CN110046569B - Unmanned driving data processing method and device and electronic equipment - Google Patents

Unmanned driving data processing method and device and electronic equipment Download PDF

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CN110046569B
CN110046569B CN201910293276.6A CN201910293276A CN110046569B CN 110046569 B CN110046569 B CN 110046569B CN 201910293276 A CN201910293276 A CN 201910293276A CN 110046569 B CN110046569 B CN 110046569B
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data
obstacle
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CN110046569A (en
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姚发亮
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Beijing Baidu Netcom Science and Technology Co Ltd
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Beijing Baidu Netcom Science and Technology Co Ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/86—Combinations of radar systems with non-radar systems, e.g. sonar, direction finder
    • G01S13/865—Combination of radar systems with lidar systems
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/86—Combinations of radar systems with non-radar systems, e.g. sonar, direction finder
    • G01S13/867—Combination of radar systems with cameras
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
    • G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/86—Combinations of lidar systems with systems other than lidar, radar or sonar, e.g. with direction finders
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/88—Lidar systems specially adapted for specific applications
    • G01S17/93—Lidar systems specially adapted for specific applications for anti-collision purposes
    • G01S17/931—Lidar systems specially adapted for specific applications for anti-collision purposes of land vehicles
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/50—Context or environment of the image
    • G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
    • G06V20/58—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads

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Abstract

The invention provides a data processing method, a data processing device and electronic equipment, wherein the method comprises the following steps: acquiring first data acquired by a sensor of a vehicle; identifying an obstacle according to the first data; judging whether the identified obstacle is a target obstacle or not according to the identified result; if the identified obstacle is the target obstacle, storing valid data associated with the target obstacle in the first data. Therefore, the data volume can be reduced, the transmission time and the storage cost of the data are saved, and the retrieval difficulty of effective data in subsequent model training is reduced.

Description

Unmanned driving data processing method and device and electronic equipment
Technical Field
The invention relates to the technical field of unmanned vehicles, in particular to an unmanned data processing method and device and electronic equipment.
Background
At present, unmanned vehicles are integrated with a large number of sensors, such as cameras, laser radars, millimeter wave radars and the like, and in the data acquisition process, the sensors can generate a large amount of data so that downstream modules can train models. However, in the data acquisition process, various sensors can acquire various data, and then the acquired data is stored or transmitted so as to facilitate the training of a downstream module; however, the acquired data is more, so that the data has the problem of low processing efficiency in the process of storage or transmission.
Disclosure of Invention
The embodiment of the invention provides an unmanned data processing method, an unmanned data processing device and electronic equipment, and aims to solve the problem of low processing efficiency of acquired data in the process of storage or transmission.
In a first aspect, an embodiment of the present invention provides a data processing method, including:
acquiring first data acquired by a sensor of a vehicle;
identifying an obstacle according to the first data;
judging whether the identified obstacle is a target obstacle or not according to the identified result;
if the identified obstacle is the target obstacle, storing valid data associated with the target obstacle in the first data.
In a second aspect, an embodiment of the present invention further provides a data processing apparatus, including:
the system comprises an acquisition module, a data acquisition module and a data processing module, wherein the acquisition module is used for acquiring first data acquired by a sensor of a vehicle;
the identification module is used for identifying the obstacle according to the first data;
the judging module is used for judging whether the identified barrier is the target barrier or not according to the identified result;
and the storage module is used for storing effective data related to the target obstacle in the first data if the identified obstacle is the target obstacle.
In a third aspect, an embodiment of the present invention further provides an electronic device, which is characterized by including a processor, a memory, and a computer program stored on the memory and executable on the processor, where the computer program, when executed by the processor, implements the steps of the data processing method.
In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to implement the steps of the data processing method.
According to the embodiment of the invention, first data acquired by a sensor of a vehicle is acquired; identifying an obstacle according to the first data; judging whether the identified obstacle is a target obstacle or not according to the identified result; if the identified obstacle is the target obstacle, storing valid data associated with the target obstacle in the first data. Therefore, the obstacles meeting the conditions are used as target obstacles, and effective data related to the target obstacles in the first data is stored, so that the downstream module can train the model. Compared with the prior art, the method has the advantages that the sensor data collected by the vehicle are stored in full, the effective data associated with the target barrier are only stored, the data volume can be reduced, the transmission time and the storage cost of the data are saved, and the retrieval difficulty of the effective data in the subsequent model training is reduced.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments of the present invention will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without inventive exercise.
FIG. 1 is a flow chart of a data processing method according to an embodiment of the present invention;
FIG. 2 is a second flowchart illustrating a data processing method according to an embodiment of the present invention;
FIG. 3 is a schematic structural diagram of a data processing apparatus according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, fig. 1 is a flowchart of a data processing method according to an embodiment of the present invention, and as shown in fig. 1, the method includes the following steps:
step 101, first data collected by a sensor of a vehicle are obtained.
In the step, a sensor for detecting the obstacle is mounted on the vehicle, and first data about the obstacle can be collected by the sensor during the running process of the vehicle, so that the vehicle can identify the obstacle based on the first data.
The sensor includes an image sensor, a distance sensor, a motion sensor, and the like, for detecting obstacle information of the vehicle during driving.
The first data may include image data, motion data, trajectory data, and the like of the obstacle, the image data may be used to identify parameters such as color, size, and shape of the obstacle, the motion data may be used to identify parameters such as speed and acceleration of the obstacle, and the trajectory data may be used to identify parameters such as a motion path and a position of the obstacle. The first data may also include other sensor data to identify other attribute parameters of the obstacle.
And 102, identifying the obstacle according to the first data.
In this step, the obstacle may be identified based on the acquired first data to obtain an obstacle identification result. Specifically, parameters such as the size, shape, speed, color and position of the obstacle may be identified according to data information such as image data, motion data and trajectory data in the first data, so as to obtain an identification result associated with the size, shape, speed, color and position of the obstacle.
The identification result can be an identification result of one parameter of the parameters such as size, shape, speed, color, position and the like or an identification result comprising a combination of multiple parameters; preferably, the recognition result is a recognition result of a combination of a plurality of parameters including a size, a shape, a speed, a color, a position, and the like, so that a more accurate recognition result of the obstacle can be obtained.
And 103, judging whether the identified obstacle is the target obstacle or not according to the identified result.
In this step, it may be determined whether the identified obstacle is the target obstacle by determining whether the identified result satisfies a preset condition, for example, it may be determined whether the size, shape, and color of the identified obstacle satisfy preset size, shape, and color, to determine whether the identified obstacle is the target obstacle.
And 104, if the identified obstacle is the target obstacle, storing effective data related to the target obstacle in the first data.
In this step, when the recognized obstacle is the target obstacle, the data related to the target obstacle in the first data may be stored as valid data, so that the downstream module performs model training, thereby improving the recognition capability of the vehicle and improving the driving capability of the vehicle in the case of unmanned driving.
The effective data can be stored in a cloud database or a server database; the effective data can be transmitted to a cloud database or a server database for storage through a local hard disk stored in the vehicle, so that model training can be performed by using the effective data subsequently, and the obstacle recognition capability of the vehicle is improved.
Optionally, the storing valid data associated with the target obstacle in the first data includes: determining a type of the target obstacle according to the recognized result; determining an identification symbol corresponding to the target obstacle according to the type of the target obstacle; extracting valid data associated with the target obstacle from the first data and marking the valid data with the identification symbol; and storing the effective data carrying the identification symbol.
In this embodiment, the type of the target obstacle may be determined from the result of the recognized obstacle, and the identification symbol of the target obstacle may be determined based on the type of the target obstacle, and the valid data associated with the target obstacle may be marked using the identification symbol. Therefore, the target obstacle is classified, and the effective data associated with the target obstacle is marked by using the identification symbol, so that the effective data of the target obstacle is classified, and the retrieval difficulty of the related effective data is reduced in the subsequent model training.
Further, the storing the valid data carrying the identifier includes: and storing the effective data to a position corresponding to the identification symbol in a preset database.
In this embodiment, the valid data is stored in the preset database at the position corresponding to the identifier, that is, the valid data is classified and stored based on the identifier, so that the retrieval difficulty of the valid data in the subsequent model training can be further improved.
Optionally, the extracting valid data associated with the target obstacle from the first data and marking the valid data with the identifier includes: determining a time window associated with the target obstacle based on the type of the target obstacle; and determining the data in the first data within the time window as the valid data, extracting the valid data, and marking the valid data by using the identification symbol.
In this embodiment, the time window associated with the target obstacle may be determined based on the type of the target obstacle, and data within the time window from the first data may be determined as valid data, extracted, and marked with the identification symbol. In this way, only the data in the time window associated with the target obstacle is determined as valid data and stored, and compared with the case where all the first data associated with the target obstacle is determined as valid data and stored, the data amount of the valid data can be further reduced, and the transmission time and storage cost of the data can be saved.
The time window may be determined according to the type of the target obstacle, for example, for a type a target obstacle, the time window may be set to (t-2s, t +2s), where t is a time point when the target obstacle is detected; for a target obstacle of type B, its time window may be set to (T, T +10s), T being the point in time at which the target obstacle is detected.
Optionally, the identifying an obstacle according to the first data includes: identifying attribute parameters of the obstacle according to the first data, wherein the attribute parameters comprise at least one of position, shape, size, color and speed of the obstacle.
Further optionally, the determining, according to the identified result, whether the identified obstacle is the target obstacle includes: and judging whether the attribute parameters of the identified obstacle are matched with preset attribute parameters or not according to the attribute parameters of the identified obstacle, and if not, determining that the identified obstacle is the target obstacle.
In this embodiment, the attribute parameters may include at least one of a position, a shape, a size, a color, and a speed of the obstacle, and the attribute parameters of the obstacle are identified based on the acquired first data acquired by the sensor, and an identification result including the attribute parameters of the obstacle is obtained; and then, determining whether the attribute parameters of the identified obstacles are matched with the preset attribute parameters or not, and if not, determining that the identified obstacles can be determined as the obstacles which cannot be identified by the preset attribute parameters, namely the target obstacles.
Through the method, the obstacles detected in the driving process of the vehicle are divided into the obstacles which can be identified by the preset attribute parameters and the obstacles which cannot be identified by the preset attribute parameters, the collected first data is further divided into the valid data and the invalid data, in the subsequent data processing process, the valid data is stored, and the invalid data is cleared, so that the data volume needing to be stored is reduced.
In this way, the detected obstacle is divided into an obstacle that can be identified by the preset attribute parameter and an obstacle that cannot be identified by the preset attribute parameter. The first data of the obstacle which can be identified by the preset attribute parameters does not help much for subsequent model training, so that the first data can occupy larger storage space when being stored, and the retrieval difficulty of effective data is increased; and the first data of the obstacles which cannot be identified by the preset attribute parameters is beneficial to subsequent model training so as to facilitate vehicle identification when the vehicle encounters the same obstacle next time.
The obstacle which cannot be identified by the preset attribute parameters can be used as a target obstacle, and effective data related to the target obstacle in the first data can be stored, so that a downstream module can train the model. Compared with the prior art, the method has the advantages that the sensor data collected by the vehicle are stored in full, the effective data associated with the target barrier are only stored, the data volume can be reduced, the transmission time and the storage cost of the data are saved, and the retrieval difficulty of the effective data in the subsequent model training is reduced.
For example, if the recognized obstacle is an animal with a diagonal and the preset attribute parameter is an animal without a diagonal, it may be determined that the recognized obstacle is a target obstacle that cannot be recognized by the preset attribute parameter, that is, the recognized obstacle cannot be recognized based on the preset attribute parameter in the vehicle or the database, and then the first data of the target obstacle that cannot be recognized is stored, so that the downstream module performs model training.
Specifically, for example, when the vehicle is in a driving process, a deer appears right ahead, and the preset attribute parameters do not have the attribute parameters of the deer, so that the deer cannot be identified, the deer can be determined as a target obstacle, the collected sensor data about the deer is used as effective data and is stored, so that when model training is performed subsequently, the collected effective data about the deer is used for establishing an identification model for identifying the deer, and thus, when the vehicle encounters the deer next time, the vehicle can be identified based on the identification model of the deer.
For another example, when the vehicle is in a driving process, a dog appears right ahead, and the preset attribute parameters have the attribute parameters of the dog, so that the dog can be identified, and the identification degree is high, therefore, the acquired sensor data about the dog cannot play a role in subsequent model training, the sensor data about the dog belongs to invalid data, the data volume is increased by storing the invalid data, and the data transmission time and the storage cost are increased.
The data processing method provided by the embodiment of the invention is applied to electronic equipment, and the electronic equipment can be a vehicle-mounted terminal, a smart phone and the like.
In the embodiment of the invention, first data acquired by a sensor of a vehicle is acquired; identifying an obstacle according to the first data; judging whether the identified obstacle is a target obstacle or not according to the identified result; if the identified obstacle is the target obstacle, storing valid data associated with the target obstacle in the first data. Therefore, the obstacles meeting the conditions are used as target obstacles, and effective data related to the target obstacles in the first data is stored, so that the downstream module can train the model. Compared with the prior art, the method has the advantages that the sensor data collected by the vehicle are stored in full, the effective data associated with the target barrier are only stored, the data volume can be reduced, the transmission time and the storage cost of the data are saved, and the retrieval difficulty of the effective data in the subsequent model training is reduced.
Referring to fig. 2, fig. 2 is a second flowchart of a data processing method according to an embodiment of the present invention, as shown in fig. 2, including the following steps: step 201, acquiring first data acquired by a sensor of a vehicle; step 202, identifying an obstacle according to the first data; step 203, judging whether the identified barrier is a target barrier or not according to the identified result; and 204, if the identified obstacle is the target obstacle, storing effective data related to the target obstacle in the first data.
In the present embodiment, when step 203 is executed, it may be determined whether the identified obstacle is the target obstacle according to the result of the identified obstacle, if so, step 204 is executed, otherwise, the process is ended or step 201 is executed again.
It should be noted that the data processing method provided in the embodiment of the present invention can implement each process implemented by the electronic device in the method embodiment in fig. 1, and is not described herein again to avoid repetition.
Referring to fig. 3, fig. 3 is a structural diagram of a data processing apparatus according to an embodiment of the present invention, and as shown in fig. 3, a data processing apparatus 300 includes:
an obtaining module 301, configured to obtain first data collected by a sensor of a vehicle;
an identification module 302, configured to identify an obstacle according to the first data;
a judging module 303, configured to judge whether the identified obstacle is a target obstacle according to the identified result;
a storage module 304, configured to store valid data associated with the target obstacle in the first data if the identified obstacle is the target obstacle.
Optionally, the storage module 304 includes:
a first determining submodule for determining a type of the target obstacle according to the recognized result;
the second determining submodule is used for determining an identification symbol corresponding to the target obstacle according to the type of the target obstacle;
a processing sub-module for extracting valid data associated with the target obstacle from the first data and marking the valid data with the identification symbol;
and the storage submodule is used for storing the effective data carrying the identification symbol.
Optionally, the processing sub-module includes:
a determination unit configured to determine a time window associated with the target obstacle based on the type of the target obstacle;
and the processing unit is used for determining the data in the time window in the first data as the valid data, extracting the valid data and marking the valid data by using the identification symbol.
Optionally, the storage sub-module is specifically configured to store the valid data to a position, corresponding to the identifier, in a preset database.
Optionally, the identifying module 302 is specifically configured to identify an attribute parameter of the obstacle according to the first data, where the attribute parameter includes at least one of a position, a shape, a size, a color, and a speed of the obstacle.
Optionally, the determining module 303 is specifically configured to determine whether the attribute parameter of the identified obstacle matches a preset attribute parameter according to the attribute parameter of the identified obstacle, and if not, determine that the identified obstacle is the target obstacle.
The data processing apparatus 300 provided in the embodiment of the present invention can implement each process implemented by the electronic device in the method embodiment in fig. 1, and is not described herein again to avoid repetition.
Fig. 4 is a schematic diagram of a hardware structure of an electronic device implementing various embodiments of the present invention.
The electronic device 400 includes, but is not limited to: radio frequency unit 401, network module 402, audio output unit 403, input unit 404, sensor 405, display unit 406, user input unit 407, interface unit 408, memory 409, processor 410, and power supply 411. Those skilled in the art will appreciate that the electronic device configuration shown in fig. 4 does not constitute a limitation of the electronic device, and that the electronic device may include more or fewer components than shown, or some components may be combined, or a different arrangement of components.
Wherein, the processor 410 is configured to:
acquiring first data acquired by a sensor of a vehicle;
identifying an obstacle according to the first data;
judging whether the identified obstacle is a target obstacle or not according to the identified result;
if the identified obstacle is the target obstacle, storing valid data associated with the target obstacle in the first data.
Optionally, the processor 410 is further configured to:
determining a type of the target obstacle according to the recognized result;
determining an identification symbol corresponding to the target obstacle according to the type of the target obstacle;
extracting valid data associated with the target obstacle from the first data and marking the valid data with the identification symbol;
and storing the effective data carrying the identification symbol.
The processor 410 is specifically configured to:
determining a time window associated with the target obstacle based on the type of the target obstacle;
and determining the data in the first data within the time window as the valid data, extracting the valid data, and marking the valid data by using the identification symbol.
The processor 410 is specifically configured to:
and storing the effective data to a position corresponding to the identification symbol in a preset database.
Optionally, the processor 410 is further configured to:
identifying attribute parameters of the obstacle according to the first data, wherein the attribute parameters comprise at least one of position, shape, size, color and speed of the obstacle.
Optionally, the processor 410 is further configured to:
and judging whether the attribute parameters of the identified obstacle are matched with preset attribute parameters or not according to the attribute parameters of the identified obstacle, and if not, determining that the identified obstacle is the target obstacle.
The electronic device 400 provided in the embodiment of the present invention can implement each process implemented by the electronic device in the above embodiments, and is not described here again to avoid repetition.
It should be understood that, in the embodiment of the present invention, the radio frequency unit 401 may be used for receiving and sending signals during a message sending and receiving process or a call process, and specifically, receives downlink data from a base station and then processes the received downlink data to the processor 410; in addition, the uplink data is transmitted to the base station. Typically, radio unit 401 includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier, a duplexer, and the like. Further, the radio unit 401 can also communicate with a network and other devices through a wireless communication system.
The electronic device provides wireless broadband internet access to the user via the network module 402, such as assisting the user in sending and receiving e-mails, browsing web pages, and accessing streaming media.
The audio output unit 403 may convert audio data received by the radio frequency unit 401 or the network module 402 or stored in the memory 409 into an audio signal and output as sound. Also, the audio output unit 403 may also provide audio output related to a specific function performed by the electronic apparatus 400 (e.g., a call signal reception sound, a message reception sound, etc.). The audio output unit 403 includes a speaker, a buzzer, a receiver, and the like.
The input unit 404 is used to receive audio or video signals. The input Unit 404 may include a Graphics Processing Unit (GPU) 4041 and a microphone 4042, and the Graphics processor 4041 processes image data of a still picture or video obtained by an image capturing apparatus (such as a camera) in a video capturing mode or an image capturing mode. The processed image frames may be displayed on the display unit 406. The image frames processed by the graphic processor 4041 may be stored in the memory 409 (or other storage medium) or transmitted via the radio frequency unit 401 or the network module 402. The microphone 4042 may receive sound, and may be capable of processing such sound into audio data. The processed audio data may be converted into a format output transmittable to a mobile communication base station via the radio frequency unit 401 in case of the phone call mode.
The electronic device 400 also includes at least one sensor 405, such as light sensors, motion sensors, and other sensors. Specifically, the light sensor includes an ambient light sensor that can adjust the brightness of the display panel 4091 according to the brightness of ambient light, and a proximity sensor that can turn off the display panel 4091 and/or a backlight when the electronic device 400 is moved to the ear. As one type of motion sensor, an accelerometer sensor can detect the magnitude of acceleration in each direction (generally three axes), detect the magnitude and direction of gravity when stationary, and can be used to identify the posture of an electronic device (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), and vibration identification related functions (such as pedometer, tapping); the sensors 405 may also include a fingerprint sensor, a pressure sensor, an iris sensor, a molecular sensor, a gyroscope, a barometer, a hygrometer, a thermometer, an infrared sensor, etc., which will not be described in detail herein.
The display unit 406 is used to display information input by the user or information provided to the user. The Display unit 406 may include a Display panel 4091, and the Display panel 4091 may be configured in the form of a Liquid Crystal Display (LCD), an Organic Light-Emitting Diode (OLED), or the like.
The user input unit 407 may be used to receive input numeric or character information and generate key signal inputs related to user settings and function control of the electronic device. Specifically, the user input unit 407 includes a touch panel 4091 and other input devices 4072. The touch panel 4091, also referred to as a touch screen, may collect touch operations by a user on or near the touch panel 4091 (e.g., operations by a user on or near the touch panel 4091 using a finger, stylus, or any other suitable object or attachment). The touch panel 4091 may include two portions of a touch detection device and a touch controller. The touch detection device detects the touch direction of a user, detects a signal brought by touch operation and transmits the signal to the touch controller; the touch controller receives touch information from the touch sensing device, converts the touch information into touch point coordinates, sends the touch point coordinates to the processor 410, receives a command from the processor 410, and executes the command. In addition, the touch panel 4091 may be implemented by various types such as a resistive type, a capacitive type, an infrared ray, and a surface acoustic wave. In addition to the touch panel 4091, the user input unit 407 may also include other input devices 4072. Specifically, the other input devices 4072 may include, but are not limited to, a physical keyboard, function keys (such as volume control keys, switch keys, etc.), a track ball, a mouse, and a joystick, which are not described herein again.
Further, the touch panel 4091 may be overlaid on the display panel 4091, and when the touch panel 4091 detects a touch operation thereon or nearby, the touch operation is transmitted to the processor 410 to determine the type of touch event, and then the processor 410 provides a corresponding visual output on the display panel 4091 according to the type of touch event. Although the touch panel 4091 and the display panel 4091 are shown in fig. 4 as two separate components to implement the input and output functions of the electronic device, in some embodiments, the touch panel 4091 and the display panel 4091 may be integrated to implement the input and output functions of the electronic device, which is not limited herein.
The interface unit 408 is an interface for connecting an external device to the electronic apparatus 400. For example, the external device may include a wired or wireless headset port, an external power supply (or battery charger) port, a wired or wireless data port, a memory card port, a port for connecting a device having an identification module, an audio input/output (I/O) port, a video I/O port, an earphone port, and the like. The interface unit 408 may be used to receive input (e.g., data information, power, etc.) from an external device and transmit the received input to one or more elements within the electronic apparatus 400 or may be used to transmit data between the electronic apparatus 400 and an external device.
The memory 409 may be used to store software programs as well as various data. The memory 409 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. Further, the memory 409 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.
The processor 410 is a control center of the electronic device, connects various parts of the entire electronic device using various interfaces and lines, performs various functions of the electronic device and processes data by operating or executing software programs and/or modules stored in the memory 409 and calling data stored in the memory 409, thereby performing overall monitoring of the electronic device. Processor 410 may include one or more processing units; preferably, the processor 410 may integrate an application processor, which mainly handles operating systems, user interfaces, application programs, etc., and a modem processor, which mainly handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 410.
The electronic device 400 may further include a power supply 411 (e.g., a battery) for supplying power to various components, and preferably, the power supply 411 may be logically connected to the processor 410 through a power management system, so as to implement functions of managing charging, discharging, and power consumption through the power management system.
In addition, the electronic device 400 includes some functional modules that are not shown, and are not described in detail herein.
Preferably, an embodiment of the present invention further provides an electronic device, which includes a processor 410, a memory 409, and a computer program that is stored in the memory 409 and can be run on the processor 410, and when being executed by the processor 410, the computer program implements each process of the data processing method embodiment, and can achieve the same technical effect, and in order to avoid repetition, details are not described here again.
The embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements each process of the data processing method embodiment, and can achieve the same technical effect, and in order to avoid repetition, details are not repeated here. The computer-readable storage medium may be a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. 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.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment of the present invention.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a U disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims (8)

1. A data processing method, comprising:
acquiring first data acquired by a sensor of a vehicle;
identifying an obstacle according to the first data;
judging whether the identified obstacle is a target obstacle or not according to the identified result;
if the identified obstacle is the target obstacle, storing valid data associated with the target obstacle in the first data;
the storing valid data associated with the target obstacle in the first data comprises:
determining a type of the target obstacle according to the recognized result;
determining an identification symbol corresponding to the target obstacle according to the type of the target obstacle;
extracting valid data associated with the target obstacle from the first data and marking the valid data with the identification symbol;
storing the effective data carrying the identification symbol;
wherein the storing the valid data carrying the identifier comprises:
storing the effective data to a position corresponding to the identification symbol in a preset database;
the extracting valid data associated with the target obstacle from the first data and marking the valid data with the identification symbol includes:
determining a time window associated with the target obstacle based on the type of the target obstacle;
and determining the data in the first data within the time window as the valid data, extracting the valid data, and marking the valid data by using the identification symbol.
2. The method of claim 1, wherein identifying an obstacle from the first data comprises:
identifying attribute parameters of the obstacle according to the first data, wherein the attribute parameters comprise at least one of position, shape, size, color and speed of the obstacle.
3. The method of claim 2, wherein determining whether the identified obstacle is a target obstacle according to the identified result comprises:
and judging whether the attribute parameters of the identified obstacle are matched with preset attribute parameters or not according to the attribute parameters of the identified obstacle, and if not, determining that the identified obstacle is the target obstacle.
4. A data processing apparatus, comprising:
the system comprises an acquisition module, a data acquisition module and a data processing module, wherein the acquisition module is used for acquiring first data acquired by a sensor of a vehicle;
the identification module is used for identifying the obstacle according to the first data;
the judging module is used for judging whether the identified barrier is the target barrier or not according to the identified result;
the storage module is used for storing effective data related to the target obstacle in the first data if the identified obstacle is the target obstacle;
the memory module includes:
a first determining submodule for determining a type of the target obstacle according to the recognized result;
the second determining submodule is used for determining an identification symbol corresponding to the target obstacle according to the type of the target obstacle;
a processing sub-module for extracting valid data associated with the target obstacle from the first data and marking the valid data with the identification symbol;
the storage submodule is used for storing the effective data carrying the identification symbol;
the storage submodule is specifically configured to store the valid data in a preset database at a position corresponding to the identifier;
the processing submodule comprises:
a determination unit configured to determine a time window associated with the target obstacle based on the type of the target obstacle;
and the processing unit is used for determining the data in the time window in the first data as the valid data, extracting the valid data and marking the valid data by using the identification symbol.
5. The data processing apparatus according to claim 4, wherein the identifying module is specifically configured to identify attribute parameters of the obstacle according to the first data, where the attribute parameters include at least one of a position, a shape, a size, a color, and a speed of the obstacle.
6. The data processing apparatus according to claim 5, wherein the determining module is specifically configured to determine whether the attribute parameter of the identified obstacle matches a preset attribute parameter according to the attribute parameter of the identified obstacle, and if the attribute parameter of the identified obstacle does not match the preset attribute parameter, determine that the identified obstacle is the target obstacle.
7. An electronic device, comprising a processor, a memory and a computer program stored on the memory and executable on the processor, the computer program, when executed by the processor, implementing the steps of the data processing method according to any one of claims 1 to 3.
8. 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 data processing method of any one of claims 1 to 3.
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