CN109703567A - Control method for vehicle - Google Patents
Control method for vehicle Download PDFInfo
- Publication number
- CN109703567A CN109703567A CN201910072731.XA CN201910072731A CN109703567A CN 109703567 A CN109703567 A CN 109703567A CN 201910072731 A CN201910072731 A CN 201910072731A CN 109703567 A CN109703567 A CN 109703567A
- Authority
- CN
- China
- Prior art keywords
- vehicle
- data
- driver
- dynamic
- control method
- 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.)
- Withdrawn
Links
- 238000000034 method Methods 0.000 title claims abstract description 32
- 230000006399 behavior Effects 0.000 claims abstract description 43
- 230000003542 behavioural effect Effects 0.000 claims 1
Landscapes
- Traffic Control Systems (AREA)
Abstract
The present invention discloses control method for vehicle, which includes: S1, constructs the vehicle drive behavior database of driver in advance, the action data and voice data of memory of driving person in the vehicle drive behavior database;S2, each action data or voice data corresponding one specific vehicle control movement, simulates working model for the operational motion of vehicle drive behavior database corresponding thereto;S3, acquires the dynamic driving behavior data of driver in real time, and will be compared in the dynamic driving behavior data inputting working model, obtains corresponding vehicle control movement to control vehicle.The control method for vehicle overcome driver in the prior art can not long-range or virtual controlling vehicle, realize movement or the voice control of vehicle.
Description
Technical field
The present invention relates to field of vehicle control, and in particular, to control method for vehicle.
Background technique
Automated vehicle control is exactly the Technology application by some automatic controls in fact into traffic system, is mentioned by previous
High-mechanical property development replaces or all replaces the manipulation of people for auxiliary or part, reaches reduction as caused by the limitation of people
Accident mitigates and drives intensity raising traffic efficiency, reduces the target of pollution.
Vehicle control at this stage still needs to execute control by the information exchange on driver and backstage, and certainly
Dynamic control technology is still less flourishing, can not accomplish practical manipulation and the combination of analog manipulation, guarantees accurate reception and registration driver's
The meaning.
Summary of the invention
The object of the present invention is to provide a kind of control method for vehicle, which overcomes in the prior art drive
The person of sailing can not long-range or virtual controlling vehicle, realize movement or the voice control of vehicle.
To achieve the goals above, the present invention provides a kind of control method for vehicle, which includes:
S1 constructs the vehicle drive behavior database of driver, memory of driving in the vehicle drive behavior database in advance
The action data and voice data of member;
S2, each action data or voice data corresponding one specific vehicle control movement, by vehicle drive behavior
The operational motion of database corresponding thereto simulates working model;
S3 acquires the dynamic driving behavior data of driver in real time, and by the dynamic driving behavior data inputting Working mould
It is compared in type, obtains corresponding vehicle control movement to control vehicle.
Preferably, after s 2 and before S3 further include: S2 ', the practical driving condition for prejudging vehicle is following drives
Sail one of state: automatic Pilot and manual drive;
In the case where the practical driving condition of the vehicle is automatic Pilot, step S3 is executed.
Preferably, in step sl, the method for the vehicle drive behavior database of building driver includes: in advance
Driver's standard operation data and standard voice data are acquired, and multiple to the movement acquisition of any one vehicle control
Corresponding standard operation data and standard voice data, to form a normal data range library.
Preferably, in step s3, show that corresponding vehicle control acts the method to be controlled vehicle further include:
Vehicle obstacle information nearby is acquired, and analyzes the numerical value for executing and colliding possibility after the vehicle control acts,
In the case that the numerical value of the collision possibility is greater than default value, alerted before executing vehicle control movement.
Preferably, it is alerted before executing vehicle control movement, and acquires the dynamic action number of driver after alarm
According to or voice data duplicate acknowledgment whether execute vehicle control movement.
Preferably, in S3, dynamic driving behavior data include: dynamic action data or voice data, by prefabricated
Camera acquires dynamic action data, and the voice data of driver is acquired by multiple microphones.
Preferably, in S3, the dynamic driving behavior data of driver are acquired in real time, and by the dynamic driving behavior data
The method being compared in typing working model includes:
Dynamic action data are acquired by prefabricated camera, and eliminate dynamic action number in the dynamic action data
Motion characteristic is covered up in the presence of a large amount of and unrelated real behavior according to middle, obtains true dynamic driving behavior data, by the dynamic
It is compared in driving behavior typing working model.
Preferably, by the method that prefabricated camera acquires dynamic action data include: in the case where vehicle launch,
The instruction of the dynamic driving behavior data of acquisition driver is obtained, the fortune in driver 20s is persistently shot by high-speed camera
It is dynamic, 200 frame images are obtained by figure acquisition software, which is dynamic action data, real-time typing action data to work
Make to be compared in model.
Through the above technical solutions, the identification that image can be carried out to the posture of human body of the invention, and can basis
The posture of the human body identified realizes the control of vehicle, realizes complete virtual vehicle performance mode, it is ensured that vehicle
Control processing, it is ensured that the expressed intact of the posture of human body realizes that driver controls vehicle by posture.
Other features and advantages of the present invention will the following detailed description will be given in the detailed implementation section.
Detailed description of the invention
The drawings are intended to provide a further understanding of the invention, and constitutes part of specification, with following tool
Body embodiment is used to explain the present invention together, but is not construed as limiting the invention.In the accompanying drawings:
Fig. 1 is a kind of flow chart of the control method for vehicle of preferred embodiment of the invention.
Specific embodiment
Below in conjunction with attached drawing, detailed description of the preferred embodiments.It should be understood that this place is retouched
The specific embodiment stated is merely to illustrate and explain the present invention, and is not intended to restrict the invention.
The present invention provides a kind of control method for vehicle, which includes:
S1 constructs the vehicle drive behavior database of driver, memory of driving in the vehicle drive behavior database in advance
The action data and voice data of member;
S2, each action data or voice data corresponding one specific vehicle control movement, by vehicle drive behavior
The operational motion of database corresponding thereto simulates working model;
S3 acquires the dynamic driving behavior data of driver in real time, and by the dynamic driving behavior data inputting Working mould
It is compared in type, obtains corresponding vehicle control movement to control vehicle.
Through the above technical solutions, the identification that image can be carried out to the posture of human body of the invention, and can basis
The posture of the human body identified realizes the control of vehicle, realizes complete virtual vehicle performance mode, it is ensured that vehicle
Control processing, it is ensured that the expressed intact of the posture of human body realizes that driver controls vehicle by posture.
In a kind of specific embodiment of the invention, in order to realize accurate judgement, needing to prejudge is automatic Pilot
The case where get off to carry out the identification of human body attitude, after s 2 and before S3 further include: S2 ' prejudges actually driving for vehicle
Sailing state is one of following driving condition: automatic Pilot and manual drive;
In the case where the practical driving condition of the vehicle is automatic Pilot, step S3 is executed.
In a kind of specific embodiment of the invention, in step sl, the vehicle drive behavior of driver is constructed in advance
The method of database may include:
Driver's standard operation data and standard voice data are acquired, and multiple to the movement acquisition of any one vehicle control
Corresponding standard operation data and standard voice data, to form a normal data range library.
By above-mentioned embodiment, multiple driver's standard operation data and standard voice data can be acquired, is passed through
These multiple data can reduce the generation of error rate, so that the movement of driver can carry out in range in river and adopt.
In a kind of specific embodiment of the invention, in step s3, obtain corresponding vehicle control movement to vehicle
The method controlled can also include:
Vehicle obstacle information nearby is acquired, and analyzes the numerical value for executing and colliding possibility after the vehicle control acts,
In the case that the numerical value of the collision possibility is greater than default value, alerted before executing vehicle control movement.
By above-mentioned mode, it can be read to avoid operation error and image information and control danger caused by fault, avoided
The collision of vehicle and the generation of accident.
In this embodiment, it is alerted before executing vehicle control movement, and acquires driver's after alarm
Whether dynamic action data or voice data duplicate acknowledgment execute vehicle control movement.
By above-mentioned embodiment, the record again of dynamic action data or voice data can be ensured after vehicle alarm
Enter to judge whether executive control operation, avoids read error.
In a kind of specific embodiment of the invention, in S3, dynamic driving behavior data may include: dynamic action
Data or voice data acquire dynamic action data by prefabricated camera, and acquire driver's by multiple microphones
Voice data.
The data acquisition of voice and motion images is realized by above-mentioned mode.
7, control method for vehicle according to claim 6, which is characterized in that in S3, acquire driver's in real time
Dynamic driving behavior data, and include: by the method being compared in the dynamic driving behavior data inputting working model
Dynamic action data are acquired by prefabricated camera, and eliminate dynamic action number in the dynamic action data
Motion characteristic is covered up in the presence of a large amount of and unrelated real behavior according to middle, obtains true dynamic driving behavior data, by the dynamic
It is compared in driving behavior typing working model.
It in this embodiment, may include: in vehicle by the method that prefabricated camera acquires dynamic action data
Starting in the case where, obtain acquisition driver dynamic driving behavior data instruction, persistently shot by high-speed camera
Movement in driver 20s obtains 200 frame images by figure acquisition software, which is dynamic action data, real-time typing
The action data is compared into working model.
It is described the prefered embodiments of the present invention in detail above in conjunction with attached drawing, still, the present invention is not limited to above-mentioned realities
The detail in mode is applied, within the scope of the technical concept of the present invention, a variety of letters can be carried out to technical solution of the present invention
Monotropic type, these simple variants all belong to the scope of protection of the present invention.
It is further to note that specific technical features described in the above specific embodiments, in not lance
In the case where shield, can be combined in any appropriate way, in order to avoid unnecessary repetition, the present invention to it is various can
No further explanation will be given for the combination of energy.
In addition, various embodiments of the present invention can be combined randomly, as long as it is without prejudice to originally
The thought of invention, it should also be regarded as the disclosure of the present invention.
Claims (8)
1. a kind of control method for vehicle, which is characterized in that the control method for vehicle includes:
S1 constructs the vehicle drive behavior database of driver in advance, memory of driving person in the vehicle drive behavior database
Action data and voice data;
S2, each action data or voice data corresponding one specific vehicle control movement, by vehicle drive behavioral data
The operational motion of library corresponding thereto simulates working model;
S3 acquires the dynamic driving behavior data of driver in real time, and will be in the dynamic driving behavior data inputting working model
It is compared, obtains corresponding vehicle control movement to control vehicle.
2. control method for vehicle according to claim 1, which is characterized in that after s 2 and before S3 further include: S2 ',
The practical driving condition for prejudging vehicle is one of following driving condition: automatic Pilot and manual drive;
In the case where the practical driving condition of the vehicle is automatic Pilot, step S3 is executed.
3. control method for vehicle according to claim 1, which is characterized in that in step sl, construct driver's in advance
The method of vehicle drive behavior database includes:
Driver's standard operation data and standard voice data are acquired, and multiple therewith to the movement acquisition of any one vehicle control
Corresponding standard operation data and standard voice data, to form a normal data range library.
4. control method for vehicle according to claim 1, which is characterized in that in step s3, obtain corresponding vehicle control
The method that braking is made to be controlled vehicle further include:
Acquire vehicle obstacle information nearby, and analyze execute vehicle control movement after collide the numerical value of possibility, touch at this
The numerical value of possibility is hit greater than in the case where default value, is alerted before executing vehicle control movement.
5. control method for vehicle according to claim 4, which is characterized in that accused before executing vehicle control movement
It is alert, and whether the dynamic action data of acquisition driver or voice data duplicate acknowledgment execute vehicle control movement after alarm.
6. control method for vehicle according to claim 1, which is characterized in that in S3, dynamic driving behavior data include:
Dynamic action data or voice data acquire dynamic action data by prefabricated camera, and are acquired by multiple microphones
The voice data of driver.
7. control method for vehicle according to claim 6, which is characterized in that in S3, acquire the dynamic of driver in real time
Driving behavior data, and include: by the method being compared in the dynamic driving behavior data inputting working model
Dynamic action data are acquired by prefabricated camera, and are eliminated in dynamic action data in the dynamic action data
Motion characteristic is covered up in the presence of a large amount of and unrelated real behavior, obtains true dynamic driving behavior data, which is driven
It is compared in behavior typing working model.
8. control method for vehicle according to claim 7, which is characterized in that acquire dynamic action by prefabricated camera
The method of data includes: that the instruction of the dynamic driving behavior data of acquisition driver is obtained in the case where vehicle launch, is passed through
High-speed camera persistently shoots the movement in driver 20s, obtains 200 frame images by figure acquisition software, which is
State action data, the real-time typing action data are compared into working model.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910072731.XA CN109703567A (en) | 2019-01-25 | 2019-01-25 | Control method for vehicle |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910072731.XA CN109703567A (en) | 2019-01-25 | 2019-01-25 | Control method for vehicle |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109703567A true CN109703567A (en) | 2019-05-03 |
Family
ID=66261822
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910072731.XA Withdrawn CN109703567A (en) | 2019-01-25 | 2019-01-25 | Control method for vehicle |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109703567A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110471411A (en) * | 2019-07-26 | 2019-11-19 | 华为技术有限公司 | Automatic driving method and automatic driving device |
| CN111231972A (en) * | 2019-09-27 | 2020-06-05 | 中国第一汽车股份有限公司 | Warning method, system, vehicle and storage medium based on driving behavior |
| CN111409646A (en) * | 2020-03-09 | 2020-07-14 | 上海博泰悦臻电子设备制造有限公司 | Automatic driving control method, system, medium and vehicle-mounted terminal based on multi-mode identification |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130204457A1 (en) * | 2012-02-06 | 2013-08-08 | Ford Global Technologies, Llc | Interacting with vehicle controls through gesture recognition |
| CN104364735A (en) * | 2012-04-13 | 2015-02-18 | 诺基亚公司 | Free hand gesture control of automotive user interface |
| US20150336588A1 (en) * | 2012-07-06 | 2015-11-26 | Audi Ag | Method and control system for operating a motor vehicle |
| CN108248402A (en) * | 2016-12-28 | 2018-07-06 | 广东合即得能源科技有限公司 | An electric car that can be controlled remotely |
-
2019
- 2019-01-25 CN CN201910072731.XA patent/CN109703567A/en not_active Withdrawn
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130204457A1 (en) * | 2012-02-06 | 2013-08-08 | Ford Global Technologies, Llc | Interacting with vehicle controls through gesture recognition |
| CN104364735A (en) * | 2012-04-13 | 2015-02-18 | 诺基亚公司 | Free hand gesture control of automotive user interface |
| US20150336588A1 (en) * | 2012-07-06 | 2015-11-26 | Audi Ag | Method and control system for operating a motor vehicle |
| CN108248402A (en) * | 2016-12-28 | 2018-07-06 | 广东合即得能源科技有限公司 | An electric car that can be controlled remotely |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110471411A (en) * | 2019-07-26 | 2019-11-19 | 华为技术有限公司 | Automatic driving method and automatic driving device |
| CN111231972A (en) * | 2019-09-27 | 2020-06-05 | 中国第一汽车股份有限公司 | Warning method, system, vehicle and storage medium based on driving behavior |
| CN111231972B (en) * | 2019-09-27 | 2021-12-10 | 中国第一汽车股份有限公司 | Warning method based on driving behavior habit, vehicle and storage medium |
| CN111409646A (en) * | 2020-03-09 | 2020-07-14 | 上海博泰悦臻电子设备制造有限公司 | Automatic driving control method, system, medium and vehicle-mounted terminal based on multi-mode identification |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11853072B2 (en) | System and method for real world autonomous vehicle trajectory simulation | |
| US12454054B2 (en) | Method for controlling robot, robot and computer-readable storage medium | |
| Mukadam et al. | Tactical decision making for lane changing with deep reinforcement learning | |
| US10824947B2 (en) | Learning method for supporting safer autonomous driving without danger of accident by estimating motions of surrounding objects through fusion of information from multiple sources, learning device, testing method and testing device using the same | |
| CN109703567A (en) | Control method for vehicle | |
| CN112906126B (en) | Vehicle hardware in-loop simulation training system and method based on deep reinforcement learning | |
| CN115469663B (en) | End-to-end navigation obstacle avoidance method based on deep reinforcement learning and oriented to automatic driving | |
| CN115303297B (en) | End-to-end autonomous driving control method and device in urban scenarios based on attention mechanism and graph model reinforcement learning | |
| DE102019206092A1 (en) | SYSTEMS AND METHOD FOR PRODUCING INSTRUCTIONS FOR ACCESSING CROSSROADS WITH AUTONOMOUS VEHICLES | |
| CN111006879A (en) | Port environment-oriented man-machine hybrid driving automatic driving test method and test platform thereof | |
| CN116348355A (en) | Method and system for testing a driver assistance system of a vehicle | |
| EP3811351A1 (en) | Adaptation of the trajectory of an ego vehicle to moved extraneous objects | |
| EP4206051A1 (en) | Method and apparatus for determining automatic parking strategy | |
| CN110969911A (en) | Intelligent subject two training system and method based on virtual reality | |
| CN110316185A (en) | Control method, device, equipment and the readable storage medium storing program for executing of car speed | |
| Schütt et al. | An application of scenario exploration to find new scenarios for the development and testing of automated driving systems in urban scenarios | |
| CN116680979A (en) | A method for automatic generation of unmanned driving test scenarios based on reinforcement learning | |
| CN120012838A (en) | Causal reinforcement learning system for vehicles in safety-critical scenarios with causal confusion | |
| CN109703560A (en) | The method for automatically controlling automatic driving vehicle and following distance between vehicle | |
| CN116629114A (en) | Multi-agent model training method, system, computer equipment and storage medium | |
| CN115092166B (en) | Interactive automatic driving speed planning method based on social force model | |
| CN116203950A (en) | CTU path planning method integrating particle swarm algorithm and dynamic window method | |
| CN111413974A (en) | Automobile automatic driving motion planning method and system based on learning sampling type | |
| CN109649379A (en) | The control method and device of automatic parking | |
| CN118760120A (en) | Vehicle fault simulation test system, method, device, and computer program product |
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 | ||
| WW01 | Invention patent application withdrawn after publication | ||
| WW01 | Invention patent application withdrawn after publication |
Application publication date: 20190503 |