Vehicle unmanned detection method, device and equipment and storage medium

Abstract

This application discloses an unmanned vehicle inspection method, apparatus, equipment, and storage medium, relating to the field of intelligent inspection technology in automotive assembly. The method includes: in response to receiving an electrical inspection station allocation instruction, acquiring vehicle configuration information of the vehicle to be inspected; activating a sensor indicating the vehicle configuration information, the sensor being configured on the vehicle to be inspected; determining guidance sign information based on production line environment information within the factory area, wherein the production line environment information is collected by the sensor, and the guidance sign information is used to characterize guidance signs within the factory area; determining a planned path from the current position of the vehicle to be inspected to the target station specified in the electrical inspection station allocation instruction based on the guidance sign information; and controlling the vehicle to be inspected to travel along the planned path to the target station. This application can control the vehicle to travel along a predetermined trajectory to the target inspection line station and complete the inspection even when the intelligent driving system is not fully activated, without manual intervention.

Description

Technical Field

[0001] This application relates to the field of intelligent testing technology for automobile assembly, and in particular to unmanned vehicle testing methods, devices, equipment and storage media. Background Technology

[0002] On vehicle inspection lines, multiple vehicles typically operate simultaneously, each requiring precise parking in a designated area. Currently, manual driving is essential for inspection, resulting in high costs and low efficiency. Therefore, unmanned inspection is necessary. However, unmanned inspection theoretically requires autonomous driving capabilities. Newly produced vehicles often lack fully activated and tested intelligent driving functions, leading to inaccurate positioning and significant parking deviations—meaning the vehicles cannot autonomously drive to their designated inspection stations. Therefore, effectively inspecting vehicles on the production line has become a critical technical challenge. Summary of the Invention

[0003] The main purpose of this application is to provide a method, device, equipment and storage medium for unmanned vehicle detection, which aims to solve the technical problem of how to detect vehicles when the intelligent driving system is not fully activated.

[0004] To achieve the above objectives, this application proposes an unmanned vehicle detection method, which includes: In response to receiving the electrical inspection station allocation instruction, obtain the vehicle configuration information of the vehicle to be inspected; Activate the sensor indicated by the vehicle configuration information, which is configured on the vehicle to be tested; Guidance signage information is determined based on production line environment information within the factory area. The production line environment information is collected by sensors, and the guidance signage information is used to characterize guidance signs within the factory area. Based on the guidance signage information, determine the planned path from the current location of the vehicle to be inspected to the target workstation specified in the electrical inspection workstation assignment instruction; and Control the vehicle to be tested to travel to the target workstation according to the planned route.

[0005] This application, upon receiving an electrical inspection station allocation instruction, obtains the vehicle configuration information of the vehicle to be inspected and identifies guidance signs based on production line environment information. This enables precise perception of production line stations, minimizing inaccurate positioning caused by incomplete activation of the vehicle's intelligent driving system. Based on the guidance sign information, it dynamically generates a planned path to the target station, ensuring accurate vehicle navigation to the designated station and controlling the vehicle to drive to the target station for electrical inspection. This can replace manual driving to achieve unmanned inspection, allowing multiple vehicles on the inspection line to autonomously complete accurate inspections at the target inspection station without human intervention.

[0006] Optionally, the steps for obtaining the vehicle configuration information of the vehicle to be tested include: Obtain the flashing package by flashing the preset controller software, and obtain the vehicle identification number (VIN) of the vehicle to be tested; and In response to the location response request of the vehicle to be tested, if the location response request indicates that the vehicle is in place, the flashing software package is written to the vehicle to be tested based on the vehicle identification code to obtain the vehicle configuration information.

[0007] This application obtains a flashing package by flashing a preset controller software and the vehicle identification number (VIN) of the vehicle to be tested. Based on the VIN, the flashing package is written to the vehicle to be tested for testing, thereby updating the vehicle configuration and minimizing sensor configuration errors caused by vehicle configuration.

[0008] Optionally, activating the sensor indicated by the vehicle configuration information, wherein the sensor is configured on the vehicle to be detected, includes the following steps: In response to the calibration operation, the sensors configured on the vehicle to be tested, as indicated by the vehicle configuration information, are calibrated; and Once sensor calibration is complete, in response to a sensor activation command, the sensors of the vehicle to be tested are activated, including cameras, lidar, and millimeter-wave radar.

[0009] This application calibrates the sensors indicated by the vehicle configuration information in response to a calibration operation. Once the sensor calibration is complete, it activates the sensors of the vehicle to be tested in response to a sensor activation command. The sensors include cameras, lidar, and millimeter-wave radar. This approach aims to minimize perception failures caused by uncalibrated or unactivated sensors, ensuring that the sensor's perception accuracy meets the requirements of unmanned operation, improving adaptability, and reducing costs.

[0010] Optionally, the guidance signage information includes lane lines, QR codes, and signage; The steps for determining the planned path from the current location of the vehicle to be inspected to the target station specified in the electrical inspection station assignment instruction, based on the guidance sign information, include: The location of the vehicle to be inspected is determined based on lane lines, QR codes, and signs. Based on the target workstation specified in the electrical inspection workstation allocation instruction, determine the destination address of the vehicle to be inspected; and The path from the location of the vehicle to be detected to the destination address is used as the planned path.

[0011] This application utilizes lane lines, QR codes, and markers in the guidance signage information to accurately determine the location of the vehicle to be inspected on the production line. Combined with the destination address obtained from the electrical inspection station allocation instructions, a planned route can be dynamically generated.

[0012] Optionally, the step of using the path from the location of the vehicle to be detected to the destination address as the planned path includes: Determine the inspection line station for the vehicle to be inspected based on the destination address; The geomagnetic field at the testing line station is detected to obtain the test results; and If the test results indicate that there are available workstations, the path from the location of the vehicle to be tested to the workstation on the testing line will be used as the planned path.

[0013] This application determines whether a workstation is available by detecting the geomagnetic state of the target workstation. When the workstation is available, a planned path is generated. The status of the target workstation can be confirmed in real time, which can avoid vehicles driving to occupied workstations and causing path conflicts or unnecessary waiting as much as possible. This improves the effectiveness of vehicle scheduling within the inspection line and the overall system flow efficiency.

[0014] Optionally, the unmanned vehicle detection method also includes: When the vehicle to be inspected undergoes an electronic inspection, the vehicle's gear position information is obtained; and Based on the vehicle gear information, the pre-set process configuration parameters of the vehicle to be tested are used for electrical testing to obtain the electrical testing results at the target workstation.

[0015] This application determines the vehicle's status by acquiring the vehicle's gear position information after the vehicle arrives at the target workstation, and triggers an electrical inspection of the process configuration parameters based on the gear position information. It ensures that the vehicle is in a safe state before starting the inspection, thereby reducing the safety risks caused by accidental vehicle movement and automating and safely starting the electrical inspection process.

[0016] Optionally, the unmanned vehicle detection method also includes: In response to the completion signal of the inspection of the vehicle to be inspected, the electronic inspection results are uploaded; and Once the vehicle to be inspected has completed uploading, the system returns a response indicating receipt of the electrical inspection station allocation instruction and retrieves the vehicle configuration information of the vehicle to be inspected.

[0017] After the electrical inspection is completed, this application automatically uploads the inspection results and returns to the initial state to respond to new workstation assignment instructions. It supports the continuous flow of vehicles between multiple workstations without manual intervention, realizing the fully autonomous cycle of unmanned operation of the inspection line.

[0018] Furthermore, to achieve the above objectives, this application also proposes an unmanned vehicle detection device, which includes: The acquisition module is used to acquire the vehicle configuration information of the vehicle to be inspected in response to receiving the electrical inspection station allocation instruction; An activation module is used to activate the sensor that indicates the vehicle configuration information; the sensor is configured on the vehicle to be detected. The processing module is used to determine guidance sign information based on the production line environment information within the factory area. The production line environment information is collected by sensors, and the guidance sign information is used to characterize the guidance signs within the factory area. The planning module is used to determine the planned path from the current location of the vehicle to be inspected to the target station specified by the electrical inspection station assignment instruction, based on the guidance sign information. The execution module is used to control the vehicle to be tested to travel to the target workstation according to the planned path.

[0019] In addition, to achieve the above objectives, this application also proposes an unmanned vehicle detection device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the unmanned vehicle detection method described above.

[0020] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the unmanned vehicle detection method described above. Attached Figure Description

[0021] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0022] To more clearly illustrate the technical solutions in some embodiments of this application or in the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a first flowchart illustrating some embodiments of the unmanned vehicle detection method of this application; Figure 2 This is a schematic diagram of the inspection line guidance signs for the unmanned vehicle inspection method of this application; Figure 3 This is a diagram of the scheduling system architecture for the unmanned vehicle detection method proposed in this application. Figure 4 This is a workstation layout diagram of the unmanned vehicle testing method for this application; Figure 5 This is a schematic diagram of the unmanned control system architecture for the unmanned vehicle testing line in this application. Figure 6 This is a flowchart of the unmanned control system for the vehicle unmanned testing line in this application. Figure 7A second flowchart is provided for some embodiments of the unmanned vehicle detection method of this application; Figure 8 A third flowchart is provided for some embodiments of the unmanned vehicle detection method of this application; Figure 9 This is a schematic diagram of the module structure of the unmanned vehicle detection device according to some embodiments of this application; Figure 10 This is a schematic diagram of the equipment structure of the hardware operating environment involved in the unmanned vehicle detection method in some embodiments of this application.

[0024] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0025] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0026] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0027] In some embodiments, for ease of description, the vehicle is used as the subject of the description.

[0028] Because the intelligent driving function of newly produced vehicles has not been activated and tested in the relevant technologies, the function is incomplete and cannot be used normally, resulting in inaccurate positioning and significant parking deviation, that is, the vehicle cannot drive autonomously to the designated work station to participate in the testing.

[0029] To enable vehicles to travel along a predetermined trajectory to the target inspection station and complete inspection even when the intelligent driving system is not fully activated, this application provides an unmanned vehicle inspection method in some embodiments. This method, in response to receiving an electrical inspection station allocation instruction, obtains the vehicle configuration information of the vehicle to be inspected and identifies guidance signs based on production line environment information. This achieves accurate perception of the production line station, minimizing inaccurate positioning caused by the vehicle's incomplete intelligent driving system activation. Based on the guidance sign information, a planned path to the target station is dynamically generated, ensuring accurate navigation of the vehicle to the designated station and controlling the vehicle to travel to the target station for electrical inspection. This method can replace manual driving to achieve unmanned inspection, allowing multiple vehicles on the inspection line to autonomously complete accurate inspections at the target inspection station without human intervention.

[0030] Based on this, some embodiments of this application provide a method for unmanned vehicle detection, referring to... Figure 1 , Figure 1 This is a first flowchart illustrating some embodiments of the unmanned vehicle detection method of this application.

[0031] In some embodiments, the unmanned vehicle detection method includes steps S10 to S50: Step S10: In response to receiving the electrical inspection station allocation instruction, obtain the vehicle configuration information of the vehicle to be inspected; Understandably, in unmanned scenarios on the final assembly and testing line, since the vehicles to be tested are those that have just finished final assembly and have not yet had their intelligent driving functions and sensors activated and calibrated, and there may be various different vehicle models circulating on the testing line, each with completely different testing process parameters, it is necessary to specifically distinguish the vehicle configuration information of different vehicles to be tested.

[0032] In some examples, in response to receiving an electrical inspection station allocation instruction—generated by the production line scheduling system based on the vehicle's current status and available production line slots—instructing the vehicle to proceed to a specific station for electrical inspection, the target station's number or address can be obtained. At this point, the vehicle obtains its Vehicle Identification Number (VIN) and, based on this VIN, requests and determines its vehicle configuration information from the production operations layer (such as the MOM system). For example, an OBD diagnostic tool connects to the vehicle to unlock its driving capabilities; downloads and reprograms all ECU controller software (engine, transmission, ABS, ESP, BMS, VCU, etc.); configures the vehicle using the reprogramming software package according to the VIN to obtain vehicle configuration information; anti-theft system matching and key matching are performed to deactivate the transport mode; high-voltage insulation testing and high-voltage power-on verification are performed on new energy vehicles, thus enabling the vehicle to drive. This allows for vehicle control even when intelligent driving functions are incomplete, compared to existing vehicle driving methods. For example, in traditional manual driving or high-level autonomous driving, this application essentially activates the vehicle's basic driving functions from the underlying electronic and electrical architecture. Existing complete intelligent driving solutions usually require that all ECU software has been finally calibrated, functional safety verified, sensor calibrated, and autonomous driving software activated before the vehicle leaves the factory. The vehicle must be in normal driving mode before it can be taken over by the intelligent driving system. However, new cars that come off the assembly line are often in transport mode, anti-theft devices are not matched, ECU software is not fully flashed, and even some controllers are not configured. At this time, even if hardware such as cameras and radar are installed, the intelligent driving system cannot work, and the vehicle's basic starting, gear shifting, steering assist, and braking response are limited.

[0033] In some examples, step S10 may include steps A11 to A12: Step A11: Obtain the flashing package by flashing the preset controller software and obtain the vehicle identification number of the vehicle to be tested; As is understandable, the Vehicle Identification Number (VIN) is a unique identifier for a vehicle, containing information such as the manufacturer, model, year, and engine code. Before entering the inspection line, the VIN is automatically uploaded to the dispatch system via a TBOX to identify the specific vehicle. Based on the VIN, the dispatch system retrieves the matching flashing software package from the production and operation system and downloads and flashes the software for all ECU controllers (engine, transmission, ABS, ESP, BMS, VCU, etc.) for configuration.

[0034] Step A12: Respond to the location response request of the vehicle to be tested. If the location response request indicates that the vehicle is in place, write the flashing software package to the vehicle to be tested according to the vehicle identification code to obtain the vehicle configuration information.

[0035] Understandably, the location response request is a signal actively sent by the vehicle to be inspected at the beginning of the inspection line to the dispatch system. It is used to inform the dispatch system that the vehicle is in position and ready to start the unmanned flow and inspection process. This allows the system to confirm the positions of different vehicles waiting to enter the inspection line, thus achieving automated inspection. The vehicle configuration information is the specific configuration parameters of the corresponding vehicle identified by the vehicle identification code after the flashing software package is written to the vehicle and the inspection is completed. This ensures that different models of vehicles can complete automated inspection according to their corresponding configuration requirements.

[0036] Step S20: Activate the sensor indicated by the vehicle configuration information, the sensor being configured on the vehicle to be detected; It is understandable that when a vehicle rolls off the assembly line, all the sensors it carries (such as cameras, lidar, millimeter-wave radar, etc.) are in an inactive or uncalibrated factory state and cannot function properly. In order to achieve unmanned operation of the vehicle within the testing line, it is necessary to rely on the vehicle's own intelligent driving capabilities to enable the vehicle to autonomously perceive the environment, recognize guidance signs, and complete path planning. However, different models and configurations have different types, numbers, and installation locations of sensors. If all sensors are activated blindly in a uniform manner, it may cause system abnormalities or detection failures due to the activation of the wrong sensors. Therefore, it is necessary to accurately identify and activate the required sensors based on the vehicle configuration information.

[0037] In some examples, after final assembly, personnel are manually transferred to the ADAS calibration room for calibration of cameras, LiDAR, and millimeter-wave radar. The ADAS calibration room is a dedicated workstation located at the beginning of the inspection line, used to accurately calibrate cameras, LiDAR, and millimeter-wave radar, effectively identifying lane lines, QR codes, and markers. These markers can be inspection line equipment or geomagnetic sensors, ensuring that the sensor combination's perception accuracy meets the requirements of unmanned operation. For example, after obtaining vehicle configuration information, the sensors indicated by the configuration information can be activated. These sensors are configured on the vehicle to be inspected. The sensors on the vehicle to be inspected are multiple sensors that need to be activated, such as cameras, LiDAR, and millimeter-wave radar. Activation at this point brings the sensors from dormant or standby mode into a working state where they can normally collect data and output results. This gives the vehicle functions similar to intelligent driving, allowing for on-demand activation of different vehicle models and configurations. The calibrated target sensors can accurately identify lane lines, QR codes, static / dynamic markers, etc., facilitating the vehicle's autonomous positioning within the inspection line.

[0038] It is understandable that a complete and mature intelligent driving system does not exist in the automotive final assembly line scenario. Instead, various sensors on the vehicle, such as cameras, LiDAR, and millimeter-wave radar, are activated on demand, switching them from dormant or standby states to a working state capable of collecting data and outputting results. This gives the vehicle autonomous perception, positioning, and driving capabilities similar to intelligent driving within the inspection line. Compared to a complete intelligent driving system, this application addresses a closed, fixed, low-speed, and controllable production line environment. Therefore, the functionality can be significantly simplified. Specifically, it does not require high-precision map modules or high-precision combined positioning modules; positioning is achieved simply by recognizing guide signs, and the vehicle only needs to follow the guide signs... The guidance sign performs simple path tracking and fixed-point parking, without requiring real-time path searching on the vehicle side. It does not require the use of functionally redundant sensors, controllers, or actuators. It only needs to have sufficient recognition and parking accuracy within the inspection line scenario. The omission of these modules can greatly save costs. The sensors themselves also do not need to be added or upgraded. They can simply utilize the vehicle's original configuration and be activated as needed. A static calibration can be completed in the production line ADAS calibration room to accurately and stably identify lane lines, QR codes, and static / dynamic signs, ensuring the vehicle's autonomous positioning and fixed-point parking within the inspection line. Thus, with extremely low complexity and deployment cost, unmanned flow between multiple vehicle models, configurations, and workstations can be achieved.

[0039] In some examples, step S11 may include steps B11 to B12: Step B11, in response to the calibration operation, calibrate the sensors configured on the vehicle to be tested as indicated by the vehicle configuration information; Understandably, the purpose of calibration is to correct physical deviations that occur in the sensor during manufacturing or installation, such as camera focal length and installation angle errors, and pitch and yaw angle deviations between lidar and millimeter-wave radar, so as to ensure that the data output by the sensor can accurately represent the external environment.

[0040] Step B12: After sensor calibration is completed, in response to a sensor activation command, activate the sensors of the vehicle to be tested, including a camera, lidar, and millimeter-wave radar.

[0041] Understandably, sensor activation commands are control signals issued after a vehicle meets safety readiness conditions. For example, after a vehicle to be inspected has completed calibration, the physical latch on the hood must be opened, personnel must exit the vehicle, and the doors must be closed to confirm that the vehicle is in a safe state. Only then can the dispatch system or vehicle controller issue sensor activation commands to switch sensors such as cameras, lidar, and millimeter-wave radar from standby to active status, enabling the vehicle to perceive its surroundings and thus meet the needs of unmanned operation and inspection.

[0042] Step S30: Determine guidance sign information based on the production line environment information within the factory area. The production line environment information is collected by sensors, and the guidance sign information is used to characterize the guidance signs within the factory area. Understandably, it is necessary to accurately identify the guidance signs on the production line in order to avoid path deviations or parking errors caused by inaccurate positioning.

[0043] In some examples, production line environmental information can be collected from the sensors of the activated vehicle under inspection. This information is real-time data collected on the inspection line environment, including perception information such as ground markings, workstation layout, distribution of markers, and the positions of other vehicles. Based on this production line environmental information, guidance signage information within the factory area can be identified. This guidance signage information consists of pre-placed positioning markers on the production line floor or at fixed locations, such as lane lines, QR codes, and markers, used to provide absolute or relative positional references for vehicles. This enables precise perception of production line workstations and driving lanes, improving the reliability of unmanned production line inspection. Figure 2 As shown, Figure 2 This is a schematic diagram of the inspection line guidance signs for the unmanned vehicle inspection method of this application, wherein, Figure 2 The 101 in the text is a guide marker. Figure 2 102 in the text is the detection line. Figure 2 103 is the target workstation. When the vehicle is moving without human intervention, it needs to use the guidance signs on the inspection line to achieve precise horizontal and vertical autonomous driving so that the car can stop precisely at the target workstation. At this time, the guidance sign information can be dynamically updated during the vehicle's movement, supporting the vehicle to continuously read multiple workstation signs and achieve seamless navigation throughout the entire process within the inspection line.

[0044] Step S40: Based on the guidance sign information, determine the planned path from the current location of the vehicle to be inspected to the target station specified by the electrical inspection station allocation instruction. It is understandable that different workstations have different spatial coordinates and orientation requirements, and the guidance signage information may be discontinuous or have multiple branch paths. Therefore, it is necessary to clarify the specific global or local movement trajectory from the current position to the pre-assigned target detection line workstation.

[0045] In some examples, the electrical inspection station allocation instructions can be obtained from the scheduling system, such as... Figure 3 As shown, Figure 3 This is a diagram of the scheduling system architecture for the unmanned vehicle inspection method of this application. The scheduling system may include a MOM system, vehicle navigation, inspection line station geomagnetic sensors, and anomaly information push. Specifically, the MOM system: The scheduling system obtains vehicle configuration information from the MOM system, performs self-checks based on the configuration information, and determines whether the vehicle meets the flow conditions. The vehicle navigation: The scheduling system sends the destination address to the vehicle navigation system, providing data support for navigation path planning. The inspection line station geomagnetic sensors: Report the availability of inspection line stations to the scheduling system. The anomaly information push: Pushes information about abnormal vehicle statuses. The scheduling system can combine global information to make optimal decisions. After the vehicle completes the calibration and activation of the target sensor combination, it possesses perception capabilities, i.e., autonomous driving functionality. At this point, the scheduling system can determine the planned path from the current location of the vehicle to be inspected to the target workstation specified in the electrical inspection workstation allocation instruction. Simultaneously, the scheduling system also possesses risk identification capabilities, pushing various abnormal information to relevant personnel throughout the process. Therefore, the scheduling system can obtain the pre-assigned inspection line workstation for the vehicle based on the workstation vacancy status specified in the electrical inspection workstation allocation instruction, and issue the destination address to the vehicle. The target workstation specified in the electrical inspection workstation allocation instruction is... Figure 2 The target workstation corresponding to the QR code is a designated workstation for the vehicle to undergo electrical inspection, pre-determined and assigned by the production line scheduling system before the vehicle performs its unmanned inspection task. This workstation can be any type of inspection line workstation, such as... Figure 4 As shown, Figure 4This is a layout diagram of the testing line workstations for the unmanned vehicle testing method of this application. The testing line workstations include a final assembly line workstation, a calibration workstation, a bumpy road workstation, an air suspension workstation, a four-wheel headlight workstation, a sideslip workstation, a hub rotation workstation, a braking workstation, a charging workstation, and a testing workstation. The vehicle navigation system can determine the destination address of the vehicle to be tested based on the lane lines, QR codes, and signs in the guidance sign information, and the target workstation specified by the electronic testing workstation allocation instruction. This allows for the automatic generation of a path, resulting in a planned path. The planned path is the expected driving trajectory from the vehicle's current location to the target testing line workstation. The vehicle then travels along the planned path to its destination and stops, supporting unmanned continuous operation of multiple workstations within the testing line.

[0046] In some examples, guidance signage includes lane lines, QR codes, and signs. Step S40 may include steps C11 to C13: Step C11: Determine the location of the vehicle to be inspected based on lane lines, QR codes, and markers; Understandably, lane lines provide a reference benchmark for the vehicle's lateral travel trajectory. By recognizing the direction and curvature of the lane lines, the vehicle can determine its lateral offset relative to the lane. The QR code embeds absolute position information such as workstation number and parking coordinates. The vehicle can obtain its precise position in the production line coordinate system by recognizing and decoding the QR code through the camera. The markers are used to help the vehicle confirm its relative position to the surrounding environment.

[0047] Step C12: Determine the destination address of the vehicle to be inspected according to the target station specified in the electrical inspection station allocation instruction; Understandably, the destination address of the vehicle to be inspected is the location of the target workstation in the global coordinate system or local map of the production line. This allows the vehicle to obtain an accurate path planning endpoint even without intelligent driving functions, and dynamically generate a driving path from the current location to the target workstation, thereby improving the accuracy of unmanned inspection.

[0048] Step C13: The path from the location of the vehicle to be detected to the destination address is used as the planned path.

[0049] Understandably, planning routes can ensure that vehicles can safely, efficiently, and orderly complete the transfer between multiple workstations under autonomous driving conditions, reducing the risk of stoppages, detours, or accidental stops caused by workstation identification errors or path conflicts.

[0050] In some examples, step C13 may include steps D11 to D13: Step D11: Determine the inspection line station for the vehicle to be inspected based on the destination address; Understandably, the testing line stations include the final assembly line station, calibration station, bumpy road station, air suspension station, four-wheel headlight station, sideslip station, hub rotation station, braking station, charging station, and inspection station. The final assembly line station is the first inspection node after the vehicle completes all assembly processes on the final assembly line and leaves the assembly line. Here, the vehicle finishes the assembly process and enters the testing line. The calibration station is used to precisely calibrate various sensors on the vehicle, adjusting the sensor's installation angle and baseline parameters using dedicated calibration equipment. The bumpy road station simulates the vehicle's driving environment under harsh road conditions, testing the vehicle's suspension system, chassis fasteners, body torsional stiffness, and abnormal noises by laying out bumpy road surfaces of specific shapes (such as washboard roads, twisted roads, and cobblestone roads). The air suspension station, or air suspension inspection station, is used to ensure that the air springs can automatically adjust the vehicle height according to load or driving mode, providing good ride comfort. The four-wheel headlight station is responsible for testing and calibrating the illumination angle, brightness, and beam distribution of the vehicle's headlights. A headlight tester is used to adjust the height and position of the left and right lights, while also checking the functionality of high / low beam switching and automatic headlights to ensure safe nighttime driving. The sideslip station measures the lateral slip of the front or rear wheels when the vehicle is traveling straight using a sideslip test bench, preventing deviations in positioning that could lead to skidding, abnormal tire wear, or decreased driving stability. The drum test bench station simulates actual road driving conditions on the drums. The braking station is equipped with a drum-type or flat-plate braking force test bench, applying different braking intensities to test the braking force, balance, and braking efficiency of the four wheels, ensuring that braking distance and stability meet safety standards as much as possible. The charging station ensures charging safety and efficiency. The testing station is the final station, incorporating multiple rapid testing items and serving as a quality control confirmation point before the vehicle leaves the factory.

[0051] Step D12: Detect the geomagnetic field at the testing line station and obtain the test results; Understandably, the detection results serve as the basis for determining whether a workstation on the testing line is occupied. This is achieved by detecting changes in the intensity or distribution of the geomagnetic field within the workstation area. Since each vehicle chassis contains a large number of ferromagnetic metal components, when a vehicle enters or stops at a workstation, it causes disturbances in the local geomagnetic field, resulting in changes in the magnetic field intensity, direction, or gradient. Therefore, by pre-positioning geomagnetic sensors on the ground or side of the workstation, the geomagnetic data of that workstation can be collected in real time and compared with a baseline geomagnetic field model in a vehicle-free state. This allows for the determination of whether a vehicle is currently occupying the workstation. If the detected geomagnetic anomaly exceeds a preset threshold, the workstation is determined to be occupied. Conversely, if the geomagnetic data returns to the baseline value, the workstation is determined to be vacant. This method requires no visual identification, is unaffected by lighting conditions, has low installation costs, and offers fast response, making it suitable for real-time workstation status monitoring in production line environments.

[0052] Step D13: If the detection result indicates that there is an available workstation, the path from the location of the vehicle to be inspected to the workstation on the inspection line is taken as the planned path.

[0053] Understandably, a vehicle will only consider a workstation as a safe destination if the geomagnetic detection results of the testing line clearly show that the workstation is vacant. The vehicle will then determine the route from its current location to the entrance of the workstation or the designated parking point as the planned route. If the workstation is occupied, the vehicle will continue to wait or change its destination address, in order to avoid vehicles blindly driving into occupied workstations and causing collisions or production line blockages, thereby improving the efficiency of production line flow.

[0054] Step S50: Control the vehicle to be inspected to travel to the target workstation according to the planned path.

[0055] Understandably, after the planned path is generated, the vehicle needs to have the ability to execute actions, namely, to actually control steering, acceleration, braking, etc., so that the vehicle can autonomously drive along the planned path to the target workstation and stop precisely. At the same time, due to the automation requirements of the inspection line equipment (such as collaborative robots replacing manual plugging and unplugging of OBD interfaces), the vehicle also needs to interact with the inspection line equipment after arrival to start the vehicle-machine electrical inspection program, so as to achieve unmanned operation of the entire process.

[0056] In some examples, when the vehicle to be inspected arrives at the target workstation, it stops. Once the ground markings are recognized by the camera, the vehicle-mounted electrical inspection system is triggered to read the vehicle's current gear information. When the vehicle's gear information is read as N gear, the vehicle automatically sends a test completion signal to the inspection line equipment and begins to perform the vehicle-mounted electrical inspection. During the inspection, the vehicle interacts with the inspection line equipment (such as power supply, load, and signal generator) to exchange data. After the inspection is completed, the electrical inspection results are uploaded to the server and MOM system via TBOX, completing the unmanned inspection process. Afterward, the scheduling system can continue to issue new destination addresses based on the idle status of the next workstation, realizing continuous unmanned operation across multiple workstations.

[0057] In some embodiments, an unmanned vehicle inspection method is proposed, which, in response to receiving an electrical inspection station allocation instruction, acquires vehicle configuration information of the vehicle to be inspected; activates a sensor indicating the vehicle configuration information, the sensor being configured on the vehicle to be inspected; determines guidance sign information based on production line environment information within the factory area, wherein the production line environment information is collected by the sensor, and the guidance sign information is used to characterize guidance signs within the factory area; determines a planned path from the current position of the vehicle to be inspected to the target station specified by the electrical inspection station allocation instruction based on the guidance sign information; and controls the vehicle to be inspected to travel to the target station according to the planned path. This application, upon receiving an electrical inspection station allocation instruction, obtains the vehicle configuration information of the vehicle to be inspected and identifies guidance signs based on production line environment information. This enables precise perception of production line stations, minimizing inaccurate positioning caused by incomplete activation of the vehicle's intelligent driving system. Based on the guidance sign information, it dynamically generates a planned path to the target station, ensuring accurate vehicle navigation to the designated station and controlling the vehicle to drive to the target station for electrical inspection. This can replace manual driving to achieve unmanned inspection, allowing multiple vehicles on the inspection line to autonomously complete accurate inspections at the target inspection station without human intervention.

[0058] It is understandable that, such as Figure 5 As shown, Figure 5 This is a schematic diagram of the unmanned control system architecture for the unmanned vehicle inspection method of this application. The unmanned control system architecture is divided into three layers: the physical equipment layer, the control and monitoring layer, and the production and operation layer. Each layer operates independently and works collaboratively. In terms of data interaction, a dual transmission mode can be adopted, with industrial Ethernet as the primary transmission and 5G wireless transmission as a secondary transmission, to strengthen the communication facilities in the inspection line area and provide a powerful communication environment. The physical equipment layer is located at the bottom and is the physical carrier for inspection execution, including vehicles, inspection line equipment, and geomagnetic modules. It can complete the actual driving of vehicles, workstation identification, inspection execution, and status feedback. The control and monitoring layer is located in the middle and includes the TSP (Remote Information Service) backend, the inspection line server, and the scheduling system. It can realize real-time data communication and monitoring between vehicles, equipment, and the cloud. The production and operation layer is located at the top and includes the MOM (Manufacturing Operations Management System) to realize the global scheduling, traceability, and production scheduling optimization of production line tasks.

[0059] It is understandable that, such as Figure 6 As shown, Figure 6The flowchart of the unmanned control system for the vehicle unmanned inspection line in this application illustrates that the vehicle can be triggered by closing the door. The vehicle uploads its current location information to the control and monitoring layer via the TBOX. After the MOM system in the production and operation layer obtains the results of the previous workstation process, the scheduling system sends the target address based on the workstation's availability. The vehicle-mounted electrical inspection module in the physical equipment layer automatically generates a path and drives the vehicle to the destination. The vehicle obtains its current gear information by identifying multiple ground magnetic modules. Simultaneously, the inspection line server uploads the availability status of the next workstation. After obtaining the vehicle model configuration, the vehicle-mounted electrical inspection module sends a ready signal and begins executing the electrical inspection program. Upon completion, the electrical inspection results are judged in real time and uploaded to the MOM system. At the same time, a "test completed" signal is sent to the inspection line server, and the scheduling system completes the vehicle handover. This enables fully unmanned closed-loop operation from task triggering, path navigation, workstation identification, inspection execution to result reporting.

[0060] In some embodiments, refer to Figure 7 , Figure 7 The second flowchart provided for some embodiments of the unmanned vehicle detection method of this application also includes steps S60-S70: Step S60: Obtain vehicle gear information while the vehicle to be tested is undergoing an electrical inspection; Understandably, normal electrical inspection methods rely on manual operation. This requires manually inserting the communication harness into the vehicle's OBD port, scanning the VIN code, waiting for the device to acquire the vehicle configuration, and then manually starting the device. After the inspection, the harness must be manually unplugged and the device returned to its original position. This process is inefficient, error-prone, and labor-intensive, failing to meet the needs of unmanned inspection lines. Therefore, it is necessary to eliminate manual plugging and unplugging of the OBD interface and simultaneously achieve automatic device start / stop and data interaction. This necessitates automating the inspection line equipment. For the inspection line equipment, the workstations requiring the addition of collaborative robots to replace manual inspection include the four-wheel headlight and charging inspection workstations. The four-wheel headlight workstation requires six collaborative robots (one hood opening robot, one steering wheel leveling robot, two headlight adjustment robots, and two four-wheel parameter adjustment robots) to automatically place the steering wheel leveling robot, automatically adjust the headlights, and automatically adjust the four-wheel parameters. The charging inspection workstation requires one collaborative robot to automatically plug and unplug the charging gun. Since the vehicle already possesses onboard computing capabilities after completing the calibration and activation of the target sensor combination, fully automated electrical inspection without human intervention can be achieved directly using onboard resources.

[0061] In some examples, the diagnostic software module Client can be embedded in the vehicle's onboard computing unit to achieve vehicle-mounted diagnostics. For instance, since the vehicle has already undergone electrical testing at the final assembly line's electrical testing station before entering the testing line, the pre-diagnostic vehicle-mounted electrical testing can automatically obtain the Vehicle Identification Number (VIN) and transmit it to the testing line server via the TBOX. Simultaneously, the MOM system has already pushed vehicle configuration information to the testing line server in advance. When the testing line server receives the VIN, it can transmit the vehicle configuration information to the equipment. The vehicle also sends relevant process parameters to the equipment via the TBOX. Subsequent testing line parameters only need to be updated in the vehicle-mounted electrical testing script. Once the guide signs at the target testing line station are all recognized by the camera, i.e., when the vehicle to be tested undergoes electrical testing, the vehicle-mounted electrical testing is triggered to read the vehicle's information. The system automatically starts the vehicle's electronic diagnostic program when the vehicle's current gear information is read as "N" (Neutral), indicating that the vehicle has received a signal that the equipment is in place. The vehicle's gear information refers to the current gear position of the transmission, such as P, R, N, D, or neutral, drive, reverse, etc., which can be directly read to ensure the vehicle is in a safe and correct gear. For example, it requires the vehicle to be in P or N before testing to prevent accidental movement. This is used to automate the perception and verification of gear position. The diagnostic software module Client is a diagnostic software module running on the vehicle's onboard computing unit, responsible for executing the electronic diagnostic script, communicating with the vehicle's ECU, interacting with the testing line server, and managing test data. TBOX is an onboard remote communication terminal (Telematics...). The TBOX is responsible for cellular network communication (4G / 5G) between the vehicle and the cloud / server, enabling transparent data transmission. The MOM system is the Manufacturing Operations Management system, which is responsible for pushing vehicle configuration and process parameters to the inspection line server and receiving inspection results for traceability. The vehicle electrical inspection script is an automated inspection script customized for each vehicle model, stored in the diagnostic client. Parameters can be updated remotely through the TBOX without modifying the hardware, enabling unmanned inspection.

[0062] Step S70: Perform electrical testing on the process configuration parameters preset on the vehicle to be tested based on the vehicle gear information to obtain the electrical testing results at the target workstation.

[0063] It is understandable that during the electrical inspection of the vehicle under test, data can be exchanged with the testing line equipment, such as real-time reading of equipment status and exchange of measurement data. After the inspection is completed, the electrical inspection result can be obtained. The electrical inspection result is the test result obtained by electrical inspection of the process configuration parameters preset on the vehicle under test.

[0064] In some examples, after the inspection is completed, the electrical inspection result indicates that the workstation has been inspected. Subsequently, the vehicle sends the corresponding inspection signal to the scheduling system and uploads the electrical inspection result to the server and the MOM system. At this time, the human-machine interface (HMI) can display the electrical inspection result on the in-vehicle infotainment screen for operators to view the progress and results. Afterward, the scheduling system can continue to request from the MOM system and issue the next destination address to the vehicle according to the availability of the next workstation, controlling the vehicle to continue to complete the inspection. This achieves continuous flow of vehicles without human intervention, minimizing production line congestion or idling, and improving the overall efficiency and intelligence level of the production line.

[0065] In some embodiments, an unmanned vehicle inspection method is proposed, which acquires the vehicle's gear position information when the vehicle to be inspected undergoes electrical inspection; and performs electrical inspection on the process configuration parameters preset on the vehicle to be inspected based on the vehicle's gear position information to obtain the electrical inspection result at the target workstation. This application determines the vehicle's status by acquiring the vehicle's gear position information after the vehicle arrives at the target workstation, and triggers electrical inspection of the process configuration parameters based on the gear position information. This ensures that inspection only begins when the vehicle is in a safe state, reducing safety risks caused by unexpected vehicle movement and achieving automation and safe startup of the electrical inspection process.

[0066] In some embodiments, refer to Figure 8 , Figure 8 The third flowchart provided for some embodiments of the unmanned vehicle detection method of this application also includes steps S80-S90: Step S80: In response to the inspection completion signal of the vehicle to be inspected, the electronic inspection result is uploaded; In some examples, the test completion signal is an automatic confirmation signal generated by the test station controller or on-board diagnostic system after the vehicle has completed all preset test items. At this time, all test data collected during the electrical test can be uploaded to the production management system. After the upload is completed, the vehicle or test system will receive a confirmation receipt to ensure data integrity as much as possible.

[0067] Step S90: If the vehicle to be inspected has completed uploading, return to the step of receiving the electrical inspection station allocation instruction and obtaining the vehicle configuration information of the vehicle to be inspected.

[0068] In some examples, once the electrical inspection results of the vehicle to be inspected are successfully uploaded to the management system and confirmed, the inspection task for the vehicle to be inspected ends. At this time, the control logic of the system or the vehicle will automatically jump back to the initial state and wait for the next electrical inspection station allocation instruction to re-execute the entire inspection process, realizing the continuous flow of unmanned inspection on the production line. For example, when a vehicle completes inspection and leaves the station, the system can release the same station or subsequent station to the next vehicle to be inspected, forming a closed-loop automated operation scheduling.

[0069] In some embodiments, an unmanned vehicle inspection method is proposed, which uploads the electrical inspection results in response to a completion signal of the vehicle to be inspected; and returns to the step of obtaining the vehicle configuration information of the vehicle to be inspected in response to receiving an electrical inspection station allocation instruction after the upload of the results. This application automatically uploads the electrical inspection results after the electrical inspection is completed and returns to the initial state to respond to new station allocation instructions, supporting continuous vehicle flow between multiple stations without manual intervention, and realizing a fully autonomous cycle of unmanned operation on the inspection line.

[0070] This application also provides an unmanned vehicle detection device; please refer to [reference needed]. Figure 9 The unmanned vehicle detection device includes: The acquisition module 10 is used to acquire the vehicle configuration information of the vehicle to be inspected in response to receiving the electrical inspection station allocation instruction; Activation module 20 is used to activate the sensor indicating vehicle configuration information, the sensor being configured on the vehicle to be detected; Processing module 30 is used to determine guidance sign information based on production line environment information within the factory area, wherein the production line environment information is collected by sensors, and the guidance sign information is used to characterize guidance signs within the factory area; The planning module 40 is used to determine the planned path from the current position of the vehicle to be inspected to the target station specified by the electrical inspection station assignment instruction based on the guidance sign information. The execution module 50 is used to control the vehicle to be tested to travel to the target workstation according to the planned path.

[0071] The acquisition module 10 is also used to acquire the flashing package by flashing the preset controller software and to acquire the vehicle identification code of the vehicle to be detected. In response to the location response request of the vehicle to be tested, if the location response request indicates that the vehicle is in place, the flashing software package is written to the vehicle to be tested based on the vehicle identification code to obtain the vehicle configuration information.

[0072] The processing module 30 is used to calibrate the sensors configured on the vehicle to be tested as indicated by the vehicle configuration information in response to the calibration operation; Once sensor calibration is complete, in response to a sensor activation command, the sensors of the vehicle to be tested are activated, including cameras, lidar, and millimeter-wave radar.

[0073] The processing module 30 is used to determine the position of the vehicle to be detected based on lane lines and QR code markers; Determine the destination address of the vehicle to be inspected based on the target station specified in the electrical inspection station allocation instruction; The path from the location of the vehicle to be detected to the destination address is used as the planned path.

[0074] Processing module 30 is used to determine the inspection line station of the vehicle to be inspected based on the destination address; The geomagnetic field at each testing station is detected to obtain the test results; If the test results indicate that there are available workstations, the path from the location of the vehicle to be tested to the workstation on the testing line will be used as the planned path.

[0075] The execution module 50 is used to obtain the vehicle gear information when the vehicle to be tested undergoes an electrical inspection; Based on the vehicle gear information, the pre-set process configuration parameters of the vehicle to be tested are used for electrical testing to obtain the electrical testing results at the target workstation.

[0076] The execution module 50 is used to upload the electrical inspection results in response to the inspection completion signal of the vehicle to be inspected; Once the vehicle to be inspected has completed uploading, the system returns a response indicating receipt of the electrical inspection station allocation instruction and retrieves the vehicle configuration information of the vehicle to be inspected.

[0077] The unmanned vehicle detection device provided in this application, employing the unmanned vehicle detection method described in the above embodiments, can solve the technical problem of how to detect vehicles when the intelligent driving system is not fully activated. Compared with the prior art, the beneficial effects of the unmanned vehicle detection device provided in this application are the same as those of the unmanned vehicle detection method provided in the above embodiments, and other technical features in the unmanned vehicle detection device are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0078] This application provides an unmanned vehicle detection device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the unmanned vehicle detection method in Embodiment 1 above.

[0079] The following is for reference. Figure 10This document illustrates a structural schematic diagram of a vehicle unmanned detection device suitable for implementing some embodiments of this application. The vehicle unmanned detection device in some embodiments of this application may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Description), PMPs (Portable Media Players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 10 The unmanned vehicle detection device shown is merely an example and should not be construed as limiting the functionality and scope of use of some embodiments of this application.

[0080] like Figure 10 As shown, the unmanned vehicle inspection device may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in ROM (Read Only Memory) 1002 or a program loaded from storage device 1003 into RAM (Random Access Memory) 1004. RAM 1004 also stores various programs and data required for the operation of the unmanned vehicle inspection device. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via bus 1005. Input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to I / O interface 1006: input devices 1007 including, for example, touch screens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. Communication device 1009 allows the unmanned vehicle inspection equipment to communicate wirelessly or wiredly with other devices to exchange data. Although the figure shows unmanned vehicle inspection equipment with various systems, it should be understood that implementation or possession of all the systems shown is not required. More or fewer systems may be implemented alternatively.

[0081] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0082] The unmanned vehicle detection device provided in this application, employing the unmanned vehicle detection method described in the above embodiments, can solve the technical problem of how to detect vehicles when the intelligent driving system is not fully activated. Compared with the prior art, the beneficial effects of the unmanned vehicle detection device provided in this application are the same as those of the unmanned vehicle detection method provided in the above embodiments, and other technical features of this unmanned vehicle detection device are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0083] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0084] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0085] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the unmanned vehicle detection method in the above embodiments.

[0086] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In some embodiments, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0087] The aforementioned computer-readable storage medium may be included in the unmanned vehicle inspection equipment; or it may exist independently and not be installed in the unmanned vehicle inspection equipment.

[0088] The aforementioned computer-readable storage medium carries one or more programs that, when executed by the unmanned vehicle inspection equipment, cause the unmanned vehicle inspection equipment to: in response to receiving an electrical inspection station allocation instruction, acquire vehicle configuration information of the vehicle to be inspected; activate sensors indicated by the vehicle configuration information, the sensors being configured on the vehicle to be inspected; determine guidance sign information based on production line environment information within the factory area, wherein the production line environment information is collected by sensors, and the guidance sign information is used to characterize guidance signs within the factory area; determine a planned path from the current position of the vehicle to be inspected to the target station specified by the electrical inspection station allocation instruction based on the guidance sign information; and control the vehicle to be inspected to travel to the target station according to the planned path.

[0089] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0090] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0091] The modules described in some embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0092] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described unmanned vehicle detection method, thereby solving the technical problem of how to detect vehicles when the intelligent driving system is not fully activated. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the unmanned vehicle detection method provided in the above embodiments, and will not be repeated here.

[0093] The above are only some embodiments of this application and do not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A method for unmanned vehicle detection, characterized in that, The method includes: In response to receiving the electrical inspection station allocation instruction, obtain the vehicle configuration information of the vehicle to be inspected; Activate the sensor indicated by the vehicle configuration information, the sensor being configured on the vehicle to be detected; Guidance sign information is determined based on production line environment information within the factory area, wherein the production line environment information is collected by the sensor, and the guidance sign information is used to characterize guidance signs within the factory area; Based on the guidance identification information, determine the planned path from the current location of the vehicle to be inspected to the target station specified by the electrical inspection station allocation instruction; and Control the vehicle to be tested to travel to the target workstation according to the planned path.

2. The method as described in claim 1, characterized in that, The steps for obtaining the vehicle configuration information of the vehicle to be detected include: Obtain the flashing package by flashing the preset controller software, and obtain the vehicle identification number of the vehicle to be detected; and In response to the location response request of the vehicle to be detected, if the location response request indicates that the vehicle is in place, the flashing software package is written to the vehicle to be detected according to the vehicle identification code for detection, and the vehicle configuration information is obtained.

3. The method as described in claim 1, characterized in that, The step of activating the sensor indicated by the vehicle configuration information includes: In response to the calibration operation, the sensors configured in the vehicle to be tested as indicated by the vehicle configuration information are calibrated; and Once the sensor calibration is complete, in response to a sensor activation command, the sensors of the vehicle to be tested are activated, including a camera, lidar, and millimeter-wave radar.

4. The method as described in claim 1, characterized in that, The guidance signage information includes lane lines, QR codes, and signage; The step of determining the planned path from the current location of the vehicle to be inspected to the target workstation specified by the electrical inspection workstation allocation instruction based on the guidance identification information includes: The location of the vehicle to be detected is determined based on the lane lines, the QR code, and the markers. The destination address of the vehicle to be inspected is determined according to the target station specified in the electrical inspection station allocation instruction; and The path from the location of the vehicle to be detected to the destination address is used as the planned path.

5. The method as described in claim 4, characterized in that, The step of using the path from the location of the vehicle to be detected to the destination address as the planned path includes: The inspection line station for the vehicle to be inspected is determined based on the destination address; The geomagnetic field at the testing line station is detected to obtain the testing results; and If the detection result indicates that there is an available workstation, the path from the location of the vehicle to be inspected to the workstation on the inspection line is used as the planned path.

6. The method as described in claim 1, characterized in that, The unmanned vehicle detection method also includes: When the vehicle under test undergoes an electrical inspection, the vehicle's gear position information is obtained; and Based on the vehicle gear information, the process configuration parameters preset on the vehicle to be tested are electrically tested to obtain the electrical test results at the target workstation.

7. The method as described in claim 6, characterized in that, The unmanned vehicle detection method also includes: In response to the detection completion signal of the vehicle under inspection, the electrical inspection result is uploaded; and If the vehicle to be inspected has completed uploading, return to the step of receiving the electrical inspection station allocation instruction and obtaining the vehicle configuration information of the vehicle to be inspected.

8. A vehicle unmanned detection device, characterized in that, The device includes: The acquisition module is used to acquire the vehicle configuration information of the vehicle to be inspected in response to receiving the electrical inspection station allocation instruction; An activation module is used to activate the sensor indicated by the vehicle configuration information, the sensor being configured on the vehicle to be detected; The processing module is used to determine guidance sign information based on the production line environment information within the factory area, wherein the production line environment information is collected by the sensor, and the guidance sign information is used to characterize the guidance signs within the factory area; The planning module is used to determine, based on the guidance identification information, the planned path from the current position of the vehicle to be inspected to the target station specified by the electrical inspection station allocation instruction; The execution module is used to control the vehicle to be tested to travel to the target workstation according to the planned path.

9. An unmanned vehicle inspection device, characterized in that, The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the unmanned vehicle detection method as described in any one of claims 1 to 7.

10. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of the unmanned vehicle detection method as described in any one of claims 1 to 7.

Images