CN113848826B - Automatic vehicle offline method, device, equipment and storage medium - Google Patents

Automatic vehicle offline method, device, equipment and storage medium Download PDF

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Publication number
CN113848826B
CN113848826B CN202111018120.0A CN202111018120A CN113848826B CN 113848826 B CN113848826 B CN 113848826B CN 202111018120 A CN202111018120 A CN 202111018120A CN 113848826 B CN113848826 B CN 113848826B
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vehicle
line
offline
calibration
verification
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CN113848826A (en
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许兆基
韩旭
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Guangzhou Weride Technology Co Ltd
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Guangzhou Weride Technology Co Ltd
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM]
    • G05B19/41875—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM] characterised by quality surveillance of production
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/30—Nc systems
    • G05B2219/32—Operator till task planning
    • G05B2219/32368—Quality control
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

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  • Engineering & Computer Science (AREA)
  • General Engineering & Computer Science (AREA)
  • Manufacturing & Machinery (AREA)
  • Quality & Reliability (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Traffic Control Systems (AREA)

Abstract

The invention belongs to the technical field of vehicle offline, and discloses a vehicle automatic offline method, device, equipment and storage medium. The method comprises the following steps: when the off-line operation of the vehicle to be off-line is required, scanning the identification information of the vehicle to be off-line so as to establish communication connection with the vehicle to be off-line; acquiring an offline verification item of the vehicle to be offline; verifying the vehicle to be off line through the communication connection according to the off line verification project; and when the verification of the vehicle to be off-line passes, the vehicle to be off-line is considered to finish the off-line flow. Through the mode, production workers do not need professional technical knowledge, the whole process of the offline verification project can be completed only by operating according to the guidance of the application program, and the offline verification project is automatically implemented, so that the labor cost of engineers is greatly reduced while the production efficiency is improved.

Description

Automatic vehicle offline method, device, equipment and storage medium
Technical Field
The present invention relates to the field of vehicle offline technology, and in particular, to a method, an apparatus, a device, and a storage medium for automatically offline a vehicle.
Background
At present, along with popularization of automatic driving vehicles, supply requirements of the automatic driving vehicles are higher and higher, and the automatic driving vehicles are assembled in a production workshop until the automatic driving systems can be assembled in normal running, the working states of equipment for checking hardware, sensor calibration parameters are generated and checked, and the states of the automatic driving systems are checked. The existing solutions all need engineers to go to the vehicle for checking, assembling and calibrating, and a great deal of time is consumed for the engineers to turn on and off, so that the existing solutions cannot meet the requirement of mass automatic driving vehicles for offline.
The foregoing is provided merely for the purpose of facilitating understanding of the technical solutions of the present invention and is not intended to represent an admission that the foregoing is prior art.
Disclosure of Invention
The invention mainly aims to provide a method, a device, equipment and a storage medium for automatically taking off a line of a vehicle, and aims to solve the technical problems that an engineering teacher needs to consume a great deal of time to carry out adjustment and the automatic driving vehicle in the prior art cannot meet the requirement of taking off the line of a large number of automatic driving vehicles.
In order to achieve the above object, the present invention provides a method for automatically disconnecting a vehicle from the line, the method comprising the steps of:
When the off-line operation of the vehicle to be off-line is required, scanning the identification information of the vehicle to be off-line so as to establish communication connection with the vehicle to be off-line;
acquiring an offline verification item of the vehicle to be offline;
verifying the vehicle to be off line through the communication connection according to the off line verification project;
and when the verification of the vehicle to be off-line passes, the vehicle to be off-line is considered to finish the off-line flow.
Optionally, before the step of obtaining the offline verification item of the vehicle to be offline, the method further includes:
acquiring configuration information of the vehicle to be off line through the communication connection;
generating a system installation instruction and a system configuration script according to the configuration information;
and sending the system installation instruction and the system configuration script to the vehicle to be offline, so that the vehicle to be offline installs an automatic driving system according to the system installation instruction, and configures the automatic driving system according to the system configuration script.
Optionally, the step of verifying the vehicle to be offline through the communication connection according to the offline verification item includes:
generating a hardware verification instruction and a hardware verification script according to the offline verification item;
And sending the hardware verification instruction and the hardware verification script to the vehicle to be offline through the communication connection, so that the vehicle to be offline carries out hardware detection on the target hardware equipment according to the hardware verification script, and feeds back the hardware detection result.
Optionally, after the step of sending the hardware verification instruction and the hardware verification script to the vehicle to be offline through the communication connection, the method further includes:
when the hardware detection result passes, generating a system calibration instruction and a preset calibration route according to the offline verification project;
the system calibration instruction and the preset calibration route are sent to the vehicle to be off line, so that the vehicle to be off line runs according to the preset calibration route, and calibration data are recorded;
after the calibration data of the vehicle to be off line is recorded, a calibration parameter generation instruction is sent to enable the vehicle to be off line to determine camera calibration images and inertia unit calibration data according to the calibration data, vehicle body posture data is generated according to the camera calibration images, inertia unit calibration parameters are determined according to the vehicle body posture data and the inertia unit calibration data, laser radar calibration point clouds are determined according to the calibration data, camera object coordinates are determined according to the camera calibration images, laser radar object coordinates are determined according to the laser radar calibration point clouds, millimeter wave radar object coordinates are determined according to the camera object coordinates and the laser radar object coordinates, millimeter wave radar object coordinates are determined according to the millimeter wave radar calibration data, millimeter wave radar calibration parameters are determined according to the laser radar object coordinates, the laser radar calibration parameters and the millimeter wave radar object coordinates, and millimeter wave radar calibration parameters are generated according to the inertia unit calibration parameters, the laser radar calibration parameters and the cloud radar calibration parameters, and the millimeter wave radar calibration parameters are sent to the millimeter wave radar.
Optionally, after the step of sending the system calibration instruction and the preset calibration route to the vehicle to be offline, the method further includes:
generating a drive test instruction according to the offline verification project;
the road test instruction is sent to the vehicle to be off line so that the vehicle to be off line runs on a preset road, a road test data packet is collected, a road test checking flow is generated, the road test checking flow is fed back, and the road test data packet is sent to the cloud;
and generating a vehicle check report according to the drive test checking flow, and sending the vehicle check report to the cloud.
Optionally, when the verification of the vehicle to be offline passes, the step of identifying that the vehicle to be offline completes the offline flow includes:
transmitting a drive test result acquisition instruction to the cloud so that the cloud determines a signal lamp image and a signal lamp vehicle identification result according to the drive test data packet, converts the signal lamp image into a signal lamp histogram, normalizes the signal lamp histogram to obtain a normalized target image, segments the normalized target image to obtain a color segmentation image, determines geometric features of the color segmentation image, determines a signal lamp region according to the geometric features, obtains a signal lamp identification result according to the signal lamp region, compares the signal lamp identification result with the signal lamp vehicle identification result to obtain a signal lamp judgment result, generates a drive test result according to the signal lamp judgment result, and feeds back the drive test result;
And when the drive test result passes the verification, the vehicle to be off-line is determined to finish the off-line process.
Optionally, when the offline operation needs to be performed on the offline vehicle, the step of scanning the identification information of the offline vehicle to establish communication connection with the offline vehicle includes:
scanning the identification information of the vehicle to be offline to obtain a key input page;
when an authentication key is received, comparing the authentication key with a preset authentication key;
and after the comparison is passed, establishing communication connection with the vehicle to be off line.
In addition, in order to achieve the above object, the present invention also provides an automatic vehicle offline device, which includes:
the scanning module is used for scanning the identification information of the vehicle to be offline when the vehicle to be offline is required to be offline, so as to establish communication connection with the vehicle to be offline;
the acquisition module is used for acquiring the offline verification item of the vehicle to be offline;
the verification module is used for verifying the vehicle to be offline through the communication connection according to the offline verification project;
and the identification module is used for identifying that the vehicle to be off-line finishes the off-line flow when the verification of the vehicle to be off-line passes.
In addition, in order to achieve the above object, the present invention also provides a vehicle automatic offline device, including: a memory, a processor, and a vehicle automatic off-line sequence stored on the memory and operable on the processor, the vehicle automatic off-line sequence configured to implement the steps of the vehicle automatic off-line method as described above.
In addition, in order to achieve the above object, the present invention also proposes a storage medium having stored thereon an automatic vehicle drop-off procedure, which when executed by a processor, implements the steps of the automatic vehicle drop-off method as described above.
When the off-line operation of the vehicle to be off-line is required, the identification information of the vehicle to be off-line is scanned so as to establish communication connection with the vehicle to be off-line; acquiring an offline verification item of the vehicle to be offline; verifying the vehicle to be off line through the communication connection according to the off line verification project; and when the verification of the vehicle to be off-line passes, the vehicle to be off-line is considered to finish the off-line flow. Through the mode, production workers do not need professional technical knowledge, the whole process of the offline verification project can be completed only by operating according to the guidance of the application program, and the offline verification project is automatically implemented, so that the labor cost of engineers is greatly reduced while the production efficiency is improved.
Drawings
FIG. 1 is a flow chart of a first embodiment of an automatic vehicle offline method according to the present invention;
FIG. 2 is a flow chart of a second embodiment of the automatic vehicle offline method according to the present invention;
FIG. 3 is a flow chart of a third embodiment of the automatic vehicle offline method according to the present invention;
FIG. 4 is a flowchart of a fourth embodiment of the automatic vehicle offline method according to the present invention;
FIG. 5 is a block diagram of a first embodiment of an automatic vehicle drop-in apparatus according to the present invention;
fig. 6 is a schematic structural diagram of a vehicle automatic offline device in a hardware running environment according to an embodiment of the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The embodiment of the invention provides an automatic vehicle offline method, and referring to fig. 1, fig. 1 is a schematic flow chart of a first embodiment of the automatic vehicle offline method.
In this embodiment, the automatic vehicle offline method includes the following steps:
step S10: when the off-line operation of the off-line vehicle is required, the identification information of the off-line vehicle is scanned so as to establish communication connection with the off-line vehicle.
It should be noted that, the execution body of the embodiment may be a mobile terminal, for example, a smart phone, a tablet computer, or other devices running an intelligent operating system, and an application program for vehicle offline is installed on the mobile terminal.
It should be understood that the off-line refers to that after the vehicle is assembled, system software configuration, software and hardware function detection and the like are required to be performed on the vehicle, and when the configuration, the detection and the like are qualified, the vehicle can be delivered to a user, so that the safety of the user in the driving process is ensured.
In a specific implementation, each vehicle to be offline has unique identification information, the identification information can be an image which can contain information, such as a two-dimensional code, a bar code and the like, when a production line worker needs to perform offline operation on the vehicle to be offline, the worker opens an application program and clicks an offline button, the application program calls a camera of the mobile terminal to scan the identification information, so that connection information of the vehicle to be offline is obtained, and the mobile terminal establishes communication connection with the vehicle to be offline through the connection information.
It can be understood that the identification information may also be a near field communication (Near Field Communication, NFC) tag, and the application program may call the NFC function of the mobile terminal and obtain the connection information of the vehicle to be offline when the application program is close to the NFC tag, so as to establish communication connection with the vehicle to be offline. The identification information is also a radio frequency identification technology (Radio Frequency Identification, RFID) tag, and the mobile terminal is connected with an RFID reader, and the RFID reader reads the information of the RFID tag and sends the information to the mobile terminal.
Further, in order to ensure the safety of the communication connection between the mobile terminal and the vehicle to be disconnected, step S10 includes: scanning the identification information of the vehicle to be offline to obtain a key input page; when an authentication key is received, comparing the authentication key with a preset authentication key; and after the comparison is passed, establishing communication connection with the vehicle to be off line.
In a specific implementation, a communication connection is established between the mobile terminal and the vehicle to be off line in advance and between the mobile terminal and the cloud end, the communication connection is established between the vehicle to be off line and the cloud end through a preset authentication key, after the mobile terminal scans the identification information, the connection information of the vehicle to be off line is sent to the mobile terminal, the connection information comprises the preset authentication key, an application program interface displays a key input page, a worker inputs the authentication key, the mobile terminal compares the authentication key with the preset authentication key, after the comparison is passed, the successfully-compared information is sent to the cloud end, and the communication connection between the mobile terminal and the vehicle to be off line is established through the cloud end.
It can be understood that after the authentication key is compared with the preset authentication key, the mobile terminal can directly establish communication connection with the vehicle to be off line without passing through the cloud, so that the problem that the connection with the vehicle to be off line is lost due to the fact that the communication connection with the cloud is lost when a wireless signal is poor, and the off line flow of the vehicle to be off line is affected is avoided.
The key input page is obtained by scanning the identification information of the vehicle to be off line; when an authentication key is received, comparing the authentication key with a preset authentication key; after the comparison is passed, communication connection is established with the vehicle to be off line, so that the data security of the whole process can be ensured when the vehicle to be off line is verified.
Step S20: and acquiring an offline verification item of the vehicle to be offline.
In the specific implementation, the offline verification project can completely detect and verify whether the software and hardware of the vehicle to be offline can normally operate, and the offline verification project comprises the projects of hardware data automatic detection, positioning and sensor calibration parameter generation, calibration parameter verification, automatic driving system automatic verification and the like.
It can be understood that after the mobile terminal establishes communication connection with the vehicle to be offline, acquiring an offline verification item required to be performed by the vehicle to be offline from the cloud; or the mobile terminal stores the offline verification item, the mobile terminal sends the version number of the offline verification item to the cloud, the cloud judges whether the offline verification item is the latest one after receiving the version number, and when the offline verification item is not the latest version, the mobile terminal sends the offline verification item of the latest version to the mobile terminal.
In a specific implementation, due to different configurations and functions of different vehicles to be taken off line, items to be verified may not be identical. For example: the radar set on the vehicle to be off-line a is a laser radar, and the radar set on the vehicle to be off-line B is a millimeter wave radar, so that the methods used by the two vehicles for detecting and verifying the radar may not be the same. The above is merely illustrative, and the present embodiment is not limited thereto.
Step S30: and verifying the vehicle to be off-line through the communication connection according to the off-line verification item.
The order of the real-time verification items is included in the offline verification items, a worker operates the order of the steps in the application program, the mobile terminal generates a corresponding offline verification item instruction after receiving the operation instruction of the worker, the offline verification item instruction is sent to the vehicle to be offline through communication connection, and the vehicle to be offline executes corresponding verification operation according to the offline verification item instruction, so that each item verification in the offline verification items is automatically completed.
It can be understood that, because each verification step in the offline verification project is performed sequentially, rather than synchronously, when a certain verification project fails, an application program prompts a worker that a certain piece of software or hardware has a problem and lists various solutions, the worker can overhaul according to the solutions, and after the overhaul is completed, the project is tested and verified again, if the verification is not passed, the worker can remotely ask the engineer for help through the application program, and the engineer can remotely check various detection data and debug and repair the vehicle to be offline, thereby ensuring the production continuity of the production line.
Step S40: and when the verification of the vehicle to be off-line passes, the vehicle to be off-line is considered to finish the off-line flow.
It should be understood that, after the vehicle to be offline is completed and passes through all offline verification projects, it is indicated that the software, hardware, system and the like of the vehicle to be offline are not problematic, and the user can directly use the vehicle to be offline.
When the offline operation needs to be performed on the offline vehicle, the embodiment scans the identification information of the offline vehicle so as to establish communication connection with the offline vehicle; acquiring an offline verification item of the vehicle to be offline; verifying the vehicle to be off line through the communication connection according to the off line verification project; and when the verification of the vehicle to be off-line passes, the vehicle to be off-line is considered to finish the off-line flow. Through the mode, production workers do not need professional technical knowledge, the whole process of the offline verification project can be completed only by operating according to the guidance of the application program, and the offline verification project is automatically implemented, so that the labor cost of engineers is greatly reduced while the production efficiency is improved.
Referring to fig. 2, fig. 2 is a flowchart of a second embodiment of a vehicle automatic offline method according to the present invention.
Based on the above-mentioned first embodiment, the vehicle automatic offline method of the present embodiment further includes, before the step S20:
step S11: and acquiring the configuration information of the vehicle to be off line through the communication connection.
It should be noted that, after the mobile terminal establishes communication connection with the vehicle to be off-line, current configuration information of the vehicle can be obtained from the vehicle to be off-line, where the configuration information includes hardware configuration, software configuration, system configuration, and the like.
It can be understood that, generally, when the vehicle to be offline is first connected to the mobile terminal, only the basic operating system is installed on the vehicle to be offline, and the basic data, service data and the like of the system are not completely configured.
Step S12: and generating a system installation instruction and a system configuration script according to the configuration information.
The automatic driving system is packaged in advance, and the automatic driving system comprises a high-definition map, basic data, service data and the like. On the production line, a worker only needs to insert the system disc into a host of the vehicle to be taken off line, and the vehicle to be taken off line can automatically recognize data in the host. The system disk may be a nonvolatile storage medium such as a usb disk.
In a specific implementation, a worker clicks on an application program to start installation, and the mobile terminal generates a system installation instruction and generates a system configuration script according to configuration information of a vehicle to be taken off line.
Step S13: and sending the system installation instruction and the system configuration script to the vehicle to be offline, so that the vehicle to be offline installs an automatic driving system according to the system installation instruction, and configures the automatic driving system according to the system configuration script.
After receiving the system installation instruction, the off-line vehicle installs the automatic driving system according to the data in the system disk, and decompresses the high-definition map data, the basic data, the service data and the like. When the automatic driving system is installed, the automatic driving system is usually indiscriminate, and the system configuration script automatically configures the automatic driving system, so that the automatic driving system is completely matched with the configuration of the vehicle to be taken off line.
The embodiment obtains the configuration information of the vehicle to be off line through the communication connection; generating a system installation instruction and a system configuration script according to the configuration information; and sending the system installation instruction and the system configuration script to the vehicle to be offline, so that the vehicle to be offline installs an automatic driving system according to the system installation instruction, and configures the automatic driving system according to the system configuration script. By the method, the application program acquires the configuration information of the vehicle after being connected with the vehicle to be off line, and configures the automatic driving system according to the configuration information of the vehicle after the vehicle is automatically installed, so that the effect that the vehicle to be off line corresponds to the automatic driving system one by one is achieved.
Referring to fig. 3, fig. 3 is a flowchart of a third embodiment of a vehicle automatic offline method according to the present invention.
Based on the above first embodiment, the vehicle automatic offline method of the present embodiment includes, at step S30:
step S31: and generating a hardware verification instruction and a hardware verification script according to the offline verification item.
In a specific implementation, the offline verification project comprises hardware detection, and when the hardware detection step is reached according to the step sequence in the offline verification project, the worker clicks the hardware detection, and the mobile terminal generates a hardware verification instruction and a hardware verification script.
It should be noted that, the hardware verification script may be a general verification script, or may be a hardware verification script generated according to a hardware configuration of the vehicle to be disconnected.
Step S32: and sending the hardware verification instruction and the hardware verification script to the vehicle to be offline through the communication connection, so that the vehicle to be offline carries out hardware detection on the target hardware equipment according to the hardware verification script, and feeds back the hardware detection result.
It can be understood that, after the vehicle to be offline receives the hardware verification instruction and the hardware verification script, the hardware verification script is executed according to the hardware verification instruction, the hardware verification script comprehensively detects the hardware devices on the vehicle, and the hardware detection items include: the hardware detection items may be slightly different according to the hardware configuration of different vehicles to be off-line, such as the working state of the hard disk, the disk configuration, the system starting time, the display card configuration and the pressure testing performance, the CPU configuration and the pressure testing performance, the memory size, the millimeter wave radar signal, the wire control signal, the GPS signal, the network signal, the laser radar network card speed, whether the camera wire sequence connection is correct, the camera frame loss condition, and the like. The target hardware device includes: hard disk, magnetic disk, display card, CPU, memory, millimeter wave radar, drive-by-wire, GPS chip, network card, laser radar network card, camera, etc.
It should be noted that, because the hardware usually works in a joint way, data interaction is performed between the hardware, so that connectivity between the hardware needs to be tested during hardware detection, and data generated by the hardware can be analyzed during hardware detection, so as to determine whether the hardware can work normally. For example: when the GPS positioning module is detected, connectivity of other hosts is detected, positioning data acquired by the GPS positioning module is analyzed, and whether the positioning data are abnormal or not is judged.
It should be noted that, the hardware on the vehicle to be off-line supports software control at the same time, so that a hardware interface for software control needs to be detected, and whether the hardware can be controlled to realize the corresponding function is judged by calling the interface corresponding to the hardware, thereby determining whether the hardware can work normally. For example: and calling a reversing image function of the high-definition reversing camera, and judging whether the reversing camera can work normally or not according to the display image.
In the specific implementation, each time one of the hardware detection is completed, the hardware detection result is fed back to the mobile terminal in real time, the mobile terminal displays the hardware detection result in real time, when the hardware detection project is completed, the worker is prompted with hardware which fails to run or fails to run to meet the standard, and repair advice is provided for repairing, if the worker cannot repair, the worker can resort to through an application program, an engineer remotely supports to repair, and after the repair is completed, the hardware detection is performed again until all target hardware equipment runs to meet the standard.
Further, after all the target hardware devices pass the verification, the step of sending the hardware verification instruction and the hardware verification script to the vehicle to be offline through the communication connection further includes: when the hardware detection result passes, generating a system calibration instruction and a preset calibration route according to the offline verification project; the system calibration instruction and the preset calibration route are sent to the vehicle to be off line, so that the vehicle to be off line runs according to the preset calibration route, and calibration data are recorded; after the calibration data of the vehicle to be off line is recorded, a calibration parameter generation instruction is sent to enable the vehicle to be off line to determine camera calibration images and inertia unit calibration data according to the calibration data, vehicle body posture data is generated according to the camera calibration images, inertia unit calibration parameters are determined according to the vehicle body posture data and the inertia unit calibration data, laser radar calibration point clouds are determined according to the calibration data, camera object coordinates are determined according to the camera calibration images, laser radar object coordinates are determined according to the laser radar calibration point clouds, millimeter wave radar object coordinates are determined according to the camera object coordinates and the laser radar object coordinates, millimeter wave radar object coordinates are determined according to the millimeter wave radar calibration data, millimeter wave radar calibration parameters are determined according to the laser radar object coordinates, the laser radar calibration parameters and the millimeter wave radar object coordinates, and millimeter wave radar calibration parameters are generated according to the inertia unit calibration parameters, the laser radar calibration parameters and the cloud radar calibration parameters, and the millimeter wave radar calibration parameters are sent to the millimeter wave radar.
After determining that all the target hardware devices pass verification according to the hardware detection result, the application program jumps to a next offline verification project page, and before performing the next offline verification project, the application program prompts a worker to transport the vehicle to be offline to a calibration site, after the vehicle to be offline is transported to the calibration site, the worker can click on starting calibration in the application program, and the application program generates a system calibration instruction and a preset calibration route and sends the system calibration instruction and the preset calibration route to the vehicle to be offline.
It can be understood that when the vehicle to be offline receives the system calibration instruction, the vehicle automatically runs in the calibration site according to the preset calibration route, and automatically collects and records the calibration objects in the site, so as to generate calibration data, and the vehicle to be offline automatically calculates the calibration parameters according to the calibration data, writes the calibration parameters into a local configuration file and uploads the calibration parameters to the cloud for storage. The preset calibration route can be a cross route in the calibration site.
Further, before the sensor calibration parameters are initialized by the vehicle to be offline, the brake calibration parameters to be offline are needed, in the closed field, the application program sends preset codes to the vehicle to be offline, a calibration track is generated by the vehicle to be offline in the closed field according to the preset codes, the vehicle to be offline is automatically started by workers, a control module of the vehicle to be offline drives the vehicle to be offline along the track by sending a brake accelerator instruction and a steering wheel instruction, a data acquisition module automatically acquires the positioning and speed difference value when the vehicle is driven to calculate a brake meter and an accelerator meter of the vehicle, and the acquired point cloud data are used for positioning calibration and sensor calibration.
It can be understood that the corresponding relation between the opening degree of the brake pedal and the acceleration is included in the brake meter, and the corresponding relation between the opening degree of the accelerator pedal and the acceleration is also included in the accelerator meter, so that the speed of the vehicle can be controlled more accurately through the brake meter and the accelerator meter during automatic driving.
When the positioning calibration is performed through the point cloud data, the point cloud data acquired by the vehicle to be taken off line is compared with the global point cloud data in the closed field, so that the specific position of the vehicle to be taken off line in the closed field can be determined, and then the positioning calibration is performed on the vehicle to be taken off line according to the positioning data acquired by the positioning module of the vehicle to be taken off line at the moment.
In specific implementation, the system calibration comprises inertial unit calibration, laser radar calibration and millimeter wave radar calibration. Sensor calibration is a basic requirement of automatic driving, and when a plurality/a plurality of sensors (such as cameras, laser radars, millimeter wave radars and the like) are installed on a vehicle, the coordinate relation between the sensors needs to be determined.
It should be noted that, the inertial unit is a device for measuring the three-axis attitude angle (or angular rate) and acceleration of an object, when the inertial unit is calibrated, because the attitude change generated by the inertial unit and the laser radar or the camera satisfies a certain constraint relationship, according to the data collected by the inertial unit and the calibration data collected by the laser radar or the camera, the coordinate conversion relationship between the inertial unit and the laser radar or the camera, namely the calibration parameters of the inertial unit. When the laser radar is calibrated, calibration data acquired by the laser radar and the camera are calculated, so that the coordinate conversion relation between the laser radar and the camera is determined, the calibration parameters of the laser radar are obtained, and the calibration parameters of the millimeter wave radar can be obtained in the same way, so that the coordinate relation among sensors on the vehicle to be off line is determined.
In the specific implementation, the inertial unit, the laser radar and the millimeter wave radar are calibrated by taking a camera calibration image of the camera (camera) captured in a calibration field as a reference. In order to facilitate the calibration of the vehicle to be off line, a calibration object with an obvious shape is arranged in a calibration field, when the vehicle to be off line passes through the calibration object, each sensor on the vehicle body records calibration data in real time, after the calibration data is recorded, the application program displays that the calibration data is recorded, calibration parameter calculation can be performed, after a worker clicks a calibration parameter calculation button, the mobile terminal sends a calibration parameter generation instruction to the vehicle to be off line, and the vehicle to be off line starts to calculate the calibration parameters of each sensor.
It can be understood that the camera calibration image and the inertial unit calibration data are calibration data recorded by the camera and the inertial unit by taking the same time line as a reference, the camera calibration image comprises image information of the camera recording calibration plate, when the vehicle body posture of the vehicle to be taken off line changes, the corresponding posture angle change of the calibration plate in the camera calibration image can also occur, the posture angle change detected by the inertial unit is determined according to the data of the inertial unit calibration data at the same moment, and the change of the posture angle captured by the camera is compared with the posture angle change detected by the inertial unit, so that the conversion parameter between the camera calibration image and the inertial unit calibration parameter can be determined.
Similarly, when the laser radar is calibrated, a camera calibration image of a calibration object captured by the camera at the same moment and a laser radar calibration point cloud of the calibration object acquired by the laser radar are determined, a coordinate system is established in the camera calibration image, the coordinates of the calibration object in the coordinate system, namely, camera object coordinates are determined, likewise, a coordinate system is established in the laser radar calibration point cloud, the coordinates of the calibration object in the coordinate system, namely, laser radar object coordinates are determined, and the conversion relation between the camera object coordinates and the laser radar object coordinates is calculated, so that laser radar calibration parameters are obtained.
In specific implementation, when the millimeter wave radar is calibrated, millimeter wave radar calibration data of a calibration object acquired by the millimeter wave radar at the same moment and a laser radar calibration point cloud of the calibration object acquired by the laser radar are determined by means of the laser radar, coordinates of the calibration object in the millimeter wave radar calibration data, namely the coordinates of the millimeter wave radar object, and coordinates of the calibration object in the laser radar calibration point cloud, namely the coordinates of the laser radar object, are calculated, and finally, a conversion relation between the coordinates of the millimeter wave radar object and the coordinates of the laser radar object is calculated, and conversion relation parameters between the millimeter wave radar and a camera, namely the millimeter wave radar calibration parameters, are obtained based on the laser radar calibration parameters.
Further, when the long-focus camera and the short-focus camera are simultaneously arranged on the vehicle with the off-line, the two cameras are required to be calibrated, firstly, a long Jiao Biaoding image and a short-focus calibration image are determined at the same time, a long-focus target image with a preset range in the long-focus calibration image is obtained, and as the images captured by the cameras generate distortion at the edge and the near position, a preset range with smaller distortion of the two images is required to be selected, for example, a calibration object in an area outside 50 meters in the images is selected. Simultaneously acquiring a short-focus target image in the preset range in the short-focus calibration image, converting coordinates of the long-focus target image and a calibration object in the short-focus target image, calculating conversion parameters, obtaining camera calibration parameters,
after calibration parameters are generated and stored, the off-line vehicle sends a calibration completion signal to the mobile terminal, and the application program prompts the worker to complete the system calibration flow, so that the off-line verification project of the next step can be developed.
Further, in order to more fully verify the vehicle to be taken off line, after the step of sending the system calibration command and the preset calibration route to the vehicle to be taken off line, the method further includes: generating a drive test instruction according to the offline verification project; the road test instruction is sent to the vehicle to be off line so that the vehicle to be off line runs on a preset road, a road test data packet is collected, a road test checking flow is generated, the road test checking flow is fed back, and the road test data packet is sent to the cloud; and generating a vehicle check report according to the drive test checking flow, and sending the vehicle check report to the cloud.
It should be understood that, after the verification project of completing the system calibration is performed, drive test verification needs to be performed, so as to detect the running condition of the vehicle to be taken off line in the real environment. At this time, the application prompts the worker to transport the vehicle to be off-line to the drive test site, where information in the real road is included, such as traffic lights, zebra crossings, and the like.
It can be understood that a worker clicks a road test start button on an application program, the application program generates a road test instruction and sends the road test instruction to a vehicle to be off line, the vehicle to be off line automatically runs on a road test site after receiving the road test instruction, an automatic driving system on the vehicle to be off line automatically drives according to road information in the road test site, and in the road test process, the application program displays a complete inspection flow for the worker to check, wherein the inspection flow comprises vehicle traffic light inspection, brake inspection, accelerator inspection, steering wheel inspection and collision inspection. And after the checking is finished, a vehicle checking report uploading cloud record is generated.
It should be understood that, wait to roll off the road data of fixed road can be gathered automatically in the drive test process of vehicle, and road data is gathered by waiting to roll off the road and is obtained by laser radar, millimeter wave radar, the camera on the vehicle to send road data to the high in the clouds, and the high in the clouds then can be according to whether road data analysis laser radar, millimeter wave radar, camera normal operating, whether the object that the established highway section detected and the response of making are correct. And obtaining a drive test result.
The embodiment generates a hardware verification instruction and a hardware verification script according to the offline verification item; and sending the hardware verification instruction and the hardware verification script to the vehicle to be offline through the communication connection, so that the vehicle to be offline carries out hardware detection on the target hardware equipment according to the hardware verification script, and feeds back the hardware detection result. By the method, the off-line vehicles are subjected to full-automatic off-line verification projects such as hardware verification, system calibration and drive test verification, and the like, and the software and hardware detection flow is strict, so that the off-line vehicles can be comprehensively detected and verified, and the delivery quality of the batch off-line automatic driving vehicles is ensured.
Referring to fig. 4, fig. 4 is a flowchart of a fourth embodiment of a vehicle automatic offline method according to the present invention.
Based on the third embodiment, the automatic vehicle offline method of the present embodiment at step S40 includes:
step S41: transmitting a drive test result acquisition instruction to the cloud so that the cloud can determine a signal lamp image and a signal lamp vehicle identification result according to the drive test data packet, convert the signal lamp image into a signal lamp histogram, normalize the signal lamp histogram to obtain a normalized target image, divide the normalized target image to obtain a color division image, determine the geometric characteristics of the color division image, determine a signal lamp area according to the geometric characteristics, obtain the signal lamp identification result according to the signal lamp area, compare the signal lamp identification result with the signal lamp vehicle identification result to obtain a signal lamp judgment result, generate a drive test result according to the signal lamp judgment result, and feed back the drive test result.
It should be noted that, after the drive test is finished, the worker clicks a drive test result acquisition button on the application program, the application program generates a drive test result acquisition instruction and sends the drive test result acquisition instruction to the cloud, and the cloud sends the corresponding drive test result to the mobile terminal.
In a specific implementation, after receiving the drive test data packet, the cloud end analyzes the drive test data packet, wherein the drive test data packet contains all data of the vehicle to be taken off line in the drive test process, including data acquired by the sensor, data judged by the vehicle according to the data acquired by the sensor, and the like.
It can be understood that, the driving process is unavoidable when the signal lamp, so the accuracy of identifying and detecting the signal lamp by the vehicle waiting to be off line is crucial, the cloud obtains the image acquired by the camera when the vehicle waiting to be off line passes through the signal lamp according to the drive test data packet, namely the signal lamp image, and the cloud firstly needs to carry out histogram equalization on the signal lamp image to obtain a signal lamp histogram in order to accurately identify the signal lamp, namely: histogram equalization is performed on each channel (R, G, B) data of the signal lamp images, which are then combined into a 3-channel image. Since the correlation between these 3 components in the RGB color space R, G, B is high, it is greatly affected by illumination, which is disadvantageous for color segmentation. Therefore, the three channels of RGB data are normalized, so that a normalized target image is obtained, and a normalization formula is:
Formula one;
wherein R is the normalized value of the R channel, G is the normalized value of the G channel, and B is the normalized value of the B channel.
Note that, since the values of the signal lights R, G, B are different in the signal light images in different light environments, the threshold range of the values of the signal lights R, G, B is determined from the signal light images in the respective light environments. According to the threshold range, the area of the normalized target image can be determined, namely, a color segmentation image can be obtained, and because other interference factors possibly exist in the environment, the color segmentation image is not necessarily an area of a signal and the like, therefore, the signal lamp area in the color segmentation image is required to be determined according to the geometric characteristics of the signal lamp, the basic geometric characteristics of the area, such as the length, the width, the length-width ratio and the like, are extracted, the area close to a circle is taken as the signal lamp area, the signal lamp is identified according to the color of the signal lamp area, the signal lamp identification result is obtained, the signal lamp identification result is compared with the signal lamp vehicle identification result of the signal lamp of the vehicle to be taken off line, the signal lamp judgment result is obtained, and the signal lamp identification signal lamp success is indicated when the signal lamp identification result of the vehicle to be taken off line is achieved.
Similarly, the cloud end also simulates automatic driving based on data acquired by a sensor of the vehicle to be offline, so that simulated steering wheel, brake and accelerator control instructions are generated, the simulated steering wheel, brake and accelerator control instructions are compared with actual control instructions of the vehicle to be offline, an automatic driving decision result is obtained, and whether the decision of the vehicle to be offline is correct or not is judged according to the automatic driving decision result.
In a specific implementation, a drive test result can be obtained according to the signal lamp judgment result and the automatic driving decision result.
Step S42: and when the drive test result passes the verification, the vehicle to be off-line is determined to finish the off-line process.
It should be noted that, when the signal lamp identification of the vehicle to be off-line is correct and the signal lamp identification is consistent with the decision made by the cloud according to the sensor data, the drive test result is indicated to pass.
In a specific implementation, because all the offline verification items are developed according to a certain sequence, the next verification item is opened after the offline verification item passes, and therefore, when the drive test result passes the verification, the fact that all the offline verification items of the vehicle to be offline pass the verification is indicated, and the vehicle can be delivered to the user.
According to the method, a drive test result acquisition instruction is sent to the cloud so that the cloud can determine a signal lamp image and a signal lamp vehicle identification result according to the drive test data packet, the signal lamp image is converted into a signal lamp histogram, the signal lamp histogram is normalized to obtain a normalized target image, the normalized target image is segmented to obtain a color segmentation image, geometric features of the color segmentation image are determined, a signal lamp area is determined according to the geometric features, the signal lamp identification result is obtained according to the signal lamp area, the signal lamp identification result is compared with the signal lamp vehicle identification result, a signal lamp judgment result is obtained, the drive test result is generated according to the signal lamp judgment result, and the drive test result is fed back; and when the drive test result passes the verification, the vehicle to be off-line is determined to finish the off-line process. By the method, the cloud verification analyzes the critical drive test data, so that the running condition of the vehicle in a real scene can be accurately judged, and after the drive test data passes the verification, the whole off-line flow is completed, and the vehicle can be delivered directly.
In addition, the embodiment of the invention also provides a storage medium, wherein the storage medium is stored with an automatic vehicle off-line sequence, and the automatic vehicle off-line sequence realizes the steps of the automatic vehicle off-line method when being executed by a processor.
Because the storage medium adopts all the technical schemes of all the embodiments, the storage medium has at least all the beneficial effects brought by the technical schemes of the embodiments, and the description is omitted here.
Referring to fig. 5, fig. 5 is a block diagram showing the structure of a first embodiment of the automatic vehicle drop-off device according to the present invention.
As shown in fig. 5, the automatic vehicle offline device provided by the embodiment of the invention includes:
and the scanning module 10 is used for scanning the identification information of the vehicle to be offline so as to establish communication connection with the vehicle to be offline when the vehicle to be offline is required to be offline.
And the acquisition module 20 is used for acquiring the offline verification item of the vehicle to be offline.
And the verification module 30 is used for verifying the vehicle to be off line through the communication connection according to the off line verification project.
And the identifying module 40 is configured to identify that the vehicle to be offline completes the offline process when the verification of the vehicle to be offline passes.
It should be understood that the foregoing is illustrative only and is not limiting, and that in specific applications, those skilled in the art may set the invention as desired, and the invention is not limited thereto.
In this embodiment, when the offline operation needs to be performed on the offline vehicle, the scanning module 10 scans the identification information of the offline vehicle to establish communication connection with the offline vehicle; the acquisition module 20 acquires an offline verification item of the vehicle to be offline; the verification module 30 verifies the vehicle to be offline through the communication connection according to the offline verification item; the identification module 40 identifies that the vehicle to be taken off line completes the process of taking off line when the vehicle to be taken off line passes the verification. Through the mode, production workers do not need professional technical knowledge, the whole process of the offline verification project can be completed only by operating according to the guidance of the application program, and the offline verification project is automatically implemented, so that the labor cost of engineers is greatly reduced while the production efficiency is improved.
It should be noted that the above-described working procedure is merely illustrative, and does not limit the scope of the present invention, and in practical application, a person skilled in the art may select part or all of them according to actual needs to achieve the purpose of the embodiment, which is not limited herein.
In addition, technical details not described in detail in the present embodiment may refer to the automatic vehicle offline method provided in any embodiment of the present invention, which is not described herein.
Referring to fig. 6, fig. 6 is a schematic diagram of a vehicle automatic offline device in a hardware running environment according to an embodiment of the present invention.
As shown in fig. 6, the vehicle automatic offline device may include: a processor 1001, such as a central processing unit (Central Processing Unit, CPU), a communication bus 1002, a user interface 1003, a network interface 1004, a memory 1005. Wherein the communication bus 1002 is used to enable connected communication between these components. The user interface 1003 may include a Display, an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may further include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a Wireless interface (e.g., a Wireless-Fidelity (Wi-Fi) interface). The Memory 1005 may be a high-speed random access Memory (Random Access Memory, RAM) Memory or a stable nonvolatile Memory (NVM), such as a disk Memory. The memory 1005 may also optionally be a storage device separate from the processor 1001 described above.
It will be appreciated by those skilled in the art that the configuration shown in fig. 6 does not constitute a limitation of the vehicle automatic off-line apparatus, and may include more or fewer components than shown, or may combine certain components, or may have a different arrangement of components.
As shown in fig. 6, an operating system, a network communication module, a user interface module, and a vehicle automatic offline program may be included in the memory 1005 as one type of storage medium.
In the vehicle automatic offline device shown in fig. 6, the network interface 1004 is mainly used for data communication with a network server; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 in the vehicle automatic-off-line apparatus of the present invention may be provided in the vehicle automatic-off-line apparatus, which invokes the vehicle automatic-off-line program stored in the memory 1005 through the processor 1001 and performs the following operations:
when the off-line operation of the vehicle to be off-line is required, scanning the identification information of the vehicle to be off-line so as to establish communication connection with the vehicle to be off-line;
acquiring an offline verification item of the vehicle to be offline;
verifying the vehicle to be off line through the communication connection according to the off line verification project;
And when the verification of the vehicle to be off-line passes, the vehicle to be off-line is considered to finish the off-line flow.
Further, the processor 1001 may call the vehicle automatic offline program stored in the memory 1005, and further perform the following operations:
acquiring configuration information of the vehicle to be off line through the communication connection;
generating a system installation instruction and a system configuration script according to the configuration information;
and sending the system installation instruction and the system configuration script to the vehicle to be offline, so that the vehicle to be offline installs an automatic driving system according to the system installation instruction, and configures the automatic driving system according to the system configuration script.
Further, the processor 1001 may call the vehicle automatic offline program stored in the memory 1005, and further perform the following operations:
generating a hardware verification instruction and a hardware verification script according to the offline verification item;
and sending the hardware verification instruction and the hardware verification script to the vehicle to be offline through the communication connection, so that the vehicle to be offline carries out hardware detection on the target hardware equipment according to the hardware verification script, and feeds back the hardware detection result.
Further, the processor 1001 may call the vehicle automatic offline program stored in the memory 1005, and further perform the following operations:
when the hardware detection result passes, generating a system calibration instruction and a preset calibration route according to the offline verification project;
the system calibration instruction and the preset calibration route are sent to the vehicle to be off line, so that the vehicle to be off line runs according to the preset calibration route, and calibration data are recorded;
after the calibration data of the vehicle to be off line is recorded, a calibration parameter generation instruction is sent to enable the vehicle to be off line to determine camera calibration images and inertia unit calibration data according to the calibration data, vehicle body posture data is generated according to the camera calibration images, inertia unit calibration parameters are determined according to the vehicle body posture data and the inertia unit calibration data, laser radar calibration point clouds are determined according to the calibration data, camera object coordinates are determined according to the camera calibration images, laser radar object coordinates are determined according to the laser radar calibration point clouds, millimeter wave radar object coordinates are determined according to the camera object coordinates and the laser radar object coordinates, millimeter wave radar object coordinates are determined according to the millimeter wave radar calibration data, millimeter wave radar calibration parameters are determined according to the laser radar object coordinates, the laser radar calibration parameters and the millimeter wave radar object coordinates, and millimeter wave radar calibration parameters are generated according to the inertia unit calibration parameters, the laser radar calibration parameters and the cloud radar calibration parameters, and the millimeter wave radar calibration parameters are sent to the millimeter wave radar.
Further, the processor 1001 may call the vehicle automatic offline program stored in the memory 1005, and further perform the following operations:
generating a drive test instruction according to the offline verification project;
the road test instruction is sent to the vehicle to be off line so that the vehicle to be off line runs on a preset road, a road test data packet is collected, a road test checking flow is generated, the road test checking flow is fed back, and the road test data packet is sent to the cloud;
and generating a vehicle check report according to the drive test checking flow, and sending the vehicle check report to the cloud.
Further, the processor 1001 may call the vehicle automatic offline program stored in the memory 1005, and further perform the following operations:
transmitting a drive test result acquisition instruction to the cloud so that the cloud determines a signal lamp image and a signal lamp vehicle identification result according to the drive test data packet, converts the signal lamp image into a signal lamp histogram, normalizes the signal lamp histogram to obtain a normalized target image, segments the normalized target image to obtain a color segmentation image, determines geometric features of the color segmentation image, determines a signal lamp region according to the geometric features, obtains a signal lamp identification result according to the signal lamp region, compares the signal lamp identification result with the signal lamp vehicle identification result to obtain a signal lamp judgment result, generates a drive test result according to the signal lamp judgment result, and feeds back the drive test result;
And when the drive test result passes the verification, the vehicle to be off-line is determined to finish the off-line process.
Further, the processor 1001 may call the vehicle automatic offline program stored in the memory 1005, and further perform the following operations:
scanning the identification information of the vehicle to be offline to obtain a key input page;
when an authentication key is received, comparing the authentication key with a preset authentication key;
and after the comparison is passed, establishing communication connection with the vehicle to be off line.
Furthermore, it should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
From the above description of embodiments, it will be clear to a person skilled in the art that the above embodiment method may be implemented by means of software plus a necessary general hardware platform, but may of course also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. Read Only Memory (ROM)/RAM, magnetic disk, optical disk) and comprising several instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method according to the embodiments of the present invention.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.

Claims (8)

1. An automatic vehicle offline method, characterized in that the automatic vehicle offline method comprises the following steps:
When the off-line operation of the vehicle to be off-line is required, scanning the identification information of the vehicle to be off-line so as to establish communication connection with the vehicle to be off-line;
acquiring an offline verification item of the vehicle to be offline;
verifying the vehicle to be off line through the communication connection according to the off line verification project;
when the vehicle to be off-line passes the verification, the vehicle to be off-line is confirmed to finish the off-line flow;
the step of verifying the vehicle to be off line through the communication connection according to the off line verification item comprises the following steps:
generating a hardware verification instruction and a hardware verification script according to the offline verification item;
the hardware verification instruction and the hardware verification script are sent to the vehicle to be offline through the communication connection, so that the vehicle to be offline carries out hardware detection on target hardware equipment according to the hardware verification script, and the hardware detection result is fed back;
after the step of sending the hardware verification instruction and the hardware verification script to the vehicle to be offline through the communication connection, the method further includes:
when the hardware detection result passes, generating a system calibration instruction and a preset calibration route according to the offline verification project;
The system calibration instruction and the preset calibration route are sent to the vehicle to be off line, so that the vehicle to be off line runs according to the preset calibration route, and calibration data are recorded;
after the calibration data of the vehicle to be off line is recorded, a calibration parameter generation instruction is sent to enable the vehicle to be off line to determine camera calibration images and inertia unit calibration data according to the calibration data, vehicle body posture data is generated according to the camera calibration images, inertia unit calibration parameters are determined according to the vehicle body posture data and the inertia unit calibration data, laser radar calibration point clouds are determined according to the calibration data, camera object coordinates are determined according to the camera calibration images, laser radar object coordinates are determined according to the laser radar calibration point clouds, millimeter wave radar object coordinates are determined according to the camera object coordinates and the laser radar object coordinates, millimeter wave radar object coordinates are determined according to the millimeter wave radar calibration data, millimeter wave radar calibration parameters are determined according to the laser radar object coordinates, the laser radar calibration parameters and the millimeter wave radar object coordinates, and millimeter wave radar calibration parameters are generated according to the inertia unit calibration parameters, the laser radar calibration parameters and the cloud radar calibration parameters, and the millimeter wave radar calibration parameters are sent to the millimeter wave radar.
2. The method of claim 1, wherein prior to the step of obtaining the offline verification item for the vehicle to be offline, further comprising:
acquiring configuration information of the vehicle to be off line through the communication connection;
generating a system installation instruction and a system configuration script according to the configuration information;
and sending the system installation instruction and the system configuration script to the vehicle to be offline, so that the vehicle to be offline installs an automatic driving system according to the system installation instruction, and configures the automatic driving system according to the system configuration script.
3. The method of claim 1, wherein after the step of sending the system calibration command and the preset calibration route to the vehicle to be off-line, further comprising:
generating a drive test instruction according to the offline verification project;
the road test instruction is sent to the vehicle to be off line so that the vehicle to be off line runs on a preset road, a road test data packet is collected, a road test checking flow is generated, the road test checking flow is fed back, and the road test data packet is sent to the cloud;
and generating a vehicle check report according to the drive test checking flow, and sending the vehicle check report to the cloud.
4. The method of claim 2, wherein the step of recognizing that the vehicle to be taken off line completes a process of taking off line when the vehicle to be taken off line passes the verification, comprises:
transmitting a drive test result acquisition instruction to the cloud so that the cloud determines a signal lamp image and a signal lamp vehicle identification result according to a drive test data packet, converts the signal lamp image into a signal lamp histogram, normalizes the signal lamp histogram to obtain a normalized target image, segments the normalized target image to obtain a color segmentation image, determines geometric features of the color segmentation image, determines a signal lamp region according to the geometric features, obtains a signal lamp identification result according to the signal lamp region, compares the signal lamp identification result with the signal lamp vehicle identification result to obtain a signal lamp judgment result, generates a drive test result according to the signal lamp judgment result, and feeds back the drive test result;
and when the drive test result passes the verification, the vehicle to be off-line is determined to finish the off-line process.
5. The method according to any one of claims 1 to 4, wherein the step of scanning the identification information of the vehicle to be taken off line to establish a communication connection with the vehicle to be taken off line when the vehicle to be taken off line is required to be taken off line, comprises:
Scanning the identification information of the vehicle to be offline to obtain a key input page;
when an authentication key is received, comparing the authentication key with a preset authentication key;
and after the comparison is passed, establishing communication connection with the vehicle to be off line.
6. An automatic vehicle drop-in device, characterized in that it comprises:
the scanning module is used for scanning the identification information of the vehicle to be offline when the vehicle to be offline is required to be offline, so as to establish communication connection with the vehicle to be offline;
the acquisition module is used for acquiring the offline verification item of the vehicle to be offline;
the verification module is used for verifying the vehicle to be offline through the communication connection according to the offline verification project;
the identifying module is used for identifying that the vehicle to be off-line finishes the off-line flow when the vehicle to be off-line passes the verification;
the verification module is further used for generating a hardware verification instruction and a hardware verification script according to the offline verification item; the hardware verification instruction and the hardware verification script are sent to the vehicle to be offline through the communication connection, so that the vehicle to be offline carries out hardware detection on target hardware equipment according to the hardware verification script, and the hardware detection result is fed back;
The verification module is further used for generating a system calibration instruction and a preset calibration route according to the offline verification project after the hardware detection result passes; the system calibration instruction and the preset calibration route are sent to the vehicle to be off line, so that the vehicle to be off line runs according to the preset calibration route, and calibration data are recorded; after the calibration data of the vehicle to be off line is recorded, a calibration parameter generation instruction is sent to enable the vehicle to be off line to determine camera calibration images and inertia unit calibration data according to the calibration data, vehicle body posture data is generated according to the camera calibration images, inertia unit calibration parameters are determined according to the vehicle body posture data and the inertia unit calibration data, laser radar calibration point clouds are determined according to the calibration data, camera object coordinates are determined according to the camera calibration images, laser radar object coordinates are determined according to the laser radar calibration point clouds, millimeter wave radar object coordinates are determined according to the camera object coordinates and the laser radar object coordinates, millimeter wave radar object coordinates are determined according to the millimeter wave radar calibration data, millimeter wave radar calibration parameters are determined according to the laser radar object coordinates, the laser radar calibration parameters and the millimeter wave radar object coordinates, and millimeter wave radar calibration parameters are generated according to the inertia unit calibration parameters, the laser radar calibration parameters and the cloud radar calibration parameters, and the millimeter wave radar calibration parameters are sent to the millimeter wave radar.
7. An automatic vehicle drop-in apparatus, the apparatus comprising: a memory, a processor, and a vehicle automatic off-line routine stored on the memory and operable on the processor, the vehicle automatic off-line routine configured to implement the vehicle automatic off-line method of any one of claims 1 to 5.
8. A storage medium having stored thereon an automatic vehicle drop-off procedure that when executed by a processor implements the automatic vehicle drop-off method of any one of claims 1 to 5.
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Family Cites Families (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102011077475A1 (en) * 2011-06-14 2012-12-20 Siemens Aktiengesellschaft Method and verification control unit for checking vehicle components
KR102639075B1 (en) * 2016-11-30 2024-02-22 현대자동차주식회사 Diagnostics device for vehicle and method of managing certificate thereof
CN108398932B (en) * 2018-01-09 2020-09-22 深圳市易成自动驾驶技术有限公司 Automatic driving vehicle detection system and method
CN109211585A (en) * 2018-08-31 2019-01-15 汽-大众汽车有限公司 A kind of hybrid vehicle multi-mode driving test method and device
CN109470490B (en) * 2018-10-15 2020-09-08 宁波吉利汽车研究开发有限公司 Vehicle off-line detection system and vehicle detection system
CN109919415A (en) * 2019-01-16 2019-06-21 北京百度网讯科技有限公司 Supervision processing method, apparatus, equipment and storage medium based on unmanned vehicle
CN111983989A (en) * 2019-05-22 2020-11-24 北京新能源汽车股份有限公司 Offline detection method and control equipment
CN111026096B (en) * 2019-12-30 2020-10-30 华人运通(江苏)技术有限公司 Vehicle diagnosis method, apparatus, system, device and computer readable storage medium
CN112590773B (en) * 2020-12-15 2022-08-19 恒大新能源汽车投资控股集团有限公司 Automatic vehicle warehousing method and device, computer equipment and storage medium

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