WO2020045057A1 - Posture estimation device, control method, program, and storage medium - Google Patents

Abstract

In the present invention, an on-board device 1 acquires a target measurement point group Ptag obtained by measuring, by a LIDAR 2 attached to the vehicle, a road sign having a surface perpendicular to the direction of advancement of the travelling road of the vehicle or a surface perpendicular to the width direction of the travelling road. The posture of the attachment of the LIDAR 2 to the vehicle is estimated on the basis of the longitudinal direction inclination of the road sign as calculated from the target measurement point group Ptag and with reference to a coordinate system based on installation information of the LIDAR 2.

Description

Attitude estimation device, control method, program, and storage medium

The present invention relates to a technique for estimating the attitude of a measuring device.

技術 Conventionally, there has been known a technology for estimating a position of a vehicle based on measurement data of a measurement device such as a radar or a camera. For example, Patent Literature 1 discloses a technique for estimating a self-position by comparing an output of a measurement sensor with position information of a feature registered on a map in advance. Patent Document 2 discloses a vehicle position estimation technology using a Kalman filter.

JP 2013-257742 A JP-A-2017-72422

The data obtained from the measuring device is a value in the coordinate system based on the measuring device, and is data depending on the attitude of the measuring device with respect to the vehicle, and so is converted into a value in the coordinate system based on the vehicle. There is a need. Therefore, when a deviation occurs in the posture of the measuring device, it is necessary to accurately detect the deviation and reflect the deviation in the data of the measuring device, or to correct the posture of the measuring device.

The present invention has been made to solve the above-described problem, and has as its main object to provide a posture estimating apparatus capable of suitably estimating a mounting posture of a measuring device attached to a moving body to the moving body. Purpose.

The invention according to claim is a posture estimating device, wherein a feature having a plane perpendicular to a traveling direction of a traveling path of the moving body or a plane perpendicular to a width direction of the traveling path is provided to the moving body. Acquisition means for acquiring a measurement point group measured by the attached measurement device, and calculated from the measurement point group, based on the inclination of the vertical plane with reference to a coordinate system based on the installation information of the measurement device, Estimating means for estimating an attachment posture of the measuring device to the moving body.

The invention described in the claims is a control method executed by the posture estimating apparatus, wherein the ground has a plane perpendicular to the traveling direction of the traveling path of the moving body or a plane perpendicular to the width direction of the traveling path. An object, an acquisition step of acquiring a group of measurement points measured by a measurement device attached to the moving body, and the vertical calculated based on the coordinate system based on the installation information of the measurement device, which is calculated from the measurement point group. An estimating step of estimating an attachment posture of the measuring device to the moving body based on a tilt of a surface.

Further, the invention according to the claims is a program executed by a computer, a feature having a plane perpendicular to the traveling direction of the traveling path of the moving body or a plane perpendicular to the width direction of the traveling path, Acquisition means for acquiring a group of measurement points measured by a measurement device attached to the moving body, and inclination of the vertical plane calculated from the measurement point group and based on a coordinate system based on installation information of the measurement device. And causing the computer to function as estimating means for estimating an attachment posture of the measuring device to the moving object based on the information.

FIG. 1 is a schematic configuration diagram of a vehicle system. It is a block diagram which shows the functional structure of an in-vehicle apparatus. FIG. 3 is a diagram illustrating a relationship between a vehicle coordinate system and a rider coordinate system represented by two-dimensional coordinates. FIG. 3 is a diagram illustrating a relationship between a vehicle coordinate system represented by three-dimensional coordinates and a rider coordinate system. FIG. 4 is a bird's-eye view of the vicinity of the vehicle when the vehicle runs near a road sign that is a detection target feature when estimating the roll angle of the rider. The positional relationship between the road sign and the target measurement point group when the measured surface of the road sign is viewed from the front is shown. 4 shows a target measurement point group and an extracted outer edge point group in a lidar coordinate system. The approximate straight line of each side of the rectangle formed by the outer edge point group is shown. It is a flowchart which shows the procedure of a roll angle estimation process. FIG. 5 is an overhead view of the vicinity of a vehicle when the vehicle travels near a road sign that is a detection target feature when estimating a rider's pitch angle. It is a flowchart which shows the procedure of a pitch angle estimation process. FIG. 4 is a bird's-eye view of the periphery of the vehicle when the vehicle travels along a lane marking serving as a detection target feature when estimating a yaw angle of a rider. FIG. 9 is a diagram showing a center point in a detection window by a circle. It shows the angle between the center line of the division line calculated for each detection window and the yaw direction reference angle. It is a flowchart which shows the procedure of a yaw angle estimation process. It is a flowchart which shows the specific example of a process based on the estimated value of a roll angle, a pitch angle, and a yaw angle.

According to a preferred embodiment of the present invention, the posture estimating device is configured to convert a feature having a plane perpendicular to the traveling direction of the traveling path of the moving body or a plane perpendicular to the width direction of the traveling path into the moving body. Acquisition means for acquiring a group of measurement points measured by a measurement device attached to the, based on the inclination of the vertical plane calculated from the measurement point group, based on a coordinate system based on the installation information of the measurement device Estimating means for estimating the posture of the measuring device attached to the moving body. According to this aspect, the posture estimating device is configured to attach the measuring device to the moving body with reference to a feature having a plane perpendicular to the traveling direction of the traveling path of the moving body or a plane perpendicular to the width direction of the traveling path. Can be suitably estimated.

In one aspect of the posture estimating apparatus, the acquiring unit recognizes a position of the feature based on feature information on the feature, so that the measurement point group measured by the measurement device at the position is determined by the feature. As a measurement point cloud. According to this aspect, the posture estimating apparatus grasps the position of a feature having a plane perpendicular to the traveling direction of the traveling path of the moving object or a plane perpendicular to the width direction of the traveling path, and measures a measurement point group of the feature. Can be suitably obtained.

In another aspect of the posture estimating device, the estimating means may include a roll of the measuring device based on the inclination calculated from a group of measurement points of a feature having a plane perpendicular to the traveling direction of the travel path. And estimating the attitude of the measuring device in the pitch direction based on the inclination calculated from a group of measurement points of a feature having a plane perpendicular to the width direction of the travel path. According to this aspect, the posture estimation device can appropriately estimate the posture of the measurement device in the roll direction and the posture of the measurement device in the pitch direction.

In a preferred example, the feature is a road sign provided on the travel path.

In another aspect of the attitude estimation device, the estimation unit extracts an outer edge point group forming an edge of the measurement point group, and calculates the inclination of the feature based on the outer edge point group. According to this aspect, the posture estimating apparatus can extract the outer edge point group representing the shape of the feature, and can appropriately calculate the inclination of the feature.

In another aspect of the attitude estimation device, the vertical plane is a rectangle, and the estimation unit calculates the inclination corresponding to each side of the rectangle from the outside point group, thereby calculating the inclination of the feature. calculate. According to this aspect, the posture estimation device can appropriately calculate the inclination of the feature from the outer edge point group.

In another aspect of the posture estimation apparatus, the slope of the feature is calculated by weighting the slope corresponding to each side based on the number of point groups forming each of the sides. According to this aspect, the posture estimation device can calculate the inclination of the feature from the outer edge point group with higher accuracy.

According to another preferred embodiment of the present invention, there is provided a control method executed by the posture estimating device, wherein the plane is a plane perpendicular to a traveling direction of a traveling path of a moving body or a plane perpendicular to a width direction of the traveling path. An acquisition step of acquiring a measurement point cloud measured by a measurement device attached to the moving body, and a feature having the coordinate system based on the installation information of the measurement device calculated from the measurement point cloud. Estimating the attitude of attaching the measuring device to the moving object based on the inclination of the vertical plane. By executing this control method, the posture estimating device can appropriately estimate the mounting posture of the measuring device on the moving body.

According to another preferred embodiment of the present invention, there is provided a program executed by a computer, comprising: a ground surface having a plane perpendicular to a traveling direction of a traveling path of a moving object or a plane perpendicular to a width direction of the traveling path. An object, an acquisition unit that acquires a measurement point group measured by a measurement device attached to the moving body, and the vertical calculated with reference to a coordinate system based on installation information of the measurement device, calculated from the measurement point group. The computer is caused to function as estimating means for estimating a mounting posture of the measuring device to the moving object based on a tilt of a surface. By executing this program, the computer can appropriately estimate the mounting posture of the measuring device on the moving body. Preferably, the program is stored in a storage medium.

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

[Schematic configuration]
FIG. 1 is a schematic configuration diagram of the vehicle system according to the present embodiment. The vehicle system shown in FIG. 1 includes an in-vehicle device 1 that performs control related to driving support of a vehicle, a lidar (Light Detection and Ranging or Laser Illuminated Detection And Ranging) 2, a gyro sensor 3, an acceleration sensor 4, and a GPS. And a sensor group such as the receiver 5.

The on-vehicle device 1 is electrically connected to a group of sensors such as the rider 2, the gyro sensor 3, the acceleration sensor 4, and the GPS receiver 5, and obtains output data of these. In addition, a map database (DB: DataBase) 10 that stores road data and feature information about features provided near the road is stored. The in-vehicle device 1 estimates the position of the vehicle based on the output data and the map DB 10, and performs control related to driving support of the vehicle such as automatic driving control based on the position estimation result. The in-vehicle device 1 estimates the attitude of the rider 2 based on the output of the rider 2 and the like. Then, the vehicle-mounted device 1 performs a process of correcting each measurement value of the point cloud data output by the rider 2 based on the estimation result. The in-vehicle device 1 is an example of the “posture estimation device” in the present invention.

The lidar 2 emits a pulse laser in a predetermined angle range in the horizontal direction and the vertical direction, thereby discretely measuring a distance to an object existing in the external world, and a three-dimensional point indicating the position of the object. Generate group information. In this case, the lidar 2 includes an irradiation unit that irradiates laser light while changing the irradiation direction, a light receiving unit that receives reflected light (scattered light) of the irradiated laser light, and scan data based on a light reception signal output by the light receiving unit. And an output unit that outputs The scan data is generated based on the irradiation direction corresponding to the laser light received by the light receiving unit and the distance to the object in the irradiation direction of the laser light specified based on the above-described light reception signal, and transmitted to the in-vehicle device 1. Supplied. The rider 2 is an example of the “measuring device” in the present invention.

FIG. 2 is a block diagram showing a functional configuration of the vehicle-mounted device 1. The in-vehicle device 1 mainly includes an interface 11, a storage unit 12, an input unit 14, a control unit 15, and an information output unit 16. These components are interconnected via a bus line.

The interface 11 acquires output data from sensors such as the rider 2, the gyro sensor 3, the acceleration sensor 4, and the GPS receiver 5, and supplies the output data to the control unit 15. Further, the interface 11 supplies a signal related to the traveling control of the vehicle generated by the control unit 15 to an electronic control unit (ECU: Electronic Control Unit) of the vehicle.

The storage unit 12 stores a program executed by the control unit 15 and information necessary for the control unit 15 to execute a predetermined process. In the present embodiment, the storage unit 12 has a map DB 10 and rider installation information IL. The map DB 10 is a database including, for example, road data, facility data, and feature data around roads. The road data includes lane network data for route search, road shape data, traffic regulation data, and the like. The feature data includes information (for example, position information and type information) on a signboard such as a road sign, a road marking such as a stop line, a road division line such as a white line, and a structure along a road. In addition, the feature data may include highly accurate point cloud information of the feature to be used for the vehicle position estimation. In addition, various data required for position estimation may be stored in the map DB.

The rider installation information IL is information relating to the relative posture and position of the rider 2 with respect to the vehicle at a certain reference time (for example, when there is no posture shift such as immediately after the alignment adjustment of the rider 2). In the present embodiment, the attitude of the rider 2 and the like is represented by a roll angle, a pitch angle, and a yaw angle (that is, an Euler angle). The rider installation information IL may be updated based on the estimation result when the later-described posture estimation process of the rider 2 is executed.

The input unit 14 is a button for a user to operate, a touch panel, a remote controller, a voice input device, and the like, and receives an input for designating a destination for a route search, an input for designating ON and OFF of automatic driving, and the like. . The information output unit 16 is, for example, a display, a speaker, or the like that outputs under the control of the control unit 15.

The control unit 15 includes a CPU that executes a program, and controls the entire vehicle-mounted device 1. The control unit 15 estimates the position of the own vehicle based on the output signal of each sensor supplied from the interface 11 and the map DB 10, and performs control related to driving support of the vehicle including automatic driving control based on the estimation result of the own vehicle position. And so on. At this time, when using the output data of the rider 2, the control unit 15 converts the measurement data output by the rider 2 based on the attitude and position included in the installation information of the rider 2 recorded in the rider installation information IL. Is converted from a coordinate system based on the rider 2 to a coordinate system based on the vehicle (hereinafter, “reference coordinate system”). Further, in the present embodiment, the control unit 15 calculates the amount of change with respect to the attitude recorded in the rider installation information IL by estimating the current (ie, processing reference) attitude of the rider 2 with respect to the vehicle. The measurement data output by the rider 2 is corrected based on the amount. As a result, even when the attitude of the rider 2 is shifted, the control unit 15 corrects the measurement data output by the rider 2 so as not to be affected by the shift. The control unit 15 is an example of a “computer” that executes a program according to the present invention.

[Coordinate system conversion]
The three-dimensional coordinates indicated by each measurement point of the three-dimensional point group data acquired by the rider 2 are expressed in a coordinate system (also referred to as a “lider coordinate system”) based on the position and orientation of the rider 2. It is necessary to convert to a coordinate system based on the position and orientation of the vehicle (also referred to as “vehicle coordinate system”). Here, the conversion between the rider coordinate system and the vehicle coordinate system will be described.

FIG. 3 is a diagram illustrating a relationship between a vehicle coordinate system and a rider coordinate system represented by two-dimensional coordinates. Here, the vehicle coordinate system has a coordinate axis “x _b ” along the traveling direction of the vehicle and a coordinate axis “y _b ” along the side direction of the vehicle, with the center of the vehicle as the origin. The rider coordinate system has a coordinate axis “x _L ” along the front direction of the rider 2 (see arrow A2) and a coordinate axis “y _L ” along the side direction of the rider 2.

Here, when the yaw angle of the rider 2 with respect to the vehicle coordinate system is “L _ψ ” and the position of the rider 2 is [L _x , L _y ] ^T , the measurement point [x] at the time “k” as viewed from the vehicle coordinate system _b (k), y _b (k)] ^T is converted to the coordinates [x _L (k), y _L (k)] ^T of the rider coordinate system by the following equation (1) using the rotation matrix “C _ψ ”. Is converted.

On the other hand, the conversion from the rider coordinate system to the vehicle coordinate system may use an inverse matrix (transposed matrix) of the rotation matrix. Therefore, the measurement point of time k obtained in the rider coordinate system _{[x L (k), y} L (k)] T is the vehicle coordinate system of coordinates by the following equation _{(2) [x b (k} ), y b (K)] can be converted to ^T.

FIG. 4 is a diagram illustrating a relationship between the vehicle coordinate system and the rider coordinate system represented by three-dimensional coordinates. Here, the coordinate axis perpendicular to the coordinate axes x _b and y _b is “z _b ”, and the coordinate axis perpendicular to the coordinate axes x _L and y _L is “z _L ”.

The roll angle of the rider 2 with respect to the vehicle coordinate system is “L _φ ”, the pitch angle is “L _θ ”, the yaw angle is “ _Lψ ”, the position of the rider 2 on the coordinate axis _xb is “L _x ”, and the position on the coordinate axis y _b If the position is “L _y ” and the position on the coordinate axis z _b is “L _z ”, the measurement point [x _b (k), y _b (k), z _b () at the time “k” viewed from the vehicle coordinate system k)] ^T is the following equation (3) using a directional cosine matrix “C” represented by rotation matrices “C _φ ”, “C _θ ”, and “C _ψ ” corresponding to roll, pitch, and yaw. Accordingly, the rider coordinate system of the coordinate is converted into _{[x L (k), y} L (k), z L (k)] T.

On the other hand, the conversion from the rider coordinate system to the vehicle coordinate system may use an inverse matrix (transposed matrix) of the direction cosine matrix. Therefore, the measurement point of time k obtained in the rider coordinate system _{[x L (k), y} L (k), z L (k)] T is the vehicle coordinate system of coordinates by the following equation (4) _{[x b} (K), y _b (k), z _b (k)] ^T.

Hereinafter, methods for estimating the roll angle L _φ , pitch angle L _θ , and yaw angle L _式 used in equation (4) for converting from the lidar coordinate system to the vehicle coordinate system will be described in order.

[Estimation of roll angle]
First, a description method for estimating the roll angle L _phi rider 2. The on-vehicle device 1 detects a square (rectangular) road sign having a plane perpendicular to the traveling direction of the traveling path (that is, a front surface with respect to the traveling path) by the rider 2 as a target feature (“detection”). also referred to as a target feature Ftag ".) and regarded, by the inclination of the road sign rider 2 is calculated based on the measurement point group to be measured to estimate the roll angle L _phi rider 2.

FIG. 5 is a bird's-eye view of the vicinity of the vehicle when the vehicle travels near the road sign 22 that is the detection target feature Ftag when estimating the roll angle of the rider 2. In FIG. 5, a dashed circle 20 indicates a range in which a feature can be detected by the rider 2 (also referred to as a “lider detection range”), and a dashed frame 21 detects a road sign 22 which is a detection target feature Ftag. The detection window for

In this case, the vehicle-mounted device 1 refers to the map DB 10 and recognizes that the rectangular road sign 22 having a plane perpendicular to the traveling direction of the traveling path exists in the lidar detection range, and A detection window indicated by a broken-line frame 21 is set based on the feature data relating to 22. In this case, the in-vehicle device 1 previously stores, for example, type information of a road sign to be a detection target feature Ftag, and determines whether or not a road sign of the type indicated by the type information exists within the lidar detection range. Is determined with reference to the feature data in the map DB 10. When the feature data of the map DB 10 includes information on the size and / or shape of the feature, the on-vehicle device 1 determines the size or / and / or the size of the road sign 22 as the detection target feature Ftag. The size and / or shape of the detection window may be determined based on the shape information. Then, the on-vehicle device 1 converts the measurement point group (also referred to as “target measurement point group Ptag”) existing in the set detection window from the measurement point group measured by the rider 2 to the measurement point group of the road sign 22. Extract as

6 (A) to 6 (C) show the target measurement point group Ptag and the scanning line 23 of the laser light by the rider 2 when the measurement target surface of the road sign 22 is viewed from the front. (Line connecting the series). Incidentally, for ease of explanation, the initial attitude angle L _phi rider 2, L _theta, taking an example where L _[psi is 0 degrees. Here, FIG. 6A shows the relationship between the target measurement point group Ptag and the scanning line 23 of the rider 2 when there is no shift in the roll direction in the rider 2, and FIGS. 6B and 6C. shows the relationship between the target measurement point group Ptag and rider second scan line 23 when the deviation [Delta] L _phi in the roll direction occurs. Here, FIG. _6B shows the relationship between the target measurement point group Ptag and the scanning line 23 of the rider 2 in the y _b -z _b plane of the vehicle coordinate system, and FIG. 6C shows the reference coordinate system. 5 shows the relationship between the target measurement point group Ptag and the scanning line 23 of the rider 2 in the y _b ′ -z _b ′ plane. Here, for the sake of convenience, when the attitude of the rider 2 is not shifted, the longitudinal direction of the road sign 22 is assumed to be parallel to the _yb axis, and the vehicle is present on a flat road. .

As shown in FIG. 6A, when there is no deviation in the roll angle of the rider 2, the rider 2 scans in a direction parallel to the lateral direction (that is, the horizontal direction or the longitudinal direction) of the road sign 22. In this case, the number of point groups in the vertical direction of the target measurement point group Ptag is the same number (six in FIG. 6A) regardless of the position in the horizontal direction.

On the other hand, when the roll angle of the rider 2 is shifted, the scanning line is inclined with respect to the road sign 22. Here, the longitudinal direction of the road sign 22 is not inclined with respect to the vehicle, and the scanning line of the rider 2 is inclined with respect to the vehicle. as shown, becomes parallel to the longitudinal direction of the y _b-axis and the road signs 22, the scanning lines of the rider 2 is inclined with respect to y _b axis. On the other hand, when viewed in the reference coordinate system, as shown in FIG. 6 (C), y b _'and the scanning line of the shaft and the rider 2 is parallel to the longitudinal direction of the road sign 22 is y _b' with respect to the axis Tilt.

Next, processing after the extraction of the target measurement point group Ptag will be described. First, the in-vehicle device 1 determines the received light intensity for each measurement point of the target measurement point group Ptag by using a predetermined threshold, and excludes the measurement points corresponding to the light reception intensity that is equal to or less than the predetermined threshold from the target measurement point group Ptag. I do. Then, the in-vehicle device 1 extracts a point group forming the outer edge (also referred to as “outer edge point group Pout”) from the target measurement point group Ptag after the exclusion process based on the received light intensity. For example, the in-vehicle device 1 extracts, as the outer edge point group Pout, the measurement points of the target measurement point group Ptag in which there is no adjacent measurement point in at least one of the vertical and horizontal directions.

FIG. 7A shows the target measurement point group Ptag in the lidar coordinate system, and FIG. 7B shows the target measurement point group Ptag after excluding the measurement points corresponding to the light receiving intensity equal to or less than the predetermined threshold value. Show. FIG. 7C shows an outer edge point group Pout extracted from the target measurement point group Ptag shown in FIG. 7B. As shown in FIGS. 7A and 7B, among the measurement points shown in FIG. 7A, the measurement intensity of a part of the laser light reflected by only a part of the laser light is missing. Is less than or equal to a predetermined threshold, and is excluded from the target measurement point group Ptag. Further, as shown in FIGS. 7B and 7C, measurement points having no adjacent measurement points in at least one of the upper, lower, left, and right directions are extracted as the outer edge point group Pout.

Next, the in-vehicle device 1 calculates the inclination of the road sign 22 in the longitudinal direction from the outer edge point group Pout. Here, since the outer edge point group Pout forms a quadrangle, the outer edge point group Pout is classified for each side of the rectangle, and a regression analysis method such as a least square method is used from the outer edge point group Pout classified for each side. To calculate the slope of the approximate straight line of each side.

FIG. 8A is a diagram in which a group of outer edge points Pout forming the upper side of a rectangle is extracted and a straight line is drawn by the least square method. FIG. 8B is a diagram in which a group of outer edge points Pout forming the base of the rectangle is extracted and a straight line is drawn by the least square method. FIG. 8C is a diagram in which a group of outer edge points Pout forming the left side of the rectangle is extracted and a straight line is drawn by the least square method. FIG. 8D shows a diagram in which a group of outer edge points Pout forming the right side of the rectangle is extracted and a straight line is drawn by the least square method.

In this case, the on-vehicle device 1 calculates each straight line shown in FIGS. 8A to 8D, and calculates the slopes “φ ₁ ” to “φ ₄ ” of each straight line with respect to the y _b ′ axis. Then, the in-vehicle device 1 calculates the average of these slopes “φ ₁ ” to “φ ₄ ” as the slope “φ” of the road sign 22 as shown in the following equation (5).

Here, since the left side and the right side of the rectangle are shifted by about 90 ° with respect to the top side and the bottom side, in equation (5), the slope φ _{3 of} the straight line obtained from the outer edge point group Pout constituting the left side and the right side of the rectangle And φ ₄ are corrected by “π / 2”.

Preferably, when determining the inclination φ, the in-vehicle device 1 may weight each of the inclinations φ ₁ to φ ₄ based on the number of the outer edge point groups Pout constituting each side of the rectangle. In this case, the number of the outer edge point groups Pout forming the upper side of the rectangle is “n ₁ ”, the number of the outer edge point groups Pout forming the base of the square is “n ₂ ”, and the number of the outer edge point group Pout forming the left side of the square is the number "n _3" and the number of the outer edge point group Pout forming the right side of the rectangle and "n _4", the vehicle-mounted device 1 performs a weighted average based on the following equation (6), the inclination φ calculate.

In another preferred example, when calculating the inclination φ, the vehicle-mounted device 1 determines the interval “I _H ” between the horizontal target measurement point group Ptag and the vertical interval “I _V ” between the target measurement point group Ptag of the rider 2. , The slopes φ ₁ to φ ₄ may be weighted. Here, the horizontal interval I _H and the vertical interval _IV are the intervals shown in FIG. 7B, respectively. In this case, the in-vehicle device 1 reduces the accuracy of the inclinations φ ₁ and φ ₂ of the top and bottom sides of the square as the vertical interval _IV increases, and decreases the inclination φ of the left side and right side of the rectangle as the horizontal interval I _H increases. Assuming that the accuracy of ₃ and ₄ is low, the slope φ is calculated by performing weighted averaging using the reciprocals of the horizontal interval I _H and the vertical interval _IV as shown in the following equation (7).

Further, the vehicle-mounted unit 1, the weighted average in consideration of both the number n _{1 ~} n ₄ and the vertical spacing I _V and horizontal spacing I _H of the point group constituting the sides of the rectangle may be calculated inclination phi. In this case, the vehicle-mounted device 1 calculates the slope φ by performing weighted averaging based on the following equation (8).

Further, the on-vehicle device 1 calculates the roll angle “φ ₀ ” of the vehicle body based on the outputs of the gyro sensor 3 and the acceleration sensor 4, and calculates the difference between the roll angle “φ ₀ ” and the inclination φ calculated by any of the equations (5) to (8). by taking, for calculating a roll angle L _phi rider 2. In this case, the vehicle-mounted device 1 calculates the roll angle L _phi rider 2 based on the following equation (9).

Thus, the vehicle-mounted device 1 can be suitably calculated roll angle L _phi lidar 2 in which the influence of inclination of the vehicle.

Preferably, considering the possibility and measurement errors such road sign 22 is detected feature Ftag is inclined with respect to the horizontal direction, the vehicle-mounted unit 1, the calculation of the roll angle L _phi of the rider 2 It is good to carry out for many road signs which become the detection target feature Ftag and average them. Thus, the vehicle-mounted device 1 can be suitably calculated roll-direction tilt L _phi of probable rider 2.

Further, since the roll angle φ _{0 of the} vehicle body can be regarded as 0 ° on average, it is not necessary to acquire the roll angle φ ₀ of the vehicle body by lengthening the averaging time. For example, when acquiring the inclination phi of sufficiently large the N content, the vehicle-mounted unit 1, the roll angle L _phi rider 2 may be defined by the following equation (10).

Above N is the number of samples that can average the body roll angle phi ₀ is regarded as substantially 0 °, for example is predetermined based on experiments or the like.

FIG. 9 is a flowchart showing the procedure of the roll angle estimation process.

First, the vehicle-mounted device 1 refers to the map DB 10 and sets a detection window for the detection target feature Ftag around the vehicle (step S101). In this case, the on-vehicle device 1 selects a rectangular road sign having a vertical plane with respect to the traveling direction of the traveling path as the detection target feature Ftag, and selects the above-described road sign existing within a predetermined distance from the current position. It is specified from the map DB 10. Then, the on-vehicle device 1 sets a detection window by acquiring position information and the like regarding the specified road sign from the map DB 10.

Next, the vehicle-mounted device 1 acquires the measurement point group of the rider 2 within the detection window set in step S101 as a point group of the detection target feature Ftag (that is, the target measurement point group Ptag) (step S102). Then, the vehicle-mounted device 1 extracts an outer edge point group Pout that forms the outer edge of these point groups from the target measurement point group Ptag acquired in step S102 (step S103).

Then, the on-vehicle device 1 calculates the lateral inclination φ of the outer edge point group Pout extracted in Step S103 (Step S104). In this case, as described with reference to FIGS. 8A to 8D, the in-vehicle device 1 changes the slope φ _{1 of} a straight line corresponding to each side from a point group corresponding to each side of the square formed by the outer edge point group Pout. seek ~ phi _4, calculates an inclination phi employ any of the formulas (5) to (8).

Then, the vehicle-mounted unit 1, the difference processing between the averaging process and / or the vehicle body roll angle phi ₀ of inclination phi, calculates the roll angle L _phi rider 2 (step S105). In the above-described averaging process, the on-vehicle device 1 obtains a plurality of slopes φ by performing the processing of steps S101 to S104 on a plurality of detection target features Ftag, and obtains an average value of the obtained plurality of slopes φ. _Is calculated as the slope _Lφ .

[Estimation of pitch angle]
Next, a description method for estimating the pitch angle L _theta rider 2. The in-vehicle device 1 regards a rectangular road sign having a plane perpendicular to the width direction of the traveling road (that is, a plane transverse to the traveling road) as the detection target feature Ftag, and determines the inclination of the road sign to the rider 2. The pitch angle of the rider 2 is estimated by performing calculation based on the measurement point group output by.

FIG. 10 is a bird's-eye view of the periphery of the vehicle when the vehicle travels near the road sign 24 that is the target feature Ftag when estimating the pitch angle of the rider 2. FIG. In FIG. 10, a dashed circle 20 indicates a lidar detection range in which a feature can be detected by the rider 2, and a dashed frame 21 indicates a detection window set for a road sign 24 which is a detection target feature Ftag.

In this case, the in-vehicle device 1 refers to the map DB 10 to determine that the rectangular road sign 24 having a vertical surface with respect to the width direction of the traveling path exists within the lidar detection range indicated by the broken circle 20. Recognition is performed, and a detection window indicated by a broken-line frame 21 is set based on position information and the like regarding the road sign 24. In this case, the in-vehicle device 1 previously stores, for example, type information of a road sign to be a detection target feature Ftag, and determines whether or not a road sign of the type indicated by the type information exists within the lidar detection range. Is determined with reference to the feature data in the map DB 10. Then, the on-vehicle device 1 extracts, as the target measurement point group Ptag, the measurement point group existing in the set detection window from the measurement point group output by the rider 2.

Next, the on-vehicle device 1 estimates the pitch angle of the rider 2 by executing the same processing as the roll angle estimation method on the extracted target measurement point group Ptag.

Specifically, the in-vehicle device 1 first determines the light receiving intensity for each of the measurement points of the target measurement point group Ptag by using a predetermined threshold, and performs the target measurement on the measurement point corresponding to the light receiving intensity that is equal to or less than the predetermined threshold. Exclude from point cloud Ptag. Then, the vehicle-mounted device 1 extracts the outer edge point group Pout constituting the outer edge from the target measurement point group Ptag after the exclusion processing based on the received light intensity. Next, the in-vehicle device 1 calculates the slopes “θ ₁ ” to “θ ₄ ” of the approximate straight lines of each side of the rectangle formed by the outer edge point group Pout by a regression analysis method such as the least square method. Then, the in-vehicle device 1 calculates an inclination “θ” of the road sign 22 by performing an averaging process based on the inclinations θ ₁ to θ ₄ . Incidentally, the vehicle-mounted device 1 is similar to the equation (6) to (8), the number _n 1 - _{n 4} points group constituting the sides of the rectangle, at least one of the vertical interval _{I V} and horizontal spacing _{I H} The inclination θ may be calculated based on the weighted average with consideration.

Further, the on-vehicle device 1 calculates the pitch angle “θ ₀ ” of the vehicle body based on the outputs of the gyro sensor 3 and the acceleration sensor 4 and calculates the pitch angle L _θ of the rider 2 by calculating the difference from the inclination θ. . In this case, the vehicle-mounted device 1 calculates the pitch direction tilt L _theta rider 2 based on equation (11) below.

Thus, the vehicle-mounted device 1 can be suitably calculated pitch angle L _theta lidar 2 in which the influence of inclination of the vehicle. Also, preferably, the detection target features a road sign 24 is Ftag are considering the possibility and measurement error and the like which are inclined with respect to the horizontal direction, the vehicle-mounted unit 1, the pitch angle L _theta of the rider 2 The calculation may be performed on a number of road signs serving as the detection target feature Ftag, and may be averaged. Thus, the vehicle-mounted device 1 can be suitably calculated pitch angle L _theta in probable rider 2. Here, since the pitch angle θ ₀ of the vehicle body can be regarded as 0 ° on average, it is not necessary to acquire the pitch angle θ ₀ of the vehicle body by lengthening the averaging time. For example, when acquiring the inclination theta of N min, the pitch angle L _theta rider 2 is expressed by the following Equation (12).

FIG. 11 is a flowchart showing the procedure of pitch angle estimation processing.

First, the in-vehicle device 1 sets a detection window for the detection target feature Ftag around the vehicle with reference to the map DB 10 (Step S201). In this case, the on-vehicle device 1 selects, as the detection target feature Ftag, a rectangular road sign having a vertical plane with respect to the width direction of the traveling path, and determines the above-described road sign existing within a predetermined distance from the current position. It is specified from the map DB 10. Then, the on-vehicle device 1 sets a detection window by acquiring position information and the like regarding the specified road sign from the map DB 10.

Next, the vehicle-mounted device 1 acquires the measurement point group of the rider 2 in the detection window set in step S201 as a point group of the detection target feature Ftag (that is, the target measurement point group Ptag) (step S202). Then, the vehicle-mounted device 1 extracts, from the point group of the detection target feature Ftag acquired in step S202, an outer edge point group Pout that forms the outer edge of these point groups (step S203).

Then, the vehicle-mounted device 1 calculates the inclination θ in the longitudinal direction of the outer edge point group Pout extracted in Step S203 (Step S204). Thereafter, the on-vehicle device 1 calculates the inclination L _θ of the rider 2 in the pitch direction by averaging the inclination θ and / or processing the difference from the pitch angle θ _{0 of the} vehicle body (step S205). In the averaging process described above, the vehicle-mounted unit 1, step S201 calculates a plurality of inclination theta by performing the process of ~ S204 for a plurality of target measurement point group PTAG, these average gradient as L _theta calculate.

[Estimation of yaw angle]
Next, a description method for estimating the yaw angle L _[psi rider 2. Vehicle device 1 regards the demarcation line, such as a white line and the detection target feature FTAG, by the direction of the center line of the lane line rider 2 is calculated based on the measurement point group to be measured of the rider 2 yaw angle L _[psi presume.

FIG. 12 is a bird's-eye view of the periphery of the vehicle when the vehicle travels along a lane marking that is a target feature Ftag when estimating the yaw angle of the rider 2. In this example, there is a continuous line 30 which is a continuous lane marking on the left side of the vehicle, and a broken line 31 which is an intermittent lane marking on the right side of the vehicle. The arrow 25 indicates the reference direction of the yaw direction when the rider 2 does not occur yaw direction deviation, be a direction obtained by rotating the coordinate axes of the rider 2 "x _L" only yaw angle L _[psi rider 2 , And the coordinate axis “x _b ” along the traveling direction of the vehicle. That is, the yaw angle L _[psi rider 2, if no deviation occurs, indicating the yaw angle regarded as the running direction of the vehicle (also referred to as "yaw direction reference angle".). On the other hand, the arrow 26 indicates the yaw direction reference angle in the case where the deviation in the yaw direction of the rider 2 is ΔLΨ. _Unless the yaw direction reference angle is corrected, the arrow 26 will not match the running direction of the vehicle. The yaw direction reference angle is stored in advance in, for example, the storage unit 12 or the like.

In this case, for example, the map DB 10 includes demarcation line information indicating the discrete coordinate position of the continuous line 30 and the discrete coordinate position of the broken line 31. The in-vehicle device 1 refers to the lane marking information and determines the nearest coordinate position from a position at a predetermined distance (for example, 5 m) from the vehicle in each of the left front, left rear, right front, and right rear directions of the vehicle. A rectangular area centered on the extracted coordinate position is set as a detection window indicated by broken-line frames 21A to 21D.

Next, the in-vehicle device 1 extracts, from the measurement point group measured by the rider 2, a point group on the road surface and having a reflection intensity equal to or higher than a predetermined threshold within the detection window as a target measurement point group Ptag. Then, the vehicle-mounted device 1 obtains the center point of the target measurement point group Ptag for each scanning line, and calculates a straight line (see arrows 27A to 27D) passing through these center points for each detection window as the center line of the division line. .

FIG. 13A is a diagram in which the center point of the dashed frame 21A in the detection window is indicated by a circle, and FIG. 13B is a diagram in which the center point of the dashed frame 21B in the detection window is indicated by a circle. is there. 13A and 13B, the scanning line 28 of the laser light by the rider 2 is clearly shown. In addition, since the laser beam of the rider 2 incident on the lane marking is emitted obliquely downward, the intervals between the scanning lines become shorter as approaching the vehicle.

13) As shown in FIGS. 13A and 13B, the vehicle-mounted device 1 calculates a center point for each scanning line. The center point may be a position obtained by averaging the coordinate positions indicated by the measurement points for each scanning line 28, or may be an intermediate point between the leftmost and rightmost measurement points on each scanning line 28. It may be a measurement point existing in the upper middle. Then, the in-vehicle device 1 calculates the center line (see arrows 27A and 27B) of the division line for each detection window from the calculated center point by a regression analysis method such as the least square method.

Then, the on-vehicle device 1 calculates an angle formed between the center line of the division line calculated for each detection window and the yaw direction reference angle (see the arrow 26 in FIG. 12) as inclinations “ψ ₁ ” to “ψ ₄ ”. . FIGS. 14A to 14D are diagrams showing the slopes ψ ₁ to _{４ 4} , respectively. As shown in FIGS. 14A to 14D, the inclinations _{１ 1} to _{４ 4} correspond to the angles formed by arrows 27A to 27D indicating the center line of the dividing line and arrows 26 indicating the yaw direction reference angle. .

Then, the vehicle-mounted device 1 calculates the slope 車載 by averaging the slopes ψ ₁ to ψ ₄ as shown in the following equation (13).

The in-vehicle device 1 may also weight slopes _{１ 1} to ψ ₄ based on the number of center points used for calculating the center line of the lane marking. In this case, "n _1" to the number of center points used to calculate the center line of division line as a gradient [psi _1, "n number of center points used to calculate the center line of division line as a gradient [psi _{2 2} ”, the number of center points used to calculate the center line of the division line having the slope ψ ₃ is“ n ₃ ”, and the number of center points used to calculate the center line of the division line having the slope _{４ 4} is“ n ”. ₄ ", the vehicle-mounted device 1 calculates the slope ψ based on the following equation (14).

Thereby, the on-vehicle device 1 can relatively lower the weight of the inclination of the center line of the division line (the broken line 31 in FIG. 12) calculated with a small number of center points, and can accurately obtain the inclination ψ. Therefore, the weight is lower in the detection situation of FIG. 13B than in the detection situation of FIG. In the description of FIG. 12 to FIG. 14, an example in which the inclinations _{１ 1} to _{４ 4} for the _four lane marking lines are calculated at the same time is shown, but the inclinations for at least one lane marking may be calculated.

Next, a method for calculating the yaw angle L _[psi rider 2 from the slope [psi. Since the lane markings such as the white line are drawn along the road, the yaw angle of the vehicle body can be regarded as substantially constant (that is, parallel to the traveling road). Therefore, the vehicle-mounted device 1 is different from the method of estimating the roll angle and the pitch angle, it calculates an inclination [psi, as the deviation [Delta] L _[psi yaw angle rider 2 (i.e., "[Delta] L _[psi = [psi"). However, in normal traveling, there are lane changes and the vehicle body fluctuates in the lane. Therefore, the in-vehicle device 1 may execute a process of calculating the inclination of the center line for many lane markings, and average the values. Thus, the vehicle-mounted device 1 can be suitably calculated deviation [Delta] L _[psi of probable yaw angle of the rider 2. For example, when acquiring the inclination [psi of N content, the yaw angle L _[psi rider 2 is expressed by the following equation (15).

Here, "L _.phi.0" indicates yaw angle L _[psi (i.e. yaw direction reference angle) when the deviation in the yaw angle has not occurred.

FIG. 15 is a flowchart showing the procedure of the yaw angle estimation process.

First, the in-vehicle device 1 refers to the map DB 10 and sets one or more detection windows for the lane markings (Step S301). Then, the vehicle-mounted device 1 acquires the measurement point group of the rider 2 within the detection window set in step S301 as a lane marking point group (ie, a target measurement point group Ptag) (step S302).

{Circle around (5)} The in-vehicle device 1 calculates the center line of the division line in each set detection window (step S303). In this case, the vehicle-mounted device 1 obtains the center point of the target measurement point group Ptag for each scanning line of the rider 2, and calculates the center line of the division line for each detection window from the center point based on the least square method or the like. Then, the vehicle-mounted device 1 calculates an angle の between the yaw angle reference angle stored in advance in the storage unit 12 and the center line of the lane marking (step S304). In this case, when two or more detection windows are set in step S301, the in-vehicle device 1 obtains the angle between the yaw angle reference angle and the center line of the division line for each detection window, and averages these angles. Alternatively, the above-described angle ψ is calculated by performing weighted averaging with the number of center points.

Then, the on-vehicle device 1 averages the plurality of angles ψ calculated by executing steps S301 to S304 on different lane _markings, and calculates the yaw angle L の of the rider 2 based on Expression (15) ( Step S305).

Here, a specific example of the processing based on the estimated values of the roll angle, the pitch angle, and the yaw angle described above will be described. FIG. 16 is a flowchart illustrating a specific example of the processing based on the estimated values of the roll angle, the pitch angle, and the yaw angle.

First, the vehicle-mounted unit 1, 9, 11, or by performing the process of the flowchart of FIG. 15, the roll angle L _phi rider 2, was calculated either pitch angle L _theta, or yaw angle L _[psi It is determined whether or not (step S401). Then, the vehicle-mounted unit 1, the roll angle L _phi rider 2, when calculating the one of the pitch angle L _theta, or yaw angle L _[psi (step S401; Yes), the calculated angles are recorded to a rider installation information IL It is determined whether or not the angle has changed by a predetermined angle or more (step S402). The above-mentioned threshold value is a threshold value for determining whether or not the measurement data of the rider 2 can be continuously used by performing the correction processing of the measurement data of the rider 2 in step S404 described later. Is set.

Then, when the calculated angle has changed by a predetermined angle or more from the angle recorded in the rider installation information IL (step S402; Yes), the in-vehicle device 1 uses the output data of the target rider 2 (that is, obstacle detection). And the information output unit 16 outputs a warning to the effect that it is necessary to perform the alignment adjustment again for the target rider 2 (step S403). As a result, a decrease in safety or the like caused by using the measurement data of the rider 2 in which the posture and the position are significantly shifted due to an accident or the like is reliably suppressed.

On the other hand, if the calculated angle has not changed by more than the predetermined angle from the angle recorded in the rider installation information IL (step S402; No), the in-vehicle device 1 calculates the angle calculated from the angle recorded in the rider installation information IL. The measured values of the point cloud data output by the rider 2 are corrected based on the amount of change (step S404). In this case, the in-vehicle device 1 stores, for example, a map indicating the correction amount of the measurement value with respect to the above-described change amount, and corrects the above-described measurement value by referring to the map or the like. Further, the measurement value may be corrected using a value of a predetermined ratio of the change amount as a correction amount of the measurement value.

As described above, the in-vehicle device 1 according to the present embodiment is configured such that a road sign having a plane perpendicular to the traveling direction of the vehicle travel path or a plane perpendicular to the width direction of the travel path is attached to the rider attached to the vehicle. 2. The target measurement point group Ptag measured by Step 2 is acquired. The in-vehicle device 1 determines the mounting posture of the rider 2 to the vehicle based on the inclination of the road sign in the longitudinal direction based on the coordinate system based on the installation information of the rider 2, which is calculated from the target measurement point group Ptag. presume. Thereby, the vehicle-mounted device 1 can accurately estimate the mounting attitude of the rider 2 to the vehicle in the roll direction and the pitch direction.

Further, as described above, the vehicle-mounted device 1 in the present embodiment acquires the group of measurement points obtained by measuring the lane markings by the rider 2 attached to the vehicle, and, based on the group of measurement points, moves along the traveling direction of the vehicle. The center line of the demarcation line is calculated. Then, the on-vehicle device 1 estimates the mounting posture of the rider 2 to the vehicle based on the direction of the center line of the lane marking with respect to the yaw direction reference angle referenced by the rider 2. Thereby, the vehicle-mounted device 1 can appropriately estimate the mounting posture of the rider 2 in the yaw direction.

[Modification]
Hereinafter, a modified example suitable for the embodiment will be described. The following modifications may be combined and applied to the embodiment.

(Modification 1)
In the description of step S303 in FIG. 13 and FIG. 15, the vehicle-mounted device 1 calculates the center line of the lane marking by calculating the center point in the detection window in the width direction of the lane marking. Instead, the on-vehicle device 1 may extract the right or left end point of the scanning line in the detection window and calculate a straight line passing through the right or left end of the division line. In this way, the on-vehicle device 1 can appropriately identify the line parallel to the traveling path and calculate the angle ψ.

(Modification 2)
In the yaw angle estimation processing described with reference to FIGS. 12 to 15, the vehicle-mounted device 1 regards the section line as the detection target feature Ftag. Alternatively or additionally, the in-vehicle device 1 may regard the curbstone or the like as the detection target feature Ftag. In this manner, the in-vehicle device 1 regards an arbitrary feature whose surface to be measured is parallel to the traveled road surface and formed along the traveled road surface as the detection target feature Ftag, without being limited to the lane markings. The yaw angle estimation process described with reference to FIG. 15 may be executed.

(Modification 3)
In step S404 in FIG. 16, instead of correcting each measurement value of the point cloud data output by the rider 2, the on-vehicle device 1 uses the roll angle and the pitch calculated by the processing in the flowchart in FIG. 9, FIG. 11, or FIG. Each measured value of the point cloud data output by the rider 2 may be converted into a vehicle coordinate system based on the angle and the yaw angle.

In this case, the in-vehicle device 1 uses the calculated roll angle L _φ , pitch angle L _θ , and yaw angle L _を to calculate each measurement value of the point cloud data output by the rider 2 based on the equation (4) in the rider coordinates. The system may be converted into a vehicle body coordinate system, and the own vehicle position estimation, automatic driving control, and the like may be executed based on the converted data.

In another example, when each rider 2 has an adjustment mechanism such as an actuator for correcting the attitude of each rider 2, the on-vehicle device 1 replaces the processing in step S404 in FIG. Control for driving the adjustment mechanism may be performed such that the attitude of the rider 2 is corrected by the amount of deviation from the angle recorded in the information IL.

(Modification 4)
The configuration of the vehicle system shown in FIG. 1 is an example, and the configuration of the vehicle system to which the present invention can be applied is not limited to the configuration shown in FIG. For example, instead of having the vehicle-mounted device 1 in the vehicle system, the electronic control unit of the vehicle may execute the processes shown in FIGS. 9, 11, 15, 16, and the like. In this case, the rider installation information IL is stored in, for example, a storage unit in the vehicle, and the electronic control unit of the vehicle is configured to be able to receive output data of various sensors such as the rider 2.

(Modification 5)
The vehicle system may include a plurality of riders 2. In this case, the in-vehicle device 1 estimates the roll angle, the pitch angle, and the yaw angle of each rider 2 by executing the processing of the flowcharts of FIGS. 9, 11, and 15 for each rider 2. .

DESCRIPTION OF SYMBOLS 1 Onboard equipment 2 Rider 3 Gyro sensor 4 Acceleration sensor 5 GPS receiver 10 Map DB

Claims (10)

1. Acquisition of a feature having a plane perpendicular to the traveling direction of the traveling path of the moving body or a plane perpendicular to the width direction of the traveling path, and acquiring a measurement point group measured by a measuring device attached to the moving body. Means,
   Estimating means for estimating the mounting posture of the measuring device on the moving body, based on the inclination of the vertical plane based on a coordinate system based on the installation information of the measuring device, calculated from the measurement point group,
   A posture estimating device having:
2. The said acquisition means acquires the measurement point group which the measuring device measured at the said position as the measurement point group of the said feature by recognizing the position of the said feature based on the feature information regarding the said feature. The attitude estimation device according to claim 1.
3. The estimating means includes:
   Based on the inclination calculated from a measurement point group of a feature having a vertical plane with respect to the traveling direction of the traveling path, the attitude of the measurement device in the roll direction is estimated,
   The attitude estimation according to claim 1, wherein the attitude of the measurement device in a pitch direction is estimated based on the inclination calculated from a group of measurement points of a feature having a plane perpendicular to the width direction of the travel path. apparatus.
4. The attitude estimation device according to any one of claims 1 to 3, wherein the feature is a road sign provided on the travel path.
5. The attitude according to any one of claims 1 to 4, wherein the estimating unit extracts an outer edge point group forming an edge of the measurement point group, and calculates the inclination of the feature based on the outer edge point group. Estimation device.
6. The vertical plane is rectangular,
   The posture estimating apparatus according to claim 5, wherein the estimating unit calculates the inclination of the feature by calculating an inclination corresponding to each side of the rectangle from the outside point group.
7. 7. The pose estimation according to claim 6, wherein the slope of the feature is calculated by weighting the slope corresponding to each side based on at least one of the number and interval of the point groups constituting each of the sides. apparatus.
8. A control method executed by the posture estimation device,
   Acquisition of a feature having a plane perpendicular to the traveling direction of the traveling path of the moving body or a plane perpendicular to the width direction of the traveling path, and acquiring a measurement point group measured by a measuring device attached to the moving body. Process and
   An estimation step of estimating the mounting posture of the measurement device to the moving body, based on the inclination of the vertical plane based on a coordinate system based on the installation information of the measurement device, calculated from the measurement point group,
   A control method having:
9. A program executed by a computer,
   Acquisition of a feature having a plane perpendicular to the traveling direction of the traveling path of the moving body or a plane perpendicular to the width direction of the traveling path, and acquiring a measurement point group measured by a measuring device attached to the moving body. Means,
   The estimating means for estimating the mounting posture of the measuring device on the moving body based on the inclination of the vertical plane based on a coordinate system based on the installation information of the measuring device, which is calculated from the measurement point group, A program that makes a computer function.
10. A storage medium storing the program according to claim 9.

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