Device

Abstract

To provide a technique capable of increasing the possibility that work on a moving body is appropriately performed.SOLUTION: And a generation unit configured to use the acquired environmental information to generate value data including at least one of a braking control value that is a control value related to braking of the moving body, a braking correction value that is a correction value for correcting the braking control value, a work control value that is a control value related to work for controlling a work apparatus that performs work on the moving body, a work setting value that is a setting value related to the work for the work apparatus, and a work correction value that is a correction value for correcting the work control value.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present disclosure relates to an apparatus. [Background technology]

[0002] Patent Document 1 discloses a technology for running a vehicle autonomously or by remote control during the vehicle manufacturing process. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Special Publication No. 2017-538619 Summary of the Invention [Problem to be solved by the invention]

[0004] A technology for transporting a mobile object, such as a vehicle, using unmanned operation of the mobile object is known at a work site where work is performed on the mobile object. In such a work site, it is sometimes desirable to stop the mobile object at a predetermined position in order to properly perform work on the mobile object. However, in an environment where the actual stopping position of the mobile object may differ from the expected stopping position, it may be impossible to properly stop the mobile object at the predetermined position, and work may not be performed properly. [Means for solving the problem]

[0005] The present disclosure can be realized in the following forms.

[0006] (1) According to one aspect of the present disclosure, there is provided an apparatus including: an acquisition unit that acquires environmental information related to at least one of an environment around a current location of an unmanned mobile body and an environment ahead in a direction of travel of the mobile body; and a generation unit that uses the acquired environmental information to generate value data including at least one of a braking control value that is a control value related to braking of the mobile body, a braking correction value that is a correction value for correcting the braking control value, a work control value that is a control value related to the work and is a work setting value for the work equipment, and a work correction value that is a correction value for correcting the work control value. According to this embodiment, even in an environment where the actual stopping position of the moving body may deviate from the expected stopping position, the generated value data is used to control at least one of the braking of the moving body and the work performed by the work equipment, thereby increasing the likelihood that work on the moving body will be performed appropriately. (2) In the above embodiment, the environmental information may include an image of the forward environment. According to this embodiment, the value data is generated taking into account the forward environment in the traveling direction of the mobile object, thereby further increasing the likelihood that the work will be performed appropriately. (3) In the above embodiment, the generating unit may acquire from the image at least one of the following feature quantities: brightness of the image, the presence or absence of a predetermined object in the image, and the proportion of the object in the image, and generate the value data using the acquired feature quantity. According to this embodiment, the image as environmental information can be used more effectively to generate more appropriate value data. (4) In the above embodiment, the environmental information may include three-dimensional point cloud information of the forward environment. According to this embodiment, the value data is generated taking into account the environment forward in the traveling direction of the mobile object, thereby further increasing the likelihood that the work will be performed appropriately. (5) In the above embodiment, the generating unit may acquire at least one feature value from the three-dimensional point cloud information, including the number of points, the density of the points, and the detection distance of the points, and generate the value data using the acquired feature value. According to this embodiment, the three-dimensional point cloud information as environmental information can be used more effectively to generate more appropriate value data. In addition to the above-described device form, the present disclosure can be realized in the form of, for example, a system, a server, a mobile object control method, a program for realizing the mobile object control method, a non-transitory recording medium on which the program is recorded, a program product, etc. Note that the program product may be provided as a recording medium on which the program is recorded, or may be provided as a program product that can be distributed via a network, for example. [Brief explanation of the drawings]

[0007] [Figure 1] FIG. 1 is a conceptual diagram showing the configuration of a system according to a first embodiment. [Figure 2] FIG. 1 is a block diagram showing the configuration of a system according to a first embodiment. [Figure 3] 3 is a flowchart showing a processing procedure for vehicle travel control in the first embodiment. [Figure 4] 4 is a flowchart of a stop process in the first embodiment. [Figure 5] FIG. 4 is a diagram illustrating an example of a stop process according to the first embodiment. [Figure 6] FIG. 10 is a block diagram showing the configuration of a system according to a second embodiment. [Figure 7] 10 is a flowchart of a stop process according to the second embodiment. [Figure 8] FIG. 10 is a diagram illustrating an example of a stop process according to the second embodiment. [Figure 9] FIG. 10 is a block diagram showing the configuration of a system according to a third embodiment. [Figure 10] 10 is a flowchart of a stop process according to the third embodiment. [Figure 11] FIG. 11 is a diagram illustrating an example of a stop process according to the third embodiment. [Figure 12] FIG. 10 is a block diagram showing the configuration of a system according to a fourth embodiment. [Figure 13] 10 is a flowchart of a stop process according to the fourth embodiment. [Figure 14] FIG. 13 is a diagram illustrating an example of a stop process according to the fourth embodiment. [Figure 15] FIG. 13 is a block diagram showing the configuration of a system according to a fifth embodiment. [Figure 16] 13 is a flowchart of a stop process according to the fifth embodiment. [Figure 17] FIG. 13 is a diagram illustrating an example of a stop process according to the fifth embodiment. [Figure 18] FIG. 13 is a block diagram of a system according to a sixth embodiment. [Figure 19] 13 is a flowchart showing a processing procedure for vehicle travel control in a sixth embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0008] A. First embodiment: 1 is a conceptual diagram showing the configuration of a system 50 in the first embodiment. The system 50 includes one or more vehicles 100 as moving bodies, a server 200, one or more external sensors 300, and one or more work devices 400. The server 200 in the first embodiment corresponds to the "device" in this disclosure.

[0009] In this disclosure, a "mobile body" refers to an object that can move, such as a vehicle or an electric vertical take-off and landing aircraft (a so-called flying car). A vehicle may be a vehicle that runs on wheels or a vehicle that runs on tracks, such as a passenger car, truck, bus, motorcycle, automobile, tank, or construction vehicle. Vehicles include electric vehicles (BEVs: Battery Electric Vehicles), gasoline-powered vehicles, hybrid vehicles, and fuel cell vehicles. When a mobile body is something other than a vehicle, the terms "vehicle" and "car" in this disclosure may be appropriately replaced with "mobile body," and the term "traveling" may be appropriately replaced with "moving."

[0010] The vehicle 100 is configured to be capable of traveling in an unmanned manner. "Unmanned driving" refers to driving without the driver's control. Driving operation refers to operations related to at least one of "running," "turning," and "stopping" of the vehicle 100. Unmanned driving is achieved by automatic or manual remote control using a device located outside the vehicle 100, or by autonomous control of the vehicle 100. A vehicle 100 traveling in an unmanned manner may have a driver on board who does not operate the vehicle. A driver who does not operate the vehicle may, for example, simply be seated in the vehicle 100, or a person who is riding in the vehicle 100 and performing work other than driving operations, such as assembly, inspection, or operating switches. Driving in which a driver controls the vehicle is sometimes called "manned driving."

[0011] In this specification, "remote control" includes "full remote control" in which all of the operations of vehicle 100 are completely determined from outside vehicle 100, and "partial remote control" in which some of the operations of vehicle 100 are determined from outside vehicle 100. Furthermore, "autonomous control" includes "full autonomous control" in which vehicle 100 autonomously controls its own operations without receiving any information from devices external to vehicle 100, and "partial autonomous control" in which vehicle 100 autonomously controls its own operations using information received from devices external to vehicle 100.

[0012] In this embodiment, the system 50 is used in a factory FC where the vehicle 100 is manufactured. The reference coordinate system of the factory FC is a global coordinate system GC, and any position within the factory FC can be expressed by X, Y, and Z coordinates in the global coordinate system GC. The factory FC corresponds to a work area where work is performed on the vehicle 100. The work area includes one or more work locations. Various types of work are performed at each work location. The work includes, for example, assembling parts into the vehicle 100, and inspecting, transporting, repairing, and shipping the vehicle 100. The transport and shipping of the vehicle 100 may be performed, for example, by unmanned operation or using a transport device such as a conveyor or an automated guided vehicle. The work location may be, for example, a parking area for transport or shipping. Each work may be performed by a work device 400 or by a worker. In order for work at the work location to be performed appropriately, it is preferable that the vehicle 100 be stopped appropriately at a target stopping position at the work location. The target stopping position may be various stopping positions, such as a stopping position on a conveyor provided in a transport device, a work position by the work equipment 400, a work position by a worker, a parking position in a parking lot, etc. The stopping position on the conveyor may be, for example, the position of an uneven portion provided on the conveyor to support the wheels of the vehicle 100.

[0013] The factory FC includes a first location PL1, a second location PL2, and a third location PL3. The first location PL1 to the third location PL3 each correspond to a work location. The first location PL1 is a work location for assembling the vehicle 100. The second location PL2 and the third location PL3 are work locations for inspecting the vehicle 100. The first location PL1 to the third location PL3 are each connected by a track TR along which the vehicle 100 can travel. More specifically, the first location PL1 and the second location PL2 are connected by a track TR1. The second location PL2 and the third location PL3 are connected by a track TR2. A plurality of external sensors 300 are installed along the track TR in the factory FC. In this embodiment, at least some of the plurality of external sensors 300 are disposed near the second location PL2. The positions of the external sensors 300 in the factory FC are adjusted in advance. The vehicle 100 moves unmanned from the first location PL1 to the third location PL3 along the track TR. In this embodiment, the vehicle 100 travels unmanned not only on the track TR but also within the second location PL2. The vehicle 100 travels within the second location PL2 from the track TR1 side to the track TR2 side. In other embodiments, the vehicle 100 may travel unmanned within the first location PL1 or the third location PL3.

[0014] 2 is a block diagram showing the configuration of a system 50 in the first embodiment. The vehicle 100 includes a vehicle control device 110 for controlling each part of the vehicle 100, an actuator group 120 including one or more actuators that are driven under the control of the vehicle control device 110, and a communication device 130 for communicating via wireless communication with an external device such as a server 200. The actuator group 120 includes an actuator for a drive device for accelerating the vehicle 100, an actuator for a steering device for changing the traveling direction of the vehicle 100, and an actuator for a braking device for decelerating the vehicle 100.

[0015] The vehicle control device 110 is configured by a computer including a processor 111, a memory 112, an input / output interface 113, and an internal bus 114. The processor 111, the memory 112, and the input / output interface 113 are connected via the internal bus 114 to enable bidirectional communication. The input / output interface 113 is connected to an actuator group 120 and a communication device 130. The processor 111 executes a program PG1 stored in the memory 112 to realize various functions including a function as a vehicle control unit 115.

[0016] The vehicle control unit 115 controls the actuator group 120 to cause the vehicle 100 to run. The vehicle control unit 115 controls the actuator group 120 using a running control signal received from the server 200 to cause the vehicle 100 to run. The running control signal is a control signal for causing the vehicle 100 to run. In this embodiment, the running control signal includes the acceleration and steering angle of the vehicle 100 as parameters. In other embodiments, the running control signal may include the speed of the vehicle 100 as a parameter instead of or in addition to the acceleration of the vehicle 100.

[0017] The external sensor 300 is a sensor located outside the vehicle 100. The external sensor 300 in this embodiment is configured to be able to capture information about the vehicle 100 and the external environment of the vehicle 100 from outside the vehicle 100. The external sensor 300 includes a control device 310, a sensor unit 320, and a communication device 330. The control device 310 controls each unit of the external sensor 300. In particular, the control device 310 controls the sensor unit 320 to capture information about the vehicle 100 and the external environment. The communication device 330 can communicate with other devices such as the server 200 via wired communication or wireless communication.

[0018] The control device 310 is configured by a computer including a processor 311, a memory 312, an input / output interface 313, and an internal bus 314. The processor 311, the memory 312, and the input / output interface 313 are connected via the internal bus 314 to enable bidirectional communication. A sensor unit 320 and a communication device 330 are connected to the input / output interface 313. The processor 311 executes a program PG3 pre-stored in the memory 312 to realize various functions, such as a function to control the sensor unit 320. The communication device 330 can communicate with other devices, such as the server 200, via wired or wireless communication.

[0019] In this embodiment, the external sensor 300 is configured as a ranging device. The ranging device serving as the external sensor 300 measures the vehicle 100 and the external environment and outputs 3D point cloud data as a detection result. A camera or a LiDAR (Light Detection and Ranging) device can be used as the ranging device. A LiDAR device is particularly preferable because it can obtain high-precision 3D point cloud data. In this embodiment, the external sensor 300 is configured as a LiDAR device. The sensor unit 320 has an optical system for emitting and receiving laser light for ranging. The optical system of the sensor unit 320 emits and receives, for example, a pulsed laser in the near-infrared region. In this embodiment, the position of each external sensor 300 is fixed, and the relative relationship between the global coordinate system GC and the device coordinate system of each external sensor 300 is known. A coordinate transformation matrix for mutually converting coordinate values ​​in the global coordinate system GC and coordinate values ​​in the device coordinate system of each external sensor 300 is stored in advance in the server 200.

[0020] The server 200 is configured as a computer including a processor 201, a memory 202, an input / output interface 203, and an internal bus 204. The processor 201, the memory 202, and the input / output interface 203 are connected via the internal bus 204 to enable bidirectional communication. A communication device 205 is connected to the input / output interface 203 for communicating with various devices external to the server 200. The communication device 205 can communicate with the vehicle 100 via wireless communication and can communicate with each external sensor 300 via wired or wireless communication. The processor 201 executes a program PG2 stored in the memory 202 to realize various functions, including those of an acquisition unit 210, a sensor identification unit 215, a remote control unit 220, and a notification unit 230. In addition to the program PG2, the memory 202 also stores route data RD and a database DB.

[0021] The route data RD represents the standard route traveled by the vehicle 100. In the route data RD, a standard route is defined for each type of vehicle 100. The "type of vehicle 100" here may be, for example, the vehicle model, make, body type, or exterior color of the vehicle 100, or may be an individual vehicle 100. In the route data RD, an identification number and a standard route are associated with each other so that the standard route of the vehicle 100 can be identified by referring to the route data RD using the identification number of the vehicle 100. In this embodiment, in the route data RD, a first standard route SR1 is associated with a vehicle 100A of a first vehicle type, and a second standard route SR2 is associated with a vehicle 100B of a second vehicle type. Note that the reference route, which will be described later, is determined based on standard routes such as the first standard route SR1 and the second standard route SR2.

[0022] In this embodiment, the acquisition unit 210 includes a location information acquisition unit 211 and an environment information acquisition unit 212 .

[0023] The position information acquisition unit 211 acquires the position of the vehicle 100. In this embodiment, the position information acquisition unit 211 acquires a detection result from a sensor and acquires vehicle position information using the detection result, thereby acquiring the position of the vehicle 100. Details of the vehicle position information will be described later.

[0024] The environmental information acquisition unit 212 acquires environmental information. The environmental information is information about at least one of the external environments, the environment around the current location of the vehicle 100 and the environment ahead of the vehicle 100. More specifically, the environmental information is information that captures at least one of the environment around the current location of the vehicle 100 and the environment ahead of the vehicle 100. The environment ahead of the vehicle 100 means the environment ahead in the traveling direction of the vehicle 100. The environment ahead of the vehicle 100 corresponds to the external environment around a point to which the vehicle 100 is scheduled to travel later.

[0025] In this embodiment, the environmental information is three-dimensional point cloud information of the forward environment. "Three-dimensional point cloud information of the forward environment" is information in which the forward environment is captured as a three-dimensional point cloud. Hereinafter, the three-dimensional point cloud information in which the external environment is captured is also referred to as "environment point cloud information." In particular, the three-dimensional point cloud information in which the forward environment is captured is also referred to as "forward point cloud information." The environment point cloud information is acquired using a ranging device as the external sensor 300. The environment point cloud information includes, for example, a point cloud representing the road surface of the road on which the vehicle 100 travels, a point cloud representing objects on the road surface, and the like.

[0026] The sensor identification unit 215 uses the position of the vehicle 100 acquired by the position information acquisition unit 211 to identify one or more external sensors 300 as target external sensors 300. The "target external sensors 300" are external sensors 300 used by the acquisition unit 210 to acquire environmental information. More specifically, the sensor identification unit 215 uses the vehicle position information and the route data RD to identify, as the target external sensors 300, external sensors 300 that are positionally capable of acquiring forward point cloud information. The environmental information acquisition unit 212 acquires environmental information from the target external sensors 300 identified by the sensor identification unit 215.

[0027] The remote control unit 220 uses the vehicle position information to generate a control command for driving the vehicle 100 in an unmanned driving manner. Then, the remote control unit 220 transmits the control command to the vehicle 100, thereby driving the vehicle 100 by remote control. In this embodiment, the remote control unit 220 generates the above-mentioned driving control signal as the control command.

[0028] In this embodiment, the remote control unit 220 functions as a generation unit 99. The generation unit 99 generates value data using the acquired environmental information. The value data is used to correct at least one of the stopping position of the vehicle 100 and the work position of the work equipment 400 in accordance with the environmental information.

[0029] The value data includes at least one of a braking relationship value and a work relationship value. The braking relationship value is a value related to the control of braking of the vehicle 100. The braking relationship value includes at least one of a braking control value and a braking correction value. The braking control value is a control value related to the braking of the vehicle 100. The braking control value includes, for example, at least one of an instruction value related to braking of the vehicle 100 and a value for generating an instruction value related to braking. The braking correction value is a correction value for correcting the braking control value. The work relationship value is a value related to the work performed by the work implement 400. The work relationship value includes at least one of a work control value, a work setting value, and a work correction value. The work control value is a control value for controlling the work implement 400. The work setting value is a setting value for the work implement 400. The work setting value is, for example, a setting value that specifies the initial position of the arm unit 420 or a setting value that specifies a standard trajectory for the operation of the arm unit 420. The work setting value may be a correction value for correcting a setting value. The work correction value is a correction value for correcting the work control value.

[0030] The value data in this embodiment includes a braking control value and a braking correction value as braking-related values. In addition, in this embodiment, the braking control value is a value that determines the magnitude of the braking force per unit time. More specifically, the braking control value is generated as an instruction value that instructs a negative acceleration in the driving control signal. The generation unit 99 first generates a braking correction value using environmental information. Next, the generation unit 99 generates a braking control value by correcting a braking control value that was previously generated without using environmental information using the braking correction value generated using the environmental information.

[0031] In this embodiment, the generation unit 99 acquires feature quantities of the environment point cloud information and generates value data using the acquired feature quantities. The feature quantities of the environment point cloud information preferably include at least one of the number of point clouds, the point cloud density, and the point cloud detection distance. The point cloud detection distance represents the limit value of the distance at which the point cloud can be detected. The point cloud detection distance in the environment point cloud information is represented, for example, by the distance of the point cloud with the smallest intensity among the point clouds included in the environment point cloud information. In this embodiment, the generation unit 99 acquires the number of point clouds as the feature quantity of the environment point cloud information.

[0032] In this embodiment, when the acquired number of point clouds is the first number of point clouds, the generation unit 99 generates value data so that the braking force per unit time is greater than when the acquired number of point clouds is the second number of point clouds. The second number of point clouds is a number of point clouds greater than the first number of point clouds. More specifically, the generation unit 99 generates a braking correction value by referencing a database DB based on the acquired number of point clouds, and corrects the control command using the generated braking correction value. In this embodiment, the database DB stores the number of point clouds and the braking correction value associated with the number of point clouds. Furthermore, the database DB associates a braking correction value for increasing the braking force per unit time with a smaller number of point clouds.

[0033] Here, laser light emitted from the sensor unit 320 of the external sensor 300 is more likely to be diffusely reflected in the atmosphere in bad weather, such as rain, snow, fog, or yellow sand, than in good weather. As a result, the number of point clouds, point cloud density, and detection distance in the acquired 3D point cloud information are more likely to decrease in bad weather than in good weather. Therefore, when the number of point clouds is the first point cloud number, the probability that the external environment is in bad weather is higher than when the number of point clouds is the second point cloud number. In such bad weather, foreign objects such as water droplets, snow, ice, and yellow sand may adhere to the road on which the vehicle 100 travels, deteriorating the road surface condition of the road. These foreign objects, such as water droplets, snow, ice, and yellow sand, contribute to a reduction in friction between the wheels of the vehicle 100 and the road surface, thereby hindering braking of the vehicle 100. Furthermore, in bad weather, foreign objects in the atmosphere may reduce the number of point clouds and point cloud density, thereby reducing the accuracy of the vehicle position information. In bad weather, the actual stopping position of the vehicle 100 is likely to deviate from the expected stopping position due to such deterioration of road conditions and reduction in accuracy of vehicle position information. In this case, the actual stopping position of the vehicle 100 tends to deviate further forward in the traveling direction than the expected stopping position due to foreign objects that interfere with braking of the vehicle 100.

[0034] The notification unit 230 notifies the user of various information related to the system 50. The notification unit 230 notifies the user of the information, for example, using an alarm device provided in the vehicle 100 or a notification device configured to be able to communicate with the server 200 and the vehicle 100. The notification device may be, for example, a display device for displaying visual information, a speaker for outputting audio information, or a mobile terminal owned by the user. The user may be, for example, a worker or manager in the factory FC.

[0035] The work device 400 includes a control device 410, an arm unit 420, and a communication device 430. The control device 410 controls each component of the work device 400. The arm unit 420 is configured as a vertically articulated robot arm. An end effector for performing work is attached to the tip of the arm unit 420. In this embodiment, the end effector is configured to clamp various items such as tools, parts, and inspection equipment. The communication device 430 can communicate with other devices such as the server 200 via wired or wireless communication. The arm unit 420 is not limited to a vertically articulated robot arm, and may be configured as a horizontally articulated robot arm, an orthogonal robot arm, or a parallel link robot arm, for example. The end effector may be configured to suck components rather than clamp them.

[0036] The control device 410 is configured by a computer including a processor 411, a memory 412, an input / output interface 413, and an internal bus 414. The processor 411, the memory 412, and the input / output interface 413 are connected via the internal bus 414 to enable bidirectional communication. The input / output interface 413 is connected to an arm unit 420 and a communication device 430. In this embodiment, the processor 411 executes a program PG4 stored in advance in the memory 412 to realize various functions, such as a function to control the arm unit 420.

[0037] FIG. 1 shows work equipment 400A and work equipment 400B as examples of work equipment 400. Work equipment 400A is a work equipment 400 for performing work on vehicle 100A stopped at position P1. Position P1 is located on first standard route SR1 at second location PL2. Position P1 corresponds to the target stopping position of vehicle 100A and the working position of work equipment 400A at second location PL2. Work equipment 400B is a work equipment 400 for performing work on vehicle 100B stopped at position P3. Position P3 is located on second standard route SR2 at second location PL2. Position P2 corresponds to the target stopping position of vehicle 100B and the working position of work equipment 400B at second location PL2.

[0038] 3 is a flowchart showing the processing procedure for driving control of the vehicle 100 in the first embodiment. In the processing procedure in FIG. 3, the processor 201 of the server 200 executes the program PG2 to function as the acquisition unit 210 and the remote control unit 220. In addition, the processor 111 of the vehicle 100 executes the program PG1 to function as the vehicle control unit 115.

[0039] In step S1, the processor 201 of the server 200 acquires vehicle position information using the detection results output from the external sensor 300. The vehicle position information is position information that serves as the basis for generating a driving control signal. In this embodiment, the vehicle position information includes the position and orientation of the vehicle 100 in the global coordinate system GC of the factory FC.

[0040] More specifically, in step S1, the processor 201 acquires vehicle position information by template matching using, for example, three-dimensional point cloud data as the detection result and reference point cloud data prepared in advance. As the template matching algorithm, various algorithms such as ICP (Iterative Closest Point) and NDT (Normal Distributions Transform) are used.

[0041] In step S2, the processor 201 of the server 200 determines a target position to which the vehicle 100 should next head. In this embodiment, the target position is represented by X, Y, and Z coordinates in the global coordinate system GC. A reference route, which is a route to be traveled by the vehicle 100, is stored in advance in the memory 202 of the server 200. The route is represented by nodes indicating the departure point, nodes indicating passing points, nodes indicating the destination, and links connecting the nodes. The processor 201 uses the vehicle position information and the reference route to determine a target position to which the vehicle 100 should next head. The processor 201 determines a target position on the reference route that is ahead of the current location of the vehicle 100.

[0042] In step S3, processor 201 of server 200 generates a travel control signal for causing vehicle 100 to travel toward the determined target position. Processor 201 calculates the travel speed of vehicle 100 from the change in position of vehicle 100 and compares the calculated travel speed with the target speed. When the travel speed is lower than the target speed, processor 201 determines an acceleration such that vehicle 100 accelerates, and when the travel speed is higher than the target speed, processor 201 determines an acceleration such that vehicle 100 decelerates. Furthermore, when vehicle 100 is located on the reference route, processor 201 determines a steering angle and acceleration such that vehicle 100 does not deviate from the reference route, and when vehicle 100 is not located on the reference route, in other words, when vehicle 100 has deviated from the reference route, processor 201 determines a steering angle and acceleration such that vehicle 100 returns to the reference route.

[0043] In step S4, the processor 201 of the server 200 transmits the generated driving control signal to the vehicle 100. The processor 201 repeats, at a predetermined cycle, the acquisition of vehicle position information, the determination of a target position, the generation of a driving control signal, and the transmission of the driving control signal.

[0044] In step S5, the processor 111 of the vehicle 100 receives the driving control signal transmitted from the server 200. In step S6, the processor 111 of the vehicle 100 controls the actuator group 120 using the received driving control signal, thereby causing the vehicle 100 to drive at the acceleration and steering angle indicated in the driving control signal. The processor 111 repeats receiving the driving control signal and controlling the actuator group 120 at a predetermined cycle. According to the system 50 of this embodiment, the vehicle 100 can be driven by remote control, and the vehicle 100 can be moved without using transportation equipment such as a crane or conveyor.

[0045] FIG. 4 is a flowchart of the stopping process in this embodiment. FIG. 5 is a diagram illustrating an example of the stopping process in this embodiment. The stopping process is executed during the processing procedure of FIG. 3 to stop the vehicle 100 at a target stopping position in the work site and perform work. The stopping process is initiated, for example, before the work site or when the vehicle 100 reaches a predetermined position within the work site. In this embodiment, the stopping process is executed by the processor 201. FIG. 5 illustrates an example of the stopping process executed to stop the vehicle 100A at position P1 in the second location PL2. That is, in the example of FIG. 5, the vehicle 100 that is the target of the stopping process is the vehicle 100A. In FIG. 5, the detectable ranges of each external sensor 300 are schematically illustrated by dashed lines. FIG. 5 also illustrates the traveling direction d1 of the vehicle 100A traveling along the first standard route SR1. The traveling direction d1 is a direction in which the traveling path TR2 side shown in FIG. 1 is the front and the traveling path TR1 side is the rear.

[0046] In step S100 of Fig. 4, the position information acquisition unit 211 acquires the position of the target vehicle 100. Specifically, the position information acquisition unit 211 acquires vehicle position information of the target vehicle 100. In the example of Fig. 5, the vehicle position information is acquired using the detection result DR of the external sensor 300A. The external sensor 300A is an external sensor 300 that can positionally capture the vehicle 100A at the start of step S100.

[0047] In step S105 of Fig. 4, the sensor identification unit 215 identifies the target external sensor 300 using the vehicle position information and route data RD acquired in step S100. In the example of Fig. 5, the external sensor 300B is identified as the target external sensor 300. The external sensor 300B corresponds to the first standard route SR1 and is located ahead of the vehicle 100 in the traveling direction d1 at the start of step S105. Furthermore, the external sensor 300B is an external sensor 300 that can detect the external environment behind position P1 on the first standard route SR1.

[0048] In step S105, multiple external sensors 300 may be identified as the target external sensor 300, or a single external sensor 300 may be identified as the target external sensor 300. When a single external sensor 300 is identified as the target external sensor 300, for example, among the multiple external sensors 300 located in front of the vehicle 100, an external sensor 300 closer to the vehicle 100 may be identified, or an external sensor 300 closer to position P1, which is the target stopping position, may be identified. For example, in the example of FIG. 5 , in addition to or instead of external sensor 300B, external sensor 300C closer to position P1 may be identified. More specifically, external sensor 300C is an external sensor 300 that can capture the external environment including position P1. By identifying the external sensor 300 closer to the target stopping position in this way, it is possible to more easily reflect the external environment near the target stopping position in the value data.

[0049] 4, the environmental information acquisition unit 212 acquires environmental information from the target external sensor 300 identified in step S105. In the example of FIG. 5, environmental information EB is acquired from the external sensor 300B.

[0050] 4, the generation unit 99 generates a braking correction value using the environmental information acquired in step S110. More specifically, the generation unit 99 acquires the number of point clouds as a feature amount from the forward point cloud information acquired in step S110, and generates a braking correction value by referring to the database DB based on the acquired number of point clouds.

[0051] If multiple external sensors 300 are identified in step S105, environmental information may be acquired from each of the identified external sensors 300 in step S110. In this case, in step S115, feature quantities may be acquired from each of the environmental information, and value data may be generated using the acquired feature quantities. For example, in this embodiment, the generation unit 99 may acquire the number of point clouds from each of the acquired environmental information, and generate the value data by referring to a database DB based on statistics of the acquired number of point clouds. More specifically, the generation unit 99 may, for example, refer to the database DB based on the average value of the number of point clouds. Note that, for example, a weighted average may be used as the statistics. In this case, by increasing the weight of the feature quantities of the environmental information acquired by the external sensors 300 closer to the target stopping position, it is possible to reflect the external environment near the vehicle 100 in the value data while making it easier to reflect the external environment near the target stopping position in the value data.

[0052] In step S120, the remote control unit 220 generates a braking control value using the vehicle position information acquired in step S105. Specifically, in step S120, the remote control unit 220 generates a driving control signal including the braking control value.

[0053] In step S125, the generation unit 99 corrects the braking control value included in the driving control signal generated in step S120, using the braking correction value generated in step S115. Then, the generation unit 99 transmits the driving control signal including the corrected braking control value to the vehicle 100. The vehicle 100 brakes the vehicle 100 by controlling the actuator group 120 using the braking control value included in the received driving control signal. In the example of FIG. 5, a driving control signal CV1 is transmitted to the vehicle 100A. The driving control signal CV1 is a driving control signal including the corrected braking correction value.

[0054] According to the server 200 of the present embodiment described above, value data including braking relationship values ​​is generated using environmental information about the vehicle 100. Therefore, even in an environment where the actual stopping position of the vehicle 100 may deviate from the expected stopping position, the braking relationship values ​​can be used to brake the vehicle 100 so that the vehicle 100 appropriately stops at the expected stopping position. More specifically, for example, in the example of FIG. 5 , if a foreign object that interferes with braking is present at the second location PL2, the actual braking distance of the vehicle 100 may be longer than the expected braking distance. As a result, if the braking control value generated in step S120 is used as is, i.e., if a braking control value not based on the environmental information is used to stop the vehicle 100 at position P1, the actual stopping position of the vehicle 100 may deviate to position P2, which is further backward in the traveling direction d1 than position P1. In contrast, in the present embodiment, the vehicle 100 is braked using value data that reflects the environmental information, thereby preventing such a deviation between the actual stopping position of the vehicle 100 and the expected stopping position. As a result, the likelihood that work on vehicle 100 will be performed appropriately can be increased.

[0055] In this embodiment, the environmental information is forward point cloud information. As a result, the value data is generated taking into account the forward environment of the vehicle 100, which further increases the likelihood that work on the vehicle 100 will be performed appropriately.

[0056] Furthermore, in this embodiment, value data is generated using the number of points as a feature of the environment point cloud information. Therefore, more appropriate value data can be generated by more effectively using the environment point cloud information. Note that in other embodiments, point cloud density may be used as a feature of the environment point cloud information. Furthermore, point cloud detection distance may be used as a feature of the environment point cloud information. These other embodiments also enable more appropriate value data to be generated by more effectively using the environment point cloud information, similar to this embodiment.

[0057] Furthermore, in this embodiment, when the number of point clouds is the first point cloud number, the generation unit 99 generates value data such that the braking force per unit time is greater than when the number of point clouds is the second point cloud number. Therefore, it is possible to prevent the actual stopping position of the vehicle 100 from shifting forward in the traveling direction from the expected stopping position due to bad weather. As a result of generating value data such that the braking force per unit time is greater as described above, even if the actual stopping position shifts backward in the traveling direction from the expected stopping position, the vehicle 100 is stopped short of the expected stopping position. Therefore, subsequent measures are easier than when the actual stopping position shifts forward in the traveling direction from the expected stopping position. In this way, this embodiment increases the likelihood that work on the vehicle 100 will be performed appropriately, even in bad weather.

[0058] Furthermore, in this embodiment, the vehicle 100 is provided with a position information acquisition unit 211 that acquires the position of the vehicle 100, and the environmental information acquisition unit 212, in the stop processing, identifies the target external sensor 300 using the position acquired by the position information acquisition unit 211, and acquires environmental information only from the identified target external sensor 300. Therefore, for example, compared to a mode in which environmental information is acquired from all external sensors 300, the communication load and processing load associated with communication between the server 200 and the external sensor 300 can be reduced.

[0059] In another embodiment, the generation unit 99 may generate value data such that, when the point cloud density as a feature of the environment point cloud information is a first point cloud density, the braking force per unit time is greater than when the point cloud density is a second point cloud density. The second point cloud density is a point cloud density greater than the first point cloud density. In another embodiment, the generation unit 99 may generate value data such that, when the detection distance as a feature of the environment point cloud information is a first detection distance, the braking force per unit time is greater than when the detection distance is a second detection distance. The second detection distance is a detection distance longer than the first detection distance. These other embodiments also make it possible to prevent the actual stopping position of the vehicle 100 from shifting forward in the traveling direction from the expected stopping position due to bad weather, in a manner similar to the present embodiment.

[0060] In other embodiments, the braking control value that determines the magnitude of the braking force per unit time may be, for example, an instruction value that indicates the vehicle speed, or an instruction value that directly indicates the braking force per unit time.

[0061] In another embodiment, the braking control value may be a control value that determines the braking start timing of the vehicle 100. The braking start timing is the timing at which braking of the vehicle 100 starts. The braking start timing may be expressed, for example, as the time at which braking starts or as the distance from an assumed stopping position. The control value that determines the braking start timing may be, for example, a control value that determines the timing at which a negative acceleration for braking first occurs. In this case, the braking timing is delayed by the braking control value specifying a positive acceleration or zero acceleration at a timing at which a negative acceleration would normally be specified. Conversely, the braking timing is accelerated by the braking control value specifying a negative acceleration at a timing at which a negative acceleration would not normally be specified. In this case, instead of or in addition to "generating value data so as to increase the braking force per unit time" as described above, the generation unit 99 may generate value data so as to advance the braking start timing. More specifically, the generation unit 99 may generate value data so as to accelerate the braking start timing in at least one of the following cases: when the number of point clouds is a first point cloud number; when the point cloud density is a first point cloud density; and when the detection distance is a first detection distance. In this case, the database DB may associate a braking correction value for determining an earlier braking start timing with a smaller number of point clouds, a smaller point cloud density, or a shorter detection distance. This embodiment can prevent the actual stopping position of the vehicle 100 from shifting forward in the traveling direction from the expected stopping position due to bad weather. Note that the control value for determining the braking start timing of the vehicle 100 may be, for example, an instruction value for instructing the vehicle speed or an instruction value for directly instructing the braking start timing of the vehicle 100.

[0062] B. Second embodiment: 6 is a block diagram showing the configuration of a system 50b according to the second embodiment. Unlike the first embodiment, in the second embodiment, the control device 310 of the external sensor 300 has a generating unit 99b. The control device 310 in the second embodiment corresponds to the "device" in this disclosure. The system 50b according to the second embodiment is similar to the first embodiment in the aspects not specifically described.

[0063] In this embodiment, the processor 311 of the control device 310 executes the program PG3 stored in the memory 312, thereby functioning as the generation unit 99b and the environmental information acquisition unit 212. The generation unit 99b generates a braking correction value, as in the first embodiment. However, unlike the first embodiment, the generation unit 99b does not generate a braking control value. Also, in this embodiment, the acquisition unit 210 of the server 200 does not function as the environmental information acquisition unit 212. Also, in this embodiment, the vehicle control unit 115b of the vehicle 100 is configured to be able to correct the braking control value.

[0064] Fig. 7 is a flowchart of the stop processing in the second embodiment. Fig. 8 is a diagram for explaining an example of the stop processing in the second embodiment. Fig. 8 shows an example of the stop processing executed for the vehicle 100A, similar to Fig. 5. In Fig. 7, the same steps as in Fig. 4 are assigned the same reference numerals as in Fig. 4.

[0065] 7, the sensor identification unit 215 transmits a request signal to the target external sensor 300 identified in step S105. The request signal is a signal that requests the generation unit 99b to generate value data. In the example of FIG. 8, the request signal DS is transmitted to the external sensor 300B.

[0066] In step S112, the environmental information acquisition unit 212 of the external sensor 300 that has received the request signal acquires environmental information.

[0067] In step S115b, the generation unit 99b of the control device 310 generates a braking correction value using the environmental information acquired in step S112, in substantially the same manner as in step S115 of Fig. 3. Thereafter, as shown in Fig. 8, the generation unit 99b transmits the generated braking correction value BC to the vehicle 100. Note that, in other embodiments, step S112 does not need to be executed after receiving a request signal. For example, when environmental information is acquired at predetermined time intervals and a request signal is received, the generation unit 99b may generate a braking correction value using the environmental information acquired immediately before in step S115b.

[0068] In step S120b of Fig. 7, the remote control unit 220 generates a driving control signal including a braking control value, similar to step S120 of Fig. 4. Thereafter, unlike step S120 of Fig. 4, the remote control unit 220 transmits the generated driving control signal to the target vehicle 100. In the example of Fig. 8, a driving control signal CV2 is transmitted to vehicle 100A. Unlike the driving control signal CV1 shown in Fig. 5, the driving control signal CV2 includes a braking control value that is not dependent on environmental information.

[0069] In step S125b of Fig. 7, the vehicle control unit 115b of the target vehicle 100 corrects the braking correction value included in the driving control signal generated in step S120, using the braking correction value generated in step S115b. In the example of Fig. 8, the braking control value included in the driving control signal CV2 is corrected using the braking correction value BC. In step S130, the vehicle control unit 115b brakes the vehicle 100 by controlling the actuator group 120 using the braking control value corrected in step S125b.

[0070] As in the first embodiment, the control device 310 in the second embodiment described above also generates value data including braking-related values ​​using environmental information about the vehicle 100. Therefore, even in an environment where the actual stopping position of the vehicle 100 may deviate from the expected stopping position, it is possible to increase the likelihood that work on the vehicle 100 will be performed appropriately.

[0071] In another embodiment, for example, the external sensor 300 may transmit environmental information to the vehicle 100, and the vehicle control unit 115b of the vehicle control device 110 provided in the vehicle 100 may generate a braking correction value using the environmental information. In this embodiment, the vehicle control device 110 corresponds to the "device" in the present disclosure. That is, in this case, the vehicle control device 110 includes at least an environmental information acquisition unit and a generation unit.

[0072] C. Third embodiment: 9 is a block diagram showing the configuration of a system 50c according to the third embodiment. Unlike the first embodiment, in the third embodiment, the value data does not include braking-related values ​​but includes work-related values. Regarding the system 50c according to the third embodiment, the points not specifically described are the same as those according to the first embodiment.

[0073] In this embodiment, the processor 201 functions as each functional unit described in the first embodiment, and also functions as a device control unit 216. Also, in this embodiment, the remote control unit 220 does not function as the generation unit 99, and the device control unit 216 functions as a generation unit 99c.

[0074] The equipment control unit 216 identifies the target work equipment 400 and controls the target work equipment 400 by transmitting a work command for the work to the target work equipment 400. The target work equipment 400 is the work equipment 400 responsible for the work on the target vehicle 100. In this embodiment, the equipment control unit 216 identifies the work equipment 400 using the position of the vehicle 100 acquired by the position information acquisition unit 211. More specifically, the sensor identification unit 215 identifies the target work equipment 400 using the vehicle position information and route data RD of the target vehicle 100. The work command includes a work control value.

[0075] In this embodiment, the value data generated by the generation unit 99c includes a work related value. More specifically, the value data includes a work control value as the work related value. In this embodiment, the work control value is a parameter related to at least one of the position and the movement of the arm unit 420 of the work implement 400.

[0076] In this embodiment, when the number of point clouds acquired as the feature amount of the environment point cloud information is the first point cloud number, the generation unit 99c generates value data so that work is performed by the work implement 400 at a position further forward in the traveling direction of the vehicle 100 compared to when the number of point clouds is the second point cloud number. More specifically, the generation unit 99c generates, as value data, for example, a work control value for positioning the arm unit 420 further forward in the traveling direction, or a work control value for operating the arm unit 420 further forward in the traveling direction.

[0077] Fig. 10 is a flowchart of the stop processing in the third embodiment. Fig. 11 is a diagram for explaining an example of the stop processing in the third embodiment. Fig. 11 shows an example of the stop processing executed for the vehicle 100A, similar to Fig. 5. In Fig. 10, the same steps as in Figs. 4 and 7 are assigned the same reference numerals as in Figs. 4 and 7.

[0078] In step S113 of FIG. 10, the equipment control unit 216 identifies the target work equipment 400 using the route data RD and the position of the vehicle 100 acquired in step S100. In the example of FIG. 11, the work equipment 400A is identified as the target work equipment 400. The work equipment 400A corresponds to the first standard route SR1 and is the work equipment 400 that is responsible for work on the vehicle 100A at the second location PL2. The work equipment 400A is adjusted in advance to perform work on the vehicle 100A using position P1 as the work position. More specifically, the placement position of the work equipment 400A, the position and operation settings of the arm unit 420, etc. are adjusted in advance so that the work equipment 400A can appropriately perform work on the vehicle 100A stopped at position P1.

[0079] In step S116 of FIG. 10, the generation unit 99c uses the environmental information acquired in step S110 to generate a work control value for the target work device 400 identified in step S113. The generation unit 99c then transmits the generated work control value to the target work device 400. In the example of FIG. 11, a work control value WV1 is transmitted to the work device 400A. The work device 400A performs work on the vehicle 100A using the received work control value WV1. The target vehicle 100 is also braked by controlling the actuator group 120 using the travel control signal CV2 transmitted from the server 200 in step S120b.

[0080] According to the server 200 in the third embodiment described above, value data including a work related value is generated using environmental information about the vehicle 100. Therefore, in an environment in which the actual stopping position of the vehicle 100 may deviate from the expected stopping position, the work related value can be used to correct the work position in accordance with the deviation. More specifically, for example, in the example of FIG. 11 , if rain, fog, snow, or yellow sand occurs at the second location PL2, the actual stopping position of the vehicle 100, which is braked using the travel control signal CV2, may deviate from position P1 to position P2. In this embodiment, the operation of the work equipment 400 is controlled using value data reflecting the environmental information, allowing the work equipment 400 to perform work on the vehicle 100 at a work position corresponding to the deviated stopping position of the vehicle 100. As a result, the likelihood that work on the vehicle 100 will be performed appropriately can be increased.

[0081] Furthermore, in this embodiment, the work control value is a parameter related to at least one of the position and operation of the arm unit 420. When the number of point clouds is the first point cloud number, the generation unit 99c generates value data so that the work implement 400 performs work at a position further forward in the traveling direction of the vehicle 100 than when the number of point clouds is the second point cloud number. Therefore, even if the actual stopping position of the vehicle 100 deviates forward in the traveling direction from the assumed stopping position due to bad weather, the work implement 400 can perform work at a position corresponding to the deviated stopping position. Note that, even if the actual stopping position deviates backward in the traveling direction from the assumed stopping position as a result of generating the value data as described above, the vehicle 100 stops short of the assumed stopping position. Therefore, subsequent measures are easier than when the actual stopping position deviates forward in the traveling direction from the assumed stopping position. In this way, this embodiment can increase the likelihood that work on the vehicle 100 will be performed appropriately, even in bad weather.

[0082] In another embodiment, the generation unit 99c may acquire a point cloud density as a feature amount of the environment point cloud information, and generate value data such that when the point cloud density is a first point cloud density, work is performed further forward in the traveling direction compared to when the point cloud density is a second point cloud density. In another embodiment, the generation unit 99c may acquire a detection distance as a feature amount of the environment point cloud information, and generate value data such that when the detection distance is a first detection distance, work is performed further forward in the traveling direction compared to when the detection distance is a second detection distance. In these other embodiments, as in the third embodiment, work can be performed by the work equipment 400 at a work position that corresponds to a stop position that has been shifted due to bad weather.

[0083] D. Fourth embodiment: 12 is a block diagram showing the configuration of a system 50d according to the fourth embodiment. Unlike the third embodiment, in the fourth embodiment, the control device 310 of the external sensor 300 includes a generating unit 99d. The control device 310 in the fourth embodiment corresponds to the "device" in this disclosure. The system 50d according to the fourth embodiment is similar to the third embodiment in the aspects not specifically described.

[0084] In the fourth embodiment, similarly to the second embodiment, the control device 310 executes a program PG3 stored in a memory 312 to function as a generation unit 99d and an environmental information acquisition unit 212. Unlike the third embodiment, in this embodiment, the generation unit 99d generates an activity correction value as the activity related value, rather than an activity control value.

[0085] In this embodiment, the processor 201 functions as the device control unit 216, similarly to the third embodiment. However, in this embodiment, the device control unit 216 does not function as the generation unit 99c. Also, in this embodiment, the acquisition unit 210 of the server 200 does not function as the environment information acquisition unit 212.

[0086] In this embodiment, the processor 411 of the control device 410 provided in the work device 400 executes the program PG4 stored in the memory 412, thereby functioning as a work control unit 440. The work control unit 440 performs work by generating a work control value and controlling the arm unit 420 using the generated work control value. In this embodiment, the work control unit 440 corrects the work control value, which is generated by the device control unit 216 of the server 200 and is not dependent on environmental information, using the work correction value generated by the generation unit 99d, to generate a corrected work control value.

[0087] Fig. 13 is a flowchart of the stop processing in the fourth embodiment. Fig. 14 is a diagram for explaining an example of the stop processing in the fourth embodiment. Like Fig. 5, Fig. 14 shows an example of the stop processing executed for the vehicle 100A. In Fig. 13, steps similar to those in Figs. 4, 7, and 10 are assigned the same reference numerals as those in Figs. 4, 7, and 10.

[0088] In step S116d, the device control unit 216 generates a work control value for the target work device 400 and transmits the generated work control value to the target work device 400. In the example of Fig. 14, the work control value WV2 is transmitted to the work device 400A. Unlike the work control value WV1 shown in Fig. 11, the work control value WV2 is a work control value that does not depend on environmental information.

[0089] In step S117, the generation unit 99 of the control device 310 generates a task correction value using the environmental information acquired in step S112, and transmits the generated task correction value to the target task device 400. In the example of Fig. 14, task correction value WC is transmitted to task device 400A. In this embodiment, when the external sensors 300A to 300C corresponding to the first standard route SR1 generate a task correction value, they are configured to transmit the generated task correction value to the task device 400A corresponding to the first standard route SR1 in the same manner as the external sensors.

[0090] In step S135 of Fig. 13, the work control unit 440 of the target work device 400 corrects the work control value generated in step S116 using the work correction value generated in step S117. In the example of Fig. 14, the work control value WV2 is corrected by the work correction value WC. In step S140 of Fig. 13, the work control unit 440 performs work by controlling the arm unit 420 using the corrected work control value generated in step S135.

[0091] As in the third embodiment, the control device 310 in the fourth embodiment described above generates value data including work-related values ​​using environmental information about the vehicle 100. Therefore, even in an environment where the actual stopping position of the vehicle 100 may deviate from the expected stopping position, it is possible to increase the likelihood that work on the vehicle 100 will be performed appropriately.

[0092] In another embodiment, for example, external sensor 300 may transmit environmental information to work device 400, and control device 410 provided in work device 400 may generate a work correction value using the environmental information. In this embodiment, control device 410 corresponds to the "device" in the present disclosure. That is, in this case, control device 410 includes at least an environmental information acquisition unit and a generation unit.

[0093] E. Fifth embodiment: 15 is a block diagram showing the configuration of a system 50e according to the fifth embodiment. In the fifth embodiment, unlike the fourth embodiment, the server 200 does not have an equipment control unit 216 and does not generate an operation control value for the operation equipment 400. The system 50e according to the fifth embodiment is similar to the fourth embodiment in the points that are not specifically described.

[0094] In this embodiment, unlike the fourth embodiment, the work control unit 440e generates a work control value that is not based on environmental information, and corrects the generated work control value using the work correction value generated by the generation unit 99d, thereby generating a corrected work control value.

[0095] Fig. 16 is a flowchart of the stop processing in the fifth embodiment, and Fig. 17 is a diagram for explaining an example of the stop processing in the fifth embodiment.

[0096] In step S116d, the work control unit 440e of the target work device 400 generates a work control value. In step S116d, for example, a preset setting value of the work control unit 440e is used to generate a work control value for performing work on the vehicle 100A stopped at position P1. In step S135d, the work control unit 440 corrects the work control value generated in step S116d using a work correction value received from the target external sensor 300. In the example of FIG. 17, the work control value generated by the work control unit 440 of the work device 400A is corrected using the work correction value WC.

[0097] As in the third embodiment, the control device 310 in the fifth embodiment described above also generates value data including work-related values ​​using environmental information about the vehicle 100. Therefore, even in an environment where the actual stopping position of the vehicle 100 may deviate from the expected stopping position, it is possible to increase the likelihood that work on the vehicle 100 will be performed appropriately.

[0098] In another embodiment, the external sensor 300 may transmit environmental information to the work device 400, and the control device 410 included in the work device 400 may generate an work control value using the environmental information. In this embodiment, the control device 410 corresponds to the "device" in the present disclosure. That is, in this case, the control device 410 includes at least an environmental information acquisition unit and a generation unit.

[0099] F. Sixth embodiment: FIG. 18 is a block diagram of a system 50v in the sixth embodiment. Unlike the first embodiment, the system 50v in the present embodiment does not include a server 200. Furthermore, the vehicle in the present embodiment can travel by autonomous vehicle control. Unless otherwise specified, the other configurations are the same as those in the first embodiment. Note that the device configuration of the vehicle in the present embodiment is the same as that of the vehicle 100 in the first embodiment, and therefore, for convenience, the vehicle in the present embodiment will also be referred to as the vehicle 100.

[0100] In this embodiment, the communication device 130 of the vehicle 100 can communicate with external sensors 300 and work equipment 400. The processor 111 of the vehicle control device 110 executes a program PG1 stored in the memory 112, thereby functioning as a vehicle control unit 115v, an acquisition unit 210, a sensor identification unit 215, a remote control unit 220, and a notification unit 230. The vehicle control unit 115v controls the actuator group 120 using a travel control signal generated by the vehicle 100, thereby enabling the vehicle 100 to travel by autonomous control. The vehicle control unit 115v also functions as a generation unit 99. In addition to the program PG1, the memory 112 stores route data RD and a database DB.

[0101] 19 is a flowchart showing the processing procedure for driving control of the vehicle 100 in the sixth embodiment. In the processing procedure in FIG. 8, the processor 111 of the vehicle 100 executes the program PG1 to function as the acquisition unit 210 and the vehicle control unit 115v.

[0102] In step S901, the processor 111 of the vehicle control device 110 acquires vehicle position information using the detection results output from the external sensor 300. In step S902, the processor 111 determines a target position to which the vehicle 100 should next head. In step S903, the processor 111 generates a driving control signal for driving the vehicle 100 toward the determined target position. In step S904, the processor 111 controls the actuator group 120 using the generated driving control signal, thereby causing the vehicle 100 to drive in accordance with parameters represented in the driving control signal. The processor 111 repeats the acquisition of vehicle position information, determination of the target position, generation of the driving control signal, and control of the actuators at a predetermined cycle. According to the system 50v of this embodiment, the vehicle 100 can be driven by autonomous control of the vehicle 100 without remote control of the vehicle 100 by the server 200.

[0103] In this embodiment, the same stop processing as in Fig. 4 is executed. However, in this embodiment, the stop processing is executed by the processor 111 of the vehicle control device 110, not by the processor 201 of the server 200. Also, in this embodiment, the "target vehicle 100" means the subject vehicle.

[0104] As in the first embodiment, the vehicle control device 110 in the sixth embodiment described above also generates value data including braking-related values ​​using environmental information about the vehicle 100. Therefore, even in an environment where the actual stopping position of the vehicle 100 may deviate from the expected stopping position, it is possible to increase the likelihood that work on the vehicle 100 will be performed appropriately.

[0105] In other embodiments in which the vehicle 100 runs under autonomous control, the stop process may be executed in the same manner as in the second to fifth embodiments. When the stop process is executed in the same manner as in the third or fourth embodiment, the processor 111 of the vehicle control device 110 may function as the equipment control unit 216. In addition, in a configuration in which the vehicle 100 runs under autonomous control, for example, the system 50 may be provided with a server 200. In this case, the server 200 may have at least some of the functional units in the system 50v, such as at least some of the functional units included in the vehicle 100 in the sixth embodiment.

[0106] G. Other Embodiments: (G1) In each of the above embodiments, the external sensor 300 is configured by a distance measuring device. However, the external sensor 300 may be configured by a camera that captures images of the vehicle 100 and the external environment.

[0107] Note that, when a camera is used as the external sensor 300, in step S1 of FIG. 3, vehicle position information can be estimated using the captured image as the detection result. Specifically, in step S1, the processor 201, for example, detects the outer shape of the vehicle 100 from the captured image, calculates the coordinates of the positioning point of the vehicle 100 in the coordinate system of the captured image, i.e., the local coordinate system, and converts the calculated coordinates into coordinates in the global coordinate system GC, thereby acquiring the position of the vehicle 100. The outer shape of the vehicle 100 included in the captured image can be detected, for example, by inputting the captured image into a detection model utilizing artificial intelligence. The detection model is prepared, for example, inside or outside the system 50 and pre-stored in the memory 202 of the server 200. Examples of the detection model include a trained machine learning model trained to realize either semantic segmentation or instance segmentation. For example, a convolutional neural network (hereinafter, CNN) trained by supervised learning using a training dataset can be used as this machine learning model. The training dataset includes, for example, a plurality of training images including the vehicle 100, and labels indicating whether each region in the training images represents the vehicle 100 or a region other than the vehicle 100. During CNN training, it is preferable to update the parameters of the CNN using backpropagation (back propagation) to reduce errors between the output results of the detection model and the labels. Furthermore, the processor 201 can acquire the orientation of the vehicle 100 by estimating the orientation based on the orientation of the movement vector of the vehicle 100 calculated from changes in the positions of feature points of the vehicle 100 between frames of captured images using, for example, an optical flow method.

[0108] (G1a) In the above-described form (G1), an image of the external environment of the vehicle 100 may be used as the environmental information. In this case, it is preferable that the environmental information be an image of the forward environment. In this case, the value data is generated taking into account the environment ahead in the traveling direction of the vehicle 100, further increasing the likelihood that work on the vehicle 100 will be performed appropriately. Hereinafter, an image of the external environment is also referred to as an "environment image." In particular, an image of the forward environment is also referred to as a "forward image." The environmental image includes, for example, pixels representing the road surface of the road on which the vehicle is traveling and pixels representing objects on the road surface. Note that the system 50 may, for example, include both a camera and a ranging device as the external sensor 300, and use both the environmental image and environmental point cloud information as the environmental information.

[0109] (G1b) In the above embodiment (G1a), it is preferable that the generation unit 99 further acquires from the environmental image at least one of the following feature quantities: the brightness of the environmental image, the presence or absence of a predetermined object in the environmental image, and the proportion of the object in the environmental image, and generates the value data using the acquired feature quantities. The object may be, for example, a foreign object that interferes with braking, such as rain, snow, fog, or yellow sand. The object in the environmental image may be detected using, for example, a trained model trained to detect objects in an input image or a rule-based model defined to detect objects in an input image. The "proportion of the object in the environmental image" may be expressed, for example, as an area ratio or a ratio of the number of pixels. This embodiment enables more effective use of the environmental image to generate more appropriate value data.

[0110] (G1c) In the above embodiments (G1a) and (G1b), the generation unit 99 may generate value data such that, when the luminance of the environmental image is a first luminance, the braking force per unit time is greater than when the luminance is a second luminance. The second luminance is a luminance higher than the first luminance. Furthermore, the generation unit 99 may generate value data such that, when an object is included in the environmental image, the braking force per unit time is greater than when the object is not included. Furthermore, the generation unit 99 may generate value data such that, when the proportion of the object in the environmental image is a first proportion, the braking force per unit time is greater than when the proportion of the object is a second proportion. The second proportion is a proportion smaller than the first proportion. In bad weather such as rain, snow, fog, or yellow sand, objects are more likely to appear in the environmental image than in good weather. As a result, the luminance of the environmental image is more likely to decrease. Therefore, by generating the value data as in this embodiment (G1c), it is possible to prevent the actual stopping position of the vehicle 100 from shifting forward in the traveling direction from the expected stopping position due to bad weather.

[0111] (G1d) In the above embodiments (G1a) to (G1c), the braking control value may be a control value that determines the timing of braking initiation of the vehicle 100. In this case, the generation unit 99 may generate value data so that the braking initiation timing is earlier in at least one of the following cases: when the brightness of the environmental image is a first brightness; when an object is included in the environmental image; and when the proportion of the object occupying the environmental image is a first proportion. According to this embodiment, it is possible to prevent the actual stopping position of the vehicle 100 from shifting forward in the traveling direction from the expected stopping position due to bad weather.

[0112] (G1e) In the above embodiments (G1a) to (G1d), the value data may include a work-related value. In this case, the generation unit 99 may generate the value data so that, when the brightness of the environmental image is a first brightness, the work by the work implement 400 is performed at a position further forward of the vehicle 100 in the traveling direction compared to when the brightness is a second brightness. Furthermore, when an object is included in the environmental image, the generation unit 99 may generate the value data so that the work by the work implement 400 is performed at a position further forward of the vehicle 100 in the traveling direction compared to when the object is not included. Furthermore, when the proportion of the object in the environmental image is a first proportion, the generation unit 99 may generate the value data so that the work by the work implement 400 is performed at a position further forward of the vehicle 100 in the traveling direction compared to when the proportion of the object is a second proportion. According to this embodiment, even if the actual stopping position of the vehicle 100 deviates forward in the traveling direction from the expected stopping position due to bad weather, the work equipment 400 can perform work at a position corresponding to the deviated stopping position.

[0113] (G2) In each of the above embodiments, the acquisition unit 210 may function as a braking distance acquisition unit that acquires a predicted value of the braking distance. In this case, the generation unit 99 may generate value data using the acquired predicted value of the braking distance. In this case, the acquisition unit 210 acquires the braking distance based on, for example, feature amounts of an environmental image as environmental information or feature amounts of environmental point cloud information as environmental information. More specifically, the acquisition unit 210 may acquire the braking distance using, for example, a trained model that has been trained to calculate the braking distance using input environmental information, a rule-based model that has been defined to calculate the braking distance using input environmental information, or a database that associates feature amounts of environmental information with braking distances.

[0114] (G2a) In the above-described form (G2), the generation unit 99 may generate value data such that, when the acquired predicted value of the braking distance is a first distance, the braking force per unit time is greater than when the predicted value of the braking distance is a second distance. The second distance is shorter than the first distance. According to this form, in an environment where the braking distance may be longer, such as in bad weather, it is possible to prevent the actual stopping position of the vehicle 100 from shifting forward in the traveling direction from the expected stopping position.

[0115] (G2b) In the above embodiments (G2) and (G2a), the generation unit 99 may generate value data so that the timing of braking commences earlier when the acquired predicted value of the braking distance is the first distance than when the predicted value of the braking distance is the second distance. According to this embodiment, in an environment where the braking distance may be longer, such as in bad weather, it is possible to prevent the actual stopping position of the vehicle 100 from shifting forward in the traveling direction from the expected stopping position.

[0116] (G2c) In the above embodiments (G2) to (G2b), the value data may include a work-related value. In this case, the generation unit 99 may generate the value data so that, when the acquired predicted value of the braking distance is a first distance, the work implement 400 performs work at a position further forward in the traveling direction of the vehicle 100 compared to when the predicted value of the braking distance is a second distance. According to this embodiment, in an environment where the braking distance may be longer, such as in bad weather, even if the actual stopping position of the vehicle 100 deviates forward in the traveling direction from the expected stopping position due to bad weather, the work implement 400 can perform work at a position corresponding to the deviated stopping position.

[0117] (G2d) In the above embodiments (G2) to (G2c), the generation unit 99 may not generate value data if the acquired braking distance prediction value is equal to or greater than a predetermined first reference distance. This embodiment allows the generation of value data to be omitted in an environment where the actual stopping position of the vehicle 100 may deviate significantly from the expected stopping position, thereby reducing the processing load associated with generating value data. In such an environment, it is preferable to perform a process other than generating value data, such as a process to stop the unmanned operation of each vehicle 100 or a process to stop the operation of each work device 400. By omitting the generation of value data, the process other than generating value data can be executed more smoothly. The first reference distance is determined based on an experiment, for example, as a distance large enough to make it preferable to perform a process other than generating value data. The experiment here includes a simulated experiment using simulation.

[0118] (G2e) In the above embodiments (G2) to (G2d), the notification unit 230 may notify the user when the acquired predicted value of the braking distance is equal to or greater than a predetermined second reference distance. The second reference distance may be the same as the first reference distance, or may be a distance different from the first reference distance. According to this embodiment, the user can be notified of an abnormality in an environment where the actual stopping position of the vehicle 100 may deviate relatively significantly from the expected stopping position.

[0119] (G3) In each of the above embodiments, when the external environment is outdoors, the generation unit 99 may use a ranging device as the external sensor 300, acquire vehicle position information using 3D point cloud information as detection results, and generate value data using environmental point cloud information as environmental information. 3D point cloud information acquired by a ranging device is generally less affected by ambient brightness than captured images acquired by a camera. Therefore, even if the brightness around the external sensor 300 changes depending on the time of day or weather, unmanned driving and value data generation can be more appropriately performed.

[0120] (G4) In each of the above embodiments, when the external environment is indoors, the generation unit 99 may use a camera as the external sensor 300, acquire vehicle position information using the captured image as detection results, and generate value data using the captured image as environmental information. According to this embodiment, the cost required to prepare the external sensor 300 can be reduced compared to, for example, using a distance measuring device as the external sensor 300 when the external environment is indoors.

[0121] (G5) In each of the above embodiments, the vehicle 100 may be configured to be capable of traveling indoors and outdoors in an unmanned manner, and the generation unit 99 may generate value data only when the external environment is indoors. This configuration makes it possible to generate value data outdoors, where the external environment is relatively unstable compared to indoors, and also reduces the processing load associated with generating the value data.

[0122] (G6) In each of the above embodiments, the acquisition unit 210 may function as a weather information acquisition unit that acquires weather information. In this case, the generation unit 99 may generate value data when the acquired weather information satisfies predetermined weather conditions, and may not generate value data when the weather information does not satisfy the weather conditions. Weather conditions include, for example, rain, snow, fog, yellow sand, or the like occurring, or the forecast of rain, snow, fog, yellow sand, or the like. The weather information may be acquired from, for example, an external computer or recording medium, or from the memory 112, 202, 312, or 412. According to this embodiment, value data may be generated when bad weather is occurring or when bad weather is forecast, thereby suppressing deviation of the stopping position, and generation of value data may be omitted when bad weather is not occurring or when bad weather is not forecast, thereby reducing the processing load associated with generating value data.

[0123] (G7) In each of the above embodiments, the generation unit 99 may generate value data when a preceding vehicle of the target vehicle 100 fails to stop at the expected stopping position, and may not generate value data when the preceding vehicle is able to stop at the expected stopping position. The preceding vehicle is a vehicle 100 that precedes the target vehicle 100. According to this embodiment, it is possible to suppress deviation of the stopping position by generating value data in an environment where the actual stopping position and the expected stopping position may deviate following the preceding vehicle, and it is possible to omit generation of value data when the probability of deviation of the stopping position occurring is low, thereby reducing the processing load associated with generating the value data.

[0124] (G8) In each of the above embodiments, the device may use the value data used for the target vehicle 100 for a vehicle following the target vehicle 100. According to this embodiment, the processing load associated with generating the value data can be reduced compared to an embodiment in which value data is generated individually for the target vehicle 100 and the following vehicle.

[0125] (G8a) In the above-described form (G8), the device may continuously use the same value data for the vehicle 100 following the following vehicle until a predetermined cancellation condition is satisfied. The cancellation condition is preferably at least one of, for example, a change in weather from rainy to sunny, a user performing an operation to stop the continuous use of the value data, and a deviation between the actual stopping position and the expected stopping position when the value data is used that exceeds a predetermined level. This form can further reduce the processing load associated with the generation of value data. Furthermore, in a situation where it is not desirable to continuously use the used value data for the following vehicle, the device can cancel the continuous use of the used value data and generate new value data.

[0126] (G9) In each of the above embodiments, unmanned driving of the vehicle 100 may be stopped when the acquired environmental information satisfies a predetermined first condition. The first condition may be, for example, a condition related to at least one of a feature amount of the environmental image and a feature amount of the environment point cloud information. More specifically, the first condition may be, for example, at least one of the following: the brightness of the environmental image is equal to or less than a predetermined reference brightness; the proportion of objects in the environmental image is equal to or greater than a reference proportion; the number of point clouds in the environment point cloud information is equal to or less than a reference number of point clouds; the point cloud density of the environment point cloud information is equal to or less than a reference point cloud density; and the detection distance of the environment point cloud information is equal to or less than a reference distance. According to this embodiment, unmanned driving can be stopped in an environment where it is not desirable to perform unmanned driving. Note that, when the environmental information satisfies the first condition, the generation unit 99 does not need to generate value data. This reduces the processing load associated with generating value data.

[0127] (G10) In each of the above embodiments, if the acquired environmental information satisfies a predetermined second condition, the driving route of the vehicle 100 may be changed. In this case, for example, if the environmental information satisfies the second condition, at least a portion of the driving route of the vehicle 100 may be changed from a route traveling outdoors to a route traveling indoors. The second condition may be, for example, a condition related to at least one of the feature amount of the environmental image and the feature amount of the environmental point cloud information, similar to the first condition. According to this embodiment, the driving route of the vehicle 100 can be changed so as to avoid an environment in which the actual stopping position and the expected stopping position may deviate relatively significantly. Note that if the environmental information satisfies the second condition, the generation unit 99 does not need to generate value data. Furthermore, both the processing of the above embodiment (G9) and the processing of this embodiment (G10) may be applied. In this case, the second condition may be a condition that is looser than the first condition. In this way, for example, unmanned driving is stopped only in an environment where both the generation of value data and the change of the vehicle 100's driving route are undesirable, thereby making it possible to achieve both efficient movement of the vehicle 100 through unmanned driving and appropriate control of the vehicle 100 through unmanned driving.

[0128] (G11) In each of the above embodiments, the remote control unit 220 or the vehicle control unit 115 may use environmental information to generate a control command to change the inter-vehicle distance between the target vehicle 100 and the preceding vehicle and the inter-vehicle distance between the target vehicle 100 and the following vehicle. According to this embodiment, it is possible to prevent the vehicles 100 from getting too close to or too far apart from each other due to the external environment, and each vehicle 100 can travel more appropriately.

[0129] (G11a) In the above embodiment (G11), the remote control unit 220 or the vehicle control unit 115 may increase the inter-vehicle distance when the brightness of the environmental image is a first brightness, compared to when the brightness is a second brightness. Furthermore, the remote control unit 220 or the vehicle control unit 115 may increase the inter-vehicle distance when an object is included in the environmental image, compared to when the object is not included. Furthermore, the remote control unit 220 or the vehicle control unit 115 may increase the inter-vehicle distance when the proportion of the object in the environmental image is a first proportion, compared to when the proportion of the object is a second proportion. This embodiment can prevent vehicles 100 from getting too close to each other due to worsening road conditions caused by bad weather or reduced accuracy of vehicle position information.

[0130] (G11b) In the above embodiment (G11), the remote control unit 220 or the vehicle control unit 115 may increase the inter-vehicle distance when the number of point clouds in the environment point cloud information is the first point cloud number, compared to when the number of point clouds is the second point cloud number. Furthermore, the remote control unit 220 or the vehicle control unit 115 may increase the inter-vehicle distance when the point cloud density in the environment point cloud information is the first point cloud density, compared to when the point cloud density is the second point cloud density. Furthermore, the remote control unit 220 or the vehicle control unit 115 may increase the inter-vehicle distance when the detection distance in the environment point cloud information is the first detection distance, compared to when the detection distance is the second detection distance. This embodiment can prevent vehicles 100 from getting too close to each other due to worsening road conditions caused by bad weather or reduced accuracy of vehicle position information.

[0131] (G12) In each of the above embodiments, the generation unit 99 may generate both a braking relationship value and a working relationship value as value data. Furthermore, the value data may include a work setting value as the working relationship value. Furthermore, the working relationship value does not have to be a parameter related to the position or operation of the arm unit 420 of the work device 400. For example, if the work device 400 is equipped with a moving unit for moving the work device 400, the working relationship value may be a parameter related to the position of the work device 400 or a parameter related to the operation of the moving unit.

[0132] (G13) In each of the above embodiments, the braking relationship value is generated as a value for correcting the stopping position of the vehicle 100 to a position further rearward in the traveling direction. In contrast, the braking relationship value may be generated as a value for correcting the stopping position of the vehicle 100 to a position further forward in the traveling direction. For example, the generation unit 99 may use environmental information to detect factors that prompt braking of the vehicle 100, and when such factors are detected, generate a braking relationship value for correcting the stopping position of the vehicle 100 to a position further forward in the traveling direction. Factors that prompt braking of the vehicle 100 include, for example, an increase in unevenness due to deterioration of the road surface, or foreign objects such as sheets or tape that may increase the frictional force between the road surface and the wheels. Similarly, the working relationship value does not have to be a value for correcting the working position to a position further forward in the traveling direction.

[0133] (G14) In each of the above embodiments, the system 50 may not be provided with the sensor identification unit 215. In this case, the environmental information to be used to generate the value data may be selected after environmental information is acquired from multiple external sensors 300 without identifying the external sensor 300. In this case, the environmental information to be used to generate the value data may be selected in a manner similar to that used by the sensor identification unit 215 to identify the target external sensor 300.

[0134] (G15) In each of the above embodiments, the control command may include at least one of a driving control signal and generation information for generating the driving control signal. For example, when the remote control unit 220 of the server 200 generates the generation information as a control command, the vehicle control device 110 of the vehicle 100 may receive the generation information from the server 200 and generate the driving control signal using the received generation information. For example, vehicle position information, a route, or a target position may be used as the generation information.

[0135] (G16) In the first embodiment, the processes from obtaining vehicle position information to generating a driving control signal are executed by the server 200. However, at least a part of the processes from obtaining vehicle position information to generating a driving control signal may be executed by the vehicle 100. For example, the following forms (1) to (3) may be used.

[0136] (1) The server 200 may acquire vehicle position information, determine a target position to which the vehicle 100 should next head, and generate a route from the current location of the vehicle 100 indicated in the acquired vehicle position information to the target position. The server 200 may generate a route to the target position between the current location and the destination, or may generate a route to the destination. The server 200 may transmit the generated route to the vehicle 100. The vehicle 100 may generate a driving control signal so that the vehicle 100 drives on the route received from the server 200, and control the actuator group 120 using the generated driving control signal.

[0137] (2) Server 200 may acquire vehicle position information and transmit the acquired vehicle position information to vehicle 100. Vehicle 100 may determine a target position to which vehicle 100 should next head, generate a route from the current location of vehicle 100 indicated in the received vehicle position information to the target position, generate a driving control signal so that vehicle 100 travels on the generated route, and control actuator group 120 using the generated driving control signal.

[0138] (3) In the above embodiments (1) and (2), the vehicle 100 may be equipped with an internal sensor, and detection results output from the internal sensor may be used for at least one of generating a route and generating a driving control signal. The internal sensor is a sensor equipped in the vehicle 100. The internal sensor may include, for example, a sensor that detects the motion state of the vehicle 100, a sensor that detects the operating state of each part of the vehicle 100, and a sensor that detects the environment around the vehicle 100. Specifically, the internal sensor may include, for example, a camera, LiDAR, millimeter-wave radar, an ultrasonic sensor, a GPS sensor, an acceleration sensor, a gyro sensor, etc. For example, in the above embodiment (1), the server 200 may acquire the detection results of the internal sensor and reflect the detection results of the internal sensor in the route when generating a route. In the above embodiment (1), the vehicle 100 may acquire the detection results of the internal sensor and reflect the detection results of the internal sensor in the driving control signal when generating a driving control signal. In the above embodiment (2), the vehicle 100 may acquire the detection results of the internal sensor and reflect the detection results of the internal sensor in the route when generating a route. In the above embodiment (2), the vehicle 100 may acquire the detection result of the internal sensor, and when generating the driving control signal, may reflect the detection result of the internal sensor in the driving control signal.

[0139] (G17) In the sixth embodiment, the vehicle 100 may be equipped with an internal sensor, and the detection results output from the internal sensor may be used for at least one of generating a route and generating a driving control signal. For example, the vehicle 100 may acquire the detection results of the internal sensor and, when generating a route, reflect the detection results of the internal sensor in the route. The vehicle 100 may acquire the detection results of the internal sensor and, when generating a driving control signal, reflect the detection results of the internal sensor in the driving control signal.

[0140] (G18) In the sixth embodiment, the vehicle 100 acquires vehicle position information using the detection results of the external sensor 300. Alternatively, the vehicle 100 may be equipped with an internal sensor. The vehicle 100 may acquire vehicle position information using the detection results of the internal sensor, determine a target position to which the vehicle 100 should next travel, generate a route from the current location of the vehicle 100 represented in the acquired vehicle position information to the target position, generate a driving control signal for traveling along the generated route, and control the actuator group 120 using the generated driving control signal. In this case, the vehicle 100 can travel without using any of the detection results of the external sensor 300. The vehicle 100 may acquire a target arrival time or traffic congestion information from outside the vehicle 100 and reflect the target arrival time or traffic congestion information in at least one of the route and the driving control signal. Furthermore, all of the functional configuration of the system 50v may be provided in the vehicle 100. In other words, the processing performed by the system 50v in the present disclosure may be performed by the vehicle 100 alone.

[0141] (G19) In the first to fifth embodiments described above, the server 200 automatically generates a driving control signal to be transmitted to the vehicle 100. Alternatively, the server 200 may generate a driving control signal to be transmitted to the vehicle 100 in accordance with the operation of an external operator located outside the vehicle 100. For example, the external operator may operate a control device including a display that displays captured images output from the external sensor 300, a steering wheel for remotely controlling the vehicle 100, an accelerator pedal, a brake pedal, and a communication device for communicating with the server 200 via wired or wireless communication, and the server 200 may generate a driving control signal in accordance with the operation applied to the control device. Hereinafter, unmanned driving achieved in accordance with the operation of the control device by an external operator in this manner may also be referred to as remote manual driving.

[0142] (G19a) In the above-described form (G19), the generation unit 99 may use environmental information to generate a braking correction value for correcting a braking control value generated in response to the operation of the control device.

[0143] (G20) In each of the above embodiments, remote manual driving may be performed when the acquired environmental information satisfies a predetermined third condition. The second condition may, for example, be a condition related to at least one of the feature amounts of a captured image of the external environment and the feature amounts of 3D point cloud information of the captured external environment, similar to the first condition. According to this embodiment, the vehicle 100 can be driven appropriately by remote manual driving in an environment where the actual stopping position may deviate relatively significantly from the expected stopping position. Note that, when the environmental information satisfies the third condition, the generation unit 99 may not generate value data. Furthermore, both the processing of the above embodiment (G9) and the processing of this embodiment (G20) may be applied. In this case, the third condition may be a more lenient condition than the first condition. In this way, for example, unmanned driving is stopped only in an environment where both the generation of value data and remote manual driving are unfavorable. This allows for both efficient movement of the unmanned vehicle 100 and appropriate control of the unmanned vehicle 100. Also, for example, both the process of the above-mentioned form (G10) and the process of this form (G20) may be applied.

[0144] (G21) In each of the above embodiments, the vehicle 100 may be configured to be able to travel by unmanned driving, and may be in the form of a platform having the configuration described below, for example. Specifically, the vehicle 100 may be equipped with at least a vehicle control device 110 and an actuator group 120 to perform the three functions of "running," "turning," and "stopping" by unmanned driving. When the vehicle 100 acquires information from the outside for unmanned driving, the vehicle 100 may further be equipped with a communication device 130. In other words, the vehicle 100 that can travel by unmanned driving may not be equipped with at least some of its interior parts, such as a driver's seat and a dashboard, may not be equipped with at least some of its exterior parts, such as bumpers and fenders, and may not be equipped with a body shell. In this case, the remaining parts, such as the body shell, may be attached to the vehicle 100 before the vehicle 100 is shipped from the factory FC, or the remaining parts, such as the body shell, may be attached to the vehicle 100 after the vehicle 100 is shipped from the factory FC without the remaining parts, such as the body shell. Each component may be attached from any direction, such as the upper, lower, front, rear, right or left side of the vehicle 100, and may be attached from the same direction or from different directions. Note that the position of the platform configuration may also be determined in the same manner as for the vehicle 100 in the first embodiment.

[0145] (G22) The vehicle 100 may be manufactured by combining multiple modules. A module refers to a unit composed of one or more parts grouped according to the configuration or function of the vehicle 100. For example, the platform of the vehicle 100 may be manufactured by combining a front module that forms the front portion of the platform, a central module that forms the center portion of the platform, and a rear module that forms the rear portion of the platform. The number of modules that form the platform is not limited to three, but may be two or less, or four or more. Furthermore, in addition to or instead of the platform, parts of the vehicle 100 that are different from the platform may be modularized. Furthermore, the various modules may include any exterior parts such as a bumper or a grille, or any interior parts such as a seat or a console. Furthermore, any type of mobile object, not limited to the vehicle 100, may be manufactured by combining multiple modules. Such a module may be manufactured, for example, by joining multiple parts using welding or fasteners, or by integrally molding at least a portion of the module as a single part by casting. The molding method of integrally molding at least a portion of the module as a single part is also called gigacasting or megacasting. By using Gigacast, each part of a moving body that has conventionally been formed by joining multiple parts can be formed as a single part. For example, the front module, center module, and rear module described above may be manufactured using Gigacast.

[0146] (G23) Transporting vehicle 100 by using the unmanned driving of vehicle 100 is also called "self-propelled transport." The configuration for realizing self-propelled transport is also called a "vehicle remote-controlled autonomous transport system." The production method for producing vehicle 100 by using self-propelled transport is also called "self-propelled production." In self-propelled production, for example, at a factory FC where vehicle 100 is manufactured, at least a portion of the transport of vehicle 100 is realized by self-propelled transport.

[0147] In each of the above embodiments, some or all of the functions and processes implemented by software may be implemented by hardware. Furthermore, some or all of the functions and processes implemented by hardware may be implemented by software. Hardware for implementing the various functions in each of the above embodiments may be implemented by various circuits, such as integrated circuits and discrete circuits.

[0148] The present disclosure is not limited to the above-described embodiments and can be realized in various configurations without departing from the spirit thereof. For example, the technical features in the embodiments corresponding to the technical features in each aspect described in the Summary of the Invention section can be appropriately replaced or combined to solve some or all of the above-described problems or achieve some or all of the above-described effects. Furthermore, if a technical feature is not described as essential in this specification, it can be appropriately deleted. [Explanation of symbols]

[0149] 50, 50b, 50c, 50d, 50e, 50v...system, 99, 99b, 99c, 99d...generation unit, 100, 100A, 100B...vehicle, 110...vehicle control device, 111...processor, 112...memory, 113...input / output interface, 114...internal bus, 115, 115b, 115v...vehicle control unit, 120...actuator group, 130...communication device, 200...server, 201...processor, 202...memory, 203...input / output interface, 204...internal bus, 205...communication device, 210...acquisition unit, 211...position information acquisition unit, 212... Environmental information acquisition unit, 215... sensor identification unit, 216... equipment control unit, 220... remote control unit, 230... alarm unit, 300, 300A, 300B, 300C... external sensors, 310... control unit, 311... processor, 312... memory, 313... input / output interface, 314... internal bus, 320... sensor unit, 330... communication device, 400, 400A, 400B... work equipment, 410... control unit, 411... processor, 412... memory, 413... input / output interface, 414... internal bus, 420... arm unit, 430... communication device, 440, 440e... work control unit

Claims

1. an acquisition unit that acquires environmental information regarding at least one of an environment around a current location of a mobile body that can move by unmanned driving and an environment ahead in a traveling direction of the mobile body; a generation unit that uses the acquired environmental information to generate value data including at least one of a braking control value that is a control value related to braking of the moving body, a braking correction value that is a correction value for correcting the braking control value, a work control value for controlling work equipment that performs work on the moving body, the work control value being a control value related to the work, a work setting value of the work equipment, the work setting value being a setting value related to the work, and a work correction value that is a correction value for correcting the work control value.

2. 10. The apparatus of claim 1, The device, wherein the environmental information includes an image of the environment in front of the device.

3. 3. The apparatus of claim 2, The generation unit acquiring, from the image, at least one feature amount of the brightness of the image, the presence or absence of a predetermined object in the image, and the proportion of the object in the image; generating the value data using at least one of the acquired feature amounts; Device.

4. 10. The apparatus of claim 1, The apparatus, wherein the environmental information includes three-dimensional point cloud information of the forward environment.

5. 5. The apparatus of claim 4, The generation unit acquiring at least one feature value of the number of points, the density of points, and the detection distance of points from the three-dimensional point cloud information; generating the value data using at least one of the acquired feature amounts; Device.

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