality, what percentage of the distribution from the upper limit or lower limit the actual measured positioning result PRO belongs to in the statistical data SDT as a reference. At this time, the determining unit 53 may determine that the actual positioning result PRO is abnormal when the calculated degree of abnormality is smaller than a predetermined value.
For example, when comparing the reception strength RI and the probability distribution, the comparison unit 531 calculates, as the degree of abnormality, what percentage of the distribution from the upper or lower limit the reception strength RI belongs to in the probability distribution of the reference reception strength. You may. At this time, the determining unit 53 may determine that the reception strength RI is abnormal when the calculated degree of abnormality is smaller than a predetermined value (for example, 0.01%).

In each of the embodiments described above, the statistical data SDT is calculated using the positioning result estimation model, but the statistical data SDT may be calculated in any manner as long as it is calculated.
For example, various parameters acquired from test vehicles and actual driving vehicles and actually measured GNSS positioning results are accumulated, and statistical data SDT is calculated by a positioning result estimation model from the various accumulated parameters and actually measured GNSS positioning results. may be done.

In each of the embodiments described above, step ST02 is performed after step ST01, but as a modification, step ST01 may be performed after step ST02 is performed.

In each of the embodiments described above, a program for realizing various functions of the abnormality detection device 5 is recorded on a computer-readable recording medium, and the program recorded on the recording medium is transmitted to a computer system such as a microcomputer. Various processes are performed by loading and executing the program. Here, various processes of the CPU of the computer system are stored in a computer-readable recording medium in the form of a program, and the various processes described above are performed by reading and executing this program by the computer. Further, the computer-readable recording medium refers to a magnetic disk, a magneto-optical disk, a CD-ROM, a DVD-ROM, a semiconductor memory, and the like. Alternatively, this computer program may be distributed to a computer via a communication line, and the computer receiving the distribution may execute the program.

In each of the embodiments described above, an example of the hardware configuration of a computer that executes programs for realizing various functions of the abnormality detection device 5 will be described.

As shown in FIG. 10, the computer 59 included in the abnormality detection device 5 communicates with a CPU 591, a memory 592, a storage/reproduction device 593, and an Input Output Interface (hereinafter referred to as "IO I/F") 594. Interface (hereinafter referred to as "communication I/F") 595.

The memory 592 is a medium such as a random access memory (hereinafter referred to as "RAM") that temporarily stores data used in a program executed by the abnormality detection device 5.
For example, the memory 592 may store statistical data SDT, actual positioning results PRO, and the like.

The storage/playback device 593 is a device for storing data and the like in external media such as CD-ROM, DVD, and flash memory, and for playing back data and the like from the external media.

The IO I/F 594 is an interface for inputting and outputting information between the abnormality detection device 5 and other devices.

The communication I/F 595 is an interface for communicating with other devices via a communication line such as the Internet or a dedicated communication line.

<Other embodiments>
Although the embodiments of the present disclosure have been described above, these embodiments are presented as examples and are not intended to limit the scope of the disclosure. These embodiments can be implemented in various other forms, and various omissions, substitutions, and changes can be made without departing from the gist of the disclosure. These embodiments and variations thereof are included within the scope and gist of the disclosure.

<Additional notes>
The abnormality detection device, vehicle-mounted device, abnormality detection method, and program described in the above-described embodiments can be understood, for example, as follows.

(1) The abnormality detection device 5 according to the first aspect includes a statistical data acquisition unit 51 that acquires statistical data SDT of the GNSS positioning result PR1 associated with the position, and a GNSS positioning result actually measured based on the GNSS signal SG. It includes a positioning result acquisition unit 52 that acquires the measured positioning result PRO including position information IP, and a determining unit 53 that determines an abnormality in the measured positioning result PRO based on the statistical data SDT.

According to this aspect, the abnormality detection device 5 detects an abnormality in the actually measured positioning result based on the statistical data SDT of the GNSS positioning result PR1 associated with the position.
Since the statistical data SDT of the GNSS positioning result PR1 includes the influence of the surrounding environment, the abnormality detection device 5 suppresses the influence of the surrounding environment at each position and detects an abnormality in the actually measured positioning result. I can do it.
Therefore, according to the abnormality detection device 5, the influence of the surrounding environment is unlikely to be detected as an abnormality in the actually measured positioning result.

(2) In the abnormality detection device 5 according to the second aspect, the determination unit 53 includes a comparison unit 531 that compares the actual positioning result PRO and the statistical data SDT related to the position information IP. This is a detection device 5.

According to this aspect, the abnormality detection device 5 can detect an abnormality in the actually measured positioning result based on the statistical data SDT including the influence of the surrounding environment of the position where the actually measured positioning result PRO was acquired.

(3) The abnormality detection device 5 according to the third aspect is an abnormality detection method according to (1) or (2), in which the actual measured positioning result PRO includes the reception strength RI, and the determination unit 53 determines the abnormality with respect to the reception strength RI. This is device 5.

According to this aspect, the abnormality detection device 5 can detect an abnormality in the actually measured reception strength RI based on the statistical data SDT of the reception strength including the influence of the surrounding environment.
Therefore, according to the abnormality detection device 5, the influence of the surrounding environment on the reception strength RI is difficult to be detected as an abnormality in the actually measured positioning result.

(4) The abnormality detection device 5 according to the fourth aspect is the abnormality detection device 5 according to any one of (1) to (3), in which the statistical data SDT is further associated with time.

According to this aspect, the abnormality detection device 5 detects an abnormality in the actually measured positioning result based on the statistical data SDT of the GNSS positioning result PR1 associated with each time.
Since the statistical data SDT of the GNSS positioning result PR1 includes the influence of the surrounding environment at each time, the anomaly detection device 5 suppresses the influence of the surrounding environment at each time and detects an abnormality in the actually measured positioning result. can be detected.
Therefore, according to the abnormality detection device 5, the influence of the surrounding environment at each time is difficult to be detected as an abnormality in the actually measured positioning result.

(5) The abnormality detection device 5 according to the fifth aspect is the abnormality detection device 5 according to any one of (1) to (4), in which the statistical data SDT is further associated with a vehicle type.

According to this aspect, the abnormality detection device 5 detects abnormalities in the actually measured positioning results based on the statistical data SDT of the GNSS positioning results PR1 associated with each vehicle type.
Since the statistical data of the GNSS positioning result PR1 includes the influence of the surrounding environment for each vehicle type, the abnormality detection device 5 detects the actually measured positioning result based on the statistical data including the influence of the surrounding environment for each vehicle type. Anomalies can be detected.
Therefore, according to the abnormality detection device 5, the influence of the surrounding environment of each vehicle type is difficult to be detected as an abnormality in the actually measured positioning result.

(6) The abnormality detection device 5 according to the sixth aspect further includes an abnormal mode identification unit 55 that identifies an abnormal mode of the actual measured positioning result PRO based on the statistical data SDT. This is an abnormality detection device 5.

According to this aspect, the abnormality detection device 5 can identify the abnormality mode of the actually measured positioning result PRO.
Therefore, the abnormal mode of the actually measured positioning result PRO can be grasped.

(7) The on-vehicle device according to the seventh aspect includes the abnormality detection device 5 according to any one of (1) to (6), the reception unit 4 that receives the GNSS signal SG received by the on-vehicle antenna 2 from a plurality of satellites, Equipped with.

According to this aspect, the onboard device 3 detects an abnormality in the actually measured positioning result based on the statistical data SDT of the GNSS positioning result PR1 associated with the position.
Since the statistical data SDT of the GNSS positioning result PR1 includes the influence of the surrounding environment, the onboard device 3 is able to suppress the influence of the surrounding environment at each position and detect abnormalities in the actually measured positioning result. can.
Therefore, according to the on-vehicle device 3, the influence of the surrounding environment is unlikely to be detected as an abnormality in the actually measured positioning result.

(8) The abnormality detection method according to the eighth aspect includes the steps of acquiring statistical data SDT of the GNSS positioning result PR1 associated with the position, and the GNSS positioning result actually measured based on the GNSS signal SG, and the position information The method includes the steps of acquiring the actually measured positioning result PRO including the IP, and determining an abnormality in the actually measured positioning result PRO based on the statistical data SDT.

According to this aspect, the abnormality detection method detects an abnormality in the actually measured positioning result based on the statistical data SDT of the GNSS positioning result PR1 associated with the position.
Since the statistical data SDT of GNSS positioning results includes the influence of the surrounding environment, the anomaly detection method can suppress the influence of the surrounding environment at each position and detect anomalies in the actually measured positioning results. .
Therefore, according to the anomaly detection method, the influence of the surrounding environment is unlikely to be detected as an anomaly in the actually measured positioning result.

(9) The program according to the ninth aspect includes the steps of: acquiring statistical data SDT of GNSS positioning results associated with the position in the computer 59 of the abnormality detection device 5; and GNSS positioning actually measured based on the GNSS signal SG. A step of acquiring the actually measured positioning result PRO which is a result and includes position information IP, and a step of determining an abnormality in the actually measured positioning result PRO based on the statistical data SDT are executed.

According to this aspect, the abnormality detection device 5 detects an abnormality in the actually measured positioning result based on the statistical data SDT of the GNSS positioning result PR1 associated with the position.
Since the statistical data SDT of the GNSS positioning result PR1 includes the influence of the surrounding environment, the anomaly detection device is able to suppress the influence of the surrounding environment at each position and detect anomalies in the actually measured positioning results. can.
Therefore, according to the program, the influence of the surrounding environment is unlikely to be detected as an abnormality in the actually measured positioning result.

According to the abnormality detection device, in-vehicle device, abnormality detection method, and program of the present disclosure, the influence of the surrounding environment is unlikely to be detected as an abnormality in the actually measured positioning result.

1 Vehicle-mounted system 2 Vehicle-mounted antenna 3 Vehicle-mounted device 4 Reception unit 5 Abnormality detection device 51 Statistical data acquisition unit 52 Positioning result acquisition unit 53 Discrimination unit 54 Output unit 55 Abnormal mode identification unit 59 Computer 531 Comparison unit 591 CPU
592 Memory 593 Storage/playback device 594 IO I/F
595 Communication I/F
IP Location information IP1 Location information PRO Actual positioning result PR1 GNSS positioning result RI Reception strength SDO Statistical data SDT Statistical data SG GNSS signal

Claims (8)

a statistical data acquisition unit that acquires statistical data of GNSS positioning results associated with the position;
a positioning result acquisition unit that acquires an actual measured positioning result that is the GNSS positioning result actually measured based on a GNSS signal and includes position information;
a determination unit that determines an abnormality in the actually measured positioning result based on the statistical data;
Equipped with
The statistical data is a probability distribution of reception strength at the position,
The statistical data is further associated with time,
The actually measured positioning result includes actually measured reception strength,
The determining unit determines the actually measured received strength to be abnormal if the actually measured received strength is included in the received strength at the position of a distribution in a predetermined range from the lower limit of the probability distribution or a distribution in a predetermined range from the upper limit of the probability distribution. Anomaly detection device. The abnormality detection device according to claim 1, wherein the determination unit includes a comparison unit that compares the actually measured positioning result and the statistical data related to the position information. The abnormality detection device according to claim 1 or 2 , wherein the statistical data is further associated with a vehicle type. The abnormality detection device according to claim 3 , wherein the positioning result acquisition unit includes preset vehicle type information in the actually measured positioning result. The abnormality detection device according to any one of claims 1 to 4 , further comprising an abnormal mode identification unit that identifies an abnormal mode of the measured positioning result based on the statistical data. An abnormality detection device according to any one of claims 1 to 5 ,
An on-vehicle device comprising: a reception unit that receives the GNSS signals received by an on-vehicle antenna from a plurality of satellites. a step in which the statistical data acquisition unit of the abnormality detection device acquires statistical data of GNSS positioning results associated with the position;
a step in which the positioning result acquisition unit of the abnormality detection device acquires the actually measured positioning result, which is the GNSS positioning result actually measured based on the GNSS signal and includes position information;
a step in which a determining unit of the abnormality detection device determines an abnormality in the actually measured positioning result based on the statistical data;
including;
The statistical data is a probability distribution of reception strength at the position,
The statistical data is further associated with time,
The actually measured positioning result includes actually measured reception strength,
In the step of determining the abnormality, if the actually measured reception strength is included in the reception strength at the position of the distribution in a predetermined range from the lower limit of the probability distribution or the distribution in a predetermined range from the upper limit, the determination unit An anomaly detection method that determines the received reception strength as an anomaly. In the computer of the abnormality detection device,
obtaining statistical data of GNSS positioning results associated with the location;
a step of acquiring an actual measured positioning result which is the GNSS positioning result actually measured based on a GNSS signal and includes position information;
determining an abnormality in the actually measured positioning result based on the statistical data;
run the
The statistical data is a probability distribution of reception strength at the position,
The statistical data is further associated with time,
The actually measured positioning result includes actually measured reception strength,
In the step of determining the abnormality, if the actually measured reception strength is included in the reception strength at the position in a distribution in a predetermined range from the lower limit of the probability distribution or in a distribution in a predetermined range from the upper limit, the actually measured reception strength is A program that identifies abnormalities.

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