CN102963356A - Human-simulated intelligent control structure of automatic parking system - Google Patents
Human-simulated intelligent control structure of automatic parking system Download PDFInfo
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- CN102963356A CN102963356A CN2012105324987A CN201210532498A CN102963356A CN 102963356 A CN102963356 A CN 102963356A CN 2012105324987 A CN2012105324987 A CN 2012105324987A CN 201210532498 A CN201210532498 A CN 201210532498A CN 102963356 A CN102963356 A CN 102963356A
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Abstract
The invention provides a human-simulated intelligent control structure of an automatic parking system, which comprises an automobile posture sensing module, a characteristic state set module, a control mode set module, a characteristic identification module, a control decision making module and an actuating mechanism, wherein the automobile posture sensing module is used for collecting automobile posture and parking environment information; the characteristic state set module and the control mode set module are used for describing the dynamic behavior characteristics of an automobile and the parking control strategy of a skilled driver; the characteristic identification module is used for identifying the current characteristic state of the automobile from a characteristic state set according to the deviation between the automobile posture and a parking target, so as to provide reference for the control decision making module; the control decision making module is used for selecting a corresponding control mode from a control mode set according to the characteristic state identified by the characteristic identification module, so as to serve as input of the actuating mechanism; and the actuating mechanism is used for controlling the automobile to park in position according to a predetermined target by adjusting steering servo, throttle servo and brake servo according to the control mode.
Description
Technical field
The present invention relates to automobile automatic parking field, say in more detail a kind of Human Simulating Intelligent Control structure of automated parking system.
Background technology
In recent years, automobile pollution increases rapidly, and the space of parking, limited city seems day by day short of money in face of the demand of parking stall.Simultaneously, careless slightly with automotive safety, successfully sail narrow and small parking position not a duck soup into, just may wipe, hang collision case, driving experience, driving skills and the capability of reaction of chaufeur all had higher requirements.If automobile can imitate driver's operation, realize that automatic parking enters the position, then can utilize more fully existing parking position resource, improve the safety of parking, reduce the complexity of driver's operation.Therefore, research automatic parking problem has important practical significance and using value.
Automatic parking is that a multiinput-multioutput non-linear owes to drive coupled system, and control method is one of its gordian technique.At present, the control method of automatic parking mainly contains two classes: one is based on the method (list of references [1]: Kang Zhi Liu of path planning, Minh Quan Dao, Takuya Inoue. An exponentially ε-convergent control algorithm for chained systems and its application to automatic parking systems[J]. IEEE Transactions on Control Systems Technology, 2006,14 (6): 1113-1126), space and automobile sport are learned characteristic according to parking, generate the desirable path planning of parking, adopt classical control theory to drive automobile and be moved into parking position along path planning, the method requires very high to the particularity of sensor and actr, be difficult to the error that compensation implementation neutralized system dynamic causes, affect the effect of parking; Two are based on the fuzzy control method of experimental knowledge, VEHICLES MUST PARK WITHIN THE MARKED BAY that experience is converted into fuzzy controller with experienced driver, the control vehicle movement is to the target parking position, the method and neural network (list of references [2]: K. Demirli, M.Khoshnejad. Autonomous parallel parking of a car-like mobile robot by a neuro-fuzzy sensor-based controller[J]. Fuzzy Sets and Systems, 2009,160:2876-2891), genetic algorithm (list of references [3]: Salvatore Pennacchio, Emanuele Bellafiore, Francesco Fontana, Orazio Nevoloso. A new algorithm for reverse car parking problem[C]. Proceedings of the 6th WSEAS Int. Conf. on Fuzzy Systems, 2005:56-60) etc. combine, obtained certain progress, but the completeness of fuzzy control rule, the Global Optimality of fuzz variable subordinate function is difficult to guarantee, the sampled data of neural network training is obtained relatively difficulty, obfuscation, calculated amount is large when defuzzification and parameter optimization.Path planning and experimental knowledge are combined, the intelligent advantage of fully imitating and utilizing experienced driver to park, the experienced driver experience of parking being converted into intelligent controller, can taking into account particularity and the robustness of parking system, is the development tendency of automated parking system.
Summary of the invention
The Human Simulating Intelligent Control structure that the purpose of this invention is to provide a kind of simple, failure-free automated parking system, the simulation experienced driver experience of parking, realize automobile automatically, safety, standard parks.
The present invention realizes above-mentioned purpose by the following technical solutions: a kind of Human Simulating Intelligent Control structure of automated parking system, it is characterized in that, and comprise the perception of automobile attitude, eigenstate collection, control mode collection, feature identification, control decision and actuating unit; The perception of automobile attitude realizes the perception to automobile current location, kinematic velocity, steering wheel angle and obstacle and vehicle body range information; Eigenstate collection and control mode collection are described respectively the control policy of parking of dynamic behaviour feature and the experienced driver of automobile; Feature identification picks out the current eigenstate of automobile from eigenstate is concentrated, for control decision provides foundation according to the deviation of automobile pose with the target of parking; Control decision is chosen corresponding control mode from control mode is concentrated, as the input of actuating unit according to the eigenstate of feature identification; Actuating unit is according to control mode, adjust turn to servo, throttle is servo and it is servo to brake, VEHICLES MUST PARK WITHIN THE MARKED BAY by intended target for the control automobile.
The flow process of described Human Simulating Intelligent Control structure is, park the beginning after, the automobile attitude information is carried out perception, pick out the current eigenstate of automobile according to the automobile posture information of perception, judge then whether current eigenstate satisfies the success conditions of parking, if satisfy, the flow process of then parking finishes, if do not satisfy, then determines corresponding control mode according to current eigenstate, control automobile sport and attitude adjustment, VEHICLES MUST PARK WITHIN THE MARKED BAY until automobile is by intended target.
The invention has the beneficial effects as follows: adopt the automated parking system of Human Simulating Intelligent Control structure, can select corresponding control mode according to the current eigenstate of automobile intelligently by the experience of parking of simulation experienced driver, the realization automobile automatically, VEHICLES MUST PARK WITHIN THE MARKED BAY safely.Be applicable to chaufeur and feel difficult occasion to parking, have good market application foreground.
Description of drawings
Fig. 1 is the Human Simulating Intelligent Control structured flowchart of automated parking system of the present invention.
Fig. 2 is the Human Simulating Intelligent Control diagram of circuit of automated parking system of the present invention.
The specific embodiment
The invention will be further described below in conjunction with accompanying drawing: see also accompanying drawing 1, be the Human Simulating Intelligent Control structured flowchart of this automated parking system, comprise automobile attitude perception 1, eigenstate collection 2, control mode collection 3, feature identification 4, control decision 5 and actuating unit 6.Automobile attitude perception 1 adopts the realizations such as CCD camera, incremental encoder, ultrasonic transduter to the perception of automobile current location, kinematic velocity, steering wheel angle and obstacle and vehicle body range information, and it generally is installed on around the auto body; Eigenstate collection 2 is set of describing the eigenstate of automobile dynamic behaviour, for feature identification provides foundation, the foundation of dividing eigenstate is that the automobile pose mainly contains deviation in range and deviation in direction with respect to the rate of change of deviation and the deviation of the target of parking in the process of parking; Control mode collection 3 is the imitation flexible and changeable parking strategy of experienced driver and the set of the control mode of parking that forms, and concrete by the control of pound-pound, ratio, differential, integration control, open loop retentive control and their modes such as combination realize; Feature identification 4 is processed the automobile pose deviation information that receives in real time according to eigenstate collection priori, and vehicle condition is carried out pattern-recognition, determines the current eigenstate of automobile, for control decision provides foundation; The experience of parking of control decision 5 imitation experienced driver according to the eigenstate of feature identification, is concentrated definite suitable control mode from control mode, as the control inputs of actuating unit 6, mainly comprises turning to control and speed control information; Actuating unit 6 is according to the control mode that receives, by the motor adjustment turn to servo, throttle is servo and it is servo to brake, VEHICLES MUST PARK WITHIN THE MARKED BAY by intended target for the control automobile.
Consult accompanying drawing 2, Human Simulating Intelligent Control diagram of circuit for this automated parking system, when chaufeur is prepared to park, can open the automatic parking control system of artificial intelligent, at this moment, the Human Simulating Intelligent Control structure begins to work, to current vehicle attitude, obstacle information carries out perception around parking lot parameters and the vehicle body, pick out the current eigenstate of automobile according to perception data, judge whether to satisfy the successful condition of parking, if automobile is in the parking position, in allowed band, and vehicle body is comparatively parallel with the parking stall direction apart from the parking position border, then think and park successfully, finish to park flow process, if current automobile eigenstate does not satisfy the success conditions of parking, then determine suitable control mode according to the current automobile eigenstate of feature identification, control automobile sport and attitude adjustment by actuating unit according to control mode, then reenter the attitude perception, so continue until satisfy the success conditions of parking, VEHICLES MUST PARK WITHIN THE MARKED BAY by intended target for automobile.
Claims (2)
1. the Human Simulating Intelligent Control structure of an automated parking system is characterized in that, comprises the perception of automobile attitude, eigenstate collection, control mode collection, feature identification, control decision and actuating unit;
Described automobile attitude perception realizes the perception to automobile current location, kinematic velocity, steering wheel angle and obstacle and vehicle body range information;
Described eigenstate collection and control mode collection are described respectively the control policy of parking of dynamic behaviour feature and the experienced driver of automobile;
Described feature identification picks out the current eigenstate of automobile from eigenstate is concentrated, for control decision provides foundation according to the deviation of automobile pose with the target of parking;
Described control decision is chosen corresponding control mode from control mode is concentrated, as the input of actuating unit according to the eigenstate of feature identification;
Described actuating unit is according to control mode, adjust turn to servo, throttle is servo and it is servo to brake, VEHICLES MUST PARK WITHIN THE MARKED BAY by intended target for the control automobile.
2. the Human Simulating Intelligent Control structure of a kind of automated parking system as claimed in claim 1, it is characterized in that, described Human Simulating Intelligent Control flow process is, park the beginning after, the automobile attitude information is carried out perception, automobile posture information according to perception picks out the current eigenstate of automobile, then judge whether current eigenstate satisfies the success conditions of parking, if satisfy, the flow process of then parking finishes, if do not satisfy, then determines corresponding control mode according to current eigenstate, control automobile sport and attitude adjustment, VEHICLES MUST PARK WITHIN THE MARKED BAY until automobile is by intended target.
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Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103950409A (en) * | 2014-04-24 | 2014-07-30 | 中国科学院深圳先进技术研究院 | Method and system for assisting in parking |
| CN104002806A (en) * | 2014-05-07 | 2014-08-27 | 江苏宁克传感器科技有限公司 | Intelligent transportation system |
| CN104118430A (en) * | 2014-07-22 | 2014-10-29 | 南京航空航天大学 | Parallel parking system and method based on sliding-mode active-disturbance-rejection control |
| CN104608766A (en) * | 2014-12-29 | 2015-05-13 | 李德毅 | Automatic parking method and system used for intelligent vehicle through parking memory stick |
| CN104637342A (en) * | 2015-01-22 | 2015-05-20 | 江苏大学 | Intelligent identification and parking path planning system and method for narrow and vertical parking space scene |
| CN105539438A (en) * | 2014-10-27 | 2016-05-04 | 福特全球技术公司 | Method and device for a vehicle control procedure |
| CN105966395A (en) * | 2016-05-24 | 2016-09-28 | 北京新能源汽车股份有限公司 | Vehicle and parking control method and device thereof |
| CN108556841A (en) * | 2018-06-25 | 2018-09-21 | 四川野马汽车股份有限公司 | A kind of system and its working method that electric vehicle is automatically parked |
| CN108725436A (en) * | 2018-05-14 | 2018-11-02 | 吉利汽车研究院（宁波）有限公司 | One kind being capable of fool proof automatic parking device and method |
| WO2018232940A1 (en) * | 2017-06-23 | 2018-12-27 | 深圳市盛路物联通讯技术有限公司 | Method and device for safe parking |
| CN109649379A (en) * | 2018-12-21 | 2019-04-19 | 北京汽车集团有限公司 | The control method and device of automatic parking |
| CN111532263A (en) * | 2020-05-08 | 2020-08-14 | 奇瑞汽车股份有限公司 | Automobile driving assisting method, device, equipment and storage medium |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2001005523A (en) * | 1999-06-22 | 2001-01-12 | Uchihashi Estec Co Ltd | Automatic parking method |
| WO2006069976A2 (en) * | 2004-12-24 | 2006-07-06 | Continental Teves Ag & Co. Ohg | Method and parking assistance device for steering a vehicle into a parking gap |
| US20080255728A1 (en) * | 2005-12-09 | 2008-10-16 | Hella Kgaa Hueck & Co. | Path Planning |
| CN101898559A (en) * | 2009-02-09 | 2010-12-01 | 通用汽车环球科技运作公司 | The path planning that is used for automatic parking |
| CN102303604A (en) * | 2011-06-29 | 2012-01-04 | 广东好帮手电子科技股份有限公司 | Automatic parking system |
| CN102658819A (en) * | 2012-05-16 | 2012-09-12 | 涂亚庆 | Automobile automatic parking method based on humanoid intelligent control |
-
2012
- 2012-12-12 CN CN2012105324987A patent/CN102963356A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2001005523A (en) * | 1999-06-22 | 2001-01-12 | Uchihashi Estec Co Ltd | Automatic parking method |
| WO2006069976A2 (en) * | 2004-12-24 | 2006-07-06 | Continental Teves Ag & Co. Ohg | Method and parking assistance device for steering a vehicle into a parking gap |
| US20080255728A1 (en) * | 2005-12-09 | 2008-10-16 | Hella Kgaa Hueck & Co. | Path Planning |
| CN101898559A (en) * | 2009-02-09 | 2010-12-01 | 通用汽车环球科技运作公司 | The path planning that is used for automatic parking |
| CN102303604A (en) * | 2011-06-29 | 2012-01-04 | 广东好帮手电子科技股份有限公司 | Automatic parking system |
| CN102658819A (en) * | 2012-05-16 | 2012-09-12 | 涂亚庆 | Automobile automatic parking method based on humanoid intelligent control |
Cited By (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103950409A (en) * | 2014-04-24 | 2014-07-30 | 中国科学院深圳先进技术研究院 | Method and system for assisting in parking |
| CN104002806A (en) * | 2014-05-07 | 2014-08-27 | 江苏宁克传感器科技有限公司 | Intelligent transportation system |
| CN104002806B (en) * | 2014-05-07 | 2016-04-13 | 江苏宁克传感器科技有限公司 | A kind of intelligent transportation system |
| CN104118430A (en) * | 2014-07-22 | 2014-10-29 | 南京航空航天大学 | Parallel parking system and method based on sliding-mode active-disturbance-rejection control |
| CN104118430B (en) * | 2014-07-22 | 2016-08-24 | 南京航空航天大学 | A kind of Parallel parking system based on sliding formwork Active Disturbance Rejection Control and method of parking |
| CN105539438B (en) * | 2014-10-27 | 2019-10-18 | 福特全球技术公司 | Method and apparatus for vehicle control program |
| CN105539438A (en) * | 2014-10-27 | 2016-05-04 | 福特全球技术公司 | Method and device for a vehicle control procedure |
| CN104608766A (en) * | 2014-12-29 | 2015-05-13 | 李德毅 | Automatic parking method and system used for intelligent vehicle through parking memory stick |
| CN104637342A (en) * | 2015-01-22 | 2015-05-20 | 江苏大学 | Intelligent identification and parking path planning system and method for narrow and vertical parking space scene |
| CN105966395A (en) * | 2016-05-24 | 2016-09-28 | 北京新能源汽车股份有限公司 | Vehicle and parking control method and device thereof |
| WO2018232940A1 (en) * | 2017-06-23 | 2018-12-27 | 深圳市盛路物联通讯技术有限公司 | Method and device for safe parking |
| CN108725436A (en) * | 2018-05-14 | 2018-11-02 | 吉利汽车研究院（宁波）有限公司 | One kind being capable of fool proof automatic parking device and method |
| CN108556841A (en) * | 2018-06-25 | 2018-09-21 | 四川野马汽车股份有限公司 | A kind of system and its working method that electric vehicle is automatically parked |
| CN109649379A (en) * | 2018-12-21 | 2019-04-19 | 北京汽车集团有限公司 | The control method and device of automatic parking |
| CN111532263A (en) * | 2020-05-08 | 2020-08-14 | 奇瑞汽车股份有限公司 | Automobile driving assisting method, device, equipment and storage medium |
| CN111532263B (en) * | 2020-05-08 | 2022-05-03 | 奇瑞汽车股份有限公司 | Automobile driving assisting method, device, equipment and storage medium |
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