CN108776472A - Intelligent driving control method and system, onboard control device and intelligent driving vehicle - Google Patents
Intelligent driving control method and system, onboard control device and intelligent driving vehicle Download PDFInfo
- Publication number
- CN108776472A CN108776472A CN201810476519.5A CN201810476519A CN108776472A CN 108776472 A CN108776472 A CN 108776472A CN 201810476519 A CN201810476519 A CN 201810476519A CN 108776472 A CN108776472 A CN 108776472A
- Authority
- CN
- China
- Prior art keywords
- control signal
- algorithm
- sensor information
- control
- generates
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 35
- 230000006870 function Effects 0.000 claims description 25
- 230000004927 fusion Effects 0.000 claims description 14
- 238000004590 computer program Methods 0.000 claims description 2
- 238000010586 diagram Methods 0.000 description 6
- 238000001514 detection method Methods 0.000 description 3
- 230000008447 perception Effects 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 241001347978 Major minor Species 0.000 description 2
- 230000009977 dual effect Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 239000011551 heat transfer agent Substances 0.000 description 2
- 230000011218 segmentation Effects 0.000 description 2
- 238000013473 artificial intelligence Methods 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 230000000295 complement effect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 239000013589 supplement Substances 0.000 description 1
- 238000003786 synthesis reaction Methods 0.000 description 1
- 230000003245 working effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
- G05D1/0246—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing means
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0255—Control of position or course in two dimensions specially adapted to land vehicles using acoustic signals, e.g. ultra-sonic singals
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0257—Control of position or course in two dimensions specially adapted to land vehicles using a radar
Abstract
The embodiment of the present disclosure is related to intelligent driving control method and system, onboard control device and intelligent driving vehicle.First control signal and second control signal are generated using two algorithms in this method, and according to the state of first control signal, selects first control signal or second control signal to control vehicle, to realize the Redundant Control of intelligent driving.Security risk can be greatly reduced.
Description
Technical field
Embodiment of the disclosure is related to intelligent driving field more particularly to intelligent driving control method and system, vehicle-mounted control
Control equipment and intelligent driving vehicle.
Background technology
Intelligent driving system including automated driving system is determined accordingly based on sensor sensing external environment
Plan, and to the control of vehicle.When intelligent driving system breaks down, the improper control to vehicle is frequently can lead to, causes weight
Big safety accident.In addition during to relation technological researching, inventor has found：Generally there are detections for automated driving system
Limitation, the automated driving system of single type be often difficult to ensure and can be accurately identified to all scenes of nature, therefore
Also control decision of the automated driving system to vehicle can be influenced.
Invention content
One purpose of an embodiment of the present disclosure is to solve at least one of technical problem mentioned above.
In a first aspect, the embodiment of the present disclosure provides a kind of intelligent driving control method, including：
Obtain first sensor information and second sensor information；
It is based on the first sensor information using the first algorithm and generates first control signal；
It is based on the second sensor information using the second algorithm and generates second control signal；
Based on the state of the first control signal, the first control signal or the second control signal pair are selected
Vehicle is controlled.
In some embodiments, the state based on the first control signal, select the first control signal or
The second control signal controls vehicle, including：
When detecting that the first control signal normally generates, vehicle is controlled based on the first control signal
System；
When detecting that the first control signal cannot be generated normally, vehicle is carried out based on the second control signal
Control.
In some embodiments, first algorithm is different from the algorithm logic of the second algorithm.
In some embodiments, the functional class of first algorithm is higher than the functional class of second algorithm.
In some embodiments, first algorithm has automatic Pilot global function；Second algorithm only has peace
Full security function.
It is in some embodiments, described to be based on first sensor information generation first control signal using the first algorithm,
Including：
Operation is carried out to the first sensor information using first algorithm, generates the first control signal；
It is described to be based on second sensor information generation second control signal using the second algorithm, including：
Operation is carried out to the second sensor information using second algorithm, generates the second control signal.
In some embodiments, the first sensor information includes one or several kinds of sensings in following sensor
The data that device is acquired：
Millimetre-wave radar, the first camera, laser radar, ultrasonic radar, GPS；
It is described that operation is carried out to the first sensor information using first algorithm, generate the first control letter
Number, including：
The first sensor information is merged, path planning and decision are carried out according to fusion results, described in generation
First control signal.
In some embodiments, the second sensor information includes：Second camera acquired image；
It is described that operation is carried out to the second sensor information using second algorithm, generate the second control letter
Number, including：
The second camera acquired image is split using intelligent algorithm, determines wheeled region；
Path planning and decision are carried out according to identified wheeled region, generates the second control signal.
Second aspect, the embodiment of the present disclosure provide a kind of intelligent driving control system again, including：
Acquisition module, for obtaining first sensor information and second sensor information；
First control module generates first control signal for being based on first sensor information using the first algorithm；
Second control module generates second control signal for being based on second sensor information using the second algorithm；
Control selections module, be used for the state based on the first control signal, select the first control signal or
The second control signal controls vehicle.
In some embodiments, the control selections module, for detecting that the first control signal normally gives birth to
Cheng Shi controls vehicle based on the first control signal；Detecting that the first control signal cannot generate normally
When, vehicle is controlled based on the second control signal.
In some embodiments, first algorithm is different from the algorithm logic of the second algorithm.
In some embodiments, the functional class of first algorithm is higher than the functional class of second algorithm.
In some embodiments, first algorithm has automatic Pilot global function；Second algorithm only has peace
Full security function.
In some embodiments, first control module is based on first sensor information using the first algorithm and generates the
One control signal, including：
Operation is carried out to the first sensor information using first algorithm, generates the first control signal；
Second control module is based on second sensor information using the second algorithm and generates second control signal, including：
Operation is carried out to the second sensor information using second algorithm, generates the second control signal.
In some embodiments, the first sensor information include one kind in following sensor or
The data that several sensors are acquired：
Millimetre-wave radar, the first camera, laser radar, ultrasonic radar, GPS；
First control module carries out operation using first algorithm to the first sensor information, described in generation
First control signal, including：
The first sensor information is merged, path planning and decision are carried out according to fusion results, described in generation
First control signal.
In some embodiments, the second sensor information includes：Second camera acquired image；
Second control module carries out operation using second algorithm to the second sensor information, described in generation
Second control signal, including：
The second camera acquired image is split using intelligent algorithm, determines wheeled region；
Path planning and decision are carried out according to identified wheeled region, generates the second control signal.
The third aspect, the embodiment of the present disclosure provide again a kind of onboard control device, including：At least one processor, extremely
The computer program that lacks a processor and storage on a memory and can run on a processor, the processor execute institute
The step of first aspect the method being realized when stating program.
Fourth aspect, a kind of intelligent driving vehicle include the onboard control device as described in the third aspect.
In at least one embodiment of the disclosure, first control signal and second control signal are generated using two algorithms, and
According to the state of first control signal, first control signal or second control signal is selected to control vehicle, to realize
The Redundant Control of intelligent driving.Security risk can be greatly reduced.
Description of the drawings
Fig. 1 shows the intelligent driving control system architecture schematic diagram that one embodiment of the disclosure provides；
Fig. 2 shows another schematic diagrames of intelligent driving Control system architecture that one embodiment of the disclosure provides；
Fig. 3 shows the onboard control device structure diagram that one embodiment of the disclosure provides；
Fig. 4 shows the flow diagram for the intelligent driving control method that one embodiment of the disclosure provides.
Specific implementation mode
It should be appreciated that specific embodiment described herein is only used to explain the disclosure, it is not used to limit the disclosure.
In a first aspect, embodiment of the disclosure provides a kind of intelligent driving control system, to execute the implementation of the disclosure
The intelligent driving control method that example provides, and then realize the intelligent driving of vehicle.Herein, intelligent driving can refer to being promoted to drive
The auxiliary of the driving experience for the person of sailing drives, and may also mean that there is no unmanned when the case where driver.
Referring to Fig. 1, Fig. 1 is the schematic diagram for the intelligent driving control system that one embodiment of the disclosure provides.As shown in Figure 1,
Embodiment of the disclosure provide intelligent driving control system 100 include：
Acquisition module 101, for obtaining first sensor information and second sensor information；
First control module 102 generates first control signal for being based on first sensor information using the first algorithm；
Second control module 103 generates second control signal for being based on second sensor information using the second algorithm；
Control selections module 104, be used for the state based on the first control signal, select the first control signal or
Second control signal described in person controls vehicle.
It is understood that " first " herein, " second " mainly distinguish, to illustrate two class herein not
Sensor information (first sensor information and second sensor information) together, two different control signals (the first control letter
Number and second control signal), two different algorithms (the first algorithm and the second algorithm), and should not be construed limit sequentially
It is fixed.It should be noted that " different algorithms " here are not meant to that algorithm used by limiting must be different, use is identical
Algorithm can't influence embodiment of the disclosure scheme implementation.
In some embodiments, first algorithm is different from the algorithm logic of the second algorithm.In some implementations
In mode, the functional class of first algorithm is higher than the functional class of second algorithm.In some embodiments, described
First algorithm has automatic Pilot global function；Second algorithm only has safety guarantee function.
In order to realize intelligent driving, firstly, it is necessary to be obtained by the acquisition module 101 in intelligent driving control system 100
First sensor information and second sensor information, wherein first sensor information is that the multiple sensors configured on vehicle are adopted
The information of collection, including：One or more of millimetre-wave radar, the first camera, laser radar, ultrasonic radar, GPS etc..
The type of the sensor configured on vehicle is more, and the first sensor information that acquisition module 101 is got is abundanter.Second sensing
Device information is the information of the forward direction camera acquisition on vehicle, to determine the wheeled region of vehicle front.
First control module 102 and the second control module 103 are connected with acquisition module 101 respectively, the first control module 102
First sensor information is obtained by acquisition module 101, the second control module 103 obtains the second sensing by acquisition module 101
Device information.103 respective independent operating of first control module 102 and the second control module, the two can be run parallel, mutually not shadow
It rings.
First control module 102 is based on first sensor information using the first algorithm, generates first control signal.Specifically
Ground, the first control module 102 first merge the information from multiple sensors, then according to fusion results into walking along the street
Diameter is planned and decision, ultimately produces first control signal.Due to the letter of the first control module 102 synthesis multiple sensors acquisition
Breath, so the perception to external environment is more comprehensive and accurate, is as far as possible identified all scenes of nature, thus generates
First control signal it is relatively reliable.
Second control module 103 is based on second sensor information using the second algorithm, generates second control signal.Specifically
Ground, the second control module 103 utilize intelligent algorithm, are split to the image of the forward direction camera acquisition on vehicle, really
Determine the wheeled region of vehicle front, path planning and decision are then carried out according to identified wheeled region, generates second
Control signal.
Control selections module 104 is respectively connected with the first control module 102 and the second control module 103.Control selections mould
In the second control signal that the first control signal and the second control module 103 that block 104 is generated from the first control module 102 generate
One control signal of selection, to control vehicle.In synchronization, control selections module 104 only selects first control signal and
Control signal of one of the two control signals as final control vehicle.Specifically, control selections module is detecting first
When control signal normally generates, vehicle is controlled based on first control signal；Detecting that first control signal cannot be just
When often generating, vehicle is controlled based on second control signal.
Due to information of the first control signal based on multiple sensors, and the forward direction that second control signal is based only upon vehicle is taken the photograph
As head, so compared to second control signal, first control signal is more accurate and reliable, thus, first control signal is suitble to
As master signal, second control signal is suitable as spare control signal or auxiliary control signal.First control signal just
Often generate when, control selections module 104 select first control signal vehicle is controlled, first control signal cannot be normal
When generation, control selections module 104 selects second control signal to control vehicle.
In this way, even if the first control module 102 break down or vehicle on one or more sensors break down,
Control selections module 104 can still control vehicle by the second control signal that the second control module 103 generates, and ensure
To the continuity and reliability of vehicle control.
Referring to Fig. 2, Fig. 2 is another schematic diagram for the intelligent driving control system that one embodiment of the disclosure provides.Such as Fig. 2 institutes
Show, the intelligent driving control system that embodiment of the disclosure provides includes：Master control system, auxiliary control system and vehicle control
Module P007.Master control system and auxiliary control system are concurrent workings, possess complete perception decision-making capability respectively, only respectively
It is vertical to complete the judgement to automatic Pilot environment and decision.Master control system and auxiliary control system form major-minor dual system, main control
System and auxiliary control system are mutual indepedent, and auxiliary control system improves intelligence and drive as the supplement of master control system or spare
Sail safety and the reliability of control system.
Wherein, master control system includes：A variety of detecting sensor P001, data fusion module P002 and automatic Pilot are complete
Function algorithm module P003, P001 are connected with P002, and P002 is connected with P003.Auxiliary control system includes：Wheeled region detection
Camera P004, wheeled regional processing algoritic module P005 and automatic Pilot safety traffic algoritic module P006, P004 with
P005 is connected, and P005 is connected with P006.P003 and P006 are connected with P007 respectively.
Wherein, P001 is a part for acquisition module 101, for obtaining first sensor information, first sensor information
It is the input of master control system, is input to P002.P001 includes a variety of detecting sensors, such as：Millimetre-wave radar, camera,
Laser radar, ultrasonic radar and GPS etc..Information based on the acquisition of a variety of detecting sensors, it is ensured that master control system is complete
The realization of function.
P002 and P003 completes the function of the first control module 102 jointly.First, P002 is to all perception from P001
Information carries out fusion treatment, and the result of fusion treatment is the external environment current to vehicle, then by the result of fusion treatment
It is output to P003.P003 according to fusion treatment as a result, completing automatic Pilot path planning and decision, believe by the first control of output
Number, realize automatic Pilot global function.
P004 is the forward direction camera for detecting wheeled region, is another part of acquisition module 101, for obtaining
It is the input of auxiliary control system to take the second heat transfer agent, the second heat transfer agent, is input to P005, based on it is preceding to camera acquire
Image realizes basic automatic Pilot detection demand.
P005 and P006 completes the function of the second control module 103 jointly.First, P005 to P004 the image collected into
Row processing, the wheeled region of vehicle front is partitioned into using artificial intelligence (AI) algorithm, then by the wheeled of vehicle front
Region is output to P006.P006 according to the wheeled region of vehicle front, based on safety is ensured under the premise of cook up vehicle
Driving path and vehicle control decision, export second control signal, and realization ensures safe Function for Automatic Pilot.
P003 in master control system uses automatic Pilot global function algorithm, and the P006 in auxiliary control system is using artificial
Intelligent algorithm, master control system and auxiliary control system use different algorithm logics, avoid the occurrence of same source error, have mutual complementary energy
Power.
P007 completes the function of control selections module 104.The work of P007 real-time judges master control system and auxiliary control system
Make state, it is ensured that the normal control of vehicle.It is normal in master control system, preferentially use master control system global function mould
Formula works, and receives the first control signal of P003 outputs；When master control system breaks down, P007 will automatically switch to auxiliary control
System safety traffic pattern work processed, receives the second control signal of P006 outputs.Whether no matter master control system breaks down,
It can guarantee that vehicle safe driving, the redundancy of major-minor dual system improve the safe class of vehicle drive.Also, main control system
System has automatic Pilot global function, and auxiliary control system only has ensures safe Function for Automatic Pilot, and auxiliary control system is compared
Degrade in master control system function, fully ensures that safety on the basis of realizing vehicle control, while being also effectively controlled and being
System cost.
Second aspect, embodiment of the disclosure provide a kind of onboard control device, referring to Fig. 3, the onboard control device,
Including：At least one processor (processor), at least one processor (memory), bus and at least one bus connect
Mouthful；
Wherein, the processor and memory complete mutual communication by the bus, and the processor is used for
The program instruction in the memory is called, to execute the intelligent driving control method that the embodiment of the present disclosure is provided.It is described total
Line interface is used to carry out data interaction with external equipment.
The third aspect, embodiment of the disclosure provide a kind of intelligent driving vehicle, including vehicle-mounted described in second aspect
Control device.Since onboard control device being described in detail above, details are not described herein.
Fourth aspect, embodiment of the disclosure provide a kind of intelligent driving control method, are carried by embodiment of the disclosure
The intelligent driving control system of confession executes, and then realizes the intelligent driving of vehicle.Referring to Fig. 4, this method includes：
Step S11 obtains first sensor information and second sensor information.
Step S12 is based on the first sensor information using the first algorithm and generates first control signal.
Step S13 is based on the second sensor information using the second algorithm and generates second control signal.
Step S14 selects the first control signal or second control based on the state of the first control signal
Signal processed controls vehicle.
Signified " control signal " refers to the signal of the traveling for controlling vehicle, these signals in embodiment of the disclosure
Can include speed control signal, steering controling signal, brake control signal, light controling signal etc.." the first algorithm " or "
Two algorithms " refer to then generating these control signal institute foundations based on acquired first sensor information or second sensor information
Algorithm.Specifically, intelligent driving control system carries out operation using the first algorithm to first sensor information, and utilizes the
Two algorithms carry out operation to second sensor information, and driving path planning and vehicle control decision are completed according to each operation, into
And generate corresponding control signal.
In some embodiments, different algorithm logics may be used in the first algorithm and the second algorithm, can reduce in this way
The probability of two algorithms simultaneous faults in application process reduces common cause fault.Further, the work(of two algorithms can be set
Energy level is identical, or for the considerations of reducing cost, and the functional class that the first algorithm can also be arranged is higher than the work(of the second algorithm
It can rank.Here functional class refer to should be generated algorithmically by control signal possessed by control function rank.Implementing
When, the first control signal generated using the first algorithm can have automatic Pilot global function；The generated using the second algorithm
Two control signals can only have safety guarantee function.
In addition to above mentioned algorithm logic and functional class are different, the sensor information that two algorithms are based on
It can be different.Specifically, the first algorithm of utilization in above-mentioned S12, which is based on the first sensor information, generates the first control
Signal may include：
The first sensor information is merged, path planning and decision are carried out according to fusion results, described in generation
First control signal.
In the specific implementation, first sensor information here may include that the one or several kinds of lower sensor kind such as pass
The information that sensor is acquired：Millimetre-wave radar, the first camera, laser radar, ultrasonic radar, GPS.Certainly can also include
The information of other sensors acquisition, it is not limited in this embodiment of the present disclosure.
Then first sensor information is merged, carries out path planning and decision according to fusion results, generates first
Control signal.It specifically, can be by millimetre-wave radar, the first camera, laser radar, ultrasonic radar, the sensors such as GPS
A variety of data of acquisition are merged.Wherein, data fusion here can be described as：The information of comprehensive multi-source, obtains Gao Pin
The useful information of matter.Since various single sensors tend not to extract enough information from scene, so that it is difficult to
It even can not independently obtain comprehensive description to a secondary scene, it is therefore desirable to obtain target data while multisensor and be melted
Analysis is closed, Classification and Identification decision just can be effectively carried out.Understandable to be, the result after merging can illustrate currently substantially
The traffic information of traveling carries out planning and the decision in path then according to the result of fusion, generates corresponding first control letter
Number.The first control signal can be driven a car with indicating intelligent and execute corresponding driver behavior, such as brake, turning, deceleration etc..
In some embodiments, the second sensor information is transported using second algorithm in step S13
It calculates, generates the second control signal, may include：
The second camera acquired image is split using intelligent algorithm, determines wheeled region；
Path planning and decision are carried out according to identified wheeled region, generates the second control signal.
Specifically, second sensor information here may include：Second camera acquired image.Second camera shooting
The image of head acquisition is the image in intelligent driving automobile direction of advance.Then utilize intelligent algorithm to second camera
Acquired image is split, and then carries out analyzing processing to the image after segmentation, is determined according to the image after segmentation
Where road ahead is wheeled region；It is possible to further carry out path planning according to identified wheeled region and determine
Plan generates second control signal, which can be driven a car with indicating intelligent travels to wheeled region direction.
In some embodiments, the state based on the first control signal in step S14 selects first control
Signal or the second control signal control vehicle, may include：
When detecting that the first control signal normally generates, vehicle is controlled based on the first control signal
System；
When detecting that the first control signal cannot be generated normally, vehicle is carried out based on the second control signal
Control.
Wherein, the reason of first control signal cannot be generated normally may include：Running software mistake or failure, Jin Erwu
Method effective integration is carried out to first sensor information and/or can not be carried out according to first sensor information correct path planning and
Decision.The reason of certain first control signal cannot be generated normally can also include：Hardware device configured with the software occurs
Failure (such as the power-off, short circuit etc.) reasons such as cause software that can not run, it is not limited in this embodiment of the present disclosure.
In embodiment of the disclosure, first control signals and second control signal are generated using two algorithms, and according to the
The state of one control signal, selects first control signal or second control signal to control vehicle, to realize intelligence
The Redundant Control of driving.Security risk can be greatly reduced.
It should be noted that since the intelligent driving control system that first aspect is introduced is that can execute implementation of the present invention
The system of intelligent driving control method in example, so the side based on the intelligent driving control described in the embodiment of the present invention
Method, those skilled in the art can understand the specific implementation mode of the intelligent driving control system of the present embodiment and it is each
Kind version, so how to realize that the intelligent driving in the embodiment of the present invention controls for the intelligent driving control system at this
Method is no longer discussed in detail.It is adopted as long as those skilled in the art implement intelligent driving control method in the embodiment of the present invention
System belongs to the range to be protected of the application.
In the instructions provided here, numerous specific details are set forth.It is to be appreciated, however, that the implementation of the application
Example can be put into practice without these specific details.In some instances, well known method, structure is not been shown in detail
And technology, so as not to obscure the understanding of this description.
Similarly, it should be understood that in order to simplify the disclosure and help to understand one or more of each application aspect,
Above in the description of the exemplary embodiment of the application, each feature of the application is grouped together into single implementation sometimes
In example, figure or descriptions thereof.However, the method for the disclosure should be construed to reflect following intention：It is i.e. required to protect
Shield this application claims the more features of feature than being expressly recited in each claim.More precisely, as following
Claims reflect as, all features less than single embodiment disclosed above are in terms of application.Therefore,
Thus the claims for following specific implementation mode are expressly incorporated in the specific implementation mode, wherein each claim itself
All as the separate embodiments of the application.
Those skilled in the art, which are appreciated that, to carry out adaptively the module in the equipment in embodiment
Change and they are arranged in the one or more equipment different from the embodiment.It can be the module or list in embodiment
Member or component be combined into a module or unit or component, and can be divided into addition multiple submodule or subelement or
Sub-component.Other than such feature and/or at least some of process or unit exclude each other, it may be used any
Combination is disclosed to all features disclosed in this specification (including adjoint claim, abstract and attached drawing) and so to appoint
Where all processes or unit of method or equipment are combined.Unless expressly stated otherwise, this specification (including adjoint power
Profit requires, abstract and attached drawing) disclosed in each feature can be by providing the alternative features of identical, equivalent or similar purpose come generation
It replaces.
In addition, it will be appreciated by those of skill in the art that although some embodiments in this include institute in other embodiments
Including certain features rather than other feature, but the combination of the feature of different embodiment means to be in scope of the present application
Within and form different embodiments.For example, in the following claims, embodiment claimed it is arbitrary it
One mode can use in any combination.
Certain unit embodiments of the application can be with hardware realization, or to run on one or more processors
Software module realize, or realized with combination thereof.
The application is limited it should be noted that above-described embodiment illustrates rather than the application, and ability
Field technique personnel can design alternative embodiment without departing from the scope of the appended claims.In the claims,
Any reference mark between bracket should not be configured to limitations on claims.Word "comprising" does not exclude the presence of not
Element or step listed in the claims.Word "a" or "an" before element does not exclude the presence of multiple such
Element.The application can be by means of including the hardware of several different elements and being come by means of properly programmed computer real
It is existing.In the unit claims listing several devices, several in these devices can be by the same hardware branch
To embody.The use of word first, second etc. does not indicate that any sequence.These words can be construed to title.
Claims (18)
1. a kind of intelligent driving control method, which is characterized in that including：
Obtain first sensor information and second sensor information；
It is based on the first sensor information using the first algorithm and generates first control signal；
It is based on the second sensor information using the second algorithm and generates second control signal；
Based on the state of the first control signal, select the first control signal or the second control signal to vehicle
It is controlled.
2. according to the method described in claim 1, it is characterized in that, the state based on the first control signal, described in selection
First control signal or the second control signal control vehicle, including：
When detecting that the first control signal normally generates, vehicle is controlled based on the first control signal；
When detecting that the first control signal cannot be generated normally, vehicle is controlled based on the second control signal
System.
3. according to the method described in claim 1, it is characterized in that, the algorithm logic of first algorithm and second algorithm
It is different.
4. according to the method described in claim 3, it is characterized in that, the functional class of first algorithm is calculated higher than described second
The functional class of method.
5. according to the method described in claim 4, it is characterized in that, first algorithm has automatic Pilot global function；It is described
Second algorithm only has safety guarantee function.
6. according to claim 1-5 any one of them methods, which is characterized in that described to be based on the first sensing using the first algorithm
Device information generates first control signal, including：
Operation is carried out to the first sensor information using first algorithm, generates the first control signal；
It is described to be based on second sensor information generation second control signal using the second algorithm, including：
Operation is carried out to the second sensor information using second algorithm, generates the second control signal.
7. according to the method described in claim 6, it is characterized in that, the first sensor information includes in following sensor
The data that one or several kinds of sensors are acquired：
Millimetre-wave radar, the first camera, laser radar, ultrasonic radar, GPS；
It is described that operation is carried out to the first sensor information using first algorithm, the first control signal is generated, is wrapped
It includes：
The first sensor information is merged, path planning and decision is carried out according to fusion results, generates described first
Control signal.
8. according to the method described in claim 6, it is characterized in that, the second sensor information includes：Second camera institute
The image of acquisition；
It is described that operation is carried out to the second sensor information using second algorithm, the second control signal is generated, is wrapped
It includes：
The second camera acquired image is split using intelligent algorithm, determines wheeled region；
Path planning and decision are carried out according to identified wheeled region, generates the second control signal.
9. a kind of intelligent driving control system, which is characterized in that including：
Acquisition module, for obtaining first sensor information and second sensor information；
First control module generates first control signal for being based on first sensor information using the first algorithm；
Second control module generates second control signal for being based on second sensor information using the second algorithm；
Control selections module is used for the state based on the first control signal, selects the first control signal or described
Second control signal controls vehicle.
10. system according to claim 9, which is characterized in that the control selections module, for detecting described
When one control signal normally generates, vehicle is controlled based on the first control signal；Detecting first control
When signal cannot be generated normally, vehicle is controlled based on the second control signal.
11. system according to claim 9, which is characterized in that the algorithm of first algorithm and second algorithm is patrolled
Collect difference.
12. system according to claim 11, which is characterized in that the functional class of first algorithm is higher than described second
The functional class of algorithm.
13. system according to claim 12, which is characterized in that first algorithm has automatic Pilot global function；Institute
Stating the second algorithm only has safety guarantee function.
14. according to claim 9-13 any one of them systems, which is characterized in that first control module is calculated using first
Method is based on first sensor information and generates first control signal, including：
Operation is carried out to the first sensor information using first algorithm, generates the first control signal；
Second control module is based on second sensor information using the second algorithm and generates second control signal, including：
Operation is carried out to the second sensor information using second algorithm, generates the second control signal.
15. system according to claim 14, which is characterized in that the first sensor information includes in following sensor
The data that are acquired of one or several kinds of sensors：
Millimetre-wave radar, the first camera, laser radar, ultrasonic radar, GPS；
First control module carries out operation using first algorithm to the first sensor information, generates described first
Signal is controlled, including：
The first sensor information is merged, path planning and decision is carried out according to fusion results, generates described first
Control signal.
16. system according to claim 14, which is characterized in that the second sensor information includes：Second camera
Acquired image；
Second control module carries out operation using second algorithm to the second sensor information, generates described second
Signal is controlled, including：
The second camera acquired image is split using intelligent algorithm, determines wheeled region；
Path planning and decision are carried out according to identified wheeled region, generates the second control signal.
17. a kind of onboard control device, including：At least one processor, at least one processor and storage are on a memory
And the computer program that can be run on a processor, which is characterized in that the processor realizes such as right when executing described program
It is required that the step of 1-8 any the methods.
18. a kind of intelligent driving vehicle, which is characterized in that including onboard control device as claimed in claim 17.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810476519.5A CN108776472A (en) | 2018-05-17 | 2018-05-17 | Intelligent driving control method and system, onboard control device and intelligent driving vehicle |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810476519.5A CN108776472A (en) | 2018-05-17 | 2018-05-17 | Intelligent driving control method and system, onboard control device and intelligent driving vehicle |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108776472A true CN108776472A (en) | 2018-11-09 |
Family
ID=64027349
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810476519.5A Pending CN108776472A (en) | 2018-05-17 | 2018-05-17 | Intelligent driving control method and system, onboard control device and intelligent driving vehicle |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108776472A (en) |
Cited By (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109343534A (en) * | 2018-11-12 | 2019-02-15 | 天津清智科技有限公司 | A kind of vehicle Unmanned Systems and Standby control method |
| CN109739232A (en) * | 2018-12-29 | 2019-05-10 | 百度在线网络技术（北京）有限公司 | Barrier method for tracing, device, car-mounted terminal and storage medium |
| CN109814552A (en) * | 2018-12-28 | 2019-05-28 | 百度在线网络技术（北京）有限公司 | Vehicular control unit, the Vehicular automatic driving method and device based on FPGA |
| CN109827610A (en) * | 2019-03-12 | 2019-05-31 | 百度在线网络技术（北京）有限公司 | Method and apparatus for check sensor fusion results |
| CN110147109A (en) * | 2019-05-21 | 2019-08-20 | 重庆长安汽车股份有限公司 | A kind of archetype development system of automated driving system |
| CN110399898A (en) * | 2019-06-17 | 2019-11-01 | 中国北方车辆研究所 | A kind of vehicle multi-sensor information fusion architectural framework |
| CN110428692A (en) * | 2019-07-16 | 2019-11-08 | 驭势（上海）汽车科技有限公司 | A kind of intelligent driving emulation mode, system, electronic equipment and storage medium |
| CN110533947A (en) * | 2019-10-14 | 2019-12-03 | 北京百度网讯科技有限公司 | Control system, method, electronic equipment and the computer storage medium of the vehicles |
| CN110568847A (en) * | 2019-08-30 | 2019-12-13 | 驭势科技（北京）有限公司 | Intelligent control system and method for vehicle, vehicle-mounted equipment and storage medium |
| CN110794839A (en) * | 2019-11-07 | 2020-02-14 | 中国第一汽车股份有限公司 | Automatic driving control method for special-shaped intersection and vehicle |
| CN111295319A (en) * | 2018-12-26 | 2020-06-16 | 华为技术有限公司 | Vehicle control method, related device and computer storage medium |
| CN111665849A (en) * | 2020-06-29 | 2020-09-15 | 北京智行者科技有限公司 | Automatic driving system |
| WO2020186625A1 (en) * | 2019-03-19 | 2020-09-24 | 驭势科技（北京）有限公司 | Method for upgrading automatic driving system, automatic driving system and vehicle-mounted device |
| WO2021102958A1 (en) * | 2019-11-29 | 2021-06-03 | 驭势（上海）汽车科技有限公司 | Traffic jam assistant driving method and system, vehicle-mounted device, and storage medium |
| WO2023201563A1 (en) * | 2022-04-20 | 2023-10-26 | 华为技术有限公司 | Control method and apparatus, and means of transportation |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107179767A (en) * | 2016-03-10 | 2017-09-19 | 松下电器（美国）知识产权公司 | Steering control device, driving control method and non-transient recording medium |
| CN107444395A (en) * | 2016-05-19 | 2017-12-08 | 本田技研工业株式会社 | Vehicle control system, control method for vehicle and wagon control program |
| CN107635844A (en) * | 2015-06-11 | 2018-01-26 | 松下知识产权经营株式会社 | Controller of vehicle, control method for vehicle and wagon control program |
| CN107672597A (en) * | 2017-09-25 | 2018-02-09 | 驭势科技（北京）有限公司 | A kind of method and apparatus for being used to control vehicle driving model |
| CN107776574A (en) * | 2017-04-07 | 2018-03-09 | 北京图森未来科技有限公司 | A kind of driving model switching method and apparatus of automatic driving vehicle |
| CN107848538A (en) * | 2015-07-29 | 2018-03-27 | 日本艺美极株式会社 | The automated driving system of vehicle |
| CN107908186A (en) * | 2017-11-07 | 2018-04-13 | 驭势科技（北京）有限公司 | For the method and system for controlling automatic driving vehicle to run |
| CN107966988A (en) * | 2017-12-11 | 2018-04-27 | 中交第二航务工程局有限公司 | The control system of shield machine construction electric locomotive |
-
2018
- 2018-05-17 CN CN201810476519.5A patent/CN108776472A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107635844A (en) * | 2015-06-11 | 2018-01-26 | 松下知识产权经营株式会社 | Controller of vehicle, control method for vehicle and wagon control program |
| CN107848538A (en) * | 2015-07-29 | 2018-03-27 | 日本艺美极株式会社 | The automated driving system of vehicle |
| CN107179767A (en) * | 2016-03-10 | 2017-09-19 | 松下电器（美国）知识产权公司 | Steering control device, driving control method and non-transient recording medium |
| CN107444395A (en) * | 2016-05-19 | 2017-12-08 | 本田技研工业株式会社 | Vehicle control system, control method for vehicle and wagon control program |
| CN107776574A (en) * | 2017-04-07 | 2018-03-09 | 北京图森未来科技有限公司 | A kind of driving model switching method and apparatus of automatic driving vehicle |
| CN107672597A (en) * | 2017-09-25 | 2018-02-09 | 驭势科技（北京）有限公司 | A kind of method and apparatus for being used to control vehicle driving model |
| CN107908186A (en) * | 2017-11-07 | 2018-04-13 | 驭势科技（北京）有限公司 | For the method and system for controlling automatic driving vehicle to run |
| CN107966988A (en) * | 2017-12-11 | 2018-04-27 | 中交第二航务工程局有限公司 | The control system of shield machine construction electric locomotive |
Cited By (24)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109343534A (en) * | 2018-11-12 | 2019-02-15 | 天津清智科技有限公司 | A kind of vehicle Unmanned Systems and Standby control method |
| CN111295319A (en) * | 2018-12-26 | 2020-06-16 | 华为技术有限公司 | Vehicle control method, related device and computer storage medium |
| US10994749B2 (en) | 2018-12-26 | 2021-05-04 | Huawei Technologies Co., Ltd. | Vehicle control method, related device, and computer storage medium |
| WO2020133005A1 (en) * | 2018-12-26 | 2020-07-02 | 华为技术有限公司 | Vehicle control method, related device, and computer storage medium |
| EP3754449A4 (en) * | 2018-12-26 | 2021-09-29 | Huawei Technologies Co., Ltd. | Vehicle control method, related device, and computer storage medium |
| CN109814552A (en) * | 2018-12-28 | 2019-05-28 | 百度在线网络技术（北京）有限公司 | Vehicular control unit, the Vehicular automatic driving method and device based on FPGA |
| CN109739232A (en) * | 2018-12-29 | 2019-05-10 | 百度在线网络技术（北京）有限公司 | Barrier method for tracing, device, car-mounted terminal and storage medium |
| CN109739232B (en) * | 2018-12-29 | 2022-06-07 | 百度在线网络技术（北京）有限公司 | Obstacle tracking method, obstacle tracking device, vehicle-mounted terminal and storage medium |
| CN109827610A (en) * | 2019-03-12 | 2019-05-31 | 百度在线网络技术（北京）有限公司 | Method and apparatus for check sensor fusion results |
| CN109827610B (en) * | 2019-03-12 | 2021-05-14 | 百度在线网络技术（北京）有限公司 | Method and device for verifying sensor fusion result |
| US11685397B2 (en) | 2019-03-19 | 2023-06-27 | Uisee Technologies (beijing) Co., Ltd. | Methods for updating autonomous driving system, autonomous driving systems, and on-board apparatuses |
| WO2020186625A1 (en) * | 2019-03-19 | 2020-09-24 | 驭势科技（北京）有限公司 | Method for upgrading automatic driving system, automatic driving system and vehicle-mounted device |
| CN110147109A (en) * | 2019-05-21 | 2019-08-20 | 重庆长安汽车股份有限公司 | A kind of archetype development system of automated driving system |
| CN110399898A (en) * | 2019-06-17 | 2019-11-01 | 中国北方车辆研究所 | A kind of vehicle multi-sensor information fusion architectural framework |
| CN110428692A (en) * | 2019-07-16 | 2019-11-08 | 驭势（上海）汽车科技有限公司 | A kind of intelligent driving emulation mode, system, electronic equipment and storage medium |
| CN110568847A (en) * | 2019-08-30 | 2019-12-13 | 驭势科技（北京）有限公司 | Intelligent control system and method for vehicle, vehicle-mounted equipment and storage medium |
| CN110568847B (en) * | 2019-08-30 | 2022-09-23 | 驭势科技（北京）有限公司 | Intelligent control system and method for vehicle, vehicle-mounted equipment and storage medium |
| CN110533947A (en) * | 2019-10-14 | 2019-12-03 | 北京百度网讯科技有限公司 | Control system, method, electronic equipment and the computer storage medium of the vehicles |
| CN110794839B (en) * | 2019-11-07 | 2022-04-29 | 中国第一汽车股份有限公司 | Automatic driving control method for special-shaped intersection and vehicle |
| CN110794839A (en) * | 2019-11-07 | 2020-02-14 | 中国第一汽车股份有限公司 | Automatic driving control method for special-shaped intersection and vehicle |
| WO2021102958A1 (en) * | 2019-11-29 | 2021-06-03 | 驭势（上海）汽车科技有限公司 | Traffic jam assistant driving method and system, vehicle-mounted device, and storage medium |
| CN111665849A (en) * | 2020-06-29 | 2020-09-15 | 北京智行者科技有限公司 | Automatic driving system |
| CN111665849B (en) * | 2020-06-29 | 2023-08-01 | 北京智行者科技股份有限公司 | Automatic driving system |
| WO2023201563A1 (en) * | 2022-04-20 | 2023-10-26 | 华为技术有限公司 | Control method and apparatus, and means of transportation |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108776472A (en) | Intelligent driving control method and system, onboard control device and intelligent driving vehicle | |
| US11644831B2 (en) | Multi-stage operation of autonomous vehicles | |
| JP7171708B2 (en) | Fault-tolerant control of autonomous vehicles with multiple control lanes | |
| CN107908186A (en) | For the method and system for controlling automatic driving vehicle to run | |
| CN106840242A (en) | The sensor self-checking system and multi-sensor fusion system of a kind of intelligent driving automobile | |
| JP2020050302A (en) | In-vehicle electronic control system | |
| US20180052453A1 (en) | Fault-tolerant method and device for controlling an autonomous technical system through diversified trajectory planning | |
| CN109606385A (en) | A kind of control method for vehicle based on automatic Pilot, device, equipment and medium | |
| EP3574287B1 (en) | A method for forming a local navigation path for an autonomous vehicle | |
| JP2016525038A (en) | Method and apparatus for operating a vehicle in automatic driving mode | |
| CN113412506A (en) | Vehicle control device and electronic control system | |
| CN110271559A (en) | Improvement control system and improvement control method for autonomous control motor vehicles | |
| CN109298713B (en) | Instruction sending method, device and system and automatic driving vehicle | |
| US20180052465A1 (en) | Fault-tolerant method and device for controlling an autonomous technical system based on a consolidated model of the environment | |
| CN113525422B (en) | Automatic driving system and method | |
| KR102396538B1 (en) | Safety control system and method of self-driving vehicles | |
| CN113173178B (en) | Automatic driving control method and system for vehicle | |
| CN113895450A (en) | Safety redundancy system and control method for unmanned vehicle sensing system | |
| CN109844839A (en) | The system and method for status analysis for the manipulation of autonomous lane changing | |
| CN113682323A (en) | Binocular vision-based safety redundancy architecture and method for low-speed unmanned vehicle | |
| CN112537311A (en) | Method for safely and reliably guiding a motor vehicle at least partially automatically | |
| JP7351321B2 (en) | Sensor abnormality estimation device | |
| CN115723783A (en) | Safety controller for automatic driving | |
| EP3293543B1 (en) | Apparatus for sensing a vehicular environment when fitted to a vehicle | |
| CN110341723B (en) | Vehicle control method, device and system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20181109 |
|
| RJ01 | Rejection of invention patent application after publication |