Vehicle manufacturing system, vehicle manufacturing method, and control device

Abstract

This disclosure provides a vehicle manufacturing system, a vehicle manufacturing method, and a control device that can appropriately control a vehicle. [Solution] The vehicle manufacturing system 50 according to the present disclosure is a vehicle manufacturing system that controls the movement of multiple vehicles during a manufacturing process or a transport process, and comprises: multiple cameras that capture images of the driving area on which the vehicles travel and its surroundings; a flashing control unit 253 that controls the lights of the vehicles so that the vehicles flash multiple lights according to a flashing pattern; and a recognition unit 255 that recognizes the flashing pattern of the lights based on images captured by at least two cameras when multiple lights are not captured by one camera.

Description

Technical Field

[0006] ,

[0001] The present disclosure relates to a vehicle manufacturing system, a vehicle manufacturing method, and a control device.

Background Art

[0002] Patent Document 1 discloses a remote control device for remotely controlling a moving object. This remote control device acquires three-dimensional point cloud data measured by a distance measuring device. The remote control device estimates the position and orientation of the moving object by matching a template point cloud indicating the moving object to the three-dimensional point cloud data.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In a vehicle manufacturing factory, a plurality of vehicles travel along a conveyance path and are sequentially manufactured. Therefore, productivity can be improved. On the other hand, it is desirable to appropriately control a plurality of vehicles traveling on the conveyance path.

[0005] Therefore, an object of the present disclosure is to provide a vehicle manufacturing system, a vehicle manufacturing method, and a control device that can appropriately control a vehicle.

Means for Solving the Problems

[0006] The vehicle manufacturing system according to this disclosure is a vehicle manufacturing system that controls the movement of a plurality of vehicles during a manufacturing process or a transport process, and comprises: a plurality of cameras that capture images of a driving area on which the vehicles travel and its surroundings; a flashing control unit that controls the lights of the vehicles so that the vehicles flash a plurality of lights according to a flashing pattern; and a recognition unit that recognizes the flashing pattern of the lights based on images captured by at least two cameras when the plurality of lights are not captured by one of the cameras.

[0007] In the above-described vehicle manufacturing system, the flashing control unit may control the lights of the plurality of vehicles so that the flashing pattern differs depending on the vehicle, and the recognition unit may identify the vehicle based on the flashing pattern.

[0008] In the vehicle manufacturing system described above, the flashing control unit may recognize the flashing pattern in accordance with the switching timing at which the multiple lights are switched on and off.

[0009] The plurality of lights may include the left and right lights of the vehicle, and the switching timing may be different for the left and right lights.

[0010] In the above-described vehicle manufacturing system, the plurality of cameras may include an on-board camera mounted on the vehicle, and the on-board camera may capture images of surrounding vehicles traveling around the vehicle on which the on-board camera is mounted, and the on-board vehicle may recognize the flashing patterns of the lights of the surrounding vehicles.

[0011] In the vehicle manufacturing system described above, the multiple lights may be illuminated at the start and end timings of the flashing pattern.

[0012] The vehicle manufacturing method according to this disclosure is a vehicle manufacturing method for controlling the movement of a plurality of vehicles during a manufacturing process or a transport process, comprising: a step of imaging a driving area on which the vehicles are traveling and its surroundings with a plurality of cameras; a step of controlling the lights of the vehicles so that the vehicles flash a plurality of lights according to a flashing pattern; and a step of recognizing the flashing pattern of the lights based on images captured by at least two cameras if the plurality of lights are not captured by one of the cameras.

[0013] In the above-described vehicle manufacturing system, the lights of the multiple vehicles may be controlled so that the flashing pattern differs depending on the vehicle, and the vehicle may be identified based on the flashing pattern.

[0014] In the vehicle manufacturing system described above, the flashing pattern may be recognized according to the switching timing at which the multiple lights are switched on and off.

[0015] In the vehicle manufacturing system described above, the plurality of lights may include the left and right lights of the vehicle, and the switching timing may be different for the left and right lights.

[0016] In the above-described vehicle manufacturing system, the plurality of cameras may include an on-board camera mounted on the vehicle, and the on-board camera may capture images of surrounding vehicles traveling around the vehicle on which the on-board camera is mounted, and the on-board vehicle may recognize the flashing patterns of the lights of the surrounding vehicles.

[0017] In the vehicle manufacturing system described above, the multiple lights may be illuminated at the start and end timings of the flashing pattern.

[0018] The control device according to the present disclosure is a vehicle control device that controls the running of a plurality of vehicles during a manufacturing process or a transportation process, and includes an imaging image acquisition unit that acquires imaging images of a running area where the vehicles run and its surroundings from a plurality of cameras, a blinking control unit that controls the lights of the vehicles so that the vehicles blink a plurality of lights according to a blinking pattern, and a recognition unit that recognizes the blinking pattern of the lights based on the imaging images captured by at least two cameras when the plurality of lights are not imaged by one of the cameras.

[0019] In the above control device, the lights of the plurality of vehicles may be controlled so that the blinking pattern differs according to the vehicle, and the vehicle may be identified based on the blinking pattern.

[0020] In the above control device, the blinking pattern may be recognized according to the switching timing of the on and off of the plurality of lights.

[0021] In the above control device, the plurality of lights may include left and right lights of the vehicle, and the switching timing may be different between the left and right lights.

[0022] In the above control device, the plurality of cameras may include in-vehicle cameras mounted on the vehicle, and the in-vehicle cameras may image surrounding vehicles running around the vehicle on which the in-vehicle cameras are mounted, and the blinking pattern of the lights of the surrounding vehicles may be recognized in the vehicle on which the in-vehicle cameras are mounted.

[0023] In the above control device, the plurality of lights may be lit at the start timing and the end timing of the blinking pattern.

Advantages of the Invention

[0024] According to the present disclosure, a vehicle manufacturing system, a vehicle manufacturing method, and a control device that can appropriately control a vehicle can be provided.

Brief Description of the Drawings

[0025] [Figure 1] It is a schematic diagram showing the overall configuration of a vehicle manufacturing system. [Figure 2] It is a schematic diagram showing a part of the vehicle manufacturing system. [Figure 3] It is a plan view schematically showing the arrangement of a vehicle in motion and sensors. [Figure 4] It is a block diagram showing the control system of the vehicle manufacturing system. [Figure 5] It is a diagram showing the timing of the blinking pattern. [Figure 6] It is a flowchart showing a vehicle manufacturing method. [Figure 7] It is a plan view schematically showing the arrangement of a vehicle in motion and in-vehicle sensors. [Figure 8] It is a diagram for explaining the travel control of a vehicle. [Figure 9] It is a control block diagram for explaining Travel Control Example 1. [Figure 10] It is a flowchart for explaining Travel Control Example 1. [Figure 11] It is a control block diagram for explaining Travel Control Example 2. [Figure 12] It is a flowchart for explaining Travel Control Example 2.

Mode for Carrying Out the Invention

[0026] Hereinafter, embodiments of the present invention will be described with reference to the drawings. However, the invention according to the claims is not limited to the following embodiments. Also, not all of the configurations described in the embodiments are essential as means for solving the problems. For clarity of explanation, the following description and drawings have been appropriately omitted and simplified. In each drawing, the same elements are denoted by the same reference numerals, and duplicate explanations are omitted as necessary.

[0027] Embodiment 1 (Vehicle Manufacturing System) The vehicle manufacturing system 50 according to this embodiment will be described with reference to Figures 1 and 2. Figure 1 is a schematic diagram showing the configuration of the vehicle manufacturing system 50. Figure 2 is a schematic diagram showing two vehicles 100 in motion. Note that in Figure 1, an XY Cartesian coordinate system is shown for illustrative purposes.

[0028] The vehicle manufacturing system (also simply called the system) 50 is used in a vehicle manufacturing plant to manufacture vehicles 100. Alternatively, the vehicle manufacturing system 50 is also used at transport locations where transport processes such as transport to yards or loading onto ships are carried out. As shown in Figure 1, the vehicle manufacturing system 50 includes a server 200, a sensor 300, and a robot 600. Multiple vehicles 100 are self-propelled vehicles that can move on their own during the manufacturing process. The vehicle manufacturing system 50 controls the multiple vehicles 100 to move in a convoy.

[0029] Sensor 300 is equipped with a communication device 330 that sends and receives data to and from server 200. Server 200 is equipped with a communication device 230 that sends and receives data to and from sensor 300. Furthermore, as shown in Figure 2, the communication device 230 has the function of sending and receiving data to and from vehicle 100. Vehicle 100 is also equipped with a communication device 130 that receives data from server 200. Each vehicle 100 is equipped with a communication device 130.

[0030] Communication devices 130, 230, and 330 may each be general-purpose devices such as network hubs or routers. Communication devices 130, 230, and 330 use general-purpose wireless communication such as WiFi (registered trademark). Each of communication devices 130, 230, and 330 is configured with an address to identify the communication partner. The communication address is, for example, an IP (Internet Protocol) address.

[0031] Each vehicle 100 is a vehicle in its pre-completion state. As shown in Figure 1, the vehicle 100 travels along a predetermined track TR. As it travels along the track TR, the vehicle 100 is manufactured. Specifically, while the vehicle 100 is traveling along the track, a worker W or a robot 600 performs tasks such as assembling parts, operating switches, welding, and inspection. This completes the execution of each manufacturing process. The vehicle 100 is then manufactured when each manufacturing process is carried out in a predetermined order.

[0032] Multiple vehicles 100 travel in a convoy. Specifically, the vehicles 100 travel at a constant speed so that the distance between them remains constant at a predetermined distance. Furthermore, the speed of all multiple vehicles 100 is the same. The track TR has a straight-line region TR1 where the vehicles 100 travel in a straight line and a turning region TR2 where they turn. In the straight-line region TR1, the track TR is straight.

[0033] The turning area TR2 is where the vehicle 100 changes direction. In the turning area TR2, the vehicle 100 makes a U-turn. In the turning area TR2, for example, the track TR is in the shape of a circular arc with a predetermined radius of curvature. In the turning area TR2, the track TR is a semicircle. The turning areas TR2 are provided at both ends of the straight-ahead area TR1. For example, if the vehicle 100 moves in the +X direction in the straight-ahead area TR1, it will reach the turning area TR2. When the vehicle 100 turns 180 degrees in the turning area TR2, it will move in the -X direction in the straight-ahead area TR1. Conversely, if the vehicle moves in the -X direction in the straight-ahead area TR1, it will reach the turning area TR2. When the vehicle 100 turns 180 degrees in the turning area TR2, it will move in the +X direction in the straight-ahead area TR1. In this way, the vehicle 100 is manufactured sequentially by alternately passing through the straight-ahead area TR1 and the turning area TR2.

[0034] Sensor 300 is a camera that captures images of moving or stationary vehicles 100. Sensor 300 captures images of one or more vehicles 100. Sensor 300 is provided to detect distances between vehicles, etc. Based on the images captured by Sensor 300, Server 200 can detect the position of vehicles 100 within the factory. For example, it may be installed on the walls, pillars, ceilings, etc., of the factory and capture images of vehicles 100 from diagonally above. Sensor 300 captures images with a field of view that includes one or more vehicles 100 in a convoy. Sensor 300 may be set at the same height as the vehicles 100 and capture images of one or more vehicles 100 from the side.

[0035] The communication device 330 transmits the image captured by the sensor 300 to the server 200. The communication device 330 may transmit not only the captured image but also information obtained from the captured image to the server 200. In other words, the communication device 330 transmits the detection results detected by the sensor 300. The communication device 330 may be built into the sensor 300 or it may be a separate unit. Also, the communication device 330 may be shared by multiple sensors 300. In other words, if multiple sensors 300 are installed, one communication device 330 may transmit data to the server 200.

[0036] In this manner, when the sensor 300 captures an image of the vehicle 100, the communication device 330 transmits the captured image and other data to the server 200. The communication device 230 receives the captured image data from the sensor 300. The server 200 can estimate the distance between vehicles by performing predetermined image processing on the image captured by the sensor 300. For example, the server 200 calculates the distance between vehicles in a convoy of multiple vehicles 100. The number of vehicles in the convoy is not particularly limited; it can be two or more.

[0037] Furthermore, the sensor 300 is not limited to a camera. The sensor for detecting the distance between vehicles may be various types of sensors such as an RGB camera, a far-infrared camera, or LiDAR. The sensor 300 is not limited to an optical sensor; it may also be radar. Of course, two or more sensors 300 may be installed, or two or more types of sensors 300 may be used in combination. For example, the sensor 300 may include both LiDAR and a camera.

[0038] The communication device 330 transmits the detection result to the server 200. As described above, the detection result transmitted by the sensor 300 may be an captured image or information extracted from the image. For example, if the sensor 300 has an image processing function, the sensor 300 transmits information extracted by image processing to the server 200.

[0039] Furthermore, the sensor 300 may be mounted on the vehicle 100, as shown in Figure 2. For example, an on-board camera, LiDAR, or radar can be the sensor 300. If the sensor 300 is an on-board camera, the sensor 300 will capture an image of the vehicle 100 in front. If the sensor 300 is an on-board LiDAR, the sensor 300 will measure the distance to the vehicle 100 in front. The communication device 130 will transmit the image and measurement results to the server 200.

[0040] The server 200 controls the vehicle 100 so that it moves along the track TR. Furthermore, the server 200 controls multiple vehicles 100 so that they travel in a convoy. For example, the vehicles 100 travel in a single file along the track TR. The server 200 transmits control signals to each vehicle 100 via the communication device 230.

[0041] Server 200 controls the blinking of the lights on the vehicles 100. This blinking control causes each vehicle 100 to blink multiple lights according to a blinking pattern. The blinking pattern indicates the timing for switching the lights on and off within a predetermined blinking period. For example, the lights may blink with different blinking patterns for each vehicle. Also, the left and right lights on each vehicle 100 may blink at different timings. Sensor 300 captures, for example, the blinking lights as a moving image.

[0042] The server 200 recognizes the flashing pattern based on the image of the vehicle 100 captured by the sensor 300. Based on the recognition result, the server 200 can control the vehicle 100. For example, if the vehicle 100 is unable to turn on its lights according to the flashing pattern, it can detect a malfunction in the communication function or other areas. This allows workers to restore the communication. Alternatively, based on the image captured by the sensor 300, the server 200 can detect the position and travel order of the vehicle 100 that is flashing its lights according to the flashing pattern. The server 200 can then control the vehicle 100 based on its position and travel order.

[0043] Furthermore, if the flashing pattern differs for each vehicle, the server 200 can identify the vehicle 100 based on the recognition result of the flashing pattern. In addition, if one sensor 300 cannot capture images of both the left and right lights, the server 200 recognizes the flashing pattern based on images captured by multiple sensors 300. For example, the server 200 integrates the imaging results from multiple sensors 300 to recognize the flashing pattern of the lights.

[0044] Below, an example of flashing control and its processing during the manufacturing or transport process will be explained using Figures 3 and 4. Figure 3 is a schematic plan view showing a vehicle 100 traveling on a track TR and sensors 300 installed around it. Figure 3 shows three vehicles 100 autonomously traveling along the track TR. Figure 4 is a block diagram showing the configuration of the control system of the vehicle manufacturing system 50.

[0045] In Figure 3, three vehicles 100 are traveling along a straight track TR. In a top view, the direction of travel of the vehicles 100 is defined as the +X direction, and the width direction of the vehicles 100 is defined as the Y direction. With the direction of travel of the vehicles 100 as the reference, the +Y direction is to the left, and the -Y direction is to the right. Multiple sensors 300 are installed around the travel area A on which the vehicles 100 travel. The sensors 300 capture images of the vehicles 100 and their surroundings as they travel within travel area A. The multiple sensors 300 are installed so as to have different field of view angles V. In Figure 3, sensors 300 are installed on both the left and right sides of travel area A. The sensors 300 are, for example, visible light cameras.

[0046] As shown in Figure 4, the server 200 is a control device that controls the movement of the vehicle 100, and includes an image information acquisition unit 252, a flashing control unit 253, a recognition unit 255, a driving control unit 257, and a communication device 230. Although only one vehicle 100 and one sensor 300 are shown in Figure 4, multiple vehicles 100 and sensors 300 are provided as shown in Figures 1 to 3.

[0047] The communication device 230 includes a receiver 231 and a transmitter 232. The receiver 231 receives various signals and data from the sensor 300 and the vehicle 100. For example, the receiver 231 receives data indicating the detection result from the sensor 300. The data received from the sensor 300 may be image data or data extracted from image data.

[0048] The transmitter 232 transmits various signals and data to the sensor 300 and the vehicle 100. For example, the transmitter 232 transmits control instruction values ​​to the vehicle 100. Of course, the server 200 may also send and receive data other than those mentioned above. For communication between the receiver 231 and the transmitter 232, it is possible to use processing in accordance with general-purpose communication standards such as WiFi (registered trademark).

[0049] Vehicle 100 includes a vehicle control unit 115, an actuator group 120, and a communication device 130. Sensor 300 is equipped with the communication device 130. Note that the server 200 is not limited to a single physical device, but may be distributed. For example, the database may be a separate storage device or cloud server located independently of the processor.

[0050] The communication device 130 of vehicle 100 is a wireless terminal device for wireless communication with server 200. The communication device 130 is configured with an IP (Internet Protocol) address, etc. When the communication device 130 of vehicle 100 receives a control instruction value, vehicle 100 moves according to the control instruction value. The actuator group 120 includes wheel motors for driving the wheels, steering motors for controlling the steering angle, brakes for stopping the vehicle, etc. The vehicle control unit 115 generates control signals to control the actuator group 120 according to the control instruction. The vehicle control unit 115 may be composed of an ECU (Electronic Control Unit). This allows vehicle 100 to move along the track TR.

[0051] Furthermore, the vehicle 100 is equipped with a lighting unit 150 and lights 151. The lights 151 are, for example, headlights, position lights (parking lights), turn signals, etc. In Figure 4, the left and right lights 151L and 151R are shown as lights 151. For example, lights 151L and 151R are front turn signals and are mounted on the front side of the vehicle 100. Of course, the lights 151 may also be mounted on the sides or rear side of the vehicle 100. For example, the lights 151 may be reverse lights, taillights, brake lights, side turn signals, rear turn signals, etc. The lights 151 are visible from the outside of the vehicle 100.

[0052] The lighting unit 150 illuminates the light 151. For example, the lighting unit 150 has a switch or the like for controlling the on / off state of the light 151. As will be described later, the lighting unit 15 can turn the light 151 on and off according to a flashing pattern. Furthermore, the lighting unit 150 can independently control the left and right lights 151L and 151R.

[0053] In the following explanation, it is assumed that the server 200 performs image processing on the captured images acquired from the sensor 300, but the processing may be performed by a device other than the server 200. For example, the sensor 300 may perform part of the processing. Specifically, the sensor 300 may extract the features necessary for image processing and send those features to the server 200. Alternatively, a processor such as a GPU (Graphics Processing Unit) installed in the sensor 300 may recognize the blinking pattern and send the recognition result.

[0054] As described above, the sensor 300 transmits the captured image to the server 200. The captured image may be a moving image or a series of still images. When the communication device 230 of the server 200 receives the captured image, the image information acquisition unit 252 acquires the captured image. The image information acquisition unit 252 acquires the frame and its capture time and records it in memory or the like. The sensor 300 captures images at a frame rate of, for example, 30fps or 60fps.

[0055] The flashing control unit 253 performs flashing control to make the lights 151 of the vehicle 100 flash. For example, the flashing control unit 253 makes the lights flash with a different flashing pattern for each vehicle 100. A flashing pattern is assigned in advance to the address of the communication device 130 of the vehicle 100. The flashing pattern involves repeatedly turning the lights 151 on and off within a fixed flashing period between a start timing and an end timing.

[0056] Figure 5 is a diagram illustrating the flashing patterns. Figure 5 shows the timing of the light 151 turning on and off within the flashing period. For illustrative purposes, Figure 5 shows two flashing patterns as flashing pattern 1 and flashing pattern 2. In Figure 5, the flashing period includes N (where N is an integer greater than or equal to 2) times the light turns on and (N-1) times it turns off.

[0057] The switching timing for turning lights 151 on and off varies depending on the flashing pattern. For example, the duration of each light-up may vary depending on the flashing pattern. The duration of each light-off may vary depending on the flashing pattern. The duration of each light-up may vary. The duration of each light-off may vary. The number of times the lights turn on and off within a flashing period may vary depending on the flashing pattern. The number of times the lights turn off within a flashing period may vary depending on the flashing pattern. Furthermore, the switching timing for turning lights on and off may differ between the left light 151L and the right light 151R.

[0058] The flashing control unit 253 generates a flashing control signal that indicates a flashing pattern. The flashing control signal is a signal that indicates the timing for switching the light 151 on and off. The transmitter 232 transmits the flashing control signal to the communication device 130.

[0059] Here, the flashing pattern differs depending on the vehicle 100. As described above, each communication device 130 mounted on the vehicle 100 has an address. Therefore, a flashing pattern can be defined for each address of the communication device 130. For example, the flashing control unit 253 stores a unique flashing pattern for each address of the communication device 130. In this way, the flashing control unit 253 can make the lights 151 flash with different flashing patterns for each vehicle 100. In this case, the flashing control signal includes the switching timing and the address of the destination. Furthermore, within a single vehicle 100, the switching timing differs between the left and right lights 151L and 151R.

[0060] The recognition unit 255 recognizes the blinking pattern based on the captured image. For example, the recognition unit 255 identifies the switching timing when the lights 151L and 151R are switched on or off by performing image analysis on the captured image. Specifically, the recognition unit 255 detects the positions of the lights 151L and 151R in the frame of the captured image and identifies their pixel addresses. Known image processing or machine learning models can be used to detect the lights 151L and 151R. The recognition unit 255 determines whether the lights 151L and 151R are lit or off based on the brightness of the pixels corresponding to the lights 151L and 151R. Alternatively, the switching of the lights 151L and 151R on or off can be detected by comparing the brightness of pixels between frames.

[0061] For example, by inputting a captured image into a detection model utilizing artificial intelligence, the recognition unit 255 can detect the position and on / off status of the lights. Examples of detection models include pre-trained machine learning models that have been trained to implement either semantic segmentation or instance segmentation. As for 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 includes, for example, multiple training images including a vehicle 100 and ground truth labels indicating the position of the lights. When training the CNN, it is preferable to update the CNN parameters by backpropagation to reduce the error between the output result of the detection model and the ground truth labels.

[0062] The recognition unit 255 extracts the start frame and end frame of each illumination from multiple frame images. The recognition unit 255 also extracts the start frame and end frame of each deactivation from multiple frame images. The start frame of illumination is the frame in which the light switches from off to on. The start frame of deactivation is the frame in which the light switches from on to off. The end frame of illumination is the frame immediately preceding the start frame of deactivation. The end frame of deactivation is the frame immediately preceding the start frame of illumination.

[0063] The recognition unit 255 then records the time of the frame corresponding to the on / off switching of lights 151L and 151R as a timestamp. In this way, the recognition unit 255 can detect the on / off switching timing of light 151 during the flashing period. The switching timing may be the elapsed time from the start of the flashing control, or it may be an absolute time.

[0064] The recognition unit 255 can measure the number of times the lights turn on and the number of times they turn off based on the switching timing. The recognition unit 255 measures the duration of each light on and the duration of each light off based on the switching timing. The recognition unit 255 may record information such as the start and end timings of the flashing control, the number of times the lights turn on and off, and the duration of each light on and off as a measurement pattern. The recognition unit 255 records the measurement patterns for the left and right lights 151L and 151R, respectively.

[0065] The recognition unit 255 recognizes the flashing pattern based on the imaging results. For example, it recognizes a flashing pattern that matches the measured pattern according to the switching timing of lights 151L and 151R. For example, the flashing control unit 253 stores the switching timing of the flashing pattern for each vehicle in advance. The recognition unit 255 recognizes the flashing pattern of vehicle 100 by comparing the switching timing in the flashing pattern with the switching timing in the measured pattern. It extracts a flashing pattern that matches the measured pattern from among a plurality of flashing patterns that have been stored in advance.

[0066] By doing so, the flashing pattern can be recognized, allowing for appropriate control of the vehicle 100. For example, it is possible to identify which vehicle in the convoy flashed its lights according to the flashing pattern. Therefore, the position of the vehicle 100 whose lights 151 flashed can be detected based on the flashing pattern. This allows for appropriate control of the vehicle 100.

[0067] Furthermore, the recognition unit 255 can identify a vehicle based on the recognition result of the flashing pattern. This allows for the appropriate determination of the position and travel order of the vehicles 100. For example, if there is a limit to the number of communication devices 130, the communication devices 130 may be used repeatedly. In the vehicle manufacturing system 50, after the manufacturing of one vehicle 100 is completed, the communication device 130 removed from that vehicle 100 may be installed in another vehicle 100. In such a case, the server 200 can accurately detect the position and travel order of each vehicle in the convoy. For example, by detecting the travel order of the vehicles 100 in the convoy, the server 200 can appropriately control multiple vehicles 100.

[0068] If one sensor 300 cannot capture images of both the left and right lights 151L and 151R, the recognition unit 255 may recognize the flashing pattern based on the images captured by multiple sensors 300. For example, in Figure 3, in the second vehicle 100, one sensor 300 cannot capture images of both the left and right lights 151L and 151R. Specifically, of the two sensors 300 shown in Figure 3, the field of view V of the sensor 300 on the +Y side includes light 151L but does not include light 151R. The field of view V of the sensor 300 on the -Y side includes light 151R but does not include light 151L.

[0069] Thus, depending on the position of the vehicle 100 within the facility and the arrangement of the sensors 300, one sensor 300 may not be able to capture images of both lights 151L and 151R. Alternatively, if an object or person is present between the vehicle 100 and the sensor 300, one sensor 300 may not be able to capture images of both the left and right lights 151L and 151R. In this way, one sensor 300 may not be able to capture images of both the left and right lights 151L and 151R of a single vehicle 100.

[0070] If multiple lights 151 are not captured by one sensor 300, the recognition unit 255 recognizes the blinking pattern based on the images captured by the two sensors 300. The recognition unit 255 recognizes the blinking pattern by integrating the images captured by the two sensors 300. In the example in Figure 3, the recognition unit 255 detects the switching timing of light 151L based on the image captured by the sensor 300 on the +Y side. It detects the switching timing of light 151R based on the image captured by the sensor 300 on the -Y side.

[0071] The recognition unit 255 integrates the detection results of the switching timing of the left and right lights 151L and 151R. In this way, the recognition unit 255 can reliably recognize the flashing pattern of the vehicle 100. In other words, even if one sensor 300 cannot capture images of the vehicle 100's lights 151L and 151R, the flashing pattern can be recognized with high accuracy.

[0072] The driving control unit 257 generates driving control signals to, for example, stop, pause, make an emergency stop, decelerate, accelerate, or start the vehicle 100. When the driving control unit 257 outputs a driving control signal to the transmitter 232, the transmitter 232 transmits the driving control signal to the vehicle 100. As a result, the vehicle 100 stops, pauses, makes an emergency stop, decelerates, accelerates, or starts.

[0073] The driving control unit 257 may control the driving of the vehicle 100 based on the recognition result of the flashing pattern. For example, suppose the location of the sensor 300 within the facility is known. In this case, the server 200 can detect the location of each vehicle 100 based on the image captured by the sensor 300. The driving control unit 257 can control the driving speed, steering angle, etc., based on the location of the vehicle 100. Alternatively, the driving control unit 257 may control the driving speed and steering angle according to the driving order in the convoy.

[0074] Furthermore, it is preferable to illuminate both the left and right lights 151 at the start and end timings of the flashing pattern. For example, in Figure 5, the lights 151 are illuminated at the beginning and end of the flashing period. This ensures reliable detection of the start and end timings of the flashing pattern. The recognition unit 255 can recognize the flashing pattern by synchronizing the start timings of the left and right lights 151L and 151R. In addition, it is preferable that the flashing period between the start and end timings of the flashing pattern is the same for multiple vehicles.

[0075] The above description illustrates an example where the flashing control unit 253 flashes the left and right lights 151L and 151R. However, the lights 151 controlled by the flashing control unit 253 are not limited to the left and right lights 151L and 151R. For example, the front and rear lights 151 may also be flashed. Furthermore, the flashing control unit 253 may be configured to flash three or more lights 151. The recognition unit 255 can recognize the flashing pattern based on the on-off timing of the multiple lights 151. This allows the vehicle 100 to be identified, enabling appropriate driving control.

[0076] When the flashing control unit 253 flashes multiple lights 151 on a single vehicle, one sensor 300 may not be able to capture images of all the lights. In this case, the recognition unit 255 can recognize the flashing pattern based on images captured by two or more sensors 300.

[0077] Furthermore, because the vehicle 100 is in motion, it may move out of the field of view V of one sensor 300 during the flashing period. Alternatively, a worker W or other person may pass between the sensor 300 and the light 151 during the flashing period. Even in such cases, the recognition unit 255 can recognize the flashing pattern based on the images captured by two or more sensors 300. For example, if one sensor 300 is unable to capture the left light 151L during the flashing period, the recognition unit 255 performs recognition processing using the image captured by another sensor 300.

[0078] An example of a vehicle manufacturing method will be explained using Figure 6. Figure 6 is a flowchart of an example of a vehicle manufacturing method. First, the flashing control unit 253 performs flashing control (S11). For example, the flashing control unit 253 generates a flashing control signal and transmits it to the vehicle 100 so that the vehicle 100 flashes its lights according to a flashing pattern. The sensor 300 takes an image of the vehicle 100 (S12). Here, the sensor 300 takes a moving image of the vehicle 100 while its lights are flashing.

[0079] The image acquisition unit acquires the captured image captured by the sensor 300 (S13). Here, the communication device 330 of the sensor 300 transmits the captured image to the server 200. Next, the recognition unit 255 determines whether the left and right lights 151L and 151R have been captured by one sensor 300 (S14). If the left and right lights 151L and 151R have been captured by one sensor 300 (YES in S14), the recognition unit 255 recognizes the blinking pattern based on the image capture result of that one sensor 300 (S15).

[0080] If one sensor 300 fails to capture images of both the left and right lights 151L and 151R (NO in S14), the recognition unit 255 recognizes the flashing pattern based on the imaging results of two sensors 300 (S16). In other words, the recognition unit 255 recognizes the flashing pattern based on the image captured by sensor 300 that captured the left light 151L and the image captured by another sensor 300 that captured the right light 151R. In this way, the flashing pattern can be recognized appropriately.

[0081] Furthermore, the same flashing pattern may be used for at least some of the vehicles 100. For example, the flashing pattern may differ for each vehicle type. In this case, the flashing pattern will be the same for vehicles 100 of the same vehicle type. Alternatively, the flashing pattern can be changed depending on the production process or vehicle type.

[0082] Embodiment 2 The system 50 according to Embodiment 2 will be described with reference to Figure 7. Figure 7 is a schematic top view showing the configuration of the system 50. The basic configuration of the system is the same as in Embodiment 1, so the explanation will be omitted as appropriate. For example, the control system of the system 50 has the same configuration as in Figure 4. In Figure 7, an on-board camera is used as the sensor 300. The sensor 300 is installed in front of the vehicle 100 and captures an image of the vehicle 100 in front of it.

[0083] For example, the sensor 300 mounted on the second vehicle 100 is capturing images of the rear of the first vehicle 100. In this case, the second vehicle 100 becomes the vehicle equipped with the sensor 300. The first vehicle 100 becomes a surrounding vehicle located near the vehicle equipped with the sensor 300. The field of view V of the sensor 300 on the second vehicle 100 includes lights 151L and 151R. The flashing control unit causes the lights 151L and 151R on the rear of the first vehicle 100 to flash.

[0084] Therefore, the sensor 300 mounted on the second vehicle 100 captures images of the flashing lights 151L and 151R. The communication device 130 of vehicle 100 then transmits the captured images to the server 200. The recognition unit 255 can recognize the flashing pattern of the first vehicle based on the image capture results from the sensor 300 mounted on the second vehicle 100. Of course, a processor provided in vehicle 100 may also detect the on / off switching timing of the lights 151L and 151. The communication device 130 of vehicle 100 may then transmit the switching timing to the server 200. In this case, the recognition unit 255 recognizes the flashing pattern based on the transmitted switching timing.

[0085] Also, in this embodiment, when the light 151L and 151R cannot be imaged by one sensor 300, the recognition unit 255 can integrate the imaging results of a plurality of sensors 300 to recognize the blinking pattern. For example, there is an operator W between the third vehicle 100 and the second vehicle 100. In this case, the sensor 300 mounted on the third vehicle 100 cannot image the light 151L. That is, the operator W causes the light 151L to enter the blind spot of the sensor 300. In this case, the switching timing of the light 151L is detected based on the imaging result captured by another sensor 300.

[0086] Note that the in-vehicle sensor 300 is not limited to imaging the vehicle in front, and may image the vehicle behind. In this case, it may be mounted so that the sensor 300 faces the rear side of the vehicle 100. Alternatively, the sensor 300 may be arranged to image the vehicle 100 on the side.

[0087] Hereinafter, a driving control example for controlling the driving of the vehicle 100 in the system will be described.

[0088] <A. Driving control example 1> FIG. 8 is a conceptual diagram showing the configuration of the system 50 in driving control example 1. The system 50 includes a plurality of vehicles 100 as moving bodies, a server 200, and one or more sensors 300.

[0089] Note that when the moving body is other than a vehicle, the expressions "vehicle" and "car" in this disclosure can be appropriately replaced with "moving body", and the expression "driving" can be appropriately replaced with "moving".

[0090] Vehicle 100 is configured to operate autonomously. "Autonomous operation" means operation without the operation of a passenger. Operation refers to operations related to at least one of the following: "going," "turning," or "stopping" of vehicle 100. Autonomous operation is achieved by automatic or manual remote control using a device located outside vehicle 100, or by autonomous control of vehicle 100. Vehicle 100 operating autonomously may have passengers on board who do not perform operation. Passengers who do not perform operation include, for example, people simply sitting in the seats of vehicle 100, or people performing tasks other than operation, such as assembly, inspection, or operating switches, while on board vehicle 100. Operation by a passenger is sometimes called "manned operation."

[0091] 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.

[0092] In this embodiment, system 50 is used in a factory FC where vehicle 100 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 and a second location PL2. The first location PL1 and the second location PL2 are connected by a track TR on which vehicle 100 can travel. Multiple sensors 300 are installed in the factory FC along the track TR. The position of each sensor 300 in the factory FC is pre-adjusted. Vehicle 100 moves from the first location PL1 to the second location PL2 via the track TR by unmanned operation.

[0093] Figure 9 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, and a communication device 130 for communicating wirelessly with external devices such as a server 200. The actuator group 120 includes actuators for a drive system to accelerate the vehicle 100, actuators for a steering system to change the direction of travel of the vehicle 100, and actuators for a braking system to decelerate the vehicle 100.

[0094] The vehicle control device 110 is composed 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 and a communication device 130. The processor 111 implements various functions, including those of a vehicle control unit 115, by executing PG1 stored in the memory 112.

[0095] The vehicle control unit 115 drives the vehicle 100 by controlling the actuator group 120. 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. In other embodiments, the driving 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.

[0096] The server 200 is composed 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 via the internal bus 204 to enable bidirectional communication. A communication device 205 for communicating with various devices outside the server 200 is connected to the input / output interface 203. The communication device 205 can communicate with the vehicle 100 via wireless communication and can communicate with each sensor 300 via wired or wireless communication. The processor 201 implements various functions, including those of a remote control unit 210, by executing PG2 stored in memory 202.

[0097] The remote control unit 210 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. In addition to the driving control signal, the remote control unit 210 may also generate and output control signals to control 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 210 may operate these various devices and auxiliary equipment by remote control.

[0098] Sensor 300 is a sensor located outside of vehicle 100. In this embodiment, sensor 300 is a sensor that detects vehicle 100 from outside of vehicle 100. Sensor 300 is equipped with a communication device (not shown) and can communicate with other devices such as server 200 via wired or wireless communication.

[0099] Specifically, the sensor 300 is comprised of a camera. The camera, as part of the sensor 300, captures an image including the vehicle 100 and outputs the captured image as the detection result.

[0100] Figure 10 is a flowchart showing the processing procedure for vehicle 100's driving control in an example of driving control. In the processing procedure shown in Figure 10, the processor 201 of the server 200 functions as a remote control unit 210 by executing program PG2. The processor 111 of the vehicle 100 functions as a vehicle control unit 115 by executing program PG1.

[0101] In step S110, the processor 201 of the server 200 acquires vehicle position information of the vehicle 100 using the detection result output from the 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 S110, the processor 201 acquires vehicle position information using the captured image acquired from the camera, which is the sensor 300.

[0102] In detail, in step S110, 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 includes, for example, multiple training images containing vehicle 100, and labels indicating whether each region in the training images represents vehicle 100 or something other than vehicle 100. During CNN training, it is preferable to update the CNN parameters using backpropagation to reduce the error between the output result of the detection model DM and the labels. Furthermore, the processor 201 can obtain the orientation of vehicle 100 by, for example, using the optical flow method, estimating it based on the direction of the vehicle 100's movement vector calculated from the positional changes of the vehicle 100's feature points between frames of the captured images.

[0103] In step S120, 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.

[0104] In step S130, the processor 201 of the server 200 generates a driving control signal to drive 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. Furthermore, if the vehicle 100 is located on the reference path RR, the processor 201 determines the steering angle and acceleration so that the vehicle 100 does not deviate from the reference path RR, and 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, the processor 201 determines the steering angle and acceleration so that the vehicle 100 returns to the reference path RR.

[0105] In step S140, 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.

[0106] In step S150, the processor 111 of the vehicle 100 receives a driving control signal transmitted from the server 200. In step S160, 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 represented by the driving control signal. The processor 111 repeats the reception of the driving control signal and the control of the actuator group 120 at a predetermined period. According to the system 50 in this example, the vehicle 100 can be driven by remote control, and the vehicle 100 can be moved without using conveying equipment such as a crane or a conveyor.

[0107] <B:Driving Control Example 2> FIG. 11 is an explanatory diagram showing a schematic configuration of the system 50v in Driving Control Example 2. In this example, the system 50v is different from Driving Control Example 1 in that it does not include the server 200. Also, the vehicle 100v in the configuration can travel by autonomous control of the vehicle 100v. For other configurations, unless otherwise particularly described, they are the same as those described above.

[0108] In this example, the processor 111v of the vehicle control device 110v functions as the vehicle control unit 115v by executing the program PG1 stored in the memory 112v. The vehicle control unit 115v acquires the output result from the sensor, generates a driving control signal using the output result, and outputs the generated driving control signal to operate the actuator group 120, thereby enabling the vehicle 100v to travel by autonomous control. In this example, in addition to the program PG1, a detection model DM and a reference route RR are stored in advance in the memory 112v.

[0109] FIG. 12 is a flowchart showing the processing procedure of the driving control of the vehicle 100v in Example 2. In the processing procedure of FIG. 12, the processor 111v of the vehicle 100v functions as the vehicle control unit 115v by executing the program PG1.

[0110] In step S210, the processor 111v of the vehicle control device 110v acquires vehicle position information using the detection result output from the camera, which is the sensor 300. In step S220, the processor 111v determines the target position to which the vehicle 100v should next go. In step S230, the processor 111v generates a driving control signal to drive the vehicle 100v toward the determined target position. In step S240, 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 example, the vehicle 100v can be driven by autonomous control of the vehicle 100v without remote control of the vehicle 100v by the server 200.

[0111] YY: Other examples of driving control (YY1) In the above example, sensor 300 is a camera. However, sensor 300 does not have to be a camera; for example, it could be LiDAR (Light Detection And Ranging). In this case, the detection result output by sensor 300 may be 3D point cloud data representing vehicle 100. In this case, the server 200 and 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.

[0112] In (YY2) Driving control example 1, the server 200 performs the processing from acquiring vehicle position information to generating driving control signals. In contrast, the vehicle 100 may perform at least a part of the processing from acquiring vehicle position information to generating driving control signals. For example, the following forms (1) to (3) may be used.

[0113] (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.

[0114] (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.

[0115] (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.

[0116] (YY3) In the driving control example 2, 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.

[0117] (YY4) In driving control example 2, vehicle 100v acquires vehicle position information using the detection results of sensor 300. Alternatively, 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 vehicle 100v should go, generate a route from 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, vehicle 100v can drive without using the detection results of sensor 300 at all. Vehicle 100v may also acquire target arrival time and congestion information from outside 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 system 50v may be provided in vehicle 100v. That is, the processing realized by system 50v in this disclosure may be realized by vehicle 100v alone. For example, the leading vehicle 100V may transmit a control instruction value to the following vehicle 100.

[0118] (YY5) In the driving control example 1, 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 that includes a display for displaying captured images output from the 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.

[0119] (YY6) In each of the above driving control examples, the vehicle 100 only needs to have a configuration that allows it to move by unmanned operation, and may be in the form of a platform having the configuration described below. Specifically, in order for the vehicle 100 to perform the three functions of "driving," "turning," and "stopping" by unmanned operation, it only needs to be equipped with at least a vehicle control device 110 and an actuator group 120. When the vehicle 100 acquires information from the outside for unmanned operation, the vehicle 100 may further be equipped with a communication device 130. That is, the vehicle 100 that can move by unmanned operation does not need to have at least some of the interior parts such as the driver's seat and dashboard installed, at least some of the exterior parts such as the bumper and fender installed, and does not need to have a body shell installed. In this case, the remaining parts such as the body shell may be attached to the vehicle 100 before it is shipped from the factory FC, or the remaining parts such as the body shell may be attached to the vehicle 100 after it has been shipped from the factory FC, while the remaining parts such as the body shell are not attached to the vehicle 100. Each part may be attached from any direction, such as the top, bottom, front, rear, right, or left side of the vehicle 100, and each part may be attached from the same direction or from different directions. The positioning of the platform can also be determined in the same way as the vehicle 100 in the first embodiment.

[0120] (YY7) 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 the 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 the vehicle 100 that are different from the platform. Various modules may also include any exterior parts such as bumpers and grilles, or any interior parts such as seats and consoles. Furthermore, not limited to vehicle 100, any type of mobile body may be manufactured by combining multiple modules. 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. A molding technique for integrally molding a single component, especially a relatively large component, is also called gigacast or megacast. For example, the front module, central module, and rear module mentioned above may be manufactured using gigacast.

[0121] (YY8) Transporting vehicle 100 using the unmanned operation of the 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 fuel cell (FC) that manufactures vehicle 100, at least a portion of the transport of vehicle 100 is realized by autonomous transport.

[0122] (YY9) In each of the above driving control examples, 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.

[0123] In the above driving control examples 1 and 2, the driving control shown in Figures 3 to 7 can also be applied. For example, the remote control unit 210 shown in Figure 9 performs driving control using image processing. In addition, in Figures 8 to 12, driving control using the suspension string 32 and control device 30 shown in Figures 3 and 4 may also be applied.

[0124] Furthermore, some or all of the processing in the aforementioned sensor 300, vehicle 100, server 200, sensor 300, robot 600, etc., can be implemented as computer programs. Such programs can be stored using various types of non-temporary computer-readable media and supplied to a computer. Non-temporary computer-readable media include various types of tangible recording media. Examples of non-temporary computer-readable media include magnetic recording media (e.g., flexible disks, magnetic tapes, hard disk drives), magneto-optical recording media (e.g., magneto-optical disks), CD-ROMs (Read Only Memory), CD-Rs, CD-R / Ws, and semiconductor memories (e.g., mask ROMs, PROMs (Programmable ROMs), EPROMs (Erasable PROMs), flash ROMs, RAMs (Random Access Memory)). Programs may also be supplied to a computer using various types of temporary computer-readable media. Examples of temporary computer-readable media include electrical signals, optical signals, and electromagnetic waves. Temporary computer-readable media can be supplied to a computer via wired communication channels such as electric wires and optical fibers, or via wireless communication channels.

[0125] It should be noted that the present invention is not limited to the embodiments described above, and can be modified as appropriate without departing from the spirit of the invention. [Explanation of Symbols]

[0126] 30 Control equipment 31 string 32 Hanging string 50 Vehicle Manufacturing Systems 100 vehicles 115 Vehicle Control Unit 120 Actuator Group 130 Communication equipment 200 servers 230 Communication equipment 231 Receiver 232 Transmitter 252 Image Information Acquisition Unit 253 Flashing control unit 255 Recognition part 257 Driving Control Unit 300 sensors 330 Communication equipment

Claims

1. A vehicle manufacturing system that controls the movement of multiple vehicles during the manufacturing process or the transport process, Multiple cameras that capture images of the driving area and its surroundings in which the vehicle travels, A flashing control unit controls the lights of the vehicle so that the vehicle flashes multiple lights according to a flashing pattern, A vehicle manufacturing system comprising: a recognition unit that recognizes the flashing pattern of the lights based on images captured by at least two cameras when the plurality of lights are not captured by one of the cameras.

2. The flashing control unit controls the lights of the plurality of vehicles so that the flashing pattern differs depending on the vehicle. The vehicle manufacturing system according to claim 1, wherein the recognition unit identifies the vehicle based on the flashing pattern.

3. The vehicle manufacturing system according to claim 2, wherein the flashing control unit recognizes the flashing pattern in accordance with the switching timing in which the plurality of lights are switched on and off.

4. The aforementioned plurality of lights include the left and right lights of the vehicle, The vehicle manufacturing system according to claim 3, wherein the left and right lights have different switching timings.

5. The aforementioned plurality of cameras include in-vehicle cameras mounted on the vehicle, The in-vehicle camera captures images of surrounding vehicles traveling around the vehicle on which the camera is mounted, A vehicle manufacturing system according to any one of claims 1 to 4, wherein the mounted vehicle recognizes the flashing pattern of the lights of the surrounding vehicles.

6. A vehicle manufacturing system according to any one of claims 1 to 4, wherein the plurality of lights are illuminated at the start timing and end timing of the flashing pattern.

7. A vehicle manufacturing method that controls the movement of multiple vehicles during the manufacturing process or the transport process, The steps include: capturing images of the driving area and its surroundings where the vehicle is traveling using multiple cameras; A step of controlling the lights of the vehicle so that the vehicle flashes multiple lights according to a flashing pattern, A vehicle manufacturing method comprising the step of recognizing the flashing pattern of the lights based on images captured by at least two cameras when the plurality of lights are not captured by one of the cameras.

8. The lights of the multiple vehicles are controlled so that the flashing pattern differs depending on the vehicle. The vehicle manufacturing method according to claim 7, wherein the vehicle is identified based on the flashing pattern.

9. The vehicle manufacturing method according to claim 8, wherein the flashing pattern is recognized in accordance with the switching timing of the switching of the plurality of lights on and off.

10. The aforementioned plurality of lights include the left and right lights of the vehicle, The vehicle manufacturing method according to claim 9, wherein the switching timing is different for the left and right lights.

11. The aforementioned plurality of cameras include in-vehicle cameras mounted on the vehicle, The in-vehicle camera captures images of surrounding vehicles traveling around the vehicle on which the camera is mounted, The vehicle manufacturing method according to any one of claims 7 to 10, wherein the mounted vehicle recognizes the flashing pattern of the lights of the surrounding vehicles.

12. A vehicle manufacturing method according to any one of claims 7 to 10, wherein the plurality of lights are illuminated at the start timing and end timing of the flashing pattern.

13. A control device for controlling the movement of multiple vehicles during a manufacturing process or a transport process, An image acquisition unit that acquires images of the driving area and its surroundings in which the vehicle travels from multiple cameras, A flashing control unit controls the lights of the vehicle so that the vehicle flashes multiple lights according to a flashing pattern, A control device comprising: a recognition unit that recognizes the flashing pattern of the lights based on images captured by at least two cameras when the plurality of lights are not captured by one of the cameras.

14. The flashing control unit controls the lights of the plurality of vehicles so that the flashing pattern differs depending on the vehicle. The control device according to claim 13, wherein the recognition unit identifies the vehicle based on the flashing pattern.

15. The control device according to claim 14, wherein the flashing control unit recognizes the flashing pattern in accordance with the switching timing at which the plurality of lights are switched on and off.

16. The aforementioned plurality of lights include the left and right lights of the vehicle, The control device according to claim 15, wherein the left and right lights have different switching timings.

17. The aforementioned plurality of cameras include in-vehicle cameras mounted on the vehicle, The in-vehicle camera captures images of surrounding vehicles traveling around the vehicle on which the camera is mounted, The control device according to any one of claims 13 to 16, which recognizes the flashing pattern of the lights of the surrounding vehicles in the vehicle on which it is installed.

18. The control device according to any one of claims 13 to 16, wherein the plurality of lights are illuminated at the start timing and end timing of the flashing pattern.

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