Axis deviation estimation device

Abstract

When the orientation of the radar device when the radar device is mounted in a reference state is set as the mounting reference direction and the actual orientation of the radar device is set as the mounting actual direction, the axis deviation angle estimating unit (37) estimates the vertical axis deviation angle representing the deviation angle of the mounting actual direction in the vertical direction relative to the mounting reference direction based on the roadside object information including information of multiple reflection points on the roadside object and the road surface information including information of multiple reflection points on the road surface.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This international application claims the priority based on Japanese Patent Application No. 2020-47820 filed with the Japan Patent Office on March 18, 2020, the entire contents of which are incorporated herein by reference. Technical Field

[0003] The present disclosure relates to a technique for estimating an axial offset of a radar device. Background Art

[0004] Conventionally, in vehicle-mounted radar devices, the central axis of the radar beam may shift due to changes in the setting state for some reason, which is called axis shift. If such axis shift occurs, the detection accuracy of the object to be detected by the radar device is reduced.

[0005] As a countermeasure, for example, Patent Document 1 below discloses a technique for estimating the angle of axis deviation in the vertical direction (ie, vertical axis deviation) of a radar device by utilizing the phenomenon that the reception intensity of reflected waves from a road surface near a vehicle becomes maximum.

[0006] Patent Document 1: Japanese Patent No. 6321448

[0007] As a result of detailed studies by the inventors regarding the above-mentioned technology, the following problems have been discovered.

[0008] In the above-mentioned technology, the vertical axis deviation angle (ie, the vertical axis deviation angle) is estimated using the reception intensity of the reflected wave on the road surface. Therefore, when the slope of the road surface changes, it is not easy to estimate the vertical axis deviation angle with good accuracy.

[0009] That is, when there is a vertical axis offset, the reception intensity of the reflected wave changes, but when the slope of the road surface changes, the reception intensity of the reflected wave also changes. Therefore, in such a case, it is not easy to detect the vertical axis offset based on the reflected wave of the road surface. Summary of the invention

[0010] One aspect of the present disclosure is to provide a technology capable of estimating a vertical axis deviation angle of a radar device with high accuracy.

[0011] An axial offset estimating device according to one aspect of the present disclosure relates to an axial offset estimating device for estimating an axial offset of a radar device mounted on a mobile object.

[0012] The axial misalignment estimation device includes an object information acquisition unit, a roadside object extraction unit, a road surface extraction unit, and an axial misalignment angle estimation unit.

[0013] The object information acquisition unit is configured to repeatedly acquire object information, wherein the object information includes an object distance and an object azimuth, wherein the object distance is the distance between the radar device and a reflecting object corresponding to a reflection point of the radar wave detected by the radar device, and the object azimuth is the azimuth at which the reflecting object is located.

[0014] The roadside object extraction unit is configured to extract roadside object information related to the roadside object from the object information. That is, the roadside object information is extracted from the object information based on a predetermined extraction condition, the roadside object information represents information of a reflection point on the roadside object, and the roadside object is arranged on the side of the travel path on which the mobile body travels, at a position higher than the travel path, along the extension direction of the travel path, according to the predetermined condition.

[0015] The road surface extraction unit is configured to extract road surface information from the object information based on a predetermined extraction condition, the road surface information indicating information of reflection points on a road surface of a travel path on which the moving body travels.

[0016] The axis deviation angle estimating unit is configured as follows: when the orientation of the radar device when the radar device is mounted in a reference state is set as the mounting reference direction, and the actual orientation of the radar device is set as the mounting actual direction, a vertical axis deviation angle is estimated based on roadside object information including information of multiple reflection points on the roadside object and road surface information including information of multiple reflection points on the road surface. The vertical axis deviation angle represents the deviation angle of the mounting actual direction in the vertical direction relative to the mounting reference direction.

[0017] With such a structure, in one aspect of the present disclosure, it is possible to easily extract roadside object information such as the position of a roadside object arranged along the travel path from object information related to a reflecting object obtained by driving a radar device. The roadside object is arranged along the travel path at a position higher than the road surface of the travel path on the side of the travel path according to prescribed conditions, so that the reflected wave on the roadside object is easier to detect than the reflected wave on the road surface. Therefore, it is possible to easily grasp the state of the position of the roadside object based on the roadside object information.

[0018] Therefore, for example, the slope of the road surface can be estimated based on the roadside object information indicating the change in the height of the roadside object (i.e., the slope). For example, if the roadside object is located higher as it gets farther away, it can be estimated that the road surface also rises as it gets farther away (i.e., uphill).

[0019] Therefore, for example, when estimating the vertical axis offset of the radar device based on road surface information, the road surface gradient and other conditions can be estimated based on the roadside object information obtained by the reflected wave from the characteristic roadside object.

[0020] That is, when the road surface has a slope, the reception state of the radar wave changes according to the slope of the road surface, etc., but in one aspect of the present disclosure, the slope of the road surface, etc. can be grasped based on the roadside object information. Therefore, the vertical axis offset is estimated based on such characteristic roadside object information and road surface information, thereby improving the accuracy of the estimation of the vertical axis offset compared to the case of using only the road surface information.

[0021] In addition, the vertical axis offset is estimated based on the roadside object information and the road surface information, so there is an advantage that the stability when estimating the vertical axis offset is increased and the robustness is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 This is a block diagram showing a vehicle control system including the axial deviation estimating device according to the first embodiment.

[0023] Figure 2 This is an explanatory diagram for explaining the irradiation range of radar waves in the horizontal direction.

[0024] Figure 3 This is an explanatory diagram for explaining the vertical irradiation range of radar waves.

[0025] Figure 4 This is a block diagram functionally showing the axial offset estimating device according to the first embodiment.

[0026] Figure 5 It is an explanatory diagram for explaining the vertical axis offset angle and the roll angle.

[0027] Figure 6 It is an explanatory diagram for explaining the axis deviation of the radar device.

[0028] Figure 7 This is an explanatory diagram for explaining the arrangement of road guardrails and the like on a plane.

[0029] Figure 8 This is an explanatory diagram for explaining a guardrail and the arrangement of its reflection points in the vertical direction.

[0030] Fig. 9 This is an explanatory diagram showing the relationship among the vertical axis offset angle, the arrangement of reflection points, and the approximate straight line.

[0031] Fig.10 This is an explanatory diagram for explaining the arrangement of reflection points on the road surface in the vertical direction, etc.

[0032] Fig.11 It is an explanatory diagram for explaining the arrangement of reflection points when the road surface is inclined.

[0033] Fig.12 : is a flowchart showing the main routine of the shaft offset estimation process.

[0034] Fig.13 Detailed description of the process of extracting roadside object candidate points.

[0035] Fig.14 Detailed description of the process of extracting a roadside object point group.

[0036] Fig.15 This is a flowchart showing the vertical axis deviation angle estimation process using roadside objects.

[0037] Fig.16 It is an explanatory diagram for explaining the inflection points in the reflection point group.

[0038] Fig.17 This is an explanatory diagram for explaining the relationship between the vehicle system coordinates, the device system coordinates, and the vertical axis offset angle.

[0039] Fig.18 is a flowchart showing the road surface reflection extraction process.

[0040] Fig.19 : is a flowchart showing the vertical axis deviation angle estimation process using road surface reflection.

[0041] Fig. 20 It is a flowchart showing the processing in the second embodiment and the like.

[0042] Fig.21 It is a flowchart which shows the process in the 4th Embodiment.

[0043] Fig. 22 It is a flowchart which shows the process in 5th Embodiment. DETAILED DESCRIPTION

[0044] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings.

[0045] [1. First embodiment]

[0046] [1-1. Overall structure]

[0047] First, the overall configuration of a vehicle control system including the axial deviation estimating device according to the first embodiment will be described.

[0048] Figure 1 The vehicle control system 1 shown is a system mounted on a vehicle VH as a mobile body. The vehicle control system 1 mainly includes a radar device 3 and a control device 5. In addition, it may also include a mounting angle adjustment device 7, a vehicle-mounted sensor group 9, an axis deviation notification device 11, and an auxiliary execution unit 13. In the following, the vehicle VH on which the vehicle control system 1 is mounted is also referred to as the host vehicle VH. In addition, the vehicle width direction of the host vehicle VH is also referred to as the horizontal direction, and the vehicle height direction is also referred to as the vertical direction.

[0049] like Figure 2 as well as Figure 3 As shown in FIG. 1 , the radar device 3 is mounted on the front side of the vehicle VH and irradiates radar waves toward the front of the vehicle VH (i.e., the traveling direction). That is, the radar device 3 irradiates radar waves within a predetermined angle range Ra in the horizontal direction in front of the vehicle VH and within a predetermined angle range Rb in the vertical direction in front of the vehicle VH. The radar device 3 generates reflection point information (i.e., object information) related to the reflection point (i.e., the reflection object) that reflected the radar wave by receiving the reflected wave of the irradiated radar wave.

[0050] In addition, the radar device 3 may be a so-called millimeter wave radar that uses electromagnetic waves in the millimeter wave band as radar waves, or a laser radar that uses lasers as radar waves, or a sonar that uses sound waves as radar waves. In short, the antenna unit that transmits and receives radar waves is configured to detect the direction of arrival of the reflected wave in either the horizontal direction or the vertical direction. The antenna unit may also include an array antenna arranged in the horizontal direction and the vertical direction.

[0051] The radar device 3 is installed so that the beam direction of the beam of the radar wave (i.e., radar beam) based on the radiation is consistent with the front in the front-rear direction of the vehicle VH, and thus the traveling direction. And it is used to detect various objects (i.e., target objects) existing in front of the vehicle VH. In addition, the so-called beam direction refers to the direction along the central axis CA of the radar beam. When the radar device 3 is set at the correct position (i.e., the reference position), the beam direction is usually consistent with the traveling direction.

[0052] The reflection point information generated by the radar device 3 includes at least the azimuth of the reflection point and the distance of the reflection point (i.e., the distance between the radar device 3 and the reflection point). In addition, the radar device 3 may also be configured to detect the relative speed of the reflection point relative to the vehicle VH and the reception intensity (i.e., reception power) of the reflected wave of the radar wave reflected by the reflection point. The reflection point information may also include the relative speed and reception intensity of the reflection point.

[0053] like Figure 2 as well as Figure 3 As shown in FIG. 1 , the azimuth of the reflection point refers to an angle obtained based on the direction along the central axis CA of the radar beam, that is, the beam direction. In other words, it is at least one of the horizontal angle (hereinafter referred to as the horizontal angle) Hor and the vertical angle (hereinafter referred to as the vertical angle) Ver where the reflection point is located. In addition, here, both the vertical angle Ver and the horizontal angle Hor are included in the reflection point information as information indicating the azimuth of the reflection point.

[0054] The radar device 3 uses, for example, the FMCW method to alternately transmit radar waves in an uplink modulation interval and radar waves in a downlink modulation interval at a preset modulation cycle, and receive reflected radar waves. FMCW is an abbreviation for Frequency Modulated Continuous Wave.

[0055] The radar device 3 detects the horizontal angle Hor and the vertical angle Ver as the azimuth of the reflection point, the distance to the reflection point, the relative speed to the reflection point, and the reception intensity of the received radar wave as the reflection point information at each modulation cycle as described above.

[0056] The mounting angle adjustment device 7 includes a motor and a gear mounted on the radar device 3. The mounting angle adjustment device 7 rotates the motor according to a drive signal output from the control device 5. Thus, the rotational force of the motor is transmitted to the gear, and the radar device 3 can be rotated around an axis along the horizontal direction and an axis along the vertical direction.

[0057] Therefore, for example, the radar device 3 is centered in the direction of arrow A along the vertical plane (for example, refer to Figure 5 ) so that the offset angle of the radar device 3 in the vertical direction can be adjusted.

[0058] The vehicle-mounted sensor group 9 is at least one sensor mounted on the vehicle VH to detect the state of the vehicle VH. The vehicle-mounted sensor group 9 may also include a vehicle speed sensor. The vehicle speed sensor is a sensor that detects the vehicle speed based on the rotation of the wheels. Figure 1 As shown, the vehicle-mounted sensor group 9 may include a camera 15 such as a CCD camera. The camera 15 captures the same range as the irradiation range of the radar wave of the radar device 3.

[0059] Furthermore, the vehicle-mounted sensor group 9 may also include an acceleration sensor. The acceleration sensor detects the acceleration of the vehicle VH. Furthermore, the vehicle-mounted sensor group 9 may also include a yaw rate sensor. The yaw rate sensor detects the speed of change of the yaw angle representing the slope of the traveling direction of the vehicle VH relative to the front of the vehicle VH. Furthermore, the vehicle-mounted sensor group 9 may also include a steering angle sensor. The steering angle sensor detects the cutting angle of the steering wheel.

[0060] In addition, the vehicle-mounted sensor group 9 may also include a navigation device 17 having map information. The navigation device 17 may also be a device that detects the position of the vehicle VH based on GPS signals, etc., and establishes a correspondence between the position of the vehicle VH and the map information. The map information may also include a guardrail (hereinafter, guardrail) 41 (for example, see FIG. 1 ) disposed as a roadside object, such as a vehicle. Figure 7 )'s location information, as well as various road-related information.

[0061] The axle misalignment notification device 11 is a sound output device provided in the vehicle cabin, and outputs a warning sound to the occupants of the host vehicle VH. Alternatively, an audio device or the like included in the assist execution unit 13 may be used as the axle misalignment notification device 11.

[0062] The assistance execution unit 13 controls various vehicle-mounted devices and executes predetermined driving assistance based on the processing results of the object detection processing described later executed by the control device 5. The various vehicle-mounted devices that become the control targets may also include a monitor that displays images and an audio device that outputs alarm sounds or guidance sounds. In addition, it may also include a control device that controls the internal combustion engine, power transmission mechanism, brake mechanism, etc. of the host vehicle VH.

[0063] The control device 5 includes a microcomputer 29, which includes a CPU 19 and a semiconductor memory (hereinafter referred to as memory) 27 such as a ROM 21, a RAM 23, and a flash memory 25. The various functions of the control device 5 are realized by the CPU 19 executing a program stored in a non-transient tangible recording medium. In this example, the memory 27 is equivalent to a non-transient tangible recording medium storing the program. In addition, by executing the program, a method corresponding to the program is executed. In addition, the control device 5 may include one microcomputer 29, or may include a plurality of microcomputers 29.

[0064] like Figure 4 As shown, the control device 5 has the functions of an object information acquisition unit 31, a roadside object extraction unit 33, a road surface extraction unit 35, and an axis deviation angle estimation unit 37, and has a function as an axis deviation estimation device.

[0065] The object information acquisition unit 31 repeatedly acquires reflection point information (ie, object information), the reflection point information including the azimuth of the reflection point (ie, the object azimuth) and the distance of the reflection point (ie, the object distance).

[0066] The roadside object extraction unit 33 extracts roadside object information from the above-mentioned reflection point information based on a predetermined extraction condition described later. The roadside object information represents information of a reflection point on a roadside object (e.g., a guardrail 41), and the roadside object is arranged at a position higher than the road surface on the side of the road (i.e., lane) on which the vehicle VH is traveling, along the extension direction of the road, under predetermined conditions (e.g., the same height). In addition, the roadside object information includes, for example, information on the position of a reflection point where radar waves are reflected by the roadside object. In addition, the reflection point of the roadside object is sometimes referred to as a roadside object reflection point.

[0067] The road surface extraction unit 35 extracts road surface information from the above-mentioned reflection point information based on a predetermined extraction condition, and the road surface information represents information about a reflection point on the road surface of the road on which the vehicle VH is traveling. In addition, the road surface information includes, for example, information about the position of a reflection point where radar waves are reflected by the road surface. In addition, a reflection point on the road surface is sometimes referred to as a road surface reflection point.

[0068] The axis deviation angle estimation unit 37 estimates the vertical axis deviation angle based on the roadside object information and the road surface information. Specifically, when the orientation of the radar device 3 when the radar device 3 is mounted in a reference state (i.e., reference position) is set as the mounting reference direction and the actual orientation of the radar device 3 is set as the mounting actual direction, the vertical axis deviation angle indicating the deviation angle of the mounting actual direction in the vertical direction relative to the mounting reference direction is estimated based on the roadside object information including information of a plurality of reflection points and the road surface information including information of a plurality of reflection points.

[0069] Here, the so-called mounting reference direction refers to the direction of the radar device 3 when the radar device 3 is mounted at the original installation position (that is, the pre-set position), that is, the reference position. Figure 2 as well as Figure 3 The direction of the X-axis (i.e., Xc) shown is consistent, and when the radar device 3 is mounted at the reference position, there is no axis deviation of the radar device 3. In addition, the front direction of the radar device 3 is the orientation of the radar device 3 (i.e., the reference orientation), and the front direction of the vehicle VH is the mounting reference direction.

[0070] [1-2. Axis deviation of radar device]

[0071] Next, the axis offset of the radar device 3 will be described.

[0072] The axis deviation of the radar device 3 refers to the deviation of the coordinate axis of the radar device 3 when the radar device 3 is actually installed on the host vehicle VH from the coordinate axis of the radar device 3 when the radar device 3 is accurately installed on the host vehicle VH.

[0073] The axis offset of the radar device 3 includes an axis offset around the device coordinate axis and an axis offset in the height direction. Here, among the axis offsets around the device coordinate axis, the vertical axis offset will be mainly described.

[0074] (a) Coordinate axis

[0075] First, the coordinate axes of the radar device 3 and the coordinate axes of the host vehicle VH will be described.

[0076] like Figure 5As shown, the coordinate axes of the radar device 3 refer to the vertical axis Zs extending vertically of the radar device 3, the left-right axis Ys extending horizontally of the radar device 3, and the front-back axis Xs extending front-back of the radar device 3 when the radar device 3 is installed on the vehicle VH. The vertical axis Zs, the left-right axis Ys, and the front-back axis Xs are orthogonal to each other. In the first embodiment in which the radar device 3 is provided in front of the vehicle VH, the front-back axis Xs coincides with the central axis CA of the radar beam. That is, the orientation of the radar device 3 coincides with the front-back axis Xs.

[0077] Furthermore, the coordinates in the radar device 3 (ie, the device system coordinates) are constituted by the up-down axis Zs, the left-right axis Ys, and the front-back axis Xs.

[0078] On the other hand, the coordinate axes of the host vehicle VH are the vertical axis Zc extending in the vertical direction, the horizontal axis Yc extending in the horizontal direction, and the traveling direction axis Xc extending in the traveling direction of the host vehicle VH. The vertical axis Zc, the horizontal axis Yc, and the traveling direction axis Xc are orthogonal to each other.

[0079] Furthermore, the coordinates of the host vehicle VH (ie, the vehicle system coordinates) are constituted by the vertical axis Zc, the horizontal axis Yc, and the traveling direction axis Xc.

[0080] In addition, in the first embodiment, as described above, when the radar device 3 is accurately mounted on the vehicle VH, the central axis CA coincides with the traveling direction of the vehicle VH. In other words, the coordinate axes of the radar device 3 and the coordinate axes of the vehicle VH coincide in all directions. For example, in the initial state when shipped from the factory, the radar device 3 is accurately mounted on the vehicle VH, that is, at a predetermined position.

[0081] (b) Axis deviation around the device coordinate axis

[0082] Next, the axis deviation around the device coordinate axis will be described.

[0083] After the initial state, in the vehicle VH, axis deviation around the device coordinate axis may occur. Such axis deviation includes vertical axis deviation and roll axis deviation. The axis deviation angle represents the magnitude of such axis deviation in degrees.

[0084] Among them, Figure 5As shown in the left figure of , the vertical axis offset refers to a state in which an offset occurs between the up-down axis Zs, which is the coordinate axis of the radar device 3, and the vertical axis Zc, which is the coordinate axis of the host vehicle VH. The axis offset angle when such a vertical axis offset occurs is called a vertical axis offset angle θp. The vertical axis offset angle θp is the so-called pitch angle θp, which is the axis offset angle of the coordinate axis of the radar device 3 around the horizontal axis Yc of the host vehicle VH. In other words, the vertical axis offset angle θp is the axis offset angle when an axis offset occurs around the horizontal axis Yc of the host vehicle VH, and therefore around the left-right axis Ys of the radar device 3.

[0085] In addition, from Figure 5 As can be seen from the left figure, the vertical axis offset angle θp can also be an angle representing the magnitude of the offset between the front-rear axis Xs as the coordinate axis of the radar device 3 and the traveling direction axis Xc as the coordinate axis of the vehicle VH.

[0086] Here, based on Figure 6 , the vertical axis offset angle is explained in more detail.

[0087] Figure 6 This shows a state where the radar beam of the radar device 3 is deflected (i.e., deflected in the vertical direction) on the ZX plane, which is a vertical plane passing through the traveling direction axis Xc. The central axis CA of the radar beam when no deflection occurs is identical to the traveling direction axis Xc.

[0088] like Figure 6 As shown, when the mounting reference direction of the radar device 3 is consistent with the traveling direction of the vehicle VH, if the actual orientation of the radar device 3, i.e., the actual mounting direction, is set as the beam direction, then in the vertical direction, the angle between the traveling direction and the beam direction is the vertical axis deviation angle θp.

[0089] That is, when the central axis CA of the radar beam of the radar device 3 deviates from the reference traveling direction to the actual beam direction in the figure due to the radar device 3 rotating in the direction of arrow A, for example, the deviation angle is the vertical axis deviation angle θp.

[0090] In addition, as mentioned above Figure 5 As shown in the right figure of FIG. 1 , the roll axis offset refers to a state in which the left-right axis Ys as the coordinate axis of the radar device 3 and the horizontal axis Yc as the coordinate axis of the host vehicle VH are offset. The axis offset angle when the roll axis is offset is called the roll angle θr.

[0091] [1-3. Principle of estimating the vertical axis offset angle]

[0092] <Estimation of the vertical axis deviation angle using roadside objects>

[0093] First, the principle of estimating the vertical axis deviation angle using roadside objects will be described.

[0094] (a) For example, Figure 7 as well as Figure 8 As shown, the case where there is a guardrail 41 arranged on the side of the road in the width direction and protruding upward from the road surface along the extending direction of the road is described. Figure 7 The left and right directions are the width of the road. Figure 7 The up and down direction is the extension direction of the road, that is, the direction in which the vehicle VH travels.

[0095] Such guardrails 41 are usually arranged along the extending direction of the road, such as Figure 8 Specifically, on the road surface, a plurality of rods 43 are arranged in a row along the direction in which the road extends, and a rod-shaped or plate-shaped transverse member 45 is fixed to laterally connect the rods 43 (for example, adjacent rods 43).

[0096] That is, the rod 43 and the cross member 45 are usually arranged to have a constant height, so that the upper end of the guardrail 41 extends substantially horizontally along the road. In addition, the entire guardrail 41 also extends substantially horizontally on the road surface in a strip shape (i.e., a predetermined upper and lower width) on a vertical plane.

[0097] Therefore, when the radar device 3 of the vehicle VH radiates a radar beam forward, the radar beam is reflected by the road surface and the guardrail 41, and the reflected wave is received by the radar device 3. Therefore, based on the reflected wave, the road surface and the guardrail 41 are detected as reflection points (ie, reflecting objects).

[0098] In fact, when a radar beam is irradiated from the radar device 3 toward the guardrail 41 and an attempt is made to check the reflected wave, the reflected wave from the upper end of the rod 43 and the upper end of the transverse member 45 has a large intensity, so it is easy to detect the reflection point at the upper end of the rod 43 and the upper end of the transverse member 45. In addition, in the guardrail 41, it is also possible to detect the reflection point at a location other than the upper end of the rod 43 and the upper end of the transverse member 45.

[0099] Therefore, when the guardrail 41 is arranged along the road, a plurality of reflection points corresponding to the guardrail 41 are detected in a strip-shaped range along the traveling direction of the vehicle VH. In particular, the reflection points corresponding to the upper end of the rod 43 and the upper end of the cross member 45 are detected in a substantially linear range with a narrow width.

[0100] Therefore, as described in detail later, the slope of the reflection point group with a vertical axis offset can be obtained based on the arrangement state of a plurality of reflection points (ie, reflection point group) detected within a strip-shaped range corresponding to the guardrail 41 .

[0101] In addition, Figure 8In FIG. 1 , for easy understanding, each reflection point at the upper end of the connecting rod 43 and the upper end of the cross member 45 is recorded as a straight line to indicate the arrangement state of the reflection point group.

[0102] (b) Next, based on Fig. 9 , the relationship between the vertical axis offset angle θp and the reflection point group is explained.

[0103] like Fig. 9 As shown in (B), when the radar device 3 does not have a vertical axis offset (ie, the central axis CA is horizontal), as shown in the graph on the right side of the figure, the configuration of multiple reflection points detected by the radar device 3 on the vertical plane is also close to horizontal.

[0104] also, Fig. 9 The diagrams on the right side of show the positions of the reflection points on the three-dimensional device system coordinates when projected onto the ZX plane along the left-right axis Ys (i.e., the projected reflection points). In addition, the straight lines in the diagrams are approximated straight lines KL (i.e., straight lines for roadside objects) obtained by approximating a plurality of projected reflection points using the least squares method. In addition, in the following, sometimes the projected reflection points are simply referred to as reflection points.

[0105] Therefore, if Fig. 9 As shown in the graph on the right side of (B), when it is known that the approximate straight line KL is horizontal based on the detection result of the radar device 3, it can be determined that no vertical axis deviation has occurred.

[0106] However, assuming that Fig. 9 As shown in (A), when the central axis CA of the radar beam of the radar device 3 (i.e., the direction of the radar device 3) is shifted downward, the further the central axis CA of the radar beam moves toward the moving direction shown by Xc (i.e., farther), the farther it moves.

[0107] In addition, the above Figure 8 The diagram shows a state in which, when the central axis CA of the radar beam is offset downward with respect to the traveling direction axis Xc, the distance between the central axis CA and the upper end of the guardrail 41 increases as the distance travels to the right side of the figure.

[0108] Therefore, if Fig. 9 As shown in the graph on the right side of (A), the further to the right of the figure, the higher the arrangement of the multiple reflection points, so the slope βa of the approximate straight line KL has a positive value. In addition, the greater the absolute value of the slope βa of the approximate straight line KL, the greater the absolute value of the downward vertical axis deviation angle θp of the radar device 3. That is, from Fig. 9 As can be seen from (A), the absolute value of the angle corresponding to the slope βa of the approximate straight line KL (ie, the inclination angle βka) is the same as the absolute value of the vertical axis deviation angle θp of the radar device 3, but their signs are opposite.

[0109] Therefore, if Fig. 9 As shown in the graph on the right side of (A), when the slope βa (i.e., positive βa) of the approximate straight line KL is known based on the detection result of the radar device 3, it can be determined that a downward vertical axis deviation occurs at a vertical axis deviation angle θp corresponding to the slope βa. In this case, the inclination angle βka is a positive value, and the vertical axis deviation angle θp is a negative value.

[0110] On the contrary, assuming Fig. 9 As shown in (C), when the radar device 3 is oriented upward, the arrangement of the reflection points decreases as shown in the graph on the right side of the figure, as the direction moves in the direction of travel (i.e., the right side of the figure). In this case, in the device system coordinates, the slope βa of the approximate straight line KL has a negative value.

[0111] Therefore, if Fig. 9 As shown in the graph on the right side of (C), when the slope βa (i.e., negative βa) of the approximate straight line KL is known based on the detection result of the radar device 3, it can be determined that an upward vertical axis deviation occurs at a vertical axis deviation angle θp corresponding to the slope βa. In this case, the inclination angle βka is a negative value, and the vertical axis deviation angle θp is a positive value.

[0112] In this way, the axis deviation of the radar device 3 in the vertical direction, that is, the vertical axis deviation angle θp can be obtained from the slope of the arrangement of the reflection points on the ZX plane, and therefore the slope βa of the approximate straight line KL.

[0113] In addition, the vertical axis offset angle θp estimated using roadside objects is sometimes referred to as the first vertical axis offset angle θpa or simply the vertical axis offset angle θpa. In addition, as described later, the vertical axis offset angle θp estimated using road surface reflection is sometimes referred to as the second vertical axis offset angle θpb or simply the vertical axis offset angle θpb. And, as described later, the final vertical axis offset angle θp is sometimes referred to as the third vertical axis offset angle θpz or simply the vertical axis offset angle θpz. In addition, when no special distinction is required, it is sometimes simply referred to as the vertical axis offset angle θp.

[0114] <Estimation of the vertical axis deviation angle of the road surface>

[0115] Next, the principle of estimating the vertical axis deviation angle using the road surface (ie, road surface reflection) will be described.

[0116] In addition, the principle of estimating the vertical axis deviation angle using the road surface reflection is basically the same as the principle of estimating the vertical axis deviation angle using the above-mentioned roadside objects, so it is briefly explained here.

[0117] like Fig.10 As shown, when a radar beam is irradiated from the radar device 3 toward the front of the vehicle VH, when the radar beam is reflected by the road surface, the radar wave is generally reflected by a plurality of locations (ie, reflection points) on the surface of the road surface.

[0118] Therefore, similar to the processing in the above-mentioned roadside objects, the multiple reflection points, i.e., the reflection point group (i.e., the road surface reflection point group), are used to obtain an approximate straight line KL (i.e., the straight line for the road surface) based on its distribution state in the vertical direction. Based on the slope βb of the approximate straight line, the vertical axis offset angle θp (i.e., the vertical axis offset angle θpb) can be estimated.

[0119] [1-4. Principle of processing when the road is inclined]

[0120] Next, the processing of the case where the road is inclined, for example, the case where the road is inclined upward from a horizontal state, that is, uphill, will be described. In addition, when the inclination of the road changes by more than a predetermined amount from midway, the position of the change is called an inflection point.

[0121] like Fig.11 As shown in the figure above, when the road becomes an uphill slope midway, when the vehicle VH is sufficiently ahead of the turning point, the arrangement of the multiple reflection points of the roadside objects before the turning point (i.e., the roadside object reflection points) on the vertical plane becomes a substantially horizontal arrangement along the substantially horizontal road. Similarly, the arrangement of the multiple reflection points of the road surface before the turning point (i.e., the road surface reflection points) on the vertical plane becomes a substantially horizontal arrangement along the substantially horizontal road.

[0122] Therefore, the vertical axis offset can be estimated almost accurately based on the roadside object reflection point. In addition, the vertical axis offset can also be estimated almost accurately based on the road surface reflection point.

[0123] However, if Fig.11 As shown in the figure below, when the vehicle VH approaches the turning point, the reception intensity of the reflected wave based on the road surface reflection point is affected by the inclination of the road surface, so it is not easy to estimate the vertical axis offset with good accuracy based on the road surface reflection point.

[0124] In such a case, even if one wants to obtain an approximate straight line KL based on the configuration of multiple road surface reflection points on a vertical plane and estimate the vertical axis offset based on the slope of the approximate straight line KL, it is not easy to estimate the vertical axis offset with good accuracy based on the road surface reflection points because the slope of the approximate straight line KL is affected by the inclination of the road surface.

[0125] Therefore, in the first embodiment, when estimating the vertical axis offset, taking into account that the reflection point information is affected by the inclination of the road, as described in detail later, the inflection point is detected based on the roadside object information, and the vertical axis offset is estimated with good accuracy using the information on the position of the inflection point.

[0126] [1-5. Processing]

[0127] Next, the processing performed by the control device will be described.

[0128] (a) Main routine of axis deviation estimation processing

[0129] First, use Fig.12 The flowchart of FIG. 1 illustrates the entire shaft offset estimation process (ie, the main routine) executed by the control device 5 .

[0130] The main axis deviation estimation process is a process for estimating the vertical axis deviation angle θp, and is started when the ignition switch is turned on.

[0131] When the control device 5 starts this process, the control device 5 performs a process of detecting an object in front of the vehicle VH using the radar device 3 in step (hereinafter, S) 100. The process of detecting the object is a so-called object detection process, and is a well-known process as described in, for example, the above-mentioned Japanese Patent No. 6321448, and therefore a detailed description thereof is omitted.

[0132] Here, the object (ie, the object marker) corresponds to the reflection point indicated by the reflection point information. At this stage, the reflection point includes not only the road surface but also roadside objects such as the guardrail 41 .

[0133] Specifically, in S100, the reflection point information is obtained from the radar device 3. The so-called reflection point information is information about each of the multiple reflection points detected by the radar device 3 mounted on the vehicle VH. The reflection point information at least includes the horizontal angle and the vertical angle as the azimuth of the reflection point, and the distance between the radar device 3 and the reflection point. In addition, the control device 5 obtains various detection results including the vehicle speed Cm from the vehicle-mounted sensor group 9.

[0134] In the next S110 , a roadside object extraction process is performed. The roadside object extraction process is a process for extracting a plurality of reflection points of a roadside object (ie, roadside object reflection points) for obtaining a vertical axis offset angle θpa based on the roadside object described later.

[0135] The roadside object extraction process includes a roadside object candidate point extraction process and a roadside object point group extraction process described later.

[0136] The roadside object candidate point extraction process is a process for extracting reflection points that are candidates for roadside objects (i.e., roadside object candidate points) from the plurality of reflection points obtained by the radar device 3. The roadside object point group extraction process is a process for further extracting a point group (i.e., a roadside object point group) that is highly likely to be a roadside object from the plurality of roadside object candidate points obtained by the roadside object candidate point extraction process.

[0137] In the next S120, a vertical axis deviation angle estimation process using a roadside object is executed. As described in detail later, the vertical axis deviation angle estimation process using the roadside object is a process for estimating the vertical axis deviation angle θpa of the radar device 3 based on the roadside object point group obtained by the roadside object point group extraction process.

[0138] In the next S130, a road surface reflection extraction process is executed. The road surface reflection extraction process is a process for extracting a plurality of reflection points on the road surface (ie, road surface reflection points) for obtaining a vertical axis deviation angle θpb based on the road surface reflection described later.

[0139] In the next S140, a vertical axis deviation angle estimation process using road surface reflection is executed. As described in detail later, the vertical axis deviation angle estimation process using road surface reflection is a process for estimating the vertical axis deviation angle θpb of the radar device 3 based on a plurality of road surface reflection points obtained by the road surface reflection extraction process.

[0140] In the next S150 , a process of estimating a final vertical axis deviation angle θpz is performed based on the vertical axis deviation angle θpa using the roadside object and the vertical axis deviation angle θpb using the road surface reflection.

[0141] For example, as described later, the reliability (e.g., a predetermined calculation weight) of estimating the vertical axis deviation angle θpb using the road surface reflection may be changed according to the distance from the vehicle VH to the turning point to perform the final vertical axis deviation angle θpz estimation process.

[0142] In the next S160, it is determined whether the final vertical axis deviation angle θpz estimated in the above S150 needs to be adjusted by the mounting angle adjustment device 7. If an affirmative determination is made here, the process proceeds to S170, while if a negative determination is made, the process proceeds to S195.

[0143] That is, when the vertical axis deviation angle θpz of the radar device 3 is greater than a predetermined angle, that is, a threshold angle, it is determined that adjustment is required and the process proceeds to S170. On the other hand, when it is less than the threshold angle, the process proceeds to S195.

[0144] In S170, it is determined whether the vertical axis deviation angle θpz is within the adjustable range of the mounting angle adjustment device 7. If an affirmative determination is made here, the process proceeds to S190, while if a negative determination is made, the process proceeds to S180.

[0145] In S190, the vertical axis offset angle θpz is within the adjustable range, so the axis offset adjustment process is executed. That is, the mounting angle adjustment device 7 is controlled to adjust the vertical axis offset angle θpz to zero.

[0146] Specifically, the following adjustment is performed: with the left-right axis Ys of the radar device 3 as the center, the radar device 3 is rotated around the left-right axis Ys by the amount of the vertical axis offset angle θpz so that the orientation of the radar device 3 becomes the mounting reference direction, and then enters S195.

[0147] On the other hand, in S180, the vertical axis offset angle θpz is outside the adjustable range, so the vertical axis offset angle θpz is not adjusted, and diagnostic information indicating that the radar device 3 has an axis offset (i.e., axis offset diagnosis) is output to the axis offset notification device 11, and the process proceeds to S195. In addition, the axis offset notification device 11 may also output a warning sound based on the axis offset diagnosis.

[0148] In S195, for example, it is determined whether to terminate the present process based on whether the ignition switch is turned off. If an affirmative determination is made here, the present process is temporarily terminated, while if a negative determination is made, the process returns to the above-mentioned S100.

[0149] (b) Roadside Object Candidate Point Extraction Process

[0150] Next, use Fig.13 The flowchart above Fig.12 The roadside object candidate point extraction process in the roadside object extraction process of S110 will be described.

[0151] This process is for extracting a candidate reflection point of a roadside object (ie, a roadside object candidate point) from a plurality of reflection points obtained by the radar device 3. The candidate reflection point extracted here is a reliable point as the reflection point of the guardrail 41 described above.

[0152] In the following description, the guardrail 41 is taken as an example as a roadside object, but the guardrail 41 may be simply referred to as a roadside object.

[0153] First, in Fig.13 In S200, it is determined whether the "determination condition based on the distance" is established (i.e., whether it is satisfied). Here, if an affirmative determination is made, the process proceeds to S210, and on the other hand, if a negative determination is made, the process proceeds to S260.

[0154] For example, in the traveling direction of the own vehicle VH, it is determined whether or not "the condition that the reflection point exists within a range of more than 2 m and less than 100 m from the own vehicle VH" is satisfied for the reflection point as the determination target.

[0155] In S210, it is determined whether the "determination condition based on the lateral position" is satisfied. If an affirmative determination is made here, the process proceeds to S220, while if a negative determination is made, the process proceeds to S260.

[0156] For example, determine whether the condition that "when the vehicle VH is traveling on a road with traffic on the left (e.g., a two-lane road), a reflection point exists on the left side of the vehicle VH's traveling direction and is within a range of more than 2m and less than 8m from the vehicle VH" is met.

[0157] Furthermore, for example, when the vehicle VH is traveling on a single-lane road, it may be determined whether a reflection point exists on the right side of the vehicle VH in a range of more than 2 m and less than 8 m from the vehicle VH.

[0158] That is, in S210 , it is determined whether the reflection point is within a range in the lateral direction of the vehicle VH where there is a high possibility that the guardrail 41 as a roadside object exists.

[0159] In S220, it is determined whether the "determination condition based on relative speed" is satisfied. If an affirmative determination is made here, the process proceeds to S230, while if a negative determination is made, the process proceeds to S260.

[0160] That is, the guardrail 41 is a stationary object, so here, it is determined whether the condition that "the speed of the reflection point relative to the vehicle VH (i.e., the relative speed) meets the speed of the vehicle VH representing a stationary object (i.e., the vehicle speed Cm)" is satisfied. In addition, when the vehicle speed Cm is positive, the detected relative speed is negative.

[0161] In the determination of the relative speed, it is possible to determine whether the absolute value of the relative speed is within a predetermined error range of ±Δ around the absolute value of the vehicle speed Cm.

[0162] In S230, it is determined whether the "determination condition based on the running state of the own vehicle VH (ie, the own vehicle state)" is satisfied. If an affirmative determination is made here, the process proceeds to S240, while if a negative determination is made, the process proceeds to S260.

[0163] For example, when the vehicle VH is traveling in a straight line and the acceleration is constant, the detection accuracy of the reflection point is considered to be high. Therefore, here, based on the information from the vehicle sensor group 9, it is determined whether the vehicle state is a stable state of steady travel.

[0164] For example, when the vehicle VH is traveling, if the yaw angle detected by the yaw rate sensor and the steering wheel angle detected by the steering angle sensor are below a predetermined value, it can be determined that the vehicle is traveling in a straight line. Also, if the acceleration detected by the acceleration sensor is below a predetermined value, it can be determined that the acceleration is constant.

[0165] Furthermore, in the case of determining whether the vehicle is traveling in a straight line or whether the acceleration is constant, if the error is within a predetermined range, it may be determined that the vehicle is traveling in a straight line or the acceleration is constant.

[0166] In S240, it is determined whether the "determination condition by the camera 15" is satisfied. If an affirmative determination is made here, the process proceeds to S250, while if a negative determination is made, the process proceeds to S260.

[0167] For example, the image captured by the camera 15 may be processed by a known image processing method, and it may be determined from the image whether the image of the object at the position of the reflection point is likely to be the guardrail 41. In addition, the method of detecting the guardrail 41 from the image of the camera 15 is known, for example, as described in Japanese Patent Application Laid-Open No. 2011-118753.

[0168] In S250, since an affirmative judgment is made about the reflection point of the determination target in all the steps S200 to S240, the reflection point is stored in the memory 27 as a roadside object candidate point with a high possibility of being a reflection point of the guardrail 41, and the present processing is temporarily terminated.

[0169] On the other hand, in S260 , a negative determination is made in any of S200 to S240 , and thus the reflection point is stored in the memory 27 as a non-roadside object with a low probability of being the guardrail 41 , and the present process is temporarily terminated.

[0170] Furthermore, the above-mentioned processes of S200 to S260 are performed on all the reflection points obtained by the above-mentioned object detection process, and therefore all the reflection points are classified as either roadside object candidate points or non-roadside objects.

[0171] (c) Roadside Object Extraction Processing Roadside Object Point Group Extraction Processing

[0172] Next, use Fig.14 The flowchart of FIG. 1 illustrates the roadside object point group extraction process in the roadside object extraction process of S110 described above.

[0173] This treatment is the above Fig.12 The S110 process is used to Fig.13The plurality of roadside object candidate points obtained by the roadside object candidate point extraction process are used to extract a roadside object point group for calculating the vertical axis offset angle θp. In addition, the roadside object point group is composed of a plurality of reflection points.

[0174] First, in Fig.14 In S300, candidate point clustering processing is performed. That is, a plurality of roadside object candidate points are clustered (ie, classified).

[0175] For example, the reflection points as multiple roadside object candidate points are divided into multiple (for example, 6) clusters by the well-known k-means method, etc. In addition, each reflection point is three-dimensional data with XYZ coordinates in the vehicle system coordinates, but clustering is performed using the XY coordinates of each reflection point.

[0176] In the next S310, it is determined whether the "longitudinal distance determination condition of the roadside object point group (ie, point group)" is satisfied. If the determination is affirmative, the process proceeds to S320, while if the determination is negative, the process proceeds to S350.

[0177] That is, in each of the divided clusters, it is determined whether the longitudinal distance determination condition is satisfied for all the roadside object candidate points (that is, roadside object point groups) included in each cluster.

[0178] Specifically, for example, for each roadside object point group corresponding to each cluster, and therefore for all reflection points in each roadside object point group, it is determined whether the length of the traveling direction, i.e., the depth direction, of the vehicle VH is within a certain range or above. In other words, for all reflection points in each cluster of the determination object, it is determined whether the value obtained by subtracting the distance closest to the vehicle VH (the minimum value) from the farthest distance from the vehicle VH (i.e., the maximum value) in the depth direction of the reflection point exceeds a predetermined threshold.

[0179] Through the determination in S310 , clusters satisfying the longitudinal distance determination condition of the point group can be extracted from all clusters. In other words, clusters having reflection points satisfying the longitudinal distance determination condition of the point group can be extracted from all clusters.

[0180] In addition, here, for each cluster, when the above distance condition is satisfied for all reflection points, the longitudinal distance determination condition of the cluster is set to be satisfied, but it is also possible to set the longitudinal distance determination condition of the cluster to be satisfied when the above distance condition is satisfied for reflection points of a predetermined ratio or more. In addition, this is also the same in the following determination conditions.

[0181] In S320, it is determined whether the "lateral distance determination condition of the above-mentioned point group" is satisfied. If the determination is affirmative, the process proceeds to S330, while if the determination is negative, the process proceeds to S350.

[0182] That is, for all the reflection points of the roadside object point group in the cluster determined affirmatively in the above S310 , it is determined whether the lateral distance determination condition is satisfied.

[0183] Specifically, for example, for all the reflection points of the above cluster, it is determined whether the length of the vehicle VH in the left-right direction, i.e., the width direction, is within a certain range. In other words, for all the reflection points, it is determined whether the value obtained by subtracting the distance closest to the vehicle VH (the minimum value) from the farthest distance from the vehicle VH in the width direction (i.e., the maximum value) exceeds a predetermined threshold.

[0184] Through the determination in S320 , clusters satisfying the lateral distance determination condition of the point group can be further extracted from clusters satisfying the lateral distance determination condition of the point group.

[0185] In S330, it is determined whether the "determination condition of the lateral position" is satisfied. If the determination is affirmative, the process proceeds to S340, while if the determination is negative, the process proceeds to S350.

[0186] That is, for the cluster for which an affirmative determination is made in the above-mentioned S320, it is determined whether the determination condition of the lateral position is satisfied.

[0187] Specifically, it is determined whether the point group of the cluster to be determined is the innermost point group in the left-right direction of the host vehicle VH. Thus, the innermost point group is selected.

[0188] For example, in left-hand traffic, when the right side of the vehicle is considered positive, it is determined whether the lateral position of the point group is positive (ie, the right side of the vehicle) and the position closest to the vehicle.

[0189] In left-hand traffic, when the right side of the vehicle is considered positive, it is determined whether the lateral position of the point group is negative (ie, the left side of the vehicle) and the position closest to the vehicle.

[0190] In S340 , since affirmative judgments are made in all of S310 to S330 , the selected clustered point group is regarded as a point group representing reflection points of roadside objects (ie, a roadside object point group) and stored in the memory 27 , and the present process is temporarily terminated.

[0191] On the other hand, in S350, a negative judgment is made in any of the above S310 to S330, so the clustered point group that makes the negative judgment is regarded as a point group that does not represent reflection points of roadside objects (i.e., a non-roadside object point group), and the present processing is temporarily terminated.

[0192] The determination processing of S310 to S330 described above is performed to extract a reliable reflection point as a roadside object such as the guardrail 41 .

[0193] (d) Using the vertical axis deviation angle estimation process of roadside objects

[0194] Next, use Fig.15 The flowchart of FIG. 1 illustrates the vertical axis deviation angle estimation process using roadside objects.

[0195] This treatment is the above Fig.12 The processing of S120 is used according to the above Fig.14 The process of calculating the vertical axis offset angle θpa from the roadside object point group (i.e., reflection point group) obtained by the roadside object point group extraction process.

[0196] First, in S400, for each roadside object point in the roadside object point group obtained by the above-mentioned roadside object point group extraction process (i.e., equivalent to the reflection point of the roadside object point), the coordinates of the position of each roadside object point (i.e., the device system coordinates) are calculated based on the distance and azimuth contained in the reflection point information corresponding to each roadside object point.

[0197] The so-called device system coordinates refer to coordinates represented by three-dimensional coordinates based on the coordinate axes of the radar device 3, that is, (Xs, Ys, Zs). Fig.12 The object detection processing is obtained.

[0198] That is, the control device 5 calculates the coordinates (Xs, Ys, Zs) as the device system coordinates for all the roadside object points (ie, reflection points) in the roadside object point group, and stores them in the memory 27 .

[0199] In the next S410, it is determined whether the deviation determination condition of the position of each roadside object point in the roadside object point group (ie, the roadside object position) is satisfied. If a positive determination is made here, the present process is temporarily terminated, while if a negative determination is made, the process proceeds to S420.

[0200] The deviation judgment condition refers to a condition for judging whether the roadside object point group (i.e., multiple reflection points) on the ZX plane of the device system coordinates has a deviation (i.e., the degree of deviation is greater than a predetermined value) to such an extent that it is difficult to approximate the above-mentioned approximate straight line KL. As the judgment condition, for example, the correlation coefficient of the multiple reflection points on the ZX plane can be used.

[0201] That is, in the first embodiment, the vertical axis deviation angle θpa is estimated using the approximate straight line KL. Therefore, here, the case where the deviation is large is excluded, and the state where the deviation of the approximate straight line KL is small so that the vertical axis deviation angle θpa can be estimated is extracted.

[0202] In S420, since the deviation is determined to be small in the above S410, the equation (1) of the approximate straight line KL is obtained for all the reflection points of the above roadside object point group by the least square method. In other words, the following approximate straight line KL is obtained on the ZX plane of the device system coordinates. In addition, the slope of equation (1) is βa, and C is the intercept.

[0203] Zs=βaXs+C ·· (1)

[0204] In the next S430 , processing related to the inflection point is performed.

[0205] Specifically, first, a process of detecting an inflection point is performed using a roadside object point group. In other words, a process of detecting an inflection point is performed using a predetermined inflection point determination condition.

[0206] like Fig.16 As shown, the inflection point determination condition refers to a condition for determining whether the arrangement of the above-mentioned multiple roadside object points (ie, multiple reflection points) on the ZX plane is generally straight as a whole in the device system coordinates.

[0207] For example, Fig.16 As shown, the above-mentioned approximate straight line KL is obtained for all reflection points in the roadside object point group, and a straight line SL is drawn between adjacent reflection points. Then, the angle of intersection of the approximate straight line KL and each straight line SL can also be obtained. When the angle of intersection is greater than a specified value, it is determined that the inflection point determination condition is not satisfied (that is, there is an inflection point). In addition, here, the intersection point of the approximate straight line KL and the straight line SL is the position of the inflection point, so the coordinates of the inflection point (for example, the X coordinate of the vehicle system coordinates) can be obtained.

[0208] Furthermore, as the two reflection points for the lead straight line SL, two reflection points separated by a minimum distance among the reflection points separated by a predetermined distance or more may be used instead of adjacent reflection points.

[0209] That is, when a roadside object such as the guardrail 41 is continuous along the road in a constant state, for example, at a constant height, the vertical axis deviation angle θpa is estimated, and therefore, here, it is determined whether the roadside object is continuous in such a state.

[0210] also, Fig.16 The figure above shows an example of a roadside object point group without an inflection point. Fig.16 The figure below shows an example of a roadside object point group with an inflection point.

[0211] In addition, "having an inflection point" means that the configuration of the multiple reflection points is not a straight line, but has a state of bending in the middle. In other words, the so-called inflection point is a point indicating the position where the roadside object point group is estimated to be bent on the vertical plane, that is, the position of the bend in the distribution state of the roadside object point group, and here, it can be defined as the intersection of the approximate straight line KL and the straight line SL as described above.

[0212] Next, the position of the inflection point thus detected, that is, the X coordinate in the vehicle system coordinates is obtained. In other words, the distance between the host vehicle VH and the inflection point is obtained. The distance between the host vehicle VH and the inflection point is used in the reliability processing described later.

[0213] In the next S440, the angle corresponding to the slope βa of the equation (1) representing the above-mentioned approximate straight line KL (i.e., the inclination angle βka) is calculated, and the vertical axis offset angle θpa based on the roadside object is calculated by reversing the positive and negative values ​​of the angle, thereby temporarily terminating this processing.

[0214] In this way, the vertical axis deviation angle θpa of the radar device 3 can be obtained by utilizing the roadside object.

[0215] also, Fig.17 Indicates the relationship between the device system coordinates and the vehicle system coordinates. Here, the vertical axis offset angle when the radar device 3 is offset to the upward axis is a positive value θpa, so, for example, the front-rear axis Xs of the device system coordinates is rotated to the left relative to the travel direction axis Xc of the vehicle system coordinates by the amount of the vertical axis offset angle θpa.

[0216] Therefore, in the vehicle system coordinates, the straight line indicating the direction of the radar device 3, that is, the central axis CA, can be expressed by the following equation (2). In addition, C is the intercept.

[0217] Zc=θpaXc+C ·· (2)

[0218] (e) Road surface reflection extraction and processing

[0219] Next, use Fig.18 The flowchart above Fig.12 The road surface reflection extraction process of S130 will be described.

[0220] This process is a process for extracting a reflection point of the road surface (that is, a road surface reflection point) from a plurality of reflection points obtained by the radar device 3 .

[0221] First, in S500, it is determined whether the determination condition based on the distance is satisfied. If an affirmative determination is made here, the process proceeds to S510, while if a negative determination is made, the process proceeds to S570.

[0222] For example, it is determined whether the distance of the reflection point is less than a predetermined distance threshold at which the possibility of the reflection point of the radar wave is high.

[0223] In S510, it is determined whether the determination condition based on the direction is satisfied. If an affirmative determination is made here, the process proceeds to S520, while if a negative determination is made, the process proceeds to S570.

[0224] For example, it is determined whether the azimuth of the reflection point is located within a predetermined azimuth range, i.e., an extraction range, which includes the central axis CA in the horizontal direction and has a high probability of being a reflection point of the radar wave. In addition, in the first embodiment in which the radar device 3 is provided in front of the vehicle VH, the extraction range may also be determined as a predetermined range near the traveling direction of the vehicle VH. The extraction range may also be predetermined by experiments or the like.

[0225] In S520, it is determined whether the determination condition based on power is satisfied. If an affirmative determination is made here, the process proceeds to S530, while if a negative determination is made, the process proceeds to S570.

[0226] For example, it is determined whether the reflected power at the reflection point is less than a predetermined power threshold. In other words, it is considered that the reflected power from the road surface is smaller than the reflected power from other vehicles, so the power threshold can also be appropriately determined based on such reflected power from the road surface. For example, the power threshold can also be predetermined by experiments, etc.

[0227] In S530, it is determined whether the determination condition based on the relative speed is satisfied. If an affirmative determination is made here, the process proceeds to S540, while if a negative determination is made, the process proceeds to S570.

[0228] That is, the road surface is a stationary object, so here, it is determined whether the condition that "the speed of the reflection point relative to the vehicle VH (i.e., the relative speed) meets the speed of the vehicle VH representing a stationary object (i.e., the vehicle speed Cm)" is satisfied. In addition, when the vehicle speed Cm is positive, the detected relative speed is negative.

[0229] In the determination of the relative speed, it is possible to determine whether the absolute value of the relative speed is within a predetermined error range of ±Δ around the absolute value of the vehicle speed Cm.

[0230] In S540, it is determined whether the "determination condition based on the running state of the own vehicle VH (ie, the own vehicle state)" is satisfied. If an affirmative determination is made here, the process proceeds to S550, while if a negative determination is made, the process proceeds to S570.

[0231] For example, it is considered that when the vehicle VH is traveling in a straight line and the acceleration is constant, the detection accuracy of the road surface reflection point is high. Therefore, here, based on the information from the vehicle sensor group 9, it is determined whether the vehicle state is a stable state of steady travel.

[0232] For example, when the vehicle VH is traveling, if the yaw angle detected by the yaw rate sensor and the steering wheel angle detected by the steering angle sensor are below a predetermined value, it can be determined that the vehicle is traveling in a straight line. Also, if the acceleration detected by the acceleration sensor is below a predetermined value, it can be determined that the acceleration is constant.

[0233] Furthermore, in the case of determining whether the vehicle is traveling in a straight line or whether the acceleration is constant, if the error is within a predetermined range, it may be determined that the vehicle is traveling in a straight line or the acceleration is constant.

[0234] In S550, it is determined whether the determination condition by the camera 15 is satisfied. Here, if an affirmative determination is made, the process proceeds to S560, while if a negative determination is made, the process proceeds to S570.

[0235] For example, the image captured by the camera 15 can be processed by a known image processing method to determine whether the image of the object at the reflection point is likely to be a road surface. In addition, the method of detecting the road surface based on the image of the camera 15 is known, so its description is omitted.

[0236] In S560, since an affirmative judgment is made for the reflection point of the determination object in all the steps S500 to S550, the reflection point is stored in the memory 27 as a reflection point on the road surface (ie, road surface reflection point), and the present processing is temporarily terminated.

[0237] On the other hand, in S570, since a negative determination is made in any of S500 to S550, the reflection point is stored in the memory 27 as a reflection point that is not a road surface reflection point (ie, a non-road surface reflection point), and the present processing is temporarily terminated.

[0238] Furthermore, the above-mentioned processes of S500 to S570 are performed on all reflection points obtained by the above-mentioned object detection process, and therefore all reflection points are classified as either road surface reflection points based on road surface reflection or non-road surface reflection points not based on road surface reflection.

[0239] (f) Vertical axis deviation angle estimation using road surface reflection

[0240] Next, use Fig.19 The flowchart of FIG. 1 illustrates the vertical axis deviation angle estimation process using road surface reflection.

[0241] In addition, the description of the vertical axis deviation angle estimation process using the road surface reflection that is the same as the vertical axis deviation angle estimation process using the roadside object described above is omitted or simplified.

[0242] This treatment is the above Fig.12 The processing of S140 is used according to the above Fig.18 The process of calculating the vertical axis offset angle θpb is performed based on the multiple road surface reflection points (i.e., road surface reflection point group) obtained by the road surface reflection extraction process.

[0243] First, in S600, for each road surface reflection point in the road surface reflection point group obtained by the road surface reflection extraction process, based on the distance and azimuth included in the reflection point information corresponding to each road surface reflection point, the coordinates of the position of each road surface reflection point (i.e., the device system coordinates) are calculated. That is, the control device 5 calculates the coordinates (Xs, Ys, Zs) as the device system coordinates for all road surface reflection points in the road surface reflection point group, and stores them in the memory 27.

[0244] In the next S610, it is determined whether the deviation determination condition of the position of each road surface reflection point in the road surface reflection point group (i.e., the road surface reflection position) is satisfied. If a positive determination is made here, the present process is temporarily terminated, and on the other hand, if a negative determination is made, the process proceeds to S620.

[0245] By using the deviation determination condition, it is determined whether all the road surface reflection points of the road surface reflection point group on the ZX plane of the device system coordinates have deviations to such an extent that they are difficult to be approximated by the above-mentioned approximate straight line KL (i.e., whether the degree of deviation is greater than a predetermined value). As the determination condition, for example, the correlation coefficient of the road surface reflection point group on the ZX plane can be used.

[0246] That is, in the first embodiment, the vertical axis deviation angle θpb is estimated using the approximate straight line KL, and therefore, a state in which the deviation of the approximate straight line KL is small so that the vertical axis deviation angle θpb can be estimated is extracted here.

[0247] In S620, since the deviation is determined to be small in the above S610, the least square method is used to obtain the equation (3) of the approximate straight line KL that is the same as the above equation (1) for all the reflection points of the above road surface reflection point group. In other words, the following approximate straight line KL on the ZX plane of the device system coordinate is obtained. In addition, the slope of equation (3) is βb, and C is the intercept.

[0248] Zs=βbXs+C ·· (3)

[0249] In the next S630, processing related to the inflection point based on the roadside object information is performed. Specifically, the X coordinate (ie, Xc) of the inflection point calculated in the above S430 is obtained.

[0250] In the next S640, the angle corresponding to the slope βb of the equation (3) representing the above-mentioned approximate straight line KL (i.e., the inclination angle βkb) is calculated, and the vertical axis deviation angle θpb based on the road surface reflection is calculated by reversing the positive and negative values ​​of the angle, thereby temporarily terminating the present processing.

[0251] In this way, the vertical axis deviation angle θpb of the radar device 3 can be obtained by utilizing the road surface reflection.

[0252] In the vehicle system coordinates, a straight line indicating the direction of the radar device 3, that is, the central axis CA, can be expressed by the following equation (4). In addition, C is an intercept.

[0253] Zc=θpbXc+C ·· (4)

[0254] (g) Final vertical axis offset angle estimation process

[0255] Next, for the above Fig.12 The final vertical axis offset angle estimation process of S150 will be described.

[0256] In this first embodiment, based on the vertical axis offset angle θpa (i.e., the first vertical axis offset angle θpa) obtained by the vertical axis offset angle estimation processing using the roadside object and the vertical axis offset angle θpb (i.e., the second vertical axis offset angle θpb) obtained by the vertical axis offset angle estimation processing using the road surface reflection, the final vertical axis offset angle θpz (i.e., the third vertical axis offset angle θpz) used when correcting the axis offset is obtained.

[0257] Here, for example, the third vertical axis offset angle θpz is calculated by taking a weighted average of the first vertical axis offset angle θpa and the second vertical axis offset angle θpb.

[0258] <When the turning point is far away>

[0259] For example, as mentioned above Fig.11 As shown in the above figure, when the position of the inflection point in the vehicle system coordinates (i.e., the X coordinate) is located farther than the maximum position of the road surface reflection point in the vehicle system coordinates (i.e., the X coordinate), it is considered that the influence of the slope of the road surface is small in the reflection point information of the road surface. That is, when the distance from the vehicle VH to the inflection point is greater than the distance from the vehicle VH to the maximum position of the road surface reflection point (i.e., the maximum distance SS), it is considered that the influence of the slope of the road surface is small in the reflection point information of the road surface.

[0260] Therefore, the second vertical axis deviation angle θpb obtained from the road surface reflection is considered to have high reliability. Furthermore, when there is an inflection point even though it is far away, the reflection point information of the roadside object is considered to be slightly affected by the slope of the road surface corresponding to the inflection point.

[0261] Therefore, as described above, when the position of the inflection point is far, the second vertical axis offset angle θpb is weighted, that is, the weight of the second vertical axis offset angle θpb is made larger (for example, set to 2) than the weight of the first vertical axis offset angle θpa (for example, 1), and the third vertical axis offset angle θpz is calculated. In other words, the weight corresponding to the reliability of the second vertical axis offset angle θpb is changed according to the position of the inflection point. In addition, the reliability indicates the level of reliability, and when the reliability (that is, the reliability) is high, the value used for weighting is increased.

[0262] For example, the value of the second vertical axis offset angle θpb (ie, θpb) is weighted and calculated as in the following equation (5). In equation (5), θpa, θpb, and θpz represent the values ​​of the first to third vertical axis offset angles.

[0263] (θpa+2θpb) / 3=θpz ·· (5)

[0264] Thus, the third vertical-axis offset angle θpz can be calculated with higher accuracy.

[0265] In addition, when it is considered that the inflection point does not need to be taken into consideration, for example, when the distance from the vehicle VH to the inflection point is several times (for example, 5 times) or more of the maximum distance SS, or when the inflection point is not detected, the reliability of the second vertical axis offset angle θpb obtained from the road surface reflection and the reliability of the first vertical axis offset angle θpa obtained from the roadside object can be set to the same level.

[0266] <When the turning point is near>

[0267] For example, as mentioned above Fig.11 As shown in the figure below, when the position of the inflection point in the vehicle system coordinates is below the maximum position of the road surface reflection point in the vehicle system coordinates, it is considered that the reflection point information of the road side object and the road surface is affected by the slope of the road surface corresponding to the inflection point. That is, when the distance from the vehicle VH to the inflection point is below the maximum distance SS from the vehicle VH to the maximum position of the road surface reflection point, it is considered that the reflection point information of the road side object and the road surface is affected by the slope of the road surface corresponding to the inflection point.

[0268] In addition, here, as the position of the inflection point, for example, a range from 1 / 2 of the maximum distance SS to the maximum distance SS is cited.

[0269] In this case, which one of the roadside object and the road surface is more affected by the slope of the road surface corresponding to the inflection point can be determined through experiments, etc., but for example, when the influence is the same, the third vertical axis offset angle θpz can be calculated as shown in the following equation (6).

[0270] (θpa+θpb) / 2=θpz ··(6)

[0271] In addition, when the host vehicle VH is closer to the inflection point, for example, when the distance between the host vehicle VH and the inflection point is less than 1 / 2 of the maximum distance SS, it is considered that the slope of the road surface has a great influence on the reflection point information of the roadside object and the road surface. Therefore, it is considered that the accuracy of the first vertical axis offset angle θpa and the second vertical axis offset angle θpb is low, and thus, the accuracy of the third vertical axis offset angle θpz is also low. Therefore, in this case, it is not necessary to implement Fig.12 The processing of S160 to S190 is completed. Fig.12 The main routine.

[0272] <Other>

[0273] In a case where one of the first vertical axis offset angle θpa or the second vertical axis offset angle θpb cannot be calculated, for example, when the deviation of the reflection point required for estimating the vertical axis offset angle θp on one side is large, if the condition that the inflection point is farther than the prescribed distance is satisfied, the vertical axis offset angle θp that can be calculated can also be used as the third vertical axis offset angle θpz.

[0274] [1-6. Effect]

[0275] In the above-mentioned first embodiment, the following effects can be obtained.

[0276] (1a) The first embodiment includes an object information acquisition unit 31 , a roadside object extraction unit 33 , a road surface extraction unit 35 , and an axis deviation angle estimation unit 37 .

[0277] With such a structure, in the first embodiment, it is possible to easily extract roadside object information such as the position of the reflection point of the roadside object such as the guardrail 41 arranged along the travel path from the reflection object information related to the reflection object corresponding to the reflection point of the radar wave obtained by driving the radar device 3. For example, the guardrail 41 is arranged at a constant height along the road at a position higher than the road surface on the side of the road, so even if the direction of the radar beam is shifted upward, the reflected wave on the guardrail 41 is easier to detect than the reflected wave on the road surface.

[0278] Therefore, in the first embodiment, the slope of the road surface of the travel path can be estimated based on such characteristic roadside object information. For example, when the guardrail 41 is located upward as it goes further away, it can be estimated that the road surface also rises as it goes further away.

[0279] Therefore, for example, when estimating the vertical axis offset of the radar device based on the road surface information, the state of the road surface gradient and the like can be estimated based on the roadside object information obtained by the reflected wave from the above-mentioned characteristic roadside object.

[0280] That is, when the road surface has a slope, the receiving state of the radar wave changes according to the slope of the road surface, etc., but in the first embodiment, the slope of the road surface, etc. can be grasped based on the roadside object information. Therefore, the vertical axis offset is estimated based on such characteristic roadside object information and road surface information, so that the accuracy of the estimation of the vertical axis offset can be improved compared with the case of using only the road surface information.

[0281] In addition, the vertical axis offset is estimated based on the roadside object information and the road surface information, so there is an advantage that the stability and robustness when estimating the vertical axis offset are increased.

[0282] (1b) In the first embodiment, for a roadside object point group representing a plurality of reflection points on a vertical plane of a roadside object, the reliability of estimating the second vertical axis offset angle θpb using road surface information is changed according to the position of the inflection point of the roadside object point group.

[0283] That is, it is considered that the reliability of the second vertical axis offset angle θpb is lower when the inflection point of the roadside object point group is close than when it is far. Therefore, as in the first embodiment, the reliability of estimating the second vertical axis offset angle θpb is changed according to the position of the inflection point, thereby suppressing the occurrence of erroneous adjustment of the vertical axis offset angle θp and erroneous diagnosis.

[0284] (1c) In the first embodiment, when the host vehicle VH is traveling straight, the vertical axis deviation angle θp is estimated.

[0285] That is, since the vertical axis offset angle θp is estimated when the conditions for estimating the vertical axis offset angle θp with high accuracy are satisfied, the vertical axis offset angle θp can be stably obtained with high accuracy.

[0286] [1-6. Correspondence between statements]

[0287] In the relationship between the first embodiment and the present disclosure, the vehicle VH corresponds to the mobile body, the radar device 3 corresponds to the radar device, the control device 5 corresponds to the axis deviation estimation device, the object information acquisition unit 31 corresponds to the object information acquisition unit, the roadside object extraction unit 33 corresponds to the roadside object extraction unit, the road surface extraction unit 35 corresponds to the road surface extraction unit, and the axis deviation angle estimation unit 37 corresponds to the axis deviation angle estimation unit.

[0288] [2. Second Embodiment]

[0289] The basic structure of the second embodiment is the same as that of the first embodiment, so the following mainly describes the differences from the first embodiment. In addition, the same reference numerals as those of the first embodiment represent the same structures, and reference is made to the previous description.

[0290] In the second embodiment, when the first vertical axis offset angle θpa is estimated using roadside object information and the second vertical axis offset angle θpb is estimated using road surface information, when the reliability of the estimation of the vertical axis offset angle θp of either side is lower than a prescribed level, the reliability of the estimation of the vertical axis offset angle θp of the other side is also reduced.

[0291] That is, it is considered that there is a correlation between the state of the road surface and the state of the roadside object. For example, it is considered that when the road surface is undulating, the height of the roadside object also changes in the same way. Therefore, it is considered that the reliability of the estimation of the first vertical axis offset angle θpa and the second vertical axis offset angle θpb also has a considerable correlation.

[0292] Therefore, in the second embodiment, when the reliability of estimation of the vertical axis offset angle θp of either the first vertical axis offset angle θpa or the second vertical axis offset angle θpb is lower than a predetermined level, the reliability of estimation of the other vertical axis offset angle θp is also reduced.

[0293] The following is a specific description.

[0294] For example, consider the case where the reliability of the first vertical axis deviation angle θpa is set based on the distribution state of the reflection points of the roadside objects, the number of reflection points, the distance to the inflection point, etc. For example, when the deviation of the reflection points is less than the specified value, when the number of reflection points is more than the specified value, when the distance to the inflection point is farther than the specified value, the reliability of each parameter is set to be high compared to the case where this is not the case, and the specified reliability can be set. For example, a reference indicating a pre-set preferred reliability is set to 1, and a coefficient relative to the reference can be set. In addition, the coefficient of the reliability can be set according to the degree of deviation from each specified value.

[0295] Therefore, the reliability of the first vertical axis offset angle θpa can be set according to the reliability of each parameter (for example, the above coefficient). For example, the reliability of the first vertical axis offset angle θpa can be set by calculating the coefficient of each parameter. In addition, as the above calculation, the addition and accumulation of coefficients are listed.

[0296] Similarly, if the reliability of the second vertical axis deviation angle θpb is set according to the distribution state of the reflection points on the road surface, the number of reflection points, the distance to the inflection point, etc., it can be said that it is the same as the above-mentioned roadside objects. That is, when the deviation of the reflection point is less than the specified value, when the number of reflection points is more than the specified value, when the distance to the inflection point is farther than the specified value, the reliability of each parameter (for example, the above-mentioned coefficient) is set to be higher than that of other cases, and the specified reliability can be set. For example, the coefficient of the reliability that becomes the benchmark can be set. In addition, the coefficient of the reliability can be set according to the degree of deviation from each specified value.

[0297] In addition, the reliability of the third vertical axis offset angle θpz can be set based on the reliability of the first vertical axis offset angle θpa and the reliability of the second vertical axis offset angle θpb. For example, the reliability of the third vertical axis offset angle θpz can be set based on the reliability of the first vertical axis offset angle θpa and the reliability of the second vertical axis offset angle θpb by a pre-set operation such as weighted average.

[0298] Furthermore, when the reliability of the third vertical axis offset angle θpz is lower than a preset determination value, the reliability of the estimation of the third vertical axis offset angle θpz is considered to be low, and the operation may not be performed as described later. Fig.12 The processing of S160 to S190 is completed. Fig.12 The main routine.

[0299] Next, based on Fig. 20 The processing of the second embodiment is described below. Fig.12 The process of S150 is performed after that.

[0300] exist Fig. 20 In S700, as described above, the reliability of the first vertical axis offset angle θpa and the reliability of the second vertical axis offset angle θpb are calculated, and the reliability of the third vertical axis offset angle θpz is calculated based on the reliability of the first vertical axis offset angle θpa and the reliability of the second vertical axis offset angle θpb.

[0301] In the next S710, it is determined whether the reliability of the third vertical axis offset angle θpz is sufficiently high (i.e., a reliability greater than a predetermined value) for implementing the vertical axis offset adjustment described later. If the determination is positive, the process proceeds to S720, while if the determination is negative, the process proceeds to S730.

[0302] In S720, the reliability of the third vertical axis offset angle θpz is high, so it is allowed to enter the subsequent Fig.12 The processing of S160 to S190 is performed and the present processing is temporarily terminated.

[0303] On the other hand, in S730, the reliability of the third vertical axis deviation angle θpz is low, so entering the subsequent Fig.12 The processing of S160 to S190 is performed and the present processing is temporarily terminated.

[0304] The second embodiment has the same effect as the first embodiment. In addition, in the second embodiment, the reliability of the first to third vertical axis offset angles θpa, θpb, and θpz is taken into consideration, so that it is possible to suppress the erroneous adjustment of the vertical axis offset and the erroneous diagnostic output caused by the erroneous vertical axis offset angle θp. Therefore, there is an advantage that the reliability and robustness of the processing in the control device 5 are improved.

[0305] [3. Third embodiment]

[0306] The basic structure of the third embodiment is the same as that of the first embodiment, so the following mainly describes the differences from the first embodiment. In addition, the same reference numerals as those of the first embodiment represent the same structures, and the above description is referred to.

[0307] In the third embodiment, when the deviation of the positions of multiple reflection points of roadside objects on the vertical plane is greater than a specified value, the reliability of the estimation of the first vertical axis offset angle θpa based on the roadside object information and the reliability of the estimation of the second vertical axis offset angle θpb based on the road surface information are reduced together.

[0308] That is, as described above, it is considered that there is a correlation between the state of the road surface and the state of the roadside object. Therefore, it is considered that the reliability of the estimation of the first vertical axis deviation angle θpa and the second vertical axis deviation angle θpb also has a considerable correlation.

[0309] Therefore, in the third embodiment, when the deviation of the reflection point group of the roadside object, more specifically the roadside object point group, in the vertical plane is above a prescribed value, for example, the correlation coefficient in the X-coordinate and the Y-coordinate is below a prescribed value, the reliability of the estimation of the first vertical axis offset angle θpa and the second vertical axis offset angle θpb is reduced together.

[0310] In addition, the meaning of reliability (for example, the above-mentioned coefficient) and the like are the same as those in the above-mentioned second embodiment, and thus the description thereof will be omitted.

[0311] Next, the processing of the third embodiment is described. The processing steps are substantially the same as those of the second embodiment. Fig. 20 Provide a brief explanation.

[0312] exist Fig. 20In S700, as described above, the reliability of the first vertical axis offset angle θpa and the reliability of the second vertical axis offset angle θpb are calculated, and the reliability of the third vertical axis offset angle θpz is calculated based on the reliability of the first vertical axis offset angle θpa and the reliability of the second vertical axis offset angle θpb.

[0313] In the next S710, it is determined whether the reliability of the third vertical axis deviation angle θpz is higher than a predetermined reliability. If the determination is affirmative, the process proceeds to S720, while if the determination is negative, the process proceeds to S730.

[0314] In S720, access to the above-mentioned Fig.12 The processing of S160 to S190 is temporarily terminated. On the other hand, in S730, entry into the above-mentioned Fig.12 The processing of S160 to S190 is performed and the present processing is temporarily terminated.

[0315] The third embodiment has the same effect as the first embodiment. In addition, in the third embodiment, the reliability of the first to third vertical axis offset angles θpa, θpb, and θpz is taken into consideration, so that it is possible to suppress the erroneous adjustment of the vertical axis offset and the erroneous diagnostic output caused by the erroneous vertical axis offset angle θp. Therefore, there is an advantage that the reliability and robustness of the processing in the control device 5 are improved.

[0316] [4. Fourth embodiment]

[0317] The basic structure of the fourth embodiment is the same as that of the first embodiment, so the following mainly describes the differences from the first embodiment. In addition, the same reference numerals as those of the first embodiment represent the same structures, and the previous description is referred to.

[0318] The fourth embodiment is configured to use the map information when extracting reflective object information representing the roadside object information, when map information representing the travel path of the host vehicle VH and its surroundings includes information on the position of roadside objects such as the guardrail 41 .

[0319] For example, Fig.21 As shown, in the control device 5, in S800, it is determined whether the map used by the navigation device 17 is a map in which the position of the roadside object such as the guardrail 41 is recorded.

[0320] Then, in the case of a map recording the position of roadside objects, in S810, based on the information of the map and the position information of the vehicle VH, it is determined whether the road along which the vehicle VH is traveling is provided with roadside objects such as guardrails 41. Then, in the case of a road with roadside objects, in S820, information on the position of the roadside objects relative to the vehicle VH, such as the range where the roadside objects are arranged on a plane, is obtained.

[0321] Furthermore, in the case of a road without roadside objects, there are no roadside objects required for estimating the axis offset, and therefore, various processes required for estimating the axis offset do not need to be performed.

[0322] Above Fig.21 The processing can be done, for example, Fig.13 The above-mentioned roadside object candidate point extraction process is performed before the roadside object candidate point extraction process is performed. Moreover, the information on the range of the roadside object obtained from the map information can be used before or after any of the processes S200 to S240. That is, before or after the processes S200 to S240, a process for locking the range of the roadside object candidate point is provided, and as a judgment condition of the process, the information on the range of the roadside object obtained from the above-mentioned map information can be used.

[0323] Thus, through the above-mentioned processing, the position and range of the roadside object can be known based on the map information, so when the roadside object is actually detected by the radar device 3, the map information is used to accurately extract the roadside object. As a result, the vertical axis deviation angle θp can be estimated more accurately.

[0324] Furthermore, in the fourth embodiment as well, the same effects as those of the first embodiment can be obtained.

[0325] [5. Fifth embodiment]

[0326] The basic structure of the fifth embodiment is the same as that of the first embodiment, so the following mainly describes the differences from the first embodiment. In addition, the same reference numerals as those of the first embodiment represent the same structures, and the previous description is referred to.

[0327] In the fifth embodiment, as the radar device 3, Figure 1 As shown, a front radar device 3a for detecting objects in the traveling direction of the vehicle VH, that is, in front (ie, reflecting objects), and a side radar device 3b for detecting objects on the side of the vehicle VH (ie, reflecting objects) are arranged.

[0328] The fifth embodiment is configured to estimate the vertical axis deviation angle θp when the front radar device 3 a and the side radar device 3 b can detect a roadside object.

[0329] Specifically, for example, Fig. 22 As shown, in the control device 5, when it is determined in S900 that a roadside object is detected by the front radar device 3a and in S910 that a roadside object is detected by the side radar device 3b, in S920, estimation of the vertical axis offset angle θp is allowed.

[0330] also, Fig. 22 The processing can be performed by each of the above-mentioned radar devices 3a, 3b, for example, after performing the roadside object candidate point extraction processing or the roadside object point group extraction processing.

[0331] Furthermore, ultimately, the vertical axis deviation angle θp can be estimated using the reflection point information obtained by the front radar device 3 a .

[0332] This makes it possible to reliably determine the roadside object, and thus obtain the vertical axis deviation angle θp with high accuracy.

[0333] In addition, in the fifth embodiment as well, the same effects as those of the first embodiment can be obtained.

[0334] [6. Other embodiments]

[0335] As mentioned above, although embodiment of this disclosure was described, this disclosure is not limited to the said embodiment, Various deformation|transformation can be made and it can be implemented.

[0336] (6a) In the present disclosure, the radar device is not limited to a radar device capable of detecting roadside objects in front of the vehicle (i.e., in front of the vehicle), and can be a radar device capable of detecting roadside objects in any direction of the vehicle, such as the rear, front side (e.g., obliquely in front of the left, obliquely in front of the right), or side (e.g., left side, right side). In other words, there is no particular limitation as long as the radar device can detect roadside objects such as guardrails.

[0337] In addition, at least two or more of the above-mentioned radar devices may be combined. For example, the vertical axis deviation angle may be estimated using the reflection object information of the radar device that detects the roadside object among the radar devices.

[0338] (6b) In the present disclosure, as a radar device, in addition to the above-mentioned FMCW method, various radar devices using 2FCW method, FCM method, pulse method, etc. can be adopted. In addition, 2FCW is the abbreviation of 2Frequency Modulated Continuous Wave, and FCM is the abbreviation of Fast-Chirp Modulation.

[0339] (6c) In each of the above-mentioned embodiments, the data obtained by the radar device is sent to the control device (for example, the axis deviation estimation device) to process the data (for example, the axis deviation estimation process), but the radar device itself may process the data (for example, the axis deviation estimation process performed in the axis deviation estimation device). In addition, the data may be processed in each sensor of the vehicle-mounted sensor group, or the data obtained by each sensor may be sent to the control device, and various processes may be performed in the control device.

[0340] (6d) As roadside objects, in addition to guardrails, multiple blocks arranged along the extension direction of the road, multiple poles for distinguishing lanes, etc. can also be used. In addition, as guardrails, guardrails, ducts, cables, box beams and other various vehicle guardrails, pedestrian and bicycle guardrails, etc. can be used.

[0341] In addition, as the roadside objects, for example, a roadside object composed of multiple structures such as the above-mentioned multiple blocks, multiple poles, etc., or a roadside object composed of an integrated single structure can be used. For example, various guardrails, concrete side walls, etc., which are continuously and integrally arranged over a long distance along the extending direction of the road, can be used.

[0342] (6e) The control device and method described in the present disclosure may also be implemented by a special-purpose computer provided by a processor and a memory programmed to execute one or more functions embodied by a computer program.

[0343] Alternatively, the control device and method described in the present disclosure may be implemented by a dedicated computer provided by configuring a processor using one or more dedicated hardware logic circuits.

[0344] Alternatively, the control device and method described in the present disclosure may be implemented by one or more special-purpose computers, each of which is composed of a processor and a memory programmed to perform one or more functions, and a processor composed of one or more hardware logic circuits.

[0345] The computer program may be stored in a computer-readable non-transitory tangible recording medium as instructions executed by the computer. The method of realizing the functions of each unit included in the control device does not necessarily include software, and all functions may be realized using one or more hardware.

[0346] (6f) Multiple functions of one component in the above-mentioned embodiment can be realized by multiple components, or one function of one component can be realized by multiple components. In addition, multiple functions of multiple components can be realized by one component, or one function realized by multiple components can be realized by one component. In addition, part of the structure of the above-mentioned embodiment can be omitted. In addition, at least part of the structure of the above-mentioned embodiment can be added to or replaced with the structure of other above-mentioned embodiments.

[0347] (6g) In addition to the above-mentioned control device, the present disclosure can also be implemented in various forms such as a system that uses the control device as a component, a program for causing a computer to function as the control device, a non-transient tangible recording medium such as a semiconductor memory that records the program, a control method, etc.

Claims

1. An axis deviation estimating device for estimating an axis deviation of a radar device mounted on a mobile body, wherein: The shaft deviation estimation device comprises: an object information acquisition unit configured to repeatedly acquire object information, the object information including an object distance and an object azimuth, the object distance being a distance between the radar device and a reflecting object corresponding to a reflection point of the radar wave detected by the radar device, and the object azimuth being an azimuth at which the reflecting object is located; a roadside object extraction unit configured to extract roadside object information from the object information based on a predetermined extraction condition, the roadside object information indicating information of the reflection point on the roadside object, the roadside object being arranged on the side of a travel path on which the mobile body is traveling, at a position higher than the travel path, along an extension direction of the travel path, according to a predetermined condition; a road surface extraction unit configured to extract road surface information from the object information based on a predetermined extraction condition, the road surface information indicating information of the reflection point on a road surface of a travel path on which the mobile body travels; as well as The axis deviation angle estimating unit is configured to estimate a vertical axis deviation angle based on the roadside object information including information of a plurality of reflection points on the roadside object and the road surface information including information of a plurality of reflection points on the road surface, when the orientation of the radar device when the radar device is mounted in a reference state is set as a mounting reference direction and the actual orientation of the radar device is set as an actual mounting direction. The vertical axis deviation angle indicates a deviation angle of the actual mounting direction in a vertical direction relative to the mounting reference direction. The shaft offset angle estimating unit is configured as follows: estimating a final vertical axis offset angle based on a first vertical axis offset angle estimated using the roadside object information and a second vertical axis offset angle estimated using the road surface information, detecting an inflection point representing a position of curvature in a distribution state of a roadside object point group based on a roadside object point group representing a plurality of the reflection points on a vertical plane of the roadside object, When the distance from the moving body to the inflection point is greater than the maximum distance from the moving body to the reflection point on the road surface, the second reliability of the second vertical axis offset angle is changed to be greater than the first reliability of the first vertical axis offset angle by weighting the second vertical axis offset angle.

2. The axial deviation estimation device according to claim 1, wherein: The axis deviation angle estimating unit has a structure in which the arrangement of the plurality of reflection points of the roadside object on a vertical plane is approximated using a straight line for the roadside object, and the vertical axis deviation angle is estimated using the straight line for the roadside object.

3. The axial deviation estimation device according to claim 1 or 2, wherein: The axis deviation angle estimating unit has a configuration that approximates the arrangement of the plurality of reflection points on the road surface on a vertical plane using a straight line for the road surface, and estimates the vertical axis deviation angle using the straight line for the road surface.

4. The axial deviation estimation device according to claim 1 or 2, wherein: The shaft offset angle estimating unit is configured as follows: In the case where the first vertical axis offset angle is estimated using the roadside object information, and the second vertical axis offset angle is estimated using the road surface information, When the reliability of the estimation of either of the vertical axis offset angles is lower than a predetermined value, the reliability of the estimation of the other vertical axis offset angle is also reduced.

5. The axial deviation estimation device according to claim 1 or 2, wherein: The shaft offset angle estimating unit is configured as follows: In the case where the first vertical axis offset angle is estimated using the roadside object information, and the second vertical axis offset angle is estimated using the road surface information, When the deviation of the positions of the multiple reflection points of the roadside object on the vertical plane is greater than a specified value, the first reliability of the estimation of the first vertical axis deviation angle based on the roadside object information and the second reliability of the estimation of the second vertical axis deviation angle based on the road surface information are reduced together.

6. The axial deviation estimation device according to claim 1 or 2, wherein: The axis deviation estimating device is configured to estimate the vertical axis deviation angle when the moving body is traveling straight.

7. The axial deviation estimation device according to claim 1 or 2, wherein: The axis deviation estimating device is configured to use the map information when extracting the roadside object information, when map information indicating the travel path and the periphery of the travel path includes information on the position of the roadside object.

8. The axial deviation estimation device according to claim 1 or 2, wherein: The axis deviation estimation device is constructed as follows: when a front radar device for detecting the reflecting object in the direction of travel of the moving body, i.e., in front, and a side radar device for detecting the reflecting object on the side of the moving body are configured as the radar device, the estimation of the vertical axis deviation angle is implemented when the roadside object can be detected by the front radar device and the side radar device.

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