Vehicle determination system

Abstract

To make it possible to determine whether or not a vehicle loading platform can be detected depending on a posture of a work machine.SOLUTION: A vehicle determination system 1 determines a vehicle 10 having a loading platform 13. The vehicle determination system 1 includes a loading platform detection unit 30, a posture detection unit 41, and a determination unit 55. The loading platform detection unit 30 detects information including a distance to the loading platform 13. The posture detection unit 41 detects a posture of a work machine 20 performing a work to the vehicle 10. The determination unit 55 determines whether or not the loading platform detection unit 30 can detect the loading platform 13 depending on the posture detected by the posture detection unit 41.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] The present invention relates to a vehicle discrimination system for discriminating the type of a vehicle. [Background technology]

[0002] For example, Patent Document 1 describes a technology for identifying the type of vehicle (called the model in the document). In the technology described in the document, a display unit is provided on the vehicle. The document describes that the blinking cycle of the display unit differs depending on the vehicle type, that the display unit has a different color depending on the vehicle type, and that the light emission color of the display unit differs depending on the vehicle type. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 11-210020 Summary of the Invention [Problem to be solved by the invention]

[0004] The technology described in this document requires that a display unit (marker) for identifying the type of vehicle be provided on the vehicle and that the display unit be set according to the type of vehicle, which is time-consuming.

[0005] SUMMARY OF THE INVENTION It is therefore an object of the present invention to provide a vehicle identification system that can identify the type of vehicle without providing a mark on the vehicle for identifying the type of vehicle. [Means for solving the problem]

[0006] The vehicle discrimination system discriminates the type of vehicle having a cargo bed. The vehicle discrimination system includes a cargo bed detection unit, a dimension information calculation unit, a memory unit, and a discrimination unit. The cargo bed detection unit detects information including the distance to the cargo bed. The dimension information calculation unit calculates dimensional information of the cargo bed based on the distance detected by the cargo bed detection unit. The memory unit stores a correspondence relationship between the dimensional information of the cargo bed and the type of the vehicle. The discrimination unit discriminates the type of the vehicle based on the dimensional information calculated by the dimension information calculation unit and the correspondence relationship stored in the memory unit. [Effects of the Invention]

[0007] With the above configuration, the type of vehicle can be identified without providing a mark on the vehicle for identifying the type of vehicle. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a side view of a vehicle 10, a work machine 20, and the like of a vehicle discrimination system 1. FIG. [Figure 2] FIG. 2 is a top view of the vehicle 10 and the work machine 20 shown in FIG. [Figure 3] 2 is a diagram showing a loading platform 13 and other components detected by a loading platform detection unit 30 shown in FIG. 1. FIG. [Figure 4] FIG. 2 is a block diagram of the vehicle discrimination system 1 shown in FIG. [Figure 5] 5 is a flowchart showing the processing of the controller 50 shown in FIG. 4. DETAILED DESCRIPTION OF THE INVENTION

[0009] The vehicle discrimination system 1 will be described with reference to FIGS.

[0010] The vehicle discrimination system 1 is a system that discriminates the type of vehicle 10 shown in Fig. 1. The vehicle discrimination system 1 includes the vehicle 10, a work machine 20, a loading platform detection unit 30, an attitude detection unit 41 shown in Fig. 4, a position detection unit 43, and a controller 50.

[0011] As shown in Fig. 1, the vehicle 10 has a loading platform 13. The vehicle 10 is a machine (a work machine for carrying out carrying work, a carrying vehicle, a transport vehicle) that carries an object to be carried stored in the loading platform 13. The vehicle 10 is, for example, a dump truck. The vehicle 10 includes a vehicle main body 11 and the loading platform 13.

[0012] The vehicle body 11 supports a loading platform 13. The vehicle body 11 is movable and may move on wheels or crawlers. The vehicle body 11 includes a vehicle cab 11a.

[0013] The loading platform 13 accommodates objects to be transported. The objects to be transported stored in the loading platform 13 may be earth and sand, stones, wood, metal, waste, or structures such as concrete. The loading platform 13 is arranged on the vehicle rear side X2 (described later) of the vehicle driver's cab 11a. The loading platform 13 is, for example, box-shaped without a lid (see FIG. 3). The loading platform 13 may be movable relative to the vehicle main body 11 or may be fixed to the vehicle main body 11. The following describes a state in which the floor surface 13a (described later) of the loading platform 13 is arranged horizontally or approximately horizontally. The loading platform 13 includes the floor surface 13a, a rear gate panel surface 13b, a side gate panel surface 13c, and a shrine gate surface 13d.

[0014] (Towards vehicle 10) A direction related to the vehicle 10, which corresponds to the vertical direction when the vehicle 10 is placed on a horizontal surface, is defined as the vehicle up-down direction Z. The longitudinal direction of the loading platform 13 is defined as the vehicle fore-and-aft direction X. In the vehicle fore-and-aft direction X, the side facing the vehicle driver's cab 11a from the loading platform 13 is defined as the vehicle front side X1, and the opposite side is defined as the vehicle rear side X2. A direction perpendicular to both the vehicle up-down direction Z and the vehicle width direction Y is defined as the vehicle width direction Y.

[0015] The floor surface 13a is the bottom surface of the loading platform 13. The floor surface 13a is flat or approximately flat (the same applies to the rear gate plate surface 13b, the side gate plate surface 13c, and the gate plate surface 13d). The rear gate plate surface 13b is the surface of the loading platform 13 on the vehicle rear side X2 and protrudes upward from the vehicle rear side X2 portion of the floor surface 13a. The side gate plate surfaces 13c are the surfaces of the loading platform 13 on the outer sides (left and right) of the vehicle width direction Y (see Figure 3) and protrude upward from the left and right ends of the floor surface 13a. The gate plate surface 13d is the surface of the loading platform 13 on the vehicle front side X1 and protrudes upward from the vehicle front side X1 portion of the floor surface 13a. The gate plate surface 13d protrudes upward above the side gate plate surfaces 13c and above the rear gate plate surface 13b.

[0016] The work machine 20 performs work on the vehicle 10. For example, the work machine 20 performs work of loading transport objects onto the loading platform 13 (such as earth and sand loading work). The work machine 20 is, for example, a construction machine, and may be, for example, a shovel or a crane. The following describes a case where the work machine 20 is a shovel. The work machine 20 comprises a lower traveling body 21, an upper rotating body 23, and an attachment 25.

[0017] The lower traveling body 21 allows the work machine 20 to travel. The lower traveling body 21 includes, for example, crawlers.

[0018] The upper rotating body 23 is mounted so as to be able to rotate on the lower traveling body 21. The upper rotating body 23 is equipped with a work machine cab 23a. The work machine cab 23a is a section where an operator can operate the work machine 20. The work machine 20 may be operated by operation by the operator, or may be operated automatically.

[0019] The attachment 25 is a part that performs work, and includes, for example, a boom 25a, an arm 25b, and a tip attachment 25c. The boom 25a is attached to the upper rotating body 23 so that it can be raised and lowered (rotated up and down). The arm 25b is attached rotatably relative to the boom 25a. The tip attachment 25c is provided at the tip of the attachment 25 and is rotatably attached to the arm 25b. The tip attachment 25c may be, for example, a bucket for scooping earth and sand, a device for clamping objects (such as a grapple), or a device for crushing, excavating, etc. (such as a breaker).

[0020] The platform detection unit 30 (distance acquisition means) detects information including the distance to the platform 13 (the distance from the platform detection unit 30 to the platform 13). The platform detection unit 30 is disposed in a position where the platform 13 can be detected. For example, the platform detection unit 30 may be attached to the work machine 20. For example, the platform detection unit 30 may be attached to the work machine cab 23a. In this case, the platform detection unit 30 may be attached to the roof of the work machine cab 23a, or may be disposed inside the work machine cab 23a. The platform detection unit 30 may be attached to a part of the work machine 20 other than the work machine cab 23a.

[0021] This bed detection unit 30 may be located outside the work machine 20 (see bed detection unit 30 indicated by a two-dot chain line in FIG. 1). For example, the bed detection unit 30 may be installed at the work site where the work machine 20 is located (the work site where the vehicle 10 is located). Like the bed detection unit 30, the position detection unit 43 and the controller 50 may each be mounted on the work machine 20 or may be located outside the work machine 20. The bed detection unit 30 may be provided in only one location, or in multiple locations (the same applies to the position detection unit 43 and the controller 50). For example, there may be a bed detection unit 30 mounted on the work machine 20 and a bed detection unit 30 located outside the work machine 20 (the same applies to the position detection unit 43 and the controller 50).

[0022] The loading platform detection unit 30 may detect the distance to a part of the loading platform 13 (for example, the shrine gate surface 13d and the rear gate panel surface 13b). The loading platform detection unit 30 may detect a distance image (described later) of the entire or substantially the entire loading platform 13. The loading platform detection unit 30 may detect information other than distance, and specifically may detect a two-dimensional image of the loading platform 13. For example, the loading platform detection unit 30 includes a two-dimensional image detection unit 31 and a three-dimensional information detection unit 33.

[0023] The two-dimensional image detection unit 31 detects a two-dimensional image of the loading platform 13. The two-dimensional image detected by the two-dimensional image detection unit 31 includes the entire loading platform 13, as shown in FIG. 3, for example (the same applies to the distance image acquired by the three-dimensional information detection unit 33). This two-dimensional image may include parts of the vehicle 10 other than the loading platform 13, and may also include the work machine 20 (for example, the attachment 25) (the same applies to the distance image acquired by the three-dimensional information detection unit 33). The two-dimensional image detection unit 31 shown in FIG. 1 is specifically a monocular camera.

[0024] The three-dimensional information detection unit 33 detects three-dimensional information (three-dimensional distance information) including the loading platform 13. The three-dimensional information detection unit 33 acquires an image (distance image) having distance information (depth information). Specifically, for example, the three-dimensional information detection unit 33 detects point cloud data, etc. The three-dimensional information detection unit 33 may be equipped with a device that detects three-dimensional information using laser light, such as a LIDAR (Light Detection and Ranging) sensor, or a TOF (Time Of Flight) sensor. The three-dimensional information detection unit 33 may be equipped with a device that detects three-dimensional information using radio waves (such as a millimeter-wave radar). The three-dimensional information detection unit 33 may be equipped with a stereo camera. The coordinate system of the two-dimensional image and the coordinate system of the three-dimensional information are unified. For example, these coordinate systems may be unified into a coordinate system based on the work machine 20 (machine coordinate system), or a coordinate system based on the work site.

[0025] The loading platform detection unit 30 may include a device that detects one-dimensional or two-dimensional distance information. More specifically, the loading platform detection unit 30 may include a device that detects the distance from the loading platform detection unit 30 to a certain point (a device that detects one-dimensional distance information). The loading platform detection unit 30 may include a device that detects the distance to each point where a plane passing through the loading platform detection unit 30 intersects with the loading platform 13 (a device that detects two-dimensional distance information). For example, the loading platform detection unit 30 may include an optical sensor (e.g., a laser sensor) or a radio wave sensor that detects one-dimensional or two-dimensional distance information.

[0026] The attitude detection unit 41 (see FIG. 4) detects the attitude of the work machine 20. The attitude detection unit 41 may detect the rotation angle (hoisting angle) of the boom 25a relative to the upper rotating body 23. The attitude detection unit 41 may detect the rotation angle of the arm 25b relative to the boom 25a. The attitude detection unit 41 may detect the rotation angle of the tip attachment 25c relative to the arm 25b. The attitude detection unit 41 may detect the swing angle of the upper rotating body 23 relative to the lower traveling body 21. The attitude detection unit 41 may be equipped with a sensor (e.g., a rotary encoder) that detects an angle, a sensor that detects an inclination with respect to a horizontal plane, or a sensor that detects the stroke of a cylinder (not shown) that drives the attachment 25. The attitude detection unit 41 may detect the attitude of the work machine 20 based on at least one of a two-dimensional image and a range image. In this case, at least one of the two-dimensional image and the distance image may be detected by the loading platform detection unit 30 (the loading platform detection unit 30 may also serve as the posture detection unit 41).

[0027] The position detection unit 43 (see FIG. 4) detects the position of the work machine 20 at the work site. The position detection unit 43 may detect the position and orientation of the work machine 20 relative to the work site (for example, the orientation of the upper rotating body 23). The position detection unit 43 may detect the position and orientation of a reference part of the work machine 20 relative to the work site. The reference part of the work machine 20 may be, for example, a specific part of the upper rotating body 23 or the lower running body 21, or may be, for example, the attachment part (boom foot) of the boom 25a to the upper rotating body 23.

[0028] The controller 50 (see FIG. 4) is a computer that inputs and outputs signals, performs calculations (processing), stores information, etc. For example, the functions of the controller 50 shown in FIG. 4 are realized by the calculation unit executing a program stored in the memory unit 53 or the like of the controller 50. The controller 50 performs processing related to the determination of the type of the vehicle 10 (see FIG. 1). The controller 50 may also perform processing other than the determination of the type of the vehicle 10. For example, the controller 50 may control the automatic operation of the work machine 20 (see FIG. 1), or may perform control to assist the operation of the work machine 20. The controller 50 includes a dimension information calculation unit 51, a memory unit 53, a discrimination unit 55, and a detection feasibility determination unit 57.

[0029] The dimension information calculation unit 51 calculates dimension information of the loading platform 13 based on the distance detected by the loading platform detection unit 30 shown in FIG. 1. This dimension information is information that serves as a reference for determining the type of the vehicle 10. Information that can determine the type of the vehicle 10 is used as the dimension information. Specific examples of the dimension information are as follows:

[0030] [Example A1] The dimensional information may include dimensions of the loading platform 13 in a specific direction or dimensions of a specific part. [Example A1a] The dimensional information may include the dimension Lx of the loading platform 13 in the vehicle's fore-and-aft direction X (the dimension or depth of the loading platform 13 in the longitudinal direction of the loading platform 13). For example, the dimension Lx is the distance between the gate surface 13d and the rear gate panel surface 13b in the vehicle's fore-and-aft direction X. [Example A1b] The dimensional information may include the dimension Ly (width) of the loading platform 13 in the vehicle's width direction Y shown in Figure 2. For example, the dimension Ly may be the distance in the vehicle's width direction Y between the side gate panel surfaces 13c on both sides of the vehicle's width direction Y. For example, the dimension Ly may be the dimension in the vehicle's width direction Y of the rear gate panel surface 13b or the gate surface 13d. [Example A1c] The dimensional information may include the dimension of the loading platform 13 in the vehicle's up-down direction Z. For example, the dimension information may include the dimension Lzb (height) in the vehicle up-down direction Z of the rear gate plate surface 13b (or the side gate plate surface 13c) shown in Figure 1. For example, the dimension information may include the dimension Lzd (height) in the vehicle up-down direction Z of the shrine gate surface 13d.

[0031] [Example A2] The dimensional information may include the overall dimensions (in each direction) of the loading platform 13. More specifically, the dimensional information may include the dimension Lx, the dimension Ly (see FIG. 2), and the dimension in the vehicle vertical direction Z (at least one of the dimension Lzb and the dimension Lzd) of the loading platform 13.

[0032] [Example A3] The dimension information may include the capacity of the loading platform 13 calculated from the dimensions of the loading platform 13. Specifically, the capacity of the loading platform 13 is the product of the dimension Lx of the loading platform 13, the dimension Ly (see FIG. 2), and the dimension Lzb.

[0033] [Example A4] The dimensional information may include information on the three-dimensional shape of the loading platform 13. More specifically, the dimensional information may include information on the three-dimensional shape of the entire loading platform 13 (or approximately the entire loading platform 13). For example, the information on the three-dimensional shape of the loading platform 13 may include the dimension Lx, the dimension Ly (see FIG. 2), and the dimension Lzb. For example, the information on the three-dimensional shape of the loading platform 13 may include the height from the intersection of the upper end of the side gate panel surface 13c and the gate surface 13d to the upper end of the gate surface 13d (the value obtained by subtracting the dimension Lzb from the dimension Lzd). For example, the information on the three-dimensional shape of the loading platform 13 may include the dimension Lzd of the gate surface 13d in the vertical direction Z of the vehicle. The information on the three-dimensional shape of the loading platform 13 may also include information on the angle between each surface (rear gate panel surface 13b, side gate panel surface 13c, etc.).

[0034] The dimension information calculation unit 51 (see FIG. 4) calculates the dimension information, for example, as follows.

[0035] [Example B1] A specific example of the case where the dimension information calculation unit 51 (see FIG. 4) calculates the three-dimensional shape of the loading platform 13 (see [Example A4] above) is as follows.

[0036] [Example B1a] For example, the dimension information calculation unit 51 shown in Fig. 4 calculates a three-dimensional shape based on a two-dimensional image and three-dimensional information. More specifically, the dimension information calculation unit 51 includes a two-dimensional shape calculation unit 51a and a three-dimensional shape calculation unit 51b.

[0037] The two-dimensional shape calculation unit 51a calculates (estimates) the two-dimensional shape of the loading platform 13 (see FIG. 3) based on the two-dimensional image detected by the two-dimensional image detection unit 31. For example, the two-dimensional shape calculation unit 51a calculates the two-dimensional shape of the loading platform 13 by image recognition. Specifically, for example, the two-dimensional shape calculation unit 51a extracts (recognizes, estimates) feature points P (see FIG. 3) corresponding to the positions of the corners of the loading platform 13 in the two-dimensional image. The two-dimensional shape calculation unit 51a also determines links L (see FIG. 3) corresponding to the sides of the loading platform 13 in the two-dimensional image. As shown in FIG. 3, the links L are line segments connecting the feature points P. The two-dimensional shape calculation unit 51a shown in FIG. 4 determines the feature points P (see FIG. 3) and the links L (see FIG. 3) by, for example, executing software that extracts a specific shape from a two-dimensional image. For example, this software uses deep learning technology.

[0038] The three-dimensional shape calculation unit 51b calculates the three-dimensional shape of the loading platform 13 (see FIG. 3). The three-dimensional shape calculation unit 51b calculates the three-dimensional shape of the loading platform 13 based on the two-dimensional shape of the loading platform 13 calculated by the two-dimensional shape calculation unit 51a and three-dimensional information (e.g., point cloud data) of the loading platform 13 detected by the three-dimensional information detection unit 33. Specifically, for example, the three-dimensional shape calculation unit 51b identifies the positions of the corners and sides of the loading platform 13 (see FIG. 3) in the three-dimensional information detected by the three-dimensional information detection unit 33 from the positions (two-dimensional coordinates) of the feature point P (see FIG. 3) and the link L (see FIG. 3) in the two-dimensional image. The three-dimensional shape calculation unit 51b then acquires the three-dimensional coordinates of the positions of the corners and sides of the loading platform 13 from the three-dimensional information (e.g., point cloud data). As a result, the three-dimensional shape calculation unit 51b determines the three-dimensional coordinates of the corners and sides of the loading platform 13 and determines the three-dimensional shape of the loading platform 13.

[0039] [Example B1b] The dimension information calculation unit 51 may calculate the three-dimensional shape of the loading platform 13 (see FIG. 3) based on three-dimensional information without using two-dimensional images. Specifically, for example, the three-dimensional shape calculation unit 51b identifies (estimates, calculates) the three-dimensional position of each surface of the loading platform 13 by clustering the three-dimensional information (e.g., point cloud data) of the loading platform 13 detected by the three-dimensional information detection unit 33. As a result, the three-dimensional shape calculation unit 51b determines the three-dimensional shape of the loading platform 13. In this example, the loading platform detection unit 30 does not need to include the two-dimensional image detection unit 31, and the dimension information calculation unit 51 does not need to include the two-dimensional shape calculation unit 51a.

[0040] [Example B2] The dimension information calculation unit 51 may calculate the dimensions and capacity of the loading platform 13 (see [Example A1], [Example A2], and [Example A3] above) based on the information on the three-dimensional shape of the loading platform 13 (see Figure 3) calculated by the three-dimensional shape calculation unit 51b.

[0041] [Example B3] The dimension information calculation unit 51 may calculate the dimensions and capacity (see [Example A1], [Example A2], and [Example A3] above) of the loading platform 13 (see FIG. 3) without calculating the three-dimensional shape of the loading platform 13. In this example, the dimension information calculation unit 51 does not need to include the two-dimensional shape calculation unit 51a and the three-dimensional shape calculation unit 51b.

[0042] [Example B3a] For example, the loading platform detection unit 30 shown in FIG. 1 detects the distances from the loading platform detection unit 30 to two opposing surfaces of the loading platform 13. Then, the dimension information calculation unit 51 (see FIG. 4) may calculate the dimension of the loading platform 13 in the direction in which these two surfaces face each other based on the detected distances. Specifically, for example, the distance in the vehicle fore-and-aft direction X from the loading platform detection unit 30 to the rear gate plate surface 13b and the distance in the vehicle fore-and-aft direction X from the loading platform detection unit 30 to the gate surface 13d are detected. Then, based on these distances, the dimension information calculation unit 51 (see FIG. 4) may calculate the distance in the vehicle fore-and-aft direction X between the gate surface 13d and the rear gate plate surface 13b, and calculate the dimension Lx of the loading platform 13 in the vehicle fore-and-aft direction X (see Example A1a above). Similarly, the dimension information calculation unit 51 may calculate the dimension Ly of the loading platform 13 in the vehicle width direction Y (see Example A1b above) from the distance between the two side gate panels 13c shown in FIG. 2. In this example, the loading platform detection unit 30 may be a device that detects one-dimensional or two-dimensional distance information. In this example, the loading platform detection unit 30 may not include the two-dimensional image detection unit 31 and the three-dimensional information detection unit 33 (this also applies to Example B3b below). In this example, the dimension information calculation unit 51 may not include the two-dimensional shape calculation unit 51a and the three-dimensional shape calculation unit 51b (this also applies to Example B3b below).

[0043] [Example B3b] For example, the loading platform detection unit 30 shown in FIG. 1 detects the dimension of a part of the surface of the loading platform 13 in a specific direction. Then, the dimension information calculation unit 51 (see FIG. 4) may use the dimension detected by the loading platform detection unit 30 as part or all of the dimensional information of the loading platform 13. Specifically, for example, the loading platform detection unit 30 detects the height (dimension Lzd) of the torii surface 13d. Then, the dimension information calculation unit 51 (see FIG. 4) may use the dimension Lzd as part or all of the dimensional information. In this example, the loading platform detection unit 30 may be, for example, a device that detects two-dimensional distance information.

[0044] The storage unit 53 (see FIG. 4) stores the correspondence between the dimensional information of the loading platform 13 and the type of the vehicle 10. The storage unit 53 stores this correspondence in advance (before the type of the vehicle 10 is determined).

[0045] [Example C1] For example, the correspondence relationship stored in the memory unit 53 (see FIG. 4) may be the relationship between the condition (e.g., a numerical range) of the dimensions of part or all of the cargo bed 13 (see [Example A1] and [Example A2] above) and the type of vehicle 10. Specifically, for example, the correspondence relationship stored in the memory unit 53 may be the relationship between the condition (e.g., a numerical range) of the dimension Lx of the cargo bed 13 and the type of vehicle 10.

[0046] [Example C2] For example, the correspondence relationship stored in the memory unit 53 (see Figure 4) may be the relationship between the condition (e.g., a numerical range) of the capacity of the loading platform 13 (see [Example A3] above) and the type of vehicle 10 (see relationship R1-R2 shown in Figure 4). [Example C3] For example, the correspondence relationship stored in the memory unit 53 may be the relationship between the condition of the information on the three-dimensional shape of the loading platform 13 (e.g., the dimensional ratio and angle of each surface) and the type of vehicle 10.

[0047] This storage unit 53 (see FIG. 4) may store information other than the correspondence between the dimensional information of the loading platform 13 and the type of vehicle 10. For example, the storage unit 53 may store specification information (known information) for each model of the vehicle 10. This specification information may include information on the dimensions of the loading platform 13, or may include information on the shape of the loading platform 13.

[0048] This storage unit 53 (see FIG. 4) may store information regarding whether or not the type of vehicle 10 is a type that is scheduled to enter the work site where the work machine 20 will be working. The storage unit 53 may store correspondence relationships regarding the types of vehicle 10 that are scheduled to enter the work site where the work machine 20 will be working, and may not need to store correspondence relationships regarding the types of vehicle 10 that are not scheduled to enter the work site.

[0049] The discrimination unit 55 discriminates the type of the vehicle 10 shown in Fig. 1 based on the dimension information calculated by the dimension information calculation unit 51 shown in Fig. 4 and the correspondence stored in the storage unit 53. Specific examples of the "type" of the vehicle 10 discriminated by the discrimination unit 55 (see Fig. 4) are as follows.

[0050] [Example D1] The type determined by the determination unit 55 (see FIG. 4) may be a classification based on the size of the loading platform 13. [Example D1a] The type may be a classification (class) based on the maximum load capacity on the loading platform 13. For example, the type may be a classification including "4t," "8t," and "10t" (see relationship R1 shown in FIG. 4). Specifically, "4t" is a classification to which vehicles 10 with a maximum load capacity on the loading platform 13 of approximately 4t belong; for example, if the vehicle 10 is a dump truck, it is a "4t dump truck." [Example D1b] The type may be a classification based on the capacity of the loading platform 13. [Example D1c] Information indicating whether the class is one in which the work machine 20 is scheduled to enter the work site where work is to be performed may be set in the memory unit 53 (see FIG. 4). In this case, the determination unit 55 (see FIG. 4) may determine the type only from the classes in which the work machine is scheduled to enter the work site. The candidate categories to be discriminated by the discriminator 55 may be narrowed down to categories that are scheduled to enter the work site.

[0051] Typically, when the classification based on the size of the loading platform 13 (specifically, for example, classes of "4t," "8t," and "10t") differs, the dimension Lx of the loading platform 13 in the vehicle's fore-and-aft direction X is more likely to differ than the dimensions of the loading platform 13 in other directions (for example, dimension Ly (see FIG. 2)). Therefore, when the classification determined by the discrimination unit 55 (see FIG. 4) is a classification based on the size of the loading platform 13, it is preferable that the dimension information includes the dimension Lx of the loading platform 13 in the vehicle's fore-and-aft direction X. For example, when the classification determined by the discrimination unit 55 is a classification based on the size of the loading platform 13, the dimension information may be only the dimension Lx of the loading platform 13 in the vehicle's fore-and-aft direction X.

[0052] [Example of Use 1] The controller 50 (see FIG. 4) may use the classification results based on the size of the loading platform 13 to determine the appropriate loading amount of transported objects onto the loading platform 13. The controller 50 may use the classification results based on the size of the loading platform 13 to provide guidance on the loading amount when loading the loading operation from the work machine 20 onto the loading platform 13.

[0053] [Example D2] The type determined by the determination unit 55 (see Figure 4) may be the model of the vehicle 10. The "model of the vehicle 10" is the type to which vehicles 10 manufactured with the same (or approximately the same) dimensions and shape belong. [Example D2a] Information indicating whether the work machine 20 is a model that is scheduled to enter the work site where work is to be performed may be set in the memory unit 53. In this case, the determination unit 55 may determine the model only from models that are scheduled to enter the work site. The candidate models determined by the determination unit 55 may be narrowed down to models that are scheduled to enter the work site.

[0054] [Usage example 2] The controller 50 (see Figure 4) may read the model specification information (specification information of the loading platform 13) stored in the memory unit 53 (see Figure 4) based on the model identification result of the vehicle 10. [Usage example 2a] The controller 50 (see Figure 4) may use the specification information of the loading platform 13 to determine the appropriate loading amount of objects to be transported onto the loading platform 13. [Usage example 2b] The controller 50 may use the specification information of the loading platform 13 for guidance on the loading amount of objects to be transported from the work machine 20 to the loading platform 13. [Usage example 2c] The controller 50 may use the specification information of the loading platform 13 to determine the precise position of the loading platform 13. [Usage example 2c-1] In this case, the controller 50 may use the information on the precise position of the loading platform 13 for automatic operation of loading objects to be transported from the work machine 20 onto the loading platform 13. For example, the controller 50 may use the information on the detailed position of the loading platform 13 to identify the loading position (e.g., unloading position) of the object to be transported from the work machine 20 to the loading platform 13. [Usage example 2c-2] The controller 50 may use the information on the detailed position of the loading platform 13 to assist in the loading operation of the object to be transported from the work machine 20 to the loading platform 13. [Usage example 2c-3] The controller 50 may use the information on the detailed position of the loading platform 13 for collision prevention control between the loading platform 13 and the work machine 20.

[0055] The determination unit 55 (see FIG. 4) does not need to determine only one type, but may narrow down the type candidates stored in the storage unit 53 (see FIG. 4) to a plurality of types.

[0056] This discrimination unit 55 (see FIG. 4) may discriminate the type based on all the information included in the dimension information, or may discriminate the type based on only a portion of the information included in the dimension information (information necessary for discriminating the type).

[0057] The detection feasibility determination unit 57 (see FIG. 4) determines whether or not it is possible for the loading platform 13 to be detected by the loading platform detection unit 30. As a result, the detection feasibility determination unit 57 determines whether or not the dimension information calculation unit 51 (see FIG. 4) can properly calculate the dimensional information of the loading platform 13, and determines whether or not the discrimination unit 55 (see FIG. 4) can properly discriminate the type of vehicle 10. The information required for the determination by the detection feasibility determination unit 57 (see FIG. 4) differs depending on whether or not the loading platform detection unit 30 is attached to the work machine 20.

[0058] [Example E1] When the platform detection unit 30 is attached to the work machine 20, the detection feasibility determination unit 57 (see Figure 4) makes a determination as follows. The detection feasibility determination unit 57 determines whether the attitude of the work machine 20 is a "platform detectable attitude." A platform detectable attitude is an attitude of the work machine 20 in which the platform detection unit 30 can detect the platform 13. More specifically, a platform detectable attitude is an attitude of the work machine 20 in which the platform detection unit 30 can detect the information necessary for the dimension information calculation unit 51 to properly calculate the dimensional information of the platform 13. The platform detectable attitude is set in the controller 50 (see Figure 4). Specifically, for example, a platform detectable attitude is an attitude in which the proportion of the attachment 25 reflected in the detection area (angle of view) of the platform detection unit 30 shown in Figure 3 is equal to or less than a predetermined value. For example, the bed detectable posture may be a posture in which the attachment 25 is not reflected in the detection area of ​​the bed detection unit 30 (the above-mentioned "predetermined value" may be zero). For example, a posture in which the proportion of the attachment 25 reflected in the detection area of ​​the bed detection unit 30 exceeds a predetermined value does not correspond to a bed detectable posture.

[0059] In this [Example E1], if the posture detected by the posture detection unit 41 (see FIG. 4) is a posture in which a load platform can be detected (YES in step S1 in FIG. 5), the dimension information calculation unit 51 (see FIG. 4) calculates the dimension information of the load platform 13 (step S2 in FIG. 5). In this case, the discrimination unit 55 (see FIG. 4) discriminates the type of vehicle 10 (step S3 in FIG. 5). On the other hand, if the posture detected by the posture detection unit 41 (see FIG. 4) is not a posture in which a load platform can be detected (NO in step S1 in FIG. 5), the dimension information calculation unit 51 does not calculate the dimension information of the load platform 13. In this case, the discrimination unit 55 does not discriminate the type of vehicle 10.

[0060] [Example E2] When the platform detection unit 30 is located outside the work machine 20 (see the platform detection unit 30 indicated by the two-dot chain line in Figure 1), the detection feasibility determination unit 57 (see Figure 4) makes a determination as follows. The detection feasibility determination unit 57 determines whether or not the "platform detectable condition" is met. The platform detectable condition is the posture and position of the work machine 20 that enables the platform detection unit 30 to detect the platform 13. More specifically, the platform detectable posture is the posture and position of the work machine 20 that enables the platform detection unit 30 to detect information necessary for the dimension information calculation unit 51 (see Figure 4) to properly calculate the dimension information of the platform 13. The platform detectable condition is set in the controller 50 (see Figure 4). Specifically, for example, the platform detectable condition is the posture and position of the work machine 20 that enables the proportion of the work machine 20 that is reflected in the detection area of ​​the platform detection unit 30 to be equal to or less than a predetermined value. For example, the bed detectable condition may be an attitude and position of the work machine 20 such that the work machine 20 is not reflected in the detection area of ​​the bed detection unit 30 (the above-mentioned "predetermined value" may be zero). For example, an attitude and position of the work machine 20 such that the amount of the work machine 20 reflected in the detection area of ​​the bed detection unit 30 exceeds the predetermined value does not satisfy the bed detectable condition.

[0061] In this [Example E2], if the attitude detected by the attitude detection unit 41 (see FIG. 4) and the position detected by the position detection unit 43 (see FIG. 4) satisfy the loading platform detectable condition, the dimension information calculation unit 51 (see FIG. 4) calculates the dimension information of the loading platform 13. In this case, the discrimination unit 55 (see FIG. 4) discriminates the type of vehicle 10. On the other hand, if the attitude detected by the attitude detection unit 41 (see FIG. 4) and the position detected by the position detection unit 43 (see FIG. 4) do not satisfy the loading platform detectable condition, the dimension information calculation unit 51 (see FIG. 4) does not calculate the dimension information of the loading platform 13. In this case, the discrimination unit 55 (see FIG. 4) does not discriminate the type of vehicle 10.

[0062] (Effects of the first invention) The effects of the vehicle discrimination system 1 shown in Fig. 1 are as follows: The vehicle discrimination system 1 discriminates the type of vehicle 10 having a cargo bed 13. As shown in Fig. 4, the vehicle discrimination system 1 includes a cargo bed detection unit 30, a dimension information calculation unit 51, a storage unit 53, and a discrimination unit 55.

[0063] [Configuration 1] The loading platform detection unit 30 detects information including the distance to the loading platform 13 (see FIG. 1) (the distance from the loading platform detection unit 30 to the loading platform 13). The dimension information calculation unit 51 calculates the dimension information of the loading platform 13 based on the distance detected by the loading platform detection unit 30. The memory unit 53 stores the correspondence between the dimension information of the loading platform 13 and the type of vehicle 10 (see FIG. 1). The discrimination unit 55 discriminates the type of vehicle 10 based on the dimension information calculated by the dimension information calculation unit 51 and the correspondence stored in the memory unit 53.

[0064] In the above [Configuration 1], dimensional information of the loading platform 13 is calculated based on the distance from the loading platform detection unit 30 shown in FIG. 1 to the loading platform 13. Then, the type of the vehicle 10 is determined based on this dimensional information. Therefore, the type of the vehicle 10 can be determined without providing a mark on the vehicle 10 for determining the type of the vehicle 10. As a result, the effort involved in providing a mark or the like on the vehicle 10 can be saved. In addition, the effort involved in setting a mark according to the type of the vehicle 10 (for example, setting the light emission pattern or color of the mark) can be saved.

[0065] (Effects of the second invention) [Configuration 2] The "dimensional information" (see [Configuration 1] above) includes the dimension Lx of the loading platform 13 in the longitudinal direction of the loading platform 13 (the vehicle front-rear direction X).

[0066] The above-mentioned [Configuration 2] provides the following effect. Normally, compared to the dimension Ly (see FIG. 2) of the loading platform 13 in the vehicle width direction Y and the dimensions Lzb and Lzd of the loading platform 13 in the vehicle up-down direction Z, the dimension Lx of the loading platform 13 in the vehicle front-rear direction X varies greatly depending on the type of vehicle 10. In the above-mentioned [Configuration 2], the dimension Lx of the loading platform 13 in the vehicle front-rear direction X is included in the dimension information, so the vehicle discrimination system 1 can appropriately discriminate the type of vehicle 10.

[0067] (Effect of the third invention) [Configuration 3] The "dimensional information" (see [Configuration 1] above) includes information on the three-dimensional shape of the loading platform 13.

[0068] The above [Configuration 3] allows the amount of information in the dimension information to be increased compared to when the dimension information does not include information on the three-dimensional shape of the loading platform 13 (for example, when the dimension information includes only the dimensions of the loading platform 13 in a specific direction). As a result, the vehicle discrimination system 1 can accurately discriminate the type of vehicle 10.

[0069] (Effect of the fourth invention) The loading platform detection unit 30 includes a two-dimensional image detection unit 31 and a three-dimensional information detection unit 33. The two-dimensional image detection unit 31 detects a two-dimensional image of the loading platform 13. The three-dimensional information detection unit 33 detects three-dimensional information of the loading platform 13. As shown in FIG. 4, the dimension information calculation unit 51 includes a two-dimensional shape calculation unit 51a and a three-dimensional shape calculation unit 51b.

[0070] [Configuration 4] The two-dimensional shape calculation unit 51a calculates the two-dimensional shape of the loading platform 13 (see FIG. 3) based on the two-dimensional image detected by the two-dimensional image detection unit 31. The three-dimensional shape calculation unit 51b calculates the three-dimensional shape of the loading platform 13 based on the two-dimensional shape of the loading platform 13 calculated by the two-dimensional shape calculation unit 51a and the three-dimensional information of the loading platform 13 detected by the three-dimensional information detection unit 33.

[0071] 1 is calculated by combining the two-dimensional image and the three-dimensional information, the three-dimensional shape can be calculated more accurately than when the three-dimensional shape is calculated from the three-dimensional information alone. As a result, the vehicle discrimination system 1 can accurately discriminate the type of the vehicle 10.

[0072] (Effect of the fifth invention) [Configuration 5] "Type of vehicle 10" (see [Configuration 1] above) is a classification based on the size of the loading platform 13.

[0073] According to the above [Configuration 5], the result of determining the type of vehicle 10 can be used for functions that require information on the size of the loading platform 13. Specifically, for example, the result of determining the type of vehicle 10 may be used to determine the appropriate loading amount of transported objects onto the loading platform 13, to provide guidance on the loading amount of transported objects onto the loading platform 13, and the like.

[0074] (Effect of the sixth aspect of the invention) [Configuration 6] "Type of vehicle 10" (see [Configuration 1] above) is the model of vehicle 10.

[0075] According to the above [Configuration 6], the result of determining the type of vehicle 10 can be used for functions that require information on the model of vehicle 10. Specifically, for example, the result of determining the type of vehicle 10 may be used to read specification information corresponding to the determined model of vehicle 10. When the specification information of vehicle 10 is read, the specification information may be used to accurately determine the position of the loading platform 13, automatically drive or assist in loading work onto the loading platform 13, control to prevent collisions between the loading platform 13 and the work machine 20, etc.

[0076] (Effect of the seventh invention) The vehicle discrimination system 1 includes an attitude detection unit 41 (see FIG. 4). The attitude detection unit 41 detects the attitude of the work machine 20 that performs work on the vehicle 10. The loading platform detection unit 30 is attached to the work machine 20.

[0077] [Configuration 7] The discrimination unit 55 (see FIG. 4) discriminates the type of vehicle 10 when the attitude detected by the attitude detection unit 41 (see FIG. 4) is a bed-detectable attitude. The bed-detectable attitude is an attitude that is set as an attitude that allows detection of the bed 13 by the bed detection unit 30. The discrimination unit 55 (see FIG. 4) does not discriminate the type of vehicle 10 when the attitude detected by the attitude detection unit 41 (see FIG. 4) is not a bed-detectable attitude.

[0078] According to the above [Configuration 7], the type of the vehicle 10 can be determined in a state where the loading platform 13 is properly detected by the loading platform detection unit 30. Therefore, the vehicle discrimination system 1 can accurately discriminate the type of the vehicle 10.

[0079] (Effect of the eighth invention) The vehicle discrimination system 1 includes an attitude detection unit 41 (see Figure 4) and a position detection unit 43 (see Figure 4). The attitude detection unit 41 (see Figure 4) detects the attitude of the work machine 20 performing work on the vehicle 10. The position detection unit 43 (see Figure 4) detects the position of the work machine 20 at the work site where the work machine 20 is located. The loading platform detection unit 30 is located outside the work machine 20.

[0080] [Configuration 8] The discrimination unit 55 shown in Fig. 4 discriminates the type of vehicle 10 when the attitude detected by the attitude detection unit 41 and the position detected by the position detection unit 43 satisfy the bed detection possible condition. The bed detection possible condition is a condition set as a condition under which the bed 13 can be detected by the bed detection unit 30 shown in Fig. 1. The discrimination unit 55 shown in Fig. 4 does not discriminate the type of vehicle 10 shown in Fig. 1 when the attitude detected by the attitude detection unit 41 and the position detected by the position detection unit 43 do not satisfy the bed detection possible condition.

[0081] According to the above [Configuration 8], the type of the vehicle 10 can be determined in a state where the loading platform 13 is properly detected by the loading platform detection unit 30. Therefore, the vehicle discrimination system 1 can accurately discriminate the type of the vehicle 10.

[0082] (Variation) The above embodiment may be modified in various ways. For example, the connections between the components of the above embodiment shown in FIG. 4 may be changed. For example, values, ranges, etc. (e.g., the correspondence conditions stored in the memory unit 53) may be constant, may be changed manually, or may be changed automatically in response to certain conditions. For example, the number of components may be changed, or some of the components may not be provided. For example, the components may be fixed or connected directly or indirectly. For example, what has been described as multiple different members or parts may be combined into a single member or part. For example, what has been described as a single member or part may be provided as multiple different members or parts. Specifically, for example, the components of the controller 50 (the dimension information calculation unit 51, the memory unit 53, and the determination unit 55) may be located in one location or may be distributed across multiple locations. For example, the components may have only some of their respective features (functions, locations, shapes, manufacturing methods, operations, etc.). [Explanation of symbols]

[0083] 1. Vehicle identification system 10 vehicles 13 Cargo bed 20 Work Machinery 30 Loading platform detector 31 Two-dimensional image detection unit 33 Three-dimensional information detection unit 41 Attitude detection unit 43 Position detection unit 51 Dimension information calculation unit 51a Two-dimensional shape calculation section 51b 3D shape calculation section 53 Memory section 55 Discrimination part

Claims

1. A vehicle discrimination system for discriminating vehicles having a cargo bed, a loading platform detection unit that detects information including the distance to the loading platform; an attitude detection unit that detects the attitude of a work machine that performs work on the vehicle; a determination unit that determines whether or not the loading platform can be detected by the loading platform detection unit based on the posture detected by the posture detection unit; Equipped with Vehicle identification system.

2. The vehicle discrimination system according to claim 1, a dimension information calculation unit that calculates dimension information of the loading platform based on the distance detected by the loading platform detection unit; a storage unit that stores a correspondence relationship between the dimension information of the loading platform and the type of the vehicle; Equipped with When the determination unit determines that the loading platform can be detected by the loading platform detection unit, the determination unit determines the type of the vehicle based on the dimension information calculated by the dimension information calculation unit and the correspondence relationship stored in the storage unit, the discrimination unit does not discriminate the type of the vehicle when it is not determined that the loading platform can be detected by the loading platform detection unit; Vehicle identification system.

3. The vehicle discrimination system according to claim 2, The dimension information includes a dimension of the loading platform in a longitudinal direction of the loading platform. Vehicle identification system.

4. The vehicle discrimination system according to claim 2 or 3, The dimension information includes information on the three-dimensional shape of the loading platform. Vehicle identification system.

5. The vehicle discrimination system according to claim 4, The loading platform detection unit a two-dimensional image detection unit that detects a two-dimensional image of the loading platform; a three-dimensional information detection unit that detects three-dimensional information of the loading platform; Equipped with The dimension information calculation unit a two-dimensional shape calculation unit that calculates a two-dimensional shape of the loading platform based on the two-dimensional image detected by the two-dimensional image detection unit; a three-dimensional shape calculation unit that calculates the three-dimensional shape of the loading platform based on the two-dimensional shape of the loading platform calculated by the two-dimensional shape calculation unit and the three-dimensional information of the loading platform detected by the three-dimensional information detection unit; Equipped with Vehicle identification system.

6. The vehicle discrimination system according to any one of claims 2 to 5, The vehicle type is a classification based on the size of the loading platform. Vehicle identification system.

7. The vehicle discrimination system according to any one of claims 2 to 6, The type of vehicle is the model of the vehicle. Vehicle identification system.

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