UAV-based Driving Ability Test System, Method, Device and Storage Medium

Abstract

An unmanned aerial vehicle-based driving ability test system, method, device and storage medium, wherein the unmanned aerial vehicle-based driving ability test system (100) includes: an unmanned aerial vehicle (10) on which an autonomous driving system (11) is carried, and the autonomous driving system (11) is used to control the movement of the unmanned aerial vehicle; a driving simulator (20) for taking over the driving task by a driver to be tested and taking over the control of the movement of the unmanned aerial vehicle (10) by operating the driving simulator (20); a data acquisition module (30) for acquiring the behavior data of the driver operating the driving simulator (20) to analyze the driving ability of the driver according to the behavior data.

Description

Technical Field

[0001] This application relates to the technical field of driving test, and particularly to a driving ability test system, method, device and storage medium based on an unmanned aerial vehicle (UAV). Background Art

[0002] Autopilot means that instead of the driver operating the vehicle, the vehicle automatically collects environmental information through sensors on the vehicle and automatically drives according to the environmental information. However, in some specific situations, such as software and hardware failures, external environmental interference, etc., the driver still needs to take over the driving task. Therefore, it is necessary to test the driving ability of the driver to take over the driving task.

[0003] Currently, driving ability tests are often carried out through virtual simulation tests to build simulation scenarios or closed - field tests. In virtual simulation tests, there is no authenticity that may cause actual collision risks, and the test results may deviate from the driver's true driving ability; while in closed - field tests, although the reliability can be guaranteed, the test cost is high. Summary of the Invention

[0004] Embodiments of this application provide a driving ability test system, method, device and storage medium based on an unmanned aerial vehicle to achieve a balance between the accuracy and reliability of driving ability tests and test costs.

[0005] In a first aspect, embodiments of this application provide a driving ability test system based on an unmanned aerial vehicle. The driving ability test system based on an unmanned aerial vehicle includes:

[0006] An unmanned aerial vehicle with an autopilot system mounted thereon, and the autopilot system is used to control the movement of the unmanned aerial vehicle;

[0007] A driving simulator, which is used to take over the control of the movement of the unmanned aerial vehicle by operating the driving simulator when a driver to be tested takes over the driving task;

[0008] A data acquisition module, which is used to collect the behavior data of the driver operating the driving simulator to analyze the driving ability of the driver based on the behavior data.

[0009] In a second aspect, embodiments of this application further provide a driving ability test method based on an unmanned aerial vehicle. The driving ability test method based on an unmanned aerial vehicle includes:

[0010] When receiving a takeover signal sent by an autonomous driving system carried on a drone, send the takeover signal to a driving simulator, so that a driver to be tested can take over the control of the movement of the drone by manipulating the driving simulator; wherein, when the autonomous driving system senses the boundary of the Operational Design Domain (ODD) where the vehicle can safely drive, the takeover signal is triggered.

[0011] Obtain the behavior data of the driver manipulating the driving simulator, so as to analyze the driving ability of the driver according to the behavior data.

[0012] In a third aspect, an embodiment of the present application further provides a driving ability test device based on a drone. The driving ability test device based on a drone includes a processor and a memory.

[0013] The memory is used to store a computer program.

[0014] The processor is configured to execute the computer program and, when executing the computer program, implement any one of the driving ability test methods based on a drone provided by the embodiments of the present application.

[0015] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor is caused to implement any one of the driving ability test methods based on a drone provided by the embodiments of the present application.

[0016] The driving ability test system, method, device and storage medium based on a drone disclosed in the embodiments of the present application can implement the driver ability test by combining a drone with a driving simulator. Compared with the virtual simulation test method, the accuracy and reliability of the driving ability test are improved. Moreover, compared with the closed-field test method, the test cost is reduced.

[0017] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0019] Figure 1 It is a schematic diagram of a driving ability test system based on a drone provided by an embodiment of the present application.

[0020] Figure 2It is a schematic block diagram of a drone provided by an embodiment of the present application;

[0021] Figure 3 It is a schematic block diagram of a data acquisition module provided by an embodiment of the present application;

[0022] Figure 4 It is a schematic diagram of another driving ability test system based on a drone provided by an embodiment of the present application;

[0023] Figure 5 It is a schematic block diagram of a driving simulator provided by an embodiment of the present application;

[0024] Figure 6 It is a schematic flow diagram of a driving ability test process for a driver provided by an embodiment of the present application;

[0025] Figure 7 It is a schematic flow diagram of another driving ability test process for a driver provided by an embodiment of the present application;

[0026] Figure 8 It is a schematic flow chart of a driving ability test method based on a drone provided by an embodiment of the present application;

[0027] Figure 9 It is a schematic diagram of a driving ability test system based on a drone provided by an embodiment of the present application;

[0028] Figure 10 It is a schematic block diagram of a driving ability test device based on a drone provided by an embodiment of the present application. Detailed implementation manners

[0029] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0030] It should also be understood that the terms used in the specification of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the specification of the present application and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include the plural forms.

[0031] It should be further understood that the term "and / or" used in the specification of the present application and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0032] The flowcharts shown in the accompanying drawings are only illustrative examples, and do not necessarily include all content and operations / steps, nor do they have to be executed in the order described. For example, some operations / steps can be decomposed, combined, or partially merged, so the actual execution order may change according to the actual situation.

[0033] With the development of science and technology and the application of artificial intelligence technology, autonomous driving technology has achieved rapid development and wide application. Based on the vehicle's driving automation level, the existing SAE J3016 standard divides driving automation into 6 levels, namely L0-L5 levels, which are No Automation (L0), Driver Assistance (L1), Partial Automation (L2), Conditional Automation (L3), High Automation (L4), and Full Automation (L5). As the driving automation level continues to increase, the degree of human participation in driving activities becomes lower and lower. It can be predicted that there will be more autonomous driving vehicles on the road in the future, resulting in a situation where autonomous driving vehicles and human-driven vehicles run parallel on the road.

[0034] Among them, when the autonomous driving systems of levels 0-3 are working, the driver still needs to take over the vehicle driving task under specific circumstances, such as when software and hardware fail, or there are external environmental interferences, etc. Therefore, it is necessary to test the driver's driving ability to take over the driving task.

[0035] Currently, driving ability tests are often carried out through virtual simulation tests to build simulation scenarios or closed-course tests. In virtual simulation tests, the authenticity of possible actual collision risks is not available, and the test results may deviate from the driver's true driving ability; while the closed-course test can ensure the authenticity and reliability, but the test cost is high.

[0036] To solve the above problems, the embodiments of the present application provide a driving ability test system, method, device, and storage medium based on an unmanned aerial vehicle (UAV), which can realize the driver ability test by combining the UAV with a driving simulator. Compared with the virtual simulation test method, the accuracy and reliability of the driving ability test are improved, and compared with the closed-course test method, the test cost is reduced.

[0037] Please refer to Figure 1 , Figure 1 which shows a schematic structural diagram of a driving ability test system based on an unmanned aerial vehicle provided by an embodiment of the present application. AsFigure 1 As shown in the figure, the drone-based driving ability test system 100 includes a drone 10, a driving simulator 20, a data acquisition module 30, etc.

[0038] In an embodiment of the present application, the drone 10 is a drone equipped with an autonomous driving system 11, and the movement of the drone 10 is controlled by the autonomous driving system 11. The drone 10 is used to replace a test vehicle for road testing, and the movement of the drone 10 fits that of a real vehicle.

[0039] Among them, the autonomous driving system 11 refers to a system composed of hardware and software that can continuously execute all dynamic driving tasks, regardless of whether there are restrictions on operating conditions. For example, the autonomous driving system refers to a system composed of hardware and software that can continuously execute some or all of the dynamic driving tasks (Dynamic Driving Task).

[0040] Among them, the dynamic driving task (Dynamic Driving Task) is: perception, decision-making, and execution required to complete vehicle driving. That is, it includes all real-time operation and tactical functions when driving a road vehicle, excluding planning functions such as trip planning, destination and route selection, etc.

[0041] Exemplarily, the dynamic driving tasks include but are not limited to the following tasks: controlling the lateral movement of the vehicle, controlling the longitudinal movement of the vehicle, monitoring the driving environment by detecting, identifying, and classifying targets and events and preparing for responses, controlling the vehicle lighting and signal devices.

[0042] Generally speaking, when exceeding the Operational Design Domain (ODD) or when the dynamic driving task-related system fails, it is necessary to switch from the autonomous driving state to the manual driving state, that is, for the driver to continue to take over the driving task. Among them, the Operational Design Domain ODD plays an important role in autonomous driving, generally including: geographical location, road type, speed range, lighting conditions, weather, time, and specific operation domains in other operation restrictions, etc.

[0043] Exemplarily, as Figure 2 shown, the drone 10 includes a flight control module 12, and the flight control module 12 realizes input control signals to control the flight of the drone 10.

[0044] In some embodiments, as Figure 2 shown, the drone 10 is also equipped with a camera device 13, and the camera device 13 includes but is not limited to a camera. The camera device 13 such as a camera simulates the perspective of the driver's naked eyes, collects road information, and transmits the road information back to the driver for viewing.

[0045] Exemplarily, the position of the camera device 13 matches the position of the driver's naked-eye observation. Among them, the position of the camera device 13 matching the position of the driver's naked-eye observation includes: the height of the camera device 13 from the ground is the same as the height of the driver's naked-eye observation position from the ground, so that the camera device 13 can better simulate the driver's naked-eye perspective.

[0046] In some embodiments, since the shooting angle of the camera device 13 may be larger than the driver's naked-eye observation angle, therefore, the shooting angle of the camera device 13 is controlled by the drone 10 so that the shooting angle of the camera device 13 is the same as the driver's naked-eye observation angle. For example, the shooting angle of the camera device 13 is cropped so that the shooting angle of the camera device 13 is the same as the driver's naked-eye observation angle, thereby enabling the camera device 13 to better simulate the driver's naked-eye perspective.

[0047] The driving simulator 20 is used for the driver to be tested to operate. When the driver takes over the driving task, by operating the driving simulator 20, the movement of the drone 10 can be taken over and controlled. The drone 10 replaces the test vehicle for the driver to operate the driving simulator 20 to simulate the test.

[0048] During the process of the driver operating the driving simulator 20, the data acquisition module 30 acquires the behavior data of the driver operating the driving simulator 20 to analyze the driver's driving ability based on the acquired behavior data. Among them, the behavior data includes but is not limited to natural takeover driving behavior data, extreme condition driving behavior data, etc. That is, the behavior data of the driver operating the driving simulator 20 in various different scenarios such as natural takeover and extreme conditions is acquired.

[0049] In some embodiments, as Figure 3 shown, the data acquisition module 30 includes at least one of a surface electromyogram signal acquisition unit 31, an electroencephalogram signal acquisition unit 32, and a camera unit 33.

[0050] Exemplarily, the surface electromyogram signal acquisition unit 31 is used to acquire the surface electromyogram signals of the driver's body. Among them, the surface electromyogram signals of the body include but are not limited to the surface electromyogram signals of the legs, etc. The electroencephalogram signal acquisition unit 32 is used to acquire the electroencephalogram signals of the driver. The camera unit 33 is used to acquire the human body images of the driver. Among them, the human body images include but are not limited to the front images, side images, etc. of the driver, and the body state information of the driver is obtained based on the front images, side images and other human body images. Among them, the body state information of the driver includes but is not limited to information such as the eye opening degree and the body forward inclination angle of the driver. For example, the eye opening degree of the driver is obtained through the front image of the driver, and the body forward inclination angle of the driver is obtained through the side image of the driver.

[0051] In some embodiments, such as Figure 3 shown, the data acquisition module 30 further includes a storage unit 34 for storing the acquired behavior data. That is, the storage unit 34 stores data such as the surface electromyogram signal, electroencephalogram signal, eye opening degree, and body forward tilt angle of the driver. Thereafter, the driving ability of the driver can be analyzed and known by querying the behavior data stored in the storage unit 34.

[0052] It should be noted that the storage unit 34 can be either a storage device provided in the data acquisition module 30 or an external storage device, and no specific limitation is made in this application.

[0053] In some embodiments, such as Figure 4 shown, the driving ability test system 100 based on the unmanned aerial vehicle further includes a control module 40. The control module 40 is connected to the driving simulator 20 and the unmanned aerial vehicle 10, and is used for transmitting information between the driving simulator 20 and the unmanned aerial vehicle 10.

[0054] Exemplarily, set the ODD corresponding to the test for the driver to take over driving. When the autonomous driving system 11 senses the ODD boundary, that is, when various factors such as geographical location, road type, speed range, lighting conditions, weather, and time exceed the set ODD, it is determined that the driver needs to take over the driving task currently, and a takeover signal is sent to the control module 40.

[0055] When the control module 40 receives the takeover signal sent by the autonomous driving system 11, it sends the takeover signal to the driving simulator 20. When the driving simulator 20 receives the takeover signal, it outputs a takeover reminder message to remind the driver to take over driving. Among them, the takeover reminder message includes at least one of a text reminder message and a voice reminder message.

[0056] In some embodiments, such as Figure 5 shown, the driving simulator 20 includes a display module 21 and / or a voice module 22. Among them, the display module 21 includes but is not limited to a touch screen, etc., and the voice module 22 includes but is not limited to a speaker, etc.

[0057] Exemplarily, when the driving simulator 20 receives the takeover signal, it displays a text reminder message through the display module 21 to remind the driver to take over driving.

[0058] Exemplarily, when the driving simulator 20 receives the takeover signal, it outputs a voice reminder message through the voice module 22 to remind the driver to take over driving.

[0059] Exemplarily, when the driving simulator 20 receives the takeover signal, it displays a text reminder message through the display module 21 and outputs a voice reminder message through the voice module 22 to remind the driver to take over driving.

[0060] In some embodiments, the camera device 13 simulates the perspective of the driver's naked eye to collect road information and transmits the road information back to the display module 21 in the driving simulator 20. The display module 21 displays the road information collected by the camera device 13 for the driver to view.

[0061] In some embodiments, the driving simulator 20 includes VR (Virtual Reality) / AR (Augmented Reality) devices for the driver to wear. Among them, the VR / AR devices include but are not limited to VR / AR glasses, VR / AR helmets, etc. The camera device 13 collects road information and transmits the road information back to the VR / AR device in the driving simulator 20. The driver views it by wearing the VR / AR device, thus generating an immersive driving experience.

[0062] In some embodiments, after the driver takes over driving and starts to control the driving simulator 20, relevant control instructions will be triggered. The driving simulator 20 sends the control instructions to the control module 40. The control module 40 receives the control instructions triggered by the driver's operation of the driving simulator 20 and sends the control instructions to the drone 10 to control the movement of the drone 10.

[0063] In some embodiments, as Figure 5 shown, the driving simulator 20 includes at least one of a brake pedal 23, a steering wheel 24, and an accelerator 25.

[0064] Exemplarily, after the driver takes over driving and starts to control the brake pedal 23, a deceleration instruction is triggered and sent to the control module 40. The control module 40 receives the deceleration instruction triggered by the driver's operation of the brake pedal 23 and sends the deceleration instruction to the drone 10 to control the drone 10 to decelerate.

[0065] Exemplarily, if the driver controls the steering wheel 24, a steering instruction is triggered and sent to the control module 40. The control module 40 receives the steering instruction triggered by the driver's operation of the steering wheel 24 and sends the steering instruction to the drone 10 to control the drone 10 to steer.

[0066] Exemplarily, if the driver controls the accelerator 25, an acceleration instruction is triggered and sent to the control module 40. The control module 40 receives the acceleration instruction triggered by the driver's operation of the accelerator 25 and sends the acceleration instruction to the drone 10 to control the drone 10 to accelerate.

[0067] In some embodiments, such as Figure 5 shown, the driving simulator 20 further includes a seat 26 for the driver to sit on.

[0068] Compared with using a test vehicle for closed-course testing, the test cost is low. At the same time, real-world testing is carried out using a drone, which can better collect the behavior data of the driver in extreme driving conditions and during natural takeover driving, including but not limited to the driver's surface electromyogram signals of the legs, electroencephalogram signals, eye opening, body forward tilt angle, etc. The data is more in line with real driving conditions, thus improving the accuracy and reliability of the driving ability test; and the safety of the driver during the test is also ensured.

[0069] Taking the natural takeover driving situation as an example, as Figure 6 shown, the driving ability test process of the driver is as follows:

[0070] Step 1: Arrange to collect the ODD corresponding to the driver's natural takeover driving test;

[0071] Step 2: The drone is equipped with an autonomous driving system and an on-board camera, where the position of the on-board camera is at the position observable by the driver's naked eyes;

[0072] Step 3: The driver operates the driving simulator and sends a "start moving" signal to the drone through the control module; the autonomous driving system carried by the drone executes the autonomous driving function, and the data acquisition module starts to collect autonomous driving data;

[0073] Step 4: When the autonomous driving system senses the ODD boundary, that is, the scenario where the driver needs to take over the driving task, it sends a takeover signal to the control module;

[0074] Step 5: The control module sends the takeover signal to the display module and / or the voice module in the driving simulator to remind the driver to take over;

[0075] Step 6: The driver receives the takeover signal and operates the driving simulator to take over the movement of the drone;

[0076] Step 7: The data acquisition module collects and stores the behavior data of the driver during the takeover driving process.

[0077] Taking the extreme driving conditions as an example, as Figure 7 shown, the driving ability test process of the driver is as follows:

[0078] Step 1: Arrange to collect the ODD corresponding to the driver's natural takeover driving test;

[0079] Step 2: The drone is equipped with an autonomous driving system and an on-board camera, where the position of the on-board camera is at the position observable by the driver's naked eyes;

[0080] Step 3: The driver operates the driving simulator to control the movement of the UAV to handle the extreme working conditions that occur.

[0081] Step 4: The data acquisition module collects and stores the driver's behavior data during the extreme working conditions.

[0082] The UAV-based driving ability test system provided by the above embodiment includes a UAV, on which an autonomous driving system is carried. The autonomous driving system is used to control the movement of the UAV; a driving simulator, which is used to take over the control of the movement of the UAV by operating the driving simulator when a driver to be tested takes over the driving task; and a data acquisition module, which is used to collect the behavior data of the driver operating the driving simulator to analyze the driving ability of the driver based on the behavior data. It can realize the driver ability test by combining the UAV with the driving simulator. Compared with the virtual simulation test method, the accuracy and reliability of the driving ability test are improved. And compared with the closed-site test method, the test cost is reduced.

[0083] Please refer to Figure 8 , Figure 8 which shows the schematic diagram of the step flow of a UAV-based driving ability test method provided by an embodiment of the present application. This UAV-based driving ability test method can be applied to the UAV-based driving ability test system of the above embodiment to test the driving ability of a driver.

[0084] It should be noted that, in this embodiment, as Figure 8 shown, this UAV-based driving ability test method includes step S101 and step S102.

[0085] S101: When receiving a takeover signal sent by the autonomous driving system carried on the UAV, send the takeover signal to the driving simulator for the driver to be tested to take over the control of the movement of the UAV by operating the driving simulator; wherein, the autonomous driving system triggers the takeover signal when perceiving the boundary of the operational design domain (ODD).

[0086] S102: Obtain the behavior data of the driver operating the driving simulator to analyze the driving ability of the driver based on the behavior data.

[0087] As Figure 9 shown in the UAV-based driving ability test system, the UAV 10 is a UAV carrying an autonomous driving system 11, and the movement of the UAV 10 is controlled by the autonomous driving system 11. The UAV 10 is used to replace the test vehicle for road testing, and the movement of the UAV 10 fits that of a real vehicle.

[0088] Among them, the autonomous driving system 11 refers to a system composed of hardware and software that can continuously perform all dynamic driving tasks, regardless of whether there are operating condition restrictions. For example, the autonomous driving system refers to a system composed of hardware and software that can continuously perform some or all of the dynamic driving tasks (Dynamic Driving Task).

[0089] Among them, the dynamic driving task (Dynamic Driving Task) is: the perception, decision-making, and execution required to complete vehicle driving. That is, it includes all real-time operational and tactical functions when driving a road vehicle, excluding planning functions such as trip planning, destination, and route selection, etc.

[0090] Exemplarily, the dynamic driving tasks include but are not limited to the following tasks: controlling the lateral movement of the vehicle, controlling the longitudinal movement of the vehicle, monitoring the driving environment and preparing for response by detecting, identifying, and classifying targets and events, and controlling the vehicle lighting and signal devices.

[0091] Generally speaking, when exceeding the operational design domain (ODD) or when the dynamic driving task-related system fails, it is necessary to switch from the autonomous driving state to the manual driving state, that is, for the driver to take over the driving task again. Among them, the operational design domain (ODD) plays an important role in autonomous driving and generally includes: geographical location, road type, speed range, lighting conditions, weather, time, and other specific operation domains in terms of operation restrictions, etc.

[0092] Exemplarily, the unmanned aerial vehicle 10 includes a flight control module 12, and the flight control module 12 realizes inputting control signals to control the flight of the unmanned aerial vehicle 10.

[0093] Exemplarily, the unmanned aerial vehicle 10 is also equipped with a camera device 13, and the camera device 13 includes but is not limited to a camera. Camera devices such as cameras simulate the perspective of the driver's naked eyes, collect road information, and transmit the road information back to the driver for viewing.

[0094] Exemplarily, the position of the camera device 13 is kept matching the position of the driver's naked-eye observation. Among them, the position of the camera device 13 being kept matching the position of the driver's naked-eye observation includes: the height of the camera device 13 from the ground being the same as the height of the driver's naked-eye observation position from the ground, so that the camera device 13 can better simulate the perspective of the driver's naked eyes.

[0095] In some embodiments, since the shooting angle of the imaging device 13 may be larger than the visual observation angle of the driver, the shooting angle of the imaging device 13 is controlled by the drone 10 so that the shooting angle of the imaging device 13 is consistent with the visual observation angle of the driver. For example, the shooting angle of the imaging device 13 is cropped so that the shooting angle of the imaging device 13 is consistent with the visual observation angle of the driver, thereby enabling the imaging device 13 to better simulate the visual angle of the driver.

[0096] The driving simulator 20 is used for the driver to be tested to operate. When the driver takes over the driving task, the movement of the drone 10 is taken over and controlled by operating the driving simulator 20. The drone 10 replaces the test vehicle for the driver to operate the driving simulator 20 to simulate the test.

[0097] During the process of the driver operating the driving simulator 20, the data acquisition module 30 acquires the behavior data of the driver operating the driving simulator 20 to analyze the driving ability of the driver based on the acquired behavior data. Among them, the behavior data includes but is not limited to natural takeover driving behavior data, extreme condition driving behavior data, etc. That is, the behavior data of the driver operating the driving simulator 20 in various different scenarios such as natural takeover and extreme conditions is acquired.

[0098] Exemplarily, the data acquisition module 30 includes at least one of a surface electromyogram signal acquisition unit 31, an electroencephalogram signal acquisition unit 32, and a camera unit 33.

[0099] Obtaining the behavior data of the driver operating the driving simulator includes at least one of the following:

[0100] Collecting the surface electromyogram signal of the driver's body surface through the surface electromyogram signal acquisition unit;

[0101] Collecting the electroencephalogram signal of the driver through the electroencephalogram signal acquisition unit;

[0102] Collecting the human body image of the driver through the camera unit to obtain the body state information of the driver according to the human body image, where the body state information includes at least one of the eye opening degree and the body forward inclination angle.

[0103] The surface electromyogram signal acquisition unit 31 is used to acquire the surface electromyogram signals of the driver. Among them, the surface electromyogram signals include but are not limited to the surface electromyogram signals of the legs, etc. The electroencephalogram signal acquisition unit 32 is used to acquire the electroencephalogram signals of the driver. The camera unit 33 is used to acquire the human body image of the driver. Among them, the human body image includes but is not limited to the front image, side image, etc. of the driver. The body state information of the driver is obtained according to the human body images such as the front image and the side image. Among them, the body state information of the driver includes but is not limited to information such as the eye opening degree and the body forward tilt angle of the driver. For example, the eye opening degree of the driver is obtained through the front image of the driver, and the body forward tilt angle of the driver is obtained through the side image of the driver.

[0104] Exemplarily, the data acquisition module 30 further includes a storage unit 34. The storage unit 34 is used to store the acquired behavior data. That is, the surface electromyogram signals, electroencephalogram signals, eye opening degree, body forward tilt angle, etc. of the driver are stored through the storage unit 34. After that, the driving ability of the driver can be analyzed and known by querying the behavior data stored in the storage unit 34.

[0105] It should be noted that the storage unit 34 can be not only a storage device provided in the data acquisition module 30, but also an external storage device, which is not specifically limited in this application.

[0106] Exemplarily, the control module 40 is connected to the driving simulator 20 and the drone 10. The control module 40 is used to transmit information between the driving simulator 20 and the drone 10.

[0107] Exemplarily, the ODD corresponding to the test of the driver taking over the driving is set. When the autonomous driving system 11 senses the ODD boundary, that is, when various factors such as geographical location, road type, speed range, lighting conditions, weather, time, etc. exceed the set ODD, it is determined that the driver needs to take over the driving task currently, and a takeover signal is sent to the control module 40.

[0108] When the control module 40 receives the takeover signal sent by the autonomous driving system 11, it sends the takeover signal to the driving simulator 20. When the driving simulator 20 receives the takeover signal, it outputs a takeover reminder message to remind the driver to take over the driving. Among them, the takeover reminder message includes at least one of a text reminder message and a voice reminder message.

[0109] Exemplarily, the driving simulator 20 includes a display module 21 and / or a voice module 22. Among them, the display module 21 includes but is not limited to a touch screen, etc., and the voice module 22 includes but is not limited to a speaker, etc.

[0110] Exemplarily, when the driving simulator 20 receives the takeover signal, it displays a text reminder message through the display module 21 to remind the driver to take over the driving.

[0111] Exemplarily, when the driving simulator 20 receives the takeover signal, it outputs a voice reminder message through the voice module 22 to remind the driver to take over the driving.

[0112] Exemplarily, when the driving simulator 20 receives the takeover signal, it displays a text reminder message through the display module 21 and outputs a voice reminder message through the voice module 22 to remind the driver to take over the driving.

[0113] Exemplarily, the camera device 13 simulates the driver's naked-eye perspective to collect road information and transmits the road information back to the display module 21 in the driving simulator 20. The display module 21 displays the road information collected by the camera device 13 for the driver to view.

[0114] In some embodiments, the driving simulator 20 includes VR (Virtual Reality) / AR (Augmented Reality) devices for the driver to wear. Among them, the VR / AR devices include but are not limited to VR / AR glasses, VR / AR helmets, etc. The camera device 13 collects road information and transmits the road information back to the VR / AR device in the driving simulator 20. The driver views it by wearing the VR / AR device, thus generating an immersive driving experience.

[0115] After the driver starts to take over the driving, the driver operates the driving simulator 20 to take over the control of the movement of the drone 10.

[0116] In some embodiments, after sending the takeover signal to the driving simulator, it includes:

[0117] Receiving a control instruction triggered by the driver operating the driving simulator and sending the control instruction to the drone to control the movement of the drone.

[0118] When the driver operates the driving simulator 20, relevant control instructions will be triggered. The driving simulator 20 sends the control instructions to the control module 40. The control module 40 receives the control instructions triggered by the driver operating the driving simulator 20 and sends the control instructions to the drone 10 to control the movement of the drone 10.

[0119] Exemplarily, the driving simulator 20 includes at least one of a brake pedal 23, a steering wheel 24, and an accelerator 25. The receiving a control instruction triggered by the driver operating the driving simulator and sending the control instruction to the drone to control the movement of the drone includes at least one of the following:

[0120] Receive the deceleration command triggered by the driver's operation of the brake pedal and send the deceleration command to the drone to control the deceleration of the drone;

[0121] The control module is configured to receive the steering command triggered by the driver's operation of the steering wheel and send the steering command to the drone to control the steering of the drone;

[0122] The control module is configured to receive the acceleration command triggered by the driver's operation of the throttle and send the acceleration command to the drone to control the acceleration of the drone.

[0123] For example, after the driver takes over the driving, if the driver operates the brake pedal 23 to trigger a deceleration command, the deceleration command is sent to the control module 40. The control module 40 receives the deceleration command triggered by the driver's operation of the brake pedal 23 and sends the deceleration command to the drone 10 to control the deceleration of the drone 10.

[0124] Another example, if the driver operates the steering wheel 24 to trigger a steering command, the steering command is sent to the control module 40. The control module 40 receives the steering command triggered by the driver's operation of the steering wheel 24 and sends the steering command to the drone 10 to control the steering of the drone 10.

[0125] Still another example, if the driver operates the throttle 25 to trigger an acceleration command, the acceleration command is sent to the control module 40. The control module 40 receives the acceleration command triggered by the driver's operation of the throttle 25 and sends the acceleration command to the drone 10 to control the acceleration of the drone 10.

[0126] Exemplarily, the driving simulator 20 further includes a seat 26 for the driver to sit on.

[0127] Compared with using a test vehicle for closed - field testing, the test cost is low. At the same time, real - field testing is carried out using a drone, and it is better to collect the behavior data of the driver in extreme working conditions and natural takeover driving situations, including but not limited to the driver's leg surface electromyogram signal, electroencephalogram signal, eye opening degree, body forward - leaning angle, etc. The data is more in line with the real driving situation, thereby improving the accuracy and reliability of the driving ability test; and the safety of the driver during the test is also ensured.

[0128] Taking the natural takeover driving situation as an example below, as Figure 6 shown, the driving ability test process of the driver is as follows:

[0129] Step 1: Arrange the ODD corresponding to the driver's natural takeover driving test;

[0130] Step 2: The drone is equipped with an autonomous driving system and an on-board camera, and the position of the on-board camera is at the position where the driver can observe with the naked eye;

[0131] Step 3: The driver operates the driving simulator and sends a "start moving" signal to the drone through the control module; the autonomous driving system carried by the drone executes the autonomous driving function, and the data acquisition module starts to collect autonomous driving data;

[0132] Step 4: When the autonomous driving system senses the ODD boundary, that is, the scenario where the driver needs to take over the driving task, it sends a takeover signal to the control module;

[0133] Step 5: The control module sends the takeover signal to the display module and / or the voice module in the driving simulator to remind the driver to take over;

[0134] Step 6: The driver receives the takeover signal and operates the driving simulator to take over the movement of the drone;

[0135] Step 7: The data acquisition module collects and stores the driver's behavior data during the takeover driving process.

[0136] The following takes the extreme working condition as an example. As Figure 7 shown, the driving ability test process of the driver is as follows:

[0137] Step 1: Arrange the ODD corresponding to the driver's natural takeover driving test;

[0138] Step 2: The drone is equipped with an autonomous driving system and an on-board camera, and the position of the on-board camera is at the position where the driver can observe with the naked eye;

[0139] Step 3: The driver operates the driving simulator to control the movement of the drone to cope with the extreme working conditions that occur;

[0140] Step 4: The data acquisition module collects and stores the driver's behavior data during the extreme working condition process.

[0141] In the driving ability test method based on the drone provided in the above embodiments, when the autonomous driving system carried by the drone senses the ODD boundary, it triggers a takeover signal. When receiving the takeover signal sent by the autonomous driving system, the takeover signal is sent to the driving simulator, so that the driver to be tested can take over the control of the movement of the drone by operating the driving simulator, and obtain the driver's behavior data of operating the driving simulator, so as to analyze the driver's driving ability based on this behavior data. It can realize the driver ability test by combining the drone with the driving simulator. Compared with the virtual simulation test method, the accuracy and reliability of the driving ability test are improved, and compared with the closed-site test method, the test cost is reduced.

[0142] In addition, an embodiment of the present application also provides a driving ability test device based on a drone. Please refer to Figure 10 , Figure 10 which is a schematic block diagram of a driving ability test device based on a drone provided by an embodiment of the present application.

[0143] As Figure 10 shown, the driving ability test device 200 based on a drone may include a processor 211 and a memory 212. The processor 211 and the memory 212 are connected through a bus, and the bus is, for example, an I2C (Inter-integrated Circuit) bus.

[0144] Specifically, the processor 211 may be a microcontroller unit (MCU), a central processing unit (CPU), a digital signal processor (DSP), or the like.

[0145] Specifically, the memory 212 may be a Flash chip, a read-only memory (ROM), a magnetic disk, an optical disc, a USB flash drive, or a mobile hard disk, etc. Various computer programs for the processor 211 to execute are stored in the memory 212.

[0146] Among them, the processor 211 is used to run the computer program stored in the memory processor 211, and when executing the computer program, the following steps are implemented:

[0147] When receiving a takeover signal sent by an autonomous driving system carried on the drone, send the takeover signal to a driving simulator for a driver to be tested to take over and control the movement of the drone by manipulating the driving simulator; wherein, when the autonomous driving system senses the boundary of the operating design domain (ODD), the takeover signal is triggered;

[0148] Obtain the behavior data of the driver manipulating the driving simulator to analyze the driving ability of the driver according to the behavior data.

[0149] In some embodiments, after the processor 211 implements sending the takeover signal to the driving simulator, it is used to implement:

[0150] Receive a control instruction triggered by the driver manipulating the driving simulator and send the control instruction to the drone to control the movement of the drone.

[0151] In some embodiments, the driving simulator includes at least one of a brake pedal, a steering wheel, and an accelerator pedal; the processor 211, when implementing receiving a control instruction triggered by the driver manipulating the driving simulator and sending the control instruction to the drone to control the movement of the drone, includes at least one of the following:

[0152] Receiving a deceleration instruction triggered by the driver manipulating the brake pedal and sending the deceleration instruction to the drone to control the drone to decelerate;

[0153] The control module is configured to receive a steering instruction triggered by the driver manipulating the steering wheel and send the steering instruction to the drone to control the drone to steer;

[0154] The control module is configured to receive an acceleration instruction triggered by the driver manipulating the accelerator pedal and send the acceleration instruction to the drone to control the drone to accelerate.

[0155] In some embodiments, the processor 211, when implementing obtaining the behavior data of the driver manipulating the driving simulator, includes at least one of the following:

[0156] Collecting the surface electromyogram signals of the driver's body through a surface electromyogram signal acquisition unit;

[0157] Collecting the electroencephalogram signals of the driver through an electroencephalogram signal acquisition unit;

[0158] Collecting the human body image of the driver through a camera unit to obtain the body state information of the driver according to the human body image, where the body state information includes at least one of the eye opening degree and the body forward inclination angle.

[0159] In some embodiments, the behavior data includes at least one of natural takeover driving behavior data and extreme condition driving behavior data.

[0160] The driving ability test device based on the drone can execute any one of the driving ability test methods provided by the embodiments of the present application. Therefore, the beneficial effects achievable by any one of the driving ability test methods provided by the embodiments of the present application can be realized. For details, see the previous embodiments and will not be elaborated here.

[0161] In addition, an embodiment of the present application further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and the computer program includes program instructions. The processor executes the program instructions to implement the steps of any one of the driving ability test methods based on the drone provided by the above embodiments.

[0162] Among them, the computer-readable storage medium may be an internal storage unit of the drone-based driving ability test system described in any of the foregoing embodiments, such as the memory or internal memory of the drone-based driving ability test system. The computer-readable storage medium may also be an external storage device of the drone-based driving ability test system, such as a plug-in hard disk, a SmartMedia Card (SMC), a Secure Digital (SD) card, a Flash Card, etc. equipped on the drone-based driving ability test system.

[0163] The above is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of various equivalent modifications or substitutions, and these modifications or substitutions should all be covered within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. An unmanned aerial vehicle-based driving ability test system, characterized in that, The drone-based driving ability test system includes: A drone, on which a vehicle autonomous driving system is carried, and the vehicle autonomous driving system is used to control the movement of the drone; A driving simulator, which is used to take over the control of the movement of the drone by manipulating the driving simulator when a vehicle driver to be tested takes over the driving task; A data acquisition module, which is used to acquire the behavior data of the vehicle driver manipulating the driving simulator, so as to analyze the driving ability of the vehicle driver according to the behavior data.

2. The drone-based driving ability test system according to claim 1, wherein The drone-based driving ability test system further includes: A control module, which is connected to the driving simulator and the drone, and is used to transmit information between the driving simulator and the drone.

3. The drone-based driving ability test system according to claim 2, wherein The autonomous driving system is used to determine that the driver needs to take over the driving task currently when perceiving the boundary of the Operational Design Domain (ODD), and send a takeover signal to the control module; The control module is used to send the takeover signal to the driving simulator when receiving the takeover signal; The driving simulator is used to output a takeover reminder message when receiving the takeover signal, so as to remind the driver to take over the driving.

4. The drone-based driving ability test system according to claim 3, wherein The driving simulator includes a display module and / or a voice module, and the takeover reminder message includes at least one of a text reminder message and a voice reminder message; the display module is used to display the text reminder message when the driving simulator receives the takeover signal; The voice module is used to output the voice reminder message when the driving simulator receives the takeover signal.

5. The drone-based driving ability test system according to claim 2, wherein The control module is used to receive the control instruction triggered by the driver manipulating the driving simulator, and send the control instruction to the drone to control the movement of the drone.

6. The drone-based driving ability test system according to claim 5, wherein The driving simulator includes at least one of a brake pedal, a steering wheel, and an accelerator; The control module is used to receive the deceleration instruction triggered by the driver manipulating the brake pedal, and send the deceleration instruction to the drone to control the drone to decelerate; The control module is used to receive the steering instruction triggered by the driver manipulating the steering wheel, and send the steering instruction to the drone to control the drone to steer; The control module is used to receive the acceleration instruction triggered by the driver manipulating the accelerator, and send the acceleration instruction to the drone to control the drone to accelerate.

7. The drone-based driving ability test system according to claim 1, characterized in that, A camera device is also carried on the drone, and the driving simulator includes a display module. The camera device is used to collect road information from the perspective of the driver's naked eyes and transmit the road information back to the display module; the display module is used to display the road information for the driver to view.

8. The drone-based driving ability test system according to claim 7, wherein The position of the camera device is kept matching with the position of the driver's naked-eye observation. Among them, the position of the camera device being kept matching with the position of the driver's naked-eye observation includes: the height of the camera device from the ground is the same as the height of the driver's naked-eye observation position from the ground.

9. The drone-based driving ability test system according to claim 7, wherein The drone is also used to control the shooting angle of the camera device so that the shooting angle of the camera device is consistent with the visual observation angle of the driver's naked eyes.

10. The drone-based driving ability test system according to claim 1, wherein The data acquisition module includes at least one of a surface electromyogram signal acquisition unit, an electroencephalogram signal acquisition unit, and a camera unit; The surface electromyogram signal acquisition unit is used to acquire the surface electromyogram signals of the driver's body; The electroencephalogram signal acquisition unit is used to acquire the electroencephalogram signals of the driver; The camera unit is used to acquire the human body image of the driver to obtain the body state information of the driver based on the human body image.

11. The drone-based driving ability test system according to claim 10, characterized in that, The body state information includes at least one of the following information: eye opening degree, body forward inclination angle.

12. The drone-based driving ability test system according to claim 1, characterized in that, The data acquisition module includes a storage unit, and the storage unit is used to store the acquired behavior data.

13. The drone-based driving ability test system according to claim 1, characterized in that, The behavior data includes at least one of natural takeover driving behavior data and extreme working condition driving behavior data.

14. A method for testing driving ability based on an unmanned aerial vehicle, characterized in that, The method for testing driving ability based on a drone includes: When receiving a takeover signal sent by a vehicle automatic driving system carried on the drone, sending the takeover signal to a driving simulator for a vehicle driver to be tested to take over and control the movement of the drone by manipulating the driving simulator; wherein, when the vehicle automatic driving system senses the boundary of the operating design domain (ODD), it triggers the takeover signal; Obtaining the behavior data of the vehicle driver manipulating the driving simulator to analyze the driving ability of the vehicle driver based on the behavior data.

15. The method for testing driving ability based on an unmanned aerial vehicle according to claim 14, wherein After sending the takeover signal to the driving simulator, it includes: Receiving a control instruction triggered by the driver manipulating the driving simulator and sending the control instruction to the drone to control the movement of the drone.

16. The method for testing driving ability based on an unmanned aerial vehicle according to claim 15, wherein The driving simulator includes at least one of a brake pedal, a steering wheel, and an accelerator; Receiving the control instruction triggered by the driver manipulating the driving simulator and sending the control instruction to the drone to control the movement of the drone includes at least one of the following: Receiving a deceleration instruction triggered by the driver manipulating the brake pedal and sending the deceleration instruction to the drone to control the drone to decelerate; The control module is used to receive a steering instruction triggered by the driver manipulating the steering wheel and send the steering instruction to the drone to control the drone to steer; The control module is used to receive an acceleration instruction triggered by the driver manipulating the accelerator and send the acceleration instruction to the drone to control the drone to accelerate.

17. The method for testing driving ability based on an unmanned aerial vehicle according to claim 14, wherein Obtaining the behavior data of the driver manipulating the driving simulator includes at least one of the following: Acquiring the surface electromyogram signals of the driver's body through the surface electromyogram signal acquisition unit; Acquiring the electroencephalogram signals of the driver through the electroencephalogram signal acquisition unit; Acquiring the human body image of the driver through the camera unit to obtain the body state information of the driver, wherein the body state information includes at least one of the eye opening degree and the body forward inclination angle.

18. The method for testing driving ability based on an unmanned aerial vehicle according to any one of claims 14 to 17, characterized in that The behavior data includes at least one of natural takeover driving behavior data and extreme condition driving behavior data.

19. An unmanned aerial vehicle-based driving ability test device, characterized in that, The drone-based driving ability test device includes a processor and a memory; The memory is used to store a computer program; The processor is configured to execute the computer program and, when executing the computer program, implement the drone-based driving ability test method according to any one of claims 14 to 18.

20. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor is caused to implement the drone-based driving ability test method according to any one of claims 14 to 18.

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