In-service equipment detection method, device and equipment for autonomous vehicle

Abstract

This application provides a method, apparatus, and device for detecting in-service equipment in autonomous vehicles. The method includes: identifying one or more consistency detection point road segments in an electronic data map that meet the requirements for stable driving in autonomous driving mode; obtaining a reference range of response parameters for in-service equipment in autonomous driving mode; collecting actual values ​​of response parameters of in-service equipment on the target vehicle when the target vehicle is driving in autonomous driving mode on the consistency detection point road segments; and outputting the performance status of the in-service equipment based on the actual values ​​of the response parameters and the reference range of the response parameters. This application enables an indirect, effective, and early assessment of the performance degradation status of key in-service equipment in autonomous vehicles.

Description

Technical Field

[0001] This application relates to the field of autonomous driving control technology, specifically to a method, apparatus, and equipment for testing in-service equipment for autonomous vehicles. Background Technology

[0002] In the field of autonomous driving technology, in order to ensure driving safety and system reliability, relevant standards clearly require autonomous driving systems to have the ability to continuously monitor the in-service operating status of their key in-service equipment (such as steering systems) so as to provide timely warnings or take corresponding measures when component performance deteriorates.

[0003] In related technologies, the condition monitoring of in-service vehicle equipment typically relies on dedicated sensors directly mounted on the equipment. These sensors directly measure the physical parameters of the equipment (such as position, pressure, and temperature), and determine whether a malfunction has occurred by monitoring whether these parameters exceed preset thresholds. However, for gradual performance degradation caused by long-term wear and aging, its early manifestations may not reach the trigger thresholds of traditional fault diagnosis, making it difficult for the system to effectively predict before a significant decline in control capabilities. Especially for some in-service equipment that is not equipped with direct performance monitoring sensors, the system lacks an effective means to quantitatively assess its performance status.

[0004] Therefore, in the absence of direct sensor monitoring technology, how to achieve indirect, effective and early assessment of the performance degradation status of key in-service equipment in autonomous vehicles has become a specific technical problem that urgently needs to be solved to improve the active safety and operational reliability of autonomous driving systems. Summary of the Invention

[0005] In view of this, this application aims to provide a method, apparatus and equipment for testing in-service equipment of autonomous vehicles, which can indirectly, effectively and in advance assess the performance degradation status of key in-service equipment of autonomous vehicles.

[0006] The first aspect of this application provides a method for detecting in-service equipment for autonomous vehicles, comprising: determining one or more consistency detection point road segments in an electronic data map that meet the requirements for stable driving in autonomous driving mode; obtaining a reference range of response parameters of in-service equipment in autonomous driving mode; collecting actual values ​​of response parameters of in-service equipment on the target vehicle when the target vehicle is driving in autonomous driving mode on the consistency detection point road segments; and outputting the performance status of the in-service equipment based on the actual values ​​of the response parameters of the in-service equipment and the reference range of the response parameters.

[0007] In one possible implementation, determining one or more consistency detection point road segments in the electronic data map that meet the requirements for stable driving in autonomous driving mode includes: filtering out one or more characteristic road segments in the electronic data map where the vehicle is in a stable control state when driving in autonomous driving mode; and determining the one or more characteristic road segments as consistency detection point road segments.

[0008] In one possible implementation, the consistency detection point segment includes a straight-ahead detection segment and / or a curve detection segment.

[0009] In one possible implementation, obtaining the baseline range of response parameters for in-service equipment in autonomous driving mode includes: collecting a first range of response parameters for the in-service equipment in autonomous driving mode before durability testing is performed on a designated test road segment; wherein the designated test road segment is the same as the consistency detection point road segment; collecting a second range of response parameters for the test vehicle with durability testing equipment after installation in autonomous driving mode on the designated test road segment; and determining the baseline range of response parameters for the in-service equipment at the consistency detection point road segment based on the first range of response parameters, the second range of response parameters, and environmental impact factors.

[0010] In one possible implementation, the consistency detection point section is a straight-ahead detection section, and the in-service equipment is a steering system. Accordingly, collecting the actual values ​​of the response parameters of the in-service equipment when the target vehicle is driving in autonomous driving mode on the consistency detection point section includes: collecting the left and right deviation values ​​of the steering system when the target vehicle is driving in autonomous driving mode on the straight-ahead detection section. Correspondingly, outputting the performance status of the in-service equipment based on the actual values ​​of the response parameters and the reference range of the response parameters includes: if the left and right deviation value of the steering system exceeds the first reference range of the steering system's response parameters, then outputting a prompt indicating a steering system malfunction; wherein the first reference range of the response parameters is the reference range of the left and right deviation values ​​corresponding to the steering system on the straight-ahead detection section; if the deviation value of the steering system does not exceed the first reference range of the steering system's response parameters, then determining that the steering system is not malfunctioning.

[0011] In one possible implementation, the consistency detection point section is a curve detection section, and the in-service equipment is a steering system. Accordingly, collecting the actual values ​​of the response parameters of the in-service equipment when the target vehicle is driving in autonomous driving mode on the consistency detection point section includes: collecting the left and right deviation values ​​of the steering angle of the steering system when the target vehicle is driving in autonomous driving mode on the curve detection section. Correspondingly, outputting the performance status of the in-service equipment based on the actual values ​​of the response parameters and the reference range of the response parameters includes: if the left and right deviation value of the steering angle of the steering system exceeds the second reference range of the steering system's response parameters, then outputting a fault indication for the steering system; wherein the second reference range of the response parameters is the reference range of the left and right deviation values ​​of the steering angle corresponding to the steering system on the curve detection section; if the deviation value of the steering system does not exceed the second reference range of the steering system's response parameters, then it is determined that the steering system is not faulty.

[0012] In one possible implementation, the in-service equipment is a steering system; correspondingly, collecting the actual values ​​of the response parameters of the in-service equipment when the target vehicle is driving in autonomous driving mode at the consistency detection point section includes: collecting the fluctuation amplitude of the operating parameters of the drive motor of the steering system when the target vehicle is driving in autonomous driving mode at the consistency detection point section; correspondingly, outputting the performance status of the in-service equipment based on the actual values ​​of the response parameters of the in-service equipment and the reference range of the response parameters includes: if the fluctuation amplitude of the operating parameters of the drive motor of the steering system exceeds the third reference range of the steering system's response parameters, then outputting a prompt that the steering system has a fault; wherein the third reference range of the response parameters is the reference range of the fluctuation amplitude of the operating parameters of the drive motor of the steering system at the consistency detection point section; if the fluctuation amplitude of the operating parameters of the drive motor of the steering system does not exceed the third reference range of the steering system's response parameters, then determining that the steering system has no fault.

[0013] In one possible implementation, the operating parameters of the drive motor of the steering system include: the current value of the drive motor and / or the torque value of the drive motor.

[0014] In one possible implementation, after outputting the performance status of the in-service equipment based on the actual value of the response parameters and the reference range of the response parameters, the method further includes: if the output performance status of the in-service equipment indicates a fault, and the actual value of the response parameters exceeds a preset maximum deviation value, then further determining whether the total mileage of the target vehicle's autonomous driving mode exceeds a preset autonomous driving lifespan limit; if the total mileage of the autonomous driving mode exceeds the preset autonomous driving lifespan limit, then outputting a prompt indicating that the autonomous driving system is scrapped and disabled; if the total mileage of the autonomous driving mode does not exceed the preset autonomous driving lifespan limit, then outputting a prompt indicating that the in-service equipment has a fault.

[0015] A second aspect of this application also provides an in-service equipment testing device for autonomous vehicles, comprising: a setting module for determining one or more consistency detection point road segments in an electronic data map that meet the requirements for stable driving in autonomous driving mode; an acquisition module for acquiring a reference range of response parameters of in-service equipment in autonomous driving mode; a collection module for collecting the actual values ​​of response parameters of in-service equipment on the target vehicle when the target vehicle is driving in autonomous driving mode on the consistency detection point road segments; and an output module for outputting the performance status of the in-service equipment based on the actual values ​​of the response parameters of the in-service equipment and the reference range of the response parameters.

[0016] A third aspect of this application provides an electronic device comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor to cause the at least one processor to perform an in-service equipment testing method for an autonomous vehicle as described in the first aspect and possible implementations thereof.

[0017] The fourth aspect of this application provides a computer storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement an in-service equipment detection method for an autonomous vehicle, as described in the first aspect and possible implementations thereof.

[0018] The fifth aspect of this application provides a computer program product comprising: a computer program that, when executed by a processor, implements an in-service equipment detection method for an autonomous vehicle as described in the first aspect and possible implementations thereof.

[0019] The present application provides a method, apparatus, and equipment for detecting in-service equipment for autonomous vehicles. In this method, a consistency detection point section that meets the requirements for stable driving in autonomous driving mode is preset in an electronic data map. When the vehicle is driving in autonomous driving mode on the consistency detection point section, the actual values ​​of the response parameters of the in-service equipment are collected. The actual values ​​of the response parameters are compared with a preset response parameter benchmark range to determine the performance status of the in-service equipment. This scheme utilizes the principle that equipment performance degradation will be reflected in the consistency of its response to stable control commands, realizing indirect and quantitative status monitoring of equipment without direct detection mechanisms. It can effectively detect performance degradation trends at an early stage, avoid driving risks caused by sudden failures of in-service equipment, and improve the safety and reliability of autonomous driving systems. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the specific embodiments or related technologies of this application, the drawings used in the description of the specific embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a schematic diagram illustrating an application scenario for in-service equipment testing of autonomous vehicles, as provided in an embodiment of this application.

[0022] Figure 2 This is a flowchart illustrating an in-service equipment testing method for autonomous vehicles provided in an embodiment of this application.

[0023] Figure 3 This is a schematic diagram illustrating the setting of consistency detection points on road segments in an electronic data map, as provided in an embodiment of this application.

[0024] Figure 4 A schematic diagram of the road segment for consistency detection points provided in the embodiments of this application. Figure 1 .

[0025] Figure 5 A schematic diagram of the road segment for consistency detection points provided in the embodiments of this application. Figure 2 .

[0026] Figure 6 This is a schematic diagram showing the fluctuations in the operating parameters of the drive motor of the steering system before and after durability testing.

[0027] Figure 7 This is a schematic diagram of the structure of an in-service equipment testing device for autonomous vehicles provided in an embodiment of this application.

[0028] Figure 8This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0029] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0030] In the field of operational health monitoring for autonomous vehicles, particularly concerning the lifespan prediction and fault warning of critical mechanical equipment such as steering and braking systems, the industry generally recognizes the need to establish an effective in-service equipment capability monitoring mechanism in order to meet the functional safety requirements of relevant regulations and standards for autonomous driving systems. Its core common objective is to promptly and accurately detect performance degradation trends in in-service equipment lacking directly built-in sensors, thereby enabling early warning or intervention measures to be taken before potential failures or functional malfunctions occur, ensuring the continuous safe operation of the autonomous driving system.

[0031] To achieve the above objectives, related technologies typically employ two main approaches. One approach relies on direct physical sensors for monitoring, such as directly acquiring specific physical signals from in-service equipment using temperature, vibration, or displacement sensors. However, this method is difficult to implement for many in-service equipment without pre-embedded sensors, or for internal mechanical wear that is not readily apparent in the early stages of performance degradation (such as increased clearance in the rack and pinion pairs of the steering system or slight jamming due to poor lubrication). Another common approach is to estimate lifespan based on simple mileage or time statistics, i.e., pre-setting a fixed mileage or time threshold, and prompting maintenance or replacement upon reaching it. The limitation of this method is that it cannot reflect the true performance degradation state of in-service equipment under complex actual operating conditions. The actual lifespan of the same model of in-service equipment varies significantly under different usage habits and road conditions, leading to warnings that may be too early or too late. This can result in unnecessary maintenance costs or safety risks due to the failure to detect potential problems in a timely manner.

[0032] Therefore, a prominent problem faced by existing technologies is that for the numerous critical in-service equipment in autonomous vehicles that lack direct detection mechanisms, the inability to directly and in real-time perceive the gradual changes in their internal mechanical characteristics makes it difficult to detect performance degradation issues in a timely, accurate, and adaptive manner. This problem makes it difficult for autonomous driving systems to meet the higher requirements for refined and proactive monitoring of the health status of in-service equipment, posing functional safety risks in the "abnormal area" where the performance of in-service equipment has declined but has not yet completely failed. How to achieve effective indirect monitoring of the performance status of such in-service equipment without adding additional dedicated sensors has become a pressing technical challenge in this field. To this end, this application provides the following inventive concept: by utilizing the vehicle's operating data under preset, repeatable characteristic driving scenarios, parameters characterizing the response consistency of in-service equipment are collected, and these parameters are compared with a preset benchmark range, thereby indirectly assessing the performance degradation status of in-service equipment. Thus, without adding internal sensors to each piece of in-service equipment or significantly increasing the complexity of the system hardware, quantitative monitoring and early warning of performance degradation of in-service equipment that is difficult to perceive directly can be effectively achieved.

[0033] Figure 1 This is a schematic diagram illustrating an application scenario for in-service equipment testing of autonomous vehicles, provided in an embodiment of this application. (Reference) Figure 1 This scenario includes a control terminal 101 and a target vehicle 102. The control terminal 101 and the target vehicle 102 can transmit data via a bus network connection. It should be noted that the control terminal 101 can be any type of controller on the vehicle, such as a vehicle controller. The control terminal 101 is used to collect various operational data related to the target vehicle 102, such as electronic data maps and response parameters of in-service equipment.

[0034] Exemplary methods Figure 2 This is a flowchart illustrating an in-service equipment testing method for autonomous vehicles provided in an embodiment of this application. The executing entity in this embodiment can be... Figure 1 The control terminal in the illustrated embodiment. For example... Figure 2 As shown, the method includes: S201: In the electronic data map, identify one or more road segments with consistency detection points that meet the requirements for stable driving in autonomous driving mode.

[0035] In the embodiments of this application, consistency detection point road segments can be set in the crowdsourced electronic data map uploaded by the user.

[0036] Specifically, one or more characteristic road segments are selected from the electronic data map where the vehicle is in a stable control state when driving in autonomous driving mode; these one or more characteristic road segments are then identified as consistency detection point road segments.

[0037] In this context, "vehicle in a stable control state" means that when the vehicle is driving in autonomous driving mode, it will not exhibit any changes in control requirements (such as lane changing, steering, etc.). For example, "vehicle in a stable control state" could mean that the vehicle is driving steadily in a straight line on a straight road or driving with a fixed steering angle on a curved road.

[0038] In one embodiment, the consistency detection point section is a straight-ahead detection section.

[0039] For example, the straight-ahead detection section is a 200-meter-long straight-ahead section. Within this section, a speed limit can be set to ensure the vehicle's autonomous driving time is no less than 3 seconds, allowing the vehicle to travel sufficiently.

[0040] In another embodiment, the consistency detection point section is the curve detection section.

[0041] For example, the curve detection section is a curve with a radius of curvature of one of R100m, R150m, R200m, and R250m, and a curve length of 100 meters. On this curve detection section, a speed limit can be set to ensure that the vehicle's autonomous driving time is no less than 3 seconds, allowing the vehicle to travel sufficiently.

[0042] In the embodiments of this application, one or more characteristic road segments can be characteristic road segments that vehicles frequently encounter in autonomous driving mode. For example, characteristic road segments are road segments that appear at least once a day on crowdsourced electronic data maps.

[0043] refer to Figure 3 , Figure 3 This is a schematic diagram illustrating the setting of consistency detection points on road segments in an electronic data map, as provided in an embodiment of this application. Figure 3 As shown, a straight-ahead detection section (A) and a curve detection section (B) are set on the electronic data map.

[0044] S202: Obtain the baseline range of response parameters for in-service equipment in automatic driving mode.

[0045] In this embodiment, the in-service equipment can be a steering system.

[0046] The steering system includes, but is not limited to, the following actuators: drive motor, power steering motor, tie rod, steering knuckle, steering column, and steering wheel.

[0047] Specifically, the baseline range of response parameters for the operational equipment in autonomous driving mode can be read from a pre-stored database. This baseline range of response parameters can be pre-built.

[0048] In the embodiments of this application, the specific process for constructing the reference range of response parameters for in-service equipment includes steps S221 to S223: S221: On a designated test road section, collect the range of first response parameters of the test vehicle in autonomous driving mode after installing the in-service equipment before durability testing; wherein the designated test road section is the same as the consistency detection point road section.

[0049] In the embodiments of this application, the same road segment as the consistency detection point road segment is selected as the set test road segment; the in-service equipment before durability is installed on the test vehicle, and the vehicle is driven in autonomous driving mode on the set test road segment. During the driving process, a series of response parameters of the in-service equipment of the test vehicle are collected, and a first response parameter range is constructed based on the maximum and minimum values ​​of the series of response parameters.

[0050] S222: On a designated test road section, collect the range of second response parameters of the test vehicle in autonomous driving mode after the durable in-service equipment is installed.

[0051] In the embodiments of this application, durable in-service equipment is installed on a test vehicle, and the vehicle is driven in an autonomous driving mode on a set test road section. During the driving process, a series of response parameters of the in-service equipment of the test vehicle are collected, and a second response parameter range is constructed based on the maximum and minimum values ​​of the series of response parameters.

[0052] S223: Based on the first response parameter range, the second response parameter range, and environmental impact factors, determine the benchmark range of response parameters for in-service equipment at the consistency detection point road section.

[0053] In the embodiments of this application, if the range of the first response parameter before durability is less than the range of the second response parameter after durability, the range of the second response parameter is determined to be reliable data, and the environmental impact coefficient is determined according to the environmental impact factor. The baseline range of the response parameter is obtained according to the environmental impact coefficient and the range of the second response parameter.

[0054] In the embodiments of this application, the environmental impact factor may be the temperature impact factor.

[0055] Specifically, the product of the environmental impact coefficient and the second response parameter range can be used as the baseline range of the response parameters.

[0056] In one example, the in-service equipment is the steering system, and the test route is set as a straight road. The first response parameter range of the test vehicle in automatic driving mode after the steering system is installed (before durability testing), i.e., the left-right deviation range of the steering angle is [-0.5°, 0.5°], is collected. The second response parameter range of the test vehicle in automatic driving mode after the steering system is installed (after durability testing), i.e., the left-right deviation range of the steering angle is [-1°, 1°], is collected. Since the first response parameter range before durability testing is smaller than the second response parameter range after durability testing, the second response parameter range is determined to be reliable data. The environmental influence coefficient is set to 1.0. The baseline range of response parameters is determined, i.e., the baseline range of the left-right deviation of the steering angle is [-1°, 1°]. 1.0 = [-1°, 1°].

[0057] S203: Collect the actual values ​​of the response parameters of the in-service equipment when the target vehicle is driving in autonomous driving mode on the road section of the consistency detection point.

[0058] S204: Based on the actual values ​​of the response parameters of the in-service equipment and the reference range of the response parameters, output the performance status of the in-service equipment.

[0059] In one embodiment of this application, reference is made to Figure 4 The consistency detection point section is the straight-ahead detection section, and the in-service equipment is the steering system; accordingly, step S203 specifically includes S1a, and S204 specifically includes S1b~S1c, as follows: S1a: Collect the left and right deviation values ​​of the steering angle of the steering system when the target vehicle is driving in autonomous driving mode on a straight detection section.

[0060] In the embodiments of this application, the left and right deviation values ​​of the steering angle of the steering system are collected in real time by a steering wheel angle sensor.

[0061] Specifically, the steering angle of the vehicle's steering system in the straight-ahead detection section is 0° (reference). Figure 4 (The median value of the row in the middle).

[0062] S1b: If the left and right deviation of the steering angle of the steering system exceeds the reference range of the first response parameter of the steering system, a fault indication of the steering system will be output; wherein the reference range of the first response parameter is the reference range of the left and right deviation of the steering angle of the steering system under the straight detection section.

[0063] For example, the reference range for the left and right deviation values ​​of the steering angle of the steering system in a straight-ahead detection section is [-1°, 1°] (reference). Figure 4(Right deviation error and left deviation error in the data); if the left and right deviation values ​​of the steering angle of the steering system are collected as 4°, a fault message is output indicating that the steering system has a fault.

[0064] S1c: If the deviation value of the steering system does not exceed the reference range of the first response parameter of the steering system, then it is determined that there is no fault in the steering system.

[0065] For example, the reference range of the left and right deviation of the steering angle of the steering system in the straight-ahead detection section is [-1°, 1°]; if the left and right deviation of the steering angle of the steering system is collected as 0.8°, it is determined that there is no fault in the steering system.

[0066] As described in this embodiment, by pre-setting consistency detection point road segments that meet the requirements for stable driving in autonomous driving mode in the electronic data map, and collecting the actual values ​​of the response parameters of the in-service equipment when the vehicle is driving in autonomous driving mode on the consistency detection point road segments, and comparing the actual values ​​of the response parameters with the preset response parameter benchmark range to determine the performance status of the in-service equipment, this scheme utilizes the principle that equipment performance degradation will be reflected in the consistency of its response to stable control commands. It realizes indirect and quantitative status monitoring of in-service equipment without direct detection mechanisms, which can effectively detect performance degradation trends in the early stage, avoid driving risks caused by sudden failures of in-service equipment, and improve the safety and reliability of the autonomous driving system.

[0067] In another embodiment of this application, reference is made to Figure 5 The consistency detection point is a curve detection section, and the in-service equipment is the steering system; accordingly, step S203 specifically includes S2a, and S204 specifically includes S2b~S2c, as follows: S2a: Collect the left and right deviation values ​​of the steering angle of the steering system when the target vehicle is driving in autonomous driving mode on a curved road section.

[0068] In the embodiments of this application, the left and right deviation values ​​of the steering angle of the steering system are collected in real time by a steering wheel angle sensor.

[0069] In this scenario, the steering angle of the vehicle's steering system on the straight-ahead detection section is determined based on the radius of curvature of the curve detection section. For example, in a curve detection section, the steering angle of the vehicle's steering system is a fixed value of 3° (reference). Figure 5 (The curve control angle value in the middle).

[0070] Sb2: If the left and right deviation of the steering angle of the steering system exceeds the reference range of the second response parameter of the steering system, a fault indication of the steering system will be output; where the reference range of the second response parameter is the reference range of the left and right deviation of the steering angle of the steering system under the curve detection section.

[0071] For example, in the curve detection section, the steering angle of the vehicle's steering system is 3°. Correspondingly, the left and right deviation range of the steering angle of the steering system in the curve detection section is [2°, 4°] (reference). Figure 5 (The right and left deviation errors in the curve); if the left and right deviation values ​​of the steering angle of the steering system are collected as 6°, a fault message is output indicating that the steering system has a malfunction.

[0072] Sc2: If the deviation value of the steering system does not exceed the reference range of the second response parameter of the steering system, then it is determined that there is no fault in the steering system.

[0073] For example, in the curve detection section, the steering angle of the vehicle's steering system in the curve detection section is 3°. Correspondingly, the left and right deviation values ​​of the steering angle of the steering system in the curve detection section are within the reference range of [2°, 4°]. If the left and right deviation value of the steering angle of the steering system is collected as 3.5°, it is determined that there is no fault in the steering system.

[0074] As described in this embodiment, by specifically selecting the "left-right deviation value" (i.e., the fluctuation range of the steering wheel angle command) as the response parameter characterizing the response state for the steering system in a characteristic driving scenario, the system directly captures changes in the steering system's ability to maintain consistent driving path in cornering scenarios. This enables the system to sensitively detect the decline in steering accuracy or the tendency to jam due to mechanical degradation such as wear and loosening of the steering system, achieving targeted monitoring and fault diagnosis of the core performance indicators of the steering system.

[0075] In another embodiment of this application, the in-service equipment is a steering system; accordingly, step S203 specifically includes S3a, and S204 specifically includes S3b~S3c, as follows: S3a: Collect the fluctuation amplitude of the operating parameters of the drive motor of the steering system when the target vehicle is driving in autonomous driving mode on the consistency detection point road section.

[0076] In the embodiments of this application, the consistency detection point road segment can be a straight detection road segment or a curve detection road segment, and this embodiment does not impose any restrictions on this.

[0077] The operating parameters of the drive motor include, but are not limited to: the current value and / or the torque value of the drive motor.

[0078] In this embodiment, the current value and / or torque value of the drive motor can be obtained through the controller of the drive motor.

[0079] S3b: If the fluctuation amplitude of the operating parameters of the steering system's drive motor exceeds the reference range of the third response parameter of the steering system, a fault indication will be output; where the reference range of the third response parameter is the reference range of the fluctuation amplitude of the operating parameters of the steering system's drive motor under the consistency detection point road segment.

[0080] In the embodiments of this application, reference is made to Figure 6 , Figure 6 This diagram illustrates the fluctuations in the operating parameters of the steering system's drive motor before and after durability testing. For example, the fluctuation range of the steering system's drive motor's operating parameters before durability testing is 20%, and the fluctuation range of the steering system's drive motor's operating parameters after durability testing is 40%.

[0081] Specifically, the fluctuation range of the operating parameters of the steering system's drive motor after durability testing is determined as the reference range of the fluctuation range of the drive motor's operating parameters under the consistency testing point road section. For example, the reference range of the fluctuation range of the drive motor's operating parameters under the consistency testing point road section is determined to be 40%.

[0082] In one example, if the fluctuation range of the driving motor's operating parameters at the consistency detection point is 40%, while the fluctuation range of the driving motor's operating parameters in the steering system is 50%, then a fault message will be output indicating that the steering system has a problem.

[0083] It should be noted that the tooth-like pattern of the current or torque wave controlled by the drive motor can be obtained through oscilloscope testing. This tooth-like pattern is also reflected in the software sampling resistor. When acquiring the current, the period is the same, for example, 10ms per current value. When there is a problem with the drive motor, ordinary filtering cannot eliminate this tooth-like pattern. Therefore, by adding several 10ms periods, the upper and lower wave values ​​can be identified within a small time window. This is called the difference in amplitude fluctuation. It is more obvious in the current with a larger motor torque and more obvious when rotating at the position of a mechanical jammed foreign object. Moreover, if it is caused by a mechanical jammed foreign object, it will appear in a regular periodic pattern.

[0084] S3c: If the fluctuation amplitude of the operating parameters of the drive motor of the steering system does not exceed the reference range of the third response parameter of the steering system, then it is determined that there is no fault in the steering system.

[0085] In one example, if the fluctuation range of the operating parameters of the drive motor at the consistency detection point is 40%, while the fluctuation range of the operating parameters of the drive motor of the steering system is 30%, then it is determined that there is no fault in the steering system.

[0086] As described in this embodiment, for the steering system, the response parameter is further selected as the fluctuation amplitude of the operating parameters of the drive motor. When the steering system experiences jamming or increased friction, the operating parameters of the drive motor, such as current or torque, will show characteristic fluctuations or increase in amplitude. This parameter can effectively supplement or verify the judgment of the steering angle deviation, thereby revealing the mechanical health status of the steering system more comprehensively and directly, and further improving the coverage and reliability of fault detection.

[0087] In one embodiment of this application, after step S204, there is also a specific process for determining how to disable autonomous driving, as follows: S205: If the output shows that the performance status of the in-service equipment is faulty and the actual value of the response parameter has exceeded the preset maximum deviation value, then continue to determine whether the total driving mileage of the target vehicle in autonomous driving mode exceeds the preset autonomous driving life limit.

[0088] In the embodiments of this application, the preset maximum deviation value can be set according to requirements.

[0089] In one example, the steering angle of the vehicle's steering system in the curve detection section is 3°. Correspondingly, the left and right deviation values ​​of the steering angle of the steering system in the curve detection section are within the reference range of [2°, 4°]. If the left and right deviation value of the steering angle of the steering system is collected as 9°, a fault message is output for the steering system. The preset maximum deviation value is [-1°, 7°]. At this time, it can be determined that the actual value of the response parameter has exceeded the preset maximum deviation value.

[0090] In the embodiments of this application, the preset autonomous driving lifespan limit is set according to the relevant standards for autonomous driving systems.

[0091] It should be noted that the performance status of in-service equipment output by the control terminal (such as fault prompts and scrapping / disabling prompts) can be sent to the HAD controller (Highly Automated Driving Controller) to trigger the life detection unit of the HAD controller to continue to determine whether the total driving mileage of the target vehicle in autonomous driving mode exceeds the preset autonomous driving life limit.

[0092] S206: If the total mileage in autonomous driving mode exceeds the preset autonomous driving lifespan limit, a prompt indicating that the autonomous driving system is obsolete and disabled will be output.

[0093] S207: If the total mileage in the automatic driving mode has not exceeded the preset automatic driving life limit, a prompt indicating that there is a fault in the in-service equipment will be output.

[0094] In one example, the preset lifespan limit for autonomous driving can be set to 800,000 kilometers; if the total mileage of autonomous driving mode exceeds 800,000 kilometers, a prompt indicating that the autonomous driving system is scrapped and disabled will be output; if the total mileage of autonomous driving mode does not exceed 800,000 kilometers, a prompt indicating that the in-service equipment has a malfunction will be output.

[0095] As described in this embodiment, after determining that there is a fault in the in-service equipment, a joint decision is made by combining this with whether the total mileage of the vehicle in autonomous driving mode exceeds a preset limit, to ultimately determine whether the conditions for scrapping and disabling the autonomous driving system have been met. By adopting this mechanism to link the real-time performance consistency detection results with the lifespan dimension of the component's cumulative working time (mileage), the performance degradation caused by the natural exhaustion of the component's lifespan and occasional temporary faults are effectively distinguished. This avoids the risk of premature scrapping due to a single misjudgment or the continued use of truly end-of-life components, thereby improving the rationality and reliability of the vehicle's safety decisions.

[0096] It should be noted that the control unit can send warnings about steering system malfunctions and automatic driving system failures to the vehicle's display devices to alert the driver. These display devices can be the central control screen or a head-up display, among other devices.

[0097] Exemplary device Figure 7 A schematic diagram of the structure of an in-service equipment testing device for autonomous vehicles provided in this application embodiment. Figure 1 .like Figure 7 As shown, the in-service equipment testing device for autonomous vehicles is applied to the control end and includes: a setting module 701, an acquisition module 702, a data collection module 703, and an output module 704.

[0098] The setting module 701 is used to identify one or more consistency detection point road segments in the electronic data map that meet the requirements for stable driving in autonomous driving mode.

[0099] The acquisition module 702 is used to acquire the baseline range of response parameters of in-service equipment in automatic driving mode.

[0100] The acquisition module 703 is used to acquire the actual values ​​of the response parameters of the in-service equipment on the target vehicle when the target vehicle is driving in autonomous driving mode on the road segment at the consistency detection point.

[0101] The output module 704 is used to output the performance status of the in-service equipment based on the actual values ​​of the response parameters of the in-service equipment and the reference range of the response parameters.

[0102] In one or more embodiments of this application, determining one or more consistency detection point road segments in the electronic data map that meet the requirements for stable driving in autonomous driving mode includes: filtering out one or more characteristic road segments in the electronic data map where the vehicle is in a stable control state when driving in autonomous driving mode; and determining the one or more characteristic road segments as consistency detection point road segments.

[0103] In one or more embodiments of this application, the consistency detection point road segment includes a straight-ahead detection road segment and / or a curve detection road segment.

[0104] In one or more embodiments of this application, obtaining the baseline range of response parameters for in-service equipment in autonomous driving mode includes: collecting a first range of response parameters for the in-service equipment in autonomous driving mode before durability testing is performed on a designated test road segment; wherein the designated test road segment is the same as the consistency detection point road segment; collecting a second range of response parameters for the test vehicle with durability testing performed on the in-service equipment in autonomous driving mode on the designated test road segment; and determining the baseline range of response parameters for the in-service equipment at the consistency detection point road segment based on the first range of response parameters, the second range of response parameters, and environmental impact factors.

[0105] In one or more embodiments of this application, the consistency detection point section is a straight-ahead detection section, and the in-service equipment is a steering system. Accordingly, collecting the actual values ​​of the response parameters of the in-service equipment when the target vehicle is driving in autonomous driving mode on the consistency detection point section includes: collecting the left and right deviation values ​​of the steering system when the target vehicle is driving in autonomous driving mode on the straight-ahead detection section. Accordingly, outputting the performance status of the in-service equipment based on the actual values ​​of the response parameters and the reference range of the response parameters includes: if the left and right deviation value of the steering system exceeds the first reference range of the steering system's response parameters, then outputting a prompt indicating a steering system malfunction; wherein the first reference range of the response parameters is the reference range of the left and right deviation values ​​corresponding to the steering system on the straight-ahead detection section; if the deviation value of the steering system does not exceed the first reference range of the steering system's response parameters, then determining that the steering system is not malfunctioning.

[0106] In one or more embodiments of this application, the consistency detection point section is a curve detection section, and the in-service equipment is a steering system. Accordingly, collecting the actual values ​​of the response parameters of the in-service equipment when the target vehicle is driving in autonomous driving mode on the consistency detection point section includes: collecting the left and right deviation values ​​of the steering angle of the steering system when the target vehicle is driving in autonomous driving mode on the curve detection section. Accordingly, outputting the performance status of the in-service equipment based on the actual values ​​of the response parameters of the in-service equipment and the reference range of the response parameters includes: if the left and right deviation value of the steering angle of the steering system exceeds the second reference range of the steering system's response parameters, then outputting a prompt that the steering system has a fault; wherein the second reference range of the response parameters is the reference range of the left and right deviation values ​​of the steering angle corresponding to the steering system on the curve detection section; if the deviation value of the steering system does not exceed the second reference range of the steering system's response parameters, then it is determined that the steering system does not have a fault.

[0107] In one or more embodiments of this application, the in-service equipment is a steering system; correspondingly, the step of collecting the actual values ​​of the response parameters of the in-service equipment when the target vehicle is driving in autonomous driving mode on the consistency detection point road segment includes: collecting the fluctuation amplitude of the operating parameters of the drive motor of the steering system when the target vehicle is driving in autonomous driving mode on the consistency detection point road segment; correspondingly, the step of outputting the performance status of the in-service equipment based on the actual values ​​of the response parameters of the in-service equipment and the reference range of the response parameters includes: if the fluctuation amplitude of the operating parameters of the drive motor of the steering system exceeds the third reference range of the steering system, then outputting a prompt that the steering system has a fault; wherein the third reference range of the response parameters is the reference range of the fluctuation amplitude of the operating parameters of the drive motor of the steering system corresponding to the consistency detection point road segment; if the fluctuation amplitude of the operating parameters of the drive motor of the steering system does not exceed the third reference range of the steering system, then it is determined that the steering system has no fault.

[0108] In one or more embodiments of this application, the operating parameters of the drive motor of the steering system include: the current value of the drive motor and / or the torque value of the drive motor.

[0109] In one or more embodiments of this application, after outputting the performance status of the in-service equipment based on the actual value of the response parameters and the reference range of the response parameters, the method further includes: if the output performance status of the in-service equipment indicates a fault, and the actual value of the response parameters exceeds a preset maximum deviation value, then further determining whether the total mileage of the autonomous driving mode of the target vehicle exceeds a preset autonomous driving lifespan limit; if the total mileage of the autonomous driving mode exceeds the preset autonomous driving lifespan limit, then outputting a prompt indicating that the autonomous driving system is scrapped and disabled; if the total mileage of the autonomous driving mode does not exceed the preset autonomous driving lifespan limit, then outputting a prompt indicating that the in-service equipment has a fault.

[0110] The apparatus provided in this application embodiment can be used to execute the technical solutions of the above method embodiments. Its implementation principle and technical effect are similar, and will not be repeated here.

[0111] Exemplary device Figure 8 This is a schematic diagram of the hardware structure of the electronic device provided in an embodiment of this application. Figure 8 As shown, the electronic device of this embodiment includes a processor 801 and a memory 802.

[0112] The memory 802 stores computer execution instructions; the processor 801 executes the computer execution instructions stored in the memory to implement the various steps performed by the electronic device in the above embodiments. For details, please refer to the relevant descriptions in the foregoing method embodiments.

[0113] Alternatively, the memory 802 can be either standalone or integrated with the processor 801.

[0114] When the memory 802 is set up independently, the electronic device also includes a bus 803 for connecting the memory 802 and the processor 801.

[0115] Exemplary media and products This application also provides a computer storage medium storing computer execution instructions. When the processor executes the computer execution instructions, the above-described method for detecting in-service equipment for autonomous vehicles is implemented.

[0116] This application also provides a computer program product, including a computer program, which, when executed by a processor, implements the above-described method for detecting in-service equipment for autonomous vehicles.

[0117] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or modules, and may be electrical, mechanical, or other forms.

[0118] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to implement the solution of this embodiment according to actual needs.

[0119] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The unit composed of the above modules can be implemented in hardware or in the form of hardware plus software functional units.

[0120] The integrated modules described above, implemented as software functional modules, can be stored in a computer-readable storage medium. These software functional modules, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute some steps of the methods of the various embodiments of this application.

[0121] It should be understood that the aforementioned processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly manifested as execution by a hardware processor, or execution by a combination of hardware and software modules within the processor.

[0122] The memory may include high-speed RAM, and may also include non-volatile storage (NVM), such as at least one disk storage device, and may also be a USB flash drive, external hard drive, read-only memory, disk or optical disc, etc.

[0123] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0124] The aforementioned storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0125] An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Alternatively, the storage medium can be an integral part of the processor. Both the processor and the storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and storage medium can exist as discrete components in an electronic device or host device.

[0126] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0127] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A method for testing in-service equipment for autonomous vehicles, characterized in that, include: In the electronic data map, identify one or more road segments with consistency detection points that meet the requirements for stable driving in autonomous driving mode; Obtain the baseline range of response parameters for in-service equipment in autonomous driving mode; The actual values ​​of the response parameters of the in-service equipment on the target vehicle are collected when the target vehicle is driving in autonomous driving mode on the road segment at the consistency detection point. Based on the actual values ​​of the response parameters of the in-service equipment and the reference range of the response parameters, the performance status of the in-service equipment is output.

2. The method according to claim 1, characterized in that, The process of identifying one or more consistency detection point road segments in the electronic data map that meet the requirements for stable driving in autonomous driving mode includes: In the electronic data map, one or more characteristic road segments are selected where the vehicle is in a stable control state when driving in autonomous driving mode. The one or more characteristic road segments are identified as consistency detection point road segments.

3. The method according to claim 2, characterized in that, The consistency detection points include straight-ahead detection sections and / or curve detection sections.

4. The method according to claim 1, characterized in that, The acquisition of the baseline range of response parameters for in-service equipment in autonomous driving mode includes: On the designated test road section, the range of first response parameters of the in-service equipment of the test vehicle before the installation of durability equipment in autonomous driving mode was collected; the designated test road section was the same as the consistency detection point road section. On the designated test section, the range of second response parameters of the test vehicle equipped with durable in-service equipment in autonomous driving mode was collected. Based on the first response parameter range, the second response parameter range, and the environmental impact factor, the baseline range of response parameters corresponding to the in-service equipment at the consistency detection point road section is determined.

5. The method according to claim 1, characterized in that, The consistency detection point section is a straight-ahead detection section, and the in-service equipment is a steering system; Accordingly, the actual values ​​of the response parameters of the in-service equipment of the target vehicle when it is driving in autonomous driving mode at the consistency detection point section include: Collect the left and right deviation values ​​of the steering system of the target vehicle when it is driving in autonomous driving mode on the straight detection section; Accordingly, the step of outputting the performance status of the in-service equipment based on the actual values ​​of the response parameters of the in-service equipment and the reference range of the response parameters includes: If the left and right deviation values ​​of the steering system exceed the reference range of the first response parameter of the steering system, a fault indication is output; wherein the reference range of the first response parameter is the reference range of the left and right deviation values ​​of the steering system under the straight-ahead detection section; If the deviation value of the steering system does not exceed the reference range of the first response parameter of the steering system, then it is determined that the steering system is not faulty.

6. The method according to claim 1, characterized in that, The consistency detection point section is a curve detection section, and the in-service equipment is a steering system; Accordingly, the actual values ​​of the response parameters of the in-service equipment of the target vehicle when it is driving in autonomous driving mode at the consistency detection point section include: The left and right deviation values ​​of the steering angle of the steering system of the target vehicle are collected when the vehicle is driving in autonomous driving mode on the curve detection section. Accordingly, the step of outputting the performance status of the in-service equipment based on the actual values ​​of the response parameters of the in-service equipment and the reference range of the response parameters includes: If the left-right deviation of the steering angle of the steering system exceeds the reference range of the second response parameter of the steering system, a fault indication is output; wherein the reference range of the second response parameter is the reference range of the left-right deviation of the steering angle of the steering system under the curve detection section. If the deviation value of the steering system does not exceed the reference range of the second response parameter of the steering system, then it is determined that the steering system is not faulty.

7. The method according to any one of claims 1 to 6, characterized in that, The in-service equipment is a steering system; Accordingly, the actual values ​​of the response parameters of the in-service equipment of the target vehicle when it is driving in autonomous driving mode at the consistency detection point section include: The fluctuation amplitude of the operating parameters of the drive motor of the steering system is collected when the target vehicle is driving in autonomous driving mode on the road section of the consistency detection point. Accordingly, the step of outputting the performance status of the in-service equipment based on the actual values ​​of the response parameters of the in-service equipment and the reference range of the response parameters includes: If the fluctuation amplitude of the operating parameters of the drive motor of the steering system exceeds the reference range of the third response parameter of the steering system, a fault indication is output; wherein the reference range of the third response parameter is the reference range of the fluctuation amplitude of the operating parameters of the drive motor of the steering system under the consistency detection point road segment. If the fluctuation amplitude of the operating parameters of the drive motor of the steering system does not exceed the reference range of the third response parameter of the steering system, then it is determined that there is no fault in the steering system.

8. The method according to claim 7, characterized in that, The operating parameters of the drive motor of the steering system include: the current value and / or the torque value of the drive motor.

9. The method according to any one of claims 1 to 6, characterized in that, After outputting the performance status of the in-service equipment based on the actual values ​​of the response parameters and the reference range of the response parameters, the method further includes: If the output shows that the performance status of the in-service equipment is faulty, and the actual value of the response parameter has exceeded the preset maximum deviation value, then it is further determined whether the total driving mileage of the target vehicle in autonomous driving mode exceeds the preset autonomous driving life limit. If the total mileage of the autonomous driving mode exceeds the preset autonomous driving life limit, a prompt indicating that the autonomous driving system is scrapped and disabled will be output. If the total mileage of the autonomous driving mode does not exceed the preset autonomous driving life limit, a prompt indicating that there is a fault in the in-service equipment will be output.

10. An in-service equipment testing device for autonomous vehicles, characterized in that, include: The setting module is used to identify one or more road segments in the electronic data map that meet the requirements for stable driving in autonomous driving mode. The acquisition module is used to acquire the baseline range of response parameters of in-service equipment in automatic driving mode; The data acquisition module is used to collect the actual values ​​of the response parameters of the in-service equipment on the target vehicle when the target vehicle is driving in autonomous driving mode on the road segment at the consistency detection point. The output module is used to output the performance status of the in-service equipment based on the actual values ​​of the response parameters and the reference range of the response parameters.

11. An electronic device, characterized in that, include: At least one processor; And a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor to cause the at least one processor to perform the in-service equipment testing method for an autonomous vehicle according to any one of claims 1 to 9.

12. A computer storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the in-service equipment testing method for autonomous vehicles as described in any one of claims 1 to 9.

13. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the in-service equipment testing method for autonomous vehicles as described in any one of claims 1 to 9.

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