JP5425713B2 - Yaw rate detector - Google Patents

Description

  The present invention relates to a yaw rate detection device.

  Conventionally, in order to correct an offset value generated in the output value of the yaw rate sensor due to a temperature change or the like while the vehicle is running, the wheel speed yaw rate is calculated from the wheel speed difference between the left and right wheels based on the wheel diameter ratio of the left and right wheels. An apparatus that calibrates an output value of a yaw rate sensor based on a wheel speed yaw rate is known (see, for example, Patent Document 1).

Japanese Patent Laid-Open No. 11-94874

By the way, in the apparatus according to the above prior art, the calculation of the wheel diameter ratio of the left and right wheels is executed only within a predetermined time at the start of traveling and during straight traveling. However, such a traveling condition may not always be satisfied, and there is a possibility that the yaw rate sensor cannot be calibrated once from the start of traveling.
In addition, when the vehicle traveling path is inclined, the output value of the yaw rate sensor may be a value other than zero even during straight traveling, and the wheel speed yaw rate based on the wheel diameter ratio of the left and right wheels There is a problem that it is difficult to improve the calculation accuracy.

  The present invention has been made in view of the above circumstances, and an object of the present invention is to provide a yaw rate detection device capable of appropriately calibrating the detection value of the yaw rate regardless of the traveling state of the vehicle.

  In order to solve the above problems and achieve the object, the yaw rate detection device according to the first aspect of the present invention detects a yaw rate of the host vehicle and outputs a detection value (for example, in the embodiment). The yaw rate sensor 11), position detecting means for detecting the position of the host vehicle (for example, the current position detecting unit 21 in the embodiment), and road data storing means for storing road data including at least curvature information of the curve. (For example, the road data storage unit 22 in the embodiment) and determination means for determining whether or not the position of the host vehicle is within a yaw rate calculation range in which the yaw rate of the host vehicle can be calculated with a predetermined accuracy or higher. (For example, the yaw rate calculation range determination unit 23a in the embodiment) and the position of the host vehicle detected by the position detection means are within the yaw rate calculation range. Then, when determined by the determination means, the yaw rate that calculates the yaw rate of the own vehicle and outputs the calculated value based on the position of the own vehicle and the curvature information stored in the road data storage means Based on the difference between the calculation means (for example, the yaw rate calculation unit 31 in the embodiment), the calculation value of the yaw rate output from the yaw rate calculation means, and the detection value of the yaw rate output from the yaw rate detection means. The first yaw rate correction means (for example, the yaw rate sensor correction unit 38 in the embodiment) that corrects the detected value of the yaw rate and outputs the calculated value obtained by the correction.

  Further, in the yaw rate detection device according to the second aspect of the present invention, the road data includes inclination information of the travel road, and the determination means is present on the travel road where the position of the host vehicle is inclined. The yaw rate calculation is performed based on the inclination information stored in the road data storage means when the determination means determines that the position of the host vehicle is on an inclined traveling road. Or the second yaw rate correction means that corrects the calculated value of the yaw rate output from the first yaw rate correction means and outputs the calculated value obtained by the correction (for example, the yaw rate calculation unit 31 or the yaw rate in the embodiment) The first yaw rate correction means calculates the yaw rate output from the yaw rate calculation means. Is corrected by the second yaw rate correcting means, the detected value of the yaw rate is corrected based on the difference between the calculated value obtained by the correction and the detected value of the yaw rate output from the yaw rate detecting means. Then, the calculated value obtained by the correction is output.

  Furthermore, the yaw rate detection device according to the third aspect of the present invention is a wheel speed detection means for detecting the wheel speed of the host vehicle and outputting a detection value (for example, the wheel speed sensors 13FL, 13FR, 13RL in the embodiment). , 13RR) and wheel speed yaw rate calculating means for calculating a wheel speed yaw rate from the detected value of the wheel speed output from the wheel speed detecting means (for example, front wheel speed yaw rate calculating unit 32 in the embodiment, rear wheel) A wheel speed yaw rate calculation unit 33), the wheel speed yaw rate calculated by the wheel speed yaw rate calculation means, and any one of the yaw rate calculation means, the first yaw rate correction means, and the second yaw rate correction means. The yaw rate calculation value output from any one of the above is corrected based on the difference from the yaw rate calculation value output from , A third yaw rate correcting means for outputting a calculated value obtained by the correction (e.g., serving also as the yaw rate sensor correcting unit 38 in the embodiment).

Further, in the yaw rate detecting device according to a fourth aspect of the present invention, the curvature information, nodes and links combining by the radius of curvature of the data of the curve which is stored in advance in the road data storage means as the road data of And an object detection means (for example, the external sensor 14 in the embodiment) capable of detecting at least a traveling division line or a structure ahead in the traveling direction of the own vehicle, and the self-detection based on the detection result of the object detection means. Based on the curve radius detection means (for example, the curve radius detection unit 36 in the embodiment) for detecting the curvature radius of the curve ahead of the traveling direction of the vehicle, and the curvature radius of the curve detected by the curve radius detection means. Forward detection yaw rate calculation means for calculating the yaw rate of the host vehicle and outputting the calculated value (for example, the forward detection yaw rate in the embodiment) Rate calculation unit 37), the calculated yaw rate output from the forward detection yaw rate calculation means, the yaw rate calculation means, the first yaw rate correction means, the second yaw rate correction means, and the third yaw rate correction means. Based on the difference from the calculated value of the yaw rate output from any one of them, the calculated value of the yaw rate output from any one of the above is corrected, and the calculated value obtained by the correction is output. 4 yaw rate correction means (for example, the yaw rate sensor correction unit 38 in the embodiment also serves).

  According to the yaw rate detection device according to the first aspect of the present invention, the vehicle is not only traveling straight but also turning while based on the detected value of the yaw rate and the calculated value of the yaw rate based on the curvature information of the curve. Also, the detected value of the yaw rate can be corrected. In addition, the yaw rate calculation value based on the curvature information of the curve is calculated when the traveling path of the host vehicle is within a yaw rate calculation range in which the yaw rate can be calculated with a predetermined accuracy or higher. Accuracy can be improved.

  According to the yaw rate detection apparatus according to the second aspect of the present invention, the correction accuracy of the yaw rate detection value can be further improved by correcting the calculation value of the yaw rate based on the inclination information of the traveling road.

  According to the yaw rate detection apparatus according to the third aspect of the present invention, the correction accuracy of the yaw rate detection value can be further improved by correcting the yaw rate detection value based on the wheel speed yaw rate.

  According to the yaw rate detection device of the fourth aspect of the present invention, the correction accuracy of the yaw rate detection value is further improved by correcting the detection value of the yaw rate based on the curvature radius of the curve detected by the curve radius detection means. This can be further improved.

It is a block diagram of the yaw rate detection apparatus which concerns on embodiment of this invention. It is a figure which shows the example of the correspondence of the curvature radius of the traveling path which concerns on embodiment of this invention, the position (for example, urban area or suburb area) where a traveling path exists, and the calculation accuracy of a yaw rate. It is a figure which shows the example of the correspondence of the correction value of the yaw rate which concerns on embodiment of this invention, a vehicle speed, and the crossing gradient (cant) of a travel path. It is a flowchart which shows operation | movement of the yaw rate detection apparatus which concerns on embodiment of this invention. It is a flowchart which shows operation | movement of the yaw rate detection apparatus which concerns on the reference Example of embodiment of this invention. It is a flowchart which shows operation | movement of the yaw rate detection apparatus which concerns on the reference Example of embodiment of this invention.

Hereinafter, an embodiment of a yaw rate detection apparatus according to the present invention will be described with reference to the accompanying drawings.
A yaw rate detection device 10 according to this embodiment is mounted on a vehicle (own vehicle), for example, as shown in FIG. 1, and includes a yaw rate sensor 11, a vehicle speed sensor 12, and four-wheel wheel speed sensors 13FL, 13FR, 13RL, 13RR. And an external sensor 14, a navigation device 15, and a control unit 16.

The yaw rate sensor 11 detects the yaw rate (rotational angular velocity about the vertical axis of the center of gravity of the vehicle) and outputs a detection value signal.
The vehicle speed sensor 12 detects the speed of the vehicle (vehicle speed) and outputs a detection value signal.
Each wheel speed sensor 13FL, 13FR, 13RL, 13RR sequentially detects the wheel speeds of the left front wheel, the right front wheel, the left rear wheel, and the right rear wheel, and outputs a detected value.

The external sensor 14 is configured by, for example, a radar device or an imaging device using electromagnetic waves.
For example, the radar device transmits an electromagnetic wave transmission signal so as to scan a detection target region (for example, a front region and a rear region in the traveling direction) set in the external environment of the vehicle. Then, the reflected signal generated by the reflected signal reflected by an object outside the vehicle (such as another vehicle or structure) or a pedestrian is received, and the distance from the radar device to the object or pedestrian is detected. The detection signal and the detection signal related to the angle (azimuth angle and elevation angle) of an external object or pedestrian are generated and output to the control unit 16.
In addition, for example, the imaging apparatus performs image processing on an image obtained by imaging an imaging area (for example, a front area and a rear area in the traveling direction) set in the external environment of the vehicle with a camera, and generates image data. To the control unit 16.

  The navigation device 15 includes, for example, a current position detection unit 21, a road data storage unit 22, a navigation processing unit 23, an input unit 24, and an output unit 25.

  The current position detection unit 21 detects the current position of the vehicle by a positioning signal such as a GPS signal or by an autonomous navigation calculation process based on the yaw rate and vehicle speed detection signals output from the sensors 11 and 12.

  The road data storage unit 22 includes, for example, a node (that is, a coordinate point for grasping the road shape), a link that is a line connecting each node, a distance of each link, a road type, a width, an intersection angle, and a shape. The road data such as is stored. Further, the road data includes curvature information (for example, information related to the curvature radius of the curve) and inclination information (for example, information related to the crossing gradient of the road).

  The navigation processing unit 23 is based on the current position of the vehicle output from the current position detection unit 21 and the road data acquired from the road data storage unit 22, for example, according to an input operation of the operator to the input unit 24, etc. It performs map matching processing, route search, route guidance, and the like. And the result of various processes is output to the output part 25. FIG.

Further, the navigation processing unit 23 includes a yaw rate calculation range determination unit 23a.
The yaw rate calculation range determination unit 23a can calculate the yaw rate calculation range in which the current position of the vehicle output from the current position detection unit 21 can calculate the yaw rate of the vehicle with a predetermined accuracy (for example, the lower limit accuracy A shown in FIG. 2). Is determined based on each data stored in the road data storage unit 22, and a signal of the determination result is output. This determination is made based on, for example, the radius of curvature of the travel path, the position where the travel path exists (for example, an urban area or a suburb area), and a travel history for the travel path.

For example, as shown in FIG. 2, a node (that is, a road shape) has a small radius of curvature and a curved road (for example, a road having a radius of curvature R2 or less in an urban area or a radius of curvature R1 or less in a suburb). Therefore, the accuracy and reliability of the curvature information of the traveling road are high, and the calculation accuracy of the yaw rate calculated based on this curvature information is high.
On the other hand, on a road with a moderate curvature radius and a gentle curve (for example, a road between curvature radii R2 and R3 in urban areas or between curvature radii R1 and R4 in suburban areas). By reducing the number of nodes, the accuracy and reliability of the curvature information of the traveling path are lowered, and the calculation accuracy of the yaw rate calculated based on the curvature information is lowered.
In addition, on a road with a large curvature radius and close to a straight road (for example, a road with a radius of curvature R3 or more in urban areas or a radius of curvature R4 or more in suburbs), the yaw rate is close to zero and there are few nodes. Even in this case, the calculation accuracy of the yaw rate calculated based on the curvature information is increased.

In urban areas, since there are many nodes (that is, coordinate points for grasping the road shape), the accuracy and reliability of the curvature information of the traveling road is high, and the calculation is based on this curvature information. The calculation accuracy of the yaw rate is increased.
On the other hand, in the suburbs, the decrease in the number of nodes reduces the accuracy and reliability of the curvature information of the traveling road, and the yaw rate calculation accuracy calculated based on the curvature information decreases.
In addition, when the arrangement of the nodes is learned according to the travel history of the vehicle, the accuracy and reliability of the curvature information of the travel path is increased according to the travel history for the travel path. The calculation accuracy of the calculated yaw rate is increased.

  Further, the yaw rate calculation range determination unit 23a determines whether or not the current position of the vehicle output from the current position detection unit 21 is present on the inclined traveling road based on the inclination information of the traveling road. Output the resulting signal.

  For example, the control unit 16 includes a yaw rate calculation unit 31, a front wheel speed yaw rate calculation unit 32, a rear wheel speed yaw rate calculation unit 33, a front wheel speed yaw rate correction unit 34, and a rear wheel speed yaw rate correction unit 35. The curve radius detection unit 36, the forward detection yaw rate calculation unit 37, and the yaw rate sensor correction unit 38 are provided.

When the yaw rate calculation range determination unit 23a of the navigation device 15 determines that the current position of the vehicle is within a yaw rate calculation range in which the yaw rate can be calculated with a predetermined accuracy or higher, the yaw rate calculation unit 31 determines the current position of the vehicle. The yaw rate Ynv of the vehicle is calculated based on the curvature information of the traveling road stored in the road data storage unit 22 and the detected vehicle speed value output from the vehicle speed sensor 12.
When the yaw rate calculation range determination unit 23a determines that the current position of the vehicle exists on the inclined road, the yaw rate calculation unit 31 determines the inclination of the road stored in the road data storage unit 22. Based on the information, the yaw rate Ynv is corrected, and the corrected yaw rate Ynva is output. In this correction, for example, as shown in FIG. 3, the correction value of the yaw rate Ynv is set based on the crossing gradient (cant) of the traveling road and the vehicle speed, and for example, the absolute value of the crossing gradient (cant) increases. As the vehicle speed increases, the absolute value of the correction value of the yaw rate Ynv is set to increase.

The front wheel speed yaw rate calculation unit 32 refers to a predetermined wheel speed yaw rate map stored in advance based on the detected values of the wheel speeds of the left front wheel and the right front wheel output from the wheel speed sensors 22FL and 22FR of the front wheels. Then, the front wheel speed yaw rate Yf is calculated, and the calculated value is output.
The rear wheel speed yaw rate calculation unit 33 is a predetermined wheel speed yaw rate stored in advance based on the detected values of the wheel speeds of the left rear wheel and the right rear wheel output from the wheel speed sensors 22RL and 22RR of the rear wheels. The rear wheel speed yaw rate Yr is calculated with reference to the map and the calculated value is output.
The predetermined wheel speed yaw rate map is, for example, a difference between left and right wheel speeds (that is, a wheel speed difference between the left front wheel and the right front wheel, or a wheel speed difference between the left rear wheel and the right rear wheel). FIG. 6 is a map showing a predetermined correspondence relationship with the yaw rate, that is, each wheel speed yaw rate Yf, Yr.

The front wheel speed yaw rate correction unit 34, when it is determined by the yaw rate calculation range determination unit 23a that the current position of the vehicle is present on an inclined traveling road, the front wheel wheel output from the front wheel speed yaw rate calculation unit 32 The speed yaw rate Yf is corrected based on the inclination information of the traveling road stored in the road data storage unit 22, and the corrected front wheel speed yaw rate Yfa is output.
The rear wheel wheel speed yaw rate correction unit 35 is output from the rear wheel wheel speed yaw rate calculation unit 33 when it is determined by the yaw rate calculation range determination unit 23a that the current position of the vehicle is on a sloping road. The rear wheel speed yaw rate Yr is corrected based on the inclination information of the traveling road stored in the road data storage unit 22, and the corrected rear wheel speed yaw rate Yra is output.
In these corrections, for example, as shown in FIG. 3, correction values of the wheel speed yaw rates Yfa and Yra are set based on the crossing gradient (cant) of the traveling road and the vehicle speed. The absolute values of the correction values of the wheel speed yaw rates Yfa and Yra are set so as to increase as the absolute value of the wheel speed increases or as the vehicle speed increases.

The curve radius detector 36 detects the radius of curvature of the curve ahead of the traveling direction of the vehicle based on the detection result of the external sensor 14.
For example, the curve radius detection unit 36 is based on a structure (for example, a guardrail or a building on the road surface) detected by the radar device of the external sensor 14 or a road surface imaged by the imaging device of the external sensor 14 The curvature radius of the curve ahead of the traveling direction of the vehicle is detected on the basis of the travel line on the road surface.

The forward detection yaw rate calculation unit 37 is based on the curvature radius of the curve detected by the curve radius detection unit 36 and the vehicle speed detection value output from the vehicle speed sensor 12, and the vehicle yaw rate at the curve ahead of the vehicle traveling direction. Ynvd is calculated.
The forward detection yaw rate calculation unit 37, when it is determined by the yaw rate calculation range determination unit 23a that the current position of the vehicle exists on the inclined road, the road stored in the road data storage unit 22 The yaw rate Ynvd is corrected based on the tilt information, and the corrected yaw rate Ynve is output. In this correction, for example, as shown in FIG. 3, the correction value of the yaw rate Ynvd is set based on the crossing gradient (cant) of the traveling road and the vehicle speed, and for example, the absolute value of the crossing gradient (cant) increases. The absolute value of the correction value of the yaw rate Ynvd is set so as to increase as the vehicle speed increases.

  The yaw rate sensor correction unit 38 outputs the yaw rate Ynva output from the yaw rate calculation unit 31, the wheel speed yaw rates Yfa and Yra output from the wheel speed yaw rate correction units 34 and 35, and the forward detection yaw rate calculation unit 37. The yaw rate (detected value) Ys output from the yaw rate sensor 11 is corrected based on the yaw rate Ynve.

For example, the yaw rate sensor correction unit 38 performs predetermined low-pass processing on the difference ΔYnva based on the difference ΔYnva (= Ynva−Ys) between the yaw rate Ynva output from the yaw rate calculation unit 31 and the yaw rate (detection value) Ys. After the change amount limiting process is performed, the corrected yaw rate Ynvb (= Ys + ΔYnva) is output.
Then, one of the wheel speed yaw rates Yfa and Yra output from each wheel speed yaw rate correction unit 34 or 35, or the wheel speed yaw rate Ywa related to each wheel speed yaw rate Yfa and Yra (for example, front wheel wheel speed yaw rate Yfa). And the rear wheel speed yaw rate Yra) and the difference ΔYnvb (= Ywa−Ynvb) between the yaw rate Ynvb and the difference ΔYnvb is subjected to predetermined low-pass processing and variation limit processing. After that, the corrected yaw rate Ynvc (= Ynvb + ΔYnvb) is output.
Then, based on the difference ΔYnvc (= Ynve−Ynvc) between the yaw rate Ynve output from the forward detection yaw rate calculation unit 37 and the yaw rate Ynvc, predetermined low-pass processing and change amount limiting processing are performed on the difference ΔYnvc. After this, the corrected yaw rate Ynvf (= Ynvc + ΔYnvc) is output.

  The yaw rate detection device 10 according to this embodiment has the above-described configuration. Next, an example of the operation of the yaw rate detection device 10 will be described.

First, for example, in step S01 shown in FIG. 4, the yaw rate (detection value) Ys output from the yaw rate sensor 11 is acquired.
Next, in step S02, the detected value of the vehicle speed output from the vehicle speed sensor 12 is acquired.
Next, in step S03, for example, the current position of the vehicle is detected by a positioning signal such as a GPS signal, and further by an autonomous navigation calculation process based on the yaw rate and vehicle speed detection signals output from the sensors 11 and 12. .

Next, in step S04, road data stored in the road data storage unit 22 is acquired.
Next, in step S05, for example, based on the radius of curvature of the travel path obtained from the road data, the position where the travel path exists (for example, an urban area or a suburb area), the travel history for the travel path, and the like. A yaw rate calculation range in which the yaw rate of the vehicle can be calculated with a predetermined accuracy or higher is acquired.
Next, in step S06, it is determined whether or not the current travel route of the vehicle is included in the yaw rate calculation range.
If this determination is “NO”, the flow proceeds to return.
On the other hand, if this determination is “YES”, the flow proceeds to step S07.

Next, in step S07, the yaw rate Ynv of the vehicle is calculated based on the curvature information of the road data and the vehicle speed.
Next, in step S08, the yaw rate Ynv is corrected based on the slope information of the road data, and the corrected yaw rate Ynva is output.
Next, in step S09, a difference ΔYnva (= Ynva−Ys) between the yaw rate (detected value) Ys and the yaw rate Ynva is calculated.
Next, in step S10, predetermined low-pass processing, change amount limiting processing, and the like are performed on the difference ΔYnva.
Next, in step S11, the yaw rate (detection value) Ys is corrected by the difference ΔYnva, and the corrected first yaw rate Ynvb (= Ys + ΔYnva) is output.

Next, in step S12, the front wheel speed yaw rate Yf is calculated based on the detected values of the wheel speeds of the left front wheel and the right front wheel output from the front wheel speed sensors 22FL, 22FR, and the rear wheel speeds are calculated. The rear wheel speed yaw rate Yr is calculated based on the detected values of the wheel speeds of the left rear wheel and the right rear wheel output from the sensors 22RL and 22RR. Note that the wheel speed yaw rate Yw shown in FIG. 4 is the front wheel speed yaw rate Yf or the rear wheel speed yaw rate Yr.
Next, in step S13, the wheel speed yaw rates Yf and Yr are corrected based on the slope information of the road data, and the corrected wheel speed yaw rates Yfa and Yra are output. Note that the wheel speed yaw rate Ywa shown in FIG. 4 is the front wheel speed yaw rate Yfa or the rear wheel speed yaw rate Yra.

Next, in step S14, a difference ΔYnvb (= Ywa−Ynvb) between the yaw rate Ynvb and the wheel speed yaw rate Ywa is calculated.
Next, in step S15, predetermined low-pass processing, change amount limiting processing, and the like are performed on the difference ΔYnvb.
Next, in step S16, the yaw rate Ynvb is corrected by the difference ΔYnvb, and the corrected yaw rate Ynvc (= Ynvb + ΔYnvb) is output.

Next, in step S17, based on the detection result of the external sensor 14, the curvature radius of the curve ahead of the traveling direction of the vehicle is detected.
Next, in step S18, the yaw rate Ynvd of the vehicle at the curve ahead of the traveling direction of the vehicle is calculated based on the curvature radius of the curve based on the detection result of the external sensor 14 and the vehicle speed.
Next, in step S19, the yaw rate Ynvd is corrected based on the slope information of the road data, and the corrected yaw rate Ynve is output.

Next, in step S20, a difference ΔYnvc (= Ynve−Ynvc) between the yaw rate Ynvc and the yaw rate Ynve is calculated.
Next, in step S21, predetermined low-pass processing, change amount limiting processing, and the like are performed on the difference ΔYnvc.
Next, in step S22, the yaw rate Ynvc is corrected by the difference ΔYnvc, the corrected yaw rate Ynvf (= Ynvc + ΔYnvc) is output, and the process proceeds to return.

  As described above, according to the yaw rate detection device 10 according to the embodiment of the present invention, the yaw rate (detection value) Ys and the yaw rate Ynv calculated based on the curvature information of the curve stored in the road data storage unit 22 are obtained. Based on this, the yaw rate (detection value) Ys can be corrected not only when the vehicle is traveling straight but also when the vehicle is turning. In addition, since the yaw rate Ynv based on the curvature information of the curve is calculated when the vehicle traveling path is within a yaw rate calculation range in which the yaw rate can be calculated with a predetermined accuracy or higher, the correction accuracy of the yaw rate (detection value) Ys is calculated. Can be improved.

Further, by correcting the yaw rate (detection value) Ys based on the wheel speed yaw rates Yf and Yr and the yaw rate Ynvd calculated by the forward detection yaw rate calculation unit 37, the correction accuracy of the yaw rate (detection value) Ys is further increased. Can be improved.
Furthermore, since each yaw rate Ynv, Yf, Yr, Ynvd is corrected based on the inclination information of the traveling road, the correction accuracy of the yaw rate (detected value) Ys can be further improved.

  In the above-described embodiment, the yaw rate sensor correction unit 38 calculates the yaw rate calculated by the yaw rate calculation unit 31 instead of the yaw rates Ynva, Yfa, Yra, and Ynve that have been corrected based on the inclination information of the traveling road. The yaw rate output from the yaw rate sensor 11 based on Ynv, the wheel speed yaw rates Yf and Yr calculated by the wheel speed yaw rate calculation units 32 and 33, and the yaw rate Ynvd calculated by the forward detection yaw rate calculation unit 37 ( (Detection value) Ys may be corrected. In this case, furthermore, the yaw rate (detected value) Ys is corrected based on at least one of the yaw rates Ynv, Yf, Yr, and Ynv, and the calculated inclination obtained from the correction is added to the inclination information of the traveling road. Correction based on this may be performed.

  In the embodiment described above, the yaw rate sensor correction unit 38 corrects the yaw rate (detection value) Ys based on the difference between the yaw rate Ynv calculated by the yaw rate calculation unit 31 and the yaw rate (detection value) Ys, and A calculated value (first yaw rate) obtained by correction (first correction) may be output.

  Further, the yaw rate sensor correction unit 38 corrects the yaw rate Ynv or the first yaw rate calculated by the yaw rate calculation unit 31 based on the inclination information of the traveling road, and a calculated value (second correction) obtained by the correction (second correction). (Second yaw rate) may be output. At this time, when the yaw rate Ynv calculated by the yaw rate calculation unit 31 is corrected based on the inclination information of the traveling road, the yaw rate is calculated based on the difference between the calculated value obtained by the correction and the yaw rate (detected value) Ys. (Detection value) Ys may be corrected.

  Further, the yaw rate sensor correction unit 38 determines the wheel speed yaw rate Yw and the difference between the yaw rate Ynv calculated by the yaw rate calculation unit 31 and any one of the first yaw rate and the second yaw rate. One of them may be corrected, and a calculated value (third yaw rate) obtained by the correction (third correction) may be output. The wheel speed yaw rate Yw is either the wheel speed yaw rate Yf or Yr output from the wheel speed yaw rate calculation unit 32 or 33, or the wheel speed yaw rate related to the wheel speed yaw rate Yf or Yr (for example, The average value of the front wheel speed yaw rate Yf and the rear wheel speed yaw rate Yr).

  Further, the yaw rate sensor correction unit 38 includes the yaw rate Ynvd calculated by the forward detection yaw rate calculation unit 37, the yaw rate Ynv calculated by the yaw rate calculation unit 31, the first yaw rate, the second yaw rate, and the third yaw rate. Any one of them may be corrected based on a difference from any one of them, and a calculated value (fourth yaw rate) obtained by the correction (fourth correction) may be output.

  In the above-described embodiment, for example, as in the reference example shown in FIGS. 5 and 6, processing for correcting the yaw rate (detected value) Ys based on the wheel speed yaw rate Ywa, and the forward detection yaw rate calculation unit 37 The process of correcting the yaw rate (detected value) Ys on the basis of the yaw rate Ynve output from may be executed independently.

For example, in step S31 shown in FIG. 5, the yaw rate (detection value) Ys output from the yaw rate sensor 11 is acquired.
Next, in step S32, the detected value of the vehicle speed output from the vehicle speed sensor 12 is acquired.
Next, in step S33, for example, the current position of the vehicle is detected by a positioning signal such as a GPS signal, and further by an autonomous navigation calculation process based on the yaw rate and vehicle speed detection signals output from the sensors 11 and 12. .

Next, in step S34, road data stored in the road data storage unit 22 is acquired.
Next, in step S35, the front wheel speed yaw rate Yf is calculated based on the detected values of the front left wheel speed and the right front wheel speed output from the front wheel speed sensors 22FL, 22FR, and the rear wheel speeds are calculated. The rear wheel speed yaw rate Yr is calculated based on the detected values of the wheel speeds of the left rear wheel and the right rear wheel output from the sensors 22RL and 22RR. Note that the wheel speed yaw rate Yw shown in FIG. 5 is the front wheel speed yaw rate Yf or the rear wheel speed yaw rate Yr.
Next, in step S36, the wheel speed yaw rates Yf and Yr are corrected based on the inclination information of the road data, and the corrected wheel speed yaw rates Yfa and Yra are output. The wheel speed yaw rate Ywa shown in FIG. 5 is the front wheel speed yaw rate Yfa or the rear wheel speed yaw rate Yra.

Next, in step S37, a difference ΔYsa (= Ywa−Ys) between the yaw rate (detected value) Ys and the wheel speed yaw rate Ywa is calculated.
Next, in step S38, predetermined low-pass processing, change amount limiting processing, and the like are performed on the difference ΔYsa.
Next, in step S39, the yaw rate Ys is corrected by the difference ΔYsa, the corrected yaw rate Ysa (= Ys + ΔYsa) is output, and the process proceeds to return.

For example, in step S41 shown in FIG. 6, the yaw rate (detection value) Ys output from the yaw rate sensor 11 is acquired.
Next, in step S42, the detected value of the vehicle speed output from the vehicle speed sensor 12 is acquired.
Next, in step S43, for example, the current position of the vehicle is detected by a positioning signal such as a GPS signal, and further by an autonomous navigation calculation process based on the yaw rate and vehicle speed detection signals output from the sensors 11 and 12. .

Next, in step S44, road data stored in the road data storage unit 22 is acquired.
Next, in step S45, based on the detection result of the external sensor 14, the radius of curvature of the curve ahead of the traveling direction of the vehicle is detected.
Next, in step S46, the yaw rate Ynvd of the vehicle at the curve ahead of the traveling direction of the vehicle is calculated based on the radius of curvature of the curve based on the detection result of the external sensor 14 and the vehicle speed.
Next, in step S47, the yaw rate Ynvd is corrected based on the slope information of the road data, and the corrected yaw rate Ynve is output.

Next, in step S48, a difference ΔYsb (= Ynve−Ys) between the yaw rate (detected value) Ys and the yaw rate Ynve is calculated.
Next, in step S49, predetermined low-pass processing, change amount limiting processing, and the like are performed on the difference ΔYsb.
Next, in step S50, the yaw rate (detected value) Ys is corrected by the difference ΔYsb, the corrected yaw rate Ysb (= Ys + ΔYsb) is output, and the process proceeds to return.

10 Yaw Rate Detection Device 11 Yaw Rate Sensor (Yaw Rate Detection Unit)
13FL, 13FR, 13RL, 13RR Wheel speed sensor (wheel speed detection means)
14 External sensor (object detection means)
21 Current position detection unit (position detection means)
22 Road data storage (road data storage means)
23 navigation processing unit 23a yaw rate calculation range determination unit (determination unit)
31 Yaw rate calculation unit (yaw rate calculation means, second yaw rate correction means)
32 Front wheel speed yaw rate calculation unit (wheel speed yaw rate calculation means)
33 Rear wheel wheel speed yaw rate calculation unit (wheel speed yaw rate calculation means)
36 Curve radius detector (curve radius detector)
37 Forward detection yaw rate calculation unit (forward detection yaw rate calculation means)
38 Yaw rate sensor correction unit (first yaw rate correction means, second yaw rate correction means, third yaw rate correction means, fourth yaw rate correction means)

Claims (4)

Yaw rate detection means for detecting the yaw rate of the host vehicle and outputting a detection value;
Position detecting means for detecting the position of the host vehicle;
Road data storage means for storing road data including at least curve curvature information;
Determining means for determining whether the position of the host vehicle is within a yaw rate calculation range capable of calculating the yaw rate of the host vehicle with a predetermined accuracy or higher;
The position of the host vehicle and the curvature stored in the road data storage unit when the determining unit determines that the position of the host vehicle detected by the position detecting unit is within the yaw rate calculation range. Yaw rate calculation means for calculating a yaw rate of the host vehicle based on the information and outputting a calculated value;
Based on the difference between the calculated value of the yaw rate output from the yaw rate calculating means and the detected value of the yaw rate output from the yaw rate detecting means, the detected value of the yaw rate is corrected, and a calculated value obtained by the correction And a first yaw rate correcting means for outputting the yaw rate detecting device. The road data includes inclination information of the traveling road,
The determination means determines whether or not the position of the host vehicle is on a sloping road,
The yaw rate calculation means or the first yaw rate based on the inclination information stored in the road data storage means when the determination means determines that the position of the host vehicle is on a sloping traveling road. A second yaw rate correcting means for correcting the calculated value of the yaw rate output from the correcting means and outputting the calculated value obtained by the correction;
The first yaw rate correction means, when the calculation value of the yaw rate output from the yaw rate calculation means is corrected by the second yaw rate correction means, the calculated value obtained by the correction and the yaw rate detection means The yaw rate detection device according to claim 1, wherein the yaw rate detection value is corrected based on a difference from the output yaw rate detection value, and a calculated value obtained by the correction is output. Wheel speed detection means for detecting the wheel speed of the host vehicle and outputting a detection value;
Wheel speed yaw rate calculating means for calculating a wheel speed yaw rate from the detected value of the wheel speed output from the wheel speed detecting means;
The wheel speed yaw rate calculated by the wheel speed yaw rate calculating means, and the calculated value of the yaw rate output from any one of the yaw rate calculating means, the first yaw rate correcting means, and the second yaw rate correcting means. 3. A third yaw rate correction unit that corrects the calculated value of the yaw rate output from any one of the two based on the difference between the two and outputs a calculated value obtained by the correction. The yaw rate detection device described. The curvature information comprises curvature radius data of the curve stored in the road data storage means in advance as the road data by a combination of nodes and links,
An object detection means capable of detecting at least a traveling division line or a structure in front of the traveling direction of the host vehicle;
Based on the detection result of the object detection means, a curve radius detection means for detecting a curvature radius of the curve ahead of the traveling direction of the host vehicle;
Forward detected yaw rate calculating means for calculating a yaw rate of the host vehicle and outputting a calculated value based on a curvature radius of the curve detected by the curve radius detecting means;
The calculated value of the yaw rate output from the forward detection yaw rate calculating means, and any one of the yaw rate calculating means, the first yaw rate correcting means, the second yaw rate correcting means, and the third yaw rate correcting means. 4th yaw rate correction means for correcting the calculated value of the yaw rate output from any one of them based on the difference from the output value of the output yaw rate and outputting the calculated value obtained by the correction. The yaw rate detection device according to claim 3.

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