Active safety control method for a spin test bench, computer program product and autonomous driving test system for a spin test bench

Abstract

The application provides an active safety control method for a test bench of a steering hub, which comprises the following steps: acquiring a current vehicle speed v and a current decision steering angle θ of a test vehicle; calculating a safe steering angle threshold θ max_v of the current vehicle speed v according to a preset vehicle speed-safe steering angle model; dividing a current side-slip risk into multiple risk levels based on a comparison relationship between the current decision steering angle θ and the safe steering angle threshold θ max_v ; and performing corresponding safety measures according to a risk level to which the current decision steering angle θ belongs. According to the embodiment of the application, dynamic joint judgment can be performed based on real-time vehicle speed and steering angle, and differentiated active intervention actions are performed according to risk levels before risks occur, so that the test continuity and safety are considered, the existing test bench of the steering hub can be applied, and the automatic driving system can be deeply cooperated to improve the reliability of the automatic driving test. The application also provides a corresponding computer program product and an automatic driving test system for the test bench of the steering hub.

Description

Technical Field

[0001] This invention relates to the field of vehicle testing technology, and in particular to an active safety control method, a computer program product, and an autonomous driving testing system for a rotating test bench. Background Technology

[0002] With the rapid iteration of autonomous driving technology, vehicle-on-the-loop bench testing has become a core means of verifying the functional safety and operational reliability of autonomous driving systems. The rotating test bench can simulate real road conditions, reproduce various dynamic responses of vehicles, and is widely used in autonomous driving control strategy calibration tests.

[0003] During autonomous driving tests on a rotary drum test bench, if the requested steering angle output by the autonomous driving system is abnormal, such as an excessively large requested steering angle or an incorrect steering command, it will drive the wheels to produce actual steering actions. Due to the low friction coefficient of the rotary drum surface and the fact that the vehicle is only longitudinally limited and lacks lateral rigid constraints, the wheels are very likely to detach from the drum, which may lead to safety accidents such as vehicle skidding or running off the test bench.

[0004] Existing safety protection measures for rotary test benches mainly consist of mechanical protective covers and emergency stop buttons, which are passive, manually triggered protection mechanisms that only take effect after an accident occurs and lack proactive intervention capabilities. At the same time, under high-speed vehicle conditions, even a small steering angle can generate a large lateral load, which can easily induce risks such as tire side slip and tire detachment from the rotary wheel. Currently, there is no proactive safety intervention mechanism to address the risk of steering over-limit under such conditions.

[0005] In summary, existing safety protection schemes for vehicle wheel rotation tests have significant limitations, and there is an urgent need for an active safety control method for vehicle wheel rotation test scenarios. Summary of the Invention

[0006] The purpose of this invention is to provide an active safety control method, a computer program product, and an automatic driving test system for a rotating hub test bench, so as to at least partially solve various technical problems existing in the prior art.

[0007] According to a first aspect of the present invention, an active safety control method for a rotating hub test bench is provided, comprising: Obtain the current vehicle speed v and the current decision steering angle θ of the test vehicle; The safe steering angle threshold θ at the current vehicle speed v is calculated based on the preset vehicle speed-safe steering angle model. max_v ; Based on the current decision steering angle θ and the safe steering angle threshold θ max_v The comparison relationship is used to classify the current sideslip risk into multiple risk levels; and Implement the corresponding safety measures based on the risk level of the current decision-making turning angle θ.

[0008] In one exemplary embodiment, the plurality of risk levels includes: Safe region L1: θ ∈ [0, α1 × θ max_v ); Alarm zone L2: θ ∈ [α1 × θ max_v , α2 × θ max_v ); Intervention zone L3: θ ∈ [α2 × θ max_v , θ max_v ); Emergency stop zone L4: θ ∈ [θ max_v , ∞). Where α1 and α2 are preset grading threshold coefficients, and 0 < α1 < α2 < 1.

[0009] In one exemplary embodiment, the security measures corresponding to the corresponding risk level include: Safe Zone L1: No intervention action; Alarm zone L2: Triggers an alarm action; Intervention zone L3: Triggers active braking and / or torque limiting actions; and Emergency Stop Zone L4: Triggers the test stop action.

[0010] In one exemplary embodiment, the alarm action is an audible and visual alarm action.

[0011] In one exemplary embodiment, the active braking action includes operating the vehicle brake pedal via an external brake actuator or sending a braking request via the vehicle CAN bus.

[0012] In one exemplary embodiment, the torque limiting action includes sending a torque limiting request to the vehicle powertrain.

[0013] In one exemplary embodiment, the test stop action includes: an emergency stop action of the hub dynamometer, a disengagement action of removing the test wheel from the hub, sending an emergency stop signal to the vehicle, and / or a power-off action of the test system.

[0014] In one exemplary embodiment, α1 = 0.7, α2 = 0.9.

[0015] In one exemplary embodiment, the current vehicle speed v is obtained from the wheel speed sensor of the hub dynamometer and / or the vehicle CAN bus.

[0016] In one exemplary embodiment, the current decision steering angle θ is obtained from an onboard steering angle sensor and / or from the decision output interface of the vehicle's autonomous driving system.

[0017] In one exemplary embodiment, the vehicle speed-safe steering angle model is established in the following manner: The critical steering angle corresponding to different vehicle speeds is obtained through experiments, or the critical steering angle corresponding to different vehicle speeds is calculated based on the side slip characteristics of the test tire, the friction coefficient of the hub surface, the vehicle track width, and the vehicle speed. The critical steering angle is the maximum allowable steering angle at which the test wheel does not leave the hub at the corresponding vehicle speed. The vehicle speed-safe steering angle model is obtained by fitting multiple sets of vehicle speed-critical steering angle data.

[0018] According to a second aspect of the present invention, a computer program product, particularly a computer-readable program carrier, is provided, the computer program product including or storing computer program instructions, which, when executed by a processor, enable the processor to at least assist in performing the method described according to the first aspect of the present invention.

[0019] According to a third aspect of the present invention, an automatic driving test system for a rotating hub test bench is provided, comprising: a controller including a memory and a processor, the memory storing computer program instructions, wherein when the computer program instructions are executed by the processor, the processor is capable of at least assisting in the execution of the method according to the first aspect of the present invention.

[0020] In one exemplary embodiment, the vehicle-mounted autonomous driving test system for the rotating test bench further includes: An external brake actuator is used to operate the vehicle's brake pedal; An alarm device used to trigger an alarm action; A lifting protection device is used to lift the vehicle so that the test wheels are removed from the hub.

[0021] The beneficial effects of the present invention, based on the above aspects, are that it enables dynamic joint judgment based on real-time vehicle speed and steering angle during the dynamometer test, allowing for proactive safety intervention before the test vehicle skids due to abnormal steering angle, thus ensuring the safety of the test process. Differentiated intervention actions are taken according to the skid risk level, from alarm to braking to emergency stop, balancing the continuity and safety of the test. Furthermore, the method according to the present invention does not require modification of the mechanical structure of the dynamometer, such as the addition of a rotatable dynamometer, making it suitable for most existing dynamometer test benches; and it can deeply collaborate with autonomous driving systems, directly accessing the decision signals of the autonomous driving controller as a "redundant layer" for its safety monitoring, improving the reliability of autonomous driving testing. Moreover, the method according to the present invention has a high degree of automation, requiring no manual intervention throughout the process, making it particularly suitable for long-term durability testing or hazardous condition verification in unmanned driving mode, and it is highly scalable, adapting to various testing needs. Attached Figure Description

[0022] The invention will now be described in more detail with reference to the accompanying drawings, which will provide a better understanding of its principles, features, and advantages. The drawings include: Figure 1 A flowchart illustrating the main steps of an active safety control method for a rotating hub test bench according to an exemplary embodiment of the present invention is shown schematically. Figure 2 A risk level determination logic diagram of an active safety control method for a rotating hub test bench according to an exemplary embodiment of the present invention is schematically shown; and Figure 3 A block diagram of an autonomous driving test system for a rotating test bench according to an exemplary embodiment of the present invention is shown schematically. Detailed Implementation

[0023] To make the technical problems to be solved, the technical solutions, and the beneficial technical effects of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and several exemplary embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of protection of this invention.

[0024] Figure 1 A flowchart illustrating the main steps of an active safety control method for a rotating hub test bench according to an exemplary embodiment of the present invention is shown schematically. Figure 1 As shown, the active safety control method for a rotating hub test bench according to an exemplary embodiment of the present invention mainly includes the following steps: S1: Obtain the current vehicle speed v and the current decision steering angle θ of the test vehicle; S2: Calculate the safe steering angle threshold θ at the current vehicle speed v based on the preset vehicle speed-safe steering angle model. max_v ; S3: Based on the current decision steering angle θ and the safe steering angle threshold θ max_v The comparison relationship is used to classify the current sideslip risk into multiple risk levels; and S4: Implement the corresponding safety measures based on the risk level of the current decision turning angle θ.

[0025] In step S1, the current vehicle speed v (km / h) can be acquired by the wheel speed sensor built into the hub dynamometer. Utilizing the contact transmission characteristics between the hub roller and the vehicle tires, the actual wheel speed measured on the test bench is accurately acquired and converted to the actual vehicle speed. This method is also adaptable to various extreme driving conditions and low-friction road surfaces. Alternatively, the current vehicle speed v can also be acquired from the vehicle's CAN bus, i.e., directly reading the vehicle's overall vehicle speed signal output by the vehicle network. On the other hand, the vehicle's current decision steering angle θ can be acquired in real time by an onboard steering angle sensor installed on the steering column of the vehicle's steering wheel. Alternatively, it can be acquired directly from the decision output interface of the vehicle's autonomous driving system, i.e., directly obtaining the target steering decision command issued by the autonomous driving controller. When dual-redundant data acquisition is used, bidirectional data acquisition and comparison between the autonomous driving decision command and the actual vehicle execution state can be achieved, providing core data support for subsequent autonomous driving lateral control accuracy verification, steering follow-up testing, and closed-loop condition simulation verification. For example, a positive value of the current decision turning angle θ indicates a right turn, a negative value indicates a left turn, and the absolute value indicates the magnitude. This article mainly focuses on the magnitude of the current decision turning angle θ, so the "current decision turning angle θ" here refers to its absolute value.

[0026] In step S2, the vehicle speed-safe steering angle model can be established through experimental calibration. Specifically, the critical steering angle at which the wheel is about to leave the hub at different vehicle speeds can be obtained through pre-testing, i.e., the maximum permissible steering angle at which the wheel will not leave the hub at the corresponding vehicle speed. Then, the vehicle speed-safe steering angle model is obtained by fitting multiple sets of vehicle speed-critical steering angle data. For example, at a vehicle speed of 30 km / h, the critical steering angle is 30°. When the vehicle speed is between 30 and 80 km / h, the critical steering angle decreases linearly. When the vehicle speed is greater than 80 km / h, the critical steering angle does not exceed 5°. Based on these data, a safe threshold curve for the steering angle can be obtained through appropriate fitting, which serves as the vehicle speed-safe steering angle model. Here, the pre-testing is conducted on the same test vehicle under the same hub surface conditions to eliminate the influence of differences in other parameters.

[0027] Alternatively, a vehicle speed-safe steering angle model can be established through theoretical calculations. Specifically, by combining three parameters—the lateral slip characteristics of the test tire, the friction coefficient of the hub surface, and the track width of the test vehicle—the steering limits of the vehicle at different driving speeds can be calculated. This yields the maximum permissible steering angle at which the test wheel can stably maintain contact with the hub without slipping or derailing at the corresponding speed; this is the critical steering angle at that speed. Then, multiple sets of one-to-one corresponding raw data on vehicle speed-critical steering angles are collected, and these sets of data are fitted to obtain the vehicle speed-safe steering angle model.

[0028] After constructing the vehicle speed-safe steering angle model, inputting the current vehicle speed v into the model will yield the safe steering angle threshold θ at the current vehicle speed v. max_v .

[0029] In step S3, preferably, risk levels are divided based on preset grading threshold coefficients α1 and α2, where 0 < α1 < α2 < 1. Setting two levels of threshold coefficients allows for interval segmentation of the process where the steering angle approaches the critical limit, accurately distinguishing between safe operating conditions, early warning conditions, intervention conditions, and dangerous operating conditions, thus forming a graded warning and intervention protection system. Of course, depending on actual requirements, more or fewer grading threshold coefficients can be used. In a preferred example, α1 = 0.7 and α2 = 0.9, thus reserving sufficient safety redundancy, allowing the current decision steering angle θ to approach the safe steering angle threshold θ. max_v Early warning intervention can be triggered in advance, which can avoid premature intervention from affecting the normal autonomous driving test conditions and effectively prevent the risk of wheel derailment caused by steering exceeding the limit.

[0030] Multiple risk levels can include: The safe zone L1 corresponds to θ ∈ [0, α1 × θ]. max_v ): This indicates that the system is running normally and no intervention is required; Alarm zone L2, corresponding to θ ∈ [α1 × θ max_v , α2 × θ max_v ): This indicates that the vehicle is approaching a danger boundary at the current steering angle θ, and an alarm should be triggered; Intervention zone L3, corresponding to θ ∈ [α2 × θ max_v , θ max_v ): This indicates that although no actual danger has occurred at the current decision steering angle θ, the vehicle has exceeded the safety limit, and proactive intervention measures should be taken to ensure safety; and Emergency stop zone L4, corresponding to θ ∈ [θ max_v , ∞): Indicates that a danger has occurred and emergency safety procedures should be performed immediately.

[0031] Figure 2A risk level determination logic diagram of a method according to an exemplary embodiment of the present invention is illustrated schematically. Figure 2 As shown, the current decision steering angle θ is obtained and the safe steering angle threshold θ is determined. max_v Furthermore, after classifying the risk levels based on the tiered threshold coefficients α1 and α2, a judgment is made: (1) If θ < α1 × θ max_v If so, the risk level is safe zone L1; (2) If α1 × θ max_v ≤ θ<α2 × θ max_v The risk level is then classified as alarm zone L2. (3) If α2 × θ max_v ≤ θ<θ max_v If so, the risk level is intervention zone L3; (4) Otherwise θ ≥ θ max_v The risk level is L4, which is an emergency stop zone.

[0032] Accordingly, in step S4, the safety measures corresponding to each risk level may include: Safe Zone L1: No intervention actions, record test data; Alarm Zone L2: Triggers alarm actions, such as issuing an audible and visual alarm through the test monitoring interface and recording the abnormal event in the log; Intervention Zone L3: Triggers active braking and / or torque limiting actions, including: applying braking force to the vehicle's brake pedal via an external brake actuator; sending a braking request via the vehicle's CAN bus to apply deceleration (e.g., ≤0.3g); and / or sending a torque limiting request to the vehicle's powertrain, such as limiting engine speed or electric motor output to prevent further vehicle acceleration, while simultaneously maintaining the dynamometer's normal operation for smooth deceleration; and Emergency Stop Zone L4: Triggers test stop actions, which may include: 1) Triggering an emergency stop of the dynamometer, which will sequentially unload resistance and stop rotating; 2) Simultaneously triggering the lifting protection device to lift the test vehicle and remove the test wheels from the dynamometer; 3) If the vehicle supports remote emergency stop, sending a wireless emergency stop signal to the vehicle; and optional 4) Powering off the test system.

[0033] In addition, the above-mentioned test stop action can also be triggered when other signals indicating impending loss of vehicle control, such as sudden wheel speed changes or excessive longitudinal tension, are detected.

[0034] When the risk level reaches the intervention zone L3, the intervention action corresponding to the intervention zone L3 can be automatically released when the risk level drops below the intervention zone and the current vehicle speed v is lower than the preset safe speed (e.g., 5 km / h), allowing the test to continue.

[0035] If the risk level reaches the emergency stop zone L4, completely stop the test task, record the fault data, and notify the test engineer to intervene.

[0036] The above describes an active safety control method for a rotating hub test bench according to embodiments of the present invention. The following describes an autonomous driving test system for a rotating hub test bench according to embodiments of the present invention, which can at least assist in implementing the method.

[0037] Figure 3 A block diagram of an autonomous driving test system 100 for a rotating test bench according to an exemplary embodiment of the present invention is shown schematically. Figure 3 As shown, an autonomous driving test system 100 for a hub test bench according to an exemplary embodiment of the present invention may include a hub dynamometer 1, a virtual scene injection unit 2, a visual feedback display device 3, an autonomous driving controller interface 4, and a controller 10 configured to at least assist in executing an active safety control method for a hub test bench according to an embodiment of the present invention.

[0038] The hub dynamometer 1 is used to support the drive wheel of the test vehicle, i.e. the test wheel, to apply driving resistance, and can collect longitudinal dynamic parameters such as vehicle speed, torque, and rotational speed in real time.

[0039] The virtual scene injection unit 2 is used to inject virtual traffic environment signals into the autonomous driving sensors of the test vehicle, and may include a vision injection module 21, a radar / LiDAR injection module 22, and a virtual-real fusion engine 23. The vision injection module 21 is, for example, an external display unit, detachably mounted in front of the vehicle's forward-facing camera, used to display visual information such as virtual road images, traffic participants, and obstacles generated by the virtual-real fusion engine 23. The radar / LiDAR injection module 22 is, for example, a radio frequency signal simulator, used to generate virtual echo signals for the vehicle's millimeter-wave radar or LiDAR, simulating the distance, speed, and azimuth of targets ahead. The virtual-real fusion engine 23 is connected to the vision injection module 21 and the radar / LiDAR injection module 22, used to generate spatiotemporally synchronized virtual scene signals, ensuring that the camera image and the target position and speed in the radar point cloud are consistent.

[0040] The visual feedback display device 3 is located in front of the rotating test bench. It can be a liftable projection screen or a large LED display screen. It is used to project road images synchronized with the virtual scene injection unit 2, so that test monitoring personnel can observe the driving status of the vehicle in the virtual scene. It can also provide visual feedback for the driver's on-loop test.

[0041] The autonomous driving controller interface 4 is used to interact with the autonomous driving controller of the test vehicle to obtain information such as the current decision steering angle θ, as described above. The autonomous driving controller interface 4 includes at least a perception signal input interface 41, a decision signal output interface 42, and a vehicle state feedback interface 43. The perception signal input interface 41 transmits the signals generated by the virtual scene injection unit 2 to the vehicle's autonomous driving controller, replacing or superimposing the inputs from the vehicle's real sensors. The decision signal output interface 42 reads the steering angle (current decision steering angle θ), acceleration, braking, and other decision commands output by the vehicle's autonomous driving controller in real time. The vehicle state feedback interface 43 sends information such as the actual vehicle speed / current vehicle speed v and wheel speed collected by the hub dynamometer 1 to the vehicle's autonomous driving controller, forming a closed loop.

[0042] The controller 10 incorporates the vehicle speed-safe steering angle model and is connected to the hub dynamometer 1, the autonomous driving controller interface 4, and the vehicle's braking / power system to monitor the autonomous driving controller's decision commands in real time and execute graded safety interventions when an anomaly is detected.

[0043] Specifically, regarding the execution of the active safety control method, the autonomous driving test system 100 for a rotating test bench according to an embodiment of the present invention further includes, connected to the controller 10: an external brake actuator 11 for operating the vehicle brake pedal; an alarm device 12 for triggering an alarm action; and a lifting protection device 13 for lifting the vehicle to remove the test wheels from the rotating hub.

[0044] The following describes the workflow of performing autonomous driving tests using the autonomous driving test system 100 for a rotating test bench according to an embodiment of the present invention.

[0045] First, in the preparation phase, the test vehicle is driven onto and secured to the dynamometer 1. Then, the virtual scene injection unit 2 is installed and aligned with the vehicle's sensors. A visual feedback display device 3, such as a retractable projection screen, is set up as the monitoring display interface. The autonomous driving controller interface 4 is connected to the autonomous driving controller of the test vehicle. Finally, the controller 10, used to execute the active safety control method, is started to complete the system self-test.

[0046] During the test execution phase, the virtual-real fusion engine 23 loads preset test scenarios, such as highways, urban roads, and emergency avoidance scenarios. The virtual scene injection unit 2 injects synchronized visual and radar signals into the vehicle's autonomous driving controller, enabling the controller to autonomously decide on steering, acceleration, braking, and other actions based on the injected virtual scene. The dynamometer 1 applies resistance based on the vehicle's actual power output, simulating real driving. The controller 10 monitors the autonomous driving controller's decision commands in real time, especially the current steering angle θ, and collects the current vehicle speed v in real time. Using the vehicle speed-safe steering angle model, the safe steering angle threshold θ at the current vehicle speed v is obtained. max_v Based on the current decision steering angle θ and the safe steering angle threshold θ max_v Based on the comparison relationship, the current sideslip risk is divided into multiple risk levels, such as a safe zone L1, an alarm zone L2, an intervention zone L3, and an emergency stop zone L4. Corresponding safety measures are then implemented according to the risk level of the current decision steering angle θ, as described above. During this period, monitoring personnel can observe the vehicle's driving status in the virtual scenario through the monitoring display interface.

[0047] At the end of the test, the virtual scene injection was stopped, all external devices were removed, and the vehicle was restored to its original state.

[0048] The method and system according to embodiments of the present invention are compatible with existing fixed rotating drums, requiring no modification to the rotating drum's mechanical structure, and can be adapted to various mainstream brand rotating drum test benches, significantly reducing equipment modification costs; they can monitor autonomous driving decisions in real time and automatically implement graded interventions in case of anomalies to ensure the safety of equipment and personnel; and they are highly scalable, supporting test cases that are difficult to reproduce in traditional road tests, such as regulatory tests, extreme working conditions, and dangerous scenarios.

[0049] The present invention also proposes a computer program product, particularly a computer-readable program carrier, the computer program product including or storing computer program instructions, which, when executed by a processor, enable the processor to at least assist in executing the active safety control method for a rotating hub test bench according to an embodiment of the present invention.

[0050] Although specific embodiments of the invention have been described in detail herein, they are given for illustrative purposes only and should not be construed as limiting the scope of the invention. Various substitutions, alterations, and modifications can be conceived without departing from the spirit and scope of the invention.

Claims

1. An active safety control method for a rotating hub test bench, comprising: Obtain the current vehicle speed v and the current decision steering angle θ of the test vehicle; The safe steering angle threshold θ at the current vehicle speed v is calculated based on the preset vehicle speed-safe steering angle model. max_v ; Based on the current decision steering angle θ and the safe steering angle threshold θ max_v Based on the comparative relationships, the current sideslip risk is divided into multiple risk levels; and Implement the corresponding safety measures based on the risk level of the current decision-making turning angle θ.

2. The active safety control method for a rotating hub test bench according to claim 1, wherein, The multiple risk levels include: Safe region L1: θ ∈ [0, α1 × θ max_v ); Alarm zone L2: θ ∈ [α1 × θ max_v , α2 × θ max_v ); Intervention zone L3: θ ∈ [α2 × θ max_v , θ max_v ); Emergency stop zone L4: θ ∈ [θ max_v , ∞). Where α1 and α2 are preset grading threshold coefficients, and 0 < α1 < α2 < 1.

3. The active safety control method for a rotating hub test bench according to claim 2, wherein, The safety measures corresponding to the respective risk levels include: Safe Zone L1: No intervention action; Alarm zone L2: Triggers an alarm action; Intervention zone L3: Triggers active braking and / or torque limiting actions; and Emergency Stop Zone L4: Triggers the test stop action.

4. The active safety control method for a rotating hub test bench according to claim 3, wherein, The alarm action is an audible and visual alarm action; The active braking action includes operating the vehicle's brake pedal via an external brake actuator, or sending a braking request via the vehicle's CAN bus. The torque limiting action includes sending a torque limiting request to the vehicle powertrain system; and / or The test stopping actions include: emergency stop of the hub dynamometer, disengagement action to remove the test wheel from the hub, sending an emergency stop signal to the vehicle, and / or power cut-off of the test system.

5. The active safety control method for a rotating hub test bench according to any one of claims 2 to 4, wherein, α1 = 0.7，α2 = 0.9。 6. The active safety control method for a rotating hub test bench according to any one of claims 1 to 5, wherein, Obtain the current vehicle speed v from the wheel speed sensor of the hub dynamometer and / or the vehicle CAN bus; and / or The current decision steering angle θ is obtained from the onboard steering angle sensor and / or from the decision output interface of the vehicle's autonomous driving system.

7. The active safety control method for a rotating hub test bench according to any one of claims 1 to 6, wherein, The vehicle speed-safe steering angle model is established in the following way: The critical steering angle at different vehicle speeds is obtained through experiments, or calculated based on the test tire's lateral slip characteristics, the friction coefficient of the hub surface, the vehicle's track width, and the vehicle speed. The critical steering angle is the maximum permissible steering angle at which the test wheel does not leave the hub at the corresponding vehicle speed. The vehicle speed-safe steering angle model is obtained by fitting multiple sets of vehicle speed-critical steering angle data.

8. A computer program product, particularly a computer-readable program carrier, the computer program product comprising or storing computer program instructions, wherein when the computer program instructions are executed by a processor, the processor is capable of at least assisting in performing the method according to any one of claims 1-7.

9. An automatic driving test system (100) for a rotating test bench, comprising: The controller (10) includes a memory and a processor, the memory storing computer program instructions that, when executed by the processor, enable the processor to at least assist in performing the method according to any one of claims 1-7.

10. The automatic driving test system (100) for a rotating test bench according to claim 9, further comprising: An external brake actuator (11) is used to operate the vehicle brake pedal; Alarm device (12), which is used to trigger an alarm action; Lifting protection device (13) is used to lift the vehicle so that the test wheels are removed from the hub.

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