CN109532824A - A kind of curb recognition methods that level is parked - Google Patents
A kind of curb recognition methods that level is parked Download PDFInfo
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- CN109532824A CN109532824A CN201811554082.9A CN201811554082A CN109532824A CN 109532824 A CN109532824 A CN 109532824A CN 201811554082 A CN201811554082 A CN 201811554082A CN 109532824 A CN109532824 A CN 109532824A
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- 238000000034 method Methods 0.000 title claims abstract description 40
- 230000008569 process Effects 0.000 claims abstract description 13
- 238000012216 screening Methods 0.000 claims description 4
- 238000001914 filtration Methods 0.000 claims 1
- 230000004888 barrier function Effects 0.000 abstract description 8
- 230000035772 mutation Effects 0.000 description 6
- 238000004891 communication Methods 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 3
- 238000012360 testing method Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 238000013480 data collection Methods 0.000 description 1
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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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- 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
- B60W2554/00—Input parameters relating to objects
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- Engineering & Computer Science (AREA)
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Abstract
The invention discloses a kind of curb recognition methods that level is parked, include the following steps: step S1, side, which is parked, to be looked for during parking stall, the variation of position in the variation and vehicle driving process that detect obstacle distance is reached according to body side Fanglei, behind the edge of parking stall two sides vehicle, body side Fanglei is switched to long range operating mode up to initial short distance operating mode;Step S2, by body side Fanglei up under long range operating mode data and truck position information record;Step S3 is filtered the radar data recorded after finding parking stall, and the positional information calculation of vehicle is combined to obtain distance of the curb apart from vehicle.The present invention can more accurately identify such as curb of barrier remotely.
Description
Technical field
The present invention relates to intelligent driving technical fields, and in particular to intelligent parking technology.
Background technique
As continuous improvement of people's living standards and automobile industry constantly flourish, automobile quantity increases year by year therewith
Add, and highway, street and parking lot seem more crowded narrow, because dispute caused by vehicle parking also increases year by year.When parking
Driver only relies on rearview mirror and glass for vehicle window observes surrounding vehicles environment, and the visual field can not be controlled it by larger limitation simultaneously
The situation of rear of vehicle and the situation for taking into account surrounding vehicles, are easy to produce unsafe factor, and park largely according to
Rely the driving experience and skill in driver, if experience is inadequate with skill, and encounters more narrow parking stall, parks difficulty just
It can greatly increase, therefore just have parking assisting system.
As parking assisting system is constantly towards intelligence, humanized requirement is strided forward, and automated parking system comes into being.
The purpose of exploitation automated parking system is to free driver from complicated parking manoeuvres, improves the comfortable of driving
Property, alleviate tensity of driver when parking, prevention is parked the generation of accident.Automated parking system includes environmental data collecting
System (ultrasonic radar system, the acquisition of vehicle CAN signal), vehicle-mounted ECU (carries out data processing, path planning and control command
Output), the vehicle parking operating system EPS of active control (can), system structure composition is as shown below:
Automatic parking, which is divided into side, parks and parks with vertical.It parks for side, since side parking position is greatly all in road
On roadside, when sometimes parking stall is narrow, the technology of driver can be tested very much, encounter problems can not be in a short time when parking
When completion, a lane long period, very disruptive traffic order can be usually blocked.Simultaneously because driver's seat is limited, also
The vehicle etc. crossed on fore-aft vehicle and road is taken into account, knocks curb after often ignoring roadside curb.Automatic parking technology can
With by automobile parking, in lesser parking stall, and whole process time-consuming is shorter, driver only should be noted ambient enviroment and time control
System brake, which can be completed, parks;It can also be when looking for parking stall by being mounted on the ultrasonic wave thunder of vehicle body side for the curb in roadside
It is identified up to probe, judges its distance apart from vehicle body, so that in parking process be avoided to knock curb.
In terms of identifying curb, since curb is usually shorter, and separating test vehicle is farther out, measures during looking for parking stall
Curb signal can be fainter, it is not easy to accurate measurement.
Summary of the invention
The technical problem to be solved by the invention is to provide a kind of curb recognition methods that level is parked, and improve curb and know
Other accuracy.
In order to solve the above technical problems, the present invention adopts the following technical scheme: a kind of curb recognition methods that level is parked,
Include the following steps:
Step S1, side, which is parked, to be looked for during parking stall, reached according to body side Fanglei detect the variation of obstacle distance with
And body side Fanglei is reached initial short distance behind the edge of parking stall two sides vehicle by the variation of position in vehicle driving process
Operating mode is switched to long range operating mode;
Step S2, by body side Fanglei up under long range operating mode data and truck position information record;
Step S3 is filtered the radar data recorded after finding parking stall, and the position of vehicle is combined to believe
Distance of the curb apart from vehicle is calculated in breath.
Optionally, in parking process establishes virtual coordinate system Oxy using the starting point for beginning of parking as virtual coordinates origin,
The distance value that this vehicle is passed by is acquired in real time, which is corresponded into the x value in virtual coordinate system, is recorded as X[0, N], while it is real
When collect and record this vehicle side radar data Radar[0, N];It is corresponded with x value.
Optionally, screening radar data will be in parking stall to the radar data progress median filter process of record for the first time
Between radar data in the individual data point that occurs being mutated filter, filter out wherein effective data point.
Optionally, programmed screening is carried out to the data point filtered out for the first time, according to existing obstacle vehicle, setting is minimum
Range data point and maximum distance data point delete the data point less than minimum range data point or are greater than maximum distance data
The data point of point, will finally obtain valid data point set RadarEffect[0, n]And X_Effect[0, n]For calculating curb position
It sets.
Optionally, to effective radar data RadarEffect[0, n], the is carried out by bubble sort method according to apart from size
One minor sort, when sequence, can be by corresponding X_Effect[0, n]It sorts together.
Optionally, radar data of being subject to sorts, and x value follows corresponding radar data.
Optionally, the data of drained sequence are further processed after the first minor sort, calculate this partial data
The difference of distance by radar between middle consecutive number strong point, record distance by radar difference less than 10cm data point distance by radar with
X value, and meet the number of the data point of this condition, when there is 10 or more the data points for meeting condition, then it is assumed that the data
Collection can be used for calculating curb, be calculated as RadarFinal[0, k]And X_Final[0, k];New data are continually looked for if being unsatisfactory for.
Optionally, by RadarFinal[0, k]And X_Final[0, k]Second on the basis of x value with the progress of bubble sort method
Sequence, distance by radar value follow corresponding x value.
Optionally, after the second minor sort, X_Final is calculated[0, k]Difference DELTA x between middle maxima and minima, if
Δ x > 240, then it is assumed that this group of data are effective;Otherwise then think data invalid, terminate to calculate.
Optionally, when data think effective, X_Final is calculated[0, k]The difference of x and Δ is recorded as between adjacent data
X[0, k-1]If Δ X[0, k-1]In difference between maximum two data less than 200, then it is assumed that X_Final[0, k]Data are effective,
It is on the contrary then invalid, terminate to calculate curb position, if X_Final[0, k]Data are effective, then according to RadarFinal[0, k]In radar
Data calculate distance of the curb apart from vehicle body.
Optionally, it is contemplated that this vehicle not necessarily with the angle of parallel curb it is straight move forward, therefore, it is necessary to calculate
Curb with respect to vehicle body angle, according to being determined as effective RadarFinal[0, k]With X_Final[0, k]Data, with minimum two
The mode of multiplication fitting a straight line goes the angle that curb is calculated with respect to this vehicle.
Optionally, it is assumed that fitting a straight line y=ax+b then has following formula according to least square method:
By X_Final[0, k]With RadarFinal[0, k]X therein is substituted into respectivelyiAnd yi, a and b is calculated, according to slope
The angle of the opposite x-axis of the curb in virtual coordinate system can be calculated in a, and pick-up position intermediate point substitutes into formula y=ax as x value
+ b, the y acquired is as curb at a distance from this workshop.
Optionally, body side Fanglei reaches under long range operating mode, by enhancing the hair intensity of wave of ultrasonic radar, adjusts
The yield value to back echo signal is turned up in criterion of the height to barrier in 2m;Under short distance operating mode, reduce
Radar sends out intensity of wave, restores barrier criterion in 2m, reduces the yield value to back echo signal.
Optionally, it looks for during parking stall, is short distance operating mode when radar is initial, when the distance that radar measures is dashed forward
After becoming and maintaining the distance after mutation, radar is switched to long range operating mode from short distance operating mode;When radar again
After detecting mutation and maintaining the distance after mutation, radar is switched to short distance operating mode from long range operating mode.
The present invention carries out integrated treatment to the range information of vehicle position information and radar, according to radar detection to barrier
The variation of position carrys out the operating mode of switching tests vehicle side radar in the variation and instruction carriage driving process of distance, thus,
When the radar of instruction carriage side is behind the edge of parking stall two sides vehicle, the operating mode of radar is switched to works over long distances at this time
Mode can more accurately identify barrier (curb) remotely.
The specific technical solution of the present invention and its advantages will in the following detailed description in conjunction with attached drawing into
Row detailed description.
Detailed description of the invention
Present invention will be further described below with reference to the accompanying drawings and specific embodiments:
Fig. 1 is flow chart of the present invention;
Fig. 2 is virtual coordinate system schematic diagram of parking;
Fig. 3 is that radar mode switches schematic diagram.
Specific embodiment
Refering to what is shown in Fig. 1, a kind of curb recognition methods that level is parked, includes the following steps:
Step S1, side, which is parked, to be looked for during parking stall, reached according to body side Fanglei detect the variation of obstacle distance with
And body side Fanglei is reached initial short distance behind the edge of parking stall two sides vehicle by the variation of position in vehicle driving process
Operating mode is switched to long range operating mode;
Step S2, by body side Fanglei up under long range operating mode data and truck position information record;
Step S3 is filtered the radar data recorded after finding parking stall, and the position of vehicle is combined to believe
Distance of the curb apart from vehicle is calculated in breath.
As shown in figure 3, radar operation mode is divided into long range operating mode and short distance operating mode.It works in long range
Under mode, enhance the hair intensity of wave of ultrasonic radar by software, the criterion to barrier in 2m is turned up, is turned up to obstacle
The yield value of object echo-signal enables radar preferably to measure the barrier of distant place;Under short distance operating mode, radar is reduced
Intensity of wave is sent out, barrier criterion in 2m is restored, the yield value to back echo signal is reduced, avoids detecting in 2m
Information of road surface and noise signal.
Radar operation mode switching has the case where vehicle mainly for parking stall two sides, looks for during parking stall, is when radar is initial
Short distance operating mode, after the distance for being mutated and maintaining after mutation occurs in the distance that radar measures, the ECU that parks passes through LIN
Communication Control headstock side radar is switched to long range operating mode from short distance operating mode;When radar detects mutation again
And after maintaining the distance after mutation, the ECU that parks passes through LIN Communication Control headstock side radar again and switches from long range operating mode
To short distance operating mode.
As shown in Fig. 2, in parking process establishes virtual coordinate system using the starting point for beginning of parking as virtual coordinates origin
Oxy。
It acquires the distance that instruction carriage is passed by real time by CAN communication, is corresponded to the x value in virtual coordinate system, remember
Record is X[0, N], the ultrasonic radar data in instruction carriage headstock side are collected and recorded by LIN communication in real time
Radar[0, N];It is corresponded with x value.Median filter process is carried out to the radar data of record, by the radar number among parking stall
It is filtered according to the middle individual data point for occurring being mutated, filters out wherein effective data point.
It parks to look for during parking stall due to side and the lateral distance of parking stall two sides obstacle vehicle and instruction carriage is limited
(0.5~2m), the vehicle width of default two sides obstacle vehicle are 1.8m, and obstacle vehicle can keep a safe distance (to be set as curb
0.2m), curb will not be close to, therefore the data point that back filters out is screened again, delete less than 2.5m or
Data point greater than 4m;(being greater than 10 data points) if more less than the number of data points of 2.5m, directly by this curb meter
Calculation is set in vain.This part valid data point set RadarEffect that will finally obtain[0, n]And X_Effect[0, n]Output is used
In calculating curb position.
To the effective radar data RadarEffect exported in radar data processing module[0, n], pass through according to apart from size
Bubble sort method is ranked up, and when sequence can be by corresponding X_Effect[0, n](radar data of being subject to sorts, x value for sequence together
Follow corresponding radar data), the data of drained sequence are further processed after sequence, are calculated in this partial data
The difference of distance by radar between consecutive number strong point records the distance by radar and x of data point of the distance by radar difference less than 10cm
Value, and meets the number of the data point of this condition, when there is 10 or more the data points for meeting condition, then it is assumed that the data set
It can be used for calculating curb, be calculated as RadarFinal[0, k]And X_Final[0, k];New data are continually looked for if being unsatisfactory for.
By RadarFinal[0, k]And X_Final[0, k]It is ranked up again with bubble sort method on the basis of x value, thunder
Corresponding x value is followed up to distance value.After sequence, X_Final is calculated[0, k]Difference DELTA x between middle maxima and minima, if
Δ x > 240, then it is assumed that this group of data are effective;Otherwise then think data invalid, terminate to calculate.When data are effective, X_ is calculated
Final[0, k]The difference of x and Δ X is recorded as between adjacent data[0, k-1]If Δ X[0, k-1]In between maximum two data
Difference is less than 200, then it is assumed that X_Final[0, k]Data are effective, on the contrary then invalid, terminate to calculate curb position.If X_
Final[0, k]Data are effective, then according to RadarFinal[0, k]In radar data calculate distance of the curb apart from vehicle body.If X_
Final[0, k]Data are effective, then by RadarFinal[0, k]In radar data and X_Final[0, k]In x value in next step
Calculate distance of the curb apart from vehicle body.
In addition, it is contemplated that instruction carriage not necessarily with the angle of parallel curb it is straight move forward, therefore, it is necessary to calculate
Curb with respect to vehicle body angle, convenient for keeping instruction carriage parallel with curb when parking and terminating.It is determined as effectively according to back
RadarFinal[0, k]With X_Final[0, k]Data, go curb is calculated in a manner of least square method fitting a straight line opposite
The angle of instruction carriage.
Assuming that fitting a straight line is y=ax+b, then there is following formula according to least square method:
By X_Final[0, k]With RadarFinal[0, k]X therein is substituted into respectivelyiAnd yi, a and b is calculated.According to slope
Angle [alpha]=arctan (a) of the opposite x-axis of the curb in virtual coordinate system can be calculated in a, and pick-up position intermediate point is as x value
Formula y=ax+b is substituted into, the y acquired is as curb at a distance from test(ing) plant.
The above description is merely a specific embodiment, but scope of protection of the present invention is not limited thereto, is familiar with
The those skilled in the art should be understood that the present invention includes but is not limited to content described in specific embodiment above.It is any
Modification without departing from function and structure principle of the invention is intended to be included in the range of claims.
Claims (10)
1. a kind of curb recognition methods that level is parked, it is characterised in that include the following steps:
Step S1, side, which is parked, to be looked for during parking stall, and variation and the vehicle for detecting obstacle distance are reached according to body side Fanglei
The variation of position in driving process works body side Fanglei up to initial short distance behind the edge of parking stall two sides vehicle
Pattern switching is to long range operating mode;
Step S2, by body side Fanglei up under long range operating mode data and truck position information record;
Step S3 is filtered the radar data recorded after finding parking stall, and combines the location information meter of vehicle
Calculation obtains distance of the curb apart from vehicle.
2. the curb recognition methods that a kind of level according to claim 1 is parked, it is characterised in that: in parking process,
Using the starting point for beginning of parking as virtual coordinates origin, virtual coordinate system oxy is established, acquires the distance value that this vehicle is passed by real time, it will
The distance value corresponds to the x value in virtual coordinate system, is recorded as x[0, N], while this vehicle side radar data is collected and recorded in real time
Radar[0, N];It is corresponded with x value.
3. the curb recognition methods that a kind of level according to claim 2 is parked, it is characterised in that: screening radar for the first time
Data carry out median filter process to the radar data of record, single by occur being mutated in the radar data among parking stall
Data point filters, and filters out wherein effective data point.
4. the curb recognition methods that a kind of level according to claim 3 is parked, it is characterised in that: to filtering out for the first time
Data point carry out programmed screening, according to existing obstacle vehicle, set minimum range data point and maximum distance data point, delete
Fall to be less than the data point of minimum range data point or the data point greater than maximum distance data point, will finally obtain valid data
Point set RadarEffect[0, n]And X_Effect[0, n]For calculating curb position.
5. the curb recognition methods that a kind of level according to claim 4 is parked, it is characterised in that: to effective radar data
RadarEffect[0, n], the first minor sort is carried out by bubble sort method according to apart from size, when sequence can be by corresponding X_
Effect[0, n]It sorts together.
6. the curb recognition methods that a kind of level according to claim 5 is parked, it is characterised in that: the first minor sort terminates
The data of drained sequence are further processed afterwards, calculate the difference of distance by radar between consecutive number strong point in this partial data
Value, records the distance by radar and x value of data point of the distance by radar difference less than 10cm, and meets the data point of this condition
Number, when there is 10 or more the data points for meeting condition, then it is assumed that the data set can be used for calculating curb, be calculated as
RadarFinal[0, k]And X_Final[0, k];New data are continually looked for if being unsatisfactory for.
7. the curb recognition methods that a kind of level according to claim 6 is parked, it is characterised in that: will
RadarFinal[0, k]And X_Final[0, k]On the basis of x value second is ranked up with bubble sort method, distance by radar value with
With corresponding x value.
8. the curb recognition methods that a kind of level according to claim 7 is parked, it is characterised in that: the second minor sort terminates
Afterwards, X_Final is calculated[0, k]Difference DELTA x between middle maxima and minima, if Δ x > 240, then it is assumed that this group of data are effective;It is no
Then think data invalid, terminates to calculate.
9. the curb recognition methods that a kind of level according to claim 8 is parked, it is characterised in that: when data think effective
When, calculate X_Final[0, k]The difference of x and Δ X is recorded as between adjacent data[0, k-1]If Δ X[0, k-1]In maximum two number
Difference between is less than 200, then it is assumed that X_Final[0, k]Data are effective, on the contrary then invalid, terminate to calculate curb position, if X_
Final[0, k]Data are effective, then according to RadarFinal[0, k]In radar data calculate distance of the curb apart from vehicle body.
10. a kind of curb recognition methods that level is parked according to claim 8 or 9, it is characterised in that: in view of this
Vehicle not necessarily with the angle of parallel curb it is straight move forward, therefore, it is necessary to calculate angle of the curb with respect to vehicle body, according to
It is determined as effective RadarFinal[0, k]With X_Final[0, k]Data, go to calculate in a manner of least square method fitting a straight line
Obtain angle of the curb with respect to this vehicle.
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