Video transmission system and video transmission method

Abstract

To ensure the accuracy of remote operation of moving vehicles by remote drivers while reducing communication costs.SOLUTION: The video transmission system transmits video from a moving vehicle, which is an object of remote operation by a remote driver, to a terminal on the remote driver's side. The video transmission system detects or predicts active operation by the remote driver whose degree of driving operation exceeds a first threshold value. The video transmission system enhances the quality of the video transmitted to the terminal during a first period after the active operation is detected or predicted, compared to a period other than the first period.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present disclosure relates to a technology for transmitting video from a moving object that is the subject of remote driving by a remote driver to a terminal on the remote driver's side. [Background technology]

[0002] Patent Document 1 discloses a technology for remotely monitoring an autonomous vehicle. The autonomous vehicle transmits video captured by a camera to a monitoring control server. The monitoring control server receives the video transmitted from the autonomous vehicle. If a key frame of the video is not received within a predetermined time, the monitoring control server transmits an emergency control signal to the autonomous vehicle. The autonomous vehicle limits its speed or makes an emergency stop in accordance with the emergency control signal.

[0003] Patent Document 2 discloses a technology for remotely monitoring an autonomous vehicle. An autonomous driving control device installed in an autonomous vehicle transmits detection data detected by a detection unit such as a camera to a remote monitoring center. The autonomous driving control device also calculates the current risk level of the autonomous vehicle. The autonomous driving control device increases the amount of detection data transmitted to the remote monitoring center as the risk level of the autonomous vehicle increases. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2019-003403 A [Patent Document 2] International Publication No. 2018 / 155159 Summary of the Invention [Problem to be solved by the invention]

[0005] Consider remote driving of a mobile object by a remote driver. Images necessary for remote driving are transmitted from the mobile object to the remote driver terminal. Providing high-quality images to the remote driver is preferable from the viewpoint of the accuracy of remote driving by the remote driver. However, as the image quality becomes higher, the amount of transmission data increases, and communication costs also increase.

[0006] One object of the present disclosure is to provide a technology that can ensure the accuracy of remote driving while reducing communication costs when a remote driver remotely drives a moving object. [Means for solving the problem]

[0007] The first aspect relates to a video transmission system that transmits video from a moving object that is the subject of remote driving by a remote driver to a terminal on the remote driver's side. The video transmission system includes one or more processors. The one or more processors execute an aggressive operation determination process to detect or predict an aggressive operation in which the degree of driving operation by the remote driver exceeds a first threshold. Further, the one or more processors execute a video quality increase process that increases the quality of video transmitted to the terminal during a first period after an active operation is detected or predicted, compared to periods other than the first period.

[0008] The second aspect relates to a video transmission method for transmitting video from a moving object that is the subject of remote driving by a remote driver to a terminal on the remote driver's side. The video transmission method is an aggressive operation determination process for detecting or predicting an aggressive operation in which the degree of driving operation by a remote driver exceeds a first threshold; A video quality increasing process for increasing the quality of the video transmitted to the terminal during a first period after an active operation is detected or predicted, compared to a period other than the first period; Includes. Effect of the Invention

[0009] According to the present disclosure, the image quality of the image transmitted from the moving object to the remote driver's terminal is not set uniformly but is changed dynamically. Specifically, the image quality is increased during a first period after an active operation by the remote driver is detected or predicted. When performing an active operation, the remote driver observes the situation around the moving object particularly carefully. Since the image quality is increased at that time, the accuracy of remote driving by the remote driver is improved.

[0010] The image quality during periods other than the first period is set lower than that during the first period. During periods other than the first period, the remote driver does not actively operate the vehicle, so the accuracy of remote driving is ensured without increasing the image quality more than necessary. If images of normal quality are provided, the remote driver can continue remote driving the vehicle with sufficient accuracy. Furthermore, since the image quality is set relatively low, the amount of transmitted data is reduced, and communication costs are reduced.

[0011] In this way, according to the present disclosure, it is possible to ensure the accuracy of remote operation while suppressing communication costs. In other words, it is possible to ensure the accuracy of remote operation while suppressing communication costs. [Brief description of the drawings]

[0012] [Figure 1] FIG. 1 is a schematic diagram showing a configuration example of a remote operation system. [Diagram 2] FIG. 13 is a conceptual diagram showing the relationship between active operation by a remote driver and image quality. [Diagram 3] FIG. 11 is a conceptual diagram for explaining an example of key frame control. [Figure 4] FIG. 11 is a conceptual diagram for explaining an example of video quality control taking into account vehicle speed. [Diagram 5] 11 is a timing chart showing an example of video quality control taking into account active operations. [Figure 6] FIG. 11 is a conceptual diagram for explaining an example of detection and release of an active operation. [Figure 7] 1 is a block diagram showing an example of a functional configuration of a video transmission system. [Figure 8]1 is a flowchart summarizing video quality control taking into account active operation. [Figure 9] FIG. 1 is a block diagram showing an example of the configuration of a vehicle. [Figure 10] FIG. 2 is a block diagram showing an example of the configuration of a remote driver's terminal. [Figure 11] 11 is a block diagram showing a first example of an active operation determination unit. FIG. [Figure 12] 13 is a block diagram showing a second example of an active operation determination unit. FIG. [Figure 13] FIG. 13 is a block diagram showing a third example of an active operation determination unit. [Figure 14] FIG. 13 is a block diagram showing a fourth example of an active operation determination unit. [Figure 15] FIG. 13 is a block diagram showing a fifth example of an active operation determination unit. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] Embodiments of the present disclosure will be described with reference to the accompanying drawings.

[0014] 1. Overview of the remote operation system Consider remote driving of a moving object. Examples of the moving object include a vehicle and a robot. The vehicle may be an autonomous vehicle. Examples of the robot include a logistics robot and a work robot. As an example, in the following description, consider a case where the moving object to be remotely driven is a vehicle. When generalizing, "vehicle" in the following description should be read as "moving object".

[0015] FIG. 1 is a schematic diagram showing a configuration example of a remote driving system 1 according to the present embodiment. The remote driving system 1 includes a vehicle 100, a remote driver terminal 200, and a management device 300. The vehicle 100 is a target for remote driving by a remote driver O (remote operator). The remote driver terminal 200 is a terminal device used when the remote driver O remotely drives the vehicle 100. The remote driver terminal 200 can also be called a remote cockpit. The management device 300 manages the remote driving system 1. Typically, the management device 300 is a management server on the cloud. The management server may be composed of multiple servers that perform distributed processing.

[0016] The vehicle 100, the remote driver terminal 200, and the management device 300 can communicate with each other via a communication network. The vehicle 100 and the remote driver terminal 200 can communicate with each other via the management device 300. In addition, the vehicle 100 and the remote driver terminal 200 may communicate directly with each other without going through the management device 300.

[0017] The vehicle 100 is equipped with various sensors including a camera C. The camera C captures the surroundings of the vehicle 100. The camera C obtains an image VID showing the surroundings of the vehicle 100. The vehicle information VCL is information obtained by the various sensors and includes the image VID captured by the camera C. The vehicle 100 transmits the vehicle information VCL to the remote driver terminal 200.

[0018] The remote driver terminal 200 receives the vehicle information VCL transmitted from the vehicle 100. The remote driver terminal 200 presents the vehicle information VCL to the remote driver O. Specifically, the remote driver terminal 200 is equipped with a display device 220, and displays the video VID and the like on the display device 220. The remote driver O recognizes the surrounding situation of the vehicle 100 by looking at the displayed information, and performs remote driving of the vehicle 100. The remote operation information OPE is information on the driving operation (steering operation, acceleration operation, deceleration operation) by the remote driver O. For example, the remote operation information OPE includes the driving operation amount (steering operation amount, acceleration operation amount, deceleration operation amount) input by the remote driver O. It can be said that the remote operation information OPE is information reflecting the degree of the driving operation by the remote driver O. The remote driver terminal 200 transmits the remote operation information OPE to the vehicle 100.

[0019] The vehicle 100 receives the remote operation information OPE transmitted from the remote driver's terminal 200. The vehicle 100 performs vehicle travel control in accordance with the received remote operation information OPE. In this manner, remote driving of the vehicle 100 is realized.

[0020] 2. Video quality control that takes active operation into account As described above, the video VID required for remote driving is transmitted from the vehicle 100 to the remote driver terminal 200. The remote driver O recognizes the situation around the vehicle 100 by watching the video VID. Providing the remote driver O with high quality video VID is preferable from the viewpoint of the accuracy of remote driving by the remote driver O. However, as the video quality increases, the amount of transmission data increases, and the communication cost increases. Therefore, this embodiment proposes a technology that can ensure the accuracy of remote driving while suppressing the communication cost.

[0021] 2-1. Active manipulation First, with reference to FIG. 2, an "active operation" by the remote driver O will be described. An active operation is a driving operation that is actively performed by the remote driver O. The driving operation is a steering operation (handle operation) to turn the vehicle 100, an acceleration operation (accelerator operation) to accelerate the vehicle 100, or a deceleration operation (brake operation) to decelerate the vehicle 100. For example, when turning the vehicle 100 on a curved road or at an intersection, the remote driver O actively performs a steering operation. As another example, when stopping the vehicle 100 at an intersection or in front of a traffic light, the remote driver O actively performs a deceleration operation. These are active operations. Conversely, when the vehicle 100 is traveling at a constant speed on a straight road, the remote driver O does not particularly perform an active operation.

[0022] In order to more clearly define active operation by the remote driver O, the term "degree of operation" is introduced. The degree of operation is the degree of driving operation by the remote driver O. For example, the degree of operation is proportional to the amount of steering by the remote driver O. As another example, the degree of operation is proportional to the steering speed by the remote driver O. As yet another example, the degree of operation is proportional to the requested acceleration requested by the remote driver O. The requested acceleration is proportional to the amount of acceleration operation by the remote driver O. As yet another example, the degree of operation is proportional to the requested deceleration requested by the remote driver O. The requested deceleration is proportional to the amount of deceleration operation by the remote driver O.

[0023] An aggressive operation by the remote driver O is a driving operation whose degree of operation exceeds the first threshold TH1. In FIG. 2, the degree of operation P0 is equal to or less than the first threshold TH1, and the degree of operation P1 exceeds the first threshold TH1. A driving operation with the degree of operation P1 is an aggressive operation. On the other hand, a driving operation with the degree of operation P0 is not an aggressive operation. For example, when the vehicle 100 is traveling at a constant speed on a straight road, the degree of operation is likely to be P0.

[0024] The aggressive operation may be divided into a plurality of stages (levels). As an example, consider a second threshold TH2 higher than the first threshold TH1 and a third threshold TH3 even higher than the second threshold TH2. The operation degree P1 exceeds the first threshold TH1 and is equal to or lower than the second threshold TH2. A driving operation of such an operation degree P1 is a weak aggressive operation. The operation degree P2 exceeds the second threshold TH2 and is equal to or lower than the third threshold TH3. A driving operation of such an operation degree P2 is a medium aggressive operation. The operation degree P3 exceeds the third threshold TH3. A driving operation of such an operation degree P3 is a strong aggressive operation.

[0025] In addition, the "habits" of remote driving may differ depending on the remote driver O. Even in the same scene, the operation degree P may differ depending on the remote driver O. In consideration of such individuality of the remote driver O, each threshold value including the first threshold value TH1 may be set individually for each remote driver O.

[0026] The aggressive operation by the remote driver O can be detected based on the above-mentioned remote operation information OPE. Also, as described later, it is possible to "predict" that an aggressive operation will be performed before the aggressive operation is actually performed by the remote driver O. A specific method for detecting or predicting an aggressive operation will be described later in Section 5.

[0027] 2-2.Video quality control When the remote driver O remotely drives the vehicle 100, the remote driver O carefully observes the situation around the vehicle 100. In particular, when the remote driver O performs active operation, the remote driver O particularly carefully observes the situation around the vehicle 100. Therefore, when the remote driver O performs active operation, it is desirable to provide the remote driver O with high-quality video VID. This improves the accuracy of remote driving.

[0028] Even when no active operation is performed, the remote driver O of course carefully observes the situation around the vehicle 100. For example, even when the vehicle 100 is traveling at a constant speed on a straight road, the remote driver O of course carefully observes the situation around the vehicle 100. However, even if the video quality is not increased more than necessary, the remote driver O can continue remote driving the vehicle 100 with sufficient accuracy as long as the video VID of normal quality is provided. Rather, by setting the video quality to normal quality, the amount of transmission data can be reduced, and communication costs can be reduced.

[0029] From the above viewpoint, according to the present embodiment, the quality of the video VID transmitted from the vehicle 100 to the remote driver terminal 200 is dynamically controlled in consideration of the active operation by the remote driver O. Such control of the quality of the video VID is hereinafter referred to as "video quality control."

[0030] Referring again to FIG. 2, video quality control that takes active operation into consideration will be described. The default video quality Q0 is the normal video quality of the video VID. When the operation degree P0 is equal to or less than the first threshold TH1, the video quality is set to the default video quality Q0. That is, the operation degree P0 equal to or less than the first threshold TH1 is associated with the default video quality Q0. And, the operation degree P1 that exceeds the first threshold TH1 is associated with the video quality Q1 that is higher than the default video quality Q0.

[0031] According to this embodiment, when an aggressive operation by the remote driver O is not detected or predicted, the video quality is set to the default video quality Q0. Then, in conjunction with the detection or prediction of an aggressive operation by the remote driver O, the video quality is increased to a video quality Q1 higher than the default video quality Q0. In other words, the detection or prediction of an aggressive operation by the remote driver O is used as a trigger to increase the video quality to the video quality Q1 higher than the default video quality Q0.

[0032] When aggressive operations are divided into a plurality of stages (levels), the video quality is also divided into a plurality of stages (levels). For example, when a weak aggressive operation corresponding to the operation degree P1 is detected or predicted, the video quality is set to video quality Q1, which is higher than the default video quality Q0. When a medium aggressive operation corresponding to the operation degree P2 is detected or predicted, the video quality is set to video quality Q2, which is higher than the video quality Q1. When a strong aggressive operation corresponding to the operation degree P3 is detected or predicted, the video quality is set to video quality Q3, which is even higher than the video quality Q2.

[0033] There are various examples of processing for improving image quality.

[0034] The first process for improving the video quality is to increase the frame rate of the video VID. The default frame rate is a frame rate that corresponds to the default video quality Q0. In conjunction with the detection or prediction of an aggressive operation, the frame rate of the video VID is set higher than the default frame rate.

[0035] The second process for improving video quality is to increase the key frame rate of the video VID, in other words, to shorten the key frame interval of the video VID. As is well known, the video VID is composed of key frames (I frames) and other P frames and B frames. A key frame holds all the information of an image, and the entire image can be reproduced from a single key frame. On the other hand, P frames and B frames hold only the information of the difference with a key frame, etc., and the P frames and B frames cannot reproduce the entire image. If P frames and B frames are consecutive, there is a possibility that the deviation from the actual image increases. Therefore, transmitting key frames that can reproduce the entire image by themselves contributes to improving video quality. The default key frame rate is a key frame rate that corresponds to the default video quality Q0. In conjunction with the detection or prediction of an active operation, the key frame rate of the video VID is set higher than the default key frame rate.

[0036] The third process for improving video quality is to temporarily insert key frames into the video VID regardless of the video VID's key frame rate setting. In response to a detected or predicted aggressive operation, a key frame is immediately inserted into the video VID. This also improves video quality for the same reasons as the second process described above.

[0037] The fourth process for improving the video quality is to increase the resolution of the video VID. The default resolution is a resolution corresponding to the default video quality Q0. In conjunction with the detection or prediction of an active operation, the resolution of the video VID is set higher than the default resolution.

[0038] The multiple types of candidate processes for improving the video quality include two or more of the first to fourth processes described above. At least one of the multiple types of candidate processes is selected and executed. Two or more of the multiple types of candidate processes may be selected and executed together. In other words, a combination of two or more processes is also possible.

[0039] 3 is a conceptual diagram for explaining an example of key frame control, showing the key frame structure of a video VID, where the horizontal axis represents time.

[0040] (A) in FIG. 3 shows a case where the second process is executed. The default value of the key frame interval is "5". At time ta, an active operation is detected or predicted. When an active operation is detected or predicted, the key frame interval is changed to "3", which is smaller than the default value. However, the key frame interval actually becomes "3" after time tb, which is later than time ta. In other words, there is a slight time lag between when an active operation is detected or predicted and when the video quality actually improves.

[0041] On the other hand, (B) in FIG. 3 shows a combination of the second process and the third process. When an active operation is detected or predicted at time ta, a temporary key frame is immediately inserted. This improves the image quality immediately without delay. In this way, by combining the third process with the second process, it is possible to suppress the delay until the image quality improves.

[0042] The first threshold TH1, which is a criterion for determining whether an active operation is performed, may be set independently for each of a plurality of types of candidate processes. The first threshold TH1 may be different for each of a plurality of types of candidate processes. For example, the first threshold TH1 for the second process may be set lower than the first threshold TH1 for the first process. In this case, the second process is executed with priority over the first process.

[0043] Depending on the "type" of the aggressive operation, one of multiple types of candidate processes may be determined to be executed. For example, if the aggressive operation is an acceleration operation, the vehicle speed increases. As the vehicle speed increases, the apparent flow of the video VID becomes faster. In particular, the flow of the video VID in the peripheral vision becomes faster. In this case, it is effective to increase the frame rate of the video VID in order to express the speed of the flow of the video VID. That is, if the aggressive operation is an acceleration operation, at least the first process may be executed.

[0044] As another example, when the active operation is a steering operation, the remote driver O increases his / her attention not only to the front but also to the left and right directions. That is, the remote driver O pays attention to the video VID across the entire screen. In this case, it is more effective to increase the definition of the entire video VID than to express the speed of the flow of the video VID. To achieve this, it is effective to increase the key frame rate of the video VID. That is, when the active operation is a steering operation, at least the second process may be executed.

[0045] Fig. 4 is a conceptual diagram for explaining an example of video quality control taking into consideration the vehicle speed of the vehicle 100. In the example shown in Fig. 4, a first process for controlling the frame rate and a second process for controlling the key frame rate are executed. The horizontal axis represents the vehicle speed, and the vertical axis represents the frame rate or the key frame rate.

[0046] When driving at high speed, the apparent flow of the video VID becomes faster. In particular, the flow of the video VID in the peripheral vision becomes faster. In this case, it is effective to increase the frame rate of the video VID in order to express the speed of the flow of the video VID. Therefore, the frame rate of the video VID may increase as the vehicle speed increases. In the example shown in FIG. 4, during the period when the vehicle speed is between Va and Vb, the frame rate increases as the vehicle speed increases. The frame rate in the video quality control is set based on the map shown in FIG. 4.

[0047] On the other hand, when driving at a low speed, the remote driver O pays attention not only to the front but also to the left and right directions. That is, the remote driver O pays attention to the video VID over the entire screen. For example, when driving the vehicle 100 at a low speed in a parking lot, the remote driver O pays attention to the video VID over the entire screen. In this case, it is more effective to increase the definition of the entire video VID than to express the speed of the flow of the video VID. For this purpose, it is effective to increase the key frame rate of the video VID. That is, the key frame rate of the video VID may increase as the vehicle speed decreases. In the example shown in FIG. 4, during the period when the vehicle speed is Vc to Vd, the key frame rate increases as the vehicle speed decreases. The key frame rate in the video quality control is set based on the map shown in FIG. 4.

[0048] 2-3.Timing chart 5 is a timing chart showing an example of video quality control taking active operation into consideration, in which the horizontal axis represents time and the vertical axis represents video quality.

[0049] (A) in FIG. 5 shows a case where an active operation by a remote driver O is detected. Before time t1, the video quality is the default video quality Q0. At time t1, an active operation is detected. In conjunction with the detection of the active operation, the video quality is increased to video quality Q1 (first video quality) that is higher than the default video quality Q0.

[0050] The release condition is a condition for returning the video quality from video quality Q1 (first video quality) to the default video quality Q0. For example, the release condition is that an active operation by the remote driver O is no longer detected. As another example, the release condition is that a certain amount of time has passed since an active operation was detected. At time t2, which is later than time t1, the release condition is met. When the release condition is met, the video quality returns from video quality Q1 to the default video quality Q0.

[0051] As shown in FIG. 5, the video quality may gradually change from video quality Q1 to default video quality Q0. That is, the time for the video quality to return from video quality Q1 to default video quality Q0 may be set to be longer than the time for the video quality to increase from default video quality Q0 to video quality Q1. In this case, the remote driver O is less likely to notice the degradation of video quality. Therefore, the discomfort felt by the remote driver O is reduced.

[0052] In the example shown in (A) of FIG. 5, the video quality is higher than the default video quality Q0 during the period from time t1 to t3. The period during which the video quality is higher than the default video quality Q0 is hereinafter referred to as the "first period." The first period is finite. The default video quality Q0 is the video quality other than the first period. During the first period after an active operation by the remote driver O is detected, the video quality is higher than the default video quality Q0.

[0053] FIG. 5B shows a case where an aggressive operation by the remote driver O is predicted. The aggressive operation is predicted at time tp, which is before time t1 at which the aggressive operation is actually performed. In conjunction with the prediction of the aggressive operation, the video quality increases to video quality Q1 (first video quality) higher than the default video quality Q0. The release condition is the same as in FIG. 5A. In the example shown in FIG. 5B, the period from time tp to t3 is the first period. In the first period after the aggressive operation by the remote driver O is predicted, the video quality becomes higher than the default video quality Q0.

[0054] FIG. 6 is a conceptual diagram for explaining an example of detection and cancellation of an aggressive operation. The horizontal axis represents the degree of operation by the remote driver O. When the degree of operation exceeds the first threshold TH1, it is determined that the remote driver O has performed an aggressive operation. The cancellation threshold THd is a threshold for determining that the remote driver O has stopped performing an aggressive operation. The cancellation condition is that the degree of operation is equal to or less than the cancellation threshold THd. As shown in FIG. 6, the cancellation threshold THd may be set lower than the first threshold TH1. That is, there may be a hysteresis characteristic regarding the detection and cancellation of the aggressive operation. Such a hysteresis characteristic suppresses hunting of the image quality.

[0055] 2-4.Video transmission system 7 is a block diagram showing an example of a functional configuration of a video transmission system 1X for transmitting a video VID from the vehicle 100 to the remote driver's terminal 200. The video transmission system 1X is a part of the remote driving system 1. As shown in FIG.

[0056] The video transmission system 1X includes a camera C and an encoder mounted on a vehicle 100. The camera C acquires a video VID. The encoder encodes the video VID. The vehicle 100 transmits the encoded video VID to a remote driver's terminal 200.

[0057] The video transmission system 1X includes a decoder and a display device 220 on the side of the remote driver terminal 200. The remote driver terminal 200 receives the video VID transmitted from the vehicle 100. The decoder decodes the received video VID. The display device 220 displays the decoded video VID.

[0058] The video transmission system 1X further includes an active operation judgment unit 10 and a video quality determination unit 20. The active operation judgment unit 10 detects or predicts an active operation by the remote driver O. A specific example of the active operation judgment unit 10 will be described in detail later in Section 5.

[0059] The video quality determination unit 20 acquires the judgment result by the active operation judgment unit 10. Then, the video quality determination unit 20 determines the control information of the video quality based on the judgment result by the active operation judgment unit 10. For example, the control information of the video quality is a setting value of the frame rate of the video VID. As another example, the control information of the video quality is a setting value of the key frame rate of the video VID. As yet another example, the control information of the video quality is an instruction to insert a temporary key frame into the video VID.

[0060] 7, video quality determination unit 20 includes a frame rate setting unit 21, a key frame rate setting unit 22, and a key frame insertion unit 23. Frame rate setting unit 21 sets the frame rate of the video VID based on the determination result by active operation judgment unit 10. Key frame rate setting unit 22 sets the key frame rate of the video VID based on the determination result by active operation judgment unit 10. Key frame insertion unit 23 generates an instruction to insert a key frame into the video VID based on the determination result by active operation judgment unit 10.

[0061] The video transmission system 1X controls the encoder mounted on the vehicle 100 in accordance with the control information of the video quality, thereby achieving the video quality control according to the present embodiment.

[0062] As described above, the vehicle 100, the remote driver terminal 200, and the management device 300 can communicate with each other via a communication network. Therefore, information necessary for image quality control can be shared between the vehicle 100, the remote driver terminal 200, and the management device 300. Since information necessary for image quality control can be shared, the active operation determination unit 10 and the image quality determination unit 20 may be included in any of the vehicle 100, the remote driver terminal 200, and the management device 300. The active operation determination unit 10 and the image quality determination unit 20 may be included in separate devices. In other words, the active operation determination unit 10 and the image quality determination unit 20 may be distributed to the vehicle 100, the remote driver terminal 200, and the management device 300. In general, the active operation determination unit 10 and the image quality determination unit 20 are realized by one or more processors.

[0063] FIG. 8 is a flowchart summarizing video quality control taking into account active operation.

[0064] In step S10, the video transmission system 1X performs an "active operation determination process." Specifically, the video transmission system 1X detects or predicts an active operation by the remote driver O. If an active operation is detected or predicted (step S10; Yes), the process proceeds to step S20. On the other hand, if an active operation is not detected or predicted (step S10; No), the process proceeds to step S40.

[0065] In step S20, the video transmission system 1X performs a "video quality increase process." Specifically, the video transmission system 1X sets the video quality of the video VID to be higher than the default video quality Q0. Then, the process proceeds to step S30.

[0066] In step S30, the video transmission system 1X determines whether the cancellation condition is met. If the cancellation condition is not met (step S30; No), the process returns to step S20. On the other hand, if the cancellation condition is met (step S30; Yes), the process proceeds to step S40.

[0067] In step S40, the video transmission system 1X sets the video quality of the video VID to the default video quality Q0.

[0068] 2-5.Effects As described above, according to this embodiment, the image quality of the image VID transmitted from the vehicle 100 to the remote driver terminal 200 is not set uniformly but is changed dynamically. Specifically, the image quality is increased during a first period after an aggressive operation by the remote driver O is detected or predicted. When performing an aggressive operation, the remote driver O observes the situation around the vehicle 100 particularly carefully. Since the image quality is increased at that time, the accuracy of the remote driving by the remote driver O is improved.

[0069] The video quality of the video VID during periods other than the first period is set lower than that during the first period. During periods other than the first period, the remote driver O does not actively operate the vehicle, so the accuracy of remote driving is ensured without increasing the video quality more than necessary. If a video VID of normal quality is provided, the remote driver O can continue remote driving the vehicle 100 with sufficient accuracy. Furthermore, since the video quality is set relatively low, the amount of transmission data is reduced, and communication costs are also reduced.

[0070] In this way, according to the present embodiment, it is possible to ensure the accuracy of remote operation while suppressing communication costs. In other words, according to the present embodiment, it is possible to ensure the accuracy of remote operation while suppressing communication costs.

[0071] 3. Examples of vehicles 3-1. Configuration example 9 is a block diagram showing an example of the configuration of the vehicle 100. The vehicle 100 includes a communication device 110, a sensor group 120, a traveling device 130, and a control device 150.

[0072] The communication device 110 communicates with the outside of the vehicle 100. For example, the communication device 110 communicates with a remote driver's terminal 200 and a management device 300. The communication device 110 may include an encoder (see FIG. 7) that encodes a video VID.

[0073] The sensor group 120 includes a recognition sensor, a vehicle state sensor, a position sensor, etc. The recognition sensor recognizes (detects) the situation around the vehicle 100. Examples of the recognition sensor include a camera C, a LIDAR (Laser Imaging Detection and Ranging), a radar, etc. The vehicle state sensor detects the state of the vehicle 100. The vehicle state sensor includes a speed sensor, an acceleration sensor, a yaw rate sensor, a steering angle sensor, etc. The position sensor detects the position and orientation of the vehicle 100. For example, the position sensor includes a GNSS (Global Navigation Satellite System).

[0074] The traveling device 130 includes a steering device, a drive device, and a braking device. The steering device steers the wheels. For example, the steering device includes an electric power steering (EPS) device. The drive device is a power source that generates a driving force. Examples of the drive device include an engine, an electric motor, and an in-wheel motor. The braking device generates a braking force.

[0075] The control device 150 is a computer that controls the vehicle 100. The control device 150 includes one or more processors 160 (hereinafter simply referred to as processor 160) and one or more storage devices 170 (hereinafter simply referred to as storage device 170). The processor 160 executes various processes. Examples of the processor 160 include a central processing unit (CPU), a graphics processing unit (GPU), an application specific integrated circuit (ASIC), and a field-programmable gate array (FPGA). The storage device 170 stores various information. Examples of the storage device 170 include a volatile memory, a non-volatile memory, a hard disk drive (HDD), and a solid state drive (SSD).

[0076] The vehicle control program PROG1 is a computer program executed by the processor 160. The functions of the control device 150 may be realized by cooperation between the processor 160, which executes the vehicle control program PROG1, and the storage device 170. The vehicle control program PROG1 is stored in the storage device 170. Alternatively, the vehicle control program PROG1 may be recorded in a computer-readable recording medium.

[0077] 3-2. Driving environment information The control device 150 acquires driving environment information ENV indicating the driving environment of the vehicle 100. The driving environment information ENV is stored in the storage device 170.

[0078] The driving environment information ENV includes map information MAP. The map information MAP includes a general navigation map. The map information MAP may indicate lane arrangements and road shapes. The map information MAP may include position information of intersections, stop lines, traffic lights, signs, etc. The control device 150 acquires map information MAP of a required area from a map database. The map database may be stored in the storage device 170, or may be stored in a map management device outside the vehicle 100. In the latter case, the control device 150 communicates with the map management device via the communication device 110 to acquire the required map information MAP.

[0079] The driving environment information ENV also includes surrounding situation information SUR indicating the recognition result by the recognition sensor. For example, the surrounding situation information SUR includes the video VID captured by the camera C. The surrounding situation information SUR may also include object information regarding objects around the vehicle 100. Examples of objects around the vehicle 100 include pedestrians, other vehicles (preceding vehicles, parked vehicles, etc.), white lines, stop lines, traffic lights, signs, roadside structures, etc. The object information indicates the relative position and relative speed of the object with respect to the vehicle 100. For example, by analyzing the video VID obtained by the camera, the object can be identified and the relative position of the object can be calculated. Also, the object can be identified and the relative position and relative speed of the object can be obtained based on the point cloud information obtained by the LIDAR.

[0080] Furthermore, the driving environment information ENV includes vehicle state information STA indicating the results of detection by the vehicle state sensors. The vehicle state information STA indicates the vehicle speed, acceleration (longitudinal acceleration, lateral acceleration), yaw rate, steering angle, etc. of the vehicle 100.

[0081] Furthermore, the driving environment information ENV includes vehicle position information POS indicating the position and moving direction (orientation) of the vehicle 100. The vehicle position information POS is obtained by a position sensor. Highly accurate vehicle position information POS may be obtained by a self-position estimation process (Localization) using map information MAP and surrounding situation information SUR (object information).

[0082] 3-3.Vehicle driving control The control device 150 executes vehicle driving control for controlling the driving of the vehicle 100. The vehicle driving control includes steering control, drive control, and braking control. The control device 150 executes the vehicle driving control by controlling the driving device 130 (the steering device, the drive device, and the braking device).

[0083] The control device 150 may perform automatic driving control based on the driving environment information ENV. Automatic driving means that at least a part of the steering, acceleration, and deceleration of the vehicle 100 is performed automatically, independent of the driver's operation. More specifically, the control device 150 generates a driving plan for the vehicle 100 based on the driving environment information ENV. Furthermore, the control device 150 generates a target trajectory required for the vehicle 100 to drive according to the driving plan, based on the driving environment information ENV. The target trajectory includes a target position and a target speed. Then, the control device 150 performs vehicle driving control so that the vehicle 100 follows the target trajectory.

[0084] 3-4. Processing related to remote operation The following describes a case where remote driving of the vehicle 100 is performed. The control device 150 communicates with the remote driver's terminal 200 via the communication device 110.

[0085] The control device 150 transmits the vehicle information VCL to the remote driver terminal 200. The vehicle information VCL is information necessary for remote driving by the remote driver O, and includes at least a part of the above-mentioned driving environment information ENV. In particular, the vehicle information VCL includes an image VID captured by the camera C. The vehicle information VCL may include other surrounding situation information SUR. The vehicle information VCL may include vehicle state information STA. The vehicle information VCL may include vehicle position information POS.

[0086] In addition, the control device 150 receives remote operation information OPE from the remote driver terminal 200. The remote operation information OPE is information related to remote driving by the remote driver O. For example, the remote operation information OPE includes a driving operation amount input by the remote driver O. The control device 150 performs vehicle driving control according to the received remote operation information OPE.

[0087] The control device 150 may have the functions of both the active manipulation judging unit 10 and the video quality determining unit 20 shown in Fig. 7. The video quality determining unit 20 determines control information for video quality based on the judgment result by the active manipulation judging unit 10. The control device 150 controls the encoder according to the control information for video quality.

[0088] The control device 150 may not have the function of the active manipulation determination unit 10, but may have the function of the video quality determination unit 20. In that case, the control device 150 acquires information on the determination result by the external active manipulation determination unit 10 via the communication device 110.

[0089] The active operation determination unit 10 and the video quality determination unit 20 may be present outside the vehicle 100. In this case, the control device 150 determines control information of the video quality determined by the video quality determination unit 20 via the communication device 110. Then, the control device 150 controls the encoder according to the control information of the video quality.

[0090] 4. Example of remote driver terminal configuration 10 is a block diagram showing an example of the configuration of the remote driver's terminal 200. The remote driver's terminal 200 includes a communication device 210, a display device 220, an input device 230, and a control device 250.

[0091] The communication device 210 communicates with the vehicle 100 and the management device 300. The communication device 110 may include a decoder (see FIG. 7) that decodes the video VID.

[0092] The display device 220 displays various information for the remote driver O who performs remote driving. In other words, the display device 220 displays various information to present the various information to the remote driver O. The display device 220 may be a touch panel.

[0093] The input device 230 accepts input from the remote driver O. For example, the input device 230 includes remote driving members that the remote driver O operates when remotely driving the vehicle 100. The remote driving members include a steering wheel, an accelerator pedal, a brake pedal, a turn signal, and the like.

[0094] The control device 250 controls the remote driver terminal 200. The control device 250 includes one or more processors 260 (hereinafter simply referred to as processor 260) and one or more storage devices 270 (hereinafter simply referred to as storage device 270). The processor 260 executes various processes. Examples of the processor 260 include a CPU, a GPU, an ASIC, and an FPGA. The storage device 270 stores various information. Examples of the storage device 270 include a volatile memory, a non-volatile memory, an HDD, and an SSD.

[0095] The remote driving control program PROG2 is a computer program executed by the processor 260. The functions of the control device 250 may be realized by cooperation between the processor 260, which executes the remote driving control program PROG2, and the storage device 270. The remote driving control program PROG2 is stored in the storage device 270. Alternatively, the remote driving control program PROG2 may be recorded in a computer-readable recording medium. The remote driving control program PROG2 may be provided via a network.

[0096] The control device 250 communicates with the vehicle 100 via the communication device 210. The control device 250 receives vehicle information VCL transmitted from the vehicle 100. The control device 250 presents the vehicle information VCL, including the video VID, to the remote driver O by displaying the vehicle information VCL on the display device 220. The remote driver O can recognize the state of the vehicle 100 and the surrounding situation based on the vehicle information VCL displayed on the display device 220.

[0097] The remote driver O operates the remote driving member of the input device 230. The amount of operation of the remote driving member is detected by a sensor installed on the remote driving member. The control device 250 generates remote operation information OPE reflecting the amount of operation of the remote driving member by the remote driver O. It can be said that the remote operation information OPE is information reflecting the degree of driving operation by the remote driver O. Then, the control device 250 transmits the remote operation information OPE to the vehicle 100 via the communication device 210.

[0098] The control device 250 may have the function of the active manipulation determination unit 10 shown in Fig. 7. In this case, the control device 250 transmits information on the determination result by the active manipulation determination unit 10 to the vehicle 100 via the communication device 210.

[0099] The control device 250 may have the functions of both the active operation determination unit 10 and the video quality determination unit 20 shown in Fig. 7. The video quality determination unit 20 determines control information for video quality based on the determination result by the active operation determination unit 10. The control device 250 transmits the control information for video quality to the vehicle 100 via the communication device 210.

[0100] 5. Example of active operation judgment unit Various examples of the aggressive operation determination unit 10 that detects or predicts aggressive operation by the remote driver O will be described below.

[0101] 5-1. First Example Fig. 11 is a block diagram showing a first example of the active operation determination unit 10. The active operation determination unit 10 includes an active operation detection unit 11 and a determination unit 15. The active operation detection unit 11 detects an active operation by a remote driver O. In the example shown in Fig. 11, the active operation detection unit 11 includes a first detection unit 11-1 and a second detection unit 11-2.

[0102] The first detection unit 11-1 detects an aggressive operation by the remote driver O based on the remote operation information OPE. As described above, the remote operation information OPE reflects the degree of driving operation (operation degree) by the remote driver O. For example, the operation degree is proportional to the steering amount by the remote driver O. As another example, the operation degree is proportional to the steering speed by the remote driver O. As yet another example, the operation degree is proportional to the requested acceleration requested by the remote driver O. As yet another example, the operation degree is proportional to the requested deceleration requested by the remote driver O. The first detection unit 11-1 detects an aggressive operation by determining whether the operation degree by the remote driver O exceeds a first threshold value TH1 based on the remote operation information OPE. The first threshold value TH1 differs for each type of operation degree. The first detection unit 11-1 may detect an aggressive operation based on a map indicating a correspondence relationship between the degree of driving operation and the aggressive operation.

[0103] The second detection unit 11-2 detects an aggressive operation by the remote driver O based on the vehicle state information STA. The remote driving of the vehicle 100 by the remote driver O is reflected in the behavior of the vehicle 100. Therefore, the aggressive operation by the remote driver O can be detected based on the vehicle state information STA. For example, when the longitudinal acceleration of the vehicle 100 exceeds the first threshold value TH1, the second detection unit 11-2 detects the aggressive operation. As another example, when the yaw rate or lateral acceleration of the vehicle 100 exceeds the first threshold value TH1, the second detection unit 11-2 detects the aggressive operation. The first threshold value TH1 differs for each vehicle state. The second detection unit 11-2 may detect the aggressive operation based on a map showing the correspondence between the vehicle state information STA and the aggressive operation.

[0104] The first threshold value TH1 or the map may be set individually for each remote driver O. The aggressive operation may be divided into a plurality of stages (levels) (see FIG. 2).

[0105] The first detection unit 11-1 and the second detection unit 11-2 each output a detection result to the determination unit 15. The detection result includes whether or not an active operation has been detected, the content (type) of the detected active operation, and the like.

[0106] The determination unit 15 receives the detection result by the first detection unit 11-1 and the detection result by the second detection unit 11-2. When an active operation is detected by at least one of the first detection unit 11-1 and the second detection unit 11-2, the determination unit 15 determines that an active operation has been performed by the remote driver O. The determination unit 15 notifies the image quality determination unit 20 of the determination result. The determination unit 15 may notify the image quality determination unit 20 of the content (type) of the detected active operation.

[0107] When the remote driver O remotely drives the vehicle 100, the remote operation information OPE changes at an earlier timing than the vehicle state information STA. Therefore, basically, the first detection unit 11-1 detects an active operation earlier than the second detection unit 11-2.

[0108] 5-2. Second Example 12 is a block diagram showing a second example of the active manipulation determination unit 10. The active manipulation determination unit 10 includes a history database and an active manipulation prediction unit 12 in addition to the active manipulation detection unit 11 described in the first example above.

[0109] The history database indicates the position where an aggressive operation was detected in the past. When an aggressive operation is detected by the aggressive operation detection unit 11, the aggressive operation determination unit 10 registers the position of the vehicle 100 at the timing when the aggressive operation was detected in the history database. The position of the vehicle 100 is obtained from the vehicle position information POS. The history database may associate the position where an aggressive operation was detected in the past with the moving direction of the vehicle 100 at that time. The moving direction of the vehicle 100 is obtained from the vehicle position information POS. The history database may associate the content of the aggressive operation with the position where the aggressive operation was detected.

[0110] In a scene where a remote driver O performs an aggressive operation, it is highly likely that the same remote driver O or other remote drivers O will also perform an aggressive operation. Therefore, by utilizing the history database, it is possible to "predict" the occurrence of aggressive operations in the near future.

[0111] More specifically, the proactive operation prediction unit 12 acquires vehicle position information POS. The vehicle position information POS indicates the current position and moving direction of the vehicle 100. The proactive operation prediction unit 12 predicts the occurrence of an aggressive operation on the road ahead of the vehicle 100 based on the history database and the current position and moving direction of the vehicle 100. In other words, the proactive operation prediction unit 12 predicts the occurrence of an aggressive operation that is likely to be performed by the remote driver O in the near future based on the history database and the current position and moving direction of the vehicle 100. The proactive operation prediction unit 12 outputs the prediction result to the determination unit 15. The prediction result includes whether or not an aggressive operation is predicted, the content (type) of the predicted aggressive operation, and the like.

[0112] The determination unit 15 receives the detection result by the active operation detection unit 11 and the prediction result by the active operation prediction unit 12, and integrates them. The determination unit 15 may weight the detection result by the active operation detection unit 11 and the prediction result by the active operation prediction unit 12. When an active operation is detected or predicted, the determination unit 15 notifies the video quality determination unit 20 of that fact. The determination unit 15 may notify the video quality determination unit 20 of the content (type) of the detected or predicted active operation.

[0113] 5-3.Third Example 13 is a block diagram showing a third example of the aggressive operation determination unit 10. The aggressive operation determination unit 10 includes an aggressive operation prediction unit 13. The aggressive operation prediction unit 13 grasps the condition of the road ahead of the vehicle 100 based on the driving environment information ENV, and predicts the occurrence of an aggressive operation on the road ahead.

[0114] For example, if the road ahead of the vehicle 100 is greatly curved, the remote driver O is predicted to steer aggressively. The shape of the road ahead of the vehicle 100 is obtained from map information MAP. As another example, if there is an intersection, a stop line, a stop sign, or a traffic light ahead of the vehicle 100, the remote driver O is predicted to decelerate aggressively. Position information of the intersection, the stop line, the traffic light, the sign, etc. is registered in the map information MAP. The current position and moving direction of the vehicle 100 are obtained from the vehicle position information POS. The aggressive operation prediction unit 13 grasps the situation of the road ahead of the vehicle 100 based on the vehicle position information POS and the map information MAP. Then, the aggressive operation prediction unit 13 predicts the occurrence of an aggressive operation on the road ahead based on the situation of the road ahead of the vehicle 100.

[0115] Instead of map information MAP, the condition of the road ahead of the vehicle 100 can also be grasped based on surrounding situation information SUR that indicates the recognition result by the recognition sensor. In this case, the active operation prediction unit 13 grasps the condition of the road ahead of the vehicle 100 based on the vehicle position information POS and the surrounding situation information SUR. Then, the active operation prediction unit 13 predicts the occurrence of an active operation on the road ahead of the vehicle 100 based on the condition of the road ahead of the vehicle 100.

[0116] The active operation prediction unit 13 may take into account the vehicle speed in addition to the condition of the road ahead of the vehicle 100. This is because the higher the vehicle speed, the more likely it is that the remote driver O will actively decelerate. In this case, the active operation prediction unit 13 also takes into account the vehicle state information STA to predict the occurrence of an active operation on the road ahead of the vehicle 100.

[0117] A prediction model generated in advance through machine learning such as deep learning may be used for the prediction process in the active operation prediction unit 13. The input to the prediction model is the driving environment information ENV, and the output from the prediction model is the presence or absence of an active operation and the content of the active operation.

[0118] The aggressive operation prediction unit 13 outputs the prediction result to the determination unit 15. The prediction result includes whether or not an aggressive operation has been predicted, the content (type) of the predicted aggressive operation, and the like.

[0119] The determination unit 15 receives the prediction result by the aggressive operation prediction unit 13. When an aggressive operation is predicted, the determination unit 15 notifies the image quality determination unit 20 of that fact. The determination unit 15 may notify the image quality determination unit 20 of the content (type) of the predicted aggressive operation.

[0120] 5-4.Fourth Example 14 is a block diagram showing a fourth example of the active operation judgment unit 10. The active operation judgment unit 10 includes an active operation prediction unit 14 and a judgment unit 15. The active operation prediction unit 14 predicts an active operation by the remote driver O based on the vehicle state information STA.

[0121] For example, when a strong crosswind blows and the vehicle 100 skids, the remote driver O is likely to actively perform a steering operation to return the vehicle 100 to its original lateral position and stabilize the vehicle 100. Therefore, when the lateral acceleration of the vehicle 100 exceeds the first threshold value TH1, the active operation prediction unit 14 predicts an active operation by the remote driver O. The determination unit 15 is the same as in the third example.

[0122] 5-5. Fifth Example It is also possible to combine two or more of the above-mentioned examples of the active operation determination unit 10.

[0123] FIG. 15 is a block diagram showing a fifth example of the aggressive operation determination unit 10. In the example shown in FIG. 15, the aggressive operation determination unit 10 includes an aggressive operation detection unit 11 and aggressive operation prediction units 12 to 14. The determination unit 15 receives the detection result by the aggressive operation detection unit 11 and the prediction result by the aggressive operation prediction units 12 to 14, and integrates them. The determination unit 15 may weight the detection result by the aggressive operation detection unit 11 and the prediction result by the aggressive operation prediction units 12 to 14. When an aggressive operation is detected or predicted, the determination unit 15 notifies the image quality determination unit 20 of the fact. The determination unit 15 may notify the image quality determination unit 20 of the content (type) of the detected or predicted aggressive operation. [Explanation of symbols]

[0124] 1 Remote Operation System 1X Video Transmission System 10 Active operation determination unit 20 Video quality determination section 21 Frame rate setting section 22 Key frame rate setting section 23 Keyframe Insertion Section 100 vehicles 200 Remote Driver Terminal 300 Management device OPE Remote Operation Information VCL vehicle information

Claims

1. A video transmission system that transmits video from a moving object that is a remote driving target by a remote driver to a terminal of the remote driver, One or more processors; The one or more processors: an aggressive operation determination process for detecting or predicting an aggressive operation in which the degree of driving operation by the remote driver exceeds a first threshold; a video quality increasing process for increasing the quality of the video transmitted to the terminal during a first period after the active operation is detected or predicted, compared to a period other than the first period; configured to run Video transmission system.

2. 2. The video transmission system according to claim 1, The image quality increase process includes inserting a key frame into the image in response to the active operation being detected or predicted, regardless of a setting of a key frame rate for the image. Video transmission system.

3. 3. A video transmission system according to claim 1, The image quality increasing process includes increasing a key frame rate of the image in the first period compared to a period other than the first period. Video transmission system.

4. 2. The video transmission system according to claim 1, Multiple types of processing candidates are a first process for making a frame rate of the video in the first period higher than a frame rate outside the first period; a second process of setting a key frame rate of the video in the first period higher than a key frame rate of a period other than the first period; a third process of inserting a key frame into the image in response to the detection or prediction of the active operation, regardless of the setting of the key frame rate of the image; Two or more of the following are included: The image quality increasing process includes executing at least one of the plurality of candidate processes. Video transmission system.

5. 5. A video transmission system according to claim 4, The first threshold is set independently for each of the plurality of types of candidate processes. Video transmission system.

6. 5. A video transmission system according to claim 4, The image quality increasing process includes determining which of the plurality of candidate processes to execute in response to the type of the active operation. Video transmission system.

7. 7. A video transmission system according to claim 6, The video quality increasing process includes: When the positive operation is an acceleration operation, executing at least the first process; When the positive operation is a steering operation, at least the second process is executed. Includes Video transmission system.

8. 5. A video transmission system according to claim 4, The video quality increasing process includes: increasing the frame rate of the video during the first period as the speed of the moving object increases; increasing the key frame rate of the video during the first time period as the speed of the moving object decreases; Includes Video transmission system.

9. 2. The video transmission system according to claim 1, a default video quality is the quality of the video outside the first time period; The video quality increasing process includes: In response to the detection or prediction of the active operation, increasing the quality of the image to a first image quality higher than the default image quality; if a release condition is met after the increase in the quality of the video, returning the quality of the video from the first video quality to the default video quality; Includes Video transmission system.

10. 10. A video transmission system according to claim 9, The video quality increasing process includes setting a time during which the quality of the video returns from the first video quality to the default video quality longer than a time during which the quality of the video increases from the default video quality to the first video quality. Video transmission system.

11. 10. A video transmission system according to claim 9, The release condition is that the degree of the driving operation by the remote driver is equal to or less than a release threshold, The release threshold is lower than the first threshold. Video transmission system.

12. 2. The video transmission system according to claim 1, The active operation determination process includes: acquiring remote operation information reflecting the degree of the driving operation by the remote driver; determining whether the degree of the driving operation exceeds the first threshold based on the remote operation information, thereby detecting the active operation; Includes Video transmission system.

13. 13. A video transmission system according to claim 12, The active operation determination process includes: accessing a history database indicating locations where the aggressive operation has been detected in the past; Obtaining information on a current position and a moving direction of the moving object; predicting the aggressive maneuver on a road ahead of the vehicle based on the history database and the current location and direction of travel of the vehicle; Includes Video transmission system.

14. A video transmission system according to claim 1 or 12, The active operation determination process includes: Obtaining information on a current position and a moving direction of the moving object; grasping a road condition ahead of the moving body based on map information or a recognition result by a recognition sensor mounted on the moving body; predicting the aggressive operation on the road ahead of the moving body based on the condition of the road ahead of the moving body; Includes Video transmission system.

15. A video transmission method for transmitting video from a moving object that is a target of remote driving by a remote driver to a terminal of the remote driver, comprising: an aggressive operation determination process for detecting or predicting an aggressive operation in which the degree of driving operation by the remote driver exceeds a first threshold; a video quality increasing process for increasing the quality of the video transmitted to the terminal during a first period after the active operation is detected or predicted, compared to a period other than the first period; Includes Video transmission method.

Images