Yaw rate sensor abnormality determination device

Abstract

The present invention addresses the problem of providing a highly practical yaw rate abnormality determination device. Provided is a yaw rate sensor abnormality determination device that is mounted on a vehicle and that determines an abnormality of a yaw rate sensor provided in the vehicle. A determination prohibition unit is provided in addition to an abnormality determination unit for determining an abnormality detected by a yaw rate sensor by comparing a detected yaw rate detected by a yaw rate sensor with an estimated yaw rate estimated on the basis of the behavior or operation of a vehicle. And a determination prohibition unit that prohibits the determination when it is determined that the abnormality determination by the abnormality determination unit is inappropriate on the basis of an image captured by a camera in front of the vehicle.

Description

Technical Field

[0001] This invention relates to a yaw rate sensor malfunction determination device for determining malfunctions of a yaw rate sensor mounted on a vehicle. Background Technology

[0002] Regarding vehicle yaw rate, for example, vehicle stabilization control (VSC) is used to ensure proper vehicle turning, and rear-wheel steering is controlled in four-wheel steering vehicles. Therefore, it is desirable to properly determine the abnormality of the yaw rate sensor that detects the yaw rate. In this regard, for example, there exists a technique described in the following patent document. In this technique, the lower of the yaw rate estimated based on vehicle speed and the vehicle's minimum turning radius and the yaw rate estimated based on the lateral acceleration generated in the vehicle is determined as a threshold yaw rate. If the yaw rate detected by the yaw rate sensor exceeds this threshold yaw rate, the yaw rate sensor is determined to be abnormal.

[0003] Patent Document 1: Japanese Patent Application Publication No. 11-83895 Summary of the Invention

[0004] According to the technology described in the aforementioned patent documents, for example, when a vehicle is turning on a surface with extremely low μ, such as ice, the yaw rate estimated based on the aforementioned lateral acceleration is extremely low, and therefore this yaw rate is always considered the threshold yaw rate. As a result, when performing a four-wheel slip turn on such a surface, even if the yaw rate sensor is not malfunctioning, it will be judged as malfunctioning. This problem exists in the technology described in the aforementioned patent documents. If the yaw rate sensor malfunction determination can be performed appropriately, the practicality of the yaw rate sensor malfunction determination device will be improved. The present invention was made in view of this situation, and its objective is to provide a highly practical yaw rate malfunction determination device.

[0005] To address the aforementioned issues, the yaw rate sensor anomaly determination device of the present invention is mounted on a vehicle and determines anomalies in the yaw rate sensor of the vehicle. The yaw rate sensor anomaly determination device comprises:

[0006] An anomaly determination unit determines an anomaly based on the yaw rate sensor's detection by comparing the detected yaw rate with an estimated yaw rate estimated based on the vehicle's behavior or operation; and

[0007] The determination prohibition unit, based on the image captured by the camera in front of the vehicle, prohibits the determination if it determines that the abnormality determination based on the abnormality determination unit is inappropriate.

[0008] Invention Effects

[0009] According to the yaw rate sensor anomaly determination device of the present invention (hereinafter, sometimes simply referred to as "this anomaly determination device"), the above-mentioned determination prohibition unit prevents the anomaly determination of the yaw rate sensor based on the anomaly determination unit when the vehicle turns on a road surface with extremely small μ, such as ice. Therefore, false determinations can be avoided, that is, the yaw rate sensor is not abnormal, but is determined to be abnormal.

[0010] Invention methods

[0011] The "estimated yaw rate" used in the "anomaly determination unit" of this anomaly determination device is not particularly limited as long as it is estimated based on the vehicle's behavior or operation. For example, it can use various estimated yaw rates, such as operation-dependent estimated yaw rate based on the amount of operation of operating components such as the steering wheel and vehicle speed, estimated yaw rate based on lateral acceleration generated in the vehicle, and estimated yaw rate based on wheel speed difference based on the circumferential speed (which can be rotational speed) of the left and right wheels. The estimated yaw rate used is not limited to only one, but can also be two or more.

[0012] Specifically, anomaly detection can be performed as follows: As an estimated yaw rate, the aforementioned estimated yaw rate based on lateral acceleration and the aforementioned estimated yaw rate based on wheel speed difference are used. If the difference between the detected yaw rate and any one of these estimated yaw rates based on lateral acceleration and wheel speed difference is greater than a first preset difference, and the difference between these estimated yaw rates based on lateral acceleration and wheel speed difference is less than a second preset difference, an anomaly can be determined based on the yaw rate sensor detection. In short, it can be set as follows: if two estimated yaw rates are approximately the same, and there is a certain degree of difference between either of them and the detected yaw rate, an anomaly can be determined based on the yaw rate sensor detection. In this way, anomalies in the yaw rate sensor detection can be appropriately determined.

[0013] When repeatedly acquiring camera-based images at set time intervals (e.g., several milliseconds to tens of milliseconds), the judgment made by the "determination prohibition unit" of this anomaly determination device can be performed, for example, as follows. Specifically, for example, during vehicle turning, comparing the previous image with the current image, if the number of pixels whose pixel values ​​have changed (hereinafter, sometimes referred to as "value-changed pixels") is less than a set number, the determination of whether there is an anomaly detected by the yaw rate sensor is prohibited. For example, when the vehicle is traveling on a normal road surface, the pixels used to mark driving lanes, tracks, etc., move, so the number of value-changed pixels becomes quite large. On the other hand, when traveling on ice, compacted snowfields, etc. (hereinafter, sometimes referred to as "ice, etc."), such markings do not exist, and the number of value-changed pixels becomes small. The above method utilizes this phenomenon. In addition, the "pixel value" can be any value of brightness, for example, the value obtained by graying each pixel constituting the image, that is, a gray value divided into a predetermined stage (e.g., 256 stages).

[0014] When using the above method, the prohibition section preferably excludes portions of the image that are not road surfaces from the camera image, and determines whether the detection based on the yaw rate sensor is inappropriate. Simply put, the upper part of the image contains buildings, trees, distant scenery, clouds in the sky, etc., which constitute noise in the above determination. Specifically, these elements constantly change their positions in the left-right direction within the image during vehicle turning, resulting in a considerable number of pixels with varying values ​​in the image containing them. Considering this, for example, the lower half of the image can be used.

[0015] Furthermore, when using the above method, even on ice or snowfields, there may be slight changes in the road surface. Therefore, to eliminate the influence caused by these changes, it is preferable to change the "set number" of pixels whose values ​​change based on the yaw rate. Specifically, for example, the set number is increased when the yaw rate is high, and kept small when the yaw rate is low. Additionally, the yaw rate used here can be the detected yaw rate or any estimated yaw rate mentioned above, but it is preferable that if the yaw rate used is an outlier, the determination and prohibition unit also changes the set number to a value that allows for appropriate judgment. Attached Figure Description

[0016] Figure 1 This is a schematic diagram illustrating the structure of a vehicle equipped with the yaw rate sensor anomaly detection device of the embodiment.

[0017] Figure 2 This is a conceptual diagram used to illustrate the appropriateness of anomaly detection based on cameras.

[0018] Figure 3 This is a conceptual diagram used to illustrate the impact of road surface changes on the appropriateness of camera-based anomaly detection.

[0019] Figure 4 This is a flowchart of the anomaly determination allow / disable determination process executed in the yaw rate sensor anomaly determination device of the embodiment.

[0020] Figure 5 This is a flowchart of the anomaly determination process executed in the yaw rate sensor anomaly determination device of the embodiment.

[0021] Figure 6 This is a flowchart of an exception handling subroutine that forms part of the exception handling procedure. Detailed Implementation

[0022] Hereinafter, as a means of implementing the present invention, a yaw rate sensor anomaly determination device as an embodiment of the present invention will be described in detail with reference to the accompanying drawings. Furthermore, in addition to the embodiments described below, the present invention can be implemented in various ways with various modifications and improvements based on the knowledge of those skilled in the art, starting from the manner described in the section on "Manifestations of the Invention".

[0023] [A] The structure of a vehicle equipped with a yaw rate sensor anomaly detection device

[0024] like Figure 1 As schematically shown, a vehicle equipped with the yaw rate sensor anomaly detection device (hereinafter, sometimes simply referred to as "this yaw rate sensor anomaly detection device" or "this anomaly detection device") 10 according to an embodiment of the present invention is mounted on a vehicle having two front wheels 12f and two rear wheels 12r. In this vehicle, the two front wheels 12f serve as steering wheels and have a steering device 14 for steering these front wheels 12f. The steering device 14 is a so-called electric power steering device, which consists of a steering wheel 16, a steering column 18, a steering actuator 20, etc., as operating components. In the following description, the front wheels 12f and the rear wheels 12r are sometimes collectively referred to as wheels 12 without needing to distinguish between them.

[0025] This vehicle is a four-wheel drive vehicle. Although not shown in the diagram, it is equipped with a drive unit for driving each wheel 12. Furthermore, each wheel 12 is provided with a braking device 22 as an electric braking device, which is controlled by a brake electronic control unit (hereinafter, sometimes referred to as the "brake ECU") 24. Although it will be described in detail later, this vehicle also has a vehicle stability control (hereinafter, sometimes referred to as "VSC control") system, and therefore a VSC controller 26 is also provided.

[0026] In this vehicle, various sensors are provided, with the yaw rate sensor 30 being the object of anomaly determination by the anomaly determination device 10. Specifically, there is a steering angle sensor 32 for detecting the steering angle δ, which is the amount of steering wheel 16 operation; a lateral acceleration sensor 34 for detecting the lateral acceleration Gy generated in the vehicle; and a wheel speed sensor 36 for detecting the wheel speed (actually rotational speed, but hereinafter treated as circumferential speed) vw of each wheel 12. Furthermore, a camera 38 for monitoring the front is also provided in this vehicle. A CAN (controllable area network or car area network) 40 is provided in this vehicle, and these sensors 30, 32, 34, 36, the camera 38, the anomaly determination device 10, the steering system 14, the brake ECU 24, and the VSC controller 26 are all connected to the CAN 40.

[0027] Here, a brief explanation of the VSC control performed by the VSC controller 26 is provided. VSC control is a general control method; simply put, it is a control used by the braking device 22 to correct the turning when the vehicle does not turn along the proper turning line during a turn. Specifically, the VSC controller 26 determines the appropriate yaw rate γ (a type of "operation-dependent estimated yaw rate") that the vehicle should achieve during a turn, based on the vehicle speed v calculated from the wheel speeds vw of each wheel 12 and the steering angle δ of the steering wheel 16. Based on the difference between this appropriate yaw rate γr and the yaw rate γ detected by the yaw rate sensor 30, i.e., the detected yaw rate γd, the braking device 22 generates braking force. More specifically, based on this difference, the VSC controller 26 applies braking force to the outer turning wheel 12 when the detected yaw rate γd is high, and sends a command to the braking ECU 24 to apply braking force to the inner turning wheel 12 when the detected yaw rate γd is low. VSC control is an example of a method that utilizes the yaw rate γd detected by the yaw rate sensor 30, but the yaw rate γd is an important parameter for various vehicle controls.

[0028] As explained above, the yaw rate γd should be properly detected. This anomaly determination device 10 determines an anomaly in the yaw rate sensor 30; in other words, it determines an anomaly in the detection of the yaw rate γd based on the yaw rate sensor 30. This anomaly determination device 10 is primarily composed of a computer. Although it will be described in detail later, based on the functions of this anomaly determination device 10, it has two functional units: an anomaly determination unit 50 and a determination prohibition unit 52.

[0029] [B] Handling of yaw rate sensor malfunctions

[0030] The process for determining whether the yaw rate sensor 30 is malfunctioning, that is, determining whether the detection of the yaw rate γd based on the yaw rate sensor 30 is malfunctioning, is performed by the aforementioned malfunction determination unit 50. If this process is referred to as malfunction determination processing, simply put, this malfunction determination processing is performed by comparing the detected yaw rate γd with an estimated yaw rate estimated based on the vehicle's behavior or operation. The malfunction determination processing will be described in detail below.

[0031] In the anomaly determination process based on this anomaly determination device 10, two yaw rates are used to estimate the yaw rate: an estimated yaw rate γg based on the lateral acceleration generated in the vehicle and an estimated yaw rate γv based on the difference in wheel speeds vw between the left and right wheels 12. The anomaly determination unit 50 estimates the estimated yaw rate γg based on the lateral acceleration Gy detected by the lateral acceleration sensor 34 and the vehicle speed v determined by the wheel speeds vw of the four wheels 12, according to the following formula:

[0032] γg=Gy / v

[0033] The wheel speed vwr is the right wheel speed vw of the right wheel 12, the wheel speed vwl is the left wheel speed vw of the left wheel 12, and the wheelbase Tr is the distance between the left and right wheels 12 (reference). Figure 1 The estimated yaw rate γv based on the wheel speed difference is estimated according to the following formula.

[0034] γv = (vwr - vwl) / Tr

[0035] Incidentally, the right wheel speed vwr, left wheel speed vwl, and wheel track Tr can be calculated by averaging the front wheel speed 12f and the rear wheel speed 12r.

[0036] The anomaly determination unit 50 compares each of the detected yaw rate γd with the estimated yaw rate γg based on lateral acceleration and the estimated yaw rate γv based on wheel speed difference, and determines whether their difference exceeds a first yaw rate threshold difference Δγa, which is a first set difference, according to the following formula. Incidentally, the first yaw rate threshold difference Δγa only needs to be set to a value that can clearly determine that an anomaly has occurred in the yaw rate sensor 30.

[0037] |γd-γg|>Δγa

[0038] |γd-γv|>Δγa

[0039] On the other hand, the anomaly determination unit 50 determines, according to the following formula, whether the difference between the estimated yaw rate γg based on lateral acceleration and the estimated yaw rate γv based on wheel speed difference is less than a second yaw rate threshold difference Δγb, which is a second set difference. Incidentally, the second yaw rate threshold difference Δγb only needs to be set so that it can be regarded as the estimated yaw rate γg based on lateral acceleration and the estimated yaw rate γv based on wheel speed difference being substantially the same.

[0040] |γg-γv|<Δγb

[0041] The anomaly determination unit 50 determines that the detection of yaw rate γd by the yaw rate sensor 30 is abnormal if the estimated yaw rate γg based on lateral acceleration and the estimated yaw rate γv based on wheel speed difference are substantially the same (without significant difference) and the detected yaw rate γd is significantly different from at least one of the estimated yaw rates γg based on lateral acceleration and γv based on wheel speed difference for a certain period of time, i.e., exceeding a set time Ct0. Incidentally, the set time Ct0 only needs to be set to approximately a few seconds to tens of seconds.

[0042] [C] is used to determine whether to disable exception handling.

[0043] As described above, anomalies in the yaw rate sensor 30 are detected. However, even if no anomaly is detected in the yaw rate sensor 30, the above conditions may still be met and an anomaly may be determined. That is, depending on the vehicle's position and the road surface it is traveling on, an anomaly may be determined even if no anomaly is detected. In detail, for example, when the vehicle is traveling on a surface with a relatively large surface area μ, such as a general road or a racetrack, the determination based on the above conditions is appropriate. On the other hand, when the vehicle is turning on a surface with a relatively small surface area μ, such as ice, compacted snow, or dry sand, especially when the vehicle is turning on a surface with an extremely small surface area μ, the above conditions will still be met even if no anomaly is detected in the yaw rate sensor 30, thus determining that the yaw rate sensor 30 is abnormal.

[0044] In view of the above, if the yaw rate sensor 30 is determined to be abnormal under inappropriate conditions, that is, if the vehicle is traveling in a position where the abnormality determination is inappropriate, the abnormality determination is prohibited. The process of prohibiting abnormality determination, in other words, the process of determining whether to allow or prohibit the determination of abnormality based on the abnormality determination unit 50 (hereinafter, sometimes referred to as "abnormality determination allow / prohibit determination process") is performed by the determination prohibition unit 52. Hereinafter, this abnormality determination allow / prohibit determination process will be described in detail with reference to the conceptual diagram.

[0045] Figure 2(a) An image captured by a camera 38 monitoring the front of the vehicle is schematically shown. This image is acquired, for example, while the vehicle is driving on a track. The image is repeatedly acquired at set time intervals (e.g., several milliseconds to tens of milliseconds). The determination prohibition unit 52 determines whether to allow or prohibit the determination of an anomaly based on the anomaly determination unit 50 by comparing the currently acquired image (hereinafter, sometimes referred to as "current image") with the previously acquired image (hereinafter, sometimes referred to as "previous image"). In addition, this determination is made by estimating the state of the ground (road surface) being driven on, so simply put, the part above the horizon HL in the image, which is not the road surface, becomes the so-called noise in this determination. Therefore, in the anomaly determination allow / prohibit determination processing based on the determination prohibition unit 52, this part is excluded from the determination object by cropping.

[0046] The determination prohibition unit 52 first converts the current image to grayscale. Specifically, it converts the brightness value of each pixel in the current image into a grayscale value (e.g., a grayscale value of 256) and stores this value as the pixel value K of each pixel. For all pixels, it compares the current pixel value Kc, which is the pixel value K of the current image, with the previous pixel value Kp, which is the pixel value K of the previously stored previous image, and determines the pixel value difference D of each pixel according to the following formula.

[0047] |Kc-Kp|=D

[0048] Furthermore, the determination prohibition unit 52 determines the binary value B of 0 and 1 for each pixel based on the pixel value difference D, as shown below, using the difference threshold Dth.

[0049] D>Dth→B=1

[0050] D≤Dth→B=0

[0051] In simple terms, by comparing the previous image with the current image, the binarized value B of pixels whose pixel value K has changed to a certain extent is set to 1, and the binarized value B of pixels whose pixel value K has not changed much is set to 0. The binarized image becomes as shown in the figure. Figure 2 The image shown in (b) shows pixels corresponding to the lane markings DL on both sides, which are represented in white in the image with a binarized value B set to 1.

[0052] In contrast, Figure 2 (c) is an image captured by camera 38, for example, when a vehicle is driving on ice. On ice, there are no markings (DL, etc.), and the image is captured as a flat surface (without visual differences overall). Therefore, as... Figure 2As shown in (d), the binarization value B of most pixels in the binarized image is set to 0. The road surface for which this binarized image was obtained is estimated to be a road surface with a relatively small surface μ. Therefore, when driving on such a road surface, it is not desirable to perform the aforementioned anomaly determination on the yaw rate sensor 30. Therefore, the determination prohibition unit 52 determines whether to allow or prohibit anomaly determination through the following process.

[0053] The determination prohibition unit 52 adds the binarized values ​​B of each pixel to calculate the total binarized value ΣB of the entire binarized image. Furthermore, if the total binarized value ΣB exceeds the determination threshold ΣBth, anomaly determination is allowed, assuming the vehicle is traveling at a location (road surface) with a low probability of misjudgment. If the total binarized value ΣB is below the determination threshold ΣBth, anomaly determination is prohibited, assuming the vehicle is traveling at a location (road surface) with a high probability of misjudgment. In short, if the number of pixels whose pixel values ​​have changed between the previous image and the current image (i.e., the number of pixels with changed values) is less than a set number, the determination of whether there is an anomaly detected by the yaw rate sensor 30 is prohibited.

[0054] However, even when driving on ice, it's possible to determine that the vehicle is in a location with a low probability of misjudgment. Although in the diagram, such as... Figure 3 As shown in (a), when there are small variations (bumps, undulations, etc.) in the UE on the road surface, during a turn with a low yaw rate γ, as Figure 3 As shown in (b), the binarized image did not detect this change in the UE, but during rotations with a high yaw rate γ, such as Figure 3 As shown in (c), the UE is detected to have this change. Therefore, the determination prohibition unit 52 sets a determination threshold ΣBth based on the yaw rate γ. Specifically, as Figure 3 As shown in the graph (d), the higher the yaw rate γ, the larger the judgment threshold ΣBth should be set. Alternatively, the judgment threshold ΣBth can be set to a fixed value independent of the yaw rate γ, rather than based on γ. In this case, the yaw rate γ used can be the detected yaw rate γd, or any of the estimated yaw rates described above: an appropriate yaw rate γr, an estimated yaw rate γv based on wheel speed difference, or an estimated yaw rate γg based on lateral acceleration. Even if the used yaw rate γ becomes an outlier, it is preferable to set the judgment threshold ΣBth to prevent false positives in anomaly detection.

[0055] [D] Processing flow based on anomaly detection device

[0056] The aforementioned determination prohibition unit 52 and anomaly determination unit 50 are executed in this anomaly determination device 10 by performing actions respectively in... Figure 4 , Figure 5The flowchart illustrates the functionalities implemented by the exception handling / enabling procedure and the exception handling process, respectively. Below, the flowchart will briefly explain the respective processes of the exception handling / enabling procedure and the exception handling process described above. Incidentally, these procedures are executed repeatedly in parallel at short time intervals (several milliseconds to tens of milliseconds).

[0057] i) Anomaly detection: Allow / disallow judgment processing

[0058] In the process of allowing / disallowing anomaly detection, firstly, in step 1 (hereinafter sometimes simply referred to as "S1," and other steps are the same), an image of the front of the vehicle captured by camera 38 is acquired. In the next step, S2, the portion above the horizon in the image is cropped out. In S3, the image remaining after cropping is converted to grayscale, that is, the pixel values ​​of each pixel are grayscaled, and this image is stored as the current image.

[0059] In the next step, S4, the current image is compared with the previous image. Specifically, as explained earlier, for each pixel, the absolute value obtained by subtracting the previous pixel value Kp (which was the pixel value of the previous image) from the current pixel value Kc (which is the pixel value of the current image) is determined as the pixel value difference D. After determining the pixel value difference D, in S5, the current image, which has been grayscaled, is used as the previous image. That is, the previous image is updated.

[0060] In the next step, S6, the binarization aggregate value ΣB is reset to 0. In the next step, S7, the pixel value difference D of a single pixel is compared with the difference threshold Dth. If the pixel value difference D is greater than the difference threshold Dth, in S8, the binarization value B of that pixel is set to 1; if the pixel value difference D is less than the difference threshold Dth, in S9, the binarization value B of that pixel is set to 0. Furthermore, in S10, the binarization value B of that pixel is added to the binarization aggregate value ΣB. Based on the determination in S11, the processing of S7 to S10 is repeated until all pixels have been processed.

[0061] In the next step, S12, as explained above, the yaw rate γ is obtained. In S13, refer to... Figure 3 The mapping shown in (d) uses the yaw rate γ to set the judgment threshold ΣBth.

[0062] Furthermore, in S14, the binarized total value ΣB is compared with the judgment threshold ΣBth. If the binarized total value ΣB is greater than the judgment threshold ΣBth, then in S15, an anomaly determination of the yaw rate sensor 30 is allowed. If the binarized total value ΣB is below the judgment threshold ΣBth, the anomaly determination is deemed inappropriate, and in S16, anomaly determination of the yaw rate sensor 30 is prohibited. After S15 or S16, one execution of this anomaly determination allow / prohibit judgment processing procedure ends.

[0063] Alternatively, as explained above, the S12 and S13 processes can be omitted, and a fixed judgment threshold ΣBth that is independent of the yaw rate γ can be used.

[0064] ii) Exception detection and handling

[0065] In the exception handling procedure, firstly, it is determined whether the preconditions for performing exception handling are met. Specifically, in S21, it is determined whether VSC control is allowed. If VSC control is not allowed, in S22, it is determined whether exception handling is prohibited through the aforementioned exception handling permission / prohibition process. If VSC control is allowed, exception handling is allowed. Furthermore, even if VSC control is allowed, exception handling is allowed if the exception handling permission / prohibition process does not prohibit exception handling. Conversely, exception handling is prohibited if the exception handling permission / prohibition process prohibits exception handling.

[0066] In the processing according to this procedure, to determine whether the preconditions for performing the anomaly determination process are met, a determination is made regarding the permissible vehicle speed vj. If the preconditions are met, in S23, the permissible vehicle speed vj is set to a low vehicle speed vjl (e.g., 10-20 km / hr). If the preconditions are not met, in S24, the permissible vehicle speed vj is set to a high vehicle speed vjh. The high vehicle speed vjh is set to a vehicle speed v that is normally unattainable, for example, 400 km / hr. Furthermore, in S25, it is determined whether the vehicle speed v, based on the wheel speed vw detected by the wheel speed sensor 36, exceeds the permissible vehicle speed vj. If the vehicle speed v exceeds the permissible vehicle speed vj, the anomaly determination of the yaw rate sensor 30 is allowed, and in S26, the process is executed. Figure 6 The flowchart shows the exception handling subroutine. If the vehicle speed v does not exceed the allowed judgment speed vj, exception handling is not allowed. In S27, the time counter Ct, described later, is reset.

[0067] Furthermore, when multiple modes such as normal mode and motion mode are set in the VSC control, for example, as shown in parentheses in S21, exception handling can be enabled only in normal mode. Also, in the processing according to this procedure, enabling VSC control is a prerequisite for exception handling, but it is also possible not to make enabling VSC control a prerequisite for exception handling. That is, the processing in S21 can be omitted. Additionally, it is also possible to omit the vehicle speed vj used for determining permission, and directly execute the exception handling subroutine in S26 if the prerequisite is met, and directly execute the processing in S27 if the prerequisite is not met.

[0068] In accordance with Figure 6 In the exception handling subroutine shown in the flowchart, firstly, in S31, the detected yaw rate γd detected by the yaw rate sensor 30 is obtained. Then, in S32 and S33, the estimated yaw rate γv based on wheel speed difference and the estimated yaw rate γg based on lateral acceleration are calculated respectively.

[0069] In the next step S34, it is determined whether at least one of the absolute value of the difference between the detected yaw rate γd and the estimated yaw rate γv based on the wheel speed difference and the absolute value of the difference between the detected yaw rate γd and the estimated yaw rate γg based on the lateral acceleration exceeds the first yaw rate threshold difference Δγa. In S35, it is determined whether the absolute value of the difference between the estimated yaw rate γv based on the wheel speed difference and the estimated yaw rate γg based on the lateral acceleration is less than the second yaw rate threshold difference Δγb. If at least one of the absolute values ​​of the difference between the detected yaw rate γd and the estimated yaw rate γv based on wheel speed difference and the absolute value of the difference between the detected yaw rate γd and the estimated yaw rate γg based on lateral acceleration exceeds the first yaw rate threshold difference Δγa, and the absolute value of the difference between the estimated yaw rate γv based on wheel speed difference and the estimated yaw rate γg based on lateral acceleration is less than the second yaw rate threshold difference Δγb, the state presumed to be abnormal for the yaw rate sensor 30 is identified as a sensor abnormality presumed state. In order to confirm the duration of this state, in S36, the time counter Ct counts with a count value ΔCt equivalent to the execution interval of the program.

[0070] On the other hand, if the absolute value of the difference between the detected yaw rate γd and the estimated yaw rate γv based on the wheel speed difference and the absolute value of the difference between the detected yaw rate γd and the estimated yaw rate γg based on the lateral acceleration do not exceed the first yaw rate threshold difference Δγa, or if the absolute value of the difference between the estimated yaw rate γv based on the wheel speed difference and the estimated yaw rate γg based on the lateral acceleration is greater than or equal to the second yaw rate threshold difference Δγb, in S37, the time counter Ct is reset, and the processing of this subroutine ends.

[0071] In step S38, if it is determined that the time counted by the time counter Ct exceeds the set time Ct0, then in step S39, it is determined that the yaw rate sensor 30 is malfunctioning, that is, the detected yaw rate γd detected by the yaw rate sensor 30 is abnormal. If the time counted by the time counter Ct does not exceed the set time Ct0, it is not determined that the yaw rate sensor 30 is malfunctioning, and the processing of this subroutine ends.

[0072] Symbol Explanation

[0073] 10-Yaw rate sensor anomaly determination device, 30-Yaw rate sensor, 32-Steering angle sensor, 34-Lateral acceleration sensor, 36-Wheel speed sensor, 38-Camera, 50-Anomaly determination unit, 52-Determination prohibition unit, Gy-Lateral acceleration, γ-Yaw rate, γd-Detected yaw rate, γv-Estimated yaw rate based on wheel speed difference, γg-Estimated yaw rate based on lateral acceleration, Δγa-First yaw rate threshold difference [first set difference], Δγb-Second yaw rate threshold difference [second set difference], vw-Wheel speed, v-Vehicle speed, HL-Horizon, DL-Marking, UE-Road surface change, K-Pixel value, Kc-Current pixel value, Kp-Previous pixel value, D-Pixel value difference, Dth-Difference threshold, B-Binarized value, ΣB-Binarized total value, ΣBth-Determination threshold.

Claims

1. A yaw rate sensor anomaly determination device, mounted on a vehicle, for determining anomalies in the yaw rate sensor of the vehicle, characterized in that the yaw rate sensor anomaly determination device comprises: An anomaly determination unit determines an anomaly based on the yaw rate sensor's detection by comparing the detected yaw rate with an estimated yaw rate estimated based on the vehicle's behavior or operation; and The determination prohibition unit, based on the image captured by the camera in front of the vehicle, prohibits the determination if it determines that the abnormality determination based on the abnormality determination unit is inappropriate.

2. The yaw rate sensor anomaly determination device according to claim 1, characterized in that, The images from the camera are repeatedly acquired at set time intervals. The determination prohibition unit is configured to prohibit the determination of the anomaly if the number of pixels whose pixel values ​​have changed when comparing the previous image with the current image is less than a set number.

3. The yaw rate sensor anomaly determination device according to claim 2, characterized in that, The determination and prohibition unit is configured to change the set quantity according to the sway rate.

4. The yaw rate sensor anomaly determination device according to claim 1, characterized in that, The determination prohibition unit is configured to exclude parts of the image from the camera that are not the road surface, and determine whether the determination of the anomaly is inappropriate.

5. The yaw rate sensor anomaly determination device according to claim 1, characterized in that, The anomaly determination unit uses an estimated yaw rate based on lateral acceleration generated in the vehicle and an estimated yaw rate based on wheel speed difference based on the difference in circumferential speed between the left and right wheels as the estimated yaw rate. It is configured such that when the difference between the detected yaw rate and any one of these estimated yaw rates based on lateral acceleration and wheel speed difference is greater than a first set difference and the difference between these estimated yaw rates based on lateral acceleration and wheel speed difference is less than a second set difference, it determines that there is a detection anomaly based on the yaw rate sensor.

Images