JP2005247023A - State quantity presumption device of vehicle - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To stably and precisely detect various state quantity generated on a vehicle. <P>SOLUTION: An elliptical marker is marked on a road surface to travel on. The marker is photographed by a camera arranged immediately downward on a lower part of the vehicle and translational speed in the longitudinal direction and in the lateral direction of the vehicle is computed from a relative positional change against the vehicle at a center-of-gravity position of the marker. A yaw angle and yaw angle speed are computed from a rotational state. A pitch angle and pitch angle speed are computed from a change in the major axial direction of the marker, and a rolling angle and rolling angle speed are computed from a change in the minor axial direction. Heel of the present road surface is computed by computing an increment of heel of the road surface previously computed in accordance with at least either one of relations of a relation of acceleration in the vertical direction, translational speed in the longitudinal direction, a radius of revolution and the heel of the road surface previously computed and a relation of acceleration in the lateral direction, the translational speed in the longitudinal direction, the radius of revolution and the heel of the road surface previously computed in accordance with a signal from a force detection sensor to detect force working in the vertical direction from the road surface on each of the wheels and a signal from a lateral acceleration sensor. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

  The present invention relates to a vehicle state quantity estimating device that calculates forward / backward and lateral translation speeds, yaw, roll and pitch angles, vehicle mass, lateral inclination of a road surface with respect to the host vehicle, and the like.

  In recent years, various state quantities of a traveling vehicle, that is, forward / backward and lateral translation speeds, yaw, roll and pitch angles, vehicle mass, lateral inclination of the road surface with respect to the host vehicle, and the like are detected or calculated. However, it is used as an important correction parameter for vehicle development and vehicle behavior control.

As a technique for estimating various vehicle state quantities, for example, in Japanese Patent Application Laid-Open No. 11-230742, vehicle speed is detected based on signals from wheel speed sensors provided on driven wheels, and vehicle heights provided before and after the vehicle body. The pitch angle is detected based on the signal from the sensor, the roll angle is detected based on the signals from the vehicle height sensors provided on the left and right sides of the vehicle body (front bumper), and the yaw angle is detected based on the signal from the yaw rate sensor. Then, the lateral acceleration is detected by the lateral acceleration sensor. In addition, the angular velocity at the time of turning of the vehicle is obtained based on the signal from the yaw rate sensor, the centrifugal force is obtained from the angular velocity and the vehicle speed, and the radius of curvature at the turning of the vehicle is obtained. Technology to determine the lateral component force that is the detection direction of the lateral acceleration sensor from the angle between the centrifugal force and the tangential direction of the turning circle of the vehicle, and to determine the lateral inclination angle of the road surface from the lateral acceleration, lateral component force, and roll angle Is disclosed.
Japanese Patent Laid-Open No. 11-230742

  However, in the technique disclosed in Patent Document 1 described above, the vehicle speed is obtained from a value from the wheel speed sensor. Therefore, an error is accumulated when tire slip occurs, and the vehicle speed is accurately measured. There is a problem that measurement is not possible. Further, since the vehicle height sensor is also detected toward the bottom of the bumper, there is a problem that it is difficult to continuously and stably measure the vehicle height with high accuracy under the influence of the uneven state of the road surface. If various state quantities are calculated using such vehicle speed and vehicle height values, accurate values cannot be obtained, and there is a possibility that accurate control and driving support cannot be performed.

  The present invention has been made in view of the above circumstances, and an object of the present invention is to provide a vehicle state quantity estimation device that can stably and accurately detect various state quantities generated in a vehicle.

  The present invention provides a recognition means for recognizing marker means on a road surface in which a change in relative position with respect to the own vehicle accompanying the movement of the own vehicle can be discriminated, and a translation speed of the own vehicle based on the recognition result of the position of the marker means. Translational speed calculating means for calculating the vertical acceleration detecting means for detecting the vertical acceleration acting on the own vehicle, lateral acceleration detecting means for detecting the lateral acceleration acting on the own vehicle, A turning radius calculating means for calculating a turning radius, the relationship between the vertical acceleration, the translation speed, the turning radius, and the lateral inclination of the road surface with respect to the vehicle previously calculated, the lateral acceleration, the translation speed, and the turning radius. Based on the relationship between at least one of the above and the previously calculated relationship of the lateral slope of the road surface, the increase in the lateral slope of the road surface relative to the previously calculated vehicle is calculated, and the current vehicle It is characterized in that a road side slope calculating means for calculating a lateral inclination of the road surface against.

  The vehicle state quantity estimation device according to the present invention has an excellent effect that various state quantities generated in the vehicle can be detected stably and accurately.

Hereinafter, embodiments of the present invention will be described with reference to the drawings.
1 to 6 show an embodiment of the present invention. FIG. 1 is an explanatory diagram of a vehicle equipped with a state quantity estimation device that travels on a road surface. FIG. 2 is a flowchart of a state quantity estimation program. FIG. FIG. 4 is an explanatory diagram of roll angle and pitch angle detection, FIG. 5 is an explanatory diagram of calculation of a turning radius, and FIG. 6 is an explanatory diagram of balance of each force due to lateral inclination. FIG.

  In FIG. 1, reference numeral 1 denotes a vehicle such as an automobile (own vehicle). The vehicle 1 includes a longitudinal translation speed vx, a lateral translation speed vy, a pitch angle θP, a pitch angular velocity (dθP / dt), A state quantity estimating device 2 for estimating each state quantity such as a roll angle θR, a roll angular velocity (dθR / dt), a yaw angle θY, a yaw angular velocity (dθY / dt), a vehicle mass m, and a lateral slope θK of a road surface is mounted. Yes.

  On the road surface 3 on which the vehicle 1 travels, markers 4 as elliptical marker means whose major axis is the traveling direction and whose minor axis is the road width direction are marked at set intervals (for example, every 4 to 5 m). The marker 4 is picked up by a camera 5 disposed directly below the vehicle 1 and its shape is recognized by a control unit 6 described later.

In order to estimate each state quantity described above, the vehicle 1 has a force acting on the four wheels (left front wheel 7fl, right front wheel 7fr, left rear wheel 7rl, right rear wheel 7rr) in addition to the camera 5 in the vertical direction from the road surface. Force detection sensors 8fl, 8fr, 8rl and 8rr for detecting Fzfl, Fzfr, Fzrl and Fzrr are embedded in the axle housings of the respective wheels, and lateral acceleration acting on the vehicle 1 (d ² y / dt ² The lateral acceleration sensor 9 is disposed as a lateral acceleration detecting means for detecting ().

  The camera 5 and the sensors 8fl, 8fr, 8rl, 8rr, and 9 are connected to the control unit 6, and the control unit 6 performs estimation calculation of each state quantity according to the following state quantity estimation program.

  The state quantity estimation process executed by the control unit 6 will be described with reference to the state quantity estimation program flowchart of FIG.

First, in step (hereinafter abbreviated as “S”) 101, necessary parameters are read. Specifically, as for this parameter, with respect to the marker 4, the long axis dimensions a1 and a2 of the previous and current ellipses, the short axis dimensions b1 and b2 of the previous and current ellipses, and the inclination angle of the ellipse from the previous recognition. (Yaw angle) θY, and the previous and current ellipse center-of-gravity position coordinates (x01, y01) and (x02, y02) with the vehicle 1 as an absolute coordinate system are read. Also, forces Fzfl, Fzfr, Fzrl, Fzrr acting in the vertical direction of the four wheels 7fl, 7fr, 7rl, 7rr are read from the force detection sensors 8fl, 8fr, 8rl, 8rr, and the lateral acceleration (d ² y / dt ² ) is read. Further, the coordinates of three points in the past travel locus, that is, as shown in FIG. 5, the current position is point P4, point P1 (x1, y1), point P2 (x2, y2), point P3 (x3, The coordinates of y3) are read as an absolute coordinate system with the point P1 as the origin. Further, the previously calculated lateral slope θKn−1 of the road surface is read.

Next, the process proceeds to S102, and the translational speed vx in the front-rear direction and the translational speed vy in the lateral direction are calculated by the following formulas (1) and (2) from the relationship shown in FIG.
vx = (x02−x01) / Δt (1)
vy = (y02−y01) / Δt (2)
Here, Δt is a sampling time.

  Next, in S103, the pitch angle θP, the pitch angular velocity (dθP / dt), the roll angle θR, the roll angular velocity (dθR / dt), the yaw angle θY, and the yaw angular velocity (dθY / dt) are calculated and output. These angles and angular velocities are calculated by the following equations (3) to (7).

First, the pitch angular velocity (dθP / dt) is calculated from the relationship shown in FIG.
(DθP / dt) = (cos ⁻¹ (a2 / a1)) / Δt (3)
However,
((DFzfl / dt) + (dFzfr / dt)) / 2
> ((DFzrl / dt) + (dFzrr / dt)) / 2, the sign is positive,
((DFzfl / dt) + (dFzfr / dt)) / 2
If <((dFzrl / dt) + (dFzrr / dt)) / 2, the sign is negative.

And the pitch angle θP is
θP = ∫ (dθP / dt) dt (4)
It calculates by.

Further, the roll angular velocity (dθR / dt) is calculated from the relationship shown in FIG.
(DθR / dt) = (cos ⁻¹ (b2 / b1)) / Δt (5)
However,
((DFzfl / dt) + (dFzrl / dt)) / 2
If <((dFzfr / dt) + (dFzrr / dt)) / 2, the sign is positive,
((DFzfl / dt) + (dFzrl / dt)) / 2
If> ((dFzfr / dt) + (dFzrr / dt)) / 2, the sign is negative.

And the roll angle θR is
θR = ∫ (dθR / dt) dt (6)
It calculates by.

The yaw angular velocity (dθY / dt) is
θY / Δt (7)
It calculates by.

Next, proceeding to S104, the vertical force Fz acting on the vehicle 1 is calculated by the following equation (8).
Fz = Fzfl + Fzfr + Fzrl + Fzrr (8)

  Next, the process proceeds to S105, where the previously calculated road slope θKn-1 is compared with a preset threshold value (a value that is almost negligible, such as 5 °, for example, 5 °). When the horizontal inclination θKn-1 of the vehicle is larger than a preset threshold value (5 °), the process proceeds to S106, and the previous vehicle mass value is calculated as the current vehicle mass without calculating the vehicle mass this time. The value is determined and the process proceeds to S108.

As a result of the comparison in S105, if the previously calculated road slope θKn-1 is less than or equal to a preset threshold value (5 °), the process proceeds to S107, and the current vehicle mass m is set to the following (9) The calculation is performed using the formula and the process proceeds to S108. In addition, g is a gravitational acceleration.
m = Fz / g (9)

When the current vehicle mass m is determined in S106 or S107 and the process proceeds to S108, the turning radius is based on the coordinates of point P1 (x1, y1), point P2 (x2, y2), and point P3 (x3, y3). r is calculated. That is, as shown in FIG. 5, if the line segment between P1 and P2 is A, the line segment between P2 and P3 is B, and the line segment between P3 and P1 is C, the circumscribing of three points P1, P2, and P3 The radius r of the circle is given by the following equation (10).
r = (A + B + C) / (4 · Sa) (10)

Here, Sa is the area of the triangle P1-P2-P3,
Sa = (λ · (λ−A) · (λ−B) · (λ−C)) ^1/2 (11)
However, λ = (A + B + C) / 2

Moreover, each line segment A, B, C is calculated | required by each following formula | equation from each coordinate value.
A = ((y2−y1) ² + (x2−x1) ² ) ^1/2 (12)
B = ((y3−y2) ² + (x3−x2) ² ) ^1/2 (13)
C = ((y1−y3) ² + (x1−x3) ² ) ^1/2 (14)

Next, the process proceeds to S109, where the lateral slope of the road surface calculated last time is based on the relationship between the vertical acceleration (Fz / m) with respect to the road surface, the translational velocity vx in the front-rear direction, the turning radius r, and the lateral slope θKn-1 calculated previously. An increase in θKn−1 is calculated as a first road surface lateral slope increase ΔθKz. The previous calculation is based on the relationship between the lateral acceleration (d ² y / dt ² ) (= (Fy / m)), the longitudinal translational velocity vx, the turning radius r, and the previously calculated lateral slope θKn−1 of the road surface. The increase in the lateral slope θKn−1 of the road surface is calculated as the second road surface lateral slope increase ΔθKy.

Specifically, the first road surface lateral slope increase ΔθKz is calculated by the following equation (15).
ΔθKz = ((Fz / m) −g · cos θKn-1−ω · vx · sin θKn-1)
/ (Ω · vx · cosθKn-1−g · sinθKn-1) (15)
Further, the second road surface lateral slope increase ΔθKy is calculated by the following equation (16).
ΔθKy = − ((Fy / m) + g · sinθKn-1−ω · vx · cosθKn-1)
/ (Ω · vx · sinθKn-1 + g · cosθKn-1) (16)
Here, ω is an angular velocity, and ω = vx / r.

  That is, as shown in FIG. 6, with respect to the vehicle local coordinate system, the following equations (17) and (18) are obtained with respect to the vertical and horizontal components using the lateral slope θKn of the road surface calculated this time from the relationship of force balance. Derived.

Fz = m · g · cos θKn + (m · vx ² / r) · sin θKn (17)
Fy = −m · g · sin θKn + (m · vx ² / r) · cos θKn (18)
Here, assuming that there is no sudden change in the lateral slope of the road surface, the following equations (19) and (20) are obtained using the previously calculated lateral slope θKn-1 of the road surface and an increase ΔΔK in the lateral slope of the road surface. .
cosθKn = cos (θKn-1 + ΔθK) ≈cosθKn-1−ΔθK · sinθKn-1 (19)
sinθKn = sin (θKn-1 + ΔθK) ≈sinθKn-1 + ΔθK · cosθKn-1 (20)

  Then, the above equations (19) and (20) are substituted into equations (17) and (18), and these equations (17) and (18) are modified with respect to the road surface lateral slope increment ΔθK, and the respective road surface lateral slopes are transformed. By using the increments ΔθK as ΔθKz and ΔθKy, the above equations (15) and (16) are obtained.

Thereafter, the process proceeds to S110, and the difference SK between the first road surface lateral slope increase ΔθKz and the second road surface lateral slope increase ΔθKy is calculated.
SK = ΔθKz−ΔθKy (21)

  Next, the process proceeds to S111, where it is determined whether or not the absolute value of the difference SK between the first road surface lateral slope increment ΔθKz and the second road surface lateral slope increment ΔθKy is equal to or smaller than a preset threshold C1. In the following cases, the process proceeds to S112.

In S112, the final road surface slope increase ΔθK is calculated by the following equation (22), and this road surface slope increase ΔθK is added to the previously calculated road surface slope θKn-1 (expression (23)). Output as the current road side slope θKn and exit the program.
ΔθK = (ΔθKz + ΔθKy) / 2 (22)
θKn = θKn-1 + ΔθK (23)
In the above equation (22), the first road surface lateral slope increment ΔθKz and the second road surface lateral slope increment ΔθKy are calculated by calculating the final road surface lateral slope increment ΔθK with a weight of 1: 1. However, depending on the characteristics of the sensor, the calculation may be performed with weighting that places importance on either value instead of 1: 1.

  On the other hand, if the absolute value of the difference SK between the first road surface lateral slope increment ΔθKz and the second road surface lateral slope increment ΔθKy exceeds the preset threshold C1 in S111 described above, the process proceeds to S113. The extrapolated value θK1n that is predicted this time from several lateral (θ, for example) road surface slopes θK obtained in the past is calculated by a known interpolation method (for example, Lagrange interpolation or spline interpolation) or a least square method. Calculate with the calculated function.

Thereafter, the process proceeds to S114, where the lateral slope θKn of the current road surface is calculated and output based on the extrapolated value θK1n calculated in S113, and the program is exited. Specifically, first, the first road surface lateral slope θKnz is calculated from the first road surface lateral slope increment ΔθKz and the previously calculated road surface lateral slope θKn-1 by the following equation (24). The second road surface slope θKny is calculated from the second road surface slope increase ΔθKy and the previously calculated road surface slope θKn−1 according to the equation (25).
θKnz = θKn-1 + ΔθKz (24)
θKny = θKn-1 + ΔθKy (25)

  Then, the extrapolation value θK1n is compared with the lateral slope θKnz of the first road surface, and the extrapolation value θK1n is compared with the lateral slope θKny of the second road surface, and the lateral slope θKnz of the first road surface is compared with the second road surface. When both the lateral slopes θKny are separated from the extrapolation value θK1n by a set value (value obtained in advance through experiments or the like), the extrapolation value θK1n is determined as the lateral slope θKn of the current road surface.

  Further, as a result of comparison between the extrapolation value θK1n and the first road surface lateral inclination θKnz, and the extrapolation value θK1n and the second road surface lateral inclination θKny, at least one of them is within the set value range from the extrapolation value θK1n. If it is within the range, the value closer to the extrapolation value θK1n is determined as the lateral slope θKn of the current road surface.

  Thus, in the embodiment of the present invention, the control unit 6 includes the recognition means, the translation speed calculation means, the vertical acceleration detection means, the turning radius calculation means, the road surface lateral inclination calculation means, the yaw angle calculation means, the pitch angle. Functions are provided as a calculation means and a roll angle calculation means.

  And as mentioned above, since each state quantity is calculated | required in the control part 6, the error by a wheel slip which arises by the estimation using the conventional wheel speed sensor does not generate | occur | produce, but accuracy. A good state quantity can be detected. Further, there is no error due to the road surface condition that occurs in the vehicle height sensor, and it is possible to detect the state quantity with high accuracy.

  In the present embodiment, the marker 4 has an elliptical shape, but may have another shape as long as the road width direction and the traveling direction can be distinguished (for example, a rectangle or the like). ).

  In the present embodiment, the longitudinal translational velocity vx, the lateral translational velocity vy, the pitch angle θP, the pitch angular velocity (dθP / dt), the roll angle θR, the roll angular velocity (dθR / dt), and the yaw angle θY. In this example, the state quantities of the yaw angular velocity (dθY / dt), the vehicle mass m, and the lateral slope θK of the road surface are estimated, but it is not necessary to estimate all of these. In that case, parameters necessary for estimation can also be deleted. For example, if the pitch angle θP and the pitch angular velocity (dθP / dt) are not estimated, it is not necessary to detect a change in the major axis direction of the marker 4.

Configuration explanatory diagram of a vehicle including a state quantity estimating device that travels on a road surface Flow chart of state quantity estimation program Illustration of front / rear and lateral translation speed and yaw angle detection Explanation of roll angle and pitch angle detection Illustration of calculation of turning radius Explanatory drawing of balance of each force by lateral inclination

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Vehicle 2 State quantity estimation apparatus 3 Road surface 4 Marker (marker means)
5 Camera 6 Control section (recognition means, translation speed calculation means, vertical acceleration detection means, turning radius calculation means, road surface lateral inclination calculation means, yaw angle calculation means, pitch angle calculation means, roll angle calculation means)
7fl, 7fr, 7rl, 7rr Wheel 8fl, 8fr, 8rl, 8rr Force detection sensor 9 Lateral acceleration sensor (lateral acceleration detection means)
Agent Patent Attorney Susumu Ito

Claims (13)

Recognizing means for recognizing a marker means on a road surface in which a change in relative position with respect to the own vehicle accompanying the movement of the own vehicle is discriminable
Translation speed calculation means for calculating the translation speed of the host vehicle based on the recognition result of the position of the marker means;
Vertical acceleration detecting means for detecting vertical acceleration acting on the host vehicle;
Lateral acceleration detecting means for detecting lateral acceleration acting on the host vehicle;
Turning radius calculating means for calculating the turning radius of the host vehicle;
The relationship between the vertical acceleration, the translation speed, the turning radius, and the lateral slope of the road surface with respect to the vehicle previously calculated, the lateral acceleration, the translation speed, the turning radius, and the lateral surface of the road surface with respect to the vehicle previously calculated. A road surface side inclination calculating means for calculating an increase in the lateral inclination of the road surface with respect to the host vehicle calculated above based on at least one of the relationships of the inclination, and calculating the lateral inclination of the road surface with respect to the current vehicle;
A vehicle state quantity estimation apparatus comprising: The recognizing means is capable of detecting a change in relative position from the previously detected position in the front-rear direction with respect to the own vehicle accompanying the movement of the own vehicle of the marker means,
The translation speed calculating means calculates a translation speed in the front-rear direction of the host vehicle based on a change in relative position from a previously detected position in the front-rear direction relative to the host vehicle as the marker unit moves. The vehicle state quantity estimating device according to claim 1, wherein The recognizing means is capable of detecting a change in relative position from the previously detected position in the lateral direction with respect to the own vehicle accompanying movement of the own vehicle of the marker means,
The translation speed calculation means calculates the lateral translation speed of the host vehicle based on a change in relative position from the previously detected position in the lateral direction relative to the host vehicle accompanying the movement of the host vehicle of the marker means. The vehicle state quantity estimation apparatus according to claim 1 or 2, wherein the vehicle state quantity estimation apparatus is characterized. The recognizing means is capable of detecting a change in relative position from the previously detected position in the rotation direction relative to the own vehicle accompanying the movement of the own vehicle of the marker means,
Yaw angle calculating means for calculating at least one of a yaw angle and a yaw angular velocity based on a change in relative position from a previously detected position of the rotation direction with respect to the own vehicle accompanying the movement of the own vehicle by the marker means. The vehicle state quantity estimating device according to any one of claims 1 to 3, wherein The recognizing means is capable of detecting a change from the previously detected value of the dimension in the front-rear direction relative to the own vehicle accompanying the movement of the own vehicle of the marker means,
Pitch angle calculating means for calculating at least one of a pitch angle and a pitch angular velocity based on a change from a previously detected value of a dimension in the front-rear direction with respect to the own vehicle accompanying the movement of the own vehicle of the marker means. The vehicle state quantity estimating device according to any one of claims 1 to 4. The recognizing means is capable of detecting a change from the previously detected value of the dimension in the lateral direction with respect to the own vehicle accompanying the movement of the own vehicle of the marker means,
A roll angle calculating means for calculating at least one of a roll angle and a roll angular velocity based on a change from a previously detected value of a dimension in a lateral direction with respect to the own vehicle accompanying the movement of the own vehicle of the marker means. The vehicle state quantity estimating device according to any one of claims 1 to 5.   The vertical acceleration detecting means detects a vertical force acting on each wheel of the host vehicle to obtain a sum of these, and calculates the sum by dividing the sum by the mass of the host vehicle. The vehicle state quantity estimation apparatus according to any one of claims 1 to 6.   The mass of the host vehicle is obtained by dividing the sum of vertical forces acting on the wheels of the host vehicle by the gravitational acceleration when the calculated lateral slope of the road surface with respect to the host vehicle is smaller than a preset threshold value. The vehicle state quantity estimating device according to claim 7, wherein the vehicle state quantity estimating device is calculated in advance.   The vehicle state quantity estimating apparatus according to any one of claims 1 to 8, wherein the turning radius calculation means approximately calculates the turning radius from a past travel locus of the host vehicle.   The road surface side inclination calculating means is based on the relationship between the vertical acceleration, the translation speed, the past traveling road of the own vehicle, and the lateral inclination of the road surface with respect to the previous vehicle. The increase in the lateral slope of the vehicle is calculated as a first road surface lateral slope increase, and the relationship between the lateral acceleration, the translational speed, the previous travel path of the host vehicle, and the previously calculated lateral slope of the road surface relative to the host vehicle is calculated. Based on the above, the previously calculated increase in the lateral slope of the road surface with respect to the host vehicle is calculated as the second increased lateral slope, and the first increased lateral slope and the second increased lateral slope If the absolute value of the difference between the two is within a preset threshold value, the first road surface lateral slope increment and the second road surface lateral slope increment are calculated and processed with a predetermined weighting. Calculate the increase in road slope 10. The road slope according to any one of claims 1 to 9, characterized in that the final road slope increase is added to the calculated road slope relative to the host vehicle to obtain the current road slope relative to the host vehicle. The vehicle state quantity estimation apparatus according to one.   The road surface side inclination calculating means is based on the relationship between the vertical acceleration, the translation speed, the past traveling road of the own vehicle, and the lateral inclination of the road surface with respect to the previous vehicle. The increase in the lateral slope of the vehicle is calculated as a first road surface lateral slope increase, and the relationship between the lateral acceleration, the translational speed, the previous travel path of the host vehicle, and the previously calculated lateral slope of the road surface relative to the host vehicle is calculated. Based on the above, the previously calculated increase in the lateral slope of the road surface with respect to the host vehicle is calculated as the second increased lateral slope, and the first increased lateral slope and the second increased lateral slope If the absolute value of the difference exceeds a preset threshold value, an extrapolation value is calculated from the lateral slope of the road surface with respect to the host vehicle calculated in the past, and the extrapolated value and the road surface with respect to the host vehicle calculated last time are calculated. Next to the first road surface A comparison is made between the lateral slope of the first road surface obtained by adding the increase in the slope and the lateral slope of the second road surface obtained by adding the second road surface slope increase to the lateral slope of the road surface with respect to the host vehicle calculated previously. The vehicle state quantity estimating apparatus according to any one of claims 1 to 10, wherein a lateral inclination of a road surface with respect to the current vehicle is determined.   The road surface lateral slope calculating means determines that the extrapolated value is the current self-automatic value when the lateral slope of the first road surface and the lateral slope of the second road surface are separated from the extrapolated value by more than a set value. 12. The vehicle state quantity estimating device according to claim 11, wherein the vehicle state quantity estimating device is determined as a lateral inclination of the road surface with respect to the vehicle.   The road surface lateral slope calculating means is configured to calculate the extrapolated value when at least one of the lateral slope of the first road surface and the lateral slope of the second road surface is within a set value range from the extrapolated value. 12. The vehicle state quantity estimating apparatus according to claim 11, wherein a value closer to is determined as a lateral slope of the road surface relative to the current vehicle.

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