Vehicle travel control device, autonomous travel vehicle, and vehicle travel control method

Abstract

A LiDAR (2), which detects the position of marks (M1, M2) provided to a movement destination (9) of an autonomous traveling vehicle (1) with respect to the autonomous traveling vehicle (1), is attached to the autonomous traveling vehicle (1). Two marks (M1, M2) are provided to a movement destination (9), and a mark position detection unit (41) detects the positions of the two marks (M1, M2) with respect to an autonomous traveling vehicle (1) by means of a LiDAR (2), and acquires the detection positions (p1, p2) of the two marks (M1, M2). Furthermore, the storage unit (5) holds reference positions (P1, P2) for the two marks (M1, M2), respectively, the reference positions (P1, P2) being detection positions (p1, p2) of the marks (M1, M2) to be acquired by the mark position detection unit (41) when the autonomous traveling vehicle (1) moves to the movement destination (9). Furthermore, on the basis of the difference between the reference position (P1, P2) and the detection position (p1, p2) of each of the two marks (M1, M2), a travel motor (13) and a steering device (14) for driving the autonomous traveling vehicle (1) are controlled.

Description

Technical Field

[0001] The present invention relates to a technology for controlling a vehicle so that the vehicle travels toward a destination. Background Art

[0002] Patent document 1 describes a technique for detecting a mark (first and second physical features) of a cart that is a destination of movement of the vehicle by using a sensor mounted on the vehicle, thereby obtaining a positional relationship between the vehicle and the mark, and causing the vehicle to autonomously travel toward the cart. In such an autonomous driving technique, it is required to control the position of the vehicle relative to the mark with high precision. In this regard, Patent document 2 describes a technique for estimating the position of the vehicle by matching the position of the mark with map data, and Patent document 3 describes a technique for estimating the position and posture by using a mark having a moiré fringe pattern.

[0003] Prior art literature

[0004] Patent Literature

[0005] Patent document 1: US10168711

[0006] Patent Document 2: Japanese Patent Application Publication No. 2021-194995

[0007] Patent Document 3: Japanese Patent Application No. 2018-135063 Summary of the invention

[0008] Problems to be solved by the invention

[0009] However, it is necessary to prepare map data in Patent Document 2, and it is necessary to prepare a light source environment for accurately reading a moire fringe pattern in Patent Document 3. Therefore, a technology capable of simply and accurately controlling the position of a vehicle relative to a marker is desired.

[0010] The present invention has been made in view of the above-mentioned problems, and an object of the present invention is to control the position of a vehicle relative to a mark simply and with high accuracy.

[0011] Technical solutions to solve problems

[0012] The vehicle travel control device involved in the present invention comprises: a position sensor installed on the vehicle; a mark position detection unit, which uses the position sensor to detect the positions of N (N is an integer greater than 2) reference marks set at the moving destination of the vehicle relative to the vehicle, and obtains the detection position of each of the N reference marks; a storage unit, which maintains a reference position for each of the N reference marks, the reference position being the detection position of the reference mark that the mark position detection unit should obtain when the vehicle moves to the moving destination; and a drive control unit, which controls the vehicle drive unit that drives the vehicle based on the difference between the reference position and the detection position of each of the N reference marks, thereby causing the vehicle to travel toward the moving destination.

[0013] The autonomous driving vehicle according to the present invention includes: a vehicle body; a vehicle drive unit that drives the vehicle body; and the above-mentioned vehicle travel control device that controls the vehicle drive unit.

[0014] The vehicle driving control method involved in the present invention includes: a process of obtaining the detection position of each of N benchmark marks using a mark position detection unit, wherein the position of N (N is an integer greater than 2) benchmark marks set at the moving destination of the vehicle relative to the vehicle is detected using a position sensor installed on the vehicle; a process of reading out the reference position of each of the N benchmark marks from a storage unit, wherein the storage unit maintains a reference position for each of the N benchmark marks, the reference position being the detection position of the benchmark mark that the mark position detection unit should obtain when the vehicle moves to the moving destination; and a process of controlling a vehicle driving unit that drives the vehicle based on the difference between the reference position and the detection position of each of the N benchmark marks, thereby causing the vehicle to travel toward the moving destination.

[0015] In the present invention (vehicle driving control device, autonomous vehicle and vehicle driving control method) thus constructed, a position sensor for detecting the position of a reference mark set at the moving destination of the vehicle relative to the vehicle is installed on the vehicle. N (N is an integer greater than 2) reference marks are set at the moving destination, and the mark position detection unit detects the position of the N reference marks relative to the vehicle using the position sensor to obtain the detection position of each of the N reference marks. In addition, the storage unit maintains a reference position for each of the N reference marks, which is the detection position of the reference mark that the mark position detection unit should obtain when the vehicle moves to the moving destination. In addition, based on the difference between the reference position and the detection position of each of the N reference marks, the vehicle driving unit that drives the vehicle is controlled. That is, based on the difference between the reference position of each of the N reference marks maintained in the storage unit and the detection position of each of the N reference marks detected using the position sensor, the driving of the vehicle is controlled. As a result, the position of the vehicle relative to the mark can be controlled simply and with high precision.

[0016] In addition, the vehicle travel control device may be configured such that an object with N reference marks installed is provided at the destination of movement, each of the N reference marks has a convex shape protruding from the object in a plan view, and the mark position detection unit obtains the position of the vertex of the convex shape of the reference mark as the detection position of the reference mark. In this configuration, the detection position of the reference mark can be easily obtained by detecting the position of the vertex of the convex shape.

[0017] In addition, the vehicle travel control device may be configured such that the convex shape is a V-shape. In this configuration, the detection position of the reference mark can be easily acquired by detecting the position of the apex of the V-shape.

[0018] In addition, the vehicle travel control device can also be configured such that the mark position detection unit has: a point cloud data acquisition unit that obtains point cloud data representing the shape of the object and N reference marks set at the mobile destination by scanning the mobile destination using a position sensor; a minimum point extraction unit that extracts from the point cloud data a point whose Y coordinate value becomes a minimum value on the θ-Y plane composed of the θ coordinate corresponding to the rotation direction of the vehicle rotation and the Y coordinate corresponding to the straight-moving direction of the vehicle; and a minimum point selection unit that obtains the positions of N minimum points that meet the prescribed conditions among the M (M is a natural number greater than N) minimum points extracted by the minimum point extraction unit as the points that become minimum values, as the detection positions of the N reference marks. In this structure, the positions of the N reference marks set on the object can be accurately detected to obtain the detection positions of the N reference marks. Therefore, the reference marks can be detected from a wide range.

[0019] It should be noted that various conditions can be considered as prescribed conditions for obtaining the detection positions of the respective N reference marks from the respective positions of the M minimum points. For example, the prescribed conditions may include the condition that the difference between the distance to the reference position and the distance to the minimum point is less than a first threshold. The prescribed conditions may also include the condition that the difference between the distance between two minimum points among the N minimum points and the distance between the respective reference positions of two reference marks among the N reference marks is less than a second threshold. Alternatively, the prescribed conditions may also include the condition that the slope of a straight line represented by a plurality of points contained in a prescribed object range with the minimum point as the end in the point cloud data is within a prescribed slope range.

[0020] In addition, N may be 2. In this configuration, the travel of the vehicle can be easily controlled based on the difference between the reference position of each of the two reference marks held in the storage unit and the detection position of each of the two reference marks detected by the position sensor.

[0021] Effects of the Invention

[0022] According to the present invention, the position of a vehicle relative to a marker can be controlled simply and with high accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 This is a diagram schematically showing an example of an autonomously traveling vehicle according to the present invention and an object disposed at a destination of movement of the autonomously traveling vehicle.

[0024] Figure 2 Yes means Figure 1 A block diagram of an example of an electrical structure of an autonomous vehicle.

[0025] Figure 3 This is a flowchart showing an example of travel control of the autonomous vehicle executed by the travel control unit.

[0026] Figure 4A It is a schematic representation of Figure 3 A diagram of actions performed for driving control.

[0027] Figure 4B It is a schematic representation of Figure 3 A diagram of actions performed for driving control.

[0028] Figure 4C It is a schematic representation of Figure 3 A diagram of actions performed for driving control.

[0029] Figure 4D It is a schematic representation of Figure 3 A diagram of actions performed for driving control.

[0030] Figure 5 It means in Figure 3 A flowchart of an example of processing performed in mark position detection.

[0031] Figure 6 It means in Figure 5 Flowchart of the operations based on the likelihood function used in the flowchart of .

[0032] Figure 7 It is schematically represented in Figure 5 A diagram of the contents of the operations performed on the point cloud data in the flowchart of FIG. DETAILED DESCRIPTION

[0033] Figure 1 is a diagram schematically showing an example of an autonomously traveling vehicle according to the present invention and an object disposed at a destination of movement of the autonomously traveling vehicle. Figure 2 Yes means Figure 1 A block diagram of an example of an electrical structure of an autonomous vehicle. Figure 1In the figure, the dimensional relationship is schematically described, and does not represent the actual dimensional relationship. The same is true in the following figures.

[0034] The autonomous vehicle 1 is a so-called AGV (Automatic Guided Vehicle). Figure 1 As shown, the autonomous vehicle 1 includes a vehicle body 11 and a plurality of wheels 12 for driving the vehicle body 11. The autonomous vehicle 1 travels by the rotation of the wheels 12. It should be noted that the specific structure for driving the vehicle body 11 is not limited to the wheels 12, and may be, for example, tracks.

[0035] The autonomous vehicle 1 travels toward the destination 9 of the autonomous vehicle 1 and stops when reaching the destination 9. An object 91 is arranged at the destination 9, and the autonomous vehicle 1 that has reached the destination 9 stops in a state of docking with the object 91 or in a state of approaching the object 91.

[0036] The object 91 has a wall 911 erected vertically, and two marks M1 and M2 are installed on the wall 911. The marks M1 and M2 are installed on the wall 911 at intervals in the horizontal direction and are located at the same height. In a top view (i.e., when observed from the upper side in the vertical direction), the marks M1 and M2 have a convex shape protruding from the wall 911, in particular a V-shape, and have vertices V1 and V2. In other words, the marks M1 and M2 have left inclined surfaces Sl1 and Sl2 extending from the wall 911 toward the vertices V1 and V2 on the left side of the vertices V1 and V2, and have right inclined surfaces Sr1 and Sr2 extending from the wall 911 toward the vertices V1 and V2 on the right side of the vertices V1 and V2. It should be noted that right / left is equivalent to right / left when the object 91 is observed from the front on the side where the autonomous vehicle 1 approaches the object 91.

[0037] like Figure 2 As shown, the autonomous vehicle 1 includes a driving motor 13 for driving wheels 12 and a steering device 14 for changing the direction of the wheels 12. That is, the wheels 12 rotate by driving the driving motor 13, and the autonomous vehicle 1 travels. In addition, the direction of the wheels 12 is changed by the steering device 14, so that the direction of the autonomous vehicle 1 travels is changed.

[0038] The autonomous vehicle 1 is equipped with a laser radar (LiDAR, Light Detection and Ranging) 2. The LiDAR 2 detects an object located in front of the autonomous vehicle 1 by scanning a predetermined range in front of the autonomous vehicle 1, and obtains point cloud data Dp representing the three-dimensional shape of the object. In particular, the LiDAR 2 is used to detect the positions of two markers M1 and M2 set at the mobile destination 9.

[0039] Furthermore, the autonomous vehicle 1 further includes a driving control unit 3, which controls a driving motor 13 and a steering device 14 based on the point cloud data Dp obtained by the LiDAR 2. The driving control unit 3 controls the driving motor 13 and the steering device 14 based on the respective positions of the two markers M1 and M2 indicated by the point cloud data Dp, thereby causing the autonomous vehicle 1 to travel toward the moving destination 9.

[0040] The travel control unit 3 includes a calculation unit 4 and a storage unit 5. The calculation unit 4 is a processor such as a CPU (Central Processing Unit), and the storage unit 5 is a storage device such as an SSD (Solid State Drive). The storage unit 5 stores reference position data Dr described below.

[0041] The operation unit 4 includes a marker position detection unit 41, which detects the positions of the two markers M1 and M2 based on the point cloud data Dp obtained by LiDAR2. In particular, the marker position detection unit 41 detects the positions of the vertices V1 and V2 of the markers M1 and M2 as the positions of the markers M1 and M2. The marker position detection unit 41 includes a point cloud data acquisition unit 411, a minimum point extraction unit 412, and a minimum point selection unit 413. The point cloud data acquisition unit 411 acquires the point cloud data Dp from LiDAR2. The functions of the minimum point extraction unit 412 and the minimum point selection unit 413 will be described later.

[0042] The calculation unit 4 also includes a drive control unit 43 . The drive control unit 43 controls the travel motor 13 and the steering device 14 based on the positions of the two markers M1 and M2 detected by the marker position detection unit 41 , thereby causing the autonomous vehicle 1 to travel toward the destination 9 .

[0043] Figure 3 is a flowchart showing an example of driving control of an autonomous vehicle executed by a driving control unit. Figure 4A to Figure 4D It is a schematic representation of Figure 3 A diagram of the actions performed for driving control. Figure 4A to Figure 4D, an XY rectangular coordinate system fixed to LiDAR 2 (in other words, the vehicle body 11) is shown, the Y coordinate represents the position coordinate in the straight direction (straight direction) of the autonomous vehicle 1, and the X coordinate represents the position coordinate in the direction orthogonal to the straight direction of the autonomous vehicle 1 (orthogonal direction).

[0044] It should be noted that LiDAR2 obtains point cloud data Dp representing the three-dimensional shape of surrounding objects by scanning in the rotation direction around the central axis parallel to the vertical direction. The point cloud data Dp is represented by polar coordinates composed of a combination of distance and position in the rotation direction. Figure 4A to Figure 4D In FIG, the detection positions p1 and p2 of the markers M1 and M2 detected by LiDAR2 are represented by polar coordinates (r1, θ1) and (r2, θ2). Here, the distances r1 and r2 are the distances from LiDAR2 to the detection positions p1 and p2 of the markers M1 and M2, and the angles θ1 and θ2 are the angles of the detection positions p1 and p2 of the markers M1 and M2 relative to LiDAR2.

[0045] Moreover, in Figure 4A to Figure 4D , the reference positions P1 and P2 of the markers M1 and M2 are represented by polar coordinates (R1, θ1) and (R2, θ2). Here, the reference positions P1 and P2 are the detection positions p1 and p2 of the markers M1 and M2 that the marker position detection unit 41 should obtain when the autonomous vehicle 1 moves to the destination 9, and are included in the reference position data Dr. That is, when the autonomous vehicle 1 arrives at the destination 9, the detection positions p1 and p2 of the markers M1 and M2 are consistent with the reference positions P1 and P2 of the markers M1 and M2, respectively. In response to this, the marker position detection unit 41 and the drive control unit 43 of the marker position detection unit 41 appropriately read the reference position data Dr from the storage unit 5 and perform the control described below.

[0046] exist Figure 4A to Figure 4C , the state of LiDAR 2 before reaching the moving destination 9 is shown. Figure 4D The state of the LiDAR 2 at the time when it reaches the destination 9 is shown. Figure 3 The autonomous vehicle 1 performs the driving control according to Figure 4A to Figure 4D It should be noted that, for simplicity, the following description is based on the assumption that R1·sin(θ1)=R2·sin(θ2) holds.

[0047] In step S101, the point cloud data acquisition unit 411 causes the LiDAR 2 to perform scanning, and acquires point cloud data Dp from the LiDAR 2. Then, the point cloud data acquisition unit 411 acquires the detection positions p1 and p2 of the markers M1 and M2 based on the point cloud data Dp.

[0048] In step S102, the drive control unit 43 determines whether the offset of the detection positions p1 and p2 of the markers M1 and M2 relative to the reference positions P1 and P2 of the markers M1 and M2 in the rotation direction of the polar coordinates is within the allowable range. Specifically, the determination is made based on the following conditions:

[0049] ΔΔy=||Y1-y1|-|Y2-y2||<ΔΔYth. Here,

[0050] Y1: Y coordinate component of the reference position P1 of the marker M1 (= R1·sin(θ1)),

[0051] y1: Y coordinate component of the detection position p1 of the marker M1 (=r1·sin(θ1)),

[0052] Y2: Y coordinate component of the reference position P2 of the marker M2 (= R2·sin(θ2)),

[0053] y2: Y coordinate component of the detection position p2 of the marker M2 (=r2·sin(θ2)),

[0054] ΔΔYth: A predetermined threshold value corresponding to the allowable range.

[0055] That is, in Figure 4A If the distance ΔΔy shown is less than the threshold ΔΔYth, it is determined that the deviation in the rotation direction is within the allowable range (“Yes” in step S102), and the process proceeds to step S104. Figure 4A If the distance ΔΔy shown is greater than the threshold ΔΔYth, it is determined that the deviation in the rotation direction is outside the allowable range ("No" in step S102), and the process proceeds to step S104 after executing step S103. However, the method of evaluating the deviation in the rotation direction is not limited to the example here, and the deviation in the rotation direction may be evaluated based on whether the angle between the straight line passing through the reference positions P1 and P2 of the markers M1 and M2 and the straight line passing through the detection positions p1 and p2 of the markers M1 and M2 is less than a predetermined threshold angle.

[0056] In the example here, Figure 4A In the state shown, step S102 is executed and the judgment is "No". Therefore, in step S103, the drive control unit 43 controls the steering device 14 according to the distance ΔΔy to rotate the autonomous vehicle 1 in the rotation direction so that the distance ΔΔy is reduced to less than the threshold value ΔΔYth. Figure 4A The result of executing step S103 is as follows: Figure 4B As shown. Figure 4B As shown, the distance ΔΔy becomes substantially zero.

[0057] In step S104, the drive control unit 43 determines whether the offset of the detection positions p1 and p2 of the markers M1 and M2 relative to the reference positions P1 and P2 of the markers M1 and M2 in the Y direction (the direction corresponding to the Y coordinate) is within the allowable range. Specifically, the determination is made based on the following conditions:

[0058] Δy1=|Y1-y1|<Y1th,

[0059] Δy2=|Y1-y1|<Y2th. Here,

[0060] Y1th: The specified threshold value corresponding to the permissible range,

[0061] Y2th: The specified threshold value corresponding to the permissible range,

[0062] The threshold value Y1th is equal to the threshold value Y2th.

[0063] Here, the distance Δy1 is equal to the distance Δy2. Figure 4B If the distance Δy1 shown is less than the threshold value Y1th, it is determined that the deviation in the Y direction is within the allowable range (“Yes” in step S104), and the process proceeds to step S106. Figure 4B When the distance Δy1 shown is equal to or larger than the threshold value Y1th, it is determined that the deviation in the Y direction is outside the allowable range (No in step S104), and the process proceeds to step S106 after executing step S105.

[0064] In the example here, Figure 4B In the state shown, step S104 is executed and the judgment is "No". Therefore, in step S105, the drive control unit 43 controls the travel motor 13 according to the distance Δy1 to move the autonomous vehicle 1 in the Y direction so that the distance Δy1 is reduced to less than the threshold value Y1th. Figure 4B The result of executing step S105 is as follows: Figure 4C As shown. Figure 4C As shown, the distance Δy1 becomes substantially zero.

[0065] In step S106, the drive control unit 43 determines whether the offset of the detection positions p1 and p2 of the markers M1 and M2 relative to the reference positions P1 and P2 of the markers M1 and M2 in the X direction (the direction corresponding to the X coordinate) is within the allowable range. It should be noted that in this example, the offset in the rotation direction in the polar coordinates is evaluated instead of the X direction, thereby substantially evaluating the offset to the X coordinate. Specifically, the determination is made based on the following conditions:

[0066] Δθ1=|θ1-θ1|<θ1th,

[0067] Δθ2=|Θ2-θ2|<Θ2th. Here,

[0068] θ1th: The specified threshold value corresponding to the permissible range,

[0069] θ2th: The specified threshold value corresponding to the permissible range,

[0070] The threshold Θ1th is equal to the threshold Θ2th.

[0071] That is to say, Figure 4C The angle Δθ1 shown is less than the threshold θ1th and Figure 4C If the angle Δθ2 shown is less than the threshold θ2th, it is determined that the deviation in the X direction is within the allowable range (“Yes” in step S106), and the process ends. Figure 3 On the other hand, in Figure 4C The angle Δθ1 shown is greater than the threshold θ1th, or Figure 4C If the angle Δθ2 shown is greater than the threshold value θ2th, it is determined that the deviation in the X direction is outside the allowable range (“No” in step S106), and the process ends after executing step S107. Figure 3 Flowchart of the process.

[0072] In the example here, Figure 4C In the state shown, step S106 is executed and the judgment is "No". Therefore, in step S107, the drive control unit 43 controls the driving motor 13 and the steering device 14 according to the angle Δθ1 and the angle Δθ2 to move the autonomous driving vehicle 1 to the X coordinate in such a way that the angle Δθ1 and the angle Δθ2 are reduced to less than the threshold value θ1th and the threshold value θ2th, respectively. Figure 4C The result of executing step S107 is as follows: Figure 4D As shown. Figure 4D As shown, the angle Δθ1 and the angle Δθ2 are substantially zero.

[0073] Figure 5 It means in Figure 3 A flowchart of an example of processing performed in the mark position detection of Figure 6 It means in Figure 5 Flowchart of the operations based on the likelihood function used in the flowchart of , Figure 7 It is schematically represented in Figure 5 A diagram of the contents of the operations performed on the point cloud data in the flowchart of FIG.

[0074] In step S201, the point cloud data acquisition unit 411 acquires point cloud data Dp from the LiDAR 2 in the above-mentioned manner. Figure 7 , point cloud data Dp composed of a plurality of points dt each representing a three-dimensional position is schematically shown.

[0075] In step S202, the minimum point extraction unit 412 extracts points (minimum points Ia, Ib, Ic) whose Y coordinate values ​​become minimum values ​​on the θ-Y plane composed of the θ coordinate corresponding to the rotation direction of the autonomous vehicle 1 and the Y coordinate corresponding to the straight direction of the autonomous vehicle 1 from the point cloud data Dp. Figure 7 In the example, three minimum points Ia, Ib, and Ic are extracted from the point cloud data Dp.

[0076] In step S203, the minimum point selection unit 413 determines whether the number M of the minimum points Ia, Ib, and Ic extracted by the minimum point extraction unit 412 is greater than the number N of the markers M1 and M2. In this example, the number of the minimum points Ia, Ib, and Ic (three) is greater than the number N (two) of the markers M1 and M2, so it is determined to be "yes" and the process proceeds to step S204.

[0077] In step S204, the minimum point selection unit 413 generates a combination of N (two) minimum points Ia, Ib, and Ic from M (three). In step S205, the minimum point selection unit 413 calculates the evaluation value of one of the multiple combinations generated in step S204 using a likelihood function. Here, the likelihood function is a function that evaluates the degree of matching between the N minimum points included in the target combination and the markers M1 and M2, and the higher the degree, the smaller the evaluation value output.

[0078] Figure 6 The calculation algorithm of the likelihood function shown is executed by the minimum point selection unit 413. In step S301, the distance Δr1 is calculated for the minimum point on the left of the two minimum points included in a combination that becomes the calculation object of the likelihood function, and the distance Δr2 is calculated for the minimum point on the right. Here, the distance Δr1 is the absolute value of the difference between the distance from LiDAR2 to the minimum point on the left and the distance r1 from LiDAR2 to the reference position P1, and the distance Δr2 is the absolute value of the difference between the distance from LiDAR2 to the minimum point on the right and the distance R2 from LiDAR2 to the reference position P2. For example, in the case of a combination consisting of minimum points Ia and Ib as the object,

[0079] Δr1=|R1-ra|,

[0080] Δr2=|R2-rb|.

[0081] In the case of a combination consisting of the minimum points Ib and Ic,

[0082] Δr1=|R1-rb|,

[0083] Δr2=|R2-rc|.

[0084] In the case of a combination consisting of the minimum points Ia and Ic,

[0085] Δr1=|R1-ra|,

[0086] Δr2=|R2-rc|.

[0087] Then, determine whether the following conditions are met:

[0088] Δr1<R1th and Δr2<R2th (step S301).

[0089] Here, R1th and R2th are preset threshold values. If the condition of step S301 is not satisfied (in the case of "No"), the evaluation value C is determined to be infinite in step S306.

[0090] On the other hand, if the condition of step S301 is met ("yes"), the process proceeds to step S302. Then, it is determined whether the following conditions are met between the distance d between the two minimum points included in a combination and the distance D between the two reference positions P1 and P2:

[0091] Δd=|Dd|<ΔDth (step S302).

[0092] Here, ΔDth is a preset threshold. For example, in the case of a combination consisting of the local minimum points Ia and Ib,

[0093] Δd=|D-dab|,

[0094] dab: The distance between the two minimum points Ia and Ib.

[0095] In the case of a combination consisting of the minimum points Ib and Ic,

[0096] Δd=|D-dbc|,

[0097] dbc: The distance between two minimum points Ib and Ic.

[0098] In the case of a combination consisting of the minimum points Ia and Ic,

[0099] Δd=|D-dac|,

[0100] dac: The distance between the two minimum points Ia and Ic.

[0101] When the condition of step S302 is not satisfied (in the case of "No"), the evaluation value C is determined to be infinite in step S306.

[0102] On the other hand, when the condition of step S302 is met (the "yes" case), proceed to step S303. Then, the slope m1 is calculated for the left minimum point of the two minimum points included in a combination, and the slope m2 is calculated for the right minimum point. Here, the slope m1 is the slope of the straight line represented by the multiple points dt included in the prescribed object range (the range below the width of the right slope Sr1 of the left mark M1) with the left minimum point as the end, and the slope m2 is the slope of the straight line represented by the multiple points dt included in the prescribed object range (the range below the width of the left slope Sl2 of the right mark M1) with the right minimum point as the end. It should be noted that the so-called straight line represented by the multiple points dt is, for example, a regression line for the multiple points dt. For example, in the case of a combination consisting of the minimum points Ia and Ib as the object,

[0103] m1=mar (the slope of the point cloud around the right side of the minimum point Ia),

[0104] m2=mbl (the slope of the point cloud contained in the left periphery of the minimum point Ib).

[0105] In the case of a combination consisting of the minimum points Ib and Ic,

[0106] m1=mbr (the slope of the point cloud around the right side of the minimum point Ib),

[0107] m2=mcl (the slope of the point cloud contained in the left periphery of the minimum point Ic).

[0108] In the case of a combination consisting of the minimum points Ia and Ic,

[0109] m1=mar (the slope of the point cloud around the right side of the minimum point Ia),

[0110] m2=mcl (the slope of the point cloud contained in the left periphery of the minimum point Ic).

[0111] Then, determine whether the following conditions are met:

[0112] M1thm<m1<M1thp and M2thm<m2<M1thp (step S303).

[0113] Here, M1thm, M1thp, M2thm, and M2thp are preset threshold values. If the condition of step S303 is not satisfied (in the case of "No"), the evaluation value C is determined to be infinite in step S306.

[0114] On the other hand, if the condition of step S303 is satisfied ("yes"), the process proceeds to step S304. Then, for the slope m1 of the left minimum point and the slope m2 of the right minimum point of the two minimum points included in one combination, it is determined whether the following conditions are satisfied:

[0115] Δm=|m1-m2|<ΔMth (step S304).

[0116] Here, ΔMth is a preset threshold value. When the condition of step S304 is not satisfied (in the case of “No”), the evaluation value C is determined to be infinite in step S306.

[0117] On the other hand, if the condition of step S304 is satisfied ("yes"), the process proceeds to step S305. Then, the evaluation value C is determined by the following relational expression:

[0118] C=Δr1 / R1+Δr2 / R2+Δd / D.

[0119] return Figure 5 Continue with the description. Figure 6 When the calculation of the evaluation value of the likelihood function (step S205) is completed for all combinations ("Yes" in step S206), the minimum point selection unit 413 selects the positions of the two minimum values ​​of the combination with the smallest evaluation value as the detection positions p1 and p2 of the two markers M1 and M2 respectively (step S207). On the other hand, in the case of "No" in step S203, the minimum point selection unit 413 selects the positions of the two minimum values ​​extracted in step S202 as the detection positions p1 and p2 of the two markers M1 and M2 respectively (step S208). As a result, Figure 7 In the example, the positions of the minimum points I1 and I3 are selected as the detection positions p1 and p2 of the two marks M1 and M2 respectively (steps S207 and S208).

[0120] In the above-described embodiment, the LiDAR 2 (position sensor) for detecting the position of the markers M1 and M2 (reference markers) provided at the destination 9 of the autonomous vehicle 1 relative to the autonomous vehicle 1 is installed on the autonomous vehicle 1. Two markers M1 and M2 are provided at the destination 9, and the marker position detection unit 41 detects the positions of the two markers M1 and M2 relative to the autonomous vehicle 1 using the LiDAR 2, and obtains the detection positions p1 and p2 of the two markers M1 and M2, respectively (step S102). In addition, the storage unit 5 stores the reference positions P1 and P2 for the two markers M1 and M2, respectively, which are the detection positions p1 and p2 of the markers M1 and M2 that the marker position detection unit 41 should obtain when the autonomous vehicle 1 moves to the destination 9. In addition, the travel motor 13 and the steering device 14 (vehicle drive unit) for driving the autonomous vehicle 1 are controlled based on the difference between the reference positions P1 and P2 of the two markers M1 and M2 and the detection positions p1 and p2, respectively. That is, the travel of the autonomous vehicle 1 is controlled based on the difference between the reference positions P1 and P2 of the two markers M1 and M2 respectively stored in the storage unit 5 and the detection positions p1 and p2 of the two markers M1 and M2 respectively detected by the LiDAR 2. As a result, the position of the autonomous vehicle 1 relative to the markers M1 and M2 can be controlled easily and with high accuracy.

[0121] In addition, an object 91 having two markers M1 and M2 attached thereto is provided at the destination 9, and the two markers M1 and M2 each have a convex shape protruding from the object 91 in a plan view. In contrast, the marker position detection unit 41 obtains the positions of the vertices V1 and V2 of the convex shapes of the markers M1 and M2 as the detection positions p1 and p2 of the markers M1 and M2. In this configuration, by detecting the positions of the vertices V1 and V2 of the convex shapes, the detection positions p1 and p2 of the markers M1 and M2 can be easily obtained.

[0122] The convex shape of the marks M1 and M2 is a V-shape. In this configuration, by detecting the positions of the vertices V1 and V2 of the V-shape, the detection positions p1 and p2 of the marks M1 and M2 can be easily acquired.

[0123] In addition, the marker position detection unit 41 includes a point cloud data acquisition unit 411, a local point extraction unit 412, and a local point selection unit 413. The point cloud data acquisition unit 411 scans the destination 9 using the LiDAR 2, thereby acquiring point cloud data Dp representing the shapes of the object 91 and the two markers M1 and M2 set at the destination 9. The local point extraction unit 412 extracts local points I1, I2, and I3 whose Y coordinate values ​​become local minimum values ​​on the θ-Y plane composed of the θ coordinate corresponding to the rotation direction of the autonomous vehicle 1 and the Y coordinate corresponding to the straight direction of the autonomous vehicle 1 from the point cloud data Dp. In addition, the local point selection unit 413 obtains the positions of two local points I1 and I3 that satisfy the prescribed conditions (steps S301, S302, S303, and S304) among the three or more local points I1, I2, and I3 extracted by the local point extraction unit 412 as points of local values, as the detection positions p1 and p2 of the two markers M1 and M2. In this configuration, the positions of the two markers M1 and M2 set on the object 91 can be accurately detected to obtain the detection positions p1 and p2 of the two markers M1 and M2. Therefore, the markers M1 and M2 can be detected from a wide range.

[0124] Thus, in the above-mentioned embodiment, the autonomous driving vehicle 1 is equivalent to an example of the “vehicle” and the “autonomous driving vehicle” of the present invention, the vehicle body 11 is equivalent to an example of the “vehicle body” of the present invention, the driving motor 13 and the steering device 14 constitute an example of the “vehicle driving unit” of the present invention, the LiDAR 2 is equivalent to an example of the “position sensor” of the present invention, the LiDAR 2 and the driving control unit 3 constitute an example of the “vehicle driving control device” of the present invention, the mark position detection unit 41 is equivalent to an example of the “mark position detection unit” of the present invention, the point cloud data acquisition unit 411 is equivalent to an example of the “point cloud data acquisition unit” of the present invention, the minimum point extraction unit 412 is equivalent to an example of the “minimum point extraction unit” of the present invention, the minimum point selection unit 413 is equivalent to an example of the “minimum point selection unit” of the present invention, and the drive control unit 43 is equivalent to the present invention. An example of a “drive control unit”, the storage unit 5 is equivalent to an example of a “storage unit” of the present invention, the moving destination 9 is equivalent to an example of a “moving destination” of the present invention, the object 91 is equivalent to an example of an “object” of the present invention, the point cloud data Dp is equivalent to an example of the “point cloud data” of the present invention, the two marks M1 and M2 are equivalent to an example of “N (N is an integer greater than 2) reference marks” of the present invention, the detection positions p1 and p2 are equivalent to an example of a “detection position” of the present invention, the reference positions P1 and P2 are equivalent to an example of a “reference position” of the present invention, the threshold values ​​ΔR1th and ΔR2th are equivalent to an example of a “first threshold value” of the present invention, the threshold value ΔDth is equivalent to an example of a “second threshold value” of the present invention, and the ranges M1thm~M1thp and M2thm~M2thp are equivalent to an example of an “object range” of the present invention.

[0125] In addition, the present invention is not limited to the above-mentioned embodiment, and various modifications can be made to the above-mentioned embodiment as long as they do not deviate from the main purpose. For example, the mark position detection unit 41 and the storage unit 5 can also be configured to be built in a server computer outside the autonomous vehicle 1, and the autonomous vehicle 1 can be controlled wirelessly from the server computer.

[0126] In addition, the number N of the markers M1 and M2 is not limited to two, and may be three or more.

[0127] In addition, the arrangement and shape of the marks M1 and M2 may be changed appropriately.

[0128] Description of symbols

[0129] 1… Autonomous vehicle (vehicle);

[0130] 11…vehicle body;

[0131] 13…travel motor (vehicle drive unit);

[0132] 14…steering device (vehicle drive unit);

[0133] 2…LiDAR (position sensor, vehicle driving control device);

[0134] 3…travel control unit (vehicle travel control device);

[0135] 41 ... a mark position detection unit;

[0136] 411…point cloud data acquisition unit;

[0137] 412…Minimum point extraction unit;

[0138] 413…Minimum point selection department;

[0139] 43 ... drive control unit;

[0140] 5…storage unit;

[0141] 9…Move destination;

[0142] 91…object;

[0143] Dp…point cloud data;

[0144] M1, M2…marks (reference marks);

[0145] p1, p2…detection position;

[0146] P1, P2…reference position.

Claims

1. A vehicle driving control device, comprising: A position sensor, mounted on the vehicle; The mark position detection unit detects the positions of N reference marks provided at the moving destination of the vehicle relative to the vehicle using the position sensor, and obtains the detection positions of the N reference marks respectively, wherein: N is an integer greater than 2; a storage unit that holds reference positions for each of the N reference marks, the reference positions being the detection positions of the reference marks that the mark position detection unit should obtain when the vehicle moves to the movement destination; and The drive control unit controls a vehicle drive unit that drives the vehicle based on a difference between the reference position and the detection position of each of the N reference marks, thereby causing the vehicle to travel toward the movement destination.

2. The vehicle travel control device according to claim 1, wherein: An object having the N reference marks installed thereon is provided at the destination of movement, The N reference marks each have a convex shape protruding from the object in a plan view, The mark position detection unit acquires the position of the vertex of the convex shape of the reference mark as the detected position of the reference mark.

3. The vehicle travel control device according to claim 2, wherein: The convex shape is a V-shape.

4. The vehicle travel control device according to claim 2 or 3, wherein: The mark position detection unit has: a point cloud data acquisition unit that acquires point cloud data representing shapes of the object and the N reference marks provided at the movement destination by scanning the movement destination using the position sensor; a minimum point extraction unit that extracts, from the point cloud data, a point whose Y coordinate value becomes a minimum value on a θ-Y plane composed of a θ coordinate corresponding to a rotation direction of the vehicle rotation and a Y coordinate corresponding to a straight direction of the vehicle straight travel; and The minimum point selection unit obtains the positions of N minimum points satisfying the specified conditions among the M minimum points extracted by the minimum point extraction unit as the detection positions of the N reference marks, where M is a natural number greater than N.

5. The vehicle travel control device according to claim 4, wherein: The predetermined condition includes a condition that the difference between the distance to the reference position and the distance to the minimum point is smaller than a first threshold value.

6. The vehicle travel control device according to claim 4 or 5, wherein: The prescribed condition includes a condition that a difference between a distance between two of the N minimum points and a distance between the respective reference positions of two of the N reference marks is smaller than a second threshold value.

7. The vehicle travel control device according to any one of claims 4 to 6, wherein: The predetermined condition includes a condition that a slope of a straight line represented by a plurality of points included in a predetermined target range with the minimum point as an end in the point cloud data is within a predetermined slope range.

8. The vehicle travel control device according to any one of claims 1 to 7, wherein: N is 2.

9. An autonomous vehicle having: Vehicle body; A vehicle driving unit drives the vehicle body; and The vehicle travel control device according to any one of claims 1 to 8 controls the vehicle drive unit.

10. A vehicle driving control method, comprising: A step of obtaining a detection position of each of N reference marks using a mark position detection unit, wherein the positions of the N reference marks provided at a moving destination of the vehicle relative to the vehicle are detected using a position sensor mounted on the vehicle, and N is an integer greater than or equal to 2; a step of reading out a reference position of each of the N reference marks from a storage unit, the storage unit storing the reference position for each of the N reference marks, the reference position being the detection position of the reference mark to be acquired by the mark position detection unit when the vehicle moves to the movement destination; and A step of controlling a vehicle driving unit that drives the vehicle based on a difference between the reference position and the detection position of each of the N reference marks, thereby causing the vehicle to travel toward the movement destination.

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