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: a plurality of first cameras that photograph each of a plurality of first divided areas constituting a first area in which a plurality of vehicles move continuously; a plurality of second cameras that photograph each of a plurality of second divided areas constituting a second area in which a plurality of vehicles move intermittently; a first image analysis unit that analyzes the images captured by each of the plurality of first cameras; a second image analysis unit that extracts and analyzes images in which vehicles are visible from the images captured by each of the plurality of second cameras; 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.

Description

Technical Field

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

Background Art

[0002] In a vehicle monitoring system that monitors 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 technique, 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 that monitors a plurality of vehicles, it is continuously required 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: a plurality of first cameras that photograph each of a plurality of first divided areas constituting a first area in which a plurality of vehicles move continuously; a plurality of second cameras that photograph each of a plurality of second divided areas constituting a second area in which a plurality of vehicles move intermittently; a first image analysis unit that analyzes the images captured by each of the plurality of first cameras; a second image analysis unit that extracts and analyzes images in which the vehicles are visible from the images captured by each of the plurality of second cameras; 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 load on image analysis processing, i.e., the load on monitoring processing, by limiting the analysis processing of images captured in an area in which a plurality of vehicles move intermittently one by one, compared to the analysis processing of images captured in an area in which a plurality of vehicles move continuously in a convoy.

[0007] The second image analysis unit may be configured to extract and analyze only the images in which the vehicle is visible from among the images captured by each of the plurality of second cameras.

[0008] 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.

[0009] The second image analysis unit may be configured to analyze the captured image at a lower resolution than the first image analysis unit.

[0010] Each of the aforementioned vehicles may be configured to be movable by unmanned operation. [Effects of the Invention]

[0011] This disclosure makes it possible to provide a vehicle monitoring system that can reduce the load on monitoring processing. [Brief explanation of the drawing]

[0012] [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]

[0013] 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.

[0014] <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.

[0015] As shown in FIG. 1, the vehicle monitoring system 50 includes a server 200, a camera group 310, and a camera group 320. FIG. 1 also shows a plurality of vehicles 100 that are the monitoring targets of the vehicle monitoring system 50. Each vehicle 100 is, for example, a self-driving vehicle that can move during the manufacturing process. In other words, each vehicle 100 is, for example, a vehicle that can move by autonomous driving during the manufacturing process.

[0016] Each vehicle 100 is a vehicle before completion. Each vehicle 100 before completion is manufactured as a finished product by receiving predetermined work from workers (not shown) or robots (not shown) in the area of each manufacturing process while moving along a preset movement route (track). The predetermined work includes, for example, component assembly, switch operation, welding, inspection, etc. In the example of FIG. 1, areas A1 and C1 are areas where predetermined work is performed on each vehicle 100, and area B1 provided between areas A1 and C1 is an area where each vehicle 100 simply passes through without any predetermined work being performed on it.

[0017] The plurality of vehicles 100 move in a formation. For example, the plurality of vehicles 100 move so that the inter-vehicle distance is constant in each area. Here, in area A1 (the first area), since predetermined work is performed on each vehicle 100, the moving speed of each vehicle 100 becomes slow. Therefore, the plurality of vehicles 100 tend to be dense and move continuously in a formation. In contrast, in area B1 (the second area), since no predetermined work is performed on each vehicle 100, the moving speed of each vehicle 100 is relatively fast. Therefore, the plurality of vehicles 100 are not likely to be dense and move intermittently one by one.

[0018] The camera group 310 is composed of a plurality of cameras, which is a type of external sensor 300, and captures an area A1 where a predetermined operation is performed for each vehicle 100. In the example of FIG. 1, the camera group 310 is composed of four cameras 311 to 314. The camera 311 captures an area A11 which is a part of the area A1, the camera 312 captures an area A12 which is a part of the area A1, the camera 313 captures an area A13 which is a part of the area A1, and the camera 314 captures an area A14 which is a part of the area A1. Each of the cameras 311 to 314 has a communication function and transmits data such as captured images via the network 500 to the server 200.

[0019] The camera group 320 is composed of a plurality of cameras, which is a type of external sensor 300, and captures an area B1 through which each vehicle 100 simply passes. In the example of FIG. 1, the camera group 320 is composed of four cameras 321 to 324. The camera 321 captures an area B11 which is a part of the area B1, the camera 322 captures an area B12 which is a part of the area B1, the camera 323 captures an area B13 which is a part of the area B1, and the camera 324 captures an area B14 which is a part of the area B1. Each of the cameras 321 to 324 has a communication function and transmits data such as captured images via the network 500 to the server 200.

[0020] The server 200 monitors the vehicle 100 in the area A1 based on the captured image of the area A1 received from the camera group 310. Also, the server 200 monitors the vehicle 100 in the area B1 based on the captured image of the area B1 received from the camera group 320. For example, the server 200 monitors whether each vehicle 100 is moving on the planned route or not, or whether the predetermined operation is being performed on each vehicle 100 or not. Also, the server 200 controls the movement of the vehicle 100 while estimating the position of the vehicle 100 based on the captured image of the vehicle 100 received from the camera groups 310 and 320, for example.

[0021] Next, we will explain the control system of the vehicle monitoring system 50 using Figure 2. Figure 2 is a block diagram showing the control system of the vehicle monitoring system 50.

[0022] As shown in Figure 2, the server 200 includes at least a communication device 205, an image analysis unit (first image analysis unit) 206, an image analysis unit (second image analysis unit) 207, a monitoring unit 208, and a remote control unit 210. Each vehicle 100 includes at least a vehicle control device 110, an actuator group 120, and a communication device 130. Note that the server 200 is not limited to being composed of a single physical device, but may be composed of multiple distributed devices. For example, the image analysis units 206 and 207 may be composed of a single physical device, or they may be composed of separate devices.

[0023] In server 200, communication device 205 communicates with camera group 310, camera group 320, and each vehicle 100 via network 500. For example, communication device 205 receives data such as captured images from camera groups 310 and 320, and transmits vehicle control information to each vehicle 100.

[0024] The image analysis unit 206 analyzes the images captured by the camera group 310 that photograph area A1. Specifically, the communication device 205 receives data such as captured images from the camera group 310 that photograph area A1. The image analysis unit 206 then analyzes the received images from the camera group 310 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 A1, as well as the driving state of the vehicle 100 in area A1.

[0025] In this case, the multiple vehicles 100 in area A1 are densely packed and moving continuously in a convoy. Therefore, the image analysis unit 206 analyzes all the images captured by the four cameras 311 to 314 that make up the camera group 310. Since there is a high probability that at least one of the vehicles 100 is always located within the shooting area of ​​each camera 311 to 314, it is preferable for the image analysis unit 206 to analyze all the images captured by cameras 311 to 314 at a higher resolution than the image analysis unit 207, which will be described later.

[0026] The image analysis unit 207 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 207 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.

[0027] In this case, the vehicles 100 in area B1 are not clustered together, but are moving intermittently one by one. Therefore, the image analysis unit 207 extracts and analyzes only the images that show the vehicles 100 from the images captured by each of the four cameras 321 to 324 that make up the camera group 320. This reduces the load on the image analysis unit.

[0028] For example, if the image analysis unit 207 detects that vehicle 100 has moved from area C1 to area B1 by analyzing images captured by a camera (not shown) capturing area C1 (or receives such information), it may perform analysis processing only on images captured by camera 321 capturing area B11 near the entrance to area B1. In this case, the image analysis unit 207 may predict the position of vehicle 100 based on the vehicle's speed in area B1, and select the images to be analyzed from the images captured by cameras 321 to 324 based on the predicted position of vehicle 100. Alternatively, the image analysis unit 207 may perform analysis processing on each of the images captured by cameras 321 to 324 at a low resolution sufficient to detect whether or not vehicle 100 is present, and when vehicle 100 is detected, it may switch to a higher resolution for the analysis processing of only the images in which vehicle 100 is visible.

[0029] Furthermore, in area B1, a higher accuracy in estimating the position of each vehicle is not required than in area A1. Therefore, the image analysis unit 207 may be configured to analyze the captured images at a lower resolution than the image analysis unit 206. This further reduces the load on image analysis.

[0030] The monitoring unit 208 monitors multiple vehicles 100 based on the image analysis results from the image analysis units 206 and 207. For example, the monitoring unit 208 monitors whether each vehicle 100 is moving along the planned route, or whether the planned work is being performed on each vehicle 100.

[0031] 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 208 (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.

[0032] Thus, the vehicle monitoring system 50 according to the present disclosure limits the analysis process of the captured image of the area where the plurality of vehicles 100 move intermittently one by one, as compared with the analysis process of the captured image of the area where the plurality of vehicles 100 form a queue and move continuously, thereby reducing the load on the image analysis process, that is, the load on the monitoring process.

[0033] Hereinafter, in the system 50 related to the manufacture of a vehicle including the above-described vehicle monitoring system, a driving control example for controlling the driving of the vehicle 100 will be described.

[0034] <A. Driving Control Example 1> FIG. 3 is a conceptual diagram showing the configuration of the system 50 in Driving 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.

[0035] 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 "driving" can be appropriately replaced with "moving".

[0036] 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 "running", "turning", and "stopping" of the vehicle 100. Autonomous driving is realized by automatic or manual remote control using a device located outside the vehicle 100, or by autonomous control of the vehicle 100. A passenger who does not perform a driving operation may be on board the vehicle 100 traveling by autonomous driving. Passengers who do not perform a driving operation include, for example, a person simply sitting in the seat of the vehicle 100, or a person performing work different from the driving operation, such as assembly, inspection, and operation of switches, while on board the vehicle 100. Note that driving by the driving operation of a passenger may be referred to as "manual driving".

[0037] 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.

[0038] 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.

[0039] 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.

[0040] 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.

[0041] 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.

[0042] 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.

[0043] 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. Note that the remote control unit 210 may also include the functions of the image analysis unit 206, 207 and the monitoring unit 208, which are shown separately from the remote control unit 210 in Figure 2.

[0044] 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.

[0045] 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.

[0046] 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.

[0047] 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.

[0048] 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.

[0049] 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.

[0050] 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.

[0051] 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.

[0052] 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, causing the vehicle 100 to travel 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.

[0053] <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 explained, they are the same as above.

[0054] 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, outputs the generated driving control signal, and operates 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.

[0055] 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.

[0056] 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.

[0057] 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.

[0058] 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.

[0059] (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.

[0060] (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.

[0061] (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.

[0062] (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.

[0063] (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.

[0064] (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.

[0065] (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.

[0066] (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.

[0067] (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.

[0068] (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.

[0069] 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.

[0070] 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.

[0071] 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]

[0072] 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 Cameras 200 servers 201 Processor 202 memory 203 Input / Output Interfaces 204 Internal Bus 205 Communication equipment 206 Image Analysis Department 207 Image Analysis Department 208 Monitoring Department 210 Remote Control Unit 300 External Sensors 310 Camera Group 311-314 Camera 320 camera group 321-324 Camera 500 Networks

Claims

1. Multiple first cameras that photograph each of the multiple first divided areas that make up the first area in which multiple vehicles move in succession, Multiple second cameras, each capturing a portion of the multiple second divided areas that make up the second area where multiple vehicles move intermittently, A first image analysis unit analyzes the images captured by each of the multiple first cameras, A second image analysis unit extracts and analyzes images from each of the multiple second cameras that show the vehicle, 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 second image analysis unit extracts and analyzes only the images showing the vehicle from among the images captured by each of the plurality of second cameras. The vehicle monitoring system according to claim 1.

3. 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.

4. 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 3.

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

Images