CN113777625A - Intelligent unmanned driving obstacle type judgment method and device - Google Patents

Intelligent unmanned driving obstacle type judgment method and device Download PDF

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Publication number
CN113777625A
CN113777625A CN202111048059.4A CN202111048059A CN113777625A CN 113777625 A CN113777625 A CN 113777625A CN 202111048059 A CN202111048059 A CN 202111048059A CN 113777625 A CN113777625 A CN 113777625A
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Prior art keywords
obstacle
information
automobile
obstacle information
screening
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CN202111048059.4A
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Chinese (zh)
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胡心怡
杨扬
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Shanghai Boonray Intelligent Technology Co Ltd
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Shanghai Boonray Intelligent Technology Co Ltd
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Priority to CN202111048059.4A priority Critical patent/CN113777625A/en
Publication of CN113777625A publication Critical patent/CN113777625A/en
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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
    • 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
    • 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
    • G08—SIGNALLING
    • G08C—TRANSMISSION SYSTEMS FOR MEASURED VALUES, CONTROL OR SIMILAR SIGNALS
    • G08C17/00—Arrangements for transmitting signals characterised by the use of a wireless electrical link
    • G08C17/02—Arrangements for transmitting signals characterised by the use of a wireless electrical link using a radio link

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  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • General Physics & Mathematics (AREA)
  • Electromagnetism (AREA)
  • Traffic Control Systems (AREA)

Abstract

The embodiment of the invention relates to the technical field of unmanned driving, and particularly discloses an intelligent unmanned driving obstacle type judgment method and device. The embodiment of the invention obtains the first barrier information; acquiring position information of an obstacle according to the first obstacle information; performing communication connection with other automobiles, and screening a target connection automobile close to the barrier according to the position information; receiving second barrier information sent by a target connection automobile; and analyzing the obstacle type according to the first obstacle information and the second obstacle information to generate an obstacle type analysis result. When the obstacle cannot be effectively identified in a severe driving environment, the obstacle information acquired and sent by the vehicle close to the obstacle is received through communication connection with other surrounding vehicles, and the obstacle information is combined with the obstacle information acquired by the vehicle and then analyzed according to the obstacle type, so that the obstacle identification precision of the unmanned vehicle is improved, and the safety of unmanned driving is guaranteed.

Description

Intelligent unmanned driving obstacle type judgment method and device
Technical Field
The invention belongs to the technical field of unmanned driving, and particularly relates to an intelligent unmanned driving obstacle type judgment method and device.
Background
With the rapid development of science and technology, an unmanned automobile is taken as an intelligent automobile capable of achieving the purpose of unmanned driving, environment information around the automobile is obtained by installing intelligent software and sensing equipment in the automobile, and the obtained information is intelligently processed and analyzed and judged to control the driving direction and speed of the automobile, so that the autonomous driving of the automobile is achieved, and traffic jam and traffic accidents can be effectively avoided; as a result, driverless automobiles are becoming a growing trend in the automotive industry.
The obstacle recognition and judgment of the unmanned driving is one of the most important technologies of the unmanned driving, and is important for the safety of the unmanned driving technology. Because the environment that the car is gone is influenced by multiple factors such as weather, road, for example in the road environment of heavy fog weather or a large amount of dust, unmanned automobile can perceive the barrier of periphery, nevertheless because the environment of going is abominable, unmanned automobile can not carry out accurate discernment to the barrier that exceeds certain distance.
Disclosure of Invention
The embodiment of the invention aims to provide an intelligent unmanned driving obstacle type judgment method and device, and aims to solve the problems in the background art.
In order to achieve the above purpose, the embodiments of the present invention provide the following technical solutions:
an intelligent unmanned driving obstacle type judgment method specifically comprises the following steps:
acquiring first obstacle information;
acquiring position information of an obstacle according to the first obstacle information;
performing communication connection with other automobiles, and screening a target connection automobile close to the barrier according to the position information;
receiving second barrier information sent by the target connection automobile;
and analyzing the obstacle type according to the first obstacle information and the second obstacle information to generate an obstacle type analysis result.
As a further limitation of the technical solution of the embodiment of the present invention, the acquiring the first obstacle information specifically includes the following steps:
acquiring visual obstacle information;
acquiring radar detection obstacle information;
and combining the visual obstacle information and the radar detection obstacle information to generate first obstacle information.
As a further limitation of the technical solution of the embodiment of the present invention, the acquiring the position information of the obstacle according to the first obstacle information specifically includes the following steps:
acquiring information capturing duration according to the first obstacle information;
determining the distance of the obstacle according to the information capturing duration;
acquiring an information capturing angle according to the first obstacle information;
determining an angle of the obstacle according to the information capturing angle;
and generating position information of the obstacle according to the obstacle distance and the obstacle angle.
As a further limitation of the technical solution of the embodiment of the present invention, the step of performing communication connection with other automobiles and screening a target connection automobile close to an obstacle according to the position information specifically includes the following steps:
sending a communication connection request;
establishing communication connection with other automobiles receiving the communication connection request;
and screening the target connection automobile close to the barrier according to the position information.
As a further limitation of the technical solution of the embodiment of the present invention, the screening of the target connected vehicle near the obstacle according to the position information specifically includes the following steps:
receiving positioning information sent by other automobiles;
and screening the target connection automobile close to the barrier according to the positioning information and the position information.
As a further limitation of the technical solution of the embodiment of the present invention, the performing obstacle type analysis according to the first obstacle information and the second obstacle information, and generating an obstacle type analysis result specifically includes the following steps:
merging the first obstacle information and the second obstacle information to generate the fusion information of the obstacles;
and inputting the fusion information into an obstacle type judgment model, and acquiring an obstacle type analysis result output by the obstacle type judgment model according to the fusion information.
As a further limitation of the technical solution of the embodiment of the present invention, the method further comprises the following steps:
and generating and displaying an obstacle icon according to the obstacle type analysis result.
An intelligent unmanned obstacle type judgment device comprises an obstacle information acquisition unit, a position information acquisition unit, a target connection automobile screening unit, an obstacle information receiving unit and an obstacle type analysis unit, wherein:
an obstacle information acquisition unit configured to acquire first obstacle information;
a position information acquiring unit, configured to acquire position information of an obstacle according to the first obstacle information;
the target connection automobile screening unit is used for carrying out communication connection with other automobiles and screening target connection automobiles close to the barrier according to the position information;
the obstacle information receiving unit is used for receiving second obstacle information sent by the target connection automobile;
and the obstacle type analysis unit is used for analyzing obstacle types according to the first obstacle information and the second obstacle information to generate an obstacle type analysis result.
As a further limitation of the technical solution of the embodiment of the present invention, the obstacle information acquiring unit specifically includes:
the visual barrier information acquisition module is used for acquiring visual barrier information;
the detection obstacle information acquisition module is used for acquiring radar detection obstacle information;
and the obstacle information generating module is used for combining the visual obstacle information and the radar detection obstacle information to generate first obstacle information.
As a further limitation of the technical solution of the embodiment of the present invention, the target connection vehicle screening unit specifically includes:
a connection request sending module for sending a communication connection request;
the communication connection establishing module is used for establishing communication connection with other automobiles receiving the communication connection request;
and the target connection automobile screening module is used for screening a target connection automobile close to the barrier according to the position information.
Compared with the prior art, the invention has the beneficial effects that:
the embodiment of the invention obtains the first barrier information; acquiring position information of an obstacle according to the first obstacle information; performing communication connection with other automobiles, and screening a target connection automobile close to the barrier according to the position information; receiving second barrier information sent by a target connection automobile; and analyzing the obstacle type according to the first obstacle information and the second obstacle information to generate an obstacle type analysis result. When the obstacle cannot be effectively identified in a severe driving environment, the obstacle information acquired and sent by the vehicle close to the obstacle is received through communication connection with other surrounding vehicles, and the obstacle information is combined with the obstacle information acquired by the vehicle and then analyzed according to the obstacle type, so that the obstacle identification precision of the unmanned vehicle is improved, and the safety of unmanned driving is guaranteed.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention.
FIG. 1 illustrates a network implementation environment diagram of a method provided by an embodiment of the invention;
FIG. 2 shows a flow chart of a method provided by an embodiment of the invention;
fig. 3 shows a flowchart for acquiring first obstacle information in the method provided by the embodiment of the present invention;
fig. 4 shows a flowchart for acquiring position information of an obstacle in the method provided by the embodiment of the invention;
FIG. 5 is a flow chart illustrating a method for connecting and screening target-connected vehicles according to an embodiment of the present invention;
FIG. 6 is a flow chart illustrating a method for screening a target-connected vehicle according to an embodiment of the present invention;
FIG. 7 is a flow chart illustrating obstacle type analysis in a method provided by an embodiment of the invention;
FIG. 8 illustrates yet another flow chart of a method provided by an embodiment of the present invention;
FIG. 9 illustrates an application architecture diagram of an apparatus provided by an embodiment of the present invention;
fig. 10 is a block diagram showing a configuration of an obstacle information acquiring unit in the apparatus provided in the embodiment of the present invention;
fig. 11 shows a block diagram of a target-connected vehicle screening unit in the apparatus according to the embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
It can be understood that, in the prior art, since the environment where the vehicle travels is affected by various factors such as weather and roads, for example, in a road environment with heavy fog weather or a lot of dust, although the unmanned vehicle can sense surrounding obstacles, the unmanned vehicle cannot accurately identify the obstacles beyond a certain distance due to the bad traveling environment.
In order to solve the above problem, an embodiment of the present invention obtains first obstacle information; acquiring position information of an obstacle according to the first obstacle information; performing communication connection with other automobiles, and screening a target connection automobile close to the barrier according to the position information; receiving second barrier information sent by a target connection automobile; and analyzing the obstacle type according to the first obstacle information and the second obstacle information to generate an obstacle type analysis result. When the obstacle cannot be effectively identified in a severe driving environment, the obstacle information acquired and sent by the vehicle close to the obstacle is received through communication connection with other surrounding vehicles, and the obstacle information is combined with the obstacle information acquired by the vehicle and then analyzed according to the obstacle type, so that the obstacle identification precision of the unmanned vehicle is improved, and the safety of unmanned driving is guaranteed.
Fig. 1 is a diagram of a network implementation environment of the method according to the embodiment of the present invention.
In the network real-time environment diagram, an automobile A, an automobile B and an automobile C run in foggy weather, an obstacle is arranged in front of the automobile A, the automobile B and the automobile C, the unmanned automobile A can detect the existence of the obstacle, but due to the influence of special weather, the distance between the unmanned automobile A and the obstacle is too large, the unmanned automobile A cannot accurately identify the obstacle, the automobile B is close to the obstacle, and therefore the obstacle can be accurately identified by acquiring the combination of the identification information of the automobile B to the obstacle and the identification information of the automobile B, and the unmanned automobile A can timely prepare for avoiding the obstacle.
Fig. 2 shows a flow chart of a method provided by an embodiment of the invention.
Specifically, the intelligent unmanned driving obstacle type judgment method specifically comprises the following steps:
step S101, first obstacle information is acquired.
In the embodiment of the present invention, the unmanned vehicle a performs obstacle photographing and scanning on the front side, the left side, and the right side, and acquires first obstacle information about an obstacle if there is an obstacle on the front side, the left side, or the right side.
It can be understood that the first obstacle information is obstacle identification information obtained when the unmanned vehicle a cannot accurately identify the obstacle under special conditions, and the unmanned vehicle a cannot judge the type of the obstacle according to the first obstacle information, so that preparation cannot be made for avoiding the obstacle in time.
Specifically, fig. 3 shows a flowchart for acquiring first obstacle information in the method provided by the embodiment of the present invention.
In a preferred embodiment provided by the present invention, the acquiring the first obstacle information specifically includes the following steps:
in step S1011, the visual obstacle information is acquired.
In the embodiment of the present invention, the unmanned vehicle a photographs an obstacle to obtain visual obstacle information about the obstacle.
In step S1012, radar detection obstacle information is acquired.
In the embodiment of the present invention, the unmanned vehicle a performs obstacle detection to the front side, the left side, and the right side in real time, and if an obstacle exists, radar detection obstacle information about the obstacle is obtained.
Step S1013, the visual obstacle information and the radar detection obstacle information are combined to generate first obstacle information.
In the embodiment of the invention, the visual obstacle information obtained by shooting the unmanned automobile A and the radar detection obstacle information obtained by detection are combined to generate the first obstacle information about the obstacle.
Further, the method comprises the following steps:
and step S102, acquiring position information of the obstacle according to the first obstacle information.
In the embodiment of the present invention, the position information is generated by obtaining the relative position of the obstacle with respect to the unmanned vehicle a based on the analysis of the first obstacle information. Specifically, the position information includes the distance and angle of the obstacle with respect to the unmanned automobile a.
Specifically, fig. 4 shows a flowchart for acquiring position information of an obstacle in the method provided by the embodiment of the present invention.
In a preferred embodiment of the present invention, the acquiring the position information of the obstacle according to the first obstacle information specifically includes the following steps:
step S1021, acquiring an information capturing duration according to the first obstacle information.
In the embodiment of the invention, the unmanned vehicle A emits a pulse signal outwards, the pulse signal is reflected after passing through the obstacle, then the unmanned vehicle A receives the pulse reflection signal reflected back from the obstacle, and the information capturing duration is obtained by calculating the time between the time when the unmanned vehicle A sends the pulse signal and the time when the unmanned vehicle A receives the pulse reflection signal. Specifically, the information capturing time is half of the time between the time when the unmanned vehicle a sends the pulse signal and the time when the pulse reflection signal is received.
And step S1022, determining the distance to the obstacle according to the information capturing duration.
In the embodiment of the invention, the distance between the obstacle and the unmanned automobile A is calculated according to the information capturing duration and the propagation speed of the pulse signal, and is set as the obstacle distance.
Step S1023, according to the first obstacle information, an information capture angle is obtained.
In the embodiment of the invention, the unmanned vehicle A emits a pulse signal outwards, the pulse signal is reflected after passing through the obstacle, then the unmanned vehicle A receives the pulse reflection signal reflected from the obstacle, and the angle for receiving the pulse reflection signal is obtained according to the information of the first obstacle, so that the information capturing angle is obtained.
And step S1024, determining the angle of the obstacle according to the information capturing angle.
In the embodiment of the invention, the relative angle of the obstacle relative to the driving direction of the unmanned automobile A is calculated according to the information capturing angle, and the obstacle angle is generated.
And S1025, generating position information of the obstacle according to the obstacle distance and the obstacle angle.
In the embodiment of the invention, the obtained obstacle distance and the obstacle angle are combined to generate the position information of the obstacle. Specifically, the position information can reflect the direction and distance of the obstacle with respect to the unmanned vehicle a.
Further, the method comprises the following steps:
and S103, performing communication connection with other automobiles, and screening targets close to the obstacles according to the position information to connect the automobiles.
In the embodiment of the invention, the unmanned automobile A is in communication connection with the automobiles B and C at a certain distance around, and the positions of the automobiles B and C are judged after connection, so that the automobile B close to the barrier is screened out as a target connection automobile.
Specifically, fig. 5 shows a flowchart of connecting and screening target connected vehicles in the method provided by the embodiment of the present invention.
In a preferred embodiment of the present invention, the performing communication connection with another vehicle and screening a target connection vehicle close to an obstacle according to the location information specifically includes the following steps:
step S1031, the communication connection request is transmitted.
In the embodiment of the invention, the unmanned automobile A sends a communication connection request to the outside. Specifically, the driverless automobile a may send the communication connection request through bluetooth or local WIFI.
And step S1032, establishing communication connection with other automobiles receiving the communication connection request.
In the embodiment of the invention, the automobile B and the automobile C which are positioned in the signal range of the unmanned automobile A can receive the communication connection request sent by the unmanned automobile A, the automobile B and the automobile C can select to receive or reject the communication connection request of the unmanned automobile A, and if the automobile B and the automobile C receive the communication connection request of the unmanned automobile A, the automobile B and the automobile C are both in communication connection with the unmanned automobile A. Specifically, communication connection can be carried out between the automobile B, the automobile C and the unmanned automobile A through modes such as Bluetooth and local WIFI.
And step S1033, screening the target connection automobile close to the obstacle according to the position information.
In the embodiment of the invention, after the communication connection is established between the unmanned automobile A and the automobiles B and C, the positions of the automobiles B and C relative to the unmanned automobile A are firstly obtained, then the automobiles B and C are screened according to the position information of the obstacles, and the target connection automobiles close to the obstacles are screened.
Specifically, fig. 6 shows a flowchart for screening a target-connected vehicle in the method provided by the embodiment of the present invention.
In a preferred embodiment provided by the present invention, the screening of the target connected vehicles near the obstacle according to the location information specifically includes the following steps:
step S10331, receiving positioning information sent by other cars.
In the embodiment of the invention, after the automobile B and the automobile C respectively receive the communication connection request of the unmanned automobile A, the automobile B and the automobile C respectively establish communication connection with the unmanned automobile A, and the unmanned automobile A receives the positioning information sent by the automobile B and the automobile C.
And step S10332, screening the target connection automobile close to the obstacle according to the positioning information and the position information.
In the embodiment of the invention, the automobile B and the automobile C are screened according to the positioning information and the position information of the obstacle sent by the automobile B and the automobile C, the automobile B corresponding to the positioning information close to the position information is screened, and the automobile B is set as a target connection automobile.
Further, the method comprises the following steps:
and step S104, receiving second obstacle information sent by the target connection automobile.
In the embodiment of the present invention, the vehicle B set as the target connected vehicle transmits the second obstacle information to the unmanned vehicle a.
It can be understood that the second obstacle information is obstacle identification information obtained when the automobile B close to the obstacle performs obstacle identification, and the second obstacle information is closer to the obstacle than the automobile a, so that the type of the obstacle can be more accurately determined by the second obstacle information than by the first obstacle information.
And step S105, analyzing the obstacle type according to the first obstacle information and the second obstacle information to generate an obstacle type analysis result.
In the embodiment of the invention, the first obstacle information acquired by the unmanned automobile A and the second obstacle information acquired by the received automobile B are combined, and then the obstacle type is analyzed and judged according to the first obstacle information and the second obstacle information to obtain an obstacle type analysis result.
Specifically, fig. 7 shows a flowchart of obstacle type analysis in the method provided by the embodiment of the present invention.
In a preferred embodiment of the present invention, the performing obstacle type analysis according to the first obstacle information and the second obstacle information, and generating an obstacle type analysis result specifically includes the following steps:
step S1051, merging the first obstacle information and the second obstacle information to generate fused information of the obstacles.
In the embodiment of the invention, the first obstacle information acquired by the unmanned automobile A and the second obstacle information acquired by the received automobile B are combined to obtain the fusion information about the obstacle.
Step S1052, inputting the fusion information into an obstacle type determination model, and obtaining an obstacle type analysis result output by the obstacle type determination model according to the fusion information.
In the embodiment of the invention, the fusion information is input into the obstacle type judgment model, and the obstacle type judgment model is used for calculation and analysis to obtain an obstacle type analysis result of the obstacle.
It can be understood that the obstacle type determination model is obtained by collecting and training sample data of various obstacle types in the driving process of the unmanned vehicle, and most obstacle types encountered by the unmanned vehicle in the driving process can be analyzed and determined through the obstacle type determination model.
Further, fig. 8 shows another flowchart of the method provided by the embodiment of the present invention.
Among others, in a preferred embodiment provided by the present invention, the method further comprises the steps of:
and S106, generating and displaying an obstacle icon according to the obstacle type analysis result.
In the embodiment of the present invention, the obstacle icon is generated and displayed in the display screen of the unmanned vehicle a according to the result of the obstacle type analysis of the obstacle. Specifically, the obstacle icon may be an icon displayed according to different obstacle types, for example: pedestrians, pets, children, cars, vans, etc. Meanwhile, the position information of the obstacle can be combined to display the obstacle icon.
Further, fig. 9 shows an application architecture diagram of the intelligent unmanned obstacle type determination device 100 according to the embodiment of the present invention.
Specifically, in still another preferred embodiment provided by the present invention, an intelligent unmanned obstacle type determination device 100 includes:
an obstacle information acquiring unit 101 is configured to acquire first obstacle information.
In the embodiment of the present invention, the unmanned vehicle a performs obstacle photographing and scanning on the front side, the left side, and the right side by the obstacle information acquiring unit 101, and acquires first obstacle information about an obstacle if there is an obstacle on the front side, the left side, or the right side.
Specifically, fig. 10 shows a block diagram of the structure of the obstacle information acquiring unit 101 in the apparatus according to the embodiment of the present invention.
In a preferred embodiment provided by the present invention, the obstacle information acquiring unit 101 specifically includes:
a visual obstacle information obtaining module 1011, configured to obtain visual obstacle information.
In the embodiment of the present invention, the unmanned vehicle a photographs an obstacle through the obstacle information acquiring module 1011 to obtain the obstacle information about the obstacle.
It can be understood that the visual obstacle information obtaining module 1011 may be a plurality of cameras installed on the unmanned vehicle a, and the plurality of cameras are respectively installed on the front side, the left side and the right side of the unmanned vehicle a, so as to be convenient for shooting the obstacles on the front side, the left side and the right side of the unmanned vehicle a, and obtain the visual obstacle information.
And a detected obstacle information obtaining module 1012, configured to obtain radar detected obstacle information.
In the embodiment of the present invention, the driverless vehicle a performs obstacle detection to the front side, the left side, and the right side in real time by the detected obstacle information obtaining module 1012, and if an obstacle exists, radar detected obstacle information about the obstacle is obtained.
It is understood that the detected obstacle information obtaining module 1012 may be a laser radar or a millimeter wave radar installed on the unmanned vehicle a, and may perform radar detection on the obstacles around the unmanned vehicle a to obtain radar detected obstacle information.
And an obstacle information generating module 1013 configured to combine the visual obstacle information and the radar detection obstacle information to generate first obstacle information.
In the embodiment of the present invention, the obstacle information generating module 1013 combines visual obstacle information captured by the unmanned vehicle a and radar-detected obstacle information obtained by detection, and generates first obstacle information about the obstacle.
Further, the intelligent unmanned driving obstacle type determination device 100 further includes:
a position information obtaining unit 102, configured to obtain position information of an obstacle according to the first obstacle information.
In the embodiment of the present invention, the position information acquiring unit 102 obtains the relative position of the obstacle with respect to the unmanned vehicle a according to the analysis of the first obstacle information, and generates the position information. Specifically, the position information includes the distance and angle of the obstacle with respect to the unmanned automobile a.
And the target connection automobile screening unit 103 is used for performing communication connection with other automobiles and screening target connection automobiles close to the barrier according to the position information.
In the embodiment of the invention, the unmanned automobile A is in communication connection with the automobiles B and C at a certain distance from the periphery through the target connection automobile screening unit 103, and the positions of the automobiles B and C are judged after the connection, so that the automobile B close to the obstacle is screened out as the target connection automobile.
Fig. 11 shows a block diagram of a target connection vehicle screening unit 103 in the apparatus according to the embodiment of the present invention.
In a preferred embodiment provided by the present invention, the target connection vehicle screening unit 103 specifically includes:
a connection request sending module 1031, configured to send a communication connection request.
In the embodiment of the present invention, the unmanned vehicle a sends a communication connection request to the outside through the connection request sending module 1031. Specifically, the connection request sending module 1031 may be a bluetooth or local WIFI transmitter.
And a communication connection establishing module 1032 for establishing communication connection with the other automobile which receives the communication connection request.
And the target connection automobile screening module 1033 is used for screening the target connection automobile close to the barrier according to the position information.
In the embodiment of the present invention, after the driverless vehicle a establishes the communication connection with the vehicles B and C through the communication connection establishing module 1032, the target connection vehicle screening module 1033 first obtains the positions of the vehicles B and C relative to the driverless vehicle a, and then screens the vehicles B and C according to the position information of the obstacle, and screens the target connection vehicles near the obstacle.
Further, the intelligent unmanned driving obstacle type determination device 100 further includes:
and an obstacle information receiving unit 104, configured to receive second obstacle information sent by the target connected vehicle.
In the embodiment of the present invention, the obstacle information receiving unit 104 receives the second obstacle information that is transmitted to the driverless automobile a by the automobile B set as the target connected automobile.
And an obstacle type analyzing unit 105, configured to perform obstacle type analysis according to the first obstacle information and the second obstacle information, and generate an obstacle type analysis result.
In the embodiment of the present invention, the obstacle type analysis unit 105 merges the first obstacle information acquired by the unmanned vehicle a and the second obstacle information acquired by the received vehicle B, and further performs obstacle type analysis and judgment according to the first obstacle information and the second obstacle information, so as to obtain an obstacle type analysis result.
In summary, in a severe driving environment, when an obstacle cannot be effectively identified, the embodiment of the invention can receive obstacle information acquired and transmitted by a vehicle close to the obstacle through communication connection with other surrounding vehicles, combine the obstacle information acquired and transmitted by the vehicle with the obstacle information acquired by the vehicle, and then perform obstacle type analysis, thereby improving the accuracy of the unmanned vehicle in identifying the obstacle and ensuring the safety of unmanned driving.
It should be understood that, although the steps in the flowcharts of the embodiments of the present invention are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a portion of the steps in various embodiments may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a non-volatile computer-readable storage medium, and can include the processes of the embodiments of the methods described above when the program is executed. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.

Claims (10)

1. An intelligent unmanned driving obstacle type judgment method is characterized by specifically comprising the following steps:
acquiring first obstacle information;
acquiring position information of an obstacle according to the first obstacle information;
performing communication connection with other automobiles, and screening a target connection automobile close to the barrier according to the position information;
receiving second barrier information sent by the target connection automobile;
and analyzing the obstacle type according to the first obstacle information and the second obstacle information to generate an obstacle type analysis result.
2. The intelligent unmanned obstacle type determination method of claim 1, wherein the acquiring of the first obstacle information specifically comprises the steps of:
acquiring visual obstacle information;
acquiring radar detection obstacle information;
and combining the visual obstacle information and the radar detection obstacle information to generate first obstacle information.
3. The method for determining the type of the intelligent unmanned obstacle according to claim 1, wherein the step of obtaining the position information of the obstacle according to the first obstacle information specifically includes the steps of:
acquiring information capturing duration according to the first obstacle information;
determining the distance of the obstacle according to the information capturing duration;
acquiring an information capturing angle according to the first obstacle information;
determining an angle of the obstacle according to the information capturing angle;
and generating position information of the obstacle according to the obstacle distance and the obstacle angle.
4. The intelligent unmanned obstacle type determination method of claim 1, wherein the step of performing communication connection with other vehicles and screening target connection vehicles close to obstacles according to the position information specifically comprises the steps of:
sending a communication connection request;
establishing communication connection with other automobiles receiving the communication connection request;
and screening the target connection automobile close to the barrier according to the position information.
5. The intelligent unmanned obstacle type determination method of claim 4, wherein the step of screening target-connected vehicles close to an obstacle according to the position information specifically comprises the steps of:
receiving positioning information sent by other automobiles;
and screening the target connection automobile close to the barrier according to the positioning information and the position information.
6. The method for determining the type of the intelligent unmanned obstacle according to claim 1, wherein the step of performing obstacle type analysis according to the first obstacle information and the second obstacle information to generate an obstacle type analysis result specifically includes the steps of:
merging the first obstacle information and the second obstacle information to generate the fusion information of the obstacles;
and inputting the fusion information into an obstacle type judgment model, and acquiring an obstacle type analysis result output by the obstacle type judgment model according to the fusion information.
7. The intelligent unmanned obstacle type determination method according to claim 1, further comprising the steps of:
and generating and displaying an obstacle icon according to the obstacle type analysis result.
8. The utility model provides an intelligent unmanned obstacle type judgement device which characterized in that, the device includes obstacle information acquisition unit, positional information acquisition unit, target connection car screening unit, obstacle information receiving unit and obstacle type analysis unit, wherein:
an obstacle information acquisition unit configured to acquire first obstacle information;
a position information acquiring unit, configured to acquire position information of an obstacle according to the first obstacle information;
the target connection automobile screening unit is used for carrying out communication connection with other automobiles and screening target connection automobiles close to the barrier according to the position information;
the obstacle information receiving unit is used for receiving second obstacle information sent by the target connection automobile;
and the obstacle type analysis unit is used for analyzing obstacle types according to the first obstacle information and the second obstacle information to generate an obstacle type analysis result.
9. The intelligent unmanned obstacle type determination device according to claim 8, wherein the obstacle information acquisition unit specifically includes:
the visual barrier information acquisition module is used for acquiring visual barrier information;
the detection obstacle information acquisition module is used for acquiring radar detection obstacle information;
and the obstacle information generating module is used for combining the visual obstacle information and the radar detection obstacle information to generate first obstacle information.
10. The intelligent unmanned obstacle type determination device of claim 8, wherein the target connection vehicle screening unit specifically comprises:
a connection request sending module for sending a communication connection request;
the communication connection establishing module is used for establishing communication connection with other automobiles receiving the communication connection request;
and the target connection automobile screening module is used for screening a target connection automobile close to the barrier according to the position information.
CN202111048059.4A 2021-09-08 2021-09-08 Intelligent unmanned driving obstacle type judgment method and device Pending CN113777625A (en)

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