CN109398349A - A kind of automatic parking method and system based on geometric programming and intensified learning - Google Patents
A kind of automatic parking method and system based on geometric programming and intensified learning Download PDFInfo
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- CN109398349A CN109398349A CN201811056910.6A CN201811056910A CN109398349A CN 109398349 A CN109398349 A CN 109398349A CN 201811056910 A CN201811056910 A CN 201811056910A CN 109398349 A CN109398349 A CN 109398349A
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- 230000007613 environmental effect Effects 0.000 claims description 3
- 238000006073 displacement reaction Methods 0.000 claims description 2
- 238000010801 machine learning Methods 0.000 description 3
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- 230000004048 modification Effects 0.000 description 2
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Classifications
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
- B60W30/06—Automatic manoeuvring for parking
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- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Transportation (AREA)
- Mechanical Engineering (AREA)
- Control Of Driving Devices And Active Controlling Of Vehicle (AREA)
- Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
Abstract
The automatic parking method and system based on geometric programming and intensified learning that the present invention relates to a kind of, initial stage of the method for the present invention in automatic parking, by determining state of parking, track of parking is determined using geometric programming, track following and chassis control is transferred to be controlled again, using the above-mentioned stage, vehicle can be adjusted to the pose that can be once put in storage, and transfer to intensified learning to be controlled again at this time.Compared with prior art, the present invention can eliminate trajectory planning-track following-chassis control error, reach pose of more preferably parking, and the narrow environment of parking that can be suitable in city, to the adaptable of environment.
Description
Technical field
The present invention relates to intelligent automobile automatic parking planning technology fields, more particularly, to one kind based on geometric programming and by force
The automatic parking method and system that chemistry is practised.
Background technique
Existing automatic parking technology is mainly realized by the following method: rule-based decision rule method passes through
Fixed process of parking plans wheelpath using the state of finite states machine control vehicle, and by the method for planning.It is this
The output result for control method of parking is predictable, more stable, but does not have intelligence, can not successfully manage the complexity really parked
Scene.Meanwhile trajectory planning-track following-chassis control conventional architectures can not eliminate the mistake of track following and chassis control
Difference causes the track of planning and actual track inconsistent, can not adapt to the scene operating condition stringenter to pose requirement of parking.
Summary of the invention
It is an object of the present invention to overcome the above-mentioned drawbacks of the prior art and provide one kind to be based on geometric programming
And the automatic parking method and system of intensified learning.
The purpose of the present invention can be achieved through the following technical solutions:
A kind of automatic parking method based on geometric programming and intensified learning, method includes the following steps:
S1: after driver controls vehicle to warehouse compartment periphery of parking, automated parking system is activated, opens automatic parking mode.
S2: module of parking controls the slow straight-line travelling of vehicle.
S3: angular coordinate and the limited block position of warehouse compartment of parking are detected using the sensing module around vehicle body, judges warehouse compartment
Whether comply with standard, if so, determining parking stall, enters step S4；Otherwise, return step S2.
Preferably, if detecting multiple warehouse compartments, the warehouse compartment nearest apart from vehicle is selected, and judge whether the warehouse compartment meets
Standard, if not meeting, the lower warehouse compartment of reselection is simultaneously judged.
Judge the whether standard compliant content of warehouse compartment are as follows:
Warehouse compartment regional location and size are obtained, and detects within warehouse compartment region that whether there are obstacles；If warehouse compartment region shape
Shape and size meet the requirements, and barrier is not present, then it is assumed that the warehouse compartment complies with standard.
S4: parking path is planned according to the coordinate of the opposite warehouse compartment of parking of vehicle and current pose.
S5: whether it is able to achieve collisionless storage according to the first segment of planning curve of parking and judges whether to need multistage path to advise
It draws, if so, performing the next step；Otherwise, S7 is entered step.
S6: the adjustment of Multiple Sections path is carried out to vehicle.
Preferably, using multistage R-S curve planing method to progress Multiple Sections path adjustment.That is:
61) premised on vehicle rear axle right side is without impinging on warehouse compartment angle point, the starting point of first segment R-S curve is determined；
62) it after vehicle being beaten steering wheel to extreme position to the right, moves backward afterwards to the right to vehicle left back point on the left of warehouse compartment
On line or its extended line；
63) after vehicle being beaten steering wheel to extreme position to the left, vehicle pose is advanced to left front and is adjusted to a certain angle
Degree arrives at front obstacle safe distance.
S7: obtaining environmental information and car status information to carry out intensified learning network training, obtains vehicle control instruction,
That is:
71) build deeply learning network, using the status information of the opposite coordinate and vehicle from vehicle of warehouse compartment angle point as
Input is obtained using the control of steering wheel angle displacement instruction and throttle, brake pedal control instruction as output with the final stage process of parking
The feedback taken is up to target and is trained；
72) after the completion of training, deeply learning network exports the control instruction of vehicle according to current input.
S8: control vehicle storage is instructed according to vehicle control, automatic parking mode is exited in end of parking.
A kind of automated parking system based on geometric programming and intensified learning, the system include:
It parks module, for controlling the slow straight-line travelling of vehicle；
Sensing module, for acquiring ambient image, identification warehouse compartment line, judging vehicle with respect to warehouse compartment posture information and detection
Obstacle information simultaneously judges whether warehouse compartment is occupied；
Decision-making module judges the validity of warehouse compartment and current for recording according to the fuse information of sensing module and instruction
Locating parks the stage, and provides the posture information for planning parking path for planning module；
Planning module plans the track R-S and sends track and dissipate for the pose according to warehouse compartment information and vehicle with respect to warehouse compartment
Point is to according to tracking module；
Track following module, the track scatterplot transmitted for receiving planning module control steering wheel, gear by controller
Position, throttle and brake pedal, and then control vehicle tracking planned trajectory；
Intensified learning module, for the status information by warehouse compartment with respect to car's location information and vehicle, outbound course
Disk corner control instruction and speed control instruction；
Chassis actuator control module passes through controller for the tracking planned trajectory that receiving locus tracking module transmits
It calculates desired steering wheel, gear, throttle and brake pedal control amount or directly receives the control instruction of intensified learning module, lead to
It crosses drive-by-wire chassis actuator and tracks above-mentioned control amount.
Preferably, the sensing module include be set to side before and after vehicle body, left and right sides four cameras and be set to
12 ultrasonic radars around vehicle body, the camera is for acquiring ambient image, identification warehouse compartment line and using binocular
Matching process judges opposite warehouse compartment posture information, and whether the ultrasonic radar judges warehouse compartment for detecting obstacle information
It is occupied.
Preferably, the track following module includes ECU and line traffic control unit.
Preferably, in a system of the invention:
When driver by vehicle parking to rational position when, automatic parking mode is opened in selection；
When the warehouse compartment fuse information that sensing module is sent has not been obtained in decision-making module, planning module sends straight line and plans road
Diameter, control vehicle low speed move ahead, and sensing module continues to detect；
After detecting available warehouse compartment, judge whether warehouse compartment available and warehouse compartment type by decision-making module, and judge to work as front truck
Which kind of park the stage in, planning module is according to this phase paths of warehouse compartment information planning, and transmitting path scatterplot is to controlling mould
Block is tracked；
When automatic parking mode ends, decision-making module completes parking backed off after random automatic parking mould by control brake pedal
Formula.
Compared with prior art, the invention has the following advantages that
(1) present invention is in the initial stage of automatic parking, the geometric programming parked according to the state of parking, and determines pool
Wheel paths, then track following module and chassis actuator control module is transferred to be controlled；By the above-mentioned stage, vehicle can be adjusted
It is whole to transfer to intensified learning module to be controlled again at this time to the pose being once put in storage, trajectory planning-track following-bottom can be eliminated
The error of disk control, reaches pose of more preferably parking；
(2) present invention is using intensified learning network training as the control strategy of final stage, it is possible to reduce process of parking is former
Ground adjustment direction number, the narrow environment of parking that can be suitable in city, to the adaptable of environment.
Detailed description of the invention
Fig. 1 is the schematic illustration of automatic parking Discrete control of the present invention；
Fig. 2 is the flow chart of the automatic parking method of the invention based on geometric programming and intensified learning.
Specific embodiment
The present invention is described in detail with specific embodiment below in conjunction with the accompanying drawings.
The automatic parking method based on geometric programming and intensified learning that the present invention relates to a kind of, this method includes following step
It is rapid:
Step 1 after controlling vehicle to warehouse compartment periphery of parking by driver, opens automatic parking mode, parking system adapter tube
Vehicle control.
Step 2, module of parking control the slow straight-line travelling of vehicle.
Step 3 carries out warehouse compartment angular coordinate and limited block position by camera around vehicle body and ultrasonic sensor
Detection, calculate warehouse compartment regional location and size, and detect barrier presence or absence within warehouse compartment region；If warehouse compartment region shape
Size meets the requirements, and barrier is not present, and determines parking stall, enters step 4；Otherwise, step 2 is returned to.
If selecting the warehouse compartment nearest apart from this vehicle preferably, detecting multiple warehouse compartments in step 3, judging whether to meet
Standard；If not meeting, reselection judges next warehouse compartment.
Whether judgment criteria whether judging warehouse compartment properly in step 3 includes depositing in warehouse compartment type, warehouse compartment size and warehouse compartment
In barrier.
As shown in Figure 1, preferably, planning the track based on R-S curve first.
The coordinate and current pose S of step 4, basis from vehicle with respect to warehouse compartment, plan parking path.
Whether step 5, curve of being parked by the first segment planned are able to achieve collisionless storage to determine whether needing multistage road
Diameter planning, if so, entering step 6；Otherwise, 7 are entered step；
Preferably, step 6 is as shown in Figure 1, the specific steps adjusted are as follows: is adjusted using multistage R-S curve, adjustment side
Method (for parking to the right) is as follows:
61) premised on vehicle rear axle right side is without impinging on warehouse compartment angle point, the starting point A of first segment R-S curve is determined.
62) vehicle beats to the right steering wheel to extreme position, moves backward afterwards to the right, until vehicle left back point on the left of warehouse compartment line or
On its extended line, vehicle is now placed in B point.
63) vehicle beats steering wheel to extreme position to the left, advances to left front, until vehicle pose be adjusted to a certain angle or
To at front obstacle safe distance, vehicle is now placed in C point.
Step 7: after the state being put in storage into final stage, environmental information and car status information being inputted, training is passed through
Intensified learning network afterwards, obtains vehicle control instruction, and vehicle follows this control instruction and travelled by C point to D point.O1 in Fig. 1,
O2, O3 are respectively the camber line center of circle that starting point A to B point, B point to C point, C point are constituted to D point.
Step 8: chassis actuator control module controls vehicle storage, and park mode is exited in end of parking.
The present invention also provides a kind of automated parking system based on geometric programming and intensified learning, the system include perception
Module, decision-making module, planning module, intensified learning module, track following module and chassis actuator control module.
Sensing module includes the camera and ultrasonic radar being arranged in around vehicle body, and camera is for acquiring environment map
Picture identifies warehouse compartment line and judges opposite warehouse compartment posture information using binocular ranging method, and ultrasonic radar is for detecting barrier
Information judges whether warehouse compartment is occupied.Preferably, sensing module include be set to vehicle body all around 4 cameras of side and
12 ultrasonic radars being set to around vehicle body, camera are installed below the rearview mirror of vehicle body, and the forward and backward side of vehicle body respectively sets
4 ultrasonic radars are set, 2 ultrasonic radars are respectively arranged in the arranged on left and right sides of vehicle body.
Decision-making module is connect with sensing module, is recorded according to the fuse information of sensing module and instruction, judge warehouse compartment has
Effect property and the stage of parking being presently in are supplied to planning module posture information for planning parking path.
Planning module is connect with decision-making module, and the pose according to warehouse compartment information and from vehicle with respect to warehouse compartment plans the track R-S
Or posture information is sent to machine learning module, it sends track scatterplot and is tracked to chassis actuator control module.
Machine learning module is industrial computer, determines starting point pose input of vertically parking by machine learning method
With the relationship of secondary spiral line parameter, and the helix planned track of parking is sent to planning module.
Track following module includes ECU and line traffic control unit, receives the track scatterplot that planning module transmits, passes through controller control
Steering wheel, gear, throttle and brake pedal processed, and then control vehicle tracking planned trajectory.
Intensified learning module, for the status information by warehouse compartment with respect to car's location information and vehicle, outbound course
Disk corner control instruction and speed control instruction；
Chassis actuator control module (including path trace and chassis control) receives the tracking that track following module transmits
Planned trajectory (or the control instruction for directly receiving intensified learning module), tracks above-mentioned control amount by drive-by-wire chassis actuator.
This system has automatic parking mode, the specific control process of this system are as follows:
When driver by vehicle parking to rational position when, Systematic selection opens automatic parking mode；
When the warehouse compartment fuse information that sensing module is sent has not been obtained in decision-making module, planning module sends straight line and plans road
Diameter, control vehicle low speed move ahead, and sensing module continues to detect；
After detecting available warehouse compartment, judge whether warehouse compartment available and warehouse compartment type by decision-making module, and judge to work as front truck
Which kind of park the stage in, planning module is according to this phase paths of warehouse compartment information planning, and transmitting path scatterplot is to controlling mould
Block is tracked；
When automatic parking mode ends, decision-making module completes parking backed off after random automatic parking mould by control brake pedal
Formula.
The above description is merely a specific embodiment, but scope of protection of the present invention is not limited thereto, any
The staff for being familiar with the art in the technical scope disclosed by the present invention, can readily occur in various equivalent modifications or replace
It changes, these modifications or substitutions should be covered by the protection scope of the present invention.Therefore, protection scope of the present invention should be with right
It is required that protection scope subject to.
Claims (10)
1. a kind of automatic parking method based on geometric programming and intensified learning, which is characterized in that method includes the following steps:
1) after driver controls vehicle to warehouse compartment periphery of parking, automated parking system is activated, opens automatic parking mode；
2) module of parking controls the slow straight-line travelling of vehicle；
3) angular coordinate and the limited block position that warehouse compartment of parking is detected using the sensing module around vehicle body, judge whether warehouse compartment accords with
4) standardization enters step if so, determining parking stall；Otherwise, return step 2)；
4) parking path is planned according to the coordinate of the opposite warehouse compartment of parking of vehicle and current pose；
5) according to the first segment of planning park curve whether be able to achieve collisionless storage judge whether to need multistage path planning, if
It is then to perform the next step；Otherwise, it enters step 7)；
6) adjustment of Multiple Sections path is carried out to vehicle；
7) environmental information and car status information are obtained to carry out intensified learning network training, obtains vehicle control instruction；
8) control vehicle storage is instructed according to vehicle control, automatic parking mode is exited in end of parking.
2. a kind of automatic parking method based on geometric programming and intensified learning according to claim 1, which is characterized in that
In step 3), if detecting multiple warehouse compartments, the warehouse compartment nearest apart from vehicle is selected, and judge whether the warehouse compartment complies with standard,
If not meeting, the lower warehouse compartment of reselection is simultaneously judged.
3. a kind of automatic parking method based on geometric programming and intensified learning according to claim 2, which is characterized in that
Judge the whether standard compliant content of warehouse compartment are as follows:
Warehouse compartment regional location and size are obtained, and detects within warehouse compartment region that whether there are obstacles；If warehouse compartment region shape and
Size meets the requirements, and barrier is not present, then it is assumed that the warehouse compartment complies with standard.
4. a kind of automatic parking method based on geometric programming and intensified learning according to claim 1, which is characterized in that
Using multistage R-S curve planing method to progress Multiple Sections path adjustment.
5. a kind of automatic parking method based on geometric programming and intensified learning according to claim 4, which is characterized in that
The specific steps of step 6) include:
61) premised on vehicle rear axle right side is without impinging on warehouse compartment angle point, the starting point of first segment R-S curve is determined；
62) after vehicle being beaten steering wheel to extreme position to the right, move backward afterwards to the right to vehicle left back point on the left of warehouse compartment line or
On its extended line；
63) after vehicle being beaten steering wheel to extreme position to the left, to left front advance to vehicle pose be adjusted to a certain angle or
To at front obstacle safe distance.
6. a kind of automatic parking method based on geometric programming and intensified learning according to claim 1, which is characterized in that
The specific steps of step 7) include:
71) deeply learning network is built, using the status information of the opposite coordinate and vehicle from vehicle of warehouse compartment angle point as inputting,
Using the control of steering wheel angle displacement instruction and throttle, brake pedal control instruction as output, park what process obtained with final stage
Feedback is up to target and is trained；
72) after the completion of training, deeply learning network exports the control instruction of vehicle according to current input.
7. a kind of realize the automatic parking method as claimed in any one of claims 1 to 6 based on geometric programming and intensified learning
Automated parking system, which is characterized in that the system includes:
It parks module, for controlling the slow straight-line travelling of vehicle；
Sensing module, for acquiring ambient image, identification warehouse compartment line, judging vehicle with respect to warehouse compartment posture information and detection obstacle
Object information simultaneously judges whether warehouse compartment is occupied；
Decision-making module judges the validity of warehouse compartment and is presently in for being recorded according to the fuse information and instruction of sensing module
Park the stage, and provide the posture information for planning parking path for planning module；
Planning module, for, with respect to the pose of warehouse compartment, planning the track R-S according to warehouse compartment information and vehicle and sending track scatterplot extremely
According to tracking module；
Track following module, the track scatterplot transmitted for receiving planning module control steering wheel, gear, oil by controller
Door and brake pedal, and then control vehicle tracking planned trajectory；
Intensified learning module, for the status information by warehouse compartment with respect to car's location information and vehicle, outbound course disk turns
Angle control instruction and speed control instruction；
Chassis actuator control module is calculated for the tracking planned trajectory that receiving locus tracking module transmits by controller
Desired control amount or the control instruction for directly receiving intensified learning module, pass through drive-by-wire chassis actuator tracing control amount.
8. automated parking system according to claim 7, which is characterized in that the sensing module includes being set to vehicle body
Front and back side, four cameras of left and right sides and 12 ultrasonic radars being set to around vehicle body, the camera are used for
It acquires ambient image, identification warehouse compartment line and opposite warehouse compartment posture information, the ultrasonic wave thunder is judged using binocular ranging method
Up to for detecting obstacle information, judge whether warehouse compartment is occupied.
9. automated parking system according to claim 7, which is characterized in that the track following module include ECU and
Line traffic control unit.
10. automated parking system according to claim 7, which is characterized in that the control amount includes steering wheel, gear
Position, throttle and brake pedal control amount.
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Cited By (6)
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| CN112078594A (en) * | 2020-08-31 | 2020-12-15 | 纵目科技（上海）股份有限公司 | Curvature continuous parking path planning device and method for intelligent parking system |
| CN112606827A (en) * | 2020-12-09 | 2021-04-06 | 武汉格罗夫氢能汽车有限公司 | Vertical parking device for fuel cell hydrogen energy automobile |
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| CN113200039A (en) * | 2021-06-09 | 2021-08-03 | 广州小鹏智慧充电科技有限公司 | Parking-based road generation method and device, vehicle and readable medium |
| CN115214630A (en) * | 2022-07-25 | 2022-10-21 | 广州汽车集团股份有限公司 | Automatic parking method and system for corner parking spaces and vehicle |
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| CN115214630B (en) * | 2022-07-25 | 2023-10-24 | 广州汽车集团股份有限公司 | Automatic parking method and system for corner parking space and vehicle |
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