JP5223632B2 - Abnormality diagnosis device - Google Patents

Description

  The present invention relates to an abnormality diagnosis apparatus for a host vehicle such as an automobile.

As a conventional abnormality diagnosis device, for example, as described in Patent Document 1, a sensor (first environment information acquisition) that is mounted on the host vehicle and acquires environment information (first environment information) related to the surrounding environment of the host vehicle. Means) and a failure detection means (abnormality diagnosis means) for detecting a sensor failure is known. In such an abnormality diagnosis apparatus, a failure of a sensor is detected based on environmental information, and a driver is warned to that effect.
JP 2007-1333 A

  Here, in the above abnormality diagnosis apparatus, the acquired first environmental information may be affected by the presence or absence of a moving object (peripheral moving object) around the own vehicle, and the accuracy of abnormality diagnosis depends on the situation of the surrounding moving object. May decrease. That is, for example, even when the first environment information varies due to the movement of the surrounding moving object, there is a possibility that the first environment information acquisition unit is erroneously diagnosed as having an abnormality.

  Then, this invention makes it a subject to provide the abnormality diagnosis apparatus which can diagnose an abnormality accurately irrespective of the condition of a surrounding moving object.

  In order to solve the above-described problems, an abnormality diagnosis device according to the present invention is mounted on a host vehicle, and is mounted on the host vehicle and first environment information acquisition means for acquiring first environment information related to the surrounding environment of the host vehicle. The second environment information acquisition means for acquiring the second environment information similar to the first environment data, and the first and second environment information are compared with each other, and the first environment information acquisition means is based on the comparison result. An abnormality diagnosis means for diagnosing an abnormality.

  In the abnormality diagnosis device of the present invention, the first and second environmental information similar to each other are compared, and therefore, in the comparison result, the presence or absence of the surrounding moving object and the fluctuation due to the movement are suppressed, and the influence of the surrounding moving object is reduced. The Therefore, instead of merely diagnosing an abnormality based on the first environment information, an abnormality diagnosis is performed by suitably considering the situation of the surrounding moving object by diagnosing the abnormality of the first environment information acquisition unit based on the comparison result. be able to. Therefore, according to the present invention, it is possible to diagnose an abnormality with high accuracy regardless of the situation of surrounding moving objects.

  The first environment information acquisition unit acquires the first environment information based on the first predetermined point data related to the surrounding environment of the predetermined point, and the second environment information acquisition unit relates to the surrounding environment of the predetermined point and the first predetermined point. It is preferable to acquire the second environment information based on second predetermined point data in which the situation of the surrounding moving object is similar to the point data. In this case, since the first and second environmental information whose conditions of the surrounding moving object are similar to each other are compared, in this comparison result, the presence or absence of the surrounding moving object and the influence due to the movement are further suppressed.

  Here, it is preferable that the second environment information acquisition unit acquires the stationary object data relating only to the stationary object around the predetermined point as the second environment information. Thereby, for example, when the influence of the surrounding moving object in the first predetermined point data is small, the first predetermined point data and the stationary object data are compared with each other, and the abnormality of the first environmental information acquisition unit is accurately diagnosed. The

  In addition, the first environment information acquisition unit specifically acquires the first moving object data related to the moving object around the predetermined point, and the first environment information based on the first predetermined point data and the first moving object data. May get.

  At this time, the first environment information acquisition means acquires data obtained by excluding the data area corresponding to the first moving object data in the first predetermined point data as the first environment information, and the second environment information acquisition means includes: Data obtained by acquiring stationary object data relating only to a stationary object around a predetermined point and second moving object data relating to a moving object around the predetermined point, and excluding a data area corresponding to the second moving object data in the stationary object data. It is preferable to obtain the second environment information. As a result, for example, if the first environment information acquisition unit has an abnormality, the data area is not correctly excluded from the first predetermined point data, so that the comparison results of the first and second environment information deviate from each other. It becomes. Therefore, in this case, based on the comparison result between the first and second environment information, it is possible to accurately diagnose the abnormality of the first environment information acquisition unit.

  In addition, a database is provided on the host vehicle or the outside, and the database performs statistical processing on the past environment information related to the past surrounding environment of the host vehicle or other vehicles and the past environment information associated with the past environment information. It is preferable that the second environment information acquisition unit calls the past environment information associated with the statistical environment information corresponding to the first environment information as the second environment information from the database. In this case, accurate second surrounding environment information can be acquired.

  According to the present invention, it is possible to accurately diagnose an abnormality regardless of the state of a surrounding moving object.

  Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. In the following description, the same or equivalent elements will be denoted by the same reference numerals, and redundant description will be omitted.

  First, a first embodiment of the present invention will be described. FIG. 1 is a schematic configuration diagram showing an abnormality diagnosis apparatus according to the first embodiment of the present invention, and FIG. 2 is a diagram for explaining the abnormality diagnosis apparatus of FIG. As shown in FIG. 1, the abnormality diagnosis apparatus 10 of the present embodiment is mounted on a host vehicle 1 such as an automobile, and includes an ECU (Electronic Control Unit) 11. An environment recognition sensor 12 is connected to the ECU 11.

  The environment recognition sensor 12 is a sensor for acquiring own vehicle environment information (first environment information) that is information related to the surrounding environment of the own vehicle 1, and includes a camera 13, a millimeter wave radar 14, a yaw rate sensor 15, and a GPS (Global Positioning System) The terminal 16 is configured.

  The camera 13 recognizes own vehicle image data around the own vehicle 1. The millimeter wave radar 14 obtains own vehicle moving object data (first moving object data) relating to the situation of the surrounding moving object T (see FIG. 9) that is a moving object around the own vehicle 1. Examples of the peripheral moving object T include pedestrians and other vehicles, and examples of the situation of the peripheral moving object T include the arrangement relationship of the peripheral moving object T. The yaw rate sensor 15 acquires yaw rate data related to the yaw rate of the host vehicle 1. The GPS terminal 16 is a navigation system terminal, and acquires own vehicle position data related to the road position of the own vehicle 1.

  Then, the ECU 11 receives each data acquired by the environment recognition sensor 12 and generates own vehicle environment information based on these data. Further, the ECU 11 is connected to a communication device 17, a host vehicle environment information storage memory 18, a reference information storage memory 19 and a display 20.

  The communication device 17 transmits / receives to / from the other vehicle 2 and the infrastructure 3 shown in FIG. 2 and acquires reference information (second environment information) similar to the own vehicle environment information. Specifically, the communication device 17 connects to the database 4 of the other vehicle 2 and the infrastructure 3 using the mobile communication network, and calls the reference information from the database 4. The database 4 includes the past environment information related to the surrounding environment of the other vehicle 2 when the other vehicle 2 travels in the past, and the statistics obtained by statistically processing the past environment information associated (linked) with the past environment information. Environment information is stored. As the statistical process, various processes can be adopted, and for example, a process of averaging a plurality of similar past environment information can be cited.

  Returning to FIG. 1, the host vehicle environment information storage memory 18 stores the generated host vehicle environment information. The host vehicle environment information storage memory 18 here corresponds to the database 4 for the other vehicle 2, and, similar to the database 4, the host vehicle environment information when the host vehicle 1 has traveled in the past is stored in the past. In addition to storing as environmental information, statistical environmental information associated with the past environmental information and statistically processing the past environmental information is stored. The reference information storage memory 19 stores the called reference information.

  Then, the ECU 11 compares the vehicle environment information and the reference information with each other, diagnoses an abnormality (for example, failure, poor placement or deterioration) of the environment recognition sensor 12 based on the comparison result, and displays the diagnosis result on the display 20. Output above (details will be described later).

  Next, the processing of the abnormality diagnosis apparatus 10 configured as described above will be described with reference to the flowchart shown in FIG.

  In the abnormality diagnosis device 10 of the present embodiment, first, each of the above data is acquired by the environment recognition sensor 12, and the vehicle environment information is generated and acquired by the ECU 11 based on these data (S1). The vehicle environment information here is first predetermined point data related to the surrounding environment of the predetermined point D, which is the current point of the own vehicle 1, and includes own vehicle image data, own vehicle position data, direction data about the vehicle body direction, and It consists of own vehicle moving object data.

  Subsequently, the generated vehicle environment information is stored in the vehicle environment information storage memory 18 and is transmitted (transmitted) to the other vehicle 2 and the infrastructure 3 by the communication device 17 (S2), and a plurality of reference information is called up. (S3).

  Specifically, when the vehicle environment information is transmitted by the communication device 17, statistical environment information similar to the vehicle environment information is selected in the database 4. More specifically, it is data relating to the surrounding environment of the other vehicle 2 at the predetermined point D, and is the second predetermined point data relating to the surrounding environment in which the situation of the surrounding moving object T and the direction of the vehicle body are similar to the own vehicle environment information. Is selected (in other words, statistical environment information that is the same as the vehicle position data of the vehicle environment information and similar to the direction data and the vehicle moving object data is selected). Then, past environment information associated with the selected statistical environment information is transmitted from the other vehicle 2 and the infrastructure 3 to the host vehicle 1 as reference information. The above “similar” means, for example, that there is not much difference between the two in terms of statistics, experience, or sensor performance, and that the difference between the two is smaller than a predetermined value. .

  Subsequently, the ECU 11 averages the plurality of called reference information, and compares and compares the averaged reference information with the vehicle environment information (S4). If the comparison result, that is, the difference between the averaged reference information and the vehicle environment information is within a threshold value (for example, the tolerance value of statistical processing in the statistical environment information), the environment recognition sensor 12 is normal. (S5 → S6), and a message to that effect is displayed on the display 20 (S7). On the other hand, if it is equal to or greater than the threshold value, it is diagnosed that an abnormality has occurred in the environment recognition sensor 12 (S5 → S8), and that effect is displayed on the display 20 (see FIG. 4).

  FIG. 5 is a graph showing an example of host vehicle environment information and reference information. The vehicle environment information F1 and the reference information F2 here relate to the image data of the predetermined point D, and the above-described averaging is performed on the reference data F2. In the figure, the horizontal axis indicates the image position in the image data, and the vertical axis indicates the luminance value. In the example shown in FIG. 5, since the own vehicle environment information F1 and the reference information F2 are largely different from each other at the image position P, it is diagnosed that an abnormality has occurred in the camera 13, and that fact is displayed on the display 20. The Rukoto.

  As described above, in the present embodiment, vehicle environment information and reference information that are similar to each other are compared, that is, information about the surrounding environment in a situation that is similar to each other is compared as vehicle environment information and reference information. Therefore, in the comparison result, the presence or absence of the peripheral moving object T and the fluctuation due to the movement are suppressed, and the influence of the peripheral moving object T is reduced. That is, for example, even if the surrounding moving object T moves, the own vehicle environment information changes, but the change in the difference between the own vehicle environment information and the reference information is suppressed. Therefore, according to the present embodiment, the abnormality of the environment recognition sensor 12 is diagnosed based on the comparison result instead of simply diagnosing the abnormality based on the own vehicle environment information. The abnormality diagnosis can be performed in consideration of the above, and the abnormality can be diagnosed with high accuracy regardless of the situation of the surrounding moving object T.

  In the present embodiment, as described above, the environment recognition sensor 12 acquires the vehicle environment information related to the surrounding environment of the predetermined point D, and the communication device 17 relates to the surrounding environment of the predetermined point D and the vehicle environment. Reference information in which the situation of the surrounding moving object T is similar to the information is acquired. Therefore, since the situation of the surrounding moving object T is similar to each other in the vehicle environment information and the reference information, the influence of the surrounding moving object T can be further suppressed in these comparison results.

  Further, in the present embodiment, as described above, statistical environment information corresponding to this vehicle environment information is selected in the database 4 by transmitting the vehicle environment information to the other vehicle 2 and the infrastructure 3 by the communication device 17. The past environment information associated with the selected statistical environment information is called as reference information. By acquiring reference information in this way, accurate reference information can be acquired.

  In the present embodiment, as described above, since the reference information obtained by averaging a plurality of reference information and the vehicle environment information are compared, the environment recognition sensor is used when a statistically significant difference between these pieces of information is large. Twelve abnormalities will be judged.

  By the way, conventionally, there is a case where such abnormality diagnosis is performed by using an abnormality occurrence database relating to abnormality of the environment recognition sensor 12 provided in advance or based on a time series change of the vehicle environment information. However, in this case, the already failed result is necessary in advance, and a stationary object having high invariance (for example, a building or a utility pole) must be used as a reference for diagnosis. Therefore, when there are not enough stationary objects in the surrounding environment or when the influence of disturbance such as moving objects is large, it is difficult to accurately diagnose the abnormality of the environment recognition sensor 12. For this reason, in the conventional abnormality diagnosis apparatus, a unique response to a reference object in the surrounding environment is required, and the point where abnormality diagnosis is possible may be limited to stable conditions.

  In this respect, in the present embodiment, as described above, the abnormality diagnosis is performed by comparing the own vehicle environment information and the reference information that are similar to each other, and therefore, a highly robust diagnosis can be performed even in the surrounding environment where there is no main stationary object. Therefore, this embodiment can be said to be particularly effective.

  Incidentally, the host vehicle environment information and the reference information are not limited to the present embodiment. For example, in the case of a radar sensor such as the millimeter wave radar 14, the received wave intensity data of the reflected wave with respect to the irradiation position (hereinafter, simply referred to as “reception wave”). (Referred to as “reception intensity data”) may be acquired as the vehicle environment information and the reference information.

  In the above, the environment recognition sensor 12 and the ECU 11 that generates the vehicle environment information constitute the first environment information acquisition means, and the communication device 17 constitutes the second environment information acquisition means, and the abnormality of the environment recognition sensor 12 is diagnosed. The ECU 11 that constitutes the abnormality diagnosis means.

  Next, a second embodiment of the present invention will be described. In the description of the present embodiment, differences from the first embodiment will be mainly described, and overlapping portions will be omitted.

  In the abnormality diagnosis device of the present embodiment, a plurality of pieces of reference information are called by the communication device 17 (S3 in FIG. 6). Here, as shown in FIG. 7, reference image data (second predetermined point data) 6 </ b> A to 6 </ b> B related to the surrounding environment of the predetermined point D is transmitted as the reference information from the other vehicles 2 </ b> A to 2 </ b> B (see FIG. 2). The

  Here, for example, when the reference image data 6A to 6B are overlapped with each other and processed so as to become one image data, the peripheral stationary objects S of these images are the same as each other. While the value becomes higher (darker), the luminance value at the image position of the peripheral moving object T becomes lower (thinner) than that of the peripheral stationary object S.

  Therefore, the ECU 11 integrates the luminance value for each image position in the reference image data 6A to 6B, and extracts an image position area where the integrated value is equal to or less than a certain value as reference movement data (second moving object data). Then, the reference movement data is excluded from the reference image data 6A to 6B, and as shown in FIG. 8A, the stationary object image data (stationary object data) 7 relating only to the peripheral stationary object S at the predetermined point D is acquired. (S21).

  Subsequently, image processing is performed based on the vehicle image data 22 (see FIG. 9A: first predetermined point data) of the vehicle environment information acquired in S1 and the vehicle moving object data. Specifically, as shown in FIG. 9B, in the vehicle image data 22 of the predetermined point D, a region (data region) R1 corresponding to the vehicle movement data related to the surrounding moving object T is masked, and the vehicle Masking data 23 is acquired (S22). Note that the masking here means processing to make the luminance value constant (for example, maximum value / minimum value) in the regions R1 and R2, and means to exclude (erase) the data region of the reference movement data. (Hereinafter the same).

  Further, image processing is performed based on the stationary object image data 7 and the reference moving object data acquired in S21. Specifically, as shown in FIG. 8B, in the stationary object image data 7, the region (data region) R2 corresponding to the reference movement data is masked, and the reference masking data 8 is acquired (S23).

  Thereafter, the own vehicle masking data 23 and the reference masking data 8 are compared (S4). If these differences are within the threshold value, the vehicle is diagnosed as normal (S6). It is diagnosed that an abnormality has occurred (S8).

  As described above, in the present embodiment, when the environment recognition sensor 12 is normal, the vehicle image data 22 and the region R1 can be accurately identified, and therefore, the accurate vehicle masking data 23 can be acquired. The difference from the data 8 and 23 is within the threshold value. On the other hand, if there is an abnormality in the environment recognition sensor 12, masking data 8 and 23 are deviated from each other because the vehicle image data 22 cannot be correctly masked. Therefore, also in the present embodiment, it is possible to diagnose an abnormality of the environment recognition sensor 12 with high accuracy.

  In the present embodiment, when the area ratio (influence) of the surrounding moving object T in the vehicle image data 22 is small, the masking data 8 and 23 are not generated, and the vehicle image data 22 is compared with the stationary object image data 7. Thus, the abnormality of the environment recognition sensor 12 can be diagnosed with high accuracy.

  Incidentally, in the present embodiment, the own vehicle masking data 23 and the reference masking data 8 are acquired as the first and second environment information, but the present invention is not limited to this. For example, the present invention relates to a radar sensor such as the millimeter wave radar 14. Then, you may acquire 1st and 2nd environmental information as follows. That is, by erasing the data area at the position where the peripheral moving object T is present in the received intensity data, it is assumed that the received intensity related to the peripheral moving object T is zero, as corresponding to the masking data 8 and 23. May be acquired as the first and second environment information. In this case, if the erasure cannot be accurately processed due to an abnormality of the radar sensor, the difference value between the received intensity data acquired as the first and second environment information becomes large.

  The preferred embodiment of the present invention has been described above, but the present invention is not limited to the above embodiment.

  For example, in the above embodiment, reference information is acquired from the external database 4, but reference information may be acquired based on past environment information in the host vehicle environment information storage memory 18. Moreover, in the said embodiment, although reference information was acquired from both the other vehicle 2 and the infrastructure 3, you may acquire only from any one of these, and even if reference information is acquired from one other vehicle 2 Good.

  Moreover, although the said embodiment is provided with the communication apparatus 17, it may replace with this and may provide what uses road-to-vehicle communication and vehicle-to-vehicle communication. In the above embodiment, the environment recognition sensor 12 includes the camera 13, the millimeter wave radar 14, the yaw rate sensor 15, and the GPS terminal 16. Etc. may be included.

  In the above-described embodiment, the display 20 is used to display the fact on the display 20, but an alarm device that outputs an alarm may be used as long as the driver can be notified of the fact.

1 is a schematic configuration diagram showing an abnormality diagnosis apparatus according to a first embodiment of the present invention. It is a figure for demonstrating the abnormality diagnosis apparatus of FIG. It is a flowchart which shows the process of the abnormality diagnosis apparatus of FIG. It is a figure which shows the display of the abnormality diagnosis apparatus of FIG. It is a graph which shows an example of the own vehicle environment information and reference information. It is a flowchart which shows the process of the abnormality diagnosis apparatus which concerns on 2nd Embodiment of this invention. It is a figure which shows reference image data. (A) is a figure which shows stationary object image data, (b) is a figure which shows reference masking data. (A) is a figure which shows own vehicle image data, (b) is a figure which shows own vehicle masking data.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 1 ... Own vehicle, 2, 2A-2C ... Other vehicles, 4 ... Database, 6A-6B ... Reference image data (2nd predetermined point data), 7 ... Still object image data (stationary object data), 10 ... Abnormality diagnosis apparatus , 11 ... ECU (first environment information acquisition means, abnormality diagnosis means), 12 ... environment recognition sensor (first environment information acquisition means), 17 ... communication device (second environment information acquisition means), 22 ... own vehicle image data (First predetermined point data), D... Predetermined point, R1, R2... Region (data region), T.

Claims (3)

A first environment information acquisition means mounted on the host vehicle for acquiring first environment information relating to the surrounding environment of the host vehicle;
Mounted on the vehicle, and the second environmental information acquisition means for acquiring a second environmental information similar to the first environmental information,
An abnormality diagnosing means for comparing the first and second environment information with each other and diagnosing an abnormality of the first environment information acquiring means based on the comparison result;
The first environment information acquisition means acquires the first environment information based on first predetermined point data related to the surrounding environment of the predetermined point,
The second environment information acquisition means acquires the second environment information based on second predetermined point data relating to the surrounding environment of the predetermined point and having a situation of a surrounding moving object similar to the first predetermined point data. And obtaining stationary object data relating only to stationary objects around the predetermined point as the second environment information,
There is a database on your vehicle or outside,
The database stores past environment information related to the past surrounding environment in the host vehicle or other vehicles, and statistical environment information obtained by statistically processing the past environment information associated with the past environment information,
The abnormality diagnosis apparatus, wherein the second environment information acquisition unit calls the past environment information associated with the statistical environment information corresponding to the first environment information from the database as the second environment information . The first environment information acquisition unit acquires first moving object data related to moving objects around the predetermined point, and acquires the first environment information based on the first predetermined point data and the first moving object data. The abnormality diagnosis device according to claim 1, wherein: The first environmental information acquisition means includes
In the first predetermined point data, data obtained by excluding a data area corresponding to the first moving object data is acquired as the first environment information,
The second environment information acquisition means includes
Obtaining stationary object data relating only to stationary objects around the predetermined point and second moving object data relating to moving objects around the predetermined point;
Abnormality diagnosis apparatus according to claim 2, wherein the acquiring the data obtained by excluding the data region corresponding to the second moving object data in said stationary object data as the second environmental information.

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