CN116030545A - Data acquisition method and system, automatic driving controller and mobile device - Google Patents
Data acquisition method and system, automatic driving controller and mobile device Download PDFInfo
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Abstract
The embodiment of the invention relates to a data acquisition method and system, an automatic driving controller and mobile equipment, which can automatically, real-timely and efficiently screen, record, store and display abnormal operation data from operation data generated by an automatic driving vehicle, do not need manual participation and reduce data acquisition cost. The data acquisition system comprises: the automatic driving controller is used for monitoring abnormal events of each algorithm module; generating monitoring data corresponding to the abnormal event; generating a data recording request containing scene description information and recording requirement information; the industrial personal computer records a target topic according to a topic demand list and recording time length in the recording demand information in the data recording request, and generates and stores a local data packet containing the target topic and scene description information; generating basic data information of the data packet according to the scene description information and the recording demand information; and sending the basic data information to a cloud server.
Description
Technical Field
The invention relates to the field of automatic driving, in particular to a data acquisition method, a data acquisition system, an automatic driving controller, an industrial personal computer and mobile equipment.
Background
With the upgrade of the automatic driving industry, a large number of automatic driving vehicles are put into test, mileage accumulation or operation use, etc., and the operation data generated by the automatic driving vehicles under various operation scenes is very huge, and some abnormal operation data which is inconsistent with expectations may exist in the operation data, for example, manual takeover, obstacle false detection and the like caused by exceeding the current system operation design domain, and the abnormal operation data has very important reference value for automatic driving algorithm feedback or scene library establishment, so how to acquire valuable abnormal operation data from the operation data of the automatic driving vehicles put into test and operation is very important.
Currently, a main mode of acquiring abnormal operation data of an automatic driving vehicle is that a tester observes whether the automatic driving vehicle has abnormal behaviors on site, records operation data corresponding to the abnormal behaviors when determining that the automatic driving vehicle has the abnormal behaviors, and records and stores the operation data as the abnormal data. The accuracy of the abnormal data recorded by the manual operation depends on experience and professional ability of testers, different testers can cause standard inconsistency of the abnormal data recorded by different testers due to difference of experience and professional ability, and abnormal conditions can not be observed in external appearance of an automatic driving vehicle, so that the problem of abnormal data missing detection can exist; in addition, the number of the automatic driving vehicles put into test operation is huge, and a large amount of manpower resources are required to be put into the manual recording mode, so that the cost is high.
Disclosure of Invention
The invention aims at overcoming the defects of the prior art, and provides a data acquisition method and system, which can automatically, real-timely and efficiently screen, record, store and display abnormal operation data from operation data generated by an automatic driving vehicle, do not need to be manually participated, and reduce data acquisition cost.
To achieve the above object, according to a first aspect of the embodiments of the present invention, there is provided a data acquisition system, including:
the automatic driving controller is used for monitoring abnormal events of each algorithm module, wherein the abnormal events comprise events of abnormal upstream data of each algorithm module and events of abnormal operation of each algorithm module; generating monitoring data corresponding to the abnormal event; acquiring corresponding scene description information and recording demand information according to the monitoring data, generating a data recording request containing the scene description information and the recording demand information, and transmitting the data recording request to an industrial personal computer;
the industrial personal computer is used for recording a target topic according to a topic demand list and recording time length in the recording demand information in the data recording request when receiving the data recording request, and generating and storing a local data packet containing the target topic and scene description information; generating basic data information of the data packet according to the scene description information and the recording demand information; the basic data information is sent to a cloud server;
and the cloud server receives and displays the basic data information.
In a second aspect of the embodiment of the present invention, a data acquisition method is provided, where the method includes:
monitoring abnormal events of each algorithm module, wherein the abnormal events comprise events of upstream data abnormality of each algorithm module and events of abnormality occurrence in the running process of each algorithm module;
generating monitoring data corresponding to the abnormal event;
acquiring corresponding scene description information and recording demand information according to the monitoring data, and generating a data recording request containing the scene description information and the recording demand information;
recording a target topic according to a topic demand list and recording time length in the recording demand information in the data recording request, and generating and storing a local data packet containing the target topic and scene description information; generating basic data information of the data packet according to the scene description information and the recording demand information; and outputting the basic data information.
In a third aspect of the embodiment of the present invention, there is provided an autopilot controller comprising:
the abnormal event monitoring module is used for monitoring abnormal events of the algorithm modules, wherein the abnormal events comprise events of abnormal upstream data of the algorithm modules and events of abnormal operation of the algorithm modules;
the monitoring data generation module is used for generating monitoring data corresponding to the abnormal event;
the service platform is used for acquiring corresponding scene description information and recording requirement information according to the monitoring data, generating a data recording request containing the scene description information and the recording requirement information, and outputting the data recording request.
In a fourth aspect of the embodiment of the present invention, another automatic driving controller is provided, in a processing chip provided with algorithm modules, an abnormal event monitoring sub-module and a monitoring data generating sub-module corresponding to each algorithm module are provided for each algorithm module;
the abnormal event monitoring sub-module is used for monitoring abnormal events of the corresponding target algorithm module, wherein the abnormal events comprise events of the upstream data abnormality of the target algorithm module and events of the abnormality occurrence in the running process of the target algorithm module;
the monitoring data generation sub-module is used for generating monitoring data corresponding to the abnormal event monitored by the abnormal event monitoring sub-module of the corresponding target algorithm module and sending the monitoring data to the service platform;
the service platform is used for acquiring corresponding scene description information and recording requirement information according to the monitoring data, generating a data recording request containing the scene description information and the recording requirement information, and outputting the data recording request. .
In a fifth aspect of the embodiment of the present invention, an industrial personal computer is provided, including:
the communication module is used for receiving the data recording request and sending the data recording request to the data recording module;
the data recording module is used for recording a target topic according to a topic demand list and recording time length in the recording demand information in the data recording request, and generating and storing a local data packet containing the target topic and scene description information; and generating basic data information of the data packet according to the scene description information and the recording demand information, and outputting the basic data information through the communication module.
According to a sixth aspect of embodiments of the present invention, there is provided a mobile device, the mobile device including the autopilot controller provided in the foregoing third or fourth aspect, and/or an industrial personal computer as provided in the fifth aspect.
According to the technical scheme, through the automatic driving controller, the cloud server or the automatic driving controller, the industrial personal computer and the cloud server, abnormal operation data can be automatically, effectively screened, recorded, stored and displayed from operation data generated by an automatic driving vehicle in real time, the whole process is automatically completed without manual participation, the data acquisition cost is reduced, the professional capability and experience of a tester are not relied on, the acquired data is comprehensive and accurate, and the problem of false detection missing is avoided.
Drawings
FIG. 1 is a schematic diagram of a data acquisition system according to an embodiment of the present invention;
FIG. 2 is a second schematic diagram of a data acquisition system according to the first embodiment of the present invention;
FIG. 3 is a diagram illustrating a monitoring data ID according to a first embodiment of the present invention;
FIG. 3A is a diagram showing a specific example of the monitoring data ID according to the first embodiment of the present invention;
fig. 4 is a schematic diagram of scene description information according to a first embodiment of the present invention;
fig. 5 is a schematic diagram of recording requirement information according to a first embodiment of the present invention;
FIG. 6 is a schematic diagram of a data acquisition system according to a first embodiment of the present invention;
FIG. 7 is a schematic diagram of an autopilot controller according to one embodiment of the present invention;
FIG. 8 is a second schematic diagram of an autopilot controller in accordance with one embodiment of the present invention;
fig. 9 is a specific example of a service platform acquiring scene description information and recording requirement information in the first embodiment of the present invention;
FIG. 10 is a schematic diagram of an industrial personal computer according to an embodiment of the present invention;
fig. 11 is a flowchart of a data acquisition method in the second embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail below with reference to the accompanying drawings, and it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Example 1
Referring to fig. 1, a schematic structural diagram of a data acquisition system provided in an embodiment of the present invention, where the data acquisition system includes an autopilot controller 1 and a cloud server 2, where the autopilot controller 1 and the cloud server 2 may be connected by wireless communication, and the autopilot controller 1 may be disposed on a mobile device having an autopilot function, where the type of the mobile device is not strictly limited, and is not specifically exemplified herein. In fig. 1, a mobile device is taken as an example of a passenger car. Wherein:
the automatic driving controller 1 is used for monitoring abnormal events of each algorithm module, wherein the abnormal events comprise events of abnormal upstream data of each algorithm module and events of abnormal operation of each algorithm module; generating monitoring data corresponding to the abnormal event; acquiring corresponding scene description information and recording demand information according to the monitoring data; recording a target topic according to the topic demand list and the recording time length in the recording demand information, and generating and storing a local data packet containing the target topic and scene description information; generating basic data information of the data packet according to the scene description information and the recording demand information, and sending the basic data information of the data packet to a cloud server 2;
and the cloud server 2 receives and displays the basic data information.
In an alternative embodiment, in order to minimize other negative effects between the data acquisition system and the autopilot system, in addition to the normal transmission trigger request function, the data recording function, which is independent of the normal operation of the autopilot system, is split off, so that the data recording function is independently adapted to the industrial personal computer. As shown in fig. 2, another data acquisition system is schematically shown, and the data acquisition system includes:
the automatic driving controller 1A is configured to monitor abnormal events of each algorithm module, where the abnormal events include an event that upstream data of each algorithm module is abnormal and an event that abnormality occurs in an operation process of each algorithm module; generating monitoring data corresponding to the abnormal event; acquiring corresponding scene description information and recording demand information according to the monitoring data, generating a data recording request containing the scene description information and the recording demand information, and transmitting the data recording request to an industrial personal computer 3;
the industrial personal computer 3 is used for recording a target topic according to a topic demand list and recording time length in the recording demand information in the data recording request and generating and storing a local data packet containing the target topic and scene description information when receiving the data recording request; generating basic data information of the data packet according to the scene description information and the recording demand information; the basic data information is sent to a cloud server 2;
and the cloud server 2 receives and displays the basic data information.
In a preferred embodiment, the generating of the monitoring data corresponding to the abnormal event specifically includes: and generating monitoring data comprising algorithm module identity information, child node identity information, abnormal event description information and abnormal event type for generating the abnormal event according to a preset data format.
The monitoring data may be a message data.
In order to improve the expansibility and suitability of the data acquisition and recording function, in the embodiment of the present invention, the monitoring data may be set to a monitoring data ID with a unique number, where the monitoring data ID may be a 16-ary number (0 x0000-0 xFFFF), as shown in fig. 3, a first bit of the monitoring data ID corresponds to identity information of an algorithm module (for example, the identity information may be a name or a number of the algorithm module), a second bit corresponds to identity information of a child node under the algorithm module (for example, a name of a child node generating the abnormal event in the algorithm module), a third bit corresponds to an abnormal event type, and a fourth bit corresponds to abnormal event description information. For example, 0x1000 represents a timeout for the laser node of the perception module to report the top lidar receive data, as shown in fig. 3A.
In an optional embodiment, a corresponding relationship between the monitoring data and the scene description information and the recording requirement information may be preset, and the acquiring the corresponding scene description information and recording requirement information according to the monitoring data specifically includes: and acquiring scene description information and recording requirement information corresponding to the monitoring data from the preset corresponding relation between the monitoring data and the scene description information and recording requirement information. The corresponding relation may be a corresponding relation between the monitoring data ID and the scene description information, and the recording requirement information, and the representation form of the corresponding relation may be a list, a tree structure, etc., which is not strictly limited in the application.
In the embodiment of the invention, the recording requirement information comprises a topic requirement list, recording duration and a storage path; recording a target topic according to a topic demand list and recording time length in the recording demand information in the data recording request, and generating and storing a local data packet containing the target topic and scene description information, wherein the method specifically comprises the following steps: determining a target topic from the topic demand list according to the recording time length, and recording the target topic; and packaging the target topic and the scene description information to generate a local data packet, and storing the local data packet according to the storage path.
In some embodiments, the scene description information may include information of scene description, scene tags, mobile device parameters, map names, and the like. Taking the foregoing monitoring data as 0x1000 as an example, the scene description information in the monitoring data is as shown in fig. 4:
scene description: the top laser radar receives the overtime data;
scene tag: sensing node, sensor failure and timeout failure;
mobile device parameters: IDPXJ000001;
map name: map001.
In some embodiments, the recording requirement information may include a topic requirement list, a storage path, and a recording duration (e.g., the first 60s and the last 10s of the time when the data recording request is received) as shown in fig. 5.
In the embodiment of the present invention, the algorithm module is disposed in the autopilot controller 1, and the algorithm module may include, but is not limited to, one or more of the following: the system comprises a positioning module, a sensing module, a decision module, a control module, a prediction module and the like.
In the embodiment of the invention, the collected data of the abnormal event can be divided into dominant safety data and invisible optimization data, wherein the dominant safety data can be data capable of directly reflecting the automatic driving performance, such as unreasonable braking, manual taking over of a driver and the like; the invisible optimized data may refer to time when the downstream algorithm module finds abnormality when calibrating the upstream data transmitted by the upstream algorithm module, such as data timeout, unstable detection result, etc., while the overall driving performance is good.
In the embodiment of the invention, the data sources of the abnormal events are divided into two types, one type is automatic mining, and the abnormal events are found by utilizing mutual checking among different algorithm modules of an automatic driving system, different moments of the same algorithm module and parallel threads. The downstream algorithm module checks whether the upstream algorithm module outputs a result that is timeout (the difference between the timestamp of the last frame of data received and the system time exceeds a threshold). For example, if the laser detection result and the visual detection result in the sensing module are different, an abnormality is confirmed if the laser detection result and the visual detection result are different. For example, for the same frame, abnormality is confirmed if the laser detection result is different from the type of obstacle obtained by visual detection. For example, if the difference between the prediction result of the prediction module and the real result is large, the abnormality is confirmed, for example, the difference between the position of an obstacle in the prediction result of the prediction module at the time t and the real position of the obstacle obtained at the time t+1 is large. Another type is manual teaching, for example, in the case that the automatic driving controller operates normally, the decision result output by the decision module is judged to be different from the corresponding operation manually driven by the driver to judge whether the vehicle is abnormal, for example, the decision result is that the vehicle is followed, and the actual operation of the driver is that the vehicle overtakes the lane change, and the vehicle is considered to be abnormal.
Preferably, the industrial personal computer 3 can communicate with the board card of the automatic driving controller 1A by adopting a tera Ethernet interface so as to realize the automatic online data acquisition and the hardware and data isolation of the automatic driving controller 1A. As shown in fig. 6, the algorithm modules in the autopilot controller 1A are distributed over a plurality of processing chips; each processing chip can transmit data through the gigabit Ethernet interface; the industrial personal computer 3 can perform data transmission through a tera Ethernet interface.
In one embodiment, as shown in fig. 7, the autopilot controller 1A is divided into functions, and may include an abnormal event monitoring module 11, a monitoring data generating module 12, and a service platform 13, wherein:
the abnormal event monitoring module 11 is configured to monitor abnormal events of each algorithm module, where the abnormal events include an event that upstream data of each algorithm module is abnormal and an event that an abnormality occurs in an operation process of each algorithm module;
a monitoring data generation module 12 for generating monitoring data corresponding to the abnormal event;
and the service platform 13 is used for acquiring corresponding scene description information and recording requirement information according to the monitoring data, generating a data recording request containing the scene description information and the recording requirement information, and outputting the data recording request.
In another embodiment, as shown in fig. 8, the automatic driving controller 1 includes a service platform 13, in a processing chip provided with algorithm modules, for each algorithm module, an abnormal event monitoring sub-module and a monitoring data generating sub-module corresponding to the algorithm module are provided;
the abnormal event monitoring sub-module is used for monitoring abnormal events of the corresponding target algorithm module, wherein the abnormal events comprise events of the upstream data abnormality of the target algorithm module and events of the abnormality occurrence in the running process of the target algorithm module;
the monitoring data generation sub-module is used for generating monitoring data corresponding to the abnormal event monitored by the abnormal event monitoring sub-module of the corresponding target algorithm module and sending the monitoring data to the service platform;
and the service platform 13 is used for acquiring corresponding scene description information and recording requirement information according to the monitoring data, generating a data recording request containing the scene description information and the recording requirement information, and outputting the data recording request. .
Taking the monitoring data ID of 0x1000 as an example, the service platform 13 obtains scene description information and recording requirement information according to the monitoring data ID as shown in fig. 9.
The structure of the industrial personal computer 3 in the embodiment of the present invention is shown in fig. 10, and includes:
the communication module 31 is configured to receive a data recording request and send the data recording request to the data recording module 32;
a data recording module 32, configured to record a target topic according to a topic requirement list and a recording duration in the recording requirement information in the data recording request, and generate and store a local data packet containing the target topic and scene description information; and generating basic data information of the data packet according to the scene description information and the recording demand information, and outputting the basic data information through the communication module.
The basic data information may include information such as a name of a local data packet, a size and a storage location of the local data packet, a mobile device ID, scene description information, and the like.
The cloud server 2 can display the basic data information according to the information in the basic data information in a classified mode, and can be checked and downloaded by a user.
According to the technical scheme, the data of the automatic driving mobile equipment in abnormal conditions in the running process can be automatically screened, recorded, stored and displayed, on one hand, the data corresponding to abnormal events of the algorithm module can be timely and comprehensively monitored, important data loss or hiding with reference value is avoided, and basic data is provided for the follow-up utilization of collected data feedback algorithm, reconstruction scene simulation debugging algorithm function and parameters so as to promote each algorithm module of automatic driving; on the other hand, the running state of a large amount of mobile equipment can be monitored on line to this scheme, and automatic acquisition screening data need not artifical the participation, uses manpower sparingly cost, also can not lead to because of different personnel because of professional ability, experience difference the inconsistent problem of collection data standard.
Example two
Based on the same inventive concept as the first embodiment, a second embodiment of the present invention further provides a data acquisition method, where a flow of the method is shown in fig. 11, and the method includes:
and 100, monitoring abnormal events of each algorithm module, wherein the abnormal events comprise events of upstream data abnormality of each algorithm module and events of abnormality in the running process of each algorithm module.
And 110, generating monitoring data corresponding to the abnormal event.
And 130, recording a target topic according to the topic demand list and the recording time length in the recording demand information in the data recording request, and generating and storing a local data packet containing the target topic and the scene description information.
And 140, generating basic data information of the data packet according to the scene description information and the recording requirement information, and outputting the basic data information.
Preferably, in the foregoing step 110, the generating monitoring data corresponding to the abnormal event specifically includes: and generating monitoring data comprising algorithm module identity information, child node identity information, abnormal event description information and abnormal event type for generating the abnormal event according to a preset data format.
Preferably, in the foregoing step 120, the obtaining corresponding scene description information and recording requirement information according to the monitoring data specifically includes: and acquiring scene description information and recording requirement information corresponding to the monitoring data from the preset corresponding relation between the monitoring data and the scene description information and recording requirement information.
Preferably, the recording requirement information comprises a topic requirement list, a recording duration and a storage path; in step 130, a target topic is recorded according to the topic requirement list and the recording duration in the recording requirement information in the data recording request, and a local data packet including the target topic and the scene description information is generated and stored, which specifically includes: determining a target topic from the topic demand list according to the recording time length, and recording the target topic; and packaging the target topic and the scene description information to generate a local data packet, and storing the local data packet according to the storage path.
Example III
An embodiment of the present invention provides a mobile device, where any one of the autopilot controllers provided in the embodiment one is disposed on the mobile device.
The mobile device may be any device capable of performing an autopilot function, such as a vehicle (passenger car, dolly, bus, sweeper, sanitation car, floor cleaning car, dust suction car, mopping machine, patrol car, van, semitrailer, etc.), robot, sweeper, AGV, etc. And are not listed here.
It should be noted that, it should be understood that the division of the modules of the above apparatus is merely a division of a logic function, and may be fully or partially integrated into a physical entity or may be physically separated. And these modules may all be implemented in software in the form of calls by the processing element; or can be realized in hardware; the method can also be realized in a form of calling software by a processing element, and the method can be realized in a form of hardware by a part of modules. For example, the determining module may be a processing element that is set up separately, may be implemented in a chip of the above apparatus, or may be stored in a memory of the above apparatus in the form of program code, and may be called by a processing element of the above apparatus and execute the functions of the determining module. The implementation of the other modules is similar. In addition, all or part of the modules can be integrated together or can be independently implemented. The processing element described herein may be an integrated circuit having signal processing capabilities. In implementation, each step of the above method or each module above may be implemented by an integrated logic circuit of hardware in a processor element or an instruction in a software form.
For example, the modules above may be one or more integrated circuits configured to implement the methods above, such as: one or more specific integrated circuits (Application Specific Integrated Circuit, ASIC), or one or more microprocessors (Digital Signal Processor, DSP), or one or more field programmable gate arrays (Field Programmable Gate Array, FPGA), or the like. For another example, when a module above is implemented in the form of a processing element scheduler code, the processing element may be a general purpose processor, such as a central processing unit (Central Processing Unit, CPU) or other processor that may invoke the program code. For another example, the modules may be integrated together and implemented in the form of a System-on-a-chip (SOC).
In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, produces, in whole or in part, the procedures or functions described in accordance with embodiments of the present application. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wired (e.g., coaxial cable, fiber optic, digital subscriber line ((Digital Subscriber Line, DSL)), or wireless (e.g., infrared, wireless, bluetooth, microwave, etc.) means, the computer-readable storage medium may be any available medium that can be accessed by the computer or a data storage device such as a server, data center, etc., that contains an integration of one or more available media, the available media may be magnetic media (e.g., floppy disk, hard disk, tape), optical media (e.g., DVD), or semiconductor media (e.g., solid state disk, SSD), etc.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative elements and steps are described above generally in terms of function in order to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied in hardware, in a software module executed by a processor, or in a combination of the two. The software modules may be disposed in Random Access Memory (RAM), memory, read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM power system control method, or any other form of storage medium known in the art.
The foregoing description of the embodiments has been provided for the purpose of illustrating the general principles of the invention, and is not meant to limit the scope of the invention, but to limit the invention to the particular embodiments, and any modifications, equivalents, improvements, etc. that fall within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (12)
1. A data acquisition system, the system comprising:
the automatic driving controller is used for monitoring abnormal events of each algorithm module, wherein the abnormal events comprise events of abnormal upstream data of each algorithm module and events of abnormal operation of each algorithm module; generating monitoring data corresponding to the abnormal event; acquiring corresponding scene description information and recording demand information according to the monitoring data, generating a data recording request containing the scene description information and the recording demand information, and transmitting the data recording request to an industrial personal computer;
the industrial personal computer is used for recording a target topic according to a topic demand list and recording time length in the recording demand information in the data recording request when receiving the data recording request, and generating and storing a local data packet containing the target topic and scene description information; generating basic data information of the data packet according to the scene description information and the recording demand information; the basic data information is sent to a cloud server;
and the cloud server receives and displays the basic data information.
2. The system of claim 1, wherein the autopilot controller generates monitoring data corresponding to the abnormal event, specifically comprising:
and generating monitoring data comprising algorithm module identity information, child node identity information, abnormal event description information and abnormal event type for generating the abnormal event according to a preset data format.
3. The system according to claim 1, wherein the automatic driving controller obtains corresponding scene description information and recording requirement information according to the monitoring data, and specifically includes:
and acquiring scene description information and recording requirement information corresponding to the monitoring data from the preset corresponding relation between the monitoring data and the scene description information and recording requirement information.
4. The system of claim 1, wherein the recording requirement information comprises a topic requirement list, a recording duration, and a storage path;
recording a target topic according to a topic demand list and recording time length in the recording demand information in the data recording request, and generating and storing a local data packet containing the target topic and scene description information, wherein the method specifically comprises the following steps:
determining a target topic from the topic demand list according to the recording time length, and recording the target topic; and packaging the target topic and the scene description information to generate a local data packet, and storing the local data packet according to the storage path.
5. The system of claim 1, wherein the algorithm modules in the autopilot controller are distributed on at least one processing chip;
each processing chip performs data transmission through a gigabit Ethernet interface;
and the industrial personal computer performs data transmission through the tera Ethernet interface.
6. A data acquisition system, the system comprising:
the automatic driving controller monitors abnormal events of each algorithm module, wherein the abnormal events comprise events of upstream data abnormality of each algorithm module and events of abnormality in the running process of each algorithm module; generating monitoring data corresponding to the abnormal event; acquiring corresponding scene description information and recording demand information according to the monitoring data; recording a target topic according to the topic demand list and the recording time length in the recording demand information, and generating and storing a local data packet containing the target topic and scene description information; generating basic data information of the data packet according to the scene description information and the recording demand information, and sending the basic data information of the data packet to a cloud server;
and the cloud server receives and displays the basic data information.
7. A method of data acquisition, the method comprising:
monitoring abnormal events of each algorithm module, wherein the abnormal events comprise events of upstream data abnormality of each algorithm module and events of abnormality occurrence in the running process of each algorithm module;
generating monitoring data corresponding to the abnormal event;
acquiring corresponding scene description information and recording demand information according to the monitoring data, and generating a data recording request containing the scene description information and the recording demand information;
recording a target topic according to a topic demand list and recording time length in the recording demand information in the data recording request, and generating and storing a local data packet containing the target topic and scene description information; generating basic data information of the data packet according to the scene description information and the recording demand information; and outputting the basic data information.
8. The method of claim 7, wherein the recording requirement information includes a topic requirement list, a recording duration, and a storage path;
recording a target topic according to a topic demand list and recording time length in the recording demand information in the data recording request, and generating and storing a local data packet containing the target topic and scene description information, wherein the method specifically comprises the following steps:
determining a target topic from the topic demand list according to the recording time length, and recording the target topic; and packaging the target topic and the scene description information to generate a local data packet, and storing the local data packet according to the storage path.
9. An autopilot controller comprising:
the abnormal event monitoring module is used for monitoring abnormal events of the algorithm modules, wherein the abnormal events comprise events of abnormal upstream data of the algorithm modules and events of abnormal operation of the algorithm modules;
the monitoring data generation module is used for generating monitoring data corresponding to the abnormal event;
the service platform is used for acquiring corresponding scene description information and recording requirement information according to the monitoring data, generating a data recording request containing the scene description information and the recording requirement information, and outputting the data recording request.
10. An automatic driving controller is characterized in that in a processing chip provided with algorithm modules, an abnormal event monitoring sub-module and a monitoring data generating sub-module corresponding to each algorithm module are arranged for each algorithm module;
the abnormal event monitoring sub-module is used for monitoring abnormal events of the corresponding target algorithm module, wherein the abnormal events comprise events of the upstream data abnormality of the target algorithm module and events of the abnormality occurrence in the running process of the target algorithm module;
the monitoring data generation sub-module is used for generating monitoring data corresponding to the abnormal event monitored by the abnormal event monitoring sub-module of the corresponding target algorithm module and sending the monitoring data to the service platform;
the service platform is used for acquiring corresponding scene description information and recording requirement information according to the monitoring data, generating a data recording request containing the scene description information and the recording requirement information, and outputting the data recording request.
11. An industrial personal computer, characterized by comprising:
the communication module is used for receiving the data recording request and sending the data recording request to the data recording module;
the data recording module is used for recording a target topic according to a topic demand list and recording time length in the recording demand information in the data recording request, and generating and storing a local data packet containing the target topic and scene description information; and generating basic data information of the data packet according to the scene description information and the recording demand information, and outputting the basic data information through the communication module.
12. A mobile device comprising an autopilot controller according to claim 9 or 10 and/or an industrial personal computer according to claim 10.
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