Estimation device, control method, program, and storage medium

Abstract

To provide an estimation device in which an attitude of a measurement unit that measures a distance to an object, for a mobile object can be optimally estimated.SOLUTION: An on-vehicle machine 1 estimates at least an attitude of a lidar 2 that measures a distance to an object for a vehicle, and performs a process to estimate the attitude of the lidar 2 for the vehicle or the like on the basis of a detection result of an acceleration sensor 5 for a lidar which is provided in the lidar 2 when the vehicle travels while accelerating or decelerating.SELECTED DRAWING: Figure 12

Description

[Technical Field]

[0001] This invention relates to a technique for estimating the orientation of a measuring unit. [Background technology]

[0002] Conventionally, technologies have been known that perform self-position estimation based on measurement data from measurement units such as radar and cameras. For example, Patent Document 1 discloses a technology that estimates the self-position by comparing the output of a measurement sensor with location information of features registered in advance on a map. Patent Document 2 also discloses a self-position estimation technology using a Kalman filter. [Prior art documents] [Patent Documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2013-257742 [Patent Document 2] Japanese Patent Publication No. 2017-72422 [Overview of the Initiative] [Problems that the invention aims to solve]

[0004] Data obtained from measurement units such as radar and cameras are in a coordinate system relative to the measurement unit and depend on the attitude of the measurement unit relative to the vehicle. Therefore, it is necessary to convert the data to a coordinate system relative to the vehicle. Consequently, if there is a shift in the attitude of the measurement unit, it is necessary to accurately detect that shift and reflect it in the measurement unit's data.

[0005] The present invention was made to solve the above-mentioned problems, and its main objective is to provide an estimation device capable of suitably estimating the orientation of a measuring unit, which measures the distance to an object, relative to a moving body. [Means for solving the problem]

[0006] The invention described in the claims is, An estimation device for estimating the orientation of a measuring unit relative to a moving body, which measures the distance to an object, The system includes an estimation unit that estimates the roll and pitch orientation of the measurement unit based on acceleration data output by an acceleration detection unit provided in the measurement unit when the moving unit is traveling or stopped at a predetermined speed. Furthermore, the invention described in the claims is, An estimation device for estimating the orientation of a measuring unit relative to a moving body, which measures the distance to an object, An estimation unit estimates the attitude of the measurement unit relative to the moving object based on the detection result of the acceleration detection unit provided in the measurement unit when the moving object is moving with acceleration and deceleration. It has, The estimation unit estimates the position of the measurement unit in the longitudinal direction of the moving body based on the distance between the road point and the moving body when the road point where the gradient changes, or when a bump on the road surface is measured by the measurement unit. Furthermore, the invention described in the claims is, An estimation device for estimating the orientation of a measuring unit relative to a moving body, which measures the distance to an object, An estimation unit estimates the attitude of the measurement unit relative to the moving object based on the detection result of the acceleration detection unit provided in the measurement unit when the moving object is moving with acceleration and deceleration. It has, The estimation unit estimates the position of the measurement unit in the left-right direction of the moving body based on the left-right acceleration data of the moving body output by the acceleration detection unit during the rotation of the moving body, the left-right acceleration data of the moving body output by the acceleration sensor mounted on the moving body, and the yaw rate of the moving body output by the gyro sensor mounted on the moving body.

[0007] Furthermore, the invention described in the claims is, A control method performed by an estimation device that estimates the attitude of a measuring unit, which measures the distance to an object, relative to a moving object, The system includes an estimation step of estimating the orientation of the measurement unit in the roll direction and pitch direction based on acceleration data output by an acceleration detection unit provided in the measurement unit when the moving unit is traveling or stopped at a predetermined speed. Furthermore, the invention described in the claims is, A control method performed by an estimation device that estimates the attitude of a measuring unit, which measures the distance to an object, relative to a moving object, The measurement unit has an estimation step of estimating the attitude of the measurement unit relative to the moving body based on the detection result of the acceleration detection unit provided in the measurement unit when the moving body is traveling while accelerating and decelerating. The estimation step estimates the position of the measuring unit in the longitudinal direction of the moving body based on the distance between the road point and the moving body when the road point where the gradient changes, or when a bump on the road surface is measured by the measuring unit. Furthermore, the invention described in the claims is, A control method performed by an estimation device that estimates the attitude of a measuring unit, which measures the distance to an object, relative to a moving object, The measurement unit has an estimation step of estimating the attitude of the measurement unit relative to the moving body based on the detection result of the acceleration detection unit provided in the measurement unit when the moving body is traveling while accelerating and decelerating. The estimation step estimates the position of the measurement unit in the left-right direction of the moving body based on the left-right acceleration data of the moving body output by the acceleration detection unit during the rotation of the moving body, the left-right acceleration data of the moving body output by the acceleration sensor mounted on the moving body, and the yaw rate of the moving body output by the gyro sensor mounted on the moving body.

[0008] Furthermore, the invention described in the claims is, A program executed by a computer to estimate the orientation of a measuring unit that measures the distance to an object relative to a moving object, An estimation unit estimates the roll and pitch orientation of the measurement unit based on acceleration data output by an acceleration detection unit provided in the measurement unit when the moving unit is traveling or stopped at a predetermined speed. The computer is made to function as described above. Furthermore, the invention described in the claims is, A program executed by a computer to estimate the orientation of a measuring unit that measures the distance to an object relative to a moving object, When the moving body is moving while accelerating and decelerating, the computer functions as an estimation unit that estimates the attitude of the measurement unit relative to the moving body based on the detection result of the acceleration detection unit provided in the measurement unit. The estimation unit estimates the position of the measurement unit in the longitudinal direction of the moving body based on the distance between the road point and the moving body when the road point where the gradient changes, or when a bump on the road surface is measured by the measurement unit. Furthermore, the invention described in the claims is, A program executed by a computer to estimate the orientation of a measuring unit that measures the distance to an object relative to a moving object, An estimation unit estimates the attitude of the measurement unit relative to the moving object based on the detection result of the acceleration detection unit provided in the measurement unit when the moving object is moving with acceleration and deceleration. The computer is made to function as follows: The estimation unit estimates the position of the measurement unit in the left-right direction of the moving body based on the left-right acceleration data of the moving body output by the acceleration detection unit during the rotation of the moving body, the left-right acceleration data of the moving body output by the acceleration sensor mounted on the moving body, and the yaw rate of the moving body output by the gyro sensor mounted on the moving body. [Brief explanation of the drawing]

[0009] [Figure 1] This is a schematic diagram of the driver assistance system. [Figure 2] This is a block diagram showing the functional configuration of an in-vehicle device. [Figure 3] This figure shows the relationship between the vehicle coordinate system and the rider coordinate system, represented by two-dimensional coordinates. [Figure 4] This figure shows the relationship between the vehicle coordinate system and the rider coordinate system, represented by three-dimensional coordinates. [Figure 5] This figure shows the vector of gravitational acceleration in the vehicle coordinate system and the rider coordinate system. [Figure 6] This figure shows the z-direction measurements of the road surface taken by the rider while the vehicle was traveling on a flat road surface, before and after a change in the rider's position in the z-direction. [Figure 7] This figure shows the magnitude of the z-axis measurement of the rider of a vehicle traveling before and after the starting point of an uphill slope. [Figure 8] This graph shows the time-dependent changes in measured values ​​and vehicle pitch angle obtained during vehicle operation. [Figure 9] This figure shows the magnitude of the z-axis measurement of the rider of a vehicle traveling before and after a bump. [Figure 10] This graph shows the time-dependent changes in measured values ​​and vehicle pitch rate obtained during vehicle operation. [Figure 11] This diagram schematically illustrates the effects that occur on a vehicle during a turn. [Figure 12] This is an example flowchart showing the procedure for correcting the output of a lider. [Modes for carrying out the invention]

[0010] According to a preferred embodiment of the present invention, an estimation device for estimating the attitude of a measuring unit for measuring distance to an object relative to a moving body comprises an estimation unit that estimates the attitude of the measuring unit relative to the moving body based on the detection result of an acceleration detection unit provided on the measuring unit when the moving body is traveling with acceleration and deceleration. In this embodiment, the estimation device can suitably estimate the attitude of the measuring unit in the yaw direction relative to the vehicle. Note that the "traveling with acceleration and deceleration" includes both the mode of traveling with acceleration and the mode of traveling with deceleration.

[0011] In one embodiment of the estimation device described above, the estimation unit estimates the roll and pitch orientations of the measurement unit based on acceleration data output by the acceleration detection unit when the moving body is traveling or stopped at a predetermined speed, and estimates the yaw orientation of the measurement unit based on acceleration data output by the acceleration detection unit and the estimated roll and pitch orientations when the moving body is traveling with acceleration and deceleration. In this embodiment, the estimation device can suitably estimate the roll and pitch orientations of the measurement unit relative to the vehicle when the moving body is traveling or stopped at a predetermined speed, and suitably estimate the yaw orientation of the measurement unit relative to the vehicle when the moving body is traveling with acceleration and deceleration.

[0012] In another embodiment of the estimation device described above, the estimation unit estimates the amount of change in the posture based on the estimated posture of the measurement unit and the posture of the measurement unit stored in the memory unit. This allows the estimation device to suitably estimate the amount of change in the current posture relative to a standard posture stored in the memory unit.

[0013] In another embodiment of the estimation device described above, the estimation unit estimates the position of the measurement unit in the height direction based on measurement data from the measurement unit indicating the position of the road surface in the height direction. In this embodiment, the estimation device can suitably estimate the position of the measurement unit in the height direction.

[0014] In another embodiment of the estimation device described above, the estimation unit estimates the position of the measuring unit in the longitudinal direction of the moving body based on the distance between the road point where the gradient changes and the moving body when the road point is measured by the measuring unit. In this embodiment, the estimation device can suitably estimate the position of the measuring unit in the longitudinal direction of the moving body.

[0015] In another embodiment of the estimation device described above, the estimation unit calculates the distance based on the time difference between the change in data output by the tilt detection unit, which detects the tilt in the pitch direction of the moving body, and the change in measurement data output by the measurement unit. In this embodiment, the estimation device can suitably calculate the distance between the road point where the gradient changes and the moving body when the road point is measured by the measurement unit, and can use the position of the measurement unit in the longitudinal direction of the moving body for estimation.

[0016] In another embodiment of the estimation device described above, the estimation unit estimates the position of the measurement unit in the left-right direction of the moving body based on the left-right acceleration data of the moving body output by the acceleration detection unit during the rotation of the moving body, the left-right acceleration data of the moving body output by the acceleration sensor mounted on the moving body, and the yaw rate of the moving body output by the gyro sensor mounted on the moving body. In this embodiment, the estimation device can suitably estimate the position of the measurement unit in the left-right direction of the moving body.

[0017] In another embodiment of the estimation device described above, the estimation unit estimates the amount of change in the position based on the estimated position of the measurement unit and the position of the measurement unit stored in the storage unit. This allows the estimation device to suitably estimate the amount of change in the current position relative to the standard position of the measurement unit stored in the storage unit.

[0018] In another embodiment of the estimation device described above, the device further includes a correction unit that corrects the measurement data output by the measurement unit based on the amount of change. In this embodiment, the estimation device can correct the measurement data of the measurement unit so that the effects of the misalignment do not occur, even if the attitude or position of the measurement unit is misaligned.

[0019] In another embodiment of the estimation device described above, the device further includes a stop control unit that stops processing based on the measurement data output by the measurement unit when the amount of change is greater than or equal to a predetermined amount. In this embodiment, the estimation device can reliably suppress the decrease in accuracy of various processes using measurement data caused by using measurement data from a measurement unit with large deviations in attitude and position.

[0020] According to another preferred embodiment of the present invention, a control method performed by an estimation device for estimating the attitude of a measuring unit for measuring distance to an object relative to a moving body comprises an estimation step of estimating the attitude of the measuring unit relative to the moving body based on the detection result of an acceleration detection unit provided on the measuring unit when the moving body is traveling with acceleration and deceleration. By using this control method, the estimation device can suitably estimate the attitude of the measuring unit in the yaw direction relative to the vehicle.

[0021] According to another preferred embodiment of the present invention, a computer program is executed to estimate the attitude of a measuring unit that measures the distance to an object relative to a moving body, wherein the computer functions as an estimation unit that estimates the attitude of the measuring unit relative to the moving body based on the detection result of an acceleration detection unit provided on the measuring unit when the moving body is accelerating and decelerating. By executing this program, the computer can suitably estimate the attitude of the measuring unit in the yaw direction relative to the vehicle. Preferably, the program is stored in a storage medium. [Examples]

[0022] Hereinafter, preferred embodiments of the present invention will be described with reference to the drawings.

[0023] [Schematic configuration] Figure 1 is a schematic diagram of the driver assistance system according to this embodiment. The driver assistance system shown in Figure 1 includes an on-board unit 1 mounted on the vehicle that performs control related to driver assistance for the vehicle, a Lidar (Light Detection and Ranging, or Laser Illuminated Detection and Ranging) 2, a gyro sensor 3, a vehicle body acceleration sensor 4, and a Lidar acceleration sensor 5.

[0024] The in-vehicle unit 1 is electrically connected to the lidar 2, gyro sensor 3, vehicle body acceleration sensor 4, and lidar acceleration sensor 5, and acquires their output data. It also stores a map database (DB:DataBase) 10 that stores road data and feature information about features located near the road. Based on the output data and the map DB 10, the in-vehicle unit 1 estimates the vehicle's position (also called "vehicle position") and performs control related to vehicle driving assistance, such as automatic driving control, based on the estimation result of the vehicle position. The in-vehicle unit 1 also estimates the attitude and position of the lidar 2 based on the outputs of the lidar 2, gyro sensor 3, vehicle body acceleration sensor 4, and lidar acceleration sensor 5. Based on this estimation result, the in-vehicle unit 1 performs processing such as correcting each measured value of the point cloud data output by the lidar 2. The in-vehicle unit 1 is an example of an "estimation device" in the present invention.

[0025] The lidar 2 discretely measures the distance to an object in the external environment by emitting a pulsed laser within a predetermined angular range in the horizontal and vertical directions, and generates three-dimensional point cloud information indicating the position of the object. In this case, the lidar 2 has 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 an output unit that outputs scan data based on the received signal output by the light receiving unit. 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 that irradiation direction of the laser light, which is determined based on the received signal described above, and is supplied to the in-vehicle unit 1. In this embodiment, as an example, the lidar 2 is provided in the front and rear portions of the vehicle, respectively. The lidar 2 is an example of a "measurement unit" in the present invention.

[0026] The gyro sensor 3 is installed on the vehicle and supplies an output signal corresponding to the vehicle's yaw rate to the on-board unit 1. The vehicle body acceleration sensor 4 is a 3-axis acceleration sensor installed on the vehicle and supplies detection signals corresponding to the acceleration data of the three axes corresponding to the vehicle's direction of travel, lateral direction, and height direction to the on-board unit 1. The gyro sensor 3 and the vehicle body acceleration sensor 4 are examples of the "tilt detection unit" in this invention. The rider acceleration sensor 5 is a 3-axis acceleration sensor installed on each rider 2 and supplies detection signals corresponding to the acceleration data of the three axes of the installed rider 2 to the on-board unit 1. The rider acceleration sensor 5 is an example of the "acceleration detection unit" in this invention.

[0027] Figure 2 is a block diagram showing the functional configuration of the in-vehicle unit 2. The in-vehicle unit 2 mainly consists of an interface 11, a storage unit 12, an input unit 14, a control unit 15, and an information output unit 16. Each of these elements is interconnected via a bus line.

[0028] Interface 11 acquires output data from sensors such as the rider 2, gyro sensor 3, vehicle body acceleration sensor 4, and rider acceleration sensor 5, and supplies it to the control unit 15. Interface 11 also supplies signals related to vehicle driving control generated by the control unit 15 to the vehicle's electronic control unit (ECU).

[0029] The storage unit 12 stores programs to be executed by the control unit 15 and information necessary for the control unit 15 to perform predetermined processing. In this embodiment, the storage unit 12 has a map DB 10 and rider placement information IL. The rider placement information IL is information about the relative three-dimensional position and attitude of each rider 2 at a certain reference time (for example, immediately after alignment adjustment of rider 2, when no attitude or positional deviation has occurred). In this embodiment, the attitude of rider 2, etc., is represented by the roll angle, pitch angle, and yaw angle (i.e., Euler angle). The rider placement information IL may be information about the position and attitude measured at the above reference time, or it may be information about the position and attitude of rider 2 estimated by the in-vehicle unit 1 through the position and attitude estimation processing of rider 2 described later.

[0030] The input unit 14 includes buttons, a touch panel, a remote controller, a voice input device, etc., for user operation, and accepts inputs such as specifying a destination for route searching and specifying whether to turn autonomous driving on or off. The information output unit 16 includes, for example, a display or speaker that outputs based on the control of the control unit 15.

[0031] The control unit 15 includes a CPU for executing programs and controls the entire in-vehicle unit 1. Based on the output signals of each sensor supplied from the interface 11 and the map DB 10, the control unit 15 estimates the vehicle's position and performs control related to vehicle driving assistance, including automatic driving control, based on the estimated vehicle position. When the control unit 15 uses the output data of the rider 2, it converts the measurement data output by the rider 2 from a coordinate system based on the rider 2 to a coordinate system based on the vehicle, using the attitude and position of the rider 2 recorded in the rider installation information IL as a reference. Furthermore, in this embodiment, the control unit 15 estimates the current (i.e., processing reference time) position and attitude of the rider 2 relative to the vehicle, calculates the amount of change from the position and attitude recorded in the rider installation information IL, and corrects the measurement data output by the rider 2 based on this amount of change. As a result, even if there is a shift in the position or attitude of the rider 2, 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 the "estimation unit," "correction unit," "stop control unit," and "computer" that executes the program in the present invention.

[0032] [Rider position and attitude estimation] Next, the method for estimating the position and attitude of LiDAR 2 will be explained. The in-vehicle unit 1 performs the following processing for each LiDAR 2.

[0033] (1) Coordinate system transformation The 3D coordinates of each measurement point in the 3D point cloud data acquired by LIDA2 are expressed in a coordinate system based on the position and orientation of LIDA2 (also called the "LIDA coordinate system"), and need to be converted to a coordinate system based on the position and orientation of the vehicle (also called the "vehicle coordinate system"). Here, we will first explain the conversion between the LIDA coordinate system and the vehicle coordinate system.

[0034] Figure 3 shows the relationship between the vehicle coordinate system and the rider coordinate system, represented by two-dimensional coordinates. Here, the vehicle coordinate system has the center of the vehicle as the origin and the coordinate axis "x" along the direction of travel of the vehicle. b "and the coordinate axis "y" along the side of the vehicleb has "". Also, the lidar coordinate system has a coordinate axis "x" along the front direction of lidar 2 (see arrow A2). L and a coordinate axis "y" along the side direction of lidar 2. L has "".

[0035] Here, when the yaw angle of lidar 2 with respect to the vehicle coordinate system is "L", and the position of lidar 2 is [L, L], the measurement point [x(k), y(k)] at time "k" as seen from the vehicle coordinate system is converted to the coordinates [x(k), y(k)] in the lidar coordinate system by the following equation (1) using the rotation matrix "C". ψ0 ", and the position of lidar 2 is [L x0 , L y0 T When considering this, the measurement point [x b (k), y b (k)] at time "k" as seen from the vehicle coordinate system is T converted to the coordinates [x ψ0 (k), y L (k)] in the lidar coordinate system by the following equation (1) using the rotation matrix "C". L (k)] T is converted to.

[0036]

Equation

[0037]

Equation

[0038] ​The roll angle of the Rider 2 relative to the vehicle coordinate system is "L φ0 ", pitch angle "L θ0 ", the yaw angle is "L ψ0 " and the coordinate axis x of Rider 2 b The position in is "L x0 ", coordinate axis y b The position in is "L y0 ", coordinate axis z b The position in is "L z0 If this is the case, the measurement point [x] at time "k" as seen from the vehicle coordinate system. b0 (k), y b0 (k), z b0 (k)] T These are the rotation matrices "C" corresponding to roll, pitch, and yaw. φ0 "C θ0 "C ψ0 The following equation (3), using the direction cosine matrix "C0" represented by ", gives the coordinates [x in the Lider coordinate system] L0 (k), y L0 (k), z L0 (k)] T It will be converted to [this].

[0039]

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[0040]

number

[0041] (2) Estimation of roll angle and pitch angle Next, the roll angle L of the Rider 2 φ0 and pitch angle L θ0 The estimation method will be explained below. As described below, the in-vehicle device 1 estimates the roll angle L of the rider 2 based on the 3-axis acceleration output values ​​obtained from the rider acceleration sensor 5 installed on the target rider 2. φ0 and pitch angle L θ0 We estimate this. Hereafter, for the sake of explanation, we will assume that the ridiculometer accelerometer 5 measures the acceleration of the three axes of the ridiculometer coordinate system.

[0042] When a vehicle is stationary on a level surface or traveling at a constant speed, the only acceleration in the vehicle coordinate system is the gravitational acceleration g in the z direction. Figure 5(A) shows the vector of gravitational acceleration g in the vehicle coordinate system, and Figure 5(B) shows the vector of gravitational acceleration g in the lidar coordinate system. Therefore, the output value of the lidar coordinate system of the lidar acceleration sensor 5 [α x ,α y ,α z ] T The following equation (5) holds true.

[0043]

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[0044]

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[0045]

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[0046]

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[0047]

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[0048]

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[0049] (3) Estimation of Yaw angle Next, the yaw angle L of Rider 2 ψ0The estimation method will be described. As described below, the in-vehicle unit 1 uses the calculated roll angle L of the lidar 2 φ0 and pitch angle L θ0 to estimate the yaw angle L based on the three-axis acceleration output values obtained from the lidar acceleration sensor 5 while the vehicle is accelerating or decelerating on a straight road. ψ0

[0050] When the vehicle is accelerating or decelerating on a straight road with an acceleration “α”, in the vehicle coordinate system, an acceleration α occurs in the x direction and a gravitational acceleration g occurs in the z direction. Therefore, for the output values [α x , α y , α z of the lidar acceleration sensor 5 T the following equation (11) holds.

[0051]

Equation

[0052] First, using α y , α z in equation (11), the following equations (12) and (13) hold respectively.

[0053]

Equation

[0054]

Equation

[0055] Then, subtracting equation (12) from equation (13), the following equation (I4) is obtained.

[0056]

Equation

[0057] ​ Similarly, for α in Equation (11) y , α z , the following Equations (15) and (16) hold respectively.

[0058]

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[0059]

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[0060]

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[0061]

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[0062]

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[0063]

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[0064] (4) Calculation of changes in posture Next, we will provide a supplementary explanation regarding the calculation of the changes in the pitch angle, roll angle, and yaw angle of Rider 2 from the time of generation of the Rider placement information IL to the current time, which is the processing reference point. In the following, the pitch angle, roll angle, and yaw angle of Rider 2 recorded in the Rider placement information IL (i.e., the initial state when there is no attitude or positional deviation of Rider 2) will be used, respectively, as "L φ0 "L θ0 "L ψ0 "

[0065] Due to some influence, the roll angle of rider 2 becomes "ΔL" as shown in equation (21) below. φ ", the pitch angle is "ΔL θ ", the yaw angle is "ΔL ψ Only the LR installation information IL changes from the time of generation, and the roll angle at the processing reference time is "L φ ", pitch angle is "L θ ", pitch angle is "L ψ Let's assume it becomes ".

[0066]

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[0067]

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[0068]

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[0069] (5) Calculation of the change in position in the z-direction Next, the method for calculating the change in position of the rider 2 in the z direction will be explained. The onboard unit 1 calculates the change in position of the rider 2 in the z direction "ΔL" based on the z-direction values ​​of the measurement points of the rider 2 that were measured on the road surface while the vehicle was stopped or traveling at a constant speed on a flat road. z Calculate ".

[0070] The coordinates of the measurement point at time k in the vehicle coordinate system at the processing reference point [x b (k), y b (k), z b (k)] T The coordinates [x] shown by equation (4) are given by equation (4). b0 (k), y b0 (k), z b0 (k)] T Similarly, using the direction cosine matrix "C", it can be expressed by the following equation (24).

[0071]

number

[0072] Figure 6(A) shows the position L of Rider 2. zThe z-direction measurement of the road surface measured by Rider 2 when the vehicle was traveling on a flat road surface before the change. b0 (k) is shown, and Figure 6(B) shows the position L of rider 2. z After the change, the measured value of the road surface in the z direction, as measured by Rider 2 while the vehicle is traveling on a flat road surface. b (k) is shown. As shown in Figures 6(A) and (B), the measured value z b0 (k), measured value z b (k) represents the position L in the z direction of Rider 2. z0 , L z They are all the same length.

[0073] Therefore, the measured value of the road surface z calculated by equation (4) b0 (k) and the measured value of the road surface after the change in posture z b The difference from (k) is the change in the z direction ΔL z It can be seen that this is equal to z. The measured value z used in this case b0 (k) and measured value z b (k) should preferably be the average and time average across multiple scan lines.

[0074] Taking the above into consideration, the in-vehicle unit 1 calculates the change amount ΔL based on the following equation (25). z Calculate.

[0075]

number

[0076] Note that the in-vehicle unit 1 is in its initial position L z0The suspension stroke amount (i.e., the amount of sag from the fully extended position) of the vehicle is estimated at the time of measurement and at the processing reference time, and the change amount ΔL in the z direction is calculated based on the difference in the estimated stroke amounts. z This may be corrected. In this case, the in-vehicle device 1 may measure the suspension stroke amount based on a stroke sensor or the like provided on the vehicle's suspension, or it may estimate the suspension stroke amount based on the number of passengers in the vehicle. This will allow for a more accurate determination of the change amount ΔL. z It is possible to calculate this.

[0077] (6) Calculation of the change in position in the x-direction Next, the method for calculating the change in position of the rider 2 in the x-direction will be explained. When the vehicle-mounted unit 1 is near the start or end of a slope, or when passing over a bump on the road surface, it calculates the change in position L in the x-direction based on the time difference between the change in the z-direction measurement value of the rider 2 and the change in pitch rate obtained from the gyro sensor 3. x Calculate.

[0078] Figures 7(A) to 7(G) show the z-direction measurements of a specific scanline of the rider 2 of a vehicle traveling before and after the starting point 50 of an uphill slope. b This figure shows the magnitude of (k) represented by line segments 51-57. Figure 8(A) shows the measured value z measured during the operation of the vehicle shown in Figures 7(A) to 7(G). b Figure 8(A) is a graph showing the time change of (k), and Figure 8(B) is a graph showing the time change of the vehicle body pitch angle (integral value of pitch rate) over the same period as Figure 8(A). Note that the numbers 51 to 57 in Figures 8(A) and 8(B) correspond to the measured values ​​z shown by line segments 51 to 57 in Figures 7(A) to 7(G). b These indicate the positions corresponding to (k).

[0079] Just before the start or end of a sloping road surface, such as an uphill or downhill slope, the measurement value of the lidar 2 in the z direction, with the road surface as the measurement point, changes near the start or end of the slope. In the example in Figure 7, as shown in Figure 8(A), the measurement value z changes from the time "t1" (see Figure 7(B)) when the lidar 2 illuminates the starting point 50 (i.e., the point where the gradient changes).b (k) gradually changes, and at time "t2" (see Figure 7(D)) when the front wheels of the vehicle reach the starting point 50, the measured value z b (k) is minimized. After that, the measured value z gradually decreases. b (k) becomes larger, and the measured value z when the rear wheel approaches the starting point 50 (see Figure 7(F)) b (k) is the measured value z when driving on a flat road surface. b This is the same as (k).

[0080] Taking the above into consideration, the in-vehicle device 1 measures the measured value z b From time t1 (see Figure 7(B)) when (k) begins to decrease, the measured value z b Calculate the time interval "Δt" until the time t2 (see Figure 7(D)) when (k) is minimized.

[0081] Here, the time interval Δt corresponds to the time required for the vehicle to travel the distance d shown in Figure 7(A), and the distance d corresponds to the distance from the starting point 50 of the slope to the front wheels of the vehicle when the starting point 50 of the slope is detected on a specific scanline. The time interval Δt is an example of a "time difference" in the present invention.

[0082] Then, as shown in equation (26) below, the in-vehicle unit 1 calculates the distance d by determining the vehicle's speed "v" from the vehicle speed pulse and multiplying it by the time interval Δt.

[0083]

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[0084] Furthermore, the on-board unit 1 can similarly measure the distance d when passing over a bump on the road surface. Figures 9(A) to 9(G) show the z-direction measurement values ​​of the rider 2 of the vehicle traveling before and after the bump 60. bThis figure shows the magnitude of (k) represented by line segments 61-66. Figure 10(A) shows the measured values ​​z obtained during the operation of the vehicle shown in Figures 9(A) to 9(G). b Figure 10(A) is a graph showing the time change of (k), and Figure 10(B) is a graph showing the time change of the vehicle body pitch rate over the same period as Figure 10(A). Note that the numbers 61 to 66 in Figures 10(A) and 10(B) correspond to the measured values ​​z indicated by line segments 61 to 66 in Figures 9(A) to 9(G). b (k) indicates the corresponding position. In this case, as shown in Figure 10(A), the measured value z in the z direction of the vehicle's rider 2. b (k) is the measured value z at the time "t3" (see Figure 9(B)) when bump 60 is irradiated. b (k) temporarily decreases, and the measured value z is at time "t4" (see Figure 9(D)) when the front wheels of the vehicle exceed bump 60. b (k) It increases temporarily. Therefore, the in-vehicle device 1 will measure the z b From time t3 (see Figure 9(B)) when (k) temporarily decreased, the measured value z b The time interval up to time t4 (see Figure 9(D)) when (k) temporarily becomes large is calculated as the time interval Δt. This also allows the on-board unit 1 to suitably calculate the distance d based on equation (26). In addition, as shown in Figure 10(B), the on-board unit 1 can also determine time t4 when the front wheels of the vehicle exceed the bump 60 using the pitch rate (vehicle pitch rate in Figure 10(B)) measured by the gyro sensor 3 mounted on the vehicle or rider 2.

[0085] Next, the change in position ΔL is obtained from the distance d. x The method for calculating the change in the x-direction of the rider 2 is explained below. The in-vehicle unit 1 stores the distance "d0" before the position of the rider 2 changes, and as shown in equation (27) below, it takes the difference with distance d to calculate the change in the x-direction of the rider 2 ΔL. x It is possible to calculate this.

[0086]

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[0087] (7) Calculation of the change in position in the y-direction Next, the method for calculating the change in position of the rider 2 in the y-direction will be explained. During vehicle rotation, the onboard unit 1 calculates the position L of the rider 2 in the y-direction from the y-direction output value of the rider acceleration sensor 5, the y-direction output value of the vehicle body acceleration sensor 4, and the output value of the gyro sensor 3. y Calculate.

[0088] Figure 11 is a schematic diagram illustrating the effects on a vehicle during a turn. Generally, the velocity of the vehicle's center of gravity during a turn is "V G ” and centripetal acceleration “α G The answer is given by equations (28) and (29) below.

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[0098] [Processing flow] Figure 12 is an example flowchart showing the procedure for correcting the output of rider 2. The in-vehicle unit 1 repeatedly executes the process shown in Figure 12 at predetermined intervals.

[0099] First, the in-vehicle unit 1, while the vehicle is stopped or traveling at a constant speed on a level road, calculates the change in the roll angle ΔL of the rider 2 from the output value of the rider acceleration sensor 5. φ and the change in pitch angle ΔL θ The roll angle L of the rider 2 is calculated (step S101). In this case, the in-vehicle unit 1 calculates the roll angle L of the rider 2 based on formulas equivalent to formulas (7) and (10). φ pitch angle L θ The roll angle L is calculated and recorded in the rider installation information IL. φ0 pitch angle L θ0 The difference between these two is the change ΔL φ ΔL θ It is calculated as follows.

[0100] Next, the in-vehicle unit 1 calculates the change in the yaw angle of the rider 2, ΔL, from the output value of the rider acceleration sensor 5 while the vehicle is accelerating or decelerating on a straight road. ψ The yaw angle L of the rider 2 is calculated (step S102). In this case, the in-vehicle unit 1 calculates the yaw angle L of the rider 2 based on an equation equivalent to equation (20). ψ The yaw angle L is calculated and recorded in the lidar installation information IL. ψ0 The difference between these two is the change ΔL ψ It is calculated as follows.

[0101] Next, when the vehicle is stopped or traveling at a constant speed on a flat road, the in-vehicle unit 1 calculates the z-direction position change ΔL from the z-direction measurement of the lidar 2 that illuminates the road surface. z The following is calculated (step S103). In this case, the onboard unit 1 calculates the measured value of the road surface z when the vehicle is stopped or traveling at a constant speed on a flat road surface. b The average of (k) is calculated, and the measured road surface value z under the same conditions is recorded in the rider installation information IL. b0 The change ΔLz is calculated by taking the difference between (k) and the mean (see equation (25)).

[0102] Next, the in-vehicle unit 1 calculates the change in position ΔL in the x direction by determining the time interval Δt between the change in the z-direction measurement value of the rider 2 and the change in the output value of the gyro sensor when the vehicle is near the start or end of a slope, or when passing over a bump on the road surface. x The following is calculated (step S104). In this case, the in-vehicle unit 1 calculates the distance d by multiplying the time interval Δt by the vehicle's travel speed v, and calculates the difference between this and the distance d0 previously stored in the rider installation information IL as the change amount ΔL. z It is calculated as follows (see formula (26)).

[0103] Next, during vehicle rotation, the in-vehicle unit 1 calculates the change in position in the y-direction ΔL from the y-direction output value of the rider acceleration sensor 5, the y-direction output value of the vehicle body acceleration sensor 4, and the output value of the gyro sensor 3. y The following is calculated (step S105). Specifically, the in-vehicle unit 1 calculates the position L at the processing reference time based on formula (36). y The initial position L is calculated and stored in the rider installation information IL. y0 The difference between these is the change in position in the y direction, ΔL. y It is calculated as follows.

[0104] Next, the in-vehicle device 1 calculates the change amount ΔL in steps S101 to S105. φ ΔL θ ΔL ψ ΔL x ΔL y ΔL zIt is determined whether there are any that exceed a predetermined threshold (step S106). The threshold mentioned above is used to determine whether the measurement data of Rider 2 can be used after the correction processing of the measurement data of Rider 2 in step S108, which will be described later, and is set in advance based on experiments, for example. Then, the in-vehicle unit 1 determines the change amount ΔL calculated in steps S101 to S105. φ ΔL θ ΔL ψ ΔL x ΔL y ΔL z If any of these exceed a predetermined threshold (step S106; Yes), the use of the output data of the target Rider 2 (i.e., use for obstacle detection, vehicle position estimation, etc.) is stopped, and the information output unit 16 outputs a warning that the target Rider 2 needs to be realigned (step S107). This reliably suppresses the reduction in safety that may occur due to using measurement data of a Rider 2 whose attitude and position have been significantly misaligned due to an accident, etc. The threshold mentioned above is an example of a "determined amount" in this invention.

[0105] On the other hand, the in-vehicle device 1 has a change of ΔL φ ΔL θ ΔL ψ ΔL x ΔL y ΔL z If none of the values ​​exceed a predetermined threshold (step S106; No), the measured values ​​of the point cloud data output by the lidar 2 are corrected based on these change amounts (step S108). In this case, the in-vehicle device 1 stores, for example, a map showing the correction amount for each magnitude of change in the measured values, and corrects the measured values ​​by referring to the map. Alternatively, the measured values ​​may be corrected using a predetermined percentage of the change amount as the correction amount.

[0106] As described above, the in-vehicle unit 1 in this embodiment at least estimates the attitude of the rider 2 relative to the vehicle, which measures the distance to an object. It performs processing such as estimating the attitude of the rider 2 relative to the vehicle based on the detection results of the rider acceleration sensor 5 provided on the rider 2 when the vehicle is accelerating and decelerating. As a result, the in-vehicle unit 1 can perform processing to convert the measurement data output by the rider 2 into the vehicle coordinate system with high accuracy, and can also determine whether the rider 2 is usable or not.

[0107] [Differentiation] The following describes suitable modifications for the examples. The following modifications may be applied in combination to the examples.

[0108] (Variation 1) In step S108 of Figure 12, instead of correcting each measured value of the point cloud data output by the rider 2 based on the change amounts calculated in steps S101 to S105, the in-vehicle device 1 may convert each measured value to the vehicle coordinate system based on the estimated attitude and position of the rider 2 at the processing reference time calculated in steps S101 to S105.

[0109] In this case, the in-vehicle device 1 uses the roll angle L calculated in steps S101 to S105. φ pitch angle L θ , yaw angle L ψ , x-direction position L x , y-direction position L y , z-direction position L z Using this method, based on equation (24), each measured value of the point cloud data output by Lidar 2 can be converted from the Lidar coordinate system to the vehicle body coordinate system, and based on the converted data, the following may be performed: self-position estimation, automatic driving control, etc.

[0110] In other examples, if each rider 2 is equipped with an adjustment mechanism such as an actuator for correcting the attitude and position of each rider 2, the in-vehicle unit 1 may, instead of performing the process in step S108, perform control to drive the adjustment mechanism to correct the attitude and position of the rider 2 by the amount of change calculated in steps S101 to S105.

[0111] (Modification 2) The configuration of the driver assistance system shown in Figure 1 is an example, and the configuration of the driver assistance system to which the present invention can be applied is not limited to the configuration shown in Figure 1. For example, instead of having an in-vehicle unit 1, the driver assistance system may have the vehicle's electronic control unit perform the processing shown in Figure 12, etc. In this case, the lidar installation information IL is stored, for example, in a storage unit in the vehicle, and the vehicle's electronic control unit is configured to receive output data from various sensors such as the lidar 2. [Explanation of symbols]

[0112] 1 On-vehicle device 2 Riders 3. Gyroscope 4. Vehicle-mounted acceleration sensor 5. Accelerometer for LiDAR 10 Map Database

Claims

1. An estimation device for estimating the orientation of a measuring unit relative to a moving body, which measures the distance to an object, An estimation device having an estimation unit that estimates the attitude of the measurement unit in the roll direction and pitch direction based on acceleration data output by an acceleration detection unit provided in the measurement unit when the moving unit is traveling or stopped at a predetermined speed.

2. The estimation device according to claim 1, wherein the estimation unit estimates the yaw direction attitude of the measurement unit based on acceleration data output by the acceleration detection unit when the moving body is traveling with acceleration and deceleration, and the estimated roll direction and pitch direction attitudes.

3. The estimation device according to claim 1 or 2, wherein the estimation unit estimates the amount of change in the posture based on the estimated posture of the measurement unit and the posture of the measurement unit stored in the storage unit.

4. The estimation device according to any one of claims 1 to 3, wherein the estimation unit estimates the position of the measurement unit in the height direction based on measurement data from the measurement unit indicating the position of the road surface in the height direction.

5. The estimation device according to claim 4, wherein the estimation unit estimates the amount of change in the position based on the estimated position of the measurement unit and the position of the measurement unit stored in the storage unit.

6. The estimation device according to claim 3 or 5, further comprising a correction unit that corrects the measurement data output by the measurement unit based on the amount of change.

7. The estimation device according to claim 3 or 5, further comprising a stop control unit that stops processing based on measurement data output by the measurement unit when the amount of change is greater than or equal to a predetermined amount.

8. An estimation device for estimating the orientation of a measuring unit relative to a moving body, which measures the distance to an object, An estimation unit estimates the attitude of the measurement unit relative to the moving object based on the detection result of the acceleration detection unit provided in the measurement unit when the moving object is moving with acceleration and deceleration. It has, The estimation unit is an estimation device that estimates the position of the measuring unit in the longitudinal direction of the moving body based on the distance between the road point and the moving body when the road point where the gradient changes, or a bump on the road surface, is measured by the measuring unit.

9. The estimation device according to claim 8, wherein the estimation unit calculates the distance based on the time difference between the change in data output by the tilt detection unit that detects the tilt in the pitch direction of the moving body and the change in measurement data output by the measurement unit.

10. An estimation device for estimating the orientation of a measuring unit relative to a moving body, which measures the distance to an object, An estimation unit estimates the attitude of the measurement unit relative to the moving object based on the detection result of the acceleration detection unit provided in the measurement unit when the moving object is moving with acceleration and deceleration. It has, The estimation unit is an estimation device that estimates the position of the measurement unit in the left-right direction of the moving body based on the left-right acceleration data of the moving body output by the acceleration detection unit during the rotation of the moving body, the left-right acceleration data of the moving body output by an acceleration sensor mounted on the moving body, and the yaw rate of the moving body output by a gyro sensor mounted on the moving body.

11. A control method performed by an estimation device that estimates the attitude of a measuring unit, which measures the distance to an object, relative to a moving object, A control method comprising an estimation step of estimating the attitude of the measurement unit in the roll direction and pitch direction based on acceleration data output by an acceleration detection unit provided in the measurement unit when the moving unit is traveling or stopped at a predetermined speed.

12. A control method performed by an estimation device that estimates the attitude of a measuring unit, which measures the distance to an object, relative to a moving object, The measurement unit has an estimation step of estimating the attitude of the measurement unit relative to the moving body based on the detection result of the acceleration detection unit provided in the measurement unit when the moving body is traveling while accelerating and decelerating. The estimation step is a control method that estimates the position of the measuring unit in the longitudinal direction of the moving body based on the distance between the road point and the moving body when the road point where the gradient changes, or a bump on the road surface, is measured by the measuring unit.

13. A control method performed by an estimation device that estimates the attitude of a measuring unit, which measures the distance to an object, relative to a moving object, The measurement unit has an estimation step of estimating the attitude of the measurement unit relative to the moving body based on the detection result of the acceleration detection unit provided in the measurement unit when the moving body is traveling while accelerating and decelerating. The estimation step is a control method that estimates the position of the measurement unit in the left-right direction of the moving body based on the left-right acceleration data of the moving body output by the acceleration detection unit during the rotation of the moving body, the left-right acceleration data of the moving body output by the acceleration sensor mounted on the moving body, and the yaw rate of the moving body output by the gyro sensor mounted on the moving body.

14. A program executed by a computer to estimate the orientation of a measuring unit that measures the distance to an object relative to a moving object, An estimation unit estimates the roll and pitch orientation of the measurement unit based on acceleration data output by an acceleration detection unit provided in the measurement unit when the moving unit is traveling or stopped at a predetermined speed. A program that causes the aforementioned computer to function.

15. A program executed by a computer to estimate the orientation of a measuring unit that measures the distance to an object relative to a moving object, When the moving body is moving while accelerating and decelerating, the computer functions as an estimation unit that estimates the attitude of the measurement unit relative to the moving body based on the detection result of the acceleration detection unit provided in the measurement unit. The estimation unit is a program that estimates the position of the measurement unit in the longitudinal direction of the moving body based on the distance between the road point and the moving body when the road point where the gradient changes, or when a bump on the road surface is measured by the measurement unit.

16. A program executed by a computer to estimate the orientation of a measuring unit that measures the distance to an object relative to a moving object, An estimation unit estimates the attitude of the measurement unit relative to the moving object based on the detection result of the acceleration detection unit provided in the measurement unit when the moving object is moving with acceleration and deceleration. The computer is made to function as follows: The estimation unit is a program that estimates the position of the measurement unit in the left-right direction of the moving body based on the left-right acceleration data of the moving body output by the acceleration detection unit during the rotation of the moving body, the left-right acceleration data of the moving body output by the acceleration sensor mounted on the moving body, and the yaw rate of the moving body output by the gyro sensor mounted on the moving body.

17. A storage medium storing the program described in any one of claims 14 to 16.

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