Vehicle monitoring system

Abstract

To provide a vehicle monitoring system that can reduce the load on monitoring processes. [Solution] The vehicle monitoring system according to this disclosure comprises: an image capture control unit which causes a vehicle moving in a first area where predetermined work is performed for each vehicle to be photographed by an onboard camera mounted on a vehicle adjacent to the vehicle, and a vehicle moving in a second area different from the first area to be photographed by an external camera that photographs the second area; a first image analysis unit which analyzes images captured by an onboard camera mounted on a vehicle moving in the first area; a second image analysis unit which analyzes images captured by an external camera that photographs the second area; and a monitoring unit which monitors multiple vehicles based on the image analysis results of the first and second image analysis units, respectively.

Description

Technical Field

[0001] The present disclosure relates to a vehicle monitoring system.

Background Art

[0002] In a vehicle monitoring system for monitoring a plurality of vehicles being assembled in a factory or the like, it is required to reduce the load on the monitoring process without reducing the monitoring accuracy for the plurality of vehicles. Patent Document 1 discloses, as a related art, an apparatus for remotely controlling a moving object.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In a monitoring system for monitoring a plurality of vehicles, there is a continuing need to reduce the load on the monitoring process without reducing the monitoring accuracy for the plurality of vehicles.

[0005] The present disclosure has been made in view of the above background, and an object thereof is to provide a vehicle monitoring system capable of reducing the load on the monitoring process.

Means for Solving the Problems

[0006] The vehicle monitoring system according to this disclosure comprises: an image capture control unit that, among a plurality of vehicles, causes a vehicle moving in a first area where predetermined work is performed for each vehicle to be photographed by an on-board camera mounted on a vehicle adjacent to the vehicle, and causes a vehicle moving in a second area different from the first area to be photographed by an external camera that photographs the second area; a first image analysis unit that analyzes images captured by the on-board camera mounted on the vehicle moving in the first area; a second image analysis unit that analyzes images captured by the external camera that photographs the second area; and a monitoring unit that monitors the plurality of vehicles based on the image analysis results of the first image analysis unit and the second image analysis unit, respectively. The vehicle monitoring system according to this disclosure can reduce the processing load on each vehicle, i.e., the processing load on monitoring, by having an external camera photograph a vehicle moving in an area other than the area where predetermined work is performed, instead of an on-board camera mounted on an adjacent vehicle.

[0007] The first area is an area in which a predetermined operation is performed for each of the plurality of vehicles, and the second area may be an area through which the plurality of vehicles pass without any predetermined operation being performed for each of the plurality of vehicles.

[0008] The second image analysis unit may be configured to analyze the captured image at a lower resolution than the first image analysis unit.

[0009] Each of the aforementioned vehicles may be configured to be movable by unmanned operation. [Effects of the Invention]

[0010] This disclosure makes it possible to provide a vehicle monitoring system that can reduce the load on monitoring processing. [Brief explanation of the drawing]

[0011] [Figure 1] This is a schematic diagram showing a part of the vehicle monitoring system according to Embodiment 1. [Figure 2]This is a block diagram showing the control system of the vehicle monitoring system according to Embodiment 1. [Figure 3] This is a diagram illustrating the vehicle's driving control. [Figure 4] This is a control block diagram illustrating example 1 of the driving control system. [Figure 5] This is a flowchart to explain example 1 of the driving control system. [Figure 6] This is a control block diagram illustrating example 2 of the driving control system. [Figure 7] This is a flowchart to explain example 2 of the driving control system. [Modes for carrying out the invention]

[0012] The following describes specific embodiments to which the present invention is applied, with reference to the drawings. However, the present invention is not limited to the following embodiments. Also, for clarity of explanation, the following description and drawings have been simplified as appropriate.

[0013] <Embodiment 1> Figure 1 is a schematic diagram showing a part of the vehicle monitoring system 50 according to Embodiment 1. The vehicle monitoring system 50 is applied, for example, in a vehicle manufacturing plant where vehicles 100 are manufactured. In the example in Figure 1, the vehicle monitoring system 50 monitors the vehicle 100 in area A1 where predetermined work is performed on the vehicle 100, and in area B1 where predetermined work is not performed on the vehicle 100. For illustrative purposes, an XY Cartesian coordinate system is shown in Figure 1.

[0014] As shown in Figure 1, the vehicle monitoring system 50 comprises a server 200 and a group of cameras 320. Figure 1 also shows multiple vehicles 100 that are monitored by the vehicle monitoring system 50. Each vehicle 100 is, for example, a self-propelled vehicle that can move under its own power during the manufacturing process. In other words, each vehicle 100 is, for example, a vehicle that can move unmanned during the manufacturing process. Although not shown in Figure 1, each vehicle 100 is equipped with a camera (hereinafter referred to as an on-board camera), which is a type of internal sensor. Each vehicle 100 uses its on-board camera to photograph the area around the vehicle body.

[0015] Each vehicle 100 is a vehicle in its pre-completion state. Each vehicle 100, in its pre-completion state, moves along a predetermined movement path (road) and is manufactured into a finished product by having predetermined tasks performed on it by workers (not shown) or robots (not shown) in each manufacturing process area. Predetermined tasks include assembling parts, operating switches, welding, and inspection. In the example in Figure 1, areas A1 and C1 are areas where predetermined tasks are performed on each vehicle 100, while area B1, located between areas A1 and C1, is an area through which each vehicle 100 simply passes without any predetermined tasks being performed on it.

[0016] Multiple vehicles 100 move in a convoy. For example, multiple vehicles 100 move in such a way that the distance between them remains constant in each area. In area A1 (first area), predetermined tasks are performed on each vehicle 100, so the movement speed of each vehicle 100 is slow. Therefore, multiple vehicles 100 tend to cluster together and move continuously in a convoy. In contrast, in area B1 (second area), predetermined tasks are not performed on each vehicle 100, so the movement speed of each vehicle 100 is relatively fast. Therefore, multiple vehicles 100 tend not to cluster together and move intermittently, one vehicle at a time.

[0017] In area A1, since the inter-vehicle distance is short, it is necessary to accurately estimate the inter-vehicle distance so that the vehicles do not contact each other. However, for example, in the case of a camera (hereinafter referred to as an external camera) installed outside the vehicle such as the ceiling of a facility, it may be difficult to perform high-precision imaging between vehicles due to the obstruction of the vehicle. Therefore, in area A1, each vehicle 100 uses an in-vehicle camera to photograph the vehicle 100 in front (or behind) during platooning. Based on the inter-vehicle distance and the like estimated by analyzing the captured image of the in-vehicle camera, the movement of each vehicle 100 in area A1 is controlled, so that, for example, contact between vehicles is suppressed. The in-vehicle camera of each vehicle 100 has a communication function and transmits data such as the captured image via the network 500 to the server 200.

[0018] The camera group 320 is composed of a plurality of external cameras which are a kind of external sensor 300, and photographs area B1 where each vehicle 100 simply passes through. In the example of FIG. 1, the camera group 320 is composed of four external cameras 321 to 324. The external camera 321 photographs a part of area B1, area B11, the external camera 322 photographs a part of area B1, area B12, the external camera 323 photographs a part of area B1, area B13, and the external camera 324 photographs a part of area B1, area B14. Each of the external cameras 321 to 324 has a communication function and transmits data such as the captured image via the network 500 to the server 200. In area B1, since the inter-vehicle distance is large, higher precision in estimating the inter-vehicle distance is not required compared to the case where the inter-vehicle distance is short. Therefore, in area B1, each vehicle 100 does not perform photographing with the in-vehicle camera. Thereby, the load on photographing of each vehicle 100 is reduced.

[0019] Server 200 monitors a plurality of vehicles 100 moving in area A1 based on the captured images received from the in-vehicle cameras of each of the plurality of vehicles 100 moving in area A1. Further, server 200 monitors the vehicles 100 in area B1 based on the captured images of area B1 received from camera group 320. For example, server 200 monitors whether each vehicle 100 is moving on a planned route, or whether work is being performed on each vehicle 100 as planned. Also, server 200 controls the movement of each vehicle 100 while estimating the position of each vehicle 100 based on, for example, the received captured images.

[0020] Subsequently, the control system of vehicle monitoring system 50 will be described using FIG. 2. FIG. 2 is a block diagram showing the control system of vehicle monitoring system 50.

[0021] As shown in FIG. 2, server 200 includes at least a communication device 205, a shooting control unit 206, an image analysis unit (first image analysis unit) 207, an image analysis unit (second image analysis unit) 208, a monitoring unit 209, and a remote control unit 210. Each vehicle 100 includes at least a vehicle control device 110, an actuator group 120, a communication device 130, and an in-vehicle camera 140. Note that server 200 is not limited to being physically configured by a single device, and may be configured by a plurality of distributed devices. For example, image analysis units 207 and 208 may be physically configured by a single device, or may be configured by separate devices.

[0022] In server 200, communication device 205 communicates with camera group 320 and each vehicle 100 via network 500. For example, communication device 205 receives data such as captured images from camera group 320, or transmits information related to vehicle control to each vehicle 100.

[0023] The shooting control unit 206 switches the camera used to photograph each vehicle 100 depending on the area. For example, in area A1, the distance between vehicles is short, so it is necessary to accurately estimate the distance between vehicles to prevent collisions. However, with external cameras, vehicles can obstruct the view, making it difficult to capture high-precision images of the spaces between vehicles. Therefore, the shooting control unit 206 has each vehicle 100 moving in area A1 photographed by an on-board camera mounted on a vehicle 100 adjacent to that vehicle 100. In contrast, in area B1, the distance between vehicles is large, so the accuracy of the distance estimation is not as important as in the case of short distances. Therefore, the shooting control unit 206 has each vehicle 100 moving in area B1 photographed by an external camera instead of an on-board camera. In addition, in areas where no external cameras are installed, or in areas where the distance between vehicles is short, such as area A1 (for example, area C1), the camera control unit 206 causes each vehicle 100 moving in the area to be photographed by an on-board camera mounted on a vehicle 100 adjacent to that vehicle 100.

[0024] The image analysis unit 207 analyzes the images captured by the on-board cameras 140 of each of the multiple vehicles 100 moving in area A1. Specifically, the communication device 205 receives data such as images captured by the on-board cameras 140 of each of the multiple vehicles 100 moving in area A1. The image analysis unit 207 then analyzes the received images to identify, for example, the external shape of the vehicle 100 in front (or behind) and its surrounding environment as seen in the captured images. This makes it possible to determine the distance between each vehicle 100 in area A1 and the vehicle in front (or behind), the position and orientation of each vehicle 100 in area A1, and the driving state of each vehicle 100 in area A1.

[0025] The image analysis unit 208 analyzes the images captured by the camera group 320 that photograph area B1. Specifically, the communication device 205 receives data such as captured images from the camera group 320 that photograph area B1. The image analysis unit 208 then analyzes the received images from the camera group 320 to identify, for example, the external shape of the vehicle 100 and its surrounding environment as seen in the captured images. This makes it possible to determine the position and orientation of the vehicle 100 in area B1, as well as the driving state of the vehicle 100 in area B1. In area B1, a higher accuracy in estimating the distance between vehicles is not required than in area A1. Therefore, the image analysis unit 208 may be configured to analyze captured images at a lower resolution than the image analysis unit 207. This reduces the load on the image analysis.

[0026] The monitoring unit 209 monitors multiple vehicles 100 based on the image analysis results from the image analysis units 207 and 208. For example, the monitoring unit 209 monitors whether each vehicle 100 is moving while maintaining a predetermined distance between vehicles, whether each vehicle 100 is moving along the planned route, and whether each vehicle 100 is performing the planned work.

[0027] The remote control unit 210 remotely controls each vehicle 100 by transmitting vehicle control information to each vehicle 100 based on the monitoring results from the monitoring unit 209 (including the location information of each vehicle 100). Specifically, the communication device 205 transmits vehicle control information instructed by the remote control unit 210 to each vehicle 100. In each vehicle 100, the communication device 130 receives vehicle control information from the server 200, and the vehicle control device 110 causes the actuator group 120 to move the vehicle according to the received vehicle control information.

[0028] In this way, the vehicle monitoring system 50 according to the present disclosure causes an external camera to photograph a vehicle 100 moving in an area other than an area (for example, area A1) where a predetermined operation is performed (for example, area B1), instead of causing an in-vehicle camera mounted on the vehicle 100 before and after it to photograph, thereby reducing the processing load on each vehicle 100, that is, the load on the monitoring process.

[0029] Hereinafter, in a system 50 related to the manufacture of a vehicle including the vehicle monitoring system described above, an example of travel control for controlling the travel of the vehicle 100 will be described.

[0030] <A. Example of Travel Control 1> FIG. 3 is a conceptual diagram showing the configuration of the system 50 in Travel Control Example 1. The system 50 includes one or more vehicles 100 as moving bodies, a server 200, and one or more external sensors 300.

[0031] [[ID=?]]When the moving body is other than a vehicle, the expressions "vehicle" and "car" in the present disclosure can be appropriately replaced with "moving body", and the expression "travel" can be appropriately replaced with "movement".

[0032] The vehicle 100 is configured to be capable of traveling by autonomous driving. "Autonomous driving" means driving that does not depend on the driving operation of a passenger. The driving operation means an operation related to at least any one of "driving", "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 an operation different from the driving operation, such as assembly, inspection, or operation of switches, while on board the vehicle 100. Note that driving by the driving operation of a passenger may be referred to as "manual driving".

[0033] It should be noted that there seems to be an error in the tag "ID=?" in the original text, and I have translated it as best as possible while maintaining the integrity of the content. If there is any specific correction or additional information, please let me know.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.

[0034] 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 external sensors 300 are installed along the track TR in the factory FC. The position of each external 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.

[0035] Figure 4 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.

[0036] 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 a program PG1 stored in the memory 112.

[0037] 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.

[0038] 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 external devices of 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 external sensor 300 via wired or wireless communication. The processor 201 implements various functions, including those of a remote control unit 210, by executing a program PG2 stored in memory 202.

[0039] 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. Specifically, the remote control unit 210 may include the functions of the image capture control unit 206 shown in Figure 2. Furthermore, the remote control unit 210 may also include the functions of the image analysis units 207, 208 and the monitoring unit 209, which are shown separately from the remote control unit 210 in Figure 2.

[0040] The external sensor 300 is a sensor located outside the vehicle 100. In this embodiment, 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.

[0041] Specifically, the external sensor 300 is comprised of a camera. The camera, acting as the external sensor 300, captures an image including the vehicle 100 and outputs the captured image as the detection result.

[0042] Figure 5 is a flowchart showing the processing procedure for vehicle 100's driving control in an example of driving control. In the processing procedure in Figure 5, the processor 201 of the server 200 functions as a remote control unit 210 by executing program PG2. Also, the processor 111 of the vehicle 100 functions as a vehicle control unit 115 by executing program PG1.

[0043] In step S110, 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 S110, the processor 201 acquires vehicle position information using the captured image acquired from the camera, which is the external sensor 300.

[0044] 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.

[0045] 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.

[0046] 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.

[0047] 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.

[0048] 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 cycle. 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 conveyance equipment such as a crane or a conveyor.

[0049] <B:Driving Control Example 2> FIG. 6 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 above.

[0050] 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 the memory 112v in advance.

[0051] FIG. 7 is a flowchart showing the processing procedure of the driving control of the vehicle 100v in Example 2. In the processing procedure of FIG. 7, the processor 111v of the vehicle 100v functions as the vehicle control unit 115v by executing the program PG1.

[0052] 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 an external 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.

[0053] YY: Other examples of driving control (YY1) In the above example, the external sensor 300 is a camera. However, the external sensor 300 does not have to be a camera; for example, it could be a LiDAR (Light Detection And Ranging). 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.

[0054] 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.

[0055] (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.

[0056] (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.

[0057] (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.

[0058] (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.

[0059] (YY4) In driving control example 2, vehicle 100v acquires vehicle position information using the detection results of the external 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 the external 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.

[0060] (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 an external sensor 300, a steering wheel for remotely controlling the vehicle 100, an accelerator pedal, a brake pedal, and a communication device for communicating with the server 200 via wired or wireless communication, and the server 200 may generate a driving control signal in accordance with the operation applied to the control device.

[0061] (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.

[0062] (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.

[0063] (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.

[0064] (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.

[0065] Furthermore, this disclosure can be realized by having a CPU (Central Processing Unit) execute a computer program to perform some or all of the processing in the external sensor 300, vehicle 100, server 200, etc. as described above.

[0066] The program described above includes, when loaded into a computer, a set of instructions (or software code) for causing the computer to perform one or more of the functions described in the embodiments. The program may be stored in a non-temporary computer-readable medium or a physical storage medium. Examples, but not limited to, include RAM (Random-Access Memory), ROM (Read-Only Memory), flash memory, SSD (Solid-State Drive), or other memory technologies, CD-ROM, DVD (Digital Versatile Disc), Blu-ray® disc, or other optical disc storage, magnetic cassette, magnetic tape, magnetic disk storage, or other magnetic storage devices. The program may be transmitted over a temporary computer-readable medium or a communication medium. Examples, but not limited to, include temporary computer-readable medium or a communication medium that includes electrically, optically, acoustically, or otherwise propagating signals.

[0067] Although the present disclosure has been described above with reference to embodiments, the present disclosure is not limited to the embodiments described above. Various modifications to the structure and details of the present disclosure can be made as can be understood by those skilled in the art within the scope of the present disclosure. Furthermore, each embodiment can be combined with other embodiments as appropriate. [Explanation of Symbols]

[0068] 50 Vehicle monitoring system 100 vehicles 110 Vehicle control device 111 processors 112 memory 113 Input / Output Interfaces 114 Internal bus 115 Vehicle Control Unit 120 Actuator Group 130 Communication equipment 140 In-car cameras 200 servers 201 Processor 202 memory 203 Input / Output Interfaces 204 Internal Bus 205 Communication equipment 206 Imaging Control Unit 207 Image Analysis Department 208 Image Analysis Department 209 Monitoring Department 210 Remote Control Unit 300 External Sensors 320 camera group 321~324 External Cameras 500 Networks

Claims

1. A camera control unit, which, among multiple vehicles, causes a vehicle moving in a first area where a predetermined task is performed for each vehicle to be photographed by an onboard camera mounted on a vehicle adjacent to that vehicle, and causes a vehicle moving in a second area different from the first area to be photographed by an external camera that photographs the second area, A first image analysis unit analyzes images captured by an on-board camera mounted on a vehicle moving through the first area, A second image analysis unit analyzes the image captured by the external camera that photographs the second area, A monitoring unit monitors the plurality of vehicles based on the image analysis results of the first image analysis unit and the second image analysis unit, respectively. A vehicle monitoring system equipped with the following features.

2. The first area is an area where a predetermined operation is performed for each of the plurality of vehicles, The second area is an area through which the multiple vehicles pass without any predetermined work being performed on each of them. The vehicle monitoring system according to claim 1.

3. The second image analysis unit analyzes the captured image at a lower resolution than the first image analysis unit. The vehicle monitoring system according to claim 1.

4. All of the aforementioned vehicles are configured to be movable by unmanned operation. The vehicle monitoring system according to claim 1.

Images