Monitoring device and method

Abstract

To monitor the output torque of a vehicle in accordance with a change in the state of the vehicle.SOLUTION: A monitoring device monitors, in a factory where multiple processes are carried out and executed in order to manufacture a vehicle that runs by unmanned drive, the vehicle subjected to the multiple processes. The monitoring device includes: a process obtaining unit that obtains, for the vehicle, process information on the currently executed process among the multiple processes; a torque obtaining unit that obtains, in the executed process, torque information on the output torque of the vehicle; and a detecting unit that detects, by using the process information and the torque information, an abnormality in the output torque of the vehicle.SELECTED DRAWING: Figure 2

Description

Technical Field

[0001] The present disclosure relates to a monitoring device and a method.

Background Art

[0002] The monitoring device described in Patent Document 1 monitors the torque of a vehicle.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In a manufacturing process for manufacturing a vehicle, there is a production method in which while driving an unfinished vehicle by remote control or autonomous control, parts are assembled to the vehicle.

[0005] In such a technique, the weight of the vehicle changes as parts are assembled. Here, when the weight of the vehicle changes, the appropriate magnitude of the output torque of the vehicle also changes accordingly. Therefore, in such a technique, it is necessary to monitor the output torque of the vehicle according to the change in the weight of the vehicle, or rather, the change in the state of the vehicle. However, the technique described in Patent Document 1 does not consider the change in the state of the vehicle and cannot monitor the output torque of the vehicle according to the change in the state of the vehicle.

Means for Solving the Problems

[0006] The present disclosure can be realized in the following forms.

[0007] (1) According to a first embodiment of the present disclosure, a monitoring device is provided for monitoring a vehicle that is the subject of a plurality of processes in a factory where a plurality of processes are carried out to manufacture a vehicle that runs autonomously. The monitoring device comprises a process acquisition unit that acquires process information relating to a target process among the plurality of processes for the vehicle, a torque acquisition unit that acquires torque information relating to the output torque of the vehicle in the target process, and a detection unit that uses the process information and the torque information to detect an abnormality in the output torque of the vehicle. In this configuration, abnormalities in the vehicle's output torque are detected using process information and torque information. In a production method in which parts are assembled while an unfinished vehicle is driven, the vehicle's output torque can be monitored in accordance with changes in the vehicle's condition. (2) In the monitoring device of the above form, the detection unit may detect an abnormality in the output torque based on the output torque of the vehicle indicated by the torque information, the process indicated by the process information, and a torque standard set in correspondence with the process. In this configuration, abnormalities in output torque are detected using torque-related standards set in accordance with the process. Therefore, in a production method in which parts are assembled while an unfinished vehicle is running, the output torque of the vehicle can be monitored in accordance with changes in the vehicle's condition. (3) In the monitoring device of the above form, a threshold value for the output torque in the process is set as a criterion for the torque, and the detection unit may determine that there is an abnormality in the output torque of the vehicle when the value of the output torque is greater than the threshold value for the output torque. In this configuration, abnormalities in output torque can be easily detected using the output torque threshold set for each process. (4) In the monitoring device of the above form, the first threshold value of the output torque set for the first step of the plurality of steps may be set to a value smaller than the second threshold value of the output torque set for the second step which is performed after the first step. In a production method where parts are assembled onto an unfinished vehicle, the vehicle's weight gradually increases. This configuration allows for accurate detection of abnormalities in output torque by setting a higher threshold for output torque in later processes than in previous processes. (5) In the above-described monitoring device, the reference for torque may be a reference for a waveform representing the output torque acquired in a time series. This configuration allows for easy detection of abnormalities in output torque using a waveform that represents the time-series change of output torque. (6) The monitoring device of the above form further comprises a control command generation unit that generates a control command for remotely controlling the operation of the vehicle and transmits the generated control command to the vehicle, wherein the detection unit detects an abnormality in the output torque of the vehicle and notifies the control command generation unit that an abnormality in the output torque has been detected, and the control command generation unit, upon being notified of the abnormality in the output torque, generates a control command to stop the vehicle or to reduce the vehicle's speed to a speed lower than the current speed. In this configuration, if an abnormality in output torque is detected, the vehicle's operation can be appropriately controlled by stopping the vehicle or driving it at a low speed. (7) In the above-described form of monitoring device, the detection unit may further include a notification unit that notifies the vehicle if it detects an abnormality in the output torque of the vehicle. In this configuration, if an abnormality in output torque occurs in a moving vehicle, it is possible to quickly transition to appropriate vehicle operation control, such as stopping the vehicle. (8) A second embodiment of the present disclosure provides a method for monitoring a vehicle that is the subject of a plurality of processes in a factory where a plurality of processes are carried out to manufacture a vehicle that is driven by an unmanned vehicle. The method includes the steps of: obtaining process information relating to a target process among the plurality of processes for the vehicle; obtaining torque information indicating the output torque of the vehicle in the target process; and detecting an abnormality in the output torque of the vehicle using the process information and the torque information. In this configuration, abnormalities in the vehicle's output torque are detected using process information and torque information. In a production method in which parts are assembled while an unfinished vehicle is driven, the vehicle's output torque can be monitored in accordance with changes in the vehicle's condition.

[0008] Furthermore, this disclosure can be implemented in various forms, for example, as a remote control system, a vehicle control device, a remote automatic driving method, and a vehicle manufacturing method. [Brief explanation of the drawing]

[0009] [Figure 1] This is a conceptual diagram showing the system configuration in the first embodiment. [Figure 2] This is a block diagram showing the system configuration in the first embodiment. [Figure 3] This is a flowchart showing the processing procedure for vehicle driving control in the first embodiment. [Figure 4] This is a flowchart showing the processing procedure for torque monitoring. [Figure 5] This is a diagram representing a torque table. [Figure 6] This diagram explains the reason for setting thresholds for each process. [Figure 7] This is a flowchart showing the torque monitoring process procedure in the second embodiment. [Figure 8] This is an explanatory diagram showing an example of a waveform when a torque anomaly occurs. [Figure 9] This is a flowchart showing the torque monitoring process procedure in the third embodiment. [Figure 10] This is an explanatory diagram showing the schematic configuration of the system in the fourth embodiment. [Figure 11] This is a flowchart showing the processing procedure for vehicle driving control in the fourth embodiment. [Figure 12] This is a flowchart showing the processing procedure for torque monitoring. [Modes for carrying out the invention]

[0010] A. First Embodiment: FIG. 1 is a conceptual diagram showing the configuration of the system 50 in the first embodiment. The system 50 is used in the factory FC that manufactures the vehicle 100. The vehicle 100 is a battery electric vehicle (BEV). The vehicle 100 is the object of a plurality of processes carried out in the factory FC. The system 50 includes one or more vehicles 100, a server 200, and a plurality of external sensors 300. The external sensor 300 is a camera that photographs the vehicle 100. Note that the server 200 may also be referred to as a "monitoring device".

[0011] As described above, the vehicle 100 according to this embodiment is a battery electric vehicle (BEV), but the vehicles to which the monitoring device and the monitoring method according to the present disclosure can be applied are not limited to this. The vehicle in the present disclosure may be a vehicle that travels by wheels or a vehicle that travels on an endless track. For example, it may be a passenger car, a truck, a bus, a two-wheeled vehicle, a four-wheeled vehicle, a tank, a construction vehicle, etc. The vehicle includes battery electric vehicles (BEVs), gasoline vehicles, hybrid vehicles, and fuel cell vehicles.

[0012] The vehicle 100 can travel by autonomous driving. "Autonomous driving" means driving without depending on the driving operation of a passenger. The driving operation means an operation related to at least any one of "running", "turning", and "stopping" of the vehicle 100. Autonomous driving is realized by automatic or manual remote control using a device located outside the vehicle 100, or by autonomous control of the vehicle 100. A passenger who does not perform a driving operation may be on board the vehicle 100 traveling by autonomous driving. Passengers who do not perform a driving operation include, for example, a person simply sitting in the seat of the vehicle 100, or a person performing work different from the driving operation, such as assembly, inspection, and operation of switches, while on board the vehicle 100. Note that driving by the driving operation of a passenger may be called "human driving".

[0013] In this specification, "remote control" includes "fully remote control," in which all operations of the vehicle 100 are completely determined from outside the vehicle 100, and "partial remote control," in which some operations of the vehicle 100 are determined from outside the vehicle 100. Furthermore, "autonomous control" includes "fully autonomous control," in which the vehicle 100 autonomously controls its own operations without receiving any information from external devices, and "partial autonomous control," in which the vehicle 100 autonomously controls its own operations using information received from external devices.

[0014] Vehicle 100 is in a manufacturing state and travels unmanned within the factory FC where it is manufactured. The reference coordinate system of the factory FC is the global coordinate system GC. That is, any position within the factory FC is represented by X, Y, Z coordinates in the global coordinate system GC. The factory FC comprises a first location PL1, a second location PL2, and a third location PL3. The first location PL1, the second location PL2, and the third location PL3 are connected by a track TR on which vehicle 100 can travel. Multiple external sensors 300 are installed along the track TR in the factory FC. The positions of each external sensor 300 in the factory FC are pre-adjusted. Vehicle 100 moves unmanned from the first location PL1 to the second location PL2 via the track TR. Furthermore, vehicle 100 moves from the second location PL2 to the third location PL3 via the track TR.

[0015] Location PL1 is where the assembly of vehicle 100 takes place. Vehicle 100 assembled at Location PL1 is in a state where it can be driven autonomously; in other words, it is in a state where it can perform the three functions of "driving," "turning," and "stopping" autonomously.

[0016] In this embodiment, the vehicle 100 assembled at the first location PL1 travels from the first location PL1 to the second location PL2 by unmanned operation in the form of a platform having the configuration described below.

[0017] Specifically, in order for vehicle 100 to perform the three functions of "driving," "turning," and "stopping" through unmanned operation, it is sufficient to have at least a vehicle control device 110 and a group of actuators 120. If vehicle 100 acquires information from the outside for unmanned operation, vehicle 100 may also be equipped with a communication device 130. In other words, vehicle 100 that can move through unmanned operation is not fitted with at least some interior parts such as the driver's seat and dashboard, at least some exterior parts such as bumpers and fenders, or a body shell.

[0018] Locations PL2 and PL3 are where the assembly of parts onto the vehicle 100 is carried out. At locations PL2 and PL3, parts are assembled onto the vehicle 100, for example, by an assembly robot (not shown) or by a worker.

[0019] In the second location, PL2, the vehicle body, including the body shell and hood, interior components such as seats and dashboards, and exterior components such as bumpers and fenders are assembled onto the vehicle 100, which is in the form of a platform, for example, by an assembly robot. Each component may be attached from any direction, such as the top, bottom, front, rear, right, or left side of the vehicle 100, and they may be attached from the same direction or from different directions. In the third location, PL3, functional components are attached to the vehicle 100, for example, by a worker. The functional components are, for example, multiple ECUs.

[0020] Figure 2 is a block diagram showing the configuration of system 50. The vehicle 100 includes a vehicle control device 110 for controlling various parts of the vehicle 100, an actuator group 120 including one or more actuators driven under the control of the vehicle control device 110, a communication device 130 for communicating wirelessly with external devices such as a server 200, and a torque sensor 140.

[0021] The actuator group 120 includes actuators for the drive system to accelerate the vehicle 100, actuators for the steering system to change the direction of travel of the vehicle 100, and actuators for the braking system to decelerate the vehicle 100.

[0022] The vehicle control device 110 is comprised of a computer comprising 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, a communication device 130, and a torque sensor 140.

[0023] The processor 111 executes the program PG1 stored in the memory 112, thereby realizing various functions, including those of the vehicle control unit 115.

[0024] The torque sensor 140 is installed on the drive shaft of the vehicle 100 and detects the torque acting on the drive shaft. The torque acting on the drive shaft is also called the "output torque". Various torque sensors such as magnetostrictive, strain gauge, and capacitive sensors can be used as the torque sensor 140. The torque sensor 140 outputs an electrical signal representing the detected torque to the processor 111.

[0025] The vehicle control unit 115 can drive the vehicle 100 by controlling the actuator group 120 using the driving control signal received from the server 200. The driving control signal is a control signal for driving the vehicle 100. In this embodiment, the driving control signal includes the acceleration and steering angle of the vehicle 100 as parameters. Alternatively, the driving control signal may include the speed of the vehicle 100 as a parameter, either in place of or in addition to the acceleration of the vehicle 100. The vehicle control unit 115 is also called the "control command generation unit". The driving control signal is also called a "control command".

[0026] Furthermore, the vehicle control unit 115 transmits a torque value based on an electrical signal representing the torque supplied from the torque sensor 140 to the server 200 via the communication device 130.

[0027] Server 200 is comprised of a computer comprising a processor 201, memory 202, an input / output interface 203, and an internal bus 204. The processor 201, memory 202, and input / output interface 203 are connected bidirectionally via the internal bus 204.

[0028] A communication device 205 is connected to the input / output interface 203 for communicating with various devices outside the server 200. The communication device 205 can communicate with the vehicle 100 via wireless communication and with each external sensor 300 via wired or wireless communication. In other words, the server 200 can communicate with the vehicle 100 and the external sensors 300 via the communication device 205.

[0029] Memory 202 pre-stores the program PG2, the reference route RR indicating the route that vehicle 100 should travel, the detection model DM (described later), the torque table TT (described later), and other similar information. The processor 201 executes the program PG2 stored in the memory 202 to realize various functions, including those of a process acquisition unit 210, a torque acquisition unit 220, an anomaly detection unit 230, a position estimation unit 240, and a remote control unit 250.

[0030] The process acquisition unit 210 acquires process information relating to the target process for the vehicle 100. In this embodiment, the target process is the current process where the vehicle 100 is located. Here, the process information represents the current process where the vehicle 100 is located. The process information includes, for example, a process number that identifies the current process and a process name that represents the current process.

[0031] For example, the process acquisition unit 210 acquires process information from the upper-level server that represents the process in which the vehicle 100 is located. After each process is completed, for example, the worker may use a terminal device to send a notification to the upper-level server indicating the completion of the process. Therefore, the upper-level server has the most recently completed process for the vehicle 100.

[0032] The torque acquisition unit 220 acquires torque information relating to the torque of the vehicle 100 from the vehicle 100. Here, the torque information represents the current torque of the vehicle 100. In this specification, the torque of the vehicle 100 refers to the torque acting on the drive shaft, which is part of the torque required for the vehicle to run. In other words, the torque of the vehicle 100 refers to the torque generated by the motor that drives the drive shaft of the vehicle 100.

[0033] The abnormality detection unit 230 detects abnormalities in the torque of the vehicle 100 by using process information and torque information to determine whether the torque output by the vehicle 100 is in accordance with the current process. The abnormality detection unit 230 is also called the "detection unit".

[0034] The position estimation unit 240 estimates the position and orientation of the vehicle 100 using the detection results output from the external sensor 300. Alternatively, the position estimation unit 240 may estimate only one of the position or orientation of the vehicle 100 using the detection results output from the external sensor 300. In this case, for example, the other of the position and orientation of the vehicle 100 is determined using the vehicle 100's driving history or the like.

[0035] The remote control unit 250 acquires detection results from sensors, generates a driving control signal to control the actuator group 120 of the vehicle 100 using the detection results, and transmits the driving control signal to the vehicle 100, thereby driving the vehicle 100 by remote control. The remote control unit 250 may generate and output not only driving control signals, but also control signals to operate various auxiliary equipment and actuators that operate various devices such as wipers, power windows, and lamps, which are provided on the vehicle 100. In other words, the remote control unit 250 may operate these various devices and auxiliary equipment by remote control. In this specification, "remote control" includes "fully remote control," in which all operations of the vehicle 100 are completely determined from outside the vehicle 100, and "partial remote control," in which some operations of the vehicle 100 are determined from outside the vehicle 100.

[0036] The external sensor 300 is a sensor located outside the vehicle 100. The external sensor 300 is a sensor that detects the vehicle 100 from outside the vehicle 100. The external sensor 300 is equipped with a communication device (not shown) and can communicate with other devices such as the server 200 via wired or wireless communication. Specifically, the external sensor 300 consists of a camera installed on the factory premises. The camera as the external sensor 300 captures an image including the vehicle 100 and outputs the captured image as the detection result.

[0037] Figure 3 is a flowchart showing the processing procedure for controlling the movement of vehicle 100. The processing shown in Figure 3 is executed by the processor 201 of the server 200, which functions as a remote control unit 250, and the processor 111 of vehicle 100, which functions as a vehicle control unit 115. The processing shown in Figure 3 is repeatedly executed at predetermined time intervals, for example, from the moment vehicle 100 starts moving under remote control.

[0038] In step 1, the processor 201 of the server 200 acquires vehicle position information of the vehicle 100 using the detection results output from the external sensor 300. The vehicle position information is the position information that forms the basis for generating the 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. Specifically, in step 1, the processor 201 acquires vehicle position information using the captured image acquired from the camera, which is the external sensor 300.

[0039] In detail, in step 1, the processor 201 detects the outline of the vehicle 100 from the captured image, calculates the coordinates of the vehicle 100's positioning point in the coordinate system of the captured image, i.e., the local coordinate system, and obtains the position of the vehicle 100 by converting the calculated coordinates to coordinates in the global coordinate system GC. The outline of the vehicle 100 included in the captured image can be detected, for example, by inputting the captured image into a detection model DM that utilizes artificial intelligence. The detection model DM is prepared, for example, within or outside the system 50 and pre-stored in the memory 202 of the server 200. Examples of the detection model DM include a pre-trained machine learning model that has been trained to implement either semantic segmentation or instance segmentation. As this machine learning model, for example, a convolutional neural network (CNN) trained by supervised learning using a training dataset can be used. The training dataset has, for example, multiple training images including the vehicle 100 and labels indicating whether each region in the training image is a region indicating the vehicle 100 or a region indicating something other than the vehicle 100. During CNN training, it is preferable that the CNN parameters be updated using backpropagation to reduce the error between the output result of the detection model DM and the label. Furthermore, the processor 201 can obtain the orientation of vehicle 100 by, for example, using the optical flow method, estimating the orientation of the vehicle 100's movement vector calculated from the positional changes of the vehicle 100's feature points between frames of the captured image.

[0040] In step 2, the processor 201 of the server 200 determines the next target location that the vehicle 100 should head to. In this embodiment, the target location is represented by X, Y, Z coordinates in the global coordinate system GC. The memory 202 of the server 200 pre-stores a reference route RR, which is the path that the vehicle 100 should travel. The route is represented by a node indicating the starting point, nodes indicating waypoints, a node indicating the destination, and links connecting each node. The processor 201 uses the vehicle position information and the reference route RR to determine the next target location that the vehicle 100 should head to. The processor 201 determines the target location on the reference route RR beyond the vehicle 100's current location.

[0041] In step 3, the processor 201 of the server 200 generates a driving control signal to move the vehicle 100 toward the determined target position. The processor 201 calculates the vehicle's speed from the change in the vehicle's position and compares the calculated speed with the target speed. Overall, the processor 201 determines the acceleration so that the vehicle 100 accelerates if the speed is lower than the target speed, and determines the acceleration so that the vehicle 100 decelerates if the speed is higher than the target speed.

[0042] Here, the processor 201 determines an acceleration that generates torque corresponding to the weight of the vehicle 100. In this embodiment, parts are assembled onto the vehicle 100, which is running in a state of being under construction. As the parts are assembled, the state of the vehicle 100, including its overall weight and weight distribution, changes. This is because the torque required for the vehicle 100 to run differs depending on the change in the state of the vehicle 100.

[0043] Furthermore, the processor 201 determines the steering angle and acceleration so that the vehicle 100 does not deviate from the reference path RR if the vehicle 100 is located on the reference path RR, and determines the steering angle and acceleration so that the vehicle 100 returns to the reference path RR if the vehicle 100 is not located on the reference path RR, in other words, if the vehicle 100 has deviated from the reference path RR.

[0044] In step 4, the processor 201 of the server 200 transmits the generated driving control signal to the vehicle 100. The processor 201 repeats the process of acquiring the position of the vehicle 100, determining the target position, generating the driving control signal, and transmitting the driving control signal at predetermined intervals.

[0045] In step 5, the processor 111 of the vehicle 100 receives a driving control signal transmitted from the server 200. In step 6, the processor 111 of the vehicle 100 controls the actuator group 120 using the received driving control signal, thereby driving the vehicle 100 at the acceleration and steering angle indicated in the driving control signal. The processor 111 repeats the reception of the driving control signal and the control of the actuator group 120 at predetermined intervals. According to the system 50 in this embodiment, the vehicle 100 can be driven by remote control, and the vehicle 100 can be moved without using transport equipment such as cranes or conveyors.

[0046] Figure 4 is a flowchart showing the torque monitoring process. The process shown in Figure 4 is performed to monitor the torque of the vehicle 100 while it is in motion. The process shown in Figure 4 is performed by a processor 111 which functions as a vehicle control unit 115, and a processor 201 which functions as a process acquisition unit 210, a torque acquisition unit 220, and an abnormality detection unit 230.

[0047] In step 11, the processor 111 of the vehicle 100 acquires torque values ​​acting on the drive wheels of the vehicle 100 as torque information, based on electrical signals representing torque supplied from the torque sensor 140.

[0048] In step 12, the processor 111 transmits a signal indicating the torque value acting on the drive wheels of the vehicle 100 as torque information to the server 200. The processor 111 repeatedly executes steps 11 and 12 at predetermined time intervals, for example, from the time when the vehicle 100 starts driving under remote control.

[0049] In step 13, the processor 201 of the server 200 receives the torque value as torque information from the vehicle 100. The processing from step 13 onward is executed each time the server 200 receives torque information from the vehicle 100.

[0050] In step 14, the processor 201 queries a higher-level server (not shown) for process information and torque reference information for the vehicle 100, thereby obtaining process information for the vehicle 100 and torque reference information set in association with the process from the higher-level server. The process information represents the current process in which the vehicle 100 is located. The torque reference is also referred to as the "torque reference set in association with the process."

[0051] Furthermore, the torque criteria define whether the torque output by the vehicle 100 is appropriate for the current process. In this embodiment, the torque criteria set a torque threshold for each process. Figure 5 is a diagram showing the torque table TT which defines the torque thresholds. The torque table TT shows the correspondence between the processes performed on the vehicle 100 and the torque thresholds of the vehicle 100 in those processes. The torque table TT is pre-stored, for example, in the memory of a higher-level server.

[0052] The torque threshold set for each process represents the upper limit that the torque of the vehicle 100 should not exceed in each process. In the example shown in Figure 5, a torque threshold for the vehicle 100 is defined for each of the first to third processes. Since a torque threshold is set for each process, abnormalities in the output torque can be detected accurately according to the process. In step 14, in response to an inquiry from the processor 201, the higher-level server sends, for example, the torque threshold for the target process to the server 200. The torque table TT may also be stored in the memory 202 of the server 200. In this case, in step 14, the processor 201 only needs to query the higher-level server for process information in which the vehicle 100 is located.

[0053] Figure 6 is an explanatory diagram illustrating the reason for setting torque thresholds for each process. As mentioned above, parts are assembled onto the vehicle 100, which is in a partially manufactured state and is currently in motion. As a result, the weight of the vehicle 100 increases as the parts are assembled. Therefore, the torque required for the vehicle 100 to move differs depending on the process in which the vehicle 100 is located, i.e., according to the weight of the vehicle 100. The weight of the vehicle 100 in the second process, which is performed after the first process, is greater than the weight of the vehicle 100 in the first process. Therefore, the torque required for the vehicle 100 to move in the second process, which is performed after the first process, is greater than the torque required for the vehicle 100 to move in the first process. Furthermore, the weight of the vehicle 100 in the third process, which is performed after the second process, is greater than the weight of the vehicle 100 in the second process. Therefore, the torque required for the vehicle 100 to move in the third process, which is greater than the torque required for the vehicle 100 to move in the second process. In this embodiment, different values ​​are set as torque thresholds for the vehicle 100 for each process in order to accommodate the changes in the weight of the vehicle 100.

[0054] Furthermore, the torque threshold set for a particular process is set to be smaller than the torque threshold set for processes performed after that process. Let Th1 be the torque threshold for the first process, Th2 for the second process, and Th3 for the third process. The torque threshold Th1 for the first process is also called the "first threshold." The torque threshold Th2 for the second process is also called the "second threshold." The threshold Th2 for the second process is set to be larger than the threshold Th1 for the first process. Similarly, the threshold Th3 for the third process is set to be larger than the threshold Th2 for the second process. In this way, the torque threshold set for a particular process is set to be larger than the torque threshold set for processes performed before that process. In a production method in which parts are assembled onto an unfinished vehicle 100, the weight of the vehicle 100 gradually increases. Therefore, by setting the torque threshold for a particular process to be larger than the threshold for processes performed before that process, torque abnormalities can be detected with high accuracy.

[0055] The weight of vehicle 100 at the completion of each process is determined according to the type and number of parts assembled to vehicle 100 in that process. Based on the weight of vehicle 100 at the completion of each process, the torque required for vehicle 100 to run can be calculated. The torque thresholds for each process set in the torque table TT shown in Figure 5 are set according to the torque required for vehicle 100 to run in each process.

[0056] Furthermore, in this embodiment, the process in which the vehicle 100 is located is determined as follows. For example, in the example shown in Figure 1, the first process is performed at the first location PL1, the second process is performed at the second location PL2, and the third process is performed at the third location PL3.

[0057] If the first process has been completed for vehicle 100, then the assembly of parts to vehicle 100 in the first process is complete. In this case, it is determined that the current process for vehicle 100 is the first process. Also, if vehicle 100 is traveling on the track TR connecting the first location PL1 and the second location PL2, the first process has been completed, and therefore, it is determined that the current process for vehicle 100 is the first process.

[0058] Furthermore, if vehicle 100 enters the second location PL2 and the second process begins, but the second process is not yet completed, then the first process is at least completed. In this case, it is determined that vehicle 100 is currently in the first process.

[0059] If the second process has been completed for vehicle 100, then the assembly of parts to vehicle 100 in the second process is complete. In this case, it is determined that the current process for vehicle 100 is the second process. Also, if vehicle 100 is traveling on the track TR connecting the second location PL2 and the third location PL3, the second process has been completed, and therefore, it is determined that the current process for vehicle 100 is the second process.

[0060] Furthermore, if vehicle 100 enters location PL3 and the third process has begun, but the third process has not yet been completed, then the second process has at least been completed. In this case, it is determined that vehicle 100 is currently in the second process.

[0061] If the third process has been completed for vehicle 100, then the assembly of parts to vehicle 100 in the third process is complete. In this case, it is determined that the current process for vehicle 100 is the third process.

[0062] In step 15, as shown in Figure 4, the processor 201 determines whether there is an abnormality in the torque of the vehicle 100 based on whether the torque value supplied from the vehicle 100 is equal to or greater than a threshold set for the current process. For example, suppose the current process is the first process. In this case, the processor 201 determines whether the torque value supplied from the vehicle 100 is equal to or greater than a threshold Th1 set for the first process. The processor 201 determines that there is an abnormality in the torque if the torque value is equal to or greater than the threshold Th1. The processor 201 also determines that there is no abnormality in the torque if the torque value is less than the threshold Th1.

[0063] If the processor 201 determines that the torque value is above a set threshold, i.e., that there is an abnormality in the torque (step 15; YES), it executes the process in step 18. On the other hand, if the processor 201 determines that the torque value is below a set threshold, i.e., that the torque is normal (step 15; NO), the process shown in Figure 4 is terminated.

[0064] In step 18, the processor 201 generates a driving control signal for emergency stopping of the vehicle 100. The driving control signal for emergency stopping instructs the vehicle 100 to stop. The driving control signal includes a target stopping point, target deceleration, target steering angle, etc., which are calculated using the vehicle 100's current position, vehicle 100's speed, etc.

[0065] In step 20, the processor 201 transmits the generated emergency stop driving control signal to the vehicle 100. The processor 111 of the vehicle 100 receives the driving control signal transmitted from the server 200, similar to step 5 in Figure 3. The processor 111 of the vehicle 100 controls the operation of the vehicle 100 according to the driving control signal, similar to step 6 in Figure 3. As a result, the vehicle 100 stops. In this embodiment, the processor 201 changes the control of the vehicle 100 by stopping the operation of the vehicle 100 when an abnormality occurs in the torque of the vehicle 100. In this way, appropriate driving control of the vehicle 100 can be performed in response to the occurrence of an abnormality in output torque.

[0066] In this embodiment, torque abnormalities are detected depending on whether the torque of the vehicle 100 is appropriate for the current process. Therefore, in a production method in which parts are assembled while the unfinished vehicle 100 is running, the output torque of the vehicle can be monitored in accordance with changes in the state of the vehicle 100. Furthermore, abnormalities in output torque can be easily detected using the output torque threshold set for each process. In addition, in the case of a vehicle 100 that is being operated unmanned by remote control, if a torque abnormality occurs, appropriate vehicle operation control can be performed, such as stopping the unmanned operation by remote control.

[0067] B. Second Embodiment: In the second embodiment, the description will focus on configurations that differ from those of the first embodiment, and will omit the description of configurations similar to those of the first embodiment.

[0068] In the second embodiment, a different torque criterion is used to determine whether or not there is a torque abnormality. In the second embodiment, a torque abnormality is determined when at least a portion of the waveform representing the time-series change in the torque of the vehicle 100 corresponds to a preset pattern shape.

[0069] Figure 7 is a flowchart showing the torque monitoring process in the second embodiment. The process in Figure 7 is performed to monitor the torque of the vehicle 100 while it is in motion. The process shown in Figure 7 is performed by a processor 111 which functions as a vehicle control unit 115, and a processor 201 which functions as a process acquisition unit 210, a torque acquisition unit 220, and an abnormality detection unit 230. In Figure 7, the same reference numerals are used for processes that are the same as in the first embodiment. Also, the processes in steps 11 to 14 are the same as in the first embodiment, so their explanation is omitted.

[0070] In step 16, a waveform representing the time-series change in torque is used to determine whether or not there is an abnormality in the torque. Specifically, first, the processor 201 generates a waveform representing the time-series change in torque using torque values ​​received from the vehicle 100 over a certain period of time retrospectively from the present.

[0071] Figure 8 is an explanatory diagram showing an example of a waveform when a torque abnormality occurs. The processor 201 determines that there is a torque abnormality if at least a portion of the waveform representing the time-series change in torque includes a portion corresponding to a preset pattern shape. In this embodiment, the preset pattern shape is a straight line. In the example shown in Figure 8, in the area P1 enclosed by the dashed line in the second step, a portion of the waveform representing the change in torque is linear.

[0072] In step 16 shown in Figure 7, if the processor 201 determines that there is an abnormality in the torque (step 16; YES), it executes the process in step 18. On the other hand, if the processor 201 determines that the torque is normal (step 18; NO), the process shown in Figure 7 is terminated. Steps 18 and 20 are the same as in the first embodiment, so their explanation is omitted.

[0073] In this embodiment, the criterion for determining whether or not there is an abnormality is that the waveform representing the output torque acquired in a time series does not correspond to a preset pattern shape. Therefore, abnormalities in the output torque can be easily detected using the waveform representing the time-series change of torque. In a production method in which parts are assembled while an unfinished vehicle is driven, the output torque of the vehicle 100 can be monitored in accordance with changes in the state of the vehicle 100. Furthermore, in a vehicle 100 that is being operated unmanned by remote control, if an abnormality in torque occurs, appropriate vehicle operation control can be performed, such as stopping the unmanned operation by remote control.

[0074] C. Third Embodiment: In the first embodiment described above, the server 200 automatically generates a driving control signal to be transmitted to the vehicle 100. Alternatively, the processor 201 may generate a driving control signal to be transmitted to the vehicle 100 according to the operation of an external operator located outside the vehicle 100. For example, the external operator may operate a control device that includes a display for displaying 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 response to the operation applied to the control device. For example, the external operator may operate a control device that includes a display for displaying 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 vehicle control unit 115 of the server 200 generates a driving control signal in response to the operation applied to the control device.

[0075] Figure 9 is a flowchart showing the torque monitoring process in the third embodiment. The process shown in Figure 9 is performed by a processor 111 that functions as a vehicle control unit 115, and a processor 201 that functions as a process acquisition unit 210, a torque acquisition unit 220, and an anomaly detection unit 230. In Figure 9, the same reference numerals are used for processes that are the same as in the first embodiment. Also, the processes in steps 11 to 15 are the same as in the first embodiment, so their explanation is omitted.

[0076] If the processor 201 determines that there is an abnormality in the torque (step 15; YES), it executes the process in step 19. Specifically, the processor 201 determines that there is an abnormality in the torque if the torque value is greater than or equal to the threshold set for the current process. On the other hand, if the processor 201 determines that there is no abnormality in the torque (step 15; NO), the process shown in Figure 9 is terminated.

[0077] In step 19, the processor 201 outputs an image to the display used by the operator to remotely control the vehicle 100, notifying the operator that an abnormality has occurred in the torque and instructing them to make an emergency stop of the vehicle 100. As a result, the operator stops the vehicle 100 in accordance with the emergency stop instruction. After that, the process shown in Figure 9 is completed.

[0078] In this embodiment, as in the first embodiment, abnormalities in the output torque are detected depending on whether the output torque of the vehicle 100 corresponds to the current process. Therefore, in a production method in which parts are assembled while an unfinished vehicle is driven, the output torque of the vehicle 100 can be monitored in accordance with changes in the state of the vehicle 100. Furthermore, if an abnormality in torque occurs in a vehicle 100 that is being operated unmanned by remote control, appropriate vehicle operation control can be performed, such as stopping the unmanned operation by remote control.

[0079] D. Fourth Embodiment: Figure 10 is an explanatory diagram showing the schematic configuration of system 50v in the fourth embodiment. In this embodiment, system 50v differs from the first embodiment in that it does not have a server 200. Also, in this embodiment, vehicle 100v can be driven by autonomous control of vehicle 100v. The other configurations are the same as in the first embodiment unless otherwise specified. The vehicle control device 110v is composed of a computer that includes a processor 111v, memory 112v, input / output interface 113, and internal bus 114. The following description will focus on the configurations that differ from the first embodiment, and the description of similar configurations will be omitted.

[0080] Memory 112v pre-stores the program PG1v, the reference route RR indicating the route that vehicle 100 should travel, the detection model DM, the torque table TT, and other information.

[0081] In this embodiment, the processor 111v of the vehicle control device 110v functions as the vehicle control unit 115v, process acquisition unit 121, torque acquisition unit 122, abnormality detection unit 123, and position estimation unit 124 by executing the program PG1 stored in the memory 112v.

[0082] The vehicle control unit 115v acquires output results from sensors, generates a driving control signal using the output results, and outputs the generated driving control signal to operate the actuator group 120, thereby enabling the vehicle 100v to be driven autonomously.

[0083] The process acquisition unit 121 acquires process information indicating the current process in which the vehicle 100 is located, similar to the process acquisition unit 210 in the first embodiment. The torque acquisition unit 122 acquires torque information related to the torque of the vehicle 100, similar to the torque acquisition unit 220 in the first embodiment. The abnormality detection unit 123 detects abnormalities in the torque of the vehicle 100 by using the process information and torque information to determine whether the torque output by the vehicle 100 corresponds to the current process, similar to the abnormality detection unit 230 in the first embodiment. The position estimation unit 124 estimates the position and orientation of the vehicle 100 using the detection results output from the external sensor 300, similar to the position estimation unit 240 in the first embodiment.

[0084] Figure 11 is a flowchart showing the processing procedure for vehicle 100V's driving control in the fourth embodiment. A processor 111V, which functions as a vehicle control unit 115V, executes the processing shown in Figure 11.

[0085] In step 101, the processor 111v acquires vehicle position information using the detection results output from the camera, which is an external sensor 300. In step 102, the processor 111v determines the target position to which the vehicle 100v should next head. In step 103, the processor 111v generates a driving control signal to drive the vehicle 100v toward the determined target position. In step 104, the processor 111v controls the actuator group 120 using the generated driving control signal to drive the vehicle 100v according to the parameters expressed in the driving control signal. The processor 111v 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 in this embodiment, the vehicle 100v can be driven by autonomous control of the vehicle 100v without remote control of the vehicle 100v by the server 200.

[0086] Figure 12 is a flowchart showing the torque monitoring process. The process shown in Figure 12 is executed by the processor 111v, which functions as a vehicle control unit 115v, a process acquisition unit 121, a torque acquisition unit 122, and an anomaly detection unit 123.

[0087] In step 211, the processor 111v acquires torque information, which is the torque value acting on the drive wheels of the vehicle 100, based on the electrical signal representing the torque supplied from the torque sensor 140. The processor 111v repeatedly executes the processes from step 211 onward at predetermined intervals, for example, from the time the vehicle 100 starts moving.

[0088] In step 214, the processor 111v obtains process information about the vehicle 100 by querying a higher-level server (not shown) for process information about the vehicle 100. The process information represents the current process in which the vehicle 100 is located.

[0089] In step 215, the processor 111v refers to the torque table TT stored in memory 202 and determines whether there is an abnormality in the torque of the vehicle 100, depending on whether the torque value is greater than or equal to the threshold set for the current process. If the processor 111v determines that the torque value is above the threshold set for the current process (step 215; YES), it executes the process in step 218. On the other hand, if the processor 201 determines that the torque value is below the threshold (step 215; NO), the process shown in Figure 12 is terminated.

[0090] In step 218, the processor 111v generates a driving control signal for emergency stopping of the vehicle 100. The driving control signal includes a target stopping point, target deceleration, target steering angle, etc., which are calculated using the current position of the vehicle 100, the speed of the vehicle 100, etc.

[0091] In step 220, the processor 111v controls the actuator group 120 using the generated driving control signal, thereby stopping the vehicle 100v from running according to the parameters expressed in the driving control signal. In this embodiment as well, the vehicle 100v is stopped if an abnormality occurs in the torque of the vehicle 100v. Therefore, appropriate operation control of the vehicle 100v can be performed. Furthermore, an abnormality in torque is detected depending on whether the torque of the vehicle 100v is appropriate for the current process. For this reason, in a production method in which parts are assembled while the unfinished vehicle 100v is running, the output torque of the vehicle can be appropriately monitored in accordance with changes in the state of the vehicle 100v. Furthermore, an abnormality in output torque can be easily detected using the output torque threshold set for each process. In addition, if an abnormality in torque occurs in the vehicle 100 which is autonomously operating without a driver, appropriate operation control of the vehicle can be performed, such as stopping the autonomous unmanned operation.

[0092] E. Other embodiments: (E1) In the second embodiment described above, an example was given in which the pattern shape set for the waveform representing the time-series change of torque is linear in order to detect an abnormality in torque. However, other shapes can be adopted as the set pattern shape. For example, it may be a needle-shaped waveform that indicates that the torque changed rapidly over a predetermined short period of time. In this case, it may be a waveform that indicates that the torque increased rapidly and then decreased, or a waveform that indicates that the torque decreased rapidly and then increased. Multiple pattern shapes may be defined in order to detect an abnormality in torque. In the configurations according to the first, third, and fourth embodiments, the method for detecting an abnormality in torque described in the other embodiment (E1) may be adopted.

[0093] Furthermore, in the second embodiment, regardless of the process, it was determined whether a portion of the waveform representing the time-series change of torque corresponds to a predefined pattern shape. However, if multiple pattern shapes are defined, the combination of pattern shapes for detecting abnormalities may differ for each process.

[0094] (E2) In addition, the method for detecting a torque anomaly when a part of the waveform representing the time-series change of torque described in the second embodiment corresponds to a preset pattern shape and the method for detecting a torque anomaly using a set threshold described in the first embodiment may be used in combination. Similarly, in the configurations according to the third and fourth embodiments, the above two methods may also be used in combination.

[0095] (E3) In addition, for example, if a sudden fluctuation in torque occurs, it may be determined that there is an abnormality in the torque. Specifically, if the slope of the waveform representing the time-series change of torque (the slope of the tangent at a certain point) is greater than or equal to a threshold, it may be determined that there is an abnormality in the torque.

[0096] For example, suppose the time required to reach the target torque value in the first step is approximately the same as the time required to reach the target torque value in the second step. In this case, the slope of the waveform representing the torque change in the later second step tends to be greater than the slope of the waveform representing the torque change in the earlier first step. The weight of vehicle 100 before the first step is greater than the weight of vehicle 100 after the first step. Therefore, the torque required for vehicle 100 to run after the first step is greater. Thus, it is desirable to set a threshold value for the waveform slope according to the weight of the vehicle, that is, according to the step. Specifically, the threshold value for the waveform slope in the later step is greater than the threshold value for the waveform slope in the earlier step. In the first, third, and fourth embodiments, the method for detecting torque abnormalities described in another embodiment (E3) may be employed.

[0097] (E4) In the first, second, and fourth embodiments, an example was described in which the processor 201, acting as the remote control unit 250, causes the vehicle 100 to be brought to an emergency stop by transmitting a driving control signal for emergency stopping of the vehicle 100 to the vehicle 100 when there is an abnormality in the torque. Alternatively, the processor 201 may generate a driving control signal instructing the vehicle 100 to decelerate and transmit the generated driving control signal to the vehicle 100. In this case, it is desirable that the speed after deceleration be very low. The vehicle 100, upon receiving the driving control signal, decelerates and drives. When an abnormality occurs in the torque of the vehicle 100, the processor 201 changes the control content of the vehicle 100 by causing the vehicle 100 to drive at a low speed. In this way, appropriate driving control of the vehicle 100 can be performed in response to the occurrence of an abnormality in the output torque.

[0098] Alternatively, the processor 201 may send a driving control signal to the vehicle 100 instructing it to decelerate, and then, after a certain period of time has elapsed, send a driving control signal to the vehicle 100 instructing it to stop. In this case, the vehicle 100 will first decelerate and then come to a stop. The processor 201 can perform appropriate driving control of the vehicle 100 by making the vehicle 100 run at a low speed if an abnormality occurs in the torque of the vehicle 100.

[0099] (E5) In the fourth embodiment, a configuration was described in which the vehicle 100v itself detects an abnormality in output torque. Alternatively, the processor 201, which functions as an abnormality detection unit 230 of the server 200 as described in the first embodiment, may detect an abnormality in the output torque of the vehicle 100v. In this case, the vehicle control unit 115v of the vehicle 100v periodically transmits a torque value based on an electrical signal representing the torque supplied from the torque sensor 140 to the server 200.

[0100] When the processor 201 of the server 200 detects an abnormality in the torque of vehicle 100v, instead of generating a driving control signal for emergency stop as in the first embodiment, it notifies that an abnormality in torque has been detected. In this case, the processor 201 functions as a notification unit that notifies that an abnormality in the torque of vehicle 100v has been detected. Furthermore, the processor 201 may also notify the higher-level server that there is an abnormality in the torque of vehicle 100v. The higher-level server may notify the operator of the current position of vehicle 100v and the occurrence of the torque abnormality. This allows, for example, the operator to quickly take necessary action on vehicle 100v after it has stopped.

[0101] When the server 200 notifies vehicle 100v that an abnormality in vehicle 100v's torque has been detected, vehicle 100v changes its control settings by stopping its movement. Alternatively, vehicle 100v may change its control settings to low-speed driving. If an abnormality in torque occurs in vehicle 100v while it is driving autonomously, appropriate vehicle operation control can be performed, such as stopping autonomous operation.

[0102] (E6) In the first and second embodiments, when the server 200 detected an abnormal torque, it output a signal indicating that an abnormal torque had been detected by transmitting a driving control signal for emergency stop to the vehicle 100. Alternatively, the server 200 may transmit a driving control signal for emergency stop to the vehicle 100 and also notify the higher-level server, workers in the factory FC, etc., that an abnormal torque has been detected, thereby outputting a signal indicating that an abnormal torque has been detected. This allows, for example, workers to quickly take necessary actions on the vehicle 100 after it has stopped.

[0103] In the third embodiment, the server 200 may also output a signal indicating that a torque anomaly has been detected by notifying the upper-level server and the workers in the factory FC of an instruction to emergency stop the vehicle 100, and by informing them that a torque anomaly has been detected. This allows, for example, the workers to quickly take necessary action on the vehicle 100 after it has stopped.

[0104] Furthermore, in the fourth embodiment, the vehicle 100v may perform control to emergency stop the vehicle 100 and output a signal indicating that a torque abnormality has been detected, thereby notifying the higher-level server and the workers in the factory FC that a torque abnormality has been detected. This allows, for example, the workers to quickly take necessary actions on the vehicle 100v after it has stopped.

[0105] (E7) In the first embodiment, an example was described in which, because the weight of the vehicle 100 is gradually increasing, the torque threshold in a certain process is made greater than the threshold in a process performed before that process.

[0106] However, the torque threshold in a given process may be lower than the threshold performed in a preceding process. For example, in process A, a worker assembles parts while riding in vehicle 100. Upon completion of process A, the worker dismounts from vehicle 100. In process B, which follows process A, a robot may assemble parts without riding in vehicle 100. In this case, the weight of vehicle 100 in process B is less than the weight of vehicle 100 with the worker riding in it during process A, which precedes process B. In such cases, a torque threshold is set for each process according to the expected weight of vehicle 100, or the combined weight of vehicle 100 and the worker.

[0107] (E8) In addition, in the torque table TT shown in Figure 5, an upper limit of torque was set as a threshold. However, in the torque table TT, both an upper and lower limit of torque may be set as thresholds. The lower limit represents the threshold below which it is undesirable for the torque of the vehicle 100 to fall in each process. In this case, the server 200 can detect a torque anomaly even if the torque necessary for driving is not being produced in the relevant process.

[0108] (E9) In each of the above embodiments, the external sensor 300 is a camera. However, the external sensor 300 does not have to be a camera; for example, the external sensor 300 may be a LiDAR (Light Detection And Ranging) as a distance measuring device. In this case, the detection result output by the external sensor 300 may be 3D point cloud data representing the vehicle 100. In this case, the server 200 and the vehicle 100 may acquire vehicle position information by template matching using the 3D point cloud data as the detection result and pre-prepared reference point cloud data.

[0109] (E10) In the first embodiment described above, the server 200 performs the processing from acquiring vehicle position information to generating a driving control signal. Alternatively, the vehicle 100 may perform at least a part of the processing from acquiring vehicle position information to generating a driving control signal. For example, the following forms (1) to (3) may be used.

[0110] (1) The server 200 may acquire vehicle location information, determine the next target location that vehicle 100 should head to, and generate a route from the vehicle 100's current location, as shown in the acquired vehicle location information, to the target location. The server 200 may generate a route to the target location between the current location and the destination, or it may generate a route to the destination. The server 200 may transmit the generated route to vehicle 100. Vehicle 100 may generate a driving control signal so that vehicle 100 travels along the route received from the server 200, and may use the generated driving control signal to control the actuator group 120.

[0111] (2) The server 200 may acquire vehicle location information and transmit the acquired vehicle location information to the vehicle 100. The vehicle 100 may determine the next target location to which the vehicle 100 should go, generate a route from the vehicle 100's current location shown in the received vehicle location information to the target location, generate a driving control signal so that the vehicle 100 travels along the generated route, and control the actuator group 120 using the generated driving control signal.

[0112] (3) In the embodiments of (1) and (2) above, the vehicle 100 is equipped with internal sensors, and the detection results output from the internal sensors may be used in at least one of the generation of a route and the generation of a driving control signal. The internal sensors are sensors mounted on the vehicle 100. The internal sensors may include, for example, sensors that detect the motion state of the vehicle 100, sensors that detect the operating state of each part of the vehicle 100, and sensors that detect the environment around the vehicle 100. Specifically, the internal sensors may include, for example, cameras, LiDAR, millimeter-wave radar, ultrasonic sensors, GPS sensors, acceleration sensors, gyroscopes, etc. For example, in the embodiment of (1) above, the server 200 may acquire the detection results of the internal sensors and reflect the detection results of the internal sensors in the route when generating a route. In the embodiment of (1) above, the vehicle 100 may acquire the detection results of the internal sensors and reflect the detection results of the internal sensors in the driving control signal when generating a driving control signal. In the embodiment of (2) above, the vehicle 100 may acquire the detection results of the internal sensors and reflect the detection results of the internal sensors in the route when generating a route. In the embodiment described in (2) above, the vehicle 100 may acquire the detection results of the internal sensors and reflect the detection results of the internal sensors in the driving control signal when generating the driving control signal.

[0113] (E11) In the above embodiment 4, the vehicle 100v is equipped with an internal sensor, and the detection result output from the internal sensor may be used in at least one of the generation of the route and the generation of the driving control signal. For example, the vehicle 100v may acquire the detection result from the internal sensor and reflect the detection result from the internal sensor in the route when generating the route. The vehicle 100v may acquire the detection result from the internal sensor and reflect the detection result from the internal sensor in the driving control signal when generating the driving control signal.

[0114] (E12) In the fourth embodiment described above, the vehicle 100v acquires vehicle position information using the detection results of the external sensor 300. Alternatively, the vehicle 100v may be equipped with an internal sensor, which may acquire vehicle position information using the detection results of the internal sensor, determine the next target location to which the vehicle 100v should go, generate a route from the vehicle 100v's current location to the target location as shown in the acquired vehicle position information, generate a driving control signal for driving along the generated route, and control the actuator group 120 using the generated driving control signal. In this case, the vehicle 100v can drive without using the detection results of the external sensor 300 at all. The vehicle 100v may also acquire target arrival time and congestion information from outside the vehicle 100v and reflect the target arrival time and congestion information in at least one of the route and the driving control signal. Furthermore, all the functional configurations of the system 50v may be provided in the vehicle 100v. That is, the processing realized by the system 50v in this disclosure may be realized by the vehicle 100v alone.

[0115] (E13) Vehicle 100 may be manufactured by combining multiple modules. A module means a unit composed of multiple parts grouped together according to the part or function of vehicle 100. For example, the platform of vehicle 100 may be manufactured by combining a front module that constitutes the front part of the platform, a central module that constitutes the central part of the platform, and a rear module that constitutes the rear part of the platform. The number of modules that constitute the platform is not limited to three, but may be two or fewer, or four or more. In addition to, or instead of, the parts that constitute the platform may be modularized, as well as parts that constitute parts of vehicle 100 that are different from the platform. Furthermore, various modules may include any exterior parts such as bumpers and grilles, or any interior parts such as seats and consoles. Such modules may be manufactured, for example, by joining multiple parts by welding or fasteners, or by integrally molding at least a part of the parts that constitute the module as a single part by casting. Molding methods that integrally mold a single part, especially a relatively large part, are also called gigacast or megacast. For example, the forward, central, and rear modules mentioned above may be manufactured using Gigacast.

[0116] (E14) Transporting vehicle 100 using the unmanned operation of vehicle 100 is also called "autonomous transport." The configuration for realizing autonomous transport is also called a "vehicle remote control autonomous driving transport system." Furthermore, a production method that uses autonomous transport to produce vehicle 100 is also called "autonomous production." In autonomous production, for example, at a factory FC that manufactures vehicle 100, at least a portion of the transport of vehicle 100 is realized by autonomous transport.

[0117] (E15) In each of the above embodiments, some or all of the functions and processes implemented in software may be implemented in hardware. Also, some or all of the functions and processes implemented in hardware may be implemented in software. As hardware for implementing the various functions in each of the above embodiments, various circuits such as integrated circuits and discrete circuits may be used.

[0118] This disclosure is not limited to the embodiments described above, and can be implemented in various configurations without departing from its spirit. For example, the technical features in the embodiments corresponding to the technical features in each form described in the summary of the invention can be replaced or combined as appropriate in order to solve the problems described above or to achieve some or all of the effects described above. Furthermore, if a technical feature is not described as essential in this specification, it can be deleted as appropriate. [Explanation of symbols]

[0119] 50, 50V... System, 100, 100V... Vehicle, 110, 110V... Vehicle control device, 111, 111V... Processor, 112, 112V... Memory, 113... Input / Output interface, 114... Internal bus, 115... Vehicle control unit, 115V... Vehicle control unit, 120... Actuator group, 121... Process acquisition unit, 122... Torque acquisition unit, 123... Anomaly detection unit, 124... Position estimation unit, 130... Communication device, 140... Torque sensor, 200... Server, 201... Processor, 202... Memory, 20 3…Input / Output Interface, 204…Internal Bus, 205…Communication Device, 210…Process Acquisition Unit, 220…Torque Acquisition Unit, 230…Anomaly Detection Unit, 240…Position Estimation Unit, 250…Remote Control Unit, 300…External Sensor, DM…Detection Model, FC…Factory, GC…Global Coordinate System, P1…Range, PG1, PG1v, PG2…Program, PL1…First Location, PL2…Second Location, PL3…Third Location, RR…Reference Path, TR…Track, TT…Torque Table, Th1…Threshold, Th2…Threshold, Th3…Threshold

Claims

1. In a factory where multiple processes are carried out to manufacture a vehicle that operates autonomously, a monitoring device for monitoring the vehicle which is the subject of the multiple processes, It comprises a processor and memory for storing programs, The processor executes the program, For the aforementioned vehicle, process information relating to the target process among the multiple processes is acquired. Torque information relating to the output torque of the vehicle in the aforementioned process is acquired. By comparing the torque information with the torque reference pre-associated with the target process shown in the process information, an abnormality in the output torque of the vehicle is detected. The aforementioned steps include a first step in which parts are assembled onto the vehicle, and a second step performed after the first step. The torque criteria include a first criterion associated with the first process and a second criterion associated with the second process, which is different from the first criterion. The aforementioned processor, If the target process indicated in the process information is the first process, an abnormality in the output torque of the vehicle is detected by comparing the torque information with the first reference. If the target process indicated in the process information is the second process, the abnormality of the output torque of the vehicle is detected by comparing the torque information with the second reference. monitoring equipment.

2. A monitoring device according to claim 1, As a criterion for the torque, a threshold value for the output torque in the process is set. The processor determines that there is an abnormality in the output torque of the vehicle when the output torque value is greater than the output torque threshold. monitoring equipment.

3. A monitoring device according to claim 2, A first threshold value for the output torque set for the first step is set to be smaller than a second threshold value for the output torque set for the second step. monitoring equipment.

4. A monitoring device according to claim 1, The aforementioned torque criterion is a criterion for the waveform representing the output torque acquired in a time series. monitoring equipment.

5. A monitoring device according to any one of claims 1 to 4, When the processor detects an abnormality in the output torque of the vehicle, it generates a control command for controlling the vehicle's movement, which is to stop the vehicle or to reduce the vehicle's speed to a speed lower than the current speed, and transmits the generated control command to the vehicle. monitoring equipment.

6. A monitoring device according to claim 1, The processor, upon detecting an abnormality in the output torque of the vehicle, notifies the workers in the factory accordingly. monitoring equipment.

7. A method performed by a computer in a factory where multiple processes are carried out to manufacture a vehicle that operates autonomously, for monitoring the vehicle which is the subject of the multiple processes, The steps include: acquiring process information for the vehicle in question, relating to a target process among the multiple processes; A step of acquiring torque information indicating the output torque of the vehicle in the aforementioned process, A step of detecting an abnormality in the output torque of the vehicle by comparing the torque information with a torque reference that has been pre-associated with the target process shown in the process information, Includes, The aforementioned steps include a first step in which parts are assembled onto the vehicle, and a second step performed after the first step. The torque criteria include a first criterion associated with the first process and a second criterion associated with the second process, which is different from the first criterion. In the step of detecting an abnormality in the output torque of the vehicle, If the target process indicated in the process information is the first process, an abnormality in the output torque of the vehicle is detected by comparing the torque information with the first reference. If the target process indicated in the process information is the second process, the abnormality of the output torque of the vehicle is detected by comparing the torque information with the second reference. method.

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