CN108594819A - Automatic Pilot vehicle computing resource management system and method - Google Patents
Automatic Pilot vehicle computing resource management system and method Download PDFInfo
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- CN108594819A CN108594819A CN201810414692.2A CN201810414692A CN108594819A CN 108594819 A CN108594819 A CN 108594819A CN 201810414692 A CN201810414692 A CN 201810414692A CN 108594819 A CN108594819 A CN 108594819A
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- 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
- G05D1/0234—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using optical markers or beacons
- G05D1/0236—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using optical markers or beacons in combination with a laser
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Abstract
Automatic Pilot vehicle computing method for managing resource of the present invention, it is related to automatic Pilot technical field, the hardware resource of vehicle computing unit is managed collectively using container technique, task and automatic Pilot intelligent decision control task are handled according to the real-time data collection of core sensor, dynamically distribute physical hardware resources, mutually isolated multiple containers running environment is generated, respective task is independently executed；According to actual operating state dynamic adjustresources, the intelligent coordinated of each automatic Pilot service application is realized；And a variety of Container Management strategies are grabbed by resource reservation, resource constraint, resource, complete the safety traffic of automatic driving vehicle.The present invention improves the utilization rate of computing resource while ensureing the isolation of calculating task performing environment, effectively reduces hardware energy consumption；Compared to single host mode, the risk that single machine failure is brought is reduced, promotes automatic Pilot overall security.The invention also provides automatic Pilot vehicle computing resource management systems.
Description
Technical field
The present invention relates to edge calculations, automatic Pilot and container technical field, specifically a kind of automatic Pilot is vehicle-mounted
Managing computing resources system and method.
Background technology
With the development of cloud computing, types of applications system turns to high in the clouds gradually, a large amount of object of high in the clouds site polymerization
Manage hardware resource, such as server, network, memory and storage, extracted using virtualization technology, convert after be in uniformly
Reveal and, realize the unified distribution, scheduling and management of heterogeneous network computing resource, construction data center is concentrated to greatly reduce
The cost for calculating and storing.Virtualization technology is as a kind of resource management techniques, effective solution high-performance physical hardware money
Source excess capacity is super to reuse problem with the too low recombination brought of problem and old hardware resource utilization, by bottom hardware physics
Transparent resource, to maximumlly utilize hardware resource.
In recent years, micro services framework comes into vogue, and the virtualization technology headed by heavy hypervisor relatively is very much
Under scene, substituted gradually by container technique.Container technique can build operation system example on demand, and be carried in a manner of process
Application is supplied to use, reduces basic overhead in this way, container technique realizes independence and the isolation of resource, provides
Lightweight, environment consistency running environment, have become a kind of physical hardware resources sharing mode being widely recognized as by everybody,
Great flexibility is provided for application developer and system operation maintenance personnel.
Automatic Pilot is automobile industry and artificial intelligence, vision calculating, Internet of Things, radar, high-precision map, high-performance calculation
Etc. generation information technologies depth integration product, the Main way for being Present Global automobile with the development of traffic trip field,
By vehicle-mounted core calculations unit, under the operation of nobody class active, automatic safe motor vehicles are operated.Compared to
Orthodox car, autonomous driving vehicle increase the core sensors such as high-definition camera, laser radar, high-precision positioner, and
By sensor real-time data collection, coordinate high-precision map, the inductive decision of real-time high-efficiency is carried out using vehicle computing unit, and
It feeds back to vehicle line control system and realizes automatic Pilot.In this course, vehicle-mounted core calculations unit needs to provide a large amount of calculate
Resource, meets the data structured demand of all kinds of sensing equipments, while to complete model reasoning and the control decision of vehicle.With this
Meanwhile being limited to the requirement of the volume and energy consumption of automobile so that vehicle-mounted core calculations unit can not use the solution party at cloud center
Case.In this case, how efficient computing resource effectively is provided for automatic driving vehicle using container technique, according to row
Parking lot scape reasonable distribution resource is realized to calculate and be optimized, and can guarantee the problem of driving safety becomes urgent need to resolve.
Invention content
The present invention is directed to the demand and shortcoming of current technology development, provides a kind of automatic Pilot vehicle computing resource pipe
Manage system and method.
Automatic Pilot vehicle computing resource management system of the present invention solves the technical solution that above-mentioned technical problem uses
It is as follows：Described to be based on automatic Pilot vehicle computing resource management system, system architecture includes core sensor, vehicle computing list
Member and vehicle string holes system；The hardware resource of vehicle computing unit is managed collectively using container technique, is passed according to core
The real-time data collection processing task and automatic Pilot intelligent decision control task of sensor, dynamically distribute physical hardware resources, raw
At mutually isolated multiple containers running environment, respective task is independently executed；It is real according to actual operating state dynamic adjustresources
Now each automatic Pilot service application is intelligent coordinated；And a variety of Container Managements are grabbed by resource reservation, resource constraint, resource
Strategy completes the safety traffic of automatic driving vehicle；Wherein,
The core sensor includes the sensing equipment realized Function for Automatic Pilot and used, and passes through the real-time collecting vehicle of core sensor
Running environment data；
The vehicle computing unit general frame is divided into four layers：Physical computing resources layer, ROS real time operating systems layer, business fortune
Row environmental chamber layer and application layer；Wherein, the physical computing resources layer, including multiple main frames, these hosts are to realize automatically
Drive the central module of function；
The ROS real time operating systems layer, is deployed on physical computing resources layer, for ensureing data acquisition and Decision Control
Real-time；The service operation environmental chamber layer is deployed on ROS real time operating system layers, is run for deployment container
Environment；The application layer, for running container management service and automatic Pilot service application；
The container management service will dynamically distribute and manage resource according to business demand, complete to sense using vehicle computing unit
The acquiring of data, the fusion and collaboration of a variety of sensing equipment data, and according to automatic Pilot Decision Control Model trained in advance
Real-time inductive decision is completed, vehicle line control system is fed back to by CAN bus, completes vehicle control response.
Specifically, the core sensor includes：Multi-path high-definition camera, laser radar, millimetre-wave radar, V2X sensings
Equipment, high-precision positioner；
Each host includes calculating, storage and network physical hardware resource and FPGA or GPU hardware acceleration components.
Specifically, the application layer specifically includes Container Management application, the application of high-precision map, Decision Control, emergency braking
Using the control of, CAN bus, data acquisition applications.
Specifically, the automatic Pilot vehicle computing resource management system carries out automatic Pilot computing resource initialization, it is interior
Appearance includes：
The vehicle computing unit loads preset Container Management configuration information, is based on ROS real time operating systems, completes container tube
The initialization of service is managed, wherein reserved part computing resource is used for emergency braking Mission critical applications；
The vehicle computing unit connects core sensor by container management service, matches confidence according to preset resource allocation
Breath loads application service container mirror image, starts container application service；The core sensor data acquisition applications service operation exists
In container, core sensor is connected, and acquire the environmental data from core sensor, carry out structuring processing；
The vehicle computing unit loads CAN bus vehicle condition data by container management service and acquires service container mirror image,
And start container application service；The CAN bus vehicle condition data acquires service operation in a reservoir, real-time collection vehicle shape
Condition data carry out structuring processing；
The vehicle computing unit loads high-precision map application service container mirror image by container management service, and starts container and answer
With service；The high-precision map application service operation in a reservoir, provides high-precision Map Services, is obtained in conjunction with high accurate positioning device
Surrounding enviroment data and road data；
The vehicle computing unit loads CAN bus vehicle control service container mirror image by container management service, and starts appearance
Device application service；The CAN bus vehicle control service operation in a reservoir, waits for control instruction；
The vehicle computing unit loads automatic Pilot Decision Control service container mirror image by container management service, and starts appearance
Device inductive decision controls application service；Automatic Pilot inductive decision control application service operation in a reservoir, and with it is each
Acquisition applications service interacts, and realizes in data set, and completes decision calculating task according to its automatic Pilot decision model, real
When feed back to the CAN bus vehicle control service；
The vehicle computing unit will load emergency braking service container mirror image by container management service at least two hosts,
And start application service；The emergency braking service operation in a reservoir, and keeps heartbeat with other application service container, in real time
Its resource and operation conditions are monitored, waits for and instructing while listening for port.
Specifically, the automatic Pilot vehicle computing resource management system carries out automatic Pilot managing computing resources, content
Including：
The vehicle computing unit is marked FPGA, GPU by container management service, for deep learning reasoning scene,
It is serviced using given host load vessel；
The vehicle computing unit monitors the container and hardware resource situation of autonomous driving vehicle by container management service；If holding
The allocated computing resource of device has reached critical value, inadequate resource phenomenon occurs, then preferential to be distributed using reserved to crucial calculate
Resource；When container resource utilization reaches saturation situation, if crucial application resource is insufficient, the money of non-key service application is grabbed
Source；If there is non-critical application container operation exception, turn off container Resource recovery, redistributes resource, load vessel mirror image
And start application；If there is crucial application container operation exception, priority scheduling executes emergency brake application service, completes automatic
The safe reduction of speed parking driven redistributes resource, load vessel mirror image simultaneously starts application, opens again after vehicle safety stops
Open Function for Automatic Pilot；
If hardware anomalies occurs in some host, priority scheduling executes emergency brake application service, completes the safety of automatic Pilot
Reduction of speed stops, and after vehicle safety stops, judging remaining available host quantity, is no less than two available hosts if existing, will break
The container mirror image of electric host operation is loaded into other hosts, reopens Function for Automatic Pilot；
The vehicle computing unit by container management service collect different vehicle driving scene computing resource data, and according to
Current driving situation individual scene dynamic optimization adjustresources.
The present invention also proposes automatic Pilot vehicle computing method for managing resource, using container technique by vehicle computing unit
Hardware resource is managed collectively, and task and automatic Pilot intelligent decision control are handled according to the real-time data collection of core sensor
Task processed dynamically distributes physical hardware resources, generates mutually isolated multiple containers running environment, independently execute respective task；
According to actual operating state dynamic adjustresources, the intelligent coordinated of each automatic Pilot service application is realized；And it is pre- by resource
It stays, a variety of Container Management strategies of resource constraint, resource plunder, completes the safety traffic of automatic driving vehicle；
The vehicle computing unit is made of multiple main frames, is the central module for realizing Function for Automatic Pilot, in vehicle computing list
On member, ROS real time operating systems are disposed to ensure the real-time of data acquisition and Decision Control, on ROS operating systems
Deployment container running environment, wherein operation container management service and automatic Pilot service application；The core sensor includes real
The sensing equipment that existing Function for Automatic Pilot is used；
The container management service will dynamically distribute and manage resource according to business demand, complete using the vehicle computing unit
At the acquiring of sensing data, the fusion and collaboration of a variety of sensing equipment data, and according to automatic Pilot decision control trained in advance
Simulation completes real-time inductive decision, feeds back to vehicle line control system by CAN bus, completes vehicle control response.
Specifically, the core sensor includes：Multi-path high-definition camera, laser radar, millimetre-wave radar, V2X sensings
Equipment, high-precision positioner；
Each host includes calculating, storage and network physical hardware resource and FPGA or GPU hardware acceleration components.
Specifically, the application layer specifically includes Container Management application, the application of high-precision map, Decision Control, emergency braking
Using the control of, CAN bus, data acquisition applications.
Automatic Pilot vehicle computing resource management system of the present invention and method, what is had compared with prior art is beneficial
Effect is：The present invention reasonably allocates management of automatic Pilot vehicle computing resource using container technique, and automatic Pilot is calculated root
According to scene, classification, many factors dynamic allocation of resources such as result influence degree are calculated, calculating task respectively in multiple containers
Independent operating, and can realize resource elastic telescopic according to scene changes；
While ensureing the isolation of calculating task performing environment, the utilization rate of computing resource is improved, and effectively reduce
Hardware energy consumption；Compare the mode of single host, and the mode of more host containers reduces the risk that single machine failure is brought, improves
Automatic Pilot overall security；The hypervisor that compares virtualizes mode, and containerization mode will occupy less computing resource,
The operational efficiency of significant increase automatic Pilot application, the container mode of more lightweight meet automatic Pilot ROS real-time operations
The container application of requirement of the system to real-time, micro services reduces failure recovery time, and it is whole to improve automated driving system
The robustness of body；In addition, more copies operation of crucial calculating task and specified, resource reservation, resource constraint, money by resource
A variety of Container Management strategies such as source plunder while efficiently utilizing resource, ensure that the high availability of crucial calculating, maximum journey
The driving safety for having ensured automatic driving vehicle of degree.
Description of the drawings
Illustrate the embodiment of the present invention or technology contents in the prior art in order to clearer, below to the embodiment of the present invention
Or required attached drawing does simple introduction in the prior art.It will be apparent that attached drawing disclosed below is only the one of the present invention
Section Example to those skilled in the art without creative efforts, can also be attached according to these
Figure obtains other attached drawings, but within protection scope of the present invention.
Attached drawing 1 is the schematic diagram of the automatic Pilot vehicle computing unit；
Attached drawing 2 is the flow chart of automatic Pilot computing resource initialization；
Attached drawing 3 is the flow chart of automatic Pilot managing computing resources.
Specific implementation mode
The technical issues of to make technical scheme of the present invention, solving and technique effect are more clearly understood, below in conjunction with tool
Body embodiment is checked technical scheme of the present invention, is completely described, it is clear that described embodiment is only this hair
Bright a part of the embodiment, instead of all the embodiments.Based on the embodiment of the present invention, those skilled in the art are not doing
All embodiments obtained under the premise of going out creative work, all within protection scope of the present invention.
Embodiment
The present embodiment proposes automatic Pilot vehicle computing resource management system, installs and uses in automatic driving vehicle, institute
It is the automobile for having Function for Automatic Pilot to state automatic driving vehicle；The framework packet of the automatic Pilot vehicle computing resource management system
It includes core sensor, vehicle computing unit and vehicle string holes system, core sensor to connect with vehicle computing unit, will collect
Vehicle running environment data transmission to vehicle computing unit, the inductive decision of real-time high-efficiency is carried out using vehicle computing unit,
Vehicle computing unit is connected to vehicle line control system, and obtained inductive decision result is fed back to vehicle line control system, realizes vehicle
Automatic Pilot；Wherein,
Core sensor includes the sensing equipment realized Function for Automatic Pilot and used, and further core sensor may include：It is more
Road high-definition camera, laser radar, millimetre-wave radar, V2X sensing equipments, high-precision positioner；Pass through core sensor reality
When collection vehicle running environment data；
As shown in Fig. 1, vehicle computing unit general frame is divided into four layers：Physical computing resources layer, ROS real time operating systems
Layer, service operation environmental chamber layer and application layer；Wherein, physical computing resources layer, including multiple main frames, these hosts are to realize
The central module of Function for Automatic Pilot；Further, each host includes the physical hardware resources such as calculating, storage and network, in addition,
Each host further includes the hardware-accelerated component such as FPGA or GPU；
ROS real time operating system layers, are deployed on physical computing resources layer, the reality for ensureing data acquisition and Decision Control
Shi Xing；Service operation environmental chamber layer is deployed on ROS real time operating system layers, is used for deployment container running environment；Using
Layer, for running container management service and automatic Pilot service application, further, application layer specifically include Container Management application,
High-precision map, Decision Control application, emergency brake application, CAN bus control, data acquisition applications etc.；
Container management service will dynamically distribute and manage resource according to business demand, and sensing data is completed using vehicle computing unit
Acquire, the fusion and collaboration of a variety of sensing equipment data, and completed according to automatic Pilot Decision Control Model trained in advance
Real-time inductive decision feeds back to vehicle line control system by CAN bus, completes vehicle control response.
The present embodiment proposes automatic Pilot vehicle computing resource management system, using container technique by vehicle computing unit
Hardware resource is managed collectively, and task and automatic Pilot intelligent decision control are handled according to the real-time data collection of core sensor
The tasks such as system dynamically distribute（Calculating, storage, network etc.）Physical hardware resources generate mutually isolated multiple containers operation ring
Border independently executes respective task；According to actual operating state dynamic adjustresources, automatic Pilot vehicle computing unit business is reduced
Interacting for operation, realizes the intelligent coordinated of each automatic Pilot service application.In addition, by resource reservation, resource constraint,
A variety of Container Management strategies such as resource plunder ensure the high availability that core key calculates, complete the safety of automatic driving vehicle
Traveling.
The present embodiment also proposed automatic Pilot vehicle computing method for managing resource, technical solution and above-mentioned automatic Pilot
Vehicle computing resource management system can be referred to mutually, it is necessary first to automatic Pilot computing resource initialization be carried out, such as attached drawing 2
Shown, the main realization process of this operation includes：
Step 1, autonomous driving vehicle start power supply system, power for vehicle computing unit, complete host supplying power and start；
Step 2, vehicle computing unit load ROS real time operating systems；
Step 3, vehicle computing unit load preset Container Management configuration information, are based on ROS real time operating systems, complete container
The initialization of management service, wherein by reserved part computing resource for Mission critical applications such as emergency brakings；
Step 4, vehicle computing unit connect core sensor by container management service, match confidence according to preset resource allocation
Breath loads application service container mirror image, and starts container application service respectively；
Step 5, core sensor data acquisition applications service operation in a reservoir, connect core sensor, and acquire and come from core
The environmental data of heart sensor carries out structuring processing；
Step 6, vehicle computing unit load CAN bus vehicle condition data by container management service and acquire service container mirror
Picture, and start container application service；
In a reservoir, real-time collection vehicle status data is tied for step 7, CAN bus vehicle condition data acquisition service operation
Structureization processing；
Step 8, vehicle computing unit load high-precision map application service container mirror image by container management service, and start container
Application service；
Step 9, high-precision map application service operation in a reservoir, provide high-precision Map Services, are obtained in conjunction with high accurate positioning device
Surrounding enviroment data and road data；
Step 10, vehicle computing unit load CAN bus vehicle control service container mirror image by container management service, and start
Container application service；
Step 11, CAN bus vehicle control service operation in a reservoir, wait for control instruction；
Step 12, vehicle computing unit load automatic Pilot Decision Control service container mirror image by container management service, and open
Visibly moved device inductive decision controls application service；
Step 13, automatic Pilot inductive decision control application service operation in a reservoir, and are serviced with each acquisition applications and are carried out
Interaction is realized in data set, and completes decision calculating task according to its automatic Pilot decision model, and Real-time Feedback is to described
CAN bus vehicle control service；
Step 14, vehicle computing unit will load emergency braking service container mirror by container management service at least two hosts
Picture, and start application service；
Step 15, emergency braking service operation in a reservoir, and keep heartbeat with other application service container, monitor its money in real time
Source and operation conditions are waited for while listening for port and being instructed；
Step 16, autonomous driving vehicle computing unit operating status are normal, and computing resource initialization is completed.
Using the present embodiment automatic Pilot vehicle computing method for managing resource, the initialization of automatic Pilot computing resource is completed
Afterwards, automatic Pilot managing computing resources are carried out, as shown in Fig. 3, this operating process specifically includes：
Step 1, vehicle computing unit are marked the specialized hardwares such as FPGA, GPU by container management service, are related to depth
The scenes such as reasoning are practised, then are serviced using given host load vessel；
Step 2, vehicle computing unit monitor the container and hardware resource situation of autonomous driving vehicle by container management service；
If the allocated computing resource of step 3, container has reached critical value, there is inadequate resource phenomenon, then it is preferential to key
It calculates distribution and uses reserved resource；
Step 4 reaches saturation situation when container resource utilization, if crucial application resource is insufficient, grabs non-key business
The resource of application ensures the operation of Core Feature；
Step 5, if there is non-critical application container operation exception, such as V2X sensing equipment data acquisition applications, some is backward
High-definition camera data acquisition applications etc., then turn off container Resource recovery, redistributes resource, and load vessel mirror image and starting is answered
With；
Step 6 is determined if there is crucial application container operation exception, such as preposition high-definition camera data acquisition service, reasoning
The safe reduction of speed parking of automatic Pilot is completed in plan service etc., then priority scheduling execution emergency brake application service, and vehicle safety stops
After only, resource is redistributed, load vessel mirror image simultaneously starts application, reopens Function for Automatic Pilot；
If hardware anomalies occur in step 7, some host, priority scheduling executes emergency brake application service, and completion is driven automatically
The safe reduction of speed parking sailed judges remaining available host quantity after vehicle safety stops, if there is no less than two available masters
The container mirror image for powering off host operation is then loaded into other hosts, reopens Function for Automatic Pilot by machine；
Step 8, vehicle computing unit collect the computing resource data of different vehicle driving scene, and root by container management service
According to current driving situation individual scene dynamic optimization adjustresources.
Use above specific case elaborates the principle of the present invention and embodiment, these embodiments are
It is used to help understand core of the invention technology contents, the protection domain being not intended to restrict the invention, technical side of the invention
Case is not limited in above-mentioned specific implementation mode.Based on the above-mentioned specific embodiment of the present invention, those skilled in the art
Without departing from the principle of the present invention, any improvement and modification to made by the present invention should all fall into the special of the present invention
Sharp protection domain.
Claims (10)
1. automatic Pilot vehicle computing resource management system, which is characterized in that its system architecture includes core sensor, vehicle-mounted
Computing unit and vehicle string holes system；The hardware resource of vehicle computing unit is managed collectively using container technique, according to
The real-time data collection processing task and automatic Pilot intelligent decision control task of core sensor, dynamically distribute physical hardware money
Source generates mutually isolated multiple containers running environment, independently executes respective task；According to actual operating state dynamic adjustment money
The intelligent coordinated of each automatic Pilot service application is realized in source；And a variety of appearances are grabbed by resource reservation, resource constraint, resource
Device management strategy completes the safety traffic of automatic driving vehicle；Wherein,
The core sensor includes the sensing equipment realized Function for Automatic Pilot and used, and passes through the real-time collecting vehicle of core sensor
Running environment data；
The vehicle computing unit general frame is divided into four layers：Physical computing resources layer, ROS real time operating systems layer, business fortune
Row environmental chamber layer and application layer；Wherein, the physical computing resources layer, including multiple main frames, these hosts are to realize automatically
Drive the central module of function；
The ROS real time operating systems layer, is deployed on physical computing resources layer, for ensureing data acquisition and Decision Control
Real-time；The service operation environmental chamber layer is deployed on ROS real time operating system layers, is run for deployment container
Environment；The application layer, for running container management service and automatic Pilot service application；
The container management service will dynamically distribute and manage resource according to business demand, complete to sense using vehicle computing unit
The acquiring of data, the fusion and collaboration of a variety of sensing equipment data, and according to automatic Pilot Decision Control Model trained in advance
Real-time inductive decision is completed, vehicle line control system is fed back to by CAN bus, completes vehicle control response.
2. automatic Pilot vehicle computing resource management system according to claim 1, which is characterized in that the core sensor
Including：Multi-path high-definition camera, laser radar, millimetre-wave radar, V2X sensing equipments, high-precision positioner；
Each host includes calculating, storage and network physical hardware resource and FPGA or GPU hardware acceleration components.
3. automatic Pilot vehicle computing resource management system according to claim 2, which is characterized in that the application layer is specific
Including Container Management application, high-precision map, Decision Control application, emergency brake application, CAN bus control, data acquisition applications.
4. automatic Pilot vehicle computing resource management system according to claim 3, which is characterized in that the automatic Pilot vehicle
It carries managing computing resources system and carries out automatic Pilot computing resource initialization, content includes：
The vehicle computing unit loads preset Container Management configuration information, is based on ROS real time operating systems, completes container tube
The initialization of service is managed, wherein reserved part computing resource is used for emergency braking Mission critical applications；
The vehicle computing unit connects core sensor by container management service, matches confidence according to preset resource allocation
Breath loads application service container mirror image, starts container application service；The core sensor data acquisition applications service operation exists
In container, core sensor is connected, and acquire the environmental data from core sensor, carry out structuring processing；
The vehicle computing unit loads CAN bus vehicle condition data by container management service and acquires service container mirror image,
And start container application service；The CAN bus vehicle condition data acquires service operation in a reservoir, real-time collection vehicle shape
Condition data carry out structuring processing；
The vehicle computing unit loads high-precision map application service container mirror image by container management service, and starts container and answer
With service；The high-precision map application service operation in a reservoir, provides high-precision Map Services, is obtained in conjunction with high accurate positioning device
Surrounding enviroment data and road data；
The vehicle computing unit loads CAN bus vehicle control service container mirror image by container management service, and starts appearance
Device application service；The CAN bus vehicle control service operation in a reservoir, waits for control instruction；
The vehicle computing unit loads automatic Pilot Decision Control service container mirror image by container management service, and starts appearance
Device inductive decision controls application service；Automatic Pilot inductive decision control application service operation in a reservoir, and with it is each
Acquisition applications service interacts, and realizes in data set, and completes decision calculating task according to its automatic Pilot decision model, real
When feed back to the CAN bus vehicle control service；
The vehicle computing unit will load emergency braking service container mirror image by container management service at least two hosts,
And start application service；The emergency braking service operation in a reservoir, and keeps heartbeat with other application service container, in real time
Its resource and operation conditions are monitored, waits for and instructing while listening for port.
5. automatic Pilot vehicle computing resource management system according to claim 4, which is characterized in that the automatic Pilot vehicle
It carries managing computing resources system and carries out automatic Pilot managing computing resources, content includes：
The vehicle computing unit is marked FPGA, GPU by container management service, for deep learning reasoning scene,
It is serviced using given host load vessel；
The vehicle computing unit monitors the container and hardware resource situation of autonomous driving vehicle by container management service；If holding
The allocated computing resource of device has reached critical value, inadequate resource phenomenon occurs, then preferential to be distributed using reserved to crucial calculate
Resource；When container resource utilization reaches saturation situation, if crucial application resource is insufficient, the money of non-key service application is grabbed
Source；If there is non-critical application container operation exception, turn off container Resource recovery, redistributes resource, load vessel mirror image
And start application；If there is crucial application container operation exception, priority scheduling executes emergency brake application service, completes automatic
The safe reduction of speed parking driven redistributes resource, load vessel mirror image simultaneously starts application, opens again after vehicle safety stops
Open Function for Automatic Pilot；
If hardware anomalies occurs in some host, priority scheduling executes emergency brake application service, completes the safety of automatic Pilot
Reduction of speed stops, and after vehicle safety stops, judging remaining available host quantity, is no less than two available hosts if existing, will break
The container mirror image of electric host operation is loaded into other hosts, reopens Function for Automatic Pilot；
The vehicle computing unit by container management service collect different vehicle driving scene computing resource data, and according to
Current driving situation individual scene dynamic optimization adjustresources.
6. automatic Pilot vehicle computing method for managing resource, which is characterized in that utilize container technique by the hard of vehicle computing unit
Part resource is managed collectively, and handles task according to the real-time data collection of core sensor and automatic Pilot intelligent decision controls
Task dynamically distributes physical hardware resources, generates mutually isolated multiple containers running environment, independently execute respective task；Root
According to actual operating state dynamic adjustresources, the intelligent coordinated of each automatic Pilot service application is realized；And by resource reservation,
Resource constraint, resource grab a variety of Container Management strategies, complete the safety traffic of automatic driving vehicle；
The vehicle computing unit is made of multiple main frames, is the central module for realizing Function for Automatic Pilot, in vehicle computing list
On member, ROS real time operating systems are disposed to ensure the real-time of data acquisition and Decision Control, on ROS operating systems
Deployment container running environment, wherein operation container management service and automatic Pilot service application；The core sensor includes real
The sensing equipment that existing Function for Automatic Pilot is used；
The container management service will dynamically distribute and manage resource according to business demand, complete using the vehicle computing unit
At the acquiring of sensing data, the fusion and collaboration of a variety of sensing equipment data, and according to automatic Pilot decision control trained in advance
Simulation completes real-time inductive decision, feeds back to vehicle line control system by CAN bus, completes vehicle control response.
7. automatic Pilot vehicle computing method for managing resource according to claim 6, which is characterized in that the core sensor
Including：Multi-path high-definition camera, laser radar, millimetre-wave radar, V2X sensing equipments, high-precision positioner；
Each host includes calculating, storage and network physical hardware resource and FPGA or GPU hardware acceleration components.
8. automatic Pilot vehicle computing method for managing resource according to claim 7, which is characterized in that the application layer is specific
Including Container Management application, high-precision map, Decision Control application, emergency brake application, CAN bus control, data acquisition applications.
9. automatic Pilot vehicle computing method for managing resource according to claim 8, which is characterized in that carry out automatic Pilot meter
Initializing resource is calculated, this operating process includes：
Step 1, autonomous driving vehicle start power supply system, power for vehicle computing unit, complete host supplying power and start；
Step 2, vehicle computing unit load ROS real time operating systems；
Step 3, vehicle computing unit load preset Container Management configuration information, are based on ROS real time operating systems, complete container
The initialization of management service, wherein by reserved part computing resource for Mission critical applications such as emergency brakings；
Step 4, vehicle computing unit connect core sensor by container management service, match confidence according to preset resource allocation
Breath loads application service container mirror image, and starts container application service respectively；
Step 5, core sensor data acquisition applications service operation in a reservoir, connect core sensor, and acquire and come from core
The environmental data of heart sensor carries out structuring processing；
Step 6, vehicle computing unit load CAN bus vehicle condition data by container management service and acquire service container mirror
Picture, and start container application service；
In a reservoir, real-time collection vehicle status data is tied for step 7, CAN bus vehicle condition data acquisition service operation
Structureization processing；
Step 8, vehicle computing unit load high-precision map application service container mirror image by container management service, and start container
Application service；
Step 9, high-precision map application service operation in a reservoir, provide high-precision Map Services, are obtained in conjunction with high accurate positioning device
Surrounding enviroment data and road data；
Step 10, vehicle computing unit load CAN bus vehicle control service container mirror image by container management service, and start
Container application service；
Step 11, CAN bus vehicle control service operation in a reservoir, wait for control instruction；
Step 12, vehicle computing unit load automatic Pilot Decision Control service container mirror image by container management service, and open
Visibly moved device inductive decision controls application service；
Step 13, automatic Pilot inductive decision control application service operation in a reservoir, and are serviced with each acquisition applications and are carried out
Interaction is realized in data set, and completes decision calculating task according to its automatic Pilot decision model, and Real-time Feedback is to described
CAN bus vehicle control service；
Step 14, vehicle computing unit will load emergency braking service container mirror by container management service at least two hosts
Picture, and start application service；
Step 15, emergency braking service operation in a reservoir, and keep heartbeat with other application service container, monitor its money in real time
Source and operation conditions are waited for while listening for port and being instructed；
Step 16, autonomous driving vehicle computing unit operating status are normal, and computing resource initialization is completed.
10. automatic Pilot vehicle computing method for managing resource according to claim 9, which is characterized in that carry out automatic Pilot
Managing computing resources, this operating process include：
Step 1, vehicle computing unit are marked the specialized hardwares such as FPGA, GPU by container management service, are related to depth
The scenes such as reasoning are practised, then are serviced using given host load vessel；
Step 2, vehicle computing unit monitor the container and hardware resource situation of autonomous driving vehicle by container management service；
If the allocated computing resource of step 3, container has reached critical value, there is inadequate resource phenomenon, then it is preferential to key
It calculates distribution and uses reserved resource；
Step 4 reaches saturation situation when container resource utilization, if crucial application resource is insufficient, grabs non-key business
The resource of application ensures the operation of Core Feature；
Step 5, if there is non-critical application container operation exception, such as V2X sensing equipment data acquisition applications, some is backward
High-definition camera data acquisition applications etc., then turn off container Resource recovery, redistributes resource, and load vessel mirror image and starting is answered
With；
Step 6 is determined if there is crucial application container operation exception, such as preposition high-definition camera data acquisition service, reasoning
The safe reduction of speed parking of automatic Pilot is completed in plan service etc., then priority scheduling execution emergency brake application service, and vehicle safety stops
After only, resource is redistributed, load vessel mirror image simultaneously starts application, reopens Function for Automatic Pilot；
If hardware anomalies occur in step 7, some host, priority scheduling executes emergency brake application service, and completion is driven automatically
The safe reduction of speed parking sailed judges remaining available host quantity after vehicle safety stops, if there is no less than two available masters
The container mirror image for powering off host operation is then loaded into other hosts, reopens Function for Automatic Pilot by machine；
Step 8, vehicle computing unit collect the computing resource data of different vehicle driving scene, and root by container management service
According to current driving situation individual scene dynamic optimization adjustresources.
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