CN115439957A - Intelligent driving data acquisition method, acquisition device, acquisition equipment and computer readable storage medium - Google Patents
Intelligent driving data acquisition method, acquisition device, acquisition equipment and computer readable storage medium Download PDFInfo
- Publication number
- CN115439957A CN115439957A CN202211117297.0A CN202211117297A CN115439957A CN 115439957 A CN115439957 A CN 115439957A CN 202211117297 A CN202211117297 A CN 202211117297A CN 115439957 A CN115439957 A CN 115439957A
- Authority
- CN
- China
- Prior art keywords
- data acquisition
- vehicle
- data
- rule
- intelligent driving
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 36
- 230000008447 perception Effects 0.000 claims abstract description 33
- 238000013480 data collection Methods 0.000 claims description 36
- 238000004590 computer program Methods 0.000 claims description 12
- 238000004891 communication Methods 0.000 claims description 10
- 238000012800 visualization Methods 0.000 claims description 10
- 230000008569 process Effects 0.000 claims description 6
- 238000005259 measurement Methods 0.000 claims description 4
- 238000012545 processing Methods 0.000 claims description 3
- 238000012216 screening Methods 0.000 claims description 3
- 230000000007 visual effect Effects 0.000 claims description 3
- 238000007726 management method Methods 0.000 description 29
- 230000005540 biological transmission Effects 0.000 description 6
- 238000010586 diagram Methods 0.000 description 4
- 230000006870 function Effects 0.000 description 4
- 238000012790 confirmation Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 239000000835 fiber Substances 0.000 description 2
- 230000007246 mechanism Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 238000012549 training Methods 0.000 description 2
- 230000009471 action Effects 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000010267 cellular communication Effects 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 230000014509 gene expression Effects 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/08—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
- G07C5/0841—Registering performance data
- G07C5/085—Registering performance data using electronic data carriers
- G07C5/0866—Registering performance data using electronic data carriers the electronic data carrier being a digital video recorder in combination with video camera
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16Y—INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS [IoT]
- G16Y40/00—IoT characterised by the purpose of the information processing
- G16Y40/10—Detection; Monitoring
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
Abstract
The invention relates to an intelligent driving data acquisition method, an intelligent driving data acquisition device, intelligent driving data acquisition equipment and a computer readable storage medium. The intelligent driving data acquisition method comprises the following steps of S1, editing data acquisition requirements at a local end, and generating data acquisition rules based on the data acquisition requirements; s2, issuing the data acquisition rule to a cloud issuing platform, and issuing the data acquisition rule to a specified vehicle through the cloud issuing platform according to the data acquisition rule; s3, adding or updating the data acquisition rule by the vehicle; s4, the vehicle acquires perception data based on a scene recognition algorithm; and S5, the vehicle sends the acquired sensing data to a data center. The invention provides an intelligent driving data acquisition method, an intelligent driving data acquisition device, intelligent driving data acquisition equipment and a computer readable storage medium, which can effectively acquire perception data of a vehicle.
Description
Technical Field
The invention relates to the technical field of vehicle big data, in particular to an intelligent driving data acquisition method, an intelligent driving data acquisition device, intelligent driving data acquisition equipment and a computer readable storage medium.
Background
Almost all host plants and intelligent driving scheme suppliers in the world try to acquire intelligent driving data, and develop more reliable and more comfortable intelligent driving functions by continuously training the data and improving the algorithm performance of intelligent driving. The vehicle big data is a source for improving the performance and functional experience of intelligent driving software.
The current mainstream method for acquiring intelligent driving data is to deploy a series of intelligent driving sensors on one or more vehicles (hereinafter referred to as vehicle ends), wherein the intelligent driving sensors comprise cameras, millimeter wave radars, laser radars, ultrasonic radars, inertial Measurement Units (IMUs), wheel speed sensors, high-precision positioning and the like, and are used for sensing environmental information and data (including peripheral vehicles, pedestrians, obstacles, lane lines, traffic lights, passable areas and the like) where the vehicles are located. And then the information is collected and stored in real time and is transmitted to a data center in a wireless network mode. As the number of on-board sensors increases, the data collected per unit time becomes more and more voluminous, and the storage capacity of the data center is more and more challenging. Furthermore, as the maturity of software algorithms continues to increase, more extreme scenarios (corner cases) are required for algorithm training, rather than a large number of normal scenarios (normal cases) to improve performance. This also means that the efficiency of vehicle-side data acquisition becomes lower and lower over time, and the exploration of limited data scenarios becomes more and more difficult. Therefore, how to find an intelligent driving data acquisition method capable of reducing cost and improving efficiency is one of the hot spots of current research.
Disclosure of Invention
In view of the above problems in the prior art, the present invention provides an intelligent driving data collection method, a collection device, and a computer-readable storage medium, which can effectively collect the sensing data of a vehicle.
Specifically, the invention provides an intelligent driving data acquisition method, which comprises the following steps:
s1, editing a data acquisition requirement at a local end, and generating a data acquisition rule based on the data acquisition requirement, wherein the data acquisition is used for acquiring sensing data of an intelligent driving sensor at a vehicle end, the data acquisition requirement is used for meeting various requirements of an acquisition scene, and the data acquisition rule is a rule set of data acquisition corresponding to the various requirements;
s2, issuing the data acquisition rule to a cloud issuing platform, and issuing the data acquisition rule to a specified vehicle through the cloud issuing platform according to the data acquisition rule;
s3, adding or updating the data acquisition rule by the vehicle;
s4, the vehicle acquires sensing data of a collection scene matched with the data collection rule based on a scene recognition algorithm, wherein the scene recognition algorithm is used for recognizing whether a scene environment where the vehicle is located is matched with the collection scene matched with the data collection rule according to the sensing data of the intelligent driving sensor at the vehicle end;
and S5, the vehicle sends the acquired sensing data to a data center.
According to an embodiment of the invention, in step S1, the vehicle-end intelligent driving sensor at least comprises a vehicle-mounted camera, a millimeter wave radar, a laser radar, an ultrasonic radar, an inertial measurement unit IMU, a wheel speed sensor and a high-precision positioning sensor, and the perception data at least comprises an image, a point cloud, a radar echo, a vehicle position, a speed, a vehicle target, a pedestrian, an obstacle, a lane line, a traffic light, passable area information and related attributes acquired by the vehicle-end intelligent driving sensor.
According to an embodiment of the present invention, in step S4, the process of the vehicle acquiring the perception data includes the steps of:
recording sensing data of all vehicle-end intelligent driving sensors in a full quantity manner;
and screening the perception data based on the scene recognition algorithm, and acquiring the perception data matched with the acquisition scene of the data acquisition rule.
According to an embodiment of the present invention, in step S4, the process of the vehicle acquiring the perception data includes the steps of:
analyzing whether the scene environment of the vehicle is matched with the acquisition scene matched with the data acquisition rule or not based on the scene identification algorithm;
if the vehicle-end intelligent driving sensor is matched with the vehicle-end intelligent driving sensor, recording sensing data of the corresponding vehicle-end intelligent driving sensor according to a data acquisition rule; if not, stopping recording.
According to an embodiment of the invention, in step S5, the vehicle directly transmits the acquired sensing data to the data center, or transmits the stored sensing data to the data center after storing the sensing data.
The invention also provides an intelligent driving data acquisition device, which comprises:
the system comprises a local terminal module, a data acquisition module and a data processing module, wherein the local terminal module is used for editing data acquisition requirements and generating data acquisition rules based on the data acquisition requirements, the data acquisition requirements refer to the acquisition of sensing data of an intelligent driving sensor at a vehicle end, the data acquisition requirements refer to the data acquisition requirements which meet various requirements of an acquisition scene, and the data acquisition rules are a rule set of data acquisition corresponding to the various requirements;
the cloud terminal sub-module is used for receiving and storing the data acquisition rule generated by the local terminal sub-module and issuing the data acquisition rule to a vehicle specified according to the data acquisition rule;
the vehicle terminal module is arranged on the vehicle and used for receiving the data acquisition rule issued by the cloud terminal module and adding or updating the data acquisition rule; acquiring sensing data of an acquisition scene matched with the data acquisition rule based on a scene identification algorithm, wherein the scene identification algorithm is used for identifying whether a scene environment where the vehicle is located is matched with the acquisition scene matched with the data acquisition rule according to the sensing data of the intelligent driving sensor at the vehicle end;
and the data center submodule is used for receiving the perception data acquired by the vehicle terminal submodule.
According to one embodiment of the invention, the local terminal module comprises a vehicle information visualization interface and a rule editing visualization interface;
the vehicle information visualization interface is used for displaying vehicle information, the vehicle information comprises the position of a vehicle and the current data acquisition state, the vehicle terminal module reports the vehicle information to the cloud terminal module, and the local terminal module acquires the vehicle information through the cloud terminal module;
the rule editing visual interface is used for editing the data acquisition rule matching.
According to one embodiment of the invention, the cloud terminal sub-module comprises a vehicle management module, a rule storage module and a rule issuing module;
the vehicle management module is used for managing the vehicle information;
the rule storage module is used for storing the received data acquisition rule;
the rule issuing module is used for issuing the data acquisition rule to the appointed vehicle.
According to one embodiment of the invention, the vehicle terminal module comprises a communication management module, a rule management module, a recording management module and a human-computer interface;
the communication management module is used for reporting the vehicle information to the cloud terminal sub-module, receiving a data acquisition rule sent by the cloud terminal sub-module and forwarding the data acquisition rule to the rule management module;
the rule management module updates, stores and synchronizes the data acquisition rule to the recording management module and the human-computer interface;
the recording management module records the perception data of the acquisition scene matched with the data acquisition rule based on the scene identification algorithm; the recording management module supports a manual recording mode and an automatic recording mode, the manual recording mode refers to the mode that sensing data of all vehicle-end intelligent driving sensors are recorded in a full scale, then the sensing data are screened based on a scene recognition algorithm, and sensing data matched with the collection scene of the data collection rule are obtained; the automatic recording mode is used for analyzing whether the scene environment of the vehicle is matched with the acquisition scene matched with the data acquisition rule or not based on a scene recognition algorithm, if so, recording the sensing data of the corresponding vehicle-end intelligent driving sensor according to the data acquisition rule, and if not, stopping recording;
the human-computer interface is used for displaying the collecting and recording state, the data collecting rule and providing a recording mode switching button, and the recording mode switching button is used for switching between a manual recording mode and an automatic recording mode.
The invention also provides intelligent driving data acquisition equipment which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor realizes the steps of the intelligent driving data acquisition method provided by the invention when executing the computer program.
The present invention also provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the intelligent driving data collection method provided by the present invention.
The intelligent driving data acquisition method, the intelligent driving data acquisition device, the intelligent driving data acquisition equipment and the computer readable storage medium can effectively acquire the perception data of the vehicle.
It is to be understood that both the foregoing general description and the following detailed description of the present invention are exemplary and explanatory and are intended to provide further explanation of the invention as claimed.
Drawings
The accompanying drawings, which are included to provide a further explanation of the invention and are incorporated in and constitute a part of this application, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention. In the drawings:
FIG. 1 shows a flow diagram of a method for intelligent driving data collection in accordance with an embodiment of the present invention.
Fig. 2 shows a schematic structural diagram of an intelligent driving data acquisition device according to an embodiment of the invention.
Detailed Description
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
The technical solution in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. It is to be understood that the embodiments described are only a few embodiments of the present application and not all embodiments. The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the application, its application, or uses. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present application without making any creative effort belong to the protection scope of the present application.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
The relative arrangement of the components and steps, the numerical expressions, and numerical values set forth in these embodiments do not limit the scope of the present application unless specifically stated otherwise. Meanwhile, it should be understood that the sizes of the respective portions shown in the drawings are not drawn in an actual proportional relationship for the convenience of description. Techniques, methods, and apparatus known to one of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate. In all examples shown and discussed herein, any particular value should be construed as exemplary only and not as limiting. Thus, other examples of the exemplary embodiments may have different values. It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, further discussion thereof is not required in subsequent figures.
It should be noted that the terms "first", "second", and the like are used to define the components, and are only used for convenience of distinguishing the corresponding components, and the terms have no special meanings unless otherwise stated, and therefore, the scope of protection of the present application is not to be construed as being limited. Further, although the terms used in the present application are selected from publicly known and used terms, some of the terms mentioned in the specification of the present application may be selected by the applicant at his or her discretion, the detailed meanings of which are described in relevant parts of the description herein. Further, it is required that the present application is understood not only by the actual terms used but also by the meaning of each term lying within.
FIG. 1 shows a flow diagram of a method of intelligent driving data collection in accordance with one embodiment of the present invention. As shown in the figure, an intelligent driving data acquisition method comprises the following steps:
s1, editing data acquisition requirements at a local end, and generating data acquisition rules based on the data acquisition requirements, wherein the data acquisition refers to the acquisition of sensing data of an intelligent driving sensor at a vehicle end, and the data acquisition requirements refer to the fact that the data acquisition is required to meet various requirements of an acquisition scene. For example, the user may specify that the collection scenario includes the time at which data collection occurs, configuration requirements of the vehicle-end intelligent driving sensor, vehicle location, weather, lane conditions, target quantity threshold, and road conditions. The data collection rule is a rule set for data collection corresponding to each requirement.
And S2, issuing the data acquisition rule to a cloud issuing platform, and issuing the data acquisition rule to a specified vehicle through the cloud issuing platform according to the data acquisition rule. For example, data collection rules may be issued to a given vehicle at a given time.
And S3, adding or updating the data acquisition rule by the vehicle. As can be readily appreciated, if a new data collection rule is used, the vehicle adds the new data collection rule; if the data acquisition rule is a new version of the existing data acquisition rule, the data acquisition rule is updated.
And S4, the vehicle acquires the sensing data of the acquisition scene matched with the data acquisition rule based on a scene recognition algorithm, and the scene recognition algorithm is used for recognizing whether the scene environment of the vehicle is matched with the acquisition scene matched with the data acquisition rule or not according to the sensing data of the intelligent driving sensor at the vehicle end. The vehicle can acquire data on time or as required through a scene recognition algorithm to acquire sensing data according with a data acquisition rule. For example, the scene recognition algorithm can obtain the information of the current geographic position, the lane where the vehicle is located, and the like of the vehicle through high-precision positioning (a sensor); the current traffic flow information can be obtained through the camera and the millimeter wave radar; traffic light information and the like can be acquired through V2X. The perception information is converged to match the collection scene requirement of the data collection rule, so that effective perception data can be obtained, and the data storage cost is reduced.
And S5, the vehicle sends the acquired sensing data to a data center.
Preferably, in step S1, the vehicle-end intelligent driving sensor at least includes a vehicle-mounted camera, a millimeter wave radar, a laser radar, an ultrasonic radar, an inertial measurement unit IMU, a wheel speed sensor and a high-precision positioning sensor, and the sensing data at least includes an image, a point cloud, a radar echo, a vehicle position, a speed, a vehicle target, a pedestrian, an obstacle, a lane line, a traffic light, passable area information and related attributes acquired by the vehicle-end intelligent driving sensor.
Preferably, in step S4, the process of acquiring the perception data by the vehicle includes the steps of:
recording sensing data of all intelligent driving sensors at the vehicle end in full, namely acquiring all the sensing data without considering data acquisition rules;
and screening the perception data based on a scene recognition algorithm, acquiring the perception data matched with the acquisition scene of the data acquisition rule, namely removing the perception data which does not accord with the data acquisition rule, and forming effective perception data.
Preferably, in step S4, the process of acquiring the perception data by the vehicle includes the steps of:
and analyzing whether the scene environment of the vehicle is matched with the acquisition scene matched with the data acquisition rule or not based on a scene identification algorithm. The scene recognition algorithm acquires road scene information of a current vehicle through an intelligent driving sensor at an analysis vehicle end, for example, the scene information of a road surface can be collected in real time through a camera, and the collected video stream is transmitted to an engine of the scene recognition algorithm; the engine of the scene recognition algorithm determines the category of the vehicle scene (such as intersection, sunny day, etc.) by analyzing and processing the video stream (which may be set to several seconds or minutes). If the category of the vehicle scene does not conform to the acquisition scene required by the data acquisition rule, the matching fails; and if the category of the vehicle scene meets the acquisition scene required by the acquisition rule, the matching is successful.
If the data are matched with the data, recording sensing data of the corresponding vehicle-end intelligent driving sensor according to a data acquisition rule; furthermore, before starting to execute the data acquisition action, data in a period of time before tracing back is firstly carried out (which can be seconds or minutes); if not, stopping recording. It is easy to understand that the engine of the scene recognition algorithm is always in a working state, and the matching condition of the current scene of the vehicle and the acquisition scene required by the data acquisition rule is monitored.
Preferably, in step S5, the vehicle directly transmits the acquired sensing data to the data center, or transmits the stored sensing data to the data center after storing the sensing data.
Fig. 2 shows a schematic structural diagram of an intelligent driving data acquisition device according to an embodiment of the invention. As shown in the figure, an intelligent driving data collecting device 200 mainly includes a local sub-module 201, a cloud sub-module 202, a vehicle terminal sub-module 203 and a data center sub-module 204.
The local terminal module 201 may be understood as a local client of the cloud terminal module 202. The local terminal module 201 is used for editing data acquisition requirements and generating data acquisition rules based on the data acquisition requirements. The data acquisition refers to the acquisition of perception data of the intelligent driving sensor at the vehicle end, the data acquisition requirement refers to the fact that the data acquisition is required to meet various requirements of an acquisition scene, and the data acquisition rule is a rule set of data acquisition corresponding to the various requirements.
The cloud sub-module 202 is configured to receive and store the data acquisition rule generated by the local sub-module 201, and send the data acquisition rule to a vehicle specified according to the data acquisition rule.
The vehicle terminal module 203 is provided on the vehicle. The vehicle terminal module 203 is configured to receive the data collection rule issued by the cloud terminal module 202, and add or update the data collection rule. The vehicle terminal module 203 acquires the sensing data of the collection scene matched with the data collection rule based on a scene recognition algorithm, and the scene recognition algorithm is used for recognizing whether the scene environment of the vehicle is matched with the collection scene matched with the data collection rule or not according to the sensing data of the vehicle terminal intelligent driving sensor.
The data center sub-module 204 is used for receiving the perception data acquired by the vehicle terminal sub-module 203.
Preferably, the local terminal module 201 includes a vehicle information visualization interface 2011 and a rule editing visualization interface 2012. The vehicle information visualization interface 2011 is configured to display vehicle information, where the vehicle information includes a position of a vehicle and a current data collection status. The vehicle terminal module 203 reports vehicle information to the cloud terminal module 202, and the local terminal module 201 obtains the vehicle information through the cloud terminal module 202. The rule editing visualization interface 2012 is used for editing the data collection rule matching, and the editing operation mainly includes operations of adding, deleting, modifying, and viewing the data collection rule.
Preferably, the cloud sub-module 202 includes a vehicle management module 2021, a rule storage module 2022, and a rule issuing module 2023. The vehicle management module 2021 is configured to manage vehicle information. The rule storage module 2022 is used to store the received data collection rules, typically in a rules database. The rule issuing module 2023 is configured to issue the data acquisition rule to the vehicle specified by the rule issuing module. The data transmission between the cloud terminal module 202 and the local terminal module 201 may use an HTTP protocol, or use a data transmission protocol mechanism such as TCP.
Preferably, the vehicle terminal module 203 includes a communication management module 2031, a rule management module 2032, a recording management module 2033, and a human-machine interface 2034. The communication management module 2031 is configured to report the vehicle information to the cloud sub-module 202. When the vehicle-side data collection state changes, the communication management module 2031 reports the vehicle information of the vehicle to the cloud sub-module 202. The communication management module 2031 further receives the data collection rule issued by the cloud sub-module 202 and forwards the data collection rule to the rule management module 2032. The vehicle terminal module 203 and the cloud terminal module 202 perform data transmission using the HTTP protocol. By way of example and not limitation, vehicle terminal module 203 and cloud terminal module 202 may also use MQTT protocol, TCP, and similar data transmission protocol mechanisms.
The rule management module 2032 updates, saves, and synchronizes the data collection rules to the recording management module 2033 and the human-machine interface 2034. The rule management module 2032 has corresponding sub-function modules, including a vehicle-end operator confirmation module, a rule update module, a rule storage module, and a rule synchronization module. After receiving the data acquisition rule, the communication management module 2031 interacts with the vehicle-end operator via the human-machine interface 2034, and the vehicle-end operator can determine whether to accept the data acquisition rule. If the vehicle-end operator refuses to accept, the vehicle-end operator confirmation module discards the received data acquisition rule and does not perform any operation; if the vehicle-end operator accepts the data, if the data is a new data acquisition rule, the data acquisition rule is stored through the rule storage module, and if the data is a new version of the existing data acquisition rule, the data acquisition rule is updated through the rule updating module. The rule synchronization module is configured to synchronize the data collection rule to the recording management module 2033 and the human-machine interface 2034.
The recording management module 2033 records (acquires) the sensing data of the acquisition scene matching the data acquisition rule based on the scene recognition algorithm. The recording management module 2033 supports a manual recording mode and an automatic recording mode. The manual recording mode is to record all perception data of the intelligent driving sensors at the vehicle end in a full amount, not consider a data acquisition rule, then screen the perception data based on a scene recognition algorithm, and acquire the perception data matched with the acquisition scene of the data acquisition rule. The automatic recording mode is to analyze whether the scene environment of the vehicle is matched with the acquisition scene matched with the data acquisition rule or not based on a scene recognition algorithm, record the sensing data of the corresponding vehicle-end intelligent driving sensor according to the data acquisition rule if the scene environment of the vehicle is matched with the acquisition scene matched with the data acquisition rule, and stop recording if the scene environment of the vehicle is not matched with the acquisition scene. The recording management module 2033 synchronizes the recording status to the human interface 2034. Specifically, the recording management module 2033 includes a synchronization status module, a manual recording module, an automatic recording module, and a scene matching module. The synchronization status module is configured to obtain the recording status and synchronize to the human-machine interface 2034. The manual recording module is used for executing manual recording. The automatic recording module is used for executing automatic recording. The scene matching module is used for analyzing whether the scene environment where the vehicle is located is matched with the acquisition scene matched with the data acquisition rule.
The human-machine interface 2034 is used for displaying acquisition recording status, data acquisition rules, and providing a recording mode switching button for switching between a manual recording mode and an automatic recording mode. The collecting and recording state comprises a recording mode of current data collection, a storage position of the collected data and the like. The data acquisition rules may be by displaying a description of the corresponding acquisition scenario, and the like. The vehicle operator can select a specific recording mode through the recording mode switching button.
Preferably, the vehicle terminal module 203 may send the acquired sensing data to the data center sub-module 204 by using a hard disk transmission manner, and may also perform data transmission by using a wireless network, for example, wifi, bluetooth, cellular communication, or the like.
The invention also provides intelligent driving data acquisition equipment which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor realizes the steps of the intelligent driving data acquisition method when executing the computer program.
The invention also provides a computer-readable storage medium, on which a computer program is stored, which computer program, when being executed by a processor, carries out the steps of the aforementioned intelligent driving data acquisition method.
Specific implementation manners and technical effects of the intelligent driving data acquisition device and the computer-readable storage medium can be found in the above-mentioned embodiment of the intelligent driving data acquisition method provided by the present invention, and are not described herein again.
Those of skill would further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. 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 various illustrative logical modules, and circuits described in connection with the embodiments disclosed herein may be implemented or performed with a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general-purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC. The ASIC may reside in a user terminal. In the alternative, the processor and the storage medium may reside as discrete components in a user terminal.
In one or more exemplary embodiments, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software as a computer program product, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a computer. By way of example, and not limitation, such computer-readable media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. Any connection is properly termed a computer-readable medium. For example, if the software is transmitted from a web site, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, digital Subscriber Line (DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. Disk (disk) and disc (disc), as used herein, includes Compact Disc (CD), laser disc, optical disc, digital Versatile Disc (DVD), floppy disk and blu-ray disc where disks (disks) usually reproduce data magnetically, while discs (discs) reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.
The intelligent driving data acquisition method, the intelligent driving data acquisition device, the intelligent driving data acquisition equipment and the computer readable storage medium have the following advantages:
1. the data acquisition rule can be edited and issued in real time in a local visual interface according to the acquisition requirement; the data acquisition rules of all vehicles in the fleet can be edited in real time, so that the diversity and flexibility of data acquisition are improved.
2. The data acquisition rule is issued to the vehicle end through the cloud end and then executed by the vehicle end; an engineer is not required to find the specified vehicle, and then the data acquisition rule is edited from the inside of the vehicle, so that the human resources are saved.
3. And a vehicle end deployment scene recognition algorithm can match the environment of the vehicle end with the data acquisition rule. If the matching is successful, on-time and on-demand data acquisition can be adopted. Effective data can be screened out through different recording modes, and therefore light-weight storage of the data is achieved.
4. Continuous full data acquisition and automatic recording can be simultaneously operated, and the flexibility of data acquisition is improved.
It will be apparent to those skilled in the art that various modifications and variations can be made to the above-described exemplary embodiments of the present invention without departing from the spirit and scope of the invention. Thus, it is intended that the present invention cover the modifications and variations of this invention provided they come within the scope of the appended claims and their equivalents.
Claims (11)
1. An intelligent driving data acquisition method comprises the following steps:
s1, editing data acquisition requirements at a local end, and generating data acquisition rules based on the data acquisition requirements, wherein the data acquisition refers to the acquisition of sensing data of an intelligent driving sensor at a vehicle end, the data acquisition requirements refer to the fact that the data acquisition is required to meet various requirements of an acquisition scene, and the data acquisition rules are a rule set of data acquisition corresponding to the various requirements;
s2, issuing the data acquisition rule to a cloud issuing platform, and issuing the data acquisition rule to a specified vehicle through the cloud issuing platform according to the data acquisition rule;
s3, adding or updating the data acquisition rule by the vehicle;
s4, the vehicle acquires sensing data of a collection scene matched with the data collection rule based on a scene recognition algorithm, wherein the scene recognition algorithm is used for recognizing whether a scene environment where the vehicle is located is matched with the collection scene matched with the data collection rule or not according to the sensing data of the vehicle-end intelligent driving sensor;
and S5, the vehicle sends the acquired sensing data to a data center.
2. The intelligent driving data collection method according to claim 1, wherein in step S1, the vehicle-end intelligent driving sensor at least comprises a vehicle-mounted camera, a millimeter wave radar, a laser radar, an ultrasonic radar, an inertial measurement unit IMU, a wheel speed sensor and a high-precision positioning sensor, and the perception data at least comprises an image, a point cloud, a radar echo, a vehicle position, a speed, a vehicle target, a pedestrian, an obstacle, a lane line, a traffic light, passable area information and related attributes acquired by the vehicle-end intelligent driving sensor.
3. The intelligent driving data collection method according to claim 1, wherein in step S4, the process of the vehicle acquiring the perception data includes the steps of:
recording sensing data of all intelligent driving sensors at the vehicle end in a full quantity;
and screening the perception data based on the scene recognition algorithm to obtain the perception data matched with the acquisition scene of the data acquisition rule.
4. The intelligent driving data collection method according to claim 1, wherein in step S4, the process of the vehicle acquiring the perception data includes the steps of:
analyzing whether the scene environment of the vehicle is matched with the acquisition scene matched with the data acquisition rule or not based on the scene identification algorithm;
if the vehicle-end intelligent driving sensor is matched with the vehicle-end intelligent driving sensor, recording sensing data of the corresponding vehicle-end intelligent driving sensor according to a data acquisition rule; and if not, stopping recording.
5. The intelligent driving data collection method according to claim 1, wherein in step S5, the vehicle directly transmits the collected perception data to a data center, or stores the perception data and then transmits the stored perception data to the data center.
6. An intelligent driving data acquisition device, comprising:
the system comprises a local terminal module, a data acquisition module and a data processing module, wherein the local terminal module is used for editing data acquisition requirements and generating data acquisition rules based on the data acquisition requirements, the data acquisition is used for acquiring perception data of an intelligent driving sensor at a vehicle end, the data acquisition requirements are used for acquiring various requirements of an acquisition scene, and the data acquisition rules are rule sets of data acquisition corresponding to the various requirements;
the cloud terminal sub-module is used for receiving and storing the data acquisition rule generated by the local terminal sub-module and sending the data acquisition rule to the vehicle appointed by the data acquisition rule;
the vehicle terminal module is arranged on the vehicle and used for receiving the data acquisition rule issued by the cloud terminal module and adding or updating the data acquisition rule; acquiring sensing data of an acquisition scene matched with the data acquisition rule based on a scene identification algorithm, wherein the scene identification algorithm is used for identifying whether a scene environment where the vehicle is located is matched with the acquisition scene matched with the data acquisition rule according to the sensing data of the intelligent driving sensor at the vehicle end;
and the data center submodule is used for receiving the sensing data acquired by the vehicle terminal submodule.
7. The intelligent driving data collection device of claim 6, wherein the local terminal modules comprise a vehicle information visualization interface and a rules editing visualization interface;
the vehicle information visualization interface is used for displaying vehicle information, the vehicle information comprises the position of a vehicle and the current data acquisition state, the vehicle terminal module reports the vehicle information to the cloud terminal module, and the local terminal module acquires the vehicle information through the cloud terminal module;
the rule editing visual interface is used for editing the data acquisition rule matching.
8. The intelligent driving data acquisition device according to claim 7, wherein the cloud-side sub-module comprises a vehicle management module, a rule storage module and a rule issuing module;
the vehicle management module is used for managing the vehicle information;
the rule storage module is used for storing the received data acquisition rule;
the rule issuing module is used for issuing the data acquisition rule to the appointed vehicle.
9. The intelligent driving data acquisition device according to claim 6, wherein the vehicle terminal module comprises a communication management module, a rule management module, a recording management module and a human-machine interface;
the communication management module is used for reporting the vehicle information to the cloud terminal sub-module, receiving a data acquisition rule sent by the cloud terminal sub-module and forwarding the data acquisition rule to the rule management module;
the rule management module updates, stores and synchronizes the data acquisition rule to the recording management module and the human-computer interface;
the recording management module records the perception data of the acquisition scene matched with the data acquisition rule based on the scene identification algorithm; the recording management module supports a manual recording mode and an automatic recording mode, the manual recording mode refers to the mode that sensing data of all vehicle-end intelligent driving sensors are recorded in a full scale, then the sensing data are screened based on a scene recognition algorithm, and sensing data matched with the collection scene of the data collection rule are obtained; the automatic recording mode is to analyze whether the scene environment of the vehicle is matched with the acquisition scene matched with the data acquisition rule or not based on a scene recognition algorithm, if so, recording the sensing data of the corresponding vehicle-end intelligent driving sensor according to the data acquisition rule, and if not, stopping recording;
the human-computer interface is used for displaying the collecting and recording state, the data collecting rule and providing a recording mode switching button, and the recording mode switching button is used for switching between a manual recording mode and an automatic recording mode.
10. An intelligent driving data acquisition device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor, when executing the computer program, implements the steps of the intelligent driving data acquisition method according to any one of claims 1-5.
11. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the intelligent driving data acquisition method according to any one of claims 1 to 5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211117297.0A CN115439957B (en) | 2022-09-14 | 2022-09-14 | Intelligent driving data acquisition method, acquisition device, acquisition equipment and computer readable storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211117297.0A CN115439957B (en) | 2022-09-14 | 2022-09-14 | Intelligent driving data acquisition method, acquisition device, acquisition equipment and computer readable storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115439957A true CN115439957A (en) | 2022-12-06 |
| CN115439957B CN115439957B (en) | 2023-12-08 |
Family
ID=84246696
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211117297.0A Active CN115439957B (en) | 2022-09-14 | 2022-09-14 | Intelligent driving data acquisition method, acquisition device, acquisition equipment and computer readable storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115439957B (en) |
Citations (21)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103345527A (en) * | 2013-07-23 | 2013-10-09 | 深圳市博瑞得科技有限公司 | Intelligent data statistical system |
| JP2015220530A (en) * | 2014-05-15 | 2015-12-07 | 株式会社Ｎｔｔドコモ | Device, program and system for identifying audience quality |
| CN107436773A (en) * | 2016-05-25 | 2017-12-05 | 全球能源互联网研究院 | A kind of rule-based scene adaptive method of Android |
| CN109947800A (en) * | 2018-08-01 | 2019-06-28 | 日海智能科技股份有限公司 | Data processing method, device, equipment and medium |
| CN110794189A (en) * | 2019-12-06 | 2020-02-14 | 杭州和利时自动化有限公司 | Data acquisition method and device and related equipment |
| CN111599183A (en) * | 2020-07-22 | 2020-08-28 | 中汽院汽车技术有限公司 | Automatic driving scene classification and identification system and method |
| CN111619482A (en) * | 2020-06-08 | 2020-09-04 | 武汉光庭信息技术股份有限公司 | Vehicle driving data acquisition and processing system and method |
| CN111785057A (en) * | 2020-06-23 | 2020-10-16 | 大众问问(北京)信息科技有限公司 | Method and device for prompting emergency and vehicle |
| CN112256584A (en) * | 2020-10-30 | 2021-01-22 | 深圳无域科技技术有限公司 | Internet number making method and system |
| CN112740725A (en) * | 2020-03-31 | 2021-04-30 | 华为技术有限公司 | Driving data acquisition method and device |
| CN113138906A (en) * | 2021-05-13 | 2021-07-20 | 北京优特捷信息技术有限公司 | Call chain data acquisition method, device, equipment and storage medium |
| CN114168632A (en) * | 2021-12-07 | 2022-03-11 | 泰康保险集团股份有限公司 | Abnormal data identification method and device, electronic equipment and storage medium |
| CN114167857A (en) * | 2021-11-08 | 2022-03-11 | 北京三快在线科技有限公司 | Control method and device of unmanned equipment |
| CN114265411A (en) * | 2021-12-28 | 2022-04-01 | 上汽大众汽车有限公司 | Method for solving problem that vehicle prediction model performance is limited by perception data performance |
| CN114407652A (en) * | 2022-01-19 | 2022-04-29 | 亿咖通(湖北)技术有限公司 | Information display method, device and equipment |
| CN114495057A (en) * | 2022-01-21 | 2022-05-13 | 亿咖通(湖北)技术有限公司 | Data acquisition method, electronic device and storage medium |
| US20220157093A1 (en) * | 2020-11-16 | 2022-05-19 | Toyota Jidosha Kabushiki Kaisha | Data recording device |
| CN114743170A (en) * | 2022-04-24 | 2022-07-12 | 重庆长安汽车股份有限公司 | Automatic driving scene labeling method based on AI algorithm |
| CN114792111A (en) * | 2022-02-28 | 2022-07-26 | 浙江大华技术股份有限公司 | Data acquisition method and device, electronic equipment and storage medium |
| CN114936122A (en) * | 2022-03-23 | 2022-08-23 | 联合汽车电子有限公司 | Vehicle monitoring system, method and readable storage medium |
| CN114979216A (en) * | 2022-05-26 | 2022-08-30 | 重庆长安汽车股份有限公司 | Server data acquisition configuration method and system thereof |
-
2022
- 2022-09-14 CN CN202211117297.0A patent/CN115439957B/en active Active
Patent Citations (21)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103345527A (en) * | 2013-07-23 | 2013-10-09 | 深圳市博瑞得科技有限公司 | Intelligent data statistical system |
| JP2015220530A (en) * | 2014-05-15 | 2015-12-07 | 株式会社Ｎｔｔドコモ | Device, program and system for identifying audience quality |
| CN107436773A (en) * | 2016-05-25 | 2017-12-05 | 全球能源互联网研究院 | A kind of rule-based scene adaptive method of Android |
| CN109947800A (en) * | 2018-08-01 | 2019-06-28 | 日海智能科技股份有限公司 | Data processing method, device, equipment and medium |
| CN110794189A (en) * | 2019-12-06 | 2020-02-14 | 杭州和利时自动化有限公司 | Data acquisition method and device and related equipment |
| CN112740725A (en) * | 2020-03-31 | 2021-04-30 | 华为技术有限公司 | Driving data acquisition method and device |
| CN111619482A (en) * | 2020-06-08 | 2020-09-04 | 武汉光庭信息技术股份有限公司 | Vehicle driving data acquisition and processing system and method |
| CN111785057A (en) * | 2020-06-23 | 2020-10-16 | 大众问问(北京)信息科技有限公司 | Method and device for prompting emergency and vehicle |
| CN111599183A (en) * | 2020-07-22 | 2020-08-28 | 中汽院汽车技术有限公司 | Automatic driving scene classification and identification system and method |
| CN112256584A (en) * | 2020-10-30 | 2021-01-22 | 深圳无域科技技术有限公司 | Internet number making method and system |
| US20220157093A1 (en) * | 2020-11-16 | 2022-05-19 | Toyota Jidosha Kabushiki Kaisha | Data recording device |
| CN113138906A (en) * | 2021-05-13 | 2021-07-20 | 北京优特捷信息技术有限公司 | Call chain data acquisition method, device, equipment and storage medium |
| CN114167857A (en) * | 2021-11-08 | 2022-03-11 | 北京三快在线科技有限公司 | Control method and device of unmanned equipment |
| CN114168632A (en) * | 2021-12-07 | 2022-03-11 | 泰康保险集团股份有限公司 | Abnormal data identification method and device, electronic equipment and storage medium |
| CN114265411A (en) * | 2021-12-28 | 2022-04-01 | 上汽大众汽车有限公司 | Method for solving problem that vehicle prediction model performance is limited by perception data performance |
| CN114407652A (en) * | 2022-01-19 | 2022-04-29 | 亿咖通(湖北)技术有限公司 | Information display method, device and equipment |
| CN114495057A (en) * | 2022-01-21 | 2022-05-13 | 亿咖通(湖北)技术有限公司 | Data acquisition method, electronic device and storage medium |
| CN114792111A (en) * | 2022-02-28 | 2022-07-26 | 浙江大华技术股份有限公司 | Data acquisition method and device, electronic equipment and storage medium |
| CN114936122A (en) * | 2022-03-23 | 2022-08-23 | 联合汽车电子有限公司 | Vehicle monitoring system, method and readable storage medium |
| CN114743170A (en) * | 2022-04-24 | 2022-07-12 | 重庆长安汽车股份有限公司 | Automatic driving scene labeling method based on AI algorithm |
| CN114979216A (en) * | 2022-05-26 | 2022-08-30 | 重庆长安汽车股份有限公司 | Server data acquisition configuration method and system thereof |
Non-Patent Citations (1)
| Title |
|---|
| 梁琼: "基于几何特征的点云目标检测方法研究", 《中国优秀硕士学位论文全文数据库 信息科技辑》, no. 2019, pages 138 - 462 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115439957B (en) | 2023-12-08 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| DE112018006665T5 (en) | PROCEDURE FOR ACCESSING ADDITIONAL PERCEPTIONAL DATA FROM OTHER VEHICLES | |
| CN106327911B (en) | A kind of intelligent parking control system for parking lot | |
| CN106469518B (en) | Method, server and the system of intelligent parking guidance based on video tracking identification | |
| US8107677B2 (en) | Measuring a cohort'S velocity, acceleration and direction using digital video | |
| CN104882001B (en) | Driving behavior monitoring method based on drive recorder, apparatus and system | |
| CN110471058A (en) | The system and method detected automatically for trailer attribute | |
| CN105849790A (en) | Road condition information acquisition method | |
| CN109804367A (en) | Use the distributed video storage and search of edge calculations | |
| CN114153220B (en) | Remote control method for automatic driving based on artificial intelligence Internet of things platform | |
| CN110753953A (en) | Method and system for object-centric stereo vision in autonomous vehicles via cross-modality verification | |
| EP3618011B1 (en) | Data collection apparatus, on-vehicle device, data collection system, and data collection method | |
| CN109508579B (en) | Method and device for acquiring virtual point cloud data | |
| CN113479195A (en) | Method for automatic valet parking and system for carrying out said method | |
| CN111862656A (en) | Map updating method and device for intelligent carrier, storage medium and processor | |
| US20220044558A1 (en) | Method and device for generating a digital representation of traffic on a road | |
| CN114445803A (en) | Driving data processing method and device and electronic equipment | |
| CN111951600B (en) | Parking space and vehicle identification information automatic matching method and parking system | |
| CN114419572B (en) | Multi-radar target detection method and device, electronic equipment and storage medium | |
| CN114492022A (en) | Road condition sensing data processing method, device, equipment, program and storage medium | |
| JP7278414B2 (en) | Digital restoration method, apparatus and system for traffic roads | |
| CN112863195B (en) | Vehicle state determination method and device | |
| CN112598908B (en) | Driver red light running recognition method and device, electronic equipment and storage medium | |
| CN112622923B (en) | Method and device for controlling a vehicle | |
| CN115439957A (en) | Intelligent driving data acquisition method, acquisition device, acquisition equipment and computer readable storage medium | |
| CN116524718A (en) | Remote visual processing method and system for intersection data |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |