Video transmission system and video transmission method

Abstract

A video transmission system (1X) transmits a video (VID) of a moving body (100), which is the target of a remotely controlled drive by a remotely controlled driver (O), to an end device (200) on one side of the remotely controlled driver (O). The video transmission system (1X) performs an active actuation determination process to detect or predict an active actuation at which the intensity level of a drive actuation by the remotely controlled driver (O) exceeds a first threshold (TH1), and a video quality enhancement process to increase the quality of the video (VID) transmitted to the end device (200) during a first time period after the active actuation has been detected or predicted, compared to a time period other than the first.

Description

Technical field

[0001] The present invention relates to a technology for transmitting a video from a moving body, which is the target of a remote or remote control drive by a remote control driver, to an end device on the remote control driver's side. General state of the art

[0002] Patent literature 1 discloses a technology for the remote monitoring of an autonomous vehicle. The autonomous vehicle transmits a video recorded by a camera to the monitoring control server. The monitoring control server receives a video transmitted by the autonomous vehicle. If the video keyframe is not received within a predetermined time, the monitoring control server transmits an emergency control signal to the autonomous vehicle. The autonomous vehicle then limits its speed or performs an emergency stop in accordance with the emergency control signal.

[0003] Patent document 2 discloses a technology for the remote monitoring of an autonomously driving vehicle. An autonomous driving control device mounted on the autonomously driving vehicle transmits data captured by a camera's sensor to a remote monitoring center. The autonomous driving control device calculates the current risk level of the autonomously driving vehicle. The autonomous driving control device increases the amount of data transmitted to the remote monitoring center as the risk level of the autonomously driving vehicle increases. List of the relevant state of the art Patent literature 1: JP 2019 - 003 403 A Patent literature 2: WO 2018 / 155159 A1 Summary

[0004] This study considers the remote control of a moving body by a remote control operator. The moving body transmits a video signal necessary for the remote control operation to the operator's device. Providing high-quality video to the operator is preferable from the perspective of accuracy in the remote control operation. However, with increasing video quality, the amount of data transmitted and the communication costs also increase.

[0005] One object of the present invention is to provide a technology that is able to ensure the accuracy of remote control driving and reduce communication costs when the remote control driver drives the moving body.

[0006] One aspect concerns a video transmission system for transmitting a video from a moving body, which is the target of a remote control drive by a remote control driver, to an end device on one side of the remote control driver.

[0007] The video transmission system has a processing circuit configured to execute: a determination process for active operation in order to detect or predict an active operation at which the intensity level of a driving operation by the remote control driver exceeds a first threshold; and a video quality enhancement process to increase the quality of a video transmitted to the terminal device during an initial period of time after the active activation has been detected or predicted, compared to a period of time other than the initial period.

[0008] A second aspect concerns a video transmission method for transmitting a video from a moving body, which is the target of a remote control drive by a remote control driver, to an end device on one side of the remote control driver.

[0009] The video transmission procedure includes: a determination process for active operation in order to detect or predict an active operation at which the intensity level of a driving operation by the remote control driver exceeds a first threshold; and a video quality enhancement process to increase the quality of a video transmitted to the terminal device during an initial period of time after the active activation has been detected or predicted, compared to a period of time that differs from the initial period of time.

[0010] According to the present disclosure, the video quality of the video transmitted from the moving body to the terminal device on the remote control operator's side is dynamically changed and not uniformly set. In particular, the video quality is increased during the initial period after the remote control operator's active input is detected or predicted. When performing an active input, the remote control operator observes the situation around the moving body with particular precision. The accuracy of the remote control operation is improved because the video quality is increased during this time.

[0011] The video quality during the period other than the first is set to be lower than that of the first period. Since the remote control operator performs no active operation during this period, the accuracy of the remote control operation is ensured without unnecessarily increasing the video quality. Even if the video is provided at normal quality, the remote control operator can continue to control the moving object with sufficient accuracy. Because the video quality is set relatively low, the amount of data transmitted and communication costs are reduced.

[0012] As described above, according to the present disclosure, it is possible to ensure the accuracy of remote control and reduce communication costs. In other words, it is possible to both ensure the accuracy of remote control and reduce communication costs. Brief description of the illustrations Fig. 1 is a schematic diagram showing a configuration example of a long-distance driving system; Fig. Figure 2 is a conceptual illustration showing a relationship between active operation by a remote control driver and video quality; Fig. Figure 3 is a conceptual diagram to illustrate an example of keyframe control; Fig. Figure 4 is a conceptual illustration to explain an example of video quality control taking into account vehicle speed; Fig. Figure 5 is a time diagram showing an example of video quality control taking into account active operation; Fig. Figure 6 is a conceptual illustration to explain an example of recording and resetting active activity; Fig. Figure 7 is a block diagram showing an example of a functional configuration of a video transmission system; Fig. Figure 8 is a flowchart that summarizes video quality control taking into account active operation; Fig. Figure 9 is a block diagram showing an example of a vehicle configuration; Fig. Figure 10 is a block diagram showing an example of a remote control driver terminal configuration; Fig. Figure 11 is a block diagram showing a first example of the unit of determination for an active operation; Fig. Figure 12 is a block diagram showing a second example of the unit of determination for an active operation; Fig. Figure 13 is a block diagram showing a third example of the unit of determination for an active activity; Fig. Figure 14 is a block diagram showing a fourth example of the unit of determination for an active activity; and Fig. Figure 15 is a block diagram showing a fifth example of the unit of determination for an active activity. Detailed description

[0013] Embodiments of the present disclosure are described with reference to the accompanying illustrations. 1. Overview of the long-distance driving system

[0014] This section considers remote control of a moving body. Examples of moving bodies include vehicles, robots, etc. The vehicle can be an autonomous vehicle. Examples of robots include distribution robots, work robots, etc. The following description considers a case where the moving body, the target of the remote control, is a vehicle. The term "vehicle" in the following description can be generalized by replacing it with "moving body."

[0015] Fig. Figure 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 comprises a vehicle 100, a remote driver terminal 200, and a management device 300. The vehicle 100 is the destination for remote driving by a remote driver O (remote operator). The remote driver terminal 200 is a terminal device used by the remote driver O during the remote driving of the vehicle 100. The remote driver terminal 200 can also be referred to as a remote cockpit. The management device 300 manages the remote driving system 1. The management device 300 is typically a management server in a cloud. The management server can be configured by a plurality of servers performing a distributed process.

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

[0017] Vehicle 100 is equipped with a variety of sensors, including a camera C. Camera C records the environment of vehicle 100. Camera C records a video (VID) showing the environment of vehicle 100. Vehicle information (VCL) is information obtained from the sensors, including the video recorded by camera C. Vehicle 100 transmits the vehicle information (VCL) to the remote control driver terminal 200.

[0018] The remote control driver terminal 200 receives the vehicle information VCL transmitted by the vehicle 100. The remote control driver terminal 200 presents the vehicle information VCL to the remote control driver O. In particular, the remote control driver terminal 200 includes a display device 220 and displays the video VID, etc., on the display device 220. The remote control driver O recognizes the environmental situation of the vehicle 100 based on the displayed information and performs a remote control drive of the vehicle 100. Remote control information OPE is information relating to a driving operation (a steering operation, an acceleration operation, or a deceleration operation) by the remote control driver O.The remote control information OPE includes, for example, a driving input amount (a steering input amount, an acceleration input amount, a deceleration input amount) entered by the remote control driver O. The remote control information OPE can be described as information that reflects the intensity level of the driving input by the remote control driver O. The remote control driver terminal 200 transmits the remote control information OPE to the vehicle 100.

[0019] Vehicle 100 receives the remote control information OPE transmitted by the remote control driver terminal 200. Vehicle 100 then executes vehicle control according to the received remote control information OPE. In this way, remote control of vehicle 100 is achieved. 2. Video quality control taking into account active operation

[0020] As described above, the video VID required for remote driving is transmitted from vehicle 100 to the remote driver terminal 200. The remote driver O recognizes the vehicle 100's surroundings by reviewing the video VID. Providing the remote driver O with high-quality video VID is preferable for the accuracy of the remote driving. However, higher video quality increases the amount of data transmitted and communication costs. The present embodiment proposes a technology that ensures the accuracy of the remote driving while reducing communication costs. 2-1. Active engagement

[0021] First, an “active activation” by the remote control driver O is described with reference to Fig. 2 described. Active operation corresponds to a driving operation actively performed by the remote control driver O. Driving operation is a steering operation (steering wheel operation) to turn vehicle 100, an acceleration operation (accelerator pedal operation) to accelerate vehicle 100, or a deceleration operation (brake operation) to decelerate vehicle 100. For example, the remote control driver O actively performs the steering operation when steering vehicle 100 on a winding road or at an intersection. As another example, the remote control driver O actively performs the deceleration operation when causing vehicle 100 to stop before an intersection or a traffic light. These are some examples of active operations. In contrast, the remote control driver O does not perform any special active operation when vehicle 100 is traveling at a constant speed on a straight road.

[0022] To define the active control input by the remote control driver O more precisely, the term "input intensity" is introduced. Input intensity corresponds to the degree of intensity of the control input by the remote control driver O. For example, input intensity is proportional to the steering input by the remote control driver O. Another example is input intensity proportional to the steering speed by the remote control driver O. Yet another example is input intensity proportional to the acceleration demanded by the remote control driver O. The required acceleration is proportional to the amount of acceleration input by the remote control driver O. Another example is input intensity proportional to the deceleration demanded by the remote control driver O.The required delay is proportional to the amount of delay applied by the remote control driver O.

[0023] The active activation by the remote control driver O corresponds to the driving activation whose activation intensity exceeds a first threshold value TH1. In Fig. 2. The actuation intensity P0 is equal to or less than the first threshold TH1, and the actuation intensity P1 exceeds the first threshold TH1. Therefore, driving with actuation intensity P1 corresponds to active actuation. On the other hand, driving with actuation intensity P0 is not active actuation. For example, if the vehicle is traveling at 100 km / h on a straight road at a constant speed, the actuation intensity is likely to be equal to P0.

[0024] Active control can be divided into multiple levels. For example, consider a second threshold TH2 and a third threshold TH3. The second threshold TH2 is higher than the first threshold TH1, and the third threshold TH3 is even higher than the second threshold TH2. The control intensity P1 is higher than the first threshold TH1 and equal to or less than the second threshold TH2. Driving with control intensity P1 corresponds to a low level of active control. Control intensity P2 is greater than the second threshold TH2 and equal to or less than the third threshold TH3. Driving with control intensity P2 represents a medium level of active control. Control intensity P3 exceeds the third threshold TH3.Driving operation with the activation intensity P3 is a strong level of active operation.

[0025] An individual's habit of remote control operation can differ depending on the remote control operator O. Even within the same scene, the activation intensity P can vary depending on the remote control operator O. Taking such individuality into account, the thresholds, including the first threshold TH1, can be individually set for each remote control operator O.

[0026] Active actuation by the remote control driver O can be detected based on the remote actuation information OPE described above. As described later, it is also possible to "predict" that active actuation will occur before it is actually performed by the remote control driver O. Some specific procedures for detecting or predicting active actuation are described in Section 5 below. 2-2. Video quality control

[0027] When performing the remote control operation of vehicle 100, the remote control operator O carefully observes the surroundings of vehicle 100. In particular, the remote control operator O pays special attention to the surroundings of vehicle 100 when actively operating the vehicle. Therefore, when the remote control operator O performs the active operation, it is desirable to provide the remote control operator O with a high-quality video. This will improve the accuracy of the remote control operation.

[0028] Even without actively controlling the vehicle, the remote operator O carefully observes the surroundings of vehicle 100. For example, if vehicle 100 is traveling at a constant speed on a straight road, the remote operator O carefully observes its surroundings. However, even if the video quality is not increased beyond what is required, the remote operator O can continue to control vehicle 100 with sufficient accuracy if the video (VID) is provided at normal quality. In fact, setting the video quality to normal reduces the amount of data transmitted and communication costs.

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

[0030] With renewed reference to Fig. Section 2 describes the video quality control taking into account the active input. A standard video quality Q0 corresponds to the normal video quality of video VID. If the input intensity P0 is equal to or less than the first threshold TH1, the video quality is set to the standard video quality Q0. That is, an input intensity P0 equal to or less than the first threshold TH1 is associated with the standard video quality Q0. An input intensity P1 that exceeds the first threshold TH1 is associated with a video quality Q1 that is higher than the standard video quality Q0.

[0031] According to the present embodiment, if active operation by the remote control driver O is not detected or predicted, the video quality is set to the standard video quality Q0. If active operation by the remote control driver O is detected or predicted, the video quality increases to video quality Q1, which is higher than the standard video quality Q0. In other words, the video quality increases to video quality Q1, which is higher than the standard video quality Q0, upon detection or prediction of active operation by the remote control driver O as a trigger.

[0032] If active activity is divided into multiple levels, the video quality is also divided into multiple levels. For example, if the low level of active activity, corresponding to activity intensity P1, is detected or predicted, the video quality is set to Q1, which is higher than the standard Q0. If the medium level of active activity, corresponding to activity intensity P2, is detected or predicted, the video quality is set to Q2, which is higher than Q1. If the high level of active activity, corresponding to activity intensity P3, is detected or predicted, the video quality is set to Q3, which is even higher than Q2.

[0033] A wide variety of processes for improving video quality can be considered.

[0034] A first step in improving video quality is to increase the frame rate of the video VID. A standard frame rate is one that corresponds to the standard video quality Q0. When capturing or predicting active interaction, the frame rate of the video VID is set higher than the standard frame rate.

[0035] A second process for increasing video quality involves increasing the keyframe rate of the video (VID), in other words, reducing the keyframe interval. As is well known, the video (VID) consists of a keyframe (I-frame) and other frames, such as a P-frame and a B-frame. The keyframe holds information about the entire image, and the entire image can be reproduced using only the keyframe. On the other hand, the P-frame and B-frame only hold information about differences from the keyframe, and so on, and the entire image cannot be reproduced using only the P-frame or B-frame. As the P-frame or B-frame continues to be transmitted, the deviation from the actual image can increase. Therefore, transmitting the keyframe, which alone can reproduce the entire image, contributes to improved video quality. A standard keyframe rate is one that corresponds to the standard video quality (Q0).In connection with the recording or prediction of active activity, the keyframe rate of the video VID is set to be higher than the standard keyframe rate.

[0036] A third process for increasing video quality involves temporarily inserting the keyframe into the video (VID), regardless of the video's keyframe rate setting. Upon responding to a detected or predicted active input, the keyframe is immediately inserted into the video. For the same reason as the second process, this method also improves video quality.

[0037] A fourth process for increasing or improving video quality is increasing the resolution of the video VID. A standard resolution is the resolution that corresponds to the standard video quality Q0. In connection with the detection or prediction of active activity, the resolution of the video VID is set higher than the standard resolution.

[0038] A plurality of process candidate types for improving video quality comprises two or more of the first through fourth processes described above. At least one of these plurality of process candidate types is selected and executed. Two or more of these plurality of process candidate types can be selected and executed together. That is, two or more processes can be combined.

[0039] Fig. Figure 3 is a conceptual diagram illustrating an example of keyframe control and shows a keyframe configuration of the video VID. The horizontal axis represents time.

[0040] Part (A) in Fig. Case 3 represents a scenario where the second process is executed. The default keyframe interval is "5". At time ta, active input is detected or predicted. When active input is detected or predicted, the keyframe interval is changed to "3", which is smaller than the default value. However, keyframe interval "3" only begins to operate, or become active, at time tb after time ta. This means there is a slight time difference (delay) between the detection or prediction of active input and the actual improvement in video quality.

[0041] On the other hand, part (B) in Fig. Figure 3 represents a case of combining the second and third processes. If the active action is detected or predicted at time ta, an additional keyframe is inserted immediately. This improves the video quality instantly and without delay. In this way, it is possible to limit the delay until the actual improvement in video quality by combining the third process with the second process.

[0042] The first threshold TH1, which is a criterion for determining whether active operation is carried out, can be set independently for each of the multiple process candidate types. The first threshold TH1 can be different for each of these multiple process candidate types. For example, the first threshold TH1 for the second process can be set lower than the first threshold TH1 for the first process. In this case, the second process is given priority over the first.

[0043] The process to be executed from the plurality of process candidate types can be determined according to a "type" of active actuation. For example, the vehicle speed increases if the active actuation is acceleration. As the vehicle speed increases, the visible flow of the video (VID) increases. In particular, the flow of the video (VID) in the peripheral field of vision becomes faster. To express the speed of the video (VID) flow, it is effective in this case to increase the frame rate of the video (VID). That is, if the active actuation corresponds to acceleration, at least the first process can be executed.

[0044] If the active operation corresponds to steering input, the remote control driver O increases attention not only in a forward direction but also in directions to the right and left. That is, the remote control driver O pays attention to the video VID across the entire screen. In this case, it is more effective to increase the sharpness of the entire video VID than to express the speed of the video flow. For this purpose, it is effective to increase the keyframe rate of the video VID. That is, if the active operation corresponds to steering input, at least the second process can be carried out.

[0045] Fig. Figure 4 is a conceptual diagram showing an example of video quality control taking into account the vehicle speed of vehicle 100. In the diagram shown... Fig. In the example shown, the first process controls the frame rate and the second process controls the keyframe rate. The horizontal axis represents the vehicle speed, and the vertical axis represents the frame rate or the keyframe rate.

[0046] When the vehicle travels at high speed, the visible flow of the video (VID) becomes rapid. In particular, the flow of the video (VID) becomes rapid in the peripheral vision. To express the speed of the video flow in this case, it is effective to increase the frame rate of the video (VID). Therefore, the frame rate of the video (VID) can increase as the vehicle speed increases. In the Fig. In example 4, the frame rate increases with increasing vehicle speed during the period in which the vehicle speed increases from Va to Vb. The frame rate in video quality control is based on the value shown in Fig. The map shown in section 4 is set.

[0047] On the other hand, the remote control driver O, while driving at low speed, increases attention not only in the forward direction but also in the directions to the right and left. That is, the remote control driver O pays attention to the video VID across the entire screen. For example, the remote control driver O pays attention to the video VID across the entire screen when the vehicle is driven at low speed in a parking lot. In this case, it is more effective to increase the sharpness of the entire video VID than to express or represent the speed of the video VID's flow. For this purpose, it is effective to increase the keyframe rate of the video VID. That is, the keyframe rate of the video VID can increase as the vehicle speed decreases. In the Fig. In example 4, the keyframe rate increases when the vehicle speed decreases during the period in which the vehicle speed drops from Vc to Vd. The keyframe rate for video quality control is based on the Fig. The map shown in section 4 is set. 2-3. Time diagram

[0048] Fig. Figure 5 is a time graph showing an example of video quality control taking active operation into account. The horizontal axis represents time, and the vertical axis represents video quality.

[0049] Part (A) in Fig. Figure 5 represents a case in which the active operation by the remote control driver O is detected. Before time t1, the video quality is set to the standard video quality Q0. At time t1, the active operation is detected. In connection with the detection of the active operation, the video quality is increased to video quality Q1 (an initial video quality), which is higher than the standard video quality Q0.

[0050] A reset condition is a condition for resetting the video quality from video quality Q1 (the initial video quality) to the default video quality Q0. For example, the reset condition might be that the active input from the remote control driver O is not detected. Another example is that a certain amount of time has elapsed since the active input was detected. At time t2 after time t1, the reset condition is met. When the reset condition is met, the video quality is reset from video quality Q1 to the default video quality Q0.

[0051] As in Fig. As shown in Figure 5, the video quality can gradually change from video quality Q1 to the standard video quality Q0. That is, the time it takes to revert the video quality from Q1 to standard video quality Q0 can be set to be longer than the time it takes to increase the video quality from standard video quality Q0 to Q1. In this case, the remote control operator O is less likely to notice a deterioration in video quality. Therefore, the remote control operator O is less likely to experience any unpleasantness.

[0052] In the section (A) in Fig. In the example shown, the video quality during the time interval from time t1 to time t3 is higher than the standard video quality Q0. The time interval during which the video quality is higher than the standard video quality Q0 is referred to below as the "first time interval." The first time interval is limited. The standard video quality Q0 is the video quality that is not present during the first time interval. The video quality is higher than the standard video quality Q0 during the first time interval after the active activation by the remote control driver O is detected.

[0053] Part (B) in Fig. Figure 5 shows a case where the active actuation by the remote control driver O is predicted. The active actuation is predicted at time tp before time t1, when the active actuation actually occurs. In connection with the predicted active actuation, the video quality is increased to video quality Q1 (the first video quality), which is higher than the standard video quality Q0. The reset condition is the same as in the case of part (A) in Figure 5. Fig. 5. In the section (B) of Fig. In example 5, the time interval between time tp and time t3 corresponds to the first time interval. During the first time interval, after the active activation by the remote control driver O has been predicted, the video quality is higher than the standard video quality Q0.

[0054] Fig. Figure 6 is a conceptual diagram illustrating an example of the detection and resetting of active actuation. The horizontal axis represents the actuation intensity by the remote control operator O. When the actuation intensity exceeds the first threshold TH1, it is determined that active actuation by the remote control operator O is performed. The reset threshold THd is a threshold used to determine that active actuation by the remote control operator O is no longer performed. The reset condition is that the actuation intensity decreases to less than or equal to the reset threshold THd. As shown in Fig. As shown in Figure 6, the reset threshold THd can be set lower than the first threshold TH1. This means that hysteresis characteristics can exist with regard to the detection and reset of the active actuation. Such hysteresis characteristics suppress any lag in video quality. 2-4. Video transmission system

[0055] Fig. Figure 7 is a block diagram illustrating an example of a functional configuration of a video transmission system 1X for transmitting the video VID from the vehicle 100 to the remote control driver terminal 200. The video transmission system 1X is part of the remote control system 1.

[0056] The video transmission system 1X comprises camera C and an encoder, both mounted in vehicle 100. Camera C receives the video VID. The encoder encodes the video VID. Vehicle 100 transmits the encoded video VID to the remote control driver terminal 200.

[0057] The video transmission system 1X comprises a decoder and the display device 220 on the remote control driver terminal 200. The remote control driver terminal 200 receives the video VID transmitted by 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 comprises an active actuation detection unit 10 and a video quality detection unit 20. The active actuation detection unit 10 detects or predicts active actuation by the remote control driver O. A specific example of the active actuation detection unit 10 is described in detail in Section 5 below.

[0059] Video quality determination unit 20 receives a result from determination unit 10 for an active actuation. Video quality determination unit 20 then determines video quality control information based on the result of determination unit 10 for an active actuation. For example, the video quality control information might be a setting value for the frame rate of video VID. Another example is a setting value for the keyframe rate of video VID. As yet another example, the video quality control information could be an instruction to insert a temporary keyframe into video VID.

[0060] As in Fig. As shown in Figure 7, the video quality determination unit 20 comprises a frame rate setting unit 21, a keyframe rate setting unit 22, and a keyframe insertion unit 23. The frame rate setting unit 21 sets the frame rate of the video VID based on the result of the determination by the determination unit 10 for an active actuation. The keyframe rate setting unit 22 sets the keyframe rate of the video VID based on the result of the determination by the determination unit 10 for an active actuation. The keyframe insertion unit 23 generates the instruction to insert the keyframe into the video VID based on the result of the determination by the determination unit 10 for an active actuation.

[0061] The video transmission system 1X controls the encoder mounted in vehicle 100 according to the video quality control information. Thus, video quality control is implemented according to the present embodiment.

[0062] As described above, the vehicle 100, the remote control driver terminal 200, and the management device 300 can communicate with each other via the communication network. Therefore, information necessary for video quality control can be exchanged or shared between the vehicle 100, the remote control driver terminal 200, and the management device 300. Since the information required for video quality control can be shared, the active actuation determination unit 10 and the video quality determination unit 20 can be included in any of the vehicles 100, the remote control driver terminal 200, and the management device 300. The active actuation determination unit 10 and the video quality determination unit 20 can be included in different devices.This means that the active actuation determination unit 10 and the video quality determination unit 20 can be distributed across the vehicle 100, the remote control driver terminal 200, and the management device 300. Generally, the active actuation determination unit 10 and the video quality determination unit 20 are implemented by one or more processors or processing circuits.

[0063] Fig. Figure 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 actuation determination process." Specifically, the video transmission system 1X detects or predicts active actuation by the remote control driver O. If active actuation is detected or predicted (step S10; Yes), the process continues to step S20. If, however, active actuation is not detected or predicted (step S10; No), the process continues to step S40.

[0065] In step S20, the video transmission system 1X performs a "video quality enhancement process." Specifically, the video transmission system 1X adjusts the video quality of the video VID so that it is higher than the standard video quality Q0. The process then continues with step S30.

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

[0067] In step S40, the video transmission system 1X sets the video quality of the video VID to the standard video quality Q0. 2-5. Effect

[0068] As described above, according to the present embodiment, the video quality of the video VID transmitted from the vehicle 100 to the remote control driver terminal 200 is not set uniformly, but rather dynamically changed. In particular, the video quality increases for the initial period after the active operation by the remote control driver O has been detected or predicted. During the execution of the active operation, the remote control driver O observes the surroundings of the vehicle 100 with particular care. At this time, the video quality increases, and thus the accuracy of the remote control driving by the remote control driver O improves.

[0069] The video quality of video VID during the time interval other than the first is set lower than during the first time interval. Since the remote control driver O does not actively operate the vehicle during the time interval other than the first, the accuracy of the remote control operation is ensured without increasing the video quality beyond what is necessary. Even if the video VID is provided at normal quality, the remote control driver O can continue the remote control operation of vehicle 100 with sufficient accuracy. Because the video quality is set relatively low, both the amount of data transmitted and the communication costs are reduced.

[0070] As described above, the present embodiment makes it possible to ensure the accuracy of remote control and to reduce communication costs. In other words, the present embodiment makes it possible to both ensure the accuracy of remote control and to reduce communication costs. 3. Example of a vehicle 3-1. Configuration example

[0071] Fig. Figure 9 is a block diagram showing a configuration example of vehicle 100. Vehicle 100 comprises a communication device 110, a sensor group 120, a driving device 130, and a control device 150.

[0072] The communication device 110 communicates with the exterior of the vehicle 100. For example, the communication device 110 communicates with the remote control driver terminal 200 and the management device 300. The communication device 110 can communicate with the encoder (see Fig. 7) include, which encodes the video VID.

[0073] Sensor group 120 includes a detection sensor, a vehicle condition sensor, a position sensor, etc. The detection sensor detects (captures) the vehicle's environment. Examples of detection sensors include camera C, laser imaging detection and ranging (LIDAR), and radar. The vehicle condition sensor detects the vehicle's condition. Vehicle condition sensors include a speed sensor, an accelerometer, a yaw rate sensor, a steering angle sensor, etc. The position sensor detects the vehicle's position and orientation. For example, a global navigation satellite system (GNSS) is included in the position sensor.

[0074] The driving device 130 comprises a steering device, a drive device, and a braking device. The steering device steers wheels. The steering device includes, for example, an electric power steering system (EPS). The drive device corresponds to a power source that generates a driving force. Examples of the drive device include a machine, an electric motor, and a wheel hub 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 comprises one or more processors 160 (hereinafter referred to simply as a processor 160) and one or more storage devices 170 (hereinafter referred to simply as a storage device 170). The processor 160 performs a variety of 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 processor 160 can be referred to as a "processing circuit." The storage device 170 stores a variety of information types. Examples of the storage device 170 include volatile memory, 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 processor 160. Functions of the control device 150 can be implemented through cooperation between processor 160, which executes the vehicle control program PROG1, and storage device 170. The vehicle control program PROG1 is stored in storage device 170. Alternatively, the vehicle control program PROG1 can be recorded on a non-transient, computer-readable recording medium. 3-2. Driving environment information

[0077] The control device 150 obtains driving environment information ENV, which displays 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) comprises a general navigation map. The map information (MAP) can display lane configurations and road layouts. The map information (MAP) can include position information for intersections, stop lines, traffic lights, signs, etc. The control device 150 obtains map information (MAP) for a required area or region from the map database. The map database can be stored in the storage device 170 or 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 and obtains the necessary map information (MAP).

[0079] The driving environment information (ENV) includes environmental situation information (SUR), which displays the result of a detection by the detection sensor. The environmental situation information (SUR) includes, for example, the video (VID) recorded by camera C. The environmental situation information (SUR) can include object information relating to an object around vehicle 100. Examples of objects around vehicle 100 include a pedestrian, another vehicle (a vehicle ahead, a parked vehicle, etc.), a white line, a stop line, a traffic light, a sign, a structure at the roadside, etc. The object information specifies the relative position and speed of the object with respect to vehicle 100. For example, by analyzing the video (VID) received from camera C, the object can be identified and its relative position calculated.Furthermore, it is possible to identify the object based on the point group information obtained by the LIDAR and to obtain the object's relative position and relative velocity.

[0080] Furthermore, the driving environment information (ENV) includes vehicle state information (STA), which displays a result of the vehicle state sensor's acquisition. The vehicle state information (STA) shows the vehicle speed, acceleration (longitudinal acceleration, lateral acceleration), yaw rate, steering angle, etc.

[0081] Furthermore, the driving environment information (ENV) includes vehicle position information (POS), which indicates the position and direction of movement (orientation) of the vehicle. The vehicle position information (POS) is obtained from the position sensor. Highly accurate vehicle position information (POS) can be obtained through a localization process using map information (MAP) and environmental situation information (SUR) (object information). 3-3. Vehicle driving control

[0082] The control device 150 performs the vehicle driving control for controlling the movement of the vehicle 100. The vehicle driving control comprises a steering control, a drive control, and a brake control. The control device 150 performs the vehicle driving control by controlling the driving device 130 (the steering device, the drive device, and the brake device).

[0083] The control device 150 can execute autonomous driving control based on the driving environment information (ENV). Autonomous driving means that at least part of the steering, acceleration, and deceleration of the vehicle 100 is performed automatically and independently of any driver input. 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 based on the driving environment information (ENV), which is necessary for the vehicle 100 to travel according to the driving plan. The target trajectory includes a target position and a target speed. The control device 150 then executes the vehicle driving control so that the vehicle 100 follows the target trajectory. 3-4. Related processes for remote control driving

[0084] The following describes a case in which the remote control operation of vehicle 100 is carried out. The control device 150 communicates with the remote control driver terminal 200 via the communication device 110.

[0085] The control device 150 transmits the vehicle information VCL to the remote control driver terminal 200. The vehicle information VCL is information necessary for remote driving by the remote control driver O and includes at least some of the driving environment information ENV described above. In particular, the vehicle information VCL includes the video VID recorded by camera C. The vehicle information VCL may include further environmental situation information SUR. The vehicle information VCL may include the vehicle status information STA. The vehicle information VCL may include the vehicle position information POS.

[0086] The control device 150 receives the remote control information OPE from the remote control driver terminal 200. The remote control information OPE is information relating to a remote control drive by the remote control driver O. The remote control information OPE includes, for example, a drive control amount entered by the remote control driver O. The control device 150 performs the vehicle drive control according to the received remote control information OPE.

[0087] The control device 150 can perform both functions of the in Fig. The device consists of the determination unit 10 shown in Figure 7 for active actuation and the video quality determination unit 20. The video quality determination unit 20 determines control information for the video quality based on the result of the determination by the determination unit 10 for active actuation. The control device 150 controls the encoder according to the video quality control information.

[0088] The control device 150 may not include the function of the determination unit 10 for active actuation and may include the function of the video quality determination unit 20. In this case, the control device 150 obtains information about the result of the determination by the external determination unit 10 for active actuation via the communication device 110.

[0089] The active actuation control unit 10 and the video quality control unit 20 can be installed outside the vehicle 100. In this case, the control device 150 determines the video quality control information, as determined by the video quality control unit 20, via the communication device 110. The control device 150 controls the encoder according to the video quality control information. 4. Configuration example of a remote control driver terminal

[0090] Fig. Figure 10 is a block diagram showing an example configuration of the remote control driver terminal 200. The remote control driver terminal 200 comprises 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 can control the decoder (see Fig. 7) include, which decodes the video VID.

[0092] The display device 220 shows the remote control driver O, who is performing the remote control drive, a variety of information. In other words, the display device 220 provides the remote control driver O with a variety of information by displaying it. The display device 220 can be a touch panel.

[0093] The input device 230 receives an input from the remote control driver O. For example, the input device 230 includes a remote control driving element, which is operated by the remote control driver O when the remote control driver O performs the remote control driving of the vehicle 100. The remote control driving element includes a steering wheel, an accelerator pedal, a brake pedal, a turn signal, etc.

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

[0095] The remote control program PROG2 is a computer program executed by processor 260. The function of the control device 250 can be realized through cooperation between processor 260, which executes the remote control program PROG2, and storage device 270. The remote control program PROG2 is stored in storage device 270. Alternatively, the remote control program PROG2 can be recorded on a non-transient, computer-readable recording medium. The remote control program PROG2 can be made available via a network.

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

[0097] The remote control driver O activates the remote control drive element of the input device 230. The degree of activation of the remote control drive element is detected by a sensor integrated into the remote control drive element. The control device 250 generates the remote control activation information OPE, which reflects the degree of activation of the remote control drive element input by the remote control driver O. The remote control activation information OPE can be described as information reflecting the intensity of the drive activation by the remote control driver O. The control device 250 then transmits the remote control activation information OPE to the vehicle 100 via the communication device 210.

[0098] The control device 250 can perform the function of the in Fig. The determination unit 10 shown in Figure 7 is capable of active actuation. In this case, the control device 250 transmits information about the result of the determination by the determination unit 10 for active actuation to the vehicle 100 via the communication device 210.

[0099] The control device 250 can perform both functions of the in Fig. The device consists of the determination unit 10 shown in Figure 7 for active actuation and the video quality determination unit 20. The video quality determination unit 20 determines the video quality control information based on the result of the determination by the determination unit 10 for active actuation. The control device 250 transmits the video quality control information to the vehicle 100 via the communication device 210. 5. Examples of the unit of determination for an active activity

[0100] The following are some examples for the determination unit 10 for an active actuation, which detects or predicts the active actuation by the remote control driver O. 5-1. First example

[0101] Fig. Figure 11 is a block diagram showing a first example of the determination unit 10 for an active actuation. The determination unit 10 for an active actuation comprises a detection unit 11 for an active actuation and a determination unit 15. The detection unit 11 for an active actuation detects the active actuation by the remote control driver O. In the diagram shown in Fig. In the example shown, the detection unit 11 for an active actuation comprises a first detection unit 11-1 and a second detection unit 11-2.

[0102] The first detection unit 11-1 detects the active operation by the remote control driver O based on the remote control information OPE. As described above, the remote control information OPE reflects the intensity of the driving operation (operation intensity) by the remote control driver O. For example, the operation intensity is proportional to the steering input by the remote control driver O. As another example, the operation intensity is proportional to the steering speed by the remote control driver O. As yet another example, the operation intensity is proportional to the acceleration requested by the remote control driver O. As yet another example, the operation intensity is proportional to the deceleration requested by the remote control driver O.The first detection unit 11-1 uses the remote control information OPE to determine whether the actuation intensity by the remote control operator O exceeds the first threshold TH1 and detects the active actuation. The first threshold TH1 is different for each type of actuation intensity. The first detection unit 11-1 can detect the active actuation based on a characteristic map that shows a correspondence between actuation intensity and active actuation.

[0103] The second sensing unit 11-2 detects the active input by the remote control driver O based on the vehicle state information STA. The remote control operation of vehicle 100 by the remote control driver O is reflected in the behavior of vehicle 100. Therefore, it is possible to detect the active input by the remote control driver O based on the vehicle state information STA. For example, if the longitudinal acceleration of vehicle 100 exceeds the first threshold TH1, the second sensing unit 11-2 detects the active input. As another example, the second sensing unit 11-2 detects the positive or active input if the yaw rate or the lateral acceleration exceeds the first threshold TH1. The first threshold TH1 is different for each vehicle state.The second detection unit 11-2 can detect the active actuation based on the characteristic map, which shows a correspondence between the vehicle status information STA and the active actuation.

[0104] The first threshold TH1 or the characteristic map can be individually set for each remote control driver O. The active activation can be divided into multiple stages (levels) (see Fig. 2).

[0105] The first acquisition unit 11-1 and the second acquisition unit 11-2 output the acquisition result to the determination unit 15. The acquisition result includes the presence or absence of the acquisition of the active activity, the content (type) of the acquired active activity, etc.

[0106] The determination unit 15 receives the result of the detection by the first detection unit 11-1 and the result of the detection by the second detection unit 11-2. If the active actuation 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 the active actuation is performed by the remote control driver O. The determination unit 15 communicates the result of the determination to the video quality determination unit 20. The determination unit 15 can communicate the content (type) of the detected active actuation to the video quality determination unit 20.

[0107] When the remote control driver O performs the remote control drive of vehicle 100, the remote control information OPE changes at an earlier time than the vehicle status information STA. Therefore, the first detection unit 11-1 generally detects the active actuation earlier than the second detection unit 11-2. 5-2. Second example

[0108] Fig. Figure 12 is a block diagram showing a second example of the determination unit 10 for an active actuation. In addition to the recording unit 11 for an active actuation described in the first example, the determination unit 10 for an active actuation includes a trend database and a forecasting unit 12 for an active actuation.

[0109] The history database displays a position where the active actuation was recorded in the past. When the active actuation is recorded by the detection unit 11, the determination unit 10 registers the position of vehicle 100 at the time the active actuation is recorded in the history database. The position of vehicle 100 is obtained from the vehicle position information (POS). The history database can link the position where the active actuation was recorded in the past with the direction of movement of vehicle 100 at that time. The direction of movement of vehicle 100 is obtained from the vehicle position information (POS). The history database can link the content of the active actuation with the position where the active actuation was recorded.

[0110] In a scene where a specific remote control driver O performs the active operation, it is likely that the same remote control driver O or a different remote control driver O will perform the active operation again. Therefore, by using the history database, it is possible to "predict" that the active operation will be performed in the near future.

[0111] In particular, the prediction unit 12 for an active actuation obtains the vehicle position information POS. The vehicle position information POS indicates the current position and direction of movement of vehicle 100. The prediction unit 12 for an active actuation predicts that the active actuation will be carried out on the road in front of vehicle 100, based on the history database and the current position and direction of movement of vehicle 100. In other words, the prediction unit 12 for an active actuation predicts the occurrence of the active actuation that the remote control driver O is likely to carry out in the near future, based on the history database and the current position and direction of movement of vehicle 100. The prediction unit 12 for an active actuation outputs the result of the prediction to the determination unit 15.The result of the forecast includes the presence or absence of the predicted active activity, the content (type) of the predicted active activity, etc.

[0112] The determination unit 15 receives the detection result from detection unit 11 for an active actuation and the result of the prediction from prediction unit 12 for an active actuation and integrates them. Determination unit 15 can weight the detection result from detection unit 11 for an active actuation and the result of the prediction from prediction unit 12 for an active actuation. When the active actuation is detected or predicted, determination unit 15 reports this to video quality determination unit 20. Determination unit 15 can report the content (type) of the detected or predicted active actuation to video quality determination unit 20. 5-3. Third example

[0113] Fig. Figure 13 is a block diagram showing a third example of the determination unit 10 for an active actuation. The determination unit 10 for an active actuation includes a prediction unit 13 for an active actuation. The prediction unit 13 for an active actuation detects the situation of the road in front of the vehicle 100 based on the driving environment information ENV and predicts that the active actuation will be carried out on the road in front of the vehicle.

[0114] For example, it is predicted that the remote control driver O will actively steer if the road ahead of vehicle 100 has a sharp curve. The shape of the road ahead of vehicle 100 is obtained from the map information MAP. As another example, it is predicted that the remote control driver O will actively decelerate if there is an intersection, stop line, stop sign, or traffic light ahead of vehicle 100. Position information for the intersection, stop line, traffic light, sign, etc., is recorded in the map information MAP. The current position and direction of travel of vehicle 100 are obtained from the vehicle position information POS. The prediction unit 13 for active steering captures the situation on the road ahead of vehicle 100 based on the vehicle position information POS and the map information MAP.Then, the forecasting unit 13 predicts the occurrence of active activation on the road in front of vehicle 100 based on the situation of the road in front of vehicle 100.

[0115] Instead of map information (MAP), the road situation in front of vehicle 100 can be determined based on the environmental situation information (SUR), which displays the result of the detection by the detection sensor. In this case, the prediction unit 13 for an active actuation determines the road situation in front of vehicle 100 based on the vehicle position information (POS) and the environmental situation information (SUR). Then, the prediction unit 13 for an active actuation predicts the occurrence of the active actuation on the road in front of vehicle 100 based on the road situation in front of vehicle 100.

[0116] In addition to the road conditions in front of vehicle 100, the prediction unit 13 for active braking can take the vehicle speed into account, since the remote control driver O is more likely to actively brake as the vehicle speed increases. In this case, the prediction unit 13 for active braking predicts the occurrence of active braking on the road in front of vehicle 100, taking into account the vehicle state information STA.

[0117] For the prediction process in prediction unit 13 for an active actuation, a prediction model can be used, which is generated in advance by machine learning, such as deep learning. The input to the prediction model corresponds to the driving environment information ENV, and the output of the prediction model corresponds to the presence or absence of the active actuation and the content of the active actuation.

[0118] The forecasting unit 13 for an active activity outputs the result of the forecast to the determination unit 15. The result of the forecast includes the presence or absence of the predicted active activity, the content (type) of the predicted active activity, etc.

[0119] The determination unit 15 receives the result of the prediction from the prediction unit 13 for an active activity. If the active activity is predicted, the determination unit 15 notifies the video quality determination unit 20 of this fact. The determination unit 15 can inform the video quality determination unit 20 about the predicted content (type) of the active activity. 5-4. Fourth example

[0120] Fig. Figure 14 is a block diagram showing a fourth example of the determination unit 10 for an active actuation. The determination unit 10 for an active actuation comprises a prediction unit 14 for an active actuation and a determination unit 15. The prediction unit 14 for an active actuation predicts the active actuation by the remote control driver O based on the vehicle state information STA.

[0121] If, for example, vehicle 100 begins to skid due to a strong crosswind, the remote control driver O will likely actively perform steering inputs to return vehicle 100 to its original lateral position and stabilize it. Therefore, if the lateral acceleration exceeds the first threshold TH1, the prediction unit 14 for active inputs predicts that the remote control driver O will actively input the steering inputs. The determination unit 15 is the same as in the third example. 5-5. Fifth example

[0122] Two or more of the examples described above for the unit of determination 10 can be combined for an active operation.

[0123] Fig. Figure 15 is a block diagram showing a fifth example of the unit of determination 10 for an active activity. In the Fig.In the example shown in Figure 15, the determination unit 10 for an active actuation comprises the detection unit 11 for an active actuation and the forecasting unit 12 to 14 for an active actuation. The determination unit 15 receives the result of the detection by the detection unit 11 for an active actuation and the result of the forecast by the forecasting unit 12 to 14 for an active actuation and integrates them. The determination unit 15 can weight the result of the detection by the detection unit 11 for an active actuation and the result of the forecast by the forecasting unit 12 to 14 for an active actuation. When the active actuation is detected or predicted, the determination unit 15 reports this to the video quality determination unit 20. The determination unit 15 can report the content (type) of the detected or predicted active actuation to the video quality determination unit 20. QUOTES INCLUDED IN THE DESCRIPTION

[0000] This list of documents cited by the applicant was automatically generated and is included solely for the reader's convenience. The list is not part of the German patent or utility model application. The DPMA accepts no liability for any errors or omissions. Cited patent literature

[0000] JP 2019 - 003 403 A

[0003] WO 2018 / 155159 A1

[0003]

Claims

[1] A video transmission system (1X) for transmitting a video (VID) from a moving body (100) which is a target of a remote control drive by a remote control driver (O) to a terminal (200) on a side of the remote control driver (O), the video transmission system (1X) comprising one or more processors (160) configured to execute: an active operation determination process for detecting or predicting an active operation in which an intensity level of a driving operation by the remote control driver (O) exceeds a first threshold value (TH1); and a video quality enhancement process to enhance the quality of the video (VID) transmitted to the terminal (200) during a first period of time after the active actuation is detected or predicted, compared to a period of time other than the first period of time. [2] The video transmission system (1X) of claim 1, wherein the video quality enhancement process comprises inserting a keyframe into the video (VID) in response to detecting or predicting the active actuation, regardless of a setting of a keyframe rate of the video (VID). [3] The video transmission system (1X) according to claim 1 or 2, wherein the video quality enhancing process comprises setting a keyframe rate of the video (VID) during the first time period to be higher than that in the time period different from the first time period. [4] Video transmission system (1X) according to claim 1, wherein a plurality of process candidate types comprises two or more of the following: a first process of setting a frame rate of the video (VID) in the first time period to be higher than that in the time period different from the first time period; a second process of setting a keyframe rate of the video (VID) in the first time period to be higher than that in the time period different from the first time period; and a third process for inserting a keyframe into the video (VID) in response to detecting or predicting the active actuation, regardless of a setting of the keyframe rate of the video (VID), and the video quality enhancement process comprises executing at least one of the plurality of types of process candidates. [5] The video transmission system (1X) according to claim 4, wherein the video quality enhancing process comprises determining one or more of the plurality of types of process candidates to be executed according to a type of active operation. [6] Video transmission system (1X) according to claim 5, wherein The video quality improvement process includes: Executing at least the first process if the active operation corresponds to an acceleration operation; and Executing at least the second process if the active operation corresponds to a steering operation. [7] Video transmission system (1X) according to claim 4, wherein The video quality improvement process includes: Increasing the frame rate of the video (VID) in the first time period with increasing speed of the moving body (100); and Increase the keyframe rate of the video (VID) in the first time period as the speed of the moving body decreases (100). [8] Video transmission system (1X) according to claim 1, wherein a standard video quality (Q0) corresponds to the quality of the video (VID) in the time period other than the first time period, and The video quality improvement process includes: Increasing the quality of the video (VID) to a first video quality (Q1) higher than the standard video quality (Q0) in connection with detecting or predicting the active actuation; and Reset the video quality (VID) from the first video quality (Q1) to the default video quality (Q0) when a reset condition is met after the video quality (VID) has been increased. [9] The video transmission system (1X) according to claim 8, wherein the video quality increasing process comprises setting a time for returning the quality of the video (VID) from the first video quality (Q1) to the standard video quality (Q0) to be longer than a time for increasing the quality of the video (VID) from the standard video quality (Q0) to the first video quality (Q1). [10] A video transmission method for transmitting a video (VID) from a moving body (100) which is a target of a remote control drive by a remote control driver (O) to a terminal (200) on a side of the remote control driver (O), wherein the video transmission method comprises: an active operation determination process for detecting or predicting an active operation in which an intensity level of the driving operation by the remote control driver (O) exceeds a first threshold value (TH1); and a video quality enhancement process for enhancing the quality of the video (VID) transmitted to the terminal during a first period of time after the active actuation is detected or predicted, compared to a period of time different from the first period of time.

Images