CN110412595A - Roadbed cognitive method, system, vehicle, equipment and storage medium - Google Patents
Roadbed cognitive method, system, vehicle, equipment and storage medium Download PDFInfo
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- CN110412595A CN110412595A CN201910480779.4A CN201910480779A CN110412595A CN 110412595 A CN110412595 A CN 110412595A CN 201910480779 A CN201910480779 A CN 201910480779A CN 110412595 A CN110412595 A CN 110412595A
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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
- G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
- G01S13/06—Systems determining position data of a target
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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
- G01S13/88—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
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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
- G01S17/02—Systems using the reflection of electromagnetic waves other than radio waves
- G01S17/06—Systems determining position data of a target
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Abstract
The present invention relates to a kind of unmanned perception roadbed cognitive method, system, vehicle, equipment and storage mediums, the perception data that terminal is sent by obtaining multiple aware base stations, and according to multiple perception datas, global perception information is generated, and then broadcast global perception information.It is that the perception data sent according to multiple aware base stations generates in above-mentioned overall situation perception information, avoids since vehicle perceived distance is limited there are problems that blind area in caused overall situation perception information, improve unpiloted safety.
Description
Technical field
The present invention relates to unmanned technical fields, more particularly to a kind of roadbed cognitive method, system, vehicle, set
Standby and storage medium.
Background technique
Pilotless automobile, also known as autonomous driving vehicle are a kind of to realize unpiloted intelligence vapour by computer system
Vehicle.Pilotless automobile relies on artificial intelligence, vision calculating, radar, monitoring device and global positioning system cooperative cooperating, allows vehicle
Automatic safe motor vehicles can be operated under the operation of nobody class active.In vehicle travel process, nobody
Driving need by sensory perceptual system understand around traffic condition, according on travel route road and traffic condition carry out
Navigation, to guarantee safety, the normally travel of vehicle.
The sensory perceptual system of existing pilotless automobile is generally arranged at various kinds of sensors on vehicle (camera, infrared dress
Set, laser radar, millimetre-wave radar etc.) and equipment is calculated, to obtain the perception information of vehicle.It is obtained in real time by various kinds of sensors
Pick up the car an extraneous perception data, and by calculating equipment by perception data be converted to can by the navigation data of vehicle identification, into
And vehicle driving is planned and is controlled.
However above-mentioned sensory perceptual system is used, the effectively perceive of sensory perceptual system is only capable of perceiving vehicle periphery apart from limited
Local message, when encountering shelter, there may be blind areas for pilotless automobile perception information.
Summary of the invention
Based on this, it is necessary to problem sensory perceptual system there may be aiming at the problem that blind area, provide a kind of roadbed cognitive method,
Base station, vehicle, device, equipment and storage medium.
In a first aspect, a kind of roadbed cognitive method, which comprises
Obtain the perception data that multiple aware base stations are sent；
According to multiple perception datas, global perception information is generated；
Broadcast the global perception information.
It is described according to multiple perception datas in one of the embodiments, generate global perception information, comprising:
Multiple perception datas are subjected to fusion treatment, generate the global perception information.
It is described in one of the embodiments, that multiple perception datas are subjected to fusion treatment, generate the global sense
Know information, comprising:
Multiple perception datas are fused in high-precision map, the global perception information is generated.
There is overlapping between the overlay area of each aware base station in one of the embodiments,.
The aware base station includes laser radar, millimetre-wave radar, camera and infrared biography in one of the embodiments,
At least one of sensor.
Second aspect, a kind of roadbed cognitive method, which comprises
Receive the global perception information of broadcast；The overall situation perception information is the perception number obtained according to multiple aware base stations
According to the perception information of generation；
According to the global perception information, vehicle driving is controlled.
It is described according to the global perception information in one of the embodiments, control vehicle driving, comprising:
Obtain the location information of the vehicle；
According to the location information of the vehicle, coordinate of the vehicle in the global perception information is determined；
According to coordinate and the global perception information of the vehicle in the global perception information, the vehicle is controlled
Traveling.
The third aspect, a kind of roadbed sensory perceptual system the system comprises: at least two aware base stations, calculate equipment and logical
Interrogate equipment；The calculating equipment is connect at least two aware base station and the communication apparatus respectively；
At least two aware base station is used to send multiple perception datas to the calculating equipment；
The calculating equipment is used to generate global perception information according to the multiple perception data；
The communication apparatus is for broadcasting the global perception information.
The calculating equipment is specifically used for carrying out multiple perception datas at fusion in one of the embodiments,
Reason generates the global perception information.
The calculating equipment is specifically used for for multiple perception datas being fused to high-precisionly in one of the embodiments,
In figure, the global perception information is generated.
Fourth aspect, a kind of automatic driving vehicle, the vehicle include:
Receiving module, for receiving the global perception information of computing terminal broadcast；The overall situation perception information is according to more
The perception information that the perception data that a base station obtains generates；
Control module, for controlling vehicle driving according to the global perception information.
5th aspect, a kind of computer equipment, including memory and processor, the memory are stored with computer journey
Sequence, the processor realize method and step shown in above-mentioned roadbed cognitive method when executing the computer program.
6th aspect, a kind of computer readable storage medium are stored thereon with computer program, the computer program quilt
Processor realizes method and step shown in above-mentioned roadbed cognitive method when executing.
Above-mentioned roadbed cognitive method, system, vehicle, equipment and storage medium, terminal is by obtaining multiple aware base station hairs
The perception data sent, and according to multiple perception datas, global perception information is generated, and then broadcast global perception information.It is above-mentioned complete
It is that the perception data sent according to multiple aware base stations generates in office's perception information, avoids since vehicle perceived distance has
It limits, there are problems that blind area in caused overall situation perception information, improve unpiloted safety.
Detailed description of the invention
Fig. 1 is the schematic diagram of the application environment of roadbed cognitive method in one embodiment；
Fig. 2 is the flow diagram of roadbed cognitive method in one embodiment；
Fig. 2 a is the schematic diagram of aware base station coverage area in one embodiment；
Fig. 3 is the flow diagram of roadbed cognitive method in another embodiment；
Fig. 4 is the flow diagram of roadbed cognitive method in another embodiment；
Fig. 5 is the structural schematic diagram of the computing device provided in one embodiment；
Fig. 6 is the structural schematic diagram of the automatic driving vehicle provided in one embodiment；
Fig. 7 is the structural schematic diagram of the automatic driving vehicle provided in another embodiment；
Fig. 8 is the internal structure chart of computer equipment in one embodiment.
Specific embodiment
To keep the purposes, technical schemes and advantages of the embodiment of the present application clearer, below in conjunction with the embodiment of the present application
In attached drawing, the technical scheme in the embodiment of the application is clearly and completely described, it is clear that described embodiment is
Some embodiments of the present application, instead of all the embodiments.
Roadbed cognitive method provided in this embodiment, can be adapted in application environment as shown in Figure 1.Wherein, it perceives
Base station 102 is connect with computing device 104, and computing device 104 is connect with automatic driving vehicle 106, and computing device 104 can be intelligence
The electronics having data processing function such as energy mobile phone, tablet computer, laptop, desktop computer or personal digital assistant are set
It is standby, the present embodiment to the concrete form of computing device 104 without limitation.
It should be noted that roadbed cognitive method provided by the embodiments of the present application, executing subject can be computing device
Or automatic driving vehicle, the computing device or automatic driving vehicle can be by way of software, hardware or software and hardware combinings
It is implemented as some or all of of unmanned sensory perceptual system.
Fig. 2 is the flow diagram of roadbed cognitive method in one embodiment.What is involved is computing devices to lead to for the present embodiment
It crosses and obtains multiple global perception informations of perception datas generation, and broadcast the detailed process of global perception information.As shown in Fig. 2, should
Method the following steps are included:
S101, the perception data that multiple aware base stations are sent is obtained.
Wherein, it includes the objects such as road, pedestrian, vehicle, barrier that perception data, which can be through aware base station acquisition,
Information.Aware base station can be the base station for being erected at both sides of the road, and one or more sensors can be set thereon, and sensor can
To include laser radar, millimetre-wave radar, camera and infrared sensor.Multiple same class can be set in one aware base station
Sensor, the sensor of multiple and different classes also can be set, the embodiment of the present application is without limitation.For example, there is 3 perception
1 millimetre-wave radar is wherein arranged in base station, respectively aware base station 1, aware base station 2 and aware base station 3 in aware base station 1；Sense
Know 2 laser radars of setting on base station 2；1 laser radar and 1 camera are set in aware base station 3.It is scanned by sensor
Ambient enviroment obtains sensing data, which can be perception data, be also possible to the sensor data into
Row processing, obtains treated data, is perception data, and the embodiment of the present application is without limitation.Multiple aware base stations can be with
It is to be evenly provided on both sides of the road, is also possible to that the density of aware base station, the embodiment of the present application are arranged according to road condition
It is without limitation.For example, it is high in people, vehicle density, and the urban road more than shelter, a perception can be set every 50 meters
Base station, it is high in people, vehicle density, and the backroad that shelter is few, it can be every 200 meters of settings, one aware base station.
Specifically, computing device can be obtained multiple aware base stations and be sent by way of wireless transmission or wire transmission
Perception data, the perception data that multiple aware base stations are sent can be received simultaneously, multiple perception bases can also be received respectively
It stands the perception data sent, the embodiment of the present application is without limitation.Computing device can be when aware base station gets perception
When data, the perception data is directly obtained by way of wireless transmission；It is also possible to after aware base station gets perception data,
When aware base station is connect with computing device by cable network, multiple perception datas are obtained；The embodiment of the present application does not do this
Limitation.
S102, according to multiple perception datas, generate global perception information.
Specifically, global perception information can be the perception information generated according to multiple perception datas, in the perception information
It may include each object in above-mentioned multiple perception datas.It, which can be, exists the coordinate unification of object each in multiple perception datas
Under one coordinate system, the perception information of generation.By the coordinate unification of object each in multiple perception datas in a coordinate system,
Can be by be each object in multiple perception datas coordinate unification under a customized coordinate system, being also possible to will be multiple
For the coordinate unification of each object under terrestrial coordinate system, the embodiment of the present application is without limitation in perception data.
During with specific reference to multiple perception datas, generating global perception information, computing device can directly will be more
The coordinate unification of object in a perception data obtains global perception information into the same coordinate system；It is also possible to first to multiple
Perception data is handled, and obtains each object that boundary is more clear, then the coordinate unification of each object is obtained into perception information
Obtain global perception information；The embodiment of the present application is without limitation.
S103, global perception information is broadcasted.
Specifically, on the basis of the above embodiments, computing device generates in global perception information, can pass through broadcast
Mode broadcasts the overall situation perception information.Global perception information can be broadcasted by it by default frequency range, correspondingly, connecing
When receiving the overall situation perception information, it can be and receive the overall situation perception information in the default frequency range for broadcasting global perception information.
For example, computing device is passed through by the multi-band broadcast overall situation perception information of 100-105MHz when receiving the overall situation perception information
The UHF band reception of the 100-105MHz overall situation perception information.
In the global perception information of specific broadcast, each computing device can be in the range of its maximum radio transmission power
The global perception information of interior broadcast is also possible to radio transmission power be controlled, so that each computing device according to the range divided in advance
Global perception information is broadcasted in default range, the embodiment of the present application is without limitation.For example, there are 2 computing devices,
What the maximum radio transmission power of respectively computing device 1 and computing device 2, the computing device 1 and computing device 2 can cover
Range is the border circular areas of 5km, wherein the spacing distance between computing device 1 and computing device 2 is 7 kilometers, then can pass through
The radio transmission power of computing device 1 is set, so that the broadcast coverage of computing device 1 is 4.5km, computing device is set
Transmission power, so that the broadcast coverage of computing device 2 is 3.5km.
Above-mentioned roadbed cognitive method, the perception data that terminal is sent by obtaining multiple aware base stations, and according to multiple senses
Primary data generates global perception information, and then broadcasts global perception information.It is according to multiple perception in above-mentioned overall situation perception information
What the perception data that base station is sent generated, it avoids since vehicle perceived distance is limited, exists in caused overall situation perception information
The problem of blind area, improves the safety of automatic driving vehicle.
Optionally, by multiple perception datas, fusion treatment is carried out, generates global perception information.
Specifically, fusion treatment can be the processing method that each object is identified from perception data, and global perception information can be with
It is the data that perception data obtains after fusion treatment, it is what and each right for can specifying each object in perception data
The location information of elephant.Wherein, each object in perception data can be the presentation in the form of scanning cloud atlas, pass through fusion treatment
It can determine that each object is in the scanning cloud atlas, and its specific location in scanning cloud atlas.For example, perception data be with
What the form of point figure occurred, may include the point cloud data of multiple objects in the point figure, the boundary of each point cloud data
It is unclear, it is handled by perception, obtains the boundary of the corresponding point cloud data of each object, to identify that each object is, and root
According to the boundary, the specific location of each object is determined.It is further assumed that include 3 regions in point figure, by fusion treatment,
The boundary for obtaining 3 regions identifies that 3 regions respectively correspond 1 pedestrian and 2 vehicles, and then according to 1 pedestrian and 2
The corresponding region of vehicle, determines the specific location of 1 pedestrian and 2 vehicles.
By multiple perception datas, fusion treatment specifically is being carried out, it, can be primary during generating global perception information
Perception processing is carried out to a perception data, obtains the corresponding perception information of each object in the perception data, and then to other senses
Primary data carries out fusion treatment, corrects the corresponding perception information of above-mentioned each object；It is also possible to same in multiple perception datas
An object carries out fusion treatment, obtains the perception information of the same target, so to other objects in multiple perception datas into
Row fusion treatment obtains the perception information of other objects；It can also be and multiple perception datas are inputted into preset perception processing mould
In type, by deep learning, global perception information is obtained, the embodiment of the present application is without limitation.
Optionally, multiple perception datas are fused in high-precision map, generate global perception information.
It specifically, on the basis of the above embodiments, can also be by fusion treatment after carrying out fusion treatment to perception data
Perception data afterwards incorporates in high-precision map, obtains global perception information, wherein high-precision map, which can be detailed mark out, to be come
Specific lane on road, the width and length of lane line, the map of the information such as street lamp position, it can be understood as a reality
The map of the complete vector quantization of the road in the world, may include multiple map elements in high-precision map, each map element it is corresponding
The precision of coordinate data is high, and error is small, and in general, the trueness error of common navigation maps is at 10-15 meters or so, pair that includes
As also very single；And the trueness error of high-precision map is within 15-20 centimetres, and detailed can mark out and carry out each object.
Automatic driving vehicle can control vehicle driving according to high-precision map.Global perception information is that above-mentioned perception data is corresponding
The coordinate of each object, conversion to the coordinate under high-precision map coordinates system obtain the new height that joined each object in perception data
Precision map, as global perception information.
On the basis of the above embodiments, computing device can obtain the corresponding perception information of each object simultaneously, can also be with
The corresponding perception information of each object is obtained respectively.Then during perception information is fused to high-precision map, can simultaneously by
The corresponding perception information of each object is fused in high-precision map, to obtain global perception information；It can also be respectively by each object pair
The perception information answered is fused in high-precision map, to obtain global perception information；The embodiment of the present application is without limitation.
Above-mentioned roadbed cognitive method, multiple perception datas are fused in high-precision map, generate global perception information, due to
The precision of high-precision map is higher, is more nearly with actual road conditions, so that multiple perception datas are fused to high-precision map
Obtained in overall situation perception information be more nearly actual road conditions, further improve and nobody controlled according to global perception information
Drive the safety of vehicle driving.
Optionally, there is overlapping between the overlay area of each aware base station.
Specifically, the overlay area of aware base station can refer to that aware base station obtains the corresponding region of perception data.
Wherein, there is overlapping between the overlay area for all aware base stations that an aware base station can be adjacent thereto.For example, such as Fig. 2 a
Shown, circular frame represents the coverage area of aware base station, the perception base that wherein coverage area of aware base station 1 can be adjacent thereto
It stands and there is overlapping between 2, aware base station 3, the coverage area of aware base station 4.
Above-mentioned roadbed cognitive method is avoided by there is overlapping between the coverage of each aware base station due to one
Signal difference at the coverage edge of aware base station, caused the case where obtaining less than perception data in the region, and then avoid
By the case where there are blind areas in global perception information, automatic driving vehicle is further improved according to global perception information
The safety of traveling.
Optionally, aware base station includes at least one in laser radar, millimetre-wave radar, camera and infrared sensor
Kind.
Specifically, aware base station can obtain perception data by the sensor being mounted in aware base station, wherein sensing
Device can include but is not limited to camera, infrared facility, laser radar, millimetre-wave radar.Aware base station is connect with computing device,
It can also be connected by cable network, the embodiment of the present application is without limitation by wireless network connection.It can be multiple
Aware base station is connect with a computing device, can also be connect with an aware base station with a computing device, the embodiment of the present application
It is without limitation.
Above-described embodiment emphasis describes how to obtain the perception data that multiple aware base stations are sent, generates global perception and believe
Breath, and global perception information is broadcasted.Be described in detail below by Fig. 3-4 automatic driving vehicle how to pass through it is above-mentioned complete
Office's perception information controls vehicle driving.
Fig. 3 is the flow diagram of roadbed cognitive method in one embodiment, and what is involved is automatic driving cars for the present embodiment
The detailed process of vehicle driving how is controlled by global perception information, as shown in figure 3, method includes the following steps:
S201, the global perception information for receiving broadcast；Global perception information is the perception obtained according to multiple aware base stations
The perception information that data generate.
Specifically, in the specific global perception information for receiving broadcast, it can be inscribed in preset subscription distance and receive office
Perception information, preset distance of subscribing to is interior there may be the global perception information of a broadcast, and there may also be multiple broadcast
Global perception information, the embodiment of the present application are without limitation.It subscribes to when preset apart from the interior global sense broadcasted there are one
When knowing information, then the overall situation perception information is received；If preset subscribe to apart from interior there are when the global perception information of multiple broadcast,
The global perception information that multiple broadcast can be received simultaneously is also possible to select the global perception letter an of broadcast according to distance
Breath is to receive.For example, the global perception information broadcasted in preset subscription range there are 3, respectively global perception information
1, global perception information 2 and global perception information 3, wherein the global corresponding calculating of perception information 1 dress of automatic driving vehicle distance
The distance for setting 1 is 1km, and the distance of the corresponding computing device 2 of the global perception information 2 of automatic driving vehicle distance is 1.5km, nobody
Driving the corresponding computing device 3 of vehicle distances overall situation perception information 3 is distance 0.8km, then selects to receive apart from recently complete
Office's perception information 3.
S202, according to global perception information, control vehicle driving.
Specifically, on the basis of the above embodiments, after receiving global perception information, automatic driving vehicle can basis
The overall situation perception information controls vehicle driving.When receiving global perception information, that is, get the seat of multiple objects
Mark, and then can be according to the location information of automatic driving vehicle, the coordinate for controlling automatic driving vehicle along road travels, and hides
Pedestrian, vehicle and barrier coordinate.
Above-mentioned roadbed cognitive method, automatic driving vehicle is by receiving the global perception information broadcasted, wherein overall situation perception
Information is the perception information that the perception data obtained according to multiple aware base stations generates, and according to global perception information, controls vehicle
Traveling.So that automatic driving vehicle is the global perception information row generated according to the perception data that multiple aware base stations obtain
It sails, avoids since vehicle perceived distance is limited, there are problems that blind area in caused overall situation perception information, improve nobody and drive
Sail the safety of vehicle.
Further, automatic driving vehicle can be according to its location information in global perception information, and global perception
Information, control automatic driving vehicle traveling.It is described in detail below by embodiment illustrated in fig. 4.
Fig. 4 is the flow diagram of roadbed cognitive method in another embodiment, and what is involved is unmanned for the present embodiment
How vehicle is according to its location information in global perception information, and global perception information, control automatic driving vehicle traveling
Detailed process, as shown in figure 4, a kind of above-mentioned S302 " according to global perception information, controlling vehicle driving " possible implementation method,
The following steps are included:
S301, the location information for obtaining vehicle.
Specifically, the location information of vehicle can be intended to indicate that specific location of the vehicle in global perception information,
It can be one group of coordinate data, be also possible to one group of latitude, longitude data, the embodiment of the present application is without limitation.Specifically obtaining
During the location information of pick-up, the location information of vehicle can be obtained by the positioning device being installed on vehicle,
It can be the sensor by being arranged in aware base station, obtain the location information of vehicle, the embodiment of the present application does not limit this
System.
S302, the location information according to vehicle determine coordinate of the vehicle in global perception information.
Specifically, it is above-mentioned be embodiment on the basis of, global perception information can merge multiple perception datas
The perception information obtained is handled, may include the location information of each object in perception data.By the location information of vehicle with
The location information of each object in above-mentioned overall situation perception information, determines the relative position of each object in vehicle and global perception information.
For example, when the location information of each object in vehicle and global perception information is the coordinate under terrestrial coordinate system, the position of vehicle
Information can be indicated with latitude, longitude, to obtain coordinate of the vehicle in global perception information.
S303, the coordinate according to vehicle in global perception information, and global perception information, control vehicle driving.
It specifically, on the basis of the above embodiments, can be according to coordinate of the vehicle in global perception information, and the overall situation
Perception information controls vehicle driving.When receiving global perception information, that is, multiple object location informations are got, together
When, automatic driving vehicle has also obtained location information of the vehicle in global perception information, that is to say, that can pass through control
Position of the automatic driving vehicle in global perception information, so that vehicle does not contact pedestrian, vehicle and barrier, and in road
It is moved in range along preset direction, that is, controls the traveling of automatic driving vehicle.
Above-mentioned roadbed cognitive method, automatic driving vehicle pass through the location information for obtaining vehicle, and according to the position of vehicle
Information determines coordinate of the vehicle in global perception information, and then the coordinate according to vehicle in global perception information, and global
Perception information controls vehicle driving.So that automatic driving vehicle is that the perception data obtained according to multiple aware base stations generates
The location information of global perception information and automatic driving vehicle traveling, further increase the safety of automatic driving vehicle
Property.
It should be understood that although each step in the flow chart of Fig. 2-4 is successively shown according to the instruction of arrow,
These steps are not that the inevitable sequence according to arrow instruction successively executes.Unless expressly stating otherwise herein, these steps
Execution there is no stringent sequences to limit, these steps can execute in other order.Moreover, at least one in Fig. 2-4
Part steps may include that perhaps these sub-steps of multiple stages or stage are not necessarily in synchronization to multiple sub-steps
Completion is executed, but can be executed at different times, the execution sequence in these sub-steps or stage is also not necessarily successively
It carries out.
Fig. 5 is the structural schematic diagram for the roadbed sensory perceptual system that one embodiment provides.As shown in figure 5, roadbed perception system
System includes: at least two aware base stations 110, calculates equipment 120 and communication apparatus 130, in which:
At least two aware base stations 110 are used to send multiple perception datas to calculating equipment 120；
Equipment 120 is calculated, for generating global perception information according to multiple perception datas；
Communication apparatus 130, for broadcasting the global perception information.
In one embodiment, equipment 120 is calculated to be specifically used for multiple perception datas carrying out perception processing, it is raw
At the global perception information.
In one embodiment, equipment 120 is calculated to be specifically used for for multiple perception datas being fused in high-precision map,
Generate the global perception information.
In one embodiment, there is overlapping between the overlay area of each aware base station.
In one embodiment, the aware base station includes laser radar, millimetre-wave radar, camera and infrared sensor
At least one of.
Roadbed sensory perceptual system provided by the embodiments of the present application, can execute above method embodiment, realization principle and skill
Art effect is similar, and details are not described herein.
Specific about a kind of roadbed sensory perceptual system limits the restriction that may refer to above for roadbed cognitive method, In
This is repeated no more.Each equipment in above-mentioned roadbed sensory perceptual system can be come real fully or partially through software, hardware and combinations thereof
It is existing.Above-mentioned each equipment can be embedded in the form of hardware or independently of in the processor in computer equipment, can also be with software shape
Formula is stored in the memory in computer equipment, executes the corresponding operation of the above modules in order to which processor calls.
Fig. 6 is the structural schematic diagram for the automatic driving vehicle that one embodiment provides.As shown in fig. 6, automatic driving vehicle
It include: receiving module 210 and control module 220, in which:
Receiving module 210, for receiving the global perception information of computing terminal broadcast；According to the overall situation perception information
The perception information that the perception data that multiple base stations obtain generates；
Control module 220, for controlling vehicle driving according to the global perception information.
Automatic driving vehicle provided by the embodiments of the present application can execute above method embodiment, realization principle and skill
Art effect is similar, and details are not described herein.
Fig. 7 is the structural schematic diagram for the automatic driving vehicle that another embodiment provides.In above-mentioned embodiment illustrated in fig. 6
On the basis of, as shown in fig. 7, control module 220 includes: acquiring unit 221, determination unit 22 and control unit 223, in which:
Acquiring unit 221, for obtaining the location information of the vehicle；
Determination unit 222 determines the vehicle in the global perception information for the location information according to the vehicle
In coordinate；
Control unit 223, for according to coordinate of the vehicle in the global perception information and described global perceiving
Information controls the vehicle driving.
Automatic driving vehicle provided by the embodiments of the present application can execute above method embodiment, realization principle and skill
Art effect is similar, and details are not described herein.
Specific about a kind of automatic driving vehicle limits the restriction that may refer to above for roadbed cognitive method, In
This is repeated no more.Modules in above-mentioned automatic driving vehicle can come real fully or partially through software, hardware and combinations thereof
It is existing.Above-mentioned each module can be embedded in the form of hardware or independently of in the processor in computer equipment, can also be with software shape
Formula is stored in the memory in computer equipment, executes the corresponding operation of the above modules in order to which processor calls.
In one embodiment, a kind of computer equipment is provided, which can be terminal, internal structure
Figure can be as shown in Figure 8.The computer equipment includes processor, the memory, network interface, display connected by system bus
Screen and input unit.Wherein, the processor of the computer equipment is for providing calculating and control ability.The computer equipment is deposited
Reservoir includes non-volatile memory medium, built-in storage.The non-volatile memory medium is stored with operating system and computer journey
Sequence.The built-in storage provides environment for the operation of operating system and computer program in non-volatile memory medium.The calculating
The network interface of machine equipment is used to communicate with external terminal by network connection.When the computer equipment is executed by processor with
Realize a kind of roadbed cognitive method.The display screen of the computer equipment can be liquid crystal display or electric ink display screen,
The input unit of the computer equipment can be the touch layer covered on display screen, be also possible to be arranged on computer equipment shell
Key, trace ball or Trackpad, can also be external keyboard, Trackpad or mouse etc..
It will be understood by those skilled in the art that structure shown in Fig. 8, only part relevant to disclosure scheme is tied
The block diagram of structure does not constitute the restriction for the computer equipment being applied thereon to disclosure scheme, specific computer equipment
It may include perhaps combining certain components or with different component layouts than more or fewer components as shown in the figure.
In one embodiment, a kind of computer equipment, including memory and processor are provided, is stored in memory
Computer program, the processor perform the steps of when executing computer program
Obtain the perception data that multiple aware base stations are sent；
According to multiple perception datas, global perception information is generated；
Broadcast the global perception information.
In one embodiment, it also performs the steps of when processor executes computer program by multiple perception numbers
According to fusion treatment is carried out, the global perception information is generated.
In one embodiment, it also performs the steps of when processor executes computer program by multiple perception numbers
According to being fused in high-precision map, the global perception information is generated.
In one embodiment, there is overlapping between the overlay area of each aware base station.
In one embodiment, the aware base station includes laser radar, millimetre-wave radar, camera and infrared sensor
At least one of.
Computer equipment provided in this embodiment, implementing principle and technical effect are similar with above method embodiment, In
This is repeated no more.
In one embodiment, a kind of computer equipment, including memory and processor are provided, is stored in memory
Computer program, the processor perform the steps of when executing computer program
Receive the global perception information of broadcast；The overall situation perception information is the perception number obtained according to multiple aware base stations
According to the perception information of generation；
According to the global perception information, vehicle driving is controlled.
In one embodiment, the position for obtaining the vehicle is also performed the steps of when processor executes computer program
Confidence breath；According to the location information of the vehicle, coordinate of the vehicle in the global perception information is determined；According to described
Coordinate and the global perception information of the vehicle in the global perception information, control the vehicle driving.
Computer equipment provided in this embodiment, implementing principle and technical effect are similar with above method embodiment, In
This is repeated no more.
In one embodiment, a kind of computer readable storage medium is provided, computer program is stored thereon with, is calculated
Machine program performs the steps of when being executed by processor
Obtain the perception data that multiple aware base stations are sent；
According to multiple perception datas, global perception information is generated；
Broadcast the global perception information.
In one embodiment, it is also performed the steps of when computer program is executed by processor by multiple perception
Data carry out fusion treatment, generate the global perception information.
In one embodiment, it is also performed the steps of when computer program is executed by processor by multiple perception
Data fusion generates the global perception information into high-precision map.
In one embodiment, there is overlapping between the overlay area of each aware base station.
In one embodiment, the aware base station includes laser radar, millimetre-wave radar, camera and infrared sensor
At least one of.
In one embodiment, a kind of computer readable storage medium is provided, computer program is stored thereon with, is calculated
Machine program performs the steps of when being executed by processor
Receive the global perception information of broadcast；The overall situation perception information is the perception number obtained according to multiple aware base stations
According to the perception information of generation；
According to the global perception information, vehicle driving is controlled.
In one embodiment, it is also performed the steps of when computer program is executed by processor and obtains the vehicle
Location information；According to the location information of the vehicle, coordinate of the vehicle in the global perception information is determined；According to institute
Coordinate and the global perception information of the vehicle in the global perception information are stated, the vehicle driving is controlled.
Those of ordinary skill in the art will appreciate that realizing all or part of the process in above-described embodiment method, being can be with
Relevant hardware is instructed to complete by computer program, the computer program can be stored in a non-volatile computer
In read/write memory medium, the computer program is when being executed, it may include such as the process of the embodiment of above-mentioned each method.Wherein,
To any reference of memory, storage, database or other media used in each embodiment provided by the disclosure,
Including non-volatile and/or volatile memory.Nonvolatile memory may include read-only memory (ROM), programming ROM
(PROM), electrically programmable ROM (EPROM), electrically erasable ROM (EEPROM) or flash memory.Volatile memory may include
Random access memory (RAM) or external cache.By way of illustration and not limitation, RAM is available in many forms,
Such as static state RAM (SRAM), dynamic ram (DRAM), synchronous dram (SDRAM), double data rate sdram (DDRSDRAM), enhancing
Type SDRAM (ESDRAM), synchronization link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM
(RDRAM), direct memory bus dynamic ram (DRDRAM) and memory bus dynamic ram (RDRAM) etc..
Each technical characteristic of embodiment described above can be combined arbitrarily, for simplicity of description, not to above-mentioned reality
It applies all possible combination of each technical characteristic in example to be all described, as long as however, the combination of these technical characteristics is not deposited
In contradiction, all should be considered as described in this specification.
The embodiments described above only express several embodiments of the present invention, and the description thereof is more specific and detailed, but simultaneously
It cannot therefore be construed as limiting the scope of the patent.It should be pointed out that coming for those of ordinary skill in the art
It says, without departing from the inventive concept of the premise, various modifications and improvements can be made, these belong to protection of the invention
Range.Therefore, the scope of protection of the patent of the invention shall be subject to the appended claims.
Claims (10)
1. a kind of roadbed cognitive method, which is characterized in that the described method includes:
Obtain the perception data that multiple aware base stations are sent；
According to multiple perception datas, global perception information is generated；
Broadcast the global perception information.
2. method according to claim 1, which is characterized in that it is described according to multiple perception datas, generate global perception
Information, comprising:
Multiple perception datas are subjected to fusion treatment, generate the global perception information.
3. method according to claim 2, which is characterized in that it is described that multiple perception datas are subjected to fusion treatment, it is raw
At the global perception information, comprising:
Multiple perception datas are fused in high-precision map, the global perception information is generated.
4. any one of -3 the method according to claim 1, which is characterized in that deposited between the overlay area of each aware base station
It is being overlapped.
5. any one of -3 the method according to claim 1, which is characterized in that the aware base station includes laser radar, millimeter
At least one of wave radar, camera and infrared sensor.
6. a kind of roadbed cognitive method, which is characterized in that the described method includes:
Receive the global perception information of broadcast；The overall situation perception information is the perception data life obtained according to multiple aware base stations
At perception information；
According to the global perception information, vehicle driving is controlled.
7. a kind of roadbed sensory perceptual system, which is characterized in that the system comprises: at least two aware base stations, calculate equipment and logical
Interrogate equipment；The calculating equipment is connect at least two aware base station and the communication apparatus respectively；
At least two aware base station is used to send multiple perception datas to the calculating equipment；
The calculating equipment is used to generate global perception information according to the multiple perception data；
The communication apparatus is for broadcasting the global perception information.
8. system according to claim 7, which is characterized in that the computing device includes integrated unit；The integrated unit
It is connect respectively at least two aware base station and the communication apparatus；
The integrated unit generates the global perception information for multiple perception datas to be carried out fusion treatment.
9. system according to claim 8, which is characterized in that
The integrated unit is specifically used for for multiple perception datas being fused in high-precision map, generates the global perception letter
Breath.
10. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that the computer program
The step of method of any of claims 1-6 is realized when being executed by processor.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111426326A (en) * | 2020-01-17 | 2020-07-17 | 深圳市镭神智能系统有限公司 | Navigation method, device, equipment, system and storage medium |
| CN111866728A (en) * | 2020-09-23 | 2020-10-30 | 深圳市速腾聚创科技有限公司 | Multi-site roadbed network sensing method, device, terminal and system |
| CN112687107A (en) * | 2021-03-15 | 2021-04-20 | 中智行科技有限公司 | Perception data acquisition method and device |
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| CN114067556A (en) * | 2020-08-05 | 2022-02-18 | 北京万集科技股份有限公司 | Environment sensing method, device, server and readable storage medium |
| CN114078325A (en) * | 2020-08-19 | 2022-02-22 | 北京万集科技股份有限公司 | Multi-perception system registration method and device, computer equipment and storage medium |
| CN114449533A (en) * | 2020-10-30 | 2022-05-06 | 北京万集科技股份有限公司 | Base station deployment method, environment perception method, device, computer equipment and storage medium |
Citations (20)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2001099930A (en) * | 1999-09-29 | 2001-04-13 | Fujitsu Ten Ltd | Sensor for monitoring periphery |
| CN101241188A (en) * | 2007-02-06 | 2008-08-13 | 通用汽车环球科技运作公司 | Collision avoidance system and method of detecting overpass locations using data fusion |
| BRPI0703071A2 (en) * | 2007-08-02 | 2009-03-17 | Andre Mauro Vas | Modular mobile automotive tracking, safety and performance analysis system |
| CN106093924A (en) * | 2016-06-01 | 2016-11-09 | 杨星 | Communication and the movement state information extracting method of radar collaborative perception |
| CN106774306A (en) * | 2016-11-30 | 2017-05-31 | 百度在线网络技术（北京）有限公司 | It is applied to startup detection method, device and the system of automatic driving vehicle |
| CN107274695A (en) * | 2016-04-08 | 2017-10-20 | 上海三思电子工程有限公司 | Intelligent illuminating system, intelligent vehicle and its vehicle DAS (Driver Assistant System) and method |
| CN107328410A (en) * | 2017-06-30 | 2017-11-07 | 百度在线网络技术（北京）有限公司 | Method and automobile computer for positioning automatic driving vehicle |
| CN108061903A (en) * | 2017-11-29 | 2018-05-22 | 江苏若博机器人科技有限公司 | A kind of round-the-clock low speed unmanned vehicle detection obstacle avoidance system of Multi-sensor Fusion |
| CN108182817A (en) * | 2018-01-11 | 2018-06-19 | 北京图森未来科技有限公司 | Automatic Pilot auxiliary system, trackside end auxiliary system and vehicle-mounted end auxiliary system |
| CN108510775A (en) * | 2018-03-12 | 2018-09-07 | 北京图森未来科技有限公司 | A kind of bus or train route cooperative system and its bus or train route cooperate with trackside awareness apparatus |
| CN108549084A (en) * | 2018-01-30 | 2018-09-18 | 西安交通大学 | A kind of target detection based on sparse two-dimensional laser radar and Attitude estimation method |
| CN108828527A (en) * | 2018-06-19 | 2018-11-16 | 驭势（上海）汽车科技有限公司 | A kind of multi-Sensor Information Fusion Approach, device, mobile unit and storage medium |
| CN108877269A (en) * | 2018-08-20 | 2018-11-23 | 清华大学 | A kind of detection of intersection vehicle-state and V2X broadcasting method |
| CN109086277A (en) * | 2017-06-13 | 2018-12-25 | 纵目科技（上海）股份有限公司 | A kind of overlay region building ground drawing method, system, mobile terminal and storage medium |
| CN109147317A (en) * | 2018-07-27 | 2019-01-04 | 中国科学院深圳先进技术研究院 | Automatic Pilot navigation system, method and device based on bus or train route collaboration |
| CN109166314A (en) * | 2018-09-29 | 2019-01-08 | 河北德冠隆电子科技有限公司 | Road conditions awareness apparatus and bus or train route cooperative system based on omnidirectional tracking detection radar |
| CN109344813A (en) * | 2018-11-28 | 2019-02-15 | 北醒（北京）光子科技有限公司 | A kind of target identification and scene modeling method and device based on RGBD |
| CN109353179A (en) * | 2018-10-19 | 2019-02-19 | 中国第汽车股份有限公司 | A kind of active suspension system and control method based on high-precision map cloud information |
| CN109774712A (en) * | 2018-12-17 | 2019-05-21 | 北京汽车集团有限公司 | The method, apparatus and vehicle of vehicle control |
| CN110132290A (en) * | 2019-05-20 | 2019-08-16 | 北京百度网讯科技有限公司 | Perception information method for amalgamation processing, device, equipment and storage medium |
-
2019
- 2019-06-04 CN CN201910480779.4A patent/CN110412595A/en active Pending
Patent Citations (20)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2001099930A (en) * | 1999-09-29 | 2001-04-13 | Fujitsu Ten Ltd | Sensor for monitoring periphery |
| CN101241188A (en) * | 2007-02-06 | 2008-08-13 | 通用汽车环球科技运作公司 | Collision avoidance system and method of detecting overpass locations using data fusion |
| BRPI0703071A2 (en) * | 2007-08-02 | 2009-03-17 | Andre Mauro Vas | Modular mobile automotive tracking, safety and performance analysis system |
| CN107274695A (en) * | 2016-04-08 | 2017-10-20 | 上海三思电子工程有限公司 | Intelligent illuminating system, intelligent vehicle and its vehicle DAS (Driver Assistant System) and method |
| CN106093924A (en) * | 2016-06-01 | 2016-11-09 | 杨星 | Communication and the movement state information extracting method of radar collaborative perception |
| CN106774306A (en) * | 2016-11-30 | 2017-05-31 | 百度在线网络技术（北京）有限公司 | It is applied to startup detection method, device and the system of automatic driving vehicle |
| CN109086277A (en) * | 2017-06-13 | 2018-12-25 | 纵目科技（上海）股份有限公司 | A kind of overlay region building ground drawing method, system, mobile terminal and storage medium |
| CN107328410A (en) * | 2017-06-30 | 2017-11-07 | 百度在线网络技术（北京）有限公司 | Method and automobile computer for positioning automatic driving vehicle |
| CN108061903A (en) * | 2017-11-29 | 2018-05-22 | 江苏若博机器人科技有限公司 | A kind of round-the-clock low speed unmanned vehicle detection obstacle avoidance system of Multi-sensor Fusion |
| CN108182817A (en) * | 2018-01-11 | 2018-06-19 | 北京图森未来科技有限公司 | Automatic Pilot auxiliary system, trackside end auxiliary system and vehicle-mounted end auxiliary system |
| CN108549084A (en) * | 2018-01-30 | 2018-09-18 | 西安交通大学 | A kind of target detection based on sparse two-dimensional laser radar and Attitude estimation method |
| CN108510775A (en) * | 2018-03-12 | 2018-09-07 | 北京图森未来科技有限公司 | A kind of bus or train route cooperative system and its bus or train route cooperate with trackside awareness apparatus |
| CN108828527A (en) * | 2018-06-19 | 2018-11-16 | 驭势（上海）汽车科技有限公司 | A kind of multi-Sensor Information Fusion Approach, device, mobile unit and storage medium |
| CN109147317A (en) * | 2018-07-27 | 2019-01-04 | 中国科学院深圳先进技术研究院 | Automatic Pilot navigation system, method and device based on bus or train route collaboration |
| CN108877269A (en) * | 2018-08-20 | 2018-11-23 | 清华大学 | A kind of detection of intersection vehicle-state and V2X broadcasting method |
| CN109166314A (en) * | 2018-09-29 | 2019-01-08 | 河北德冠隆电子科技有限公司 | Road conditions awareness apparatus and bus or train route cooperative system based on omnidirectional tracking detection radar |
| CN109353179A (en) * | 2018-10-19 | 2019-02-19 | 中国第汽车股份有限公司 | A kind of active suspension system and control method based on high-precision map cloud information |
| CN109344813A (en) * | 2018-11-28 | 2019-02-15 | 北醒（北京）光子科技有限公司 | A kind of target identification and scene modeling method and device based on RGBD |
| CN109774712A (en) * | 2018-12-17 | 2019-05-21 | 北京汽车集团有限公司 | The method, apparatus and vehicle of vehicle control |
| CN110132290A (en) * | 2019-05-20 | 2019-08-16 | 北京百度网讯科技有限公司 | Perception information method for amalgamation processing, device, equipment and storage medium |
Cited By (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111426326A (en) * | 2020-01-17 | 2020-07-17 | 深圳市镭神智能系统有限公司 | Navigation method, device, equipment, system and storage medium |
| CN111426326B (en) * | 2020-01-17 | 2022-03-08 | 深圳市镭神智能系统有限公司 | Navigation method, device, equipment, system and storage medium |
| CN113433542A (en) * | 2020-03-18 | 2021-09-24 | 广州汽车集团股份有限公司 | Vehicle positioning method and device, road side equipment and storage medium |
| CN114067556B (en) * | 2020-08-05 | 2023-03-14 | 北京万集科技股份有限公司 | Environment sensing method, device, server and readable storage medium |
| CN114067556A (en) * | 2020-08-05 | 2022-02-18 | 北京万集科技股份有限公司 | Environment sensing method, device, server and readable storage medium |
| CN114078325A (en) * | 2020-08-19 | 2022-02-22 | 北京万集科技股份有限公司 | Multi-perception system registration method and device, computer equipment and storage medium |
| CN114078325B (en) * | 2020-08-19 | 2023-09-05 | 北京万集科技股份有限公司 | Multi-perception system registration method, device, computer equipment and storage medium |
| WO2022062571A1 (en) * | 2020-09-23 | 2022-03-31 | 深圳市速腾聚创科技有限公司 | Multi-site roadbed network perception method, apparatus and system, and terminal |
| CN112566032A (en) * | 2020-09-23 | 2021-03-26 | 深圳市速腾聚创科技有限公司 | Multi-site roadbed network sensing method, terminal and system |
| US20230228593A1 (en) * | 2020-09-23 | 2023-07-20 | Suteng Innovation Technology Co., Ltd. | Method, device and system for perceiving multi-site roadbed network and terminal |
| CN111866728A (en) * | 2020-09-23 | 2020-10-30 | 深圳市速腾聚创科技有限公司 | Multi-site roadbed network sensing method, device, terminal and system |
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