WO2017168588A1

WO2017168588A1 - Measurement device, measurement method, and program

Info

Publication number: WO2017168588A1
Application number: PCT/JP2016/060234
Authority: WO
Inventors: 諒子新原; 加藤　正浩
Original assignee: パイオニア株式会社
Priority date: 2016-03-29
Filing date: 2016-03-29
Publication date: 2017-10-05

Abstract

This measurement device acquires distances from a moving body to two ground objects at a first clock time and a second clock time, and angles formed between the direction of movement of the moving body and directions of the two ground objects from the moving body. On the basis of the acquired results of the first acquisition unit, a change amount in the direction of movement of the moving body from the first clock time to the second clock time is calculated.

Description

Measuring apparatus, measuring method, and program

The present invention relates to a technique for detecting a change in the traveling direction of a moving object.

A method for recognizing an object existing in front of a moving body and correcting the yaw rate of the moving body is known. Patent Document 1 describes a method of recognizing a fixed object existing in front of a moving body and correcting a deviation amount of a yaw rate sensor based on a movement trajectory in which the fixed object moves relative to the host vehicle. ing.

JP 2012-66777 A

In the method described in Patent Document 1, in addition to the above movement trajectory, parameters used for calculating the estimated yaw rate, such as the vehicle speed, the deviation from the turning radius, and the lateral movement amount in which the fixed object moves relatively in the lateral direction, are used. In many cases, the deviation amount of the sensor that acquires these parameters must also be taken into consideration.

The above are examples of problems to be solved by the present invention. An object of the present invention is to provide a measuring apparatus capable of calculating the azimuth angle of a moving body with one sensor and obtaining the amount of change in the traveling direction.

Invention of Claim 1 is a measuring device, Comprising: Each distance from a mobile body to two features in each of 1st time and 2nd time, and direction of these 2 features seen from the mobile body And a moving direction of the moving body from the first time to the second time based on an acquisition result of the first acquiring section. And a calculating unit that calculates the amount of change.

The invention according to claim 7 is a measuring method executed by a measuring device, wherein each distance from a moving body to two features at each of a first time and a second time and the distance from the moving body. Based on the acquisition result of the 1st acquisition process and the 1st acquisition process which acquires the angle which each direction of two features and the advancing direction of the above-mentioned moving body make, the above-mentioned from the 1st time to the 2nd time And a calculating step of calculating the amount of change in the traveling direction of the moving body.

The invention according to claim 8 is a program executed by a measuring apparatus including a computer, and each distance from a moving body to two features at each of a first time and a second time and from the moving body From the first time to the second time based on the acquisition result of the first acquisition unit and the first acquisition unit that acquire the angles formed by the direction of the two features and the traveling direction of the moving body. The computer is caused to function as a calculation unit that calculates an amount of change in the traveling direction of the moving body.

The calculation method of the azimuth change amount according to the first example of the first embodiment will be described. The calculation method of the azimuth change amount according to the second example of the first embodiment will be described. It is a block diagram which shows the structure of the coefficient update apparatus by 1st Example. It is a flowchart of the coefficient update process by 1st Example. The calculation method of the azimuth change amount according to the second embodiment will be described. It is a figure explaining a map coordinate system and a vehicle coordinate system. The calculation method of the azimuth angle of the vehicle by 2nd Example is shown. It is a block diagram which shows the structure of the coefficient update apparatus by 2nd Example. It is a flowchart of the coefficient update process by 2nd Example. The example of the positional relationship of three features and a moving vehicle is shown. The other example of the positional relationship of three features and a moving vehicle is shown.

In a preferred embodiment of the present invention, the distance from the moving body to the two features at the first time and the second time, the direction of the two features viewed from the moving body, and the progress of the moving body, respectively. A first acquisition unit that acquires an angle formed by each direction, and a calculation that calculates an amount of change in the traveling direction of the moving body from the first time to the second time based on an acquisition result of the first acquisition unit A section.

In the measurement apparatus, the distance from the moving body to the two features at the first time and the second time, the direction of the two features viewed from the moving body, and the traveling direction of the moving body are determined. Get the angle between each. And based on the acquisition result of the said 1st acquisition part, the variation | change_quantity of the advancing direction of the said mobile body from the said 1st time to the said 2nd time is calculated. Thereby, the amount of change in the traveling direction of the moving body can be calculated using any feature that can be measured from the moving body.

One aspect of the measurement apparatus further includes a second acquisition unit that acquires a distance between the two features, and the calculation unit is based on the acquisition results of the first acquisition unit and the second acquisition unit, An amount of change in the traveling direction of the moving body from the first time to the second time is calculated. In this aspect, the distance between two features is acquired, and the amount of change in the traveling direction of the moving object is calculated using this distance. In a preferred example in this case, the second acquisition unit is based on the distance between the two features and the angle formed by the moving direction of the moving body and the direction of each of the two features. Get the distance between two features. In another preferred example, the second acquisition unit acquires a distance between the two features based on map information.

According to another aspect of the measurement apparatus, the output result at the second time of the angular velocity sensor mounted on the moving body is calculated based on the change amount in the traveling direction per unit time. To a correction unit that corrects the first information for calculating the yaw rate of the mobile body. In this aspect, the first information for calculating the yaw rate of the moving body is corrected based on the amount of change in the traveling direction per unit time. In a preferred example, the first information includes sensitivity and offset of the angular velocity sensor.

In another preferred embodiment of the present invention, the measuring method executed by the measuring device includes the distance from the moving body to the two features at the first time and the second time, and the distance from the moving body. Based on the acquisition result of the 1st acquisition process and the 1st acquisition process which acquires the angle which each direction of two features and the advancing direction of the above-mentioned moving body make, the above-mentioned from the 1st time to the 2nd time And a calculation step of calculating a change amount in the traveling direction of the moving body. Thereby, the amount of change in the traveling direction of the moving body can be calculated using any feature that can be measured from the moving body.

In another preferred embodiment of the present invention, the program executed by the measuring device including the computer is the distance from the moving body to the two features and the moving body at the first time and the second time, respectively. From the first time to the second time based on the acquisition result of the first acquisition unit and the first acquisition unit that acquire the angles formed by the direction of the two features and the traveling direction of the moving body. The computer is caused to function as a calculation unit that calculates the amount of change in the traveling direction of the moving body. Thereby, the amount of change in the traveling direction of the moving body can be calculated using any feature that can be measured from the moving body. This program can be stored in a storage medium and used.

Hereinafter, preferred embodiments of the present invention will be described with reference to the drawings.

[1] Background In a vehicle position estimation system mounted in a conventional car navigation device, the moving state of a vehicle is measured using a speed calculated from a vehicle speed pulse and an azimuth calculated from an output of a gyro sensor, A compound navigation system that estimates the current position by integrating with GPS information is used. In order to improve the vehicle position estimation accuracy by the composite navigation system, it is necessary to accurately grasp the vehicle body speed and the azimuth (yaw angle).

The sensitivity and offset of the gyro sensor have characteristics that change with temperature and vibration. Therefore, if the angular velocity is integrated in a state including these errors, the errors accumulate, and the calculated azimuth angle deviates greatly from the actual value. Therefore, in order to estimate the azimuth angle with high accuracy, it is necessary to continuously correct the sensitivity and offset of the gyro sensor.

In the conventional car navigation apparatus, the sensitivity and offset are corrected using the direction change amount based on GPS information. For this reason, the accuracy of correction deteriorates in an environment such as an urban area where the GPS reception state is poor. Moreover, it cannot correct | amend in the environment where GPS positioning cannot be carried out like a tunnel or an underground parking lot. Therefore, it is required to continuously correct the sensitivity and offset regardless of the GPS reception state.

The coefficient updating apparatus according to the present embodiment calculates the azimuth change amount of the vehicle based on the measurement result of the feature by the external sensor without using the GPS information, and corrects the sensitivity and offset of the gyro sensor. Examples of the external sensor include a camera, LiDAR (Light Detection And Ranging), and a millimeter wave radar.

Specifically, the coefficient updating device corrects the sensitivity and offset of the gyro sensor through the following steps.
(1) Two features are detected at time t-1 and time t.
(2) Based on the feature measurement result at each time, the amount of change in the azimuth angle of the vehicle between time t-1 and time t is calculated.
(3) The sensitivity coefficient and the offset coefficient are estimated by the successive least square method.

[2] Gyro sensor sensitivity and offset estimation method The relationship between the true angular velocity _{Ψ_dot (t)} and the angular velocity ω _t detected by the gyro sensor is expressed as follows using the sensitivity coefficient α and the offset coefficient β. be able to.

When the change amount of the azimuth angle of the vehicle (hereinafter referred to as “azimuth angle change amount”) ΔΨ _L can be obtained from the feature measurement value by the external sensor, the following is obtained by dividing this by the time interval Δt. The angular velocity is calculated as follows.

When the angular velocity (also referred to as “measured yaw rate”) obtained from the feature measurement value by the external sensor is regarded as the true angular velocity, it can be expressed as follows.

So if you put

It can be represented by the following primary expression.

Thus, if there are multiple data x _t and y _t, the recursive least square method, it is possible to obtain the α and beta. That is, if the azimuth angle change amount ΔΨ of the vehicle can be acquired using an external sensor, the sensitivity and offset of the gyro sensor can be estimated.

[3] Method of calculating azimuth angle change amount Hereinafter, a method for obtaining the azimuth angle change amount ΔΨ of the vehicle using an external sensor will be described.

[3.1] First Example In the first example, the azimuth angle change amount ΔΨ is obtained using the measured value of the feature by the external sensor.

[3.1.1] Azimuth angle change calculation method (first example)
When two or more identical features can be measured at time t-1 and time t, the azimuth change amount of the vehicle can be calculated using the measurement result. Here, it is assumed that the relative distance and relative angle (r, φ) of the feature with respect to the host vehicle can be acquired from the external sensor. FIG. 1 is a diagram for explaining a method of calculating the azimuth change amount of a vehicle according to the first example of the first embodiment. In the example of FIG. 1, it is assumed that the feature A and the feature B can be measured by the external sensor at time t-1 and time t. In the first example, it is necessary that the same two features can be measured by the external sensor at each time.

The azimuth angle variation ΔΨ of the vehicle is expressed as follows using the azimuth angles φ _{A, t-1} , φ _{A, t} of the feature A at time t-1 and time t and the angles Δθ, γ in FIG. Can be calculated.

First, from the relationship between the inner and outer angles of the triangle,

Is obtained. Therefore, the azimuth angle change amount ΔΨ is

It is obtained by.

Here, the angle θ _t−1 is obtained from the cosine theorem.

It becomes. Similarly, the angle θ _t is

It becomes.

Therefore, the azimuth angles φ _{A, t−1} , φ _{A, t} obtained by the external sensor and the angles θ _t−1 , θ _t obtained by the above equations (8), (9) are _expressed by equation (7). By substituting into, the azimuth angle change amount ΔΨ can be calculated.

[3.1.2] Azimuth angle change calculation method (second example)
In the first example described above, the angle on the side of the feature A is used, but the azimuth change amount ΔΨ can be calculated in the same manner even if the angle on the side of the feature B is used. FIG. 2 is a diagram for explaining a method of calculating the azimuth change amount of the vehicle according to the second example of the first embodiment. In the example of FIG. 2 also, it is assumed that the feature A and the feature B can be measured by the external sensor at time t−1 and time t. In the second example, it is necessary that the same two features can be measured by the external sensor at each time.

The azimuth angle change amount ΔΨ of the vehicle is expressed as follows using the azimuth angles φ _{B, t−1} , φ _{B, t} of the feature A at time t−1 and time t and the angles Δθ ′ and γ ′ in FIG. It can be calculated as follows.

Is obtained.

Therefore, the azimuth angle change ΔΨ is

It is obtained by.

Here, the angle θ ′ _t−1 is obtained from the cosine theorem.

It becomes. Similarly, the angle θ ′ _t is

It becomes.

Therefore, the azimuth angles φ _{B, t−1} , φ _{B, t} obtained by the external sensor and the angles θ ′ _t−1 , θ ′ _t obtained by the above equations (12), (13) By substituting into 11), the azimuth angle change amount ΔΨ can be calculated.

[3.1.3] Feature Measured Value In the first and second examples above, the relative distance r of the feature and the relative angle φ of the feature can be obtained from the external sensor. When the relative position (x, y) of the feature can be obtained instead of the distance r and the relative angle φ, the relative distance r and the relative angle φ can be obtained from the relative position (x, y) by the following formula and used. That's fine.

[3.1.4] Distance between features In the first and second examples above, the distance R between two features is used in the equations (8), (9), (12), and (13). is doing. The distance R between features can be acquired by the following method.

First, the distance R between the features can be calculated using the feature measurement value by the external sensor. Specifically, when the relative distance r and the relative angle φ of the feature with respect to the host vehicle can be acquired from the external sensor, the distance R between the features can be calculated as follows using the cosine theorem.

On the other hand, when the relative position (x, y) of the feature relative to the host vehicle can be acquired from the external sensor, the distance R between the features can be calculated as follows.

In addition, when a high-accuracy map having position information of features can be used, the distance R between the features may be acquired from the high-accuracy map. When the distance between features is calculated from the feature measurement value by the external sensor, the accuracy of the distance between features also changes depending on the measurement accuracy. That is, if the measurement accuracy is poor, the accuracy of the calculated distance between the features is also deteriorated, and the accuracy of the azimuth change amount of the vehicle to be calculated later is also deteriorated. When a high-precision map is used, this problem can be avoided and the accuracy of the obtained azimuth angle change amount of the vehicle can be improved.

[3.1.5] Coefficient Update Device Next, a coefficient update device that updates the sensitivity coefficient α and the offset coefficient β of the gyro sensor will be described. FIG. 3 is a block diagram showing the configuration of the coefficient update device 10 according to the first embodiment. As illustrated, the coefficient update device 10 includes a gyro sensor 11, an external sensor 12, a traveling direction acquisition unit 13, a feature measurement unit 14, an inter-feature distance calculation unit 15, a coefficient calculation unit 16, And an azimuth angle variation calculation unit 17. The traveling direction acquisition unit 13, the feature measurement unit 14, the feature distance calculation unit 15, the coefficient calculation unit 16, and the azimuth change amount calculation unit 17 execute a program prepared in advance by a computer such as a CPU. This can be realized.

The gyro sensor 11 supplies the detected angular velocity ω _t to the traveling direction acquisition unit 13 and the coefficient calculation unit 16. The traveling direction acquisition unit 13 acquires the traveling direction Hd of the vehicle based on the angular velocity ω _t supplied from the gyro sensor 11 and supplies it to the feature measurement unit 14.

The external sensor 12 is, for example, a camera, LiDAR, millimeter wave radar, or the like. The feature measuring unit 14 measures the distance to the feature and the angle with the feature based on the output of the external sensor 12. Specifically, the feature measuring unit 14 measures the distances (relative distances) r _{A, t−1} , r _{B, t−1} from the vehicle to the two features A, B at time t−1. At the same time, the azimuth angles (relative angles) φ _{A, t−1} , φ _{B, t−1} of the two features A and B with respect to the traveling direction Hd _t−1 of the vehicle supplied from the traveling direction acquisition unit 13 are calculated. Then, the distance between the features is supplied to the distance calculation unit 15 and the azimuth angle change calculation unit 17. In addition, the feature measurement unit 14 measures the distances r _{A, t} , r _{B, t} from the vehicle to the two features A, B at the time t, and the vehicle supplied from the traveling direction acquisition unit 13 two features a to the traveling direction Hd _t, the azimuth angle phi _{a, t} of B, calculates the φ _{B, t,} and supplies the feature distance calculation unit 15 and azimuth angle change amount calculation unit 17.

Based on the distances r _A and r _B and the azimuth angles φ _A and φ _B of the two features A and B measured by the feature measuring unit 14, the inter-feature distance calculation unit 15 uses the above equation (15). A distance R between the features A and B is calculated and supplied to the azimuth angle change amount calculation unit 17. In addition, when a high precision map can be utilized, the distance calculation part 15 between features may acquire the distance R between features from a high precision map.

The azimuth angle variation calculation unit 17 includes the azimuth angles φ _{A, t−1} , φ _{B, t−1} , φ _{A, t} , φ _{B, t} , and distance between features supplied from the feature measurement unit 14. Based on the distance R between the features calculated by the calculation unit 15, the azimuth change amount ΔΨ of the vehicle is calculated by the above formulas (7) to (9) or the formulas (11) to (13) to calculate the coefficient. 16 is supplied.

Coefficient calculation unit 16, and the angular velocity omega _t supplied from the gyro sensor 11, based on the azimuth angle variation calculating unit 17 on the supplied azimuth angle variation [Delta] [Psi], by the aforementioned equation (2) to (3), The sensitivity coefficient α and the offset coefficient β of the gyro sensor are calculated and updated.

In the above configuration, the feature measurement unit 14 is an example of the first acquisition unit of the present invention, the azimuth change amount calculation unit 17 is an example of the calculation unit of the present invention, and the inter-feature distance calculation unit 15 is the main acquisition unit. It is an example of the 2nd acquisition part of invention, and a coefficient calculation part is an example of the correction | amendment part of this invention. The azimuth angle change amount corresponds to the change amount in the traveling direction in the present invention.

[3.1.6] Coefficient Update Process Next, the coefficient update process performed by the coefficient update apparatus 10 will be described. FIG. 4 is a flowchart of the coefficient update process. In the following description, the first example of the method for calculating the azimuth angle change amount described above is used.

First, the coefficient updating unit 10, the external sensor 12 detects the feature A, B (Step S10), and calculates an angle theta _t by the formula (9) described above (step S11). Next, the coefficient updating apparatus 10 determines whether or not flag = 1 (step S12). Note that “flag” is reset to “0” at the start of processing. If flag = 1 is not satisfied (step S12: NO), the coefficient updating apparatus 10 sets “1” in the flag (step S13), and returns to step S10.

On the other hand, when flag = 1 (step S12: YES), the features A and B are detected at two times and the angles θ _t−1 and θ _t are obtained. time and azimuth angle phi _{a, t-1} and the angle theta _t-1 of the previous feature a, the azimuth angle phi _{a, t} and angle theta _t of feature a at the current time, using the above-described formula (7) Then, the azimuth angle change amount ΔΨ is calculated (step S14).

Next, the coefficient updating apparatus 10 calculates the true angular velocity (measured yaw rate) _{Ψ_dot (t)} from the azimuth change amount ΔΨ and the time interval Δt using the equation (2) (Step S15), and obtained. From the measured yaw rate _{Ψ_dot (t)} and the output ω _{t of the} gyro sensor, the sensitivity coefficient α and the offset coefficient β are calculated and updated by the above equation (3) (step S16).

[3.2] Second embodiment [3.2.1] Method of calculating azimuth angle change amount In the second embodiment, the azimuth angle change amount of the vehicle using a high-accuracy map and a feature measurement result by an external sensor. Is calculated. FIG. 5 is a diagram for explaining a method of calculating the azimuth change amount according to the second embodiment. In FIG. 5, the position of the vehicle is shown on the map coordinate system (X _m , Y _m ). Here, the relationship between the map coordinate system and the vehicle coordinate system is shown in FIG. As shown in FIG. 6 (A), map coordinates system is defined by X _m-axis and the Y _m axis. On the other hand, as shown in FIG. 6 (B), the vehicle coordinate system is defined by an _Xv axis indicating the front-rear direction of the vehicle, a _Yv axis indicating the left-right direction of the vehicle, and a _Zv axis indicating the vertical direction of the vehicle. Is done.

Returning to FIG. 5, in the second embodiment, first, at time t−1, at least two features registered in the high-precision map are measured using an external sensor. In the example of FIG. 5, the feature A and the feature B are measured. Then, the azimuth angle Ψ _t−1 of the vehicle is calculated from the position information of the features A and B obtained from the high-accuracy map and the measurement result by the external sensor.

Next, at time t, similarly, at least two features registered in the high-precision map are measured using the external sensor. In the example of FIG. 5, the feature C and the feature D are measured. And the azimuth | direction angle (psi) _{t of a} vehicle is calculated from the positional information on the features C and D obtained from a highly accurate map, and the measurement result by an external sensor.

Next, from the difference between the azimuth angles Ψ _t−1 and Ψ _t of the vehicle at each time, a change amount ΔΨ of the azimuth angle of the vehicle between time t-1 and time t is obtained by the following equation.

In the second embodiment, since the azimuth angle of the vehicle can be calculated independently at each time, it is not necessary that the same two features can be detected by the external sensor at time t-1 and time t. In the example of FIG. 5, the external sensor detects the features A and B at time t−1 and detects the features C and D different from the features A and B at time t−1.

Next, a method for calculating the azimuth angle of the vehicle at each time will be described. FIG. 7 shows a method of calculating the azimuth angle of the vehicle according to the second embodiment. Now, the position (x _mA , y _mA ) of the feature A and the position (x _mB , y _mB ) of the feature A can be acquired from the high-precision map, and the relative position ( x _vA , y _vA ) and the relative position (x _vB , y _vB ) of the feature B can be acquired. The vector p from the feature B to the feature A is in the map coordinate system
[X _mA -x _mB y _mA -y _mB ] ^T
In the vehicle coordinate system,
[X _vA -x _vB y _vA -y _vB ] ^T
It is expressed. Here, it is set as follows.

The direction cosine matrix C from the map coordinate system to the vehicle coordinate system is as follows.

Therefore,

It becomes.

From Expression (20) × dx _m + Expression (21) × dy _m ,

Is obtained.

Further, from the equation (20) × dy _m −the equation (21) × dx _m ,

Is obtained. Therefore, the azimuth angle Ψ of the vehicle can be calculated using the equations (22) to (24).

Thus, the vehicle azimuth angles Ψ _t-1 and Ψ _t are calculated at time t-1 and time t, respectively, and are substituted into equation (17), whereby the azimuth angle change amount ΔΨ of the vehicle can be calculated.

[3.2.2] Coefficient Update Device Next, a coefficient update device according to the second embodiment will be described. FIG. 8 is a block diagram showing the configuration of the coefficient update device 20 according to the second embodiment. As shown in the figure, the coefficient update device 20 includes a gyro sensor 21, an external sensor 22, a feature measurement unit 23, a coefficient calculation unit 24, an azimuth change amount calculation unit 25, and a map database (DB) 26. Is provided. The feature measurement unit 23, the coefficient calculation unit 24, and the azimuth change amount calculation unit 25 can be realized by executing a program prepared in advance by a computer such as a CPU.

The gyro sensor 21 supplies the detected angular velocity ω _t to the coefficient calculation unit 24. The external sensor 22 is, for example, a camera, LiDAR, millimeter wave radar, or the like. The feature measurement unit 23 measures the relative position (x _v , y _v ) of the two features based on the output of the external sensor 22 and supplies the measured relative position (x _v , y _v ) to the azimuth angle change amount calculation unit 25.

The azimuth angle variation calculation unit 25 acquires the relative positions (x _m , y _m ) of the two features from the map DB 26 storing the high-accuracy map. Then, the azimuth angle change amount calculation unit 25 uses the relative positions (x _v , y _v ) and (x _m , y _m ) of the two features to calculate the azimuth angle Ψ _{t according} to equations (18) to (24). Is calculated. By performing this processing at two different times, the azimuth angle change amount calculation unit 25 calculates azimuth angles ψ _t−1 and ψ _t , calculates the azimuth angle change amount Δψ by equation (17), and calculates coefficients. To the unit 24.

Based on the angular velocity ω _t supplied from the gyro sensor 21 and the azimuth angle change amount ΔΨ supplied from the azimuth angle change amount calculation unit 25, the coefficient calculation unit 24 performs the following equations (2) to (3). The sensitivity coefficient α and the offset coefficient β of the gyro sensor are calculated and updated.

[3.2.3] Coefficient Update Processing Next, coefficient update processing according to the second embodiment will be described. FIG. 9 is a flowchart of the coefficient update process according to the second embodiment.

First, the coefficient update device 20 acquires the positions of two features by the external sensor 12 (step S20). Next, the coefficient update device 20 acquires the positions of these two features from the high-accuracy map stored in the map DB 26 (step S21). Next, the coefficient updating device 20 calculates the azimuth angle by the equations (18) to (24) based on the positions of the two features acquired from the external sensor and the positions of the two features acquired from the high-precision map. Ψ is calculated (step S22).

Next, the coefficient update device 20 determines whether or not flag = 1 (step S23). Note that “flag” is reset to “0” at the start of processing. If flag = 1 is not satisfied (step S23: NO), the coefficient updating apparatus 20 sets “1” in the flag (step S24), and the process returns to step S20.

On the other hand, if flag = 1 (step S23: YES), two features are detected at two times and azimuth angles Ψ _t−1 and Ψ _t are obtained. The azimuth angle change amount ΔΨ is calculated from the equation (17) (step S25).

Next, the coefficient updating device 20 calculates the true angular velocity (measured yaw rate) _{Ψ_dot (t)} from the azimuth angle change amount ΔΨ and the time interval Δt using the equation (2) (step S26). Then, the coefficient update device 20 calculates and updates the sensitivity coefficient α and the offset coefficient β from the measured yaw rate _{Ψ_dot (t)} and the output ω _{t of the} gyro sensor by the above-described equation (3) (step S27).

[4] Processing when three or more features can be measured In the above coefficient update processing, two features are measured, but when three or more features can be measured simultaneously, The azimuth angle change amount ΔΨ can be calculated by the method.

(A) Method of Using Average Value When three or more features can be measured simultaneously, a plurality of azimuth angle change amounts ΔΨ can be calculated, and the averaged value can be used to update the coefficient.

For example, when three features can be measured, combinations of the feature 1 and the feature 2, the feature 2 and the feature 3, and the feature 3 and the feature 1 can be selected as shown in FIG. In each combination, the azimuth angle change amount ΔΨ between time t-1 and time t is calculated by the coefficient update process described above. The azimuth angle change obtained by the combination of the feature 1 and the feature 2 is ΔΨ ₁₂ , the azimuth change obtained by the combination of the feature 2 and the feature 3 is ΔΨ ₂₃ , and the feature 3 and the feature Assuming that the azimuth change amount obtained by the combination of 1 is ΔΨ ₃₁ , a value obtained by averaging these can be used as the azimuth change ΔΨ as follows.

Thereby, the accuracy of the azimuth angle variation ΔΨ can be statistically improved.

(B) Method of selecting two features in consideration of the distance to the feature When three or more features can be measured at the same time, the azimuth based on the combination of two features with high reliability By obtaining the change amount, the azimuth change amount can be obtained with high accuracy. In general, the accuracy of the measurement by the external sensor decreases as the distance increases. Therefore, when three or more features can be measured at the same time, two features are selected from the closest distance from the vehicle, and the azimuth angle change is performed based on them by the method of the first embodiment or the second embodiment. The quantity ΔΨ is determined.

For example, when three features 1 to 3 can be measured as in the example of FIG. 10, the distance from the vehicle to the three features is L ₁ <L ₃ <L ₂ . Therefore, the coefficient updating device may obtain the azimuth angle change amount ΔΨ by using two features that are closer to the vehicle, that is, the feature 1 and the feature 3.

(C) Method of selecting two features in consideration of the distance between the features Usually, if the positions of the features are too close, the calculation accuracy decreases. Therefore, when able to measure more than two feature simultaneously, eliminating the two combinations of features closer than a predetermined threshold L _th, previously determined.

For example, when the three features 1 to 3 can be measured as in the example of FIG. 11, the distance between the features is compared with the threshold value L _th . In the example of FIG. 11, it is assumed that L ₁₂ <L _th , L ₂₃ > L _th , and L ₃₁ > L _th . In this case, combinations in which the distance between the features is shorter than the threshold L _th , that is, combinations of the features 1 and 2 are excluded, combinations of the features 2 and 3 and features 1 and features The azimuth angle change amount ΔΨ may be obtained using the combination of three. Specifically, considering the distance from the vehicle to the feature by the method (B), the feature update device is closer to the vehicle than the feature 2 (L ₁ <L ₂ ). Based on the combination of the feature 1 and the feature 3, the azimuth angle change amount ΔΨ may be obtained.

Instead, the azimuth angle change amount ΔΨ ₁₂ obtained by the combination of the feature 1 and the feature 2 and the azimuth angle change amount obtained by the combination of the feature 1 and the feature 3 using the method (A) described above. The average value of ΔΨ ₃₁ may be used as the azimuth angle change amount ΔΨ. In the above method, the predetermined distance is set as the threshold value L _th in advance, but instead, an average value of three or more measured distances between features may be used as the threshold value L _th .

[5] Modification In the above embodiment, either the method for calculating the distance R between the features from the measurement results of the two features or the method for obtaining the distance R between the features using the map data of the high-precision map. However, they may be used in combination. For example, in an area where high-precision map data exists, the distance between features R is obtained using high-precision map data, and in an area where no high-precision map data exists, the distance R between features is obtained from the measurement result of the features. May be. Moreover, it is good also as using the distance R between the features obtained by the more accurate one according to the condition of a vehicle.

The present invention can be used for an apparatus mounted on a moving body.

DESCRIPTION OF SYMBOLS 11, 21

Gyro sensor

12, 22 External sensor 13 Travel

direction acquisition part

14, 23 Feature measurement part 15 Distance between

feature calculation part

16, 24

Coefficient calculation part

17, 25 Azimuth change calculation part

Claims

The respective distances from the moving body to the two features at the first time and the second time, and the angles formed by the directions of the two features viewed from the moving body and the traveling direction of the moving body are acquired. A first acquisition unit;
Based on the acquisition result of the first acquisition unit, a calculation unit that calculates the amount of change in the traveling direction of the moving body from the first time to the second time;
A measuring apparatus comprising:
A second acquisition unit for acquiring a distance between the two features;
The calculation unit calculates the amount of change in the traveling direction of the moving body from the first time to the second time based on the acquisition results of the first acquisition unit and the second acquisition unit. The measuring apparatus according to claim 1.
The second acquisition unit calculates a distance between the two features based on a distance between the two features and an angle formed by a traveling direction of the moving body and a direction of each of the two features. The distance estimation apparatus according to claim 2, wherein the distance estimation apparatus acquires the distance.
The distance estimation apparatus according to claim 2, wherein the second acquisition unit acquires a distance between the two features based on map information.
Based on the amount of change in the traveling direction per unit time calculated based on the amount of change, for calculating the yaw rate of the mobile body from the output result at the second time of the angular velocity sensor mounted on the mobile body The measuring apparatus according to claim 1, further comprising a correction unit that corrects the first information.
The measuring apparatus according to claim 5, wherein the first information includes sensitivity and offset of the angular velocity sensor.
A measuring method executed by a measuring device,
The respective distances from the moving body to the two features at the first time and the second time, and the angles formed by the directions of the two features viewed from the moving body and the traveling direction of the moving body are acquired. A first acquisition step;
Based on the acquisition result of the first acquisition step, a calculation step of calculating the amount of change in the traveling direction of the moving body from the first time to the second time;
A measurement method comprising:
A program executed by a measuring apparatus including a computer,
The respective distances from the moving body to the two features at the first time and the second time, and the angles formed by the directions of the two features viewed from the moving body and the traveling direction of the moving body are acquired. A first acquisition unit,
A calculation unit that calculates a change amount in a traveling direction of the moving body from the first time to the second time based on an acquisition result of the first acquisition unit;
A program for causing the computer to function as:
A storage medium storing the program according to claim 8.