CN102951151B - The track of vehicle keeps aid system and method thereof - Google Patents

The track of vehicle keeps aid system and method thereof Download PDF

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Publication number
CN102951151B
CN102951151B CN201210305698.9A CN201210305698A CN102951151B CN 102951151 B CN102951151 B CN 102951151B CN 201210305698 A CN201210305698 A CN 201210305698A CN 102951151 B CN102951151 B CN 102951151B
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curvature
radius
track
vehicle
chassis
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CN102951151A (en
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李俊翰
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Hyundai Mobis Co Ltd
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Hyundai Mobis Co Ltd
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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, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
    • B60W30/10—Path keeping
    • B60W30/12—Lane keeping
    • 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
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
    • B60W40/06—Road conditions
    • B60W40/072—Curvature of the road
    • 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
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
    • B60W40/105—Speed
    • 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
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
    • B60W40/114—Yaw movement
    • 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
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0001—Details of the control system
    • B60W2050/0019—Control system elements or transfer functions
    • B60W2050/0022—Gains, weighting coefficients or weighting functions
    • 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
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0001—Details of the control system
    • B60W2050/0043—Signal treatments, identification of variables or parameters, parameter estimation or state estimation
    • B60W2050/0052—Filtering, filters
    • 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
    • B60W2520/00—Input parameters relating to overall vehicle dynamics
    • B60W2520/10—Longitudinal speed
    • 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
    • B60W2520/00—Input parameters relating to overall vehicle dynamics
    • B60W2520/14—Yaw
    • 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
    • B60W2552/00—Input parameters relating to infrastructure
    • B60W2552/30—Road curve radius
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60Y—INDEXING SCHEME RELATING TO ASPECTS CROSS-CUTTING VEHICLE TECHNOLOGY
    • B60Y2300/00—Purposes or special features of road vehicle drive control systems
    • B60Y2300/10—Path keeping
    • B60Y2300/12—Lane keeping

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  • Engineering & Computer Science (AREA)
  • Automation & Control Theory (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Traffic Control Systems (AREA)
  • Steering Control In Accordance With Driving Conditions (AREA)

Abstract

The present invention is the radius of curvature that the Chassis data i.e. vehicle speed sensor by carriageway image information and vehicle and yaw-rate sensor calculate road, utilize the road curvature radius calculation function merging said two signal application weighted value, it was predicted that the travel track of vehicle.The track of the present invention keeps aid system to be that its composition includes: left side and right side curvature wave filter, utilizes the image information obtained from described image device, obtains the radius of curvature of left-hand lane and right-hand lane；Chassis curvature wave filter, utilizes the yaw velocity obtained from described yaw-rate sensor and vehicle speed sensor and speed to obtain Chassis radius of curvature；Curvature construction of condition and weighted value structural portion, utilize the described left side and right-hand lane radius of curvature and described Chassis radius of curvature obtained from described left side and right side curvature wave filter and described Chassis curvature wave filter, determine curvature condition and weighted value condition value according to Current vehicle operating state, obtain final curvature value.

Description

The track of vehicle keeps aid system and method thereof
Technical field
The track that the present invention relates to vehicle keeps aid system and method thereof, and the most no matter vehicle at transport condition or has Outside hindering factor, the most measurable vehicle travel track and the track not affected by vehicle running state or outside hindering factor are protected Hold aid system and method thereof.
Background technology
Track keeps aid system (LKAS:Lane Keeping Assistance System) to be to utilize camera identification Track the technology of auto-steering, utilize the image procossing of photographic head, the horizontal position of the vehicle on mensuration lane width, track Put the distance between track, both sides and track form, road curvature radius, utilize obtained vehicle location and road information control Vehicle processed.
Korean Patent Publication 2009-0089079, No. 2010-0005362, No. 2010-0000388 and United States Patent (USP) No. 7626533 Deng Doushi tracks keep the conventional art in terms of control.
But described traditional track keeps control technology to be that the radius of curvature of road is with the image information obtained from photographic head Based on, therefore on bend during change lane, be as the criterion with vehicle location, become relative radius of curvature and be change lane implement Cannot be applied to be intended to the Back ground Information of feedback during control.
It is to utilize to obtain from vehicle speed sensor and yaw-rate sensor that other conventional art solves the method for described problem The road curvature radius taken.But the road curvature radius obtained from vehicle speed sensor and yaw-rate sensor is that vehicle travels Under the transport conditions such as tortuous bend, the change of steering angle becomes greatly the most therewith, therefore may not apply to wagon control.
Summary of the invention
Technical task
The present invention is to create under described technical background, its object is to provide one can predict vehicle traveling rail Mark and the track of vehicle not affected by vehicle running state or outside hindering factor keep aid system and method thereof.
Solution
For solving described problem, the technical solution adopted in the present invention is, utilizes carriageway image information and vehicle Chassis Data i.e. vehicle speed sensor and yaw-rate sensor calculate the radius of curvature of road, use and merge the application of said two signal The travel track of the road curvature radius calculation function prediction vehicle of weighted value.
The track holding aid system that one aspect of the present invention relates to is, with vehicle image device and yaw-rate sensor And vehicle speed sensor connects, identify that the track holding aid system (LKAS:Lane of described vehicle auto-steering is implemented in track Keeping Assistance System), its composition includes: left side and right side curvature wave filter, utilizes from described image device The image information obtained, obtains the radius of curvature of left-hand lane and right-hand lane；Chassis curvature wave filter, utilizes from described Yaw velocity and speed that yaw-rate sensor and vehicle speed sensor obtain obtain Chassis radius of curvature；Curvature bar Part is constituted and weighted value constituting portion, utilizes from described left side and right side curvature wave filter and described Chassis curvature wave filter The described left side obtained and right-hand lane radius of curvature and described Chassis radius of curvature, according to Current vehicle operating state Determine curvature condition and weighted value condition value, obtain final curvature value.
Described left side and right side curvature wave filter and described Chassis curvature wave filter are should be by by following [mathematical expression 1] Kalman filter constitute be advisable.
[mathematical expression 1]
P K - = F K - 1 P K - 1 + F K - 1 T + Q K - 1
K K = P K - H K T ( H K P K - H K T + R K ) - 1
P K + = ( 1 - K K H K ) P K - ( 1 - K K H K ) T + K K R K K K T
(P is system covariance, Q and R is process noise covariance respectively and measures noise covariance, and K is to pass through covariance The Kalman gain calculated).
The track that another aspect of the present invention relates to keeps the method predicting vehicle travel track in aid system, and it implements step Suddenly include: utilize the image information obtained from vehicle image device to obtain the radius of curvature of each left-hand lane and right-hand lane；Profit Chassis is obtained bent with the yaw velocity obtained from yaw-rate sensor and the vehicle speed sensor of described vehicle and speed Rate radius；Utilize the described left side obtained from described left side and right side curvature wave filter and described Chassis curvature wave filter and The radius of curvature of right-hand lane and described Chassis radius of curvature, determine curvature condition according to the operating state of Current vehicle With weighted value condition value, then obtain final curvature value.
Set critical asking the step of final curvature value, the difference of the radius of curvature of described left side and right-hand lane to exceed Value, and the difference of the radius of curvature of described left-hand lane and described Chassis radius of curvature and described right-hand lane radius of curvature With when in the difference of described Chassis radius of curvature, wherein some is bigger, from radius of curvature and the described right side of described left-hand lane The value of the bigger side of difference got rid of in the radius of curvature in track, side and obtain final curvature value.If described yaw velocity exceedes Set marginal value, then get rid of described Chassis radius of curvature, only utilizes the curvature half of described left-hand lane and right-hand lane Footpath, obtains final curvature value.
Beneficial effect
According to the present invention it is possible to utilize the image information in track and the vehicle i.e. vehicle speed sensor of Chassis Data and yaw Angular-rate sensor, calculates road curvature radius, and utilizes the road curvature radius merging said two signal application weighted value Calculate function, it was predicted that vehicle travel track and not by the special transport condition of vehicle and track misrecognition/unidentified wait outside hinder Hinder the impact of factor.
Specifically, be likely to occur when utilizing the lane curvature radius information control vehicle by image device cannot The situation controlled i.e. misidentifies/situation in unidentified track under can also implement to control.
The shape that the road curvature radius data being likely to occur when steering angle Rapid Variable Design such as tortuous negotiation of bends is beated Can also implement under state to control.
Moreover, the radius of curvature in track can also be stably provided when vehicle changes track on bend.
Another effect of the present invention is exactly failure safe function.It is exactly repeatedly to confirm image device and vehicle sensors portion, Even if breaking down in side, it is also possible in time isolated fault and all-the-time stable controls vehicle.
Accompanying drawing explanation
Fig. 1 is that the track of the vehicle of the embodiment of the present invention keeps the sensor used in aid system fusion curvature compensation to patrol Collect structure chart.
Fig. 2 is that the track of the vehicle of the embodiment of the present invention keeps aid system curvature construction of condition and weighted value block structure Middle according to Current vehicle operating state decision curvature condition and the process flow diagram flow chart of weighted value condition value.
Detailed description of the invention
For making the purpose of the embodiment of the present invention, technical scheme and advantage clearer, below in conjunction with the embodiment of the present invention In accompanying drawing, the technical scheme in the embodiment of the present invention is clearly and completely described, it is clear that described embodiment is The a part of embodiment of the present invention rather than whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art The every other embodiment obtained under not making creative work premise, broadly falls into the scope of protection of the invention.This The term of bright middle use, only in order to embodiment to be described, is not to limit the invention.Singulative in this specification, On the premise of sentence does not has special suggestion, also comprise plural form.In description use " including (comprises) " or " (comprising) that include " be not excluded for beyond involved component, step, action and/or element more than one its The existence of its component, step, action and/or element or supplement.
Below in conjunction with the accompanying drawings, the track to the vehicle of the embodiment of the present invention keeps aid system and method thereof to retouch in detail State.
Fig. 1 is that the track of the vehicle of the embodiment of the present invention keeps the sensor used in aid system fusion curvature compensation to patrol Collect structure chart.
As it is shown in figure 1, the track of the vehicle of the embodiment of the present invention keeps in aid system, to from the image device of vehicle On the left of the image information application that 110 obtain, curvature wave filter 140 and right side curvature wave filter 150 obtain left-hand lane and right side car Radius of curvature (the ρ in roadLFT, ρRGT), to the vehicle Chassis obtained from yaw-rate sensor 120 and vehicle speed sensor 130 Data i.e. yaw velocityChassis radius of curvature is obtained with speed (V) application Chassis curvature wave filter 160 (ρChassis).Then curvature bar is determined in curvature structure condition and weighted value block structure 170 according to the operating state of Current vehicle Part and weighted value condition, it is thus achieved that final curvature value (ρmaster)
The card of application on left side curvature wave filter 140, right side curvature wave filter 150 and Chassis curvature wave filter 160 The formula of Thalmann filter is shown in following [mathematical expression 1].
[mathematical expression 1]
P K - = F K - 1 P K - 1 + F K - 1 T + Q K - 1
K K = P K - H K T ( H K P K - H K T + R K ) - 1
P K + = ( 1 - K K H K ) P K - ( 1 - K K H K ) T + K K R K K K T .
Here P is system covariance, Q and R is process noise covariance respectively and measures noise covariance, and K is to utilize The Kalman gain that covariance calculates.
At curvature construction of condition and weighted value block structure 170, as in figure 2 it is shown, determine according to the operating state of Current vehicle Curvature condition and weighted value condition value.Fig. 2 is that the track of the vehicle of the embodiment of the present invention keeps aid system curvature construction of condition And weighted value block structure 170 determines curvature condition and the process flow of weighted value condition value according to Current vehicle operating state Figure.
Below in conjunction with the accompanying drawings 2, to determining that with vehicle operating state the method for curvature is described in detail.
First, illustrate as a example by change track when negotiation of bends.
The curvature value of the left-hand lane that track then receives and the song of right-hand lane is changed from image device when negotiation of bends Rate value is different and meets condition ρcm＞ ρth().And with condition ρLC＞ ρRCThe comparison of (), φ (φ1Or φ2) can be closed.
The value obtained by remaining wave filter according to condition is utilized to obtain ρmaster。
Then, illustrate as a example by tortuous negotiation of bends.
When tortuous negotiation of bends, yaw velocity can exceed marginal value (), therefore in Chassis curvature wave filter φ3Can be closed.
φ3Be closed, then γ becomes 0, the most only trusts by left side curvature wave filter 140 and right side curvature wave filter 150 obtain values and obtain ρmaster。
Illustrate as a example by the unidentified/misrecognition of image device below.
Image device is unidentified/misrecognition track, side time, from left-hand lane curvature value and the right side of image device input The curvature value in track is different, meets condition ρ therewithcm＞ ρth().And along with condition ρLC＞ ρRCThe comparison of (), left side or the right side The φ of side curvature wave filter (140,150) is closed.
ρ is obtained therewith only trusting the value obtained according to condition by remaining wave filter in addition to φmaster。
According to the present invention, by the image information in track and the Chassis data i.e. vehicle speed sensor of vehicle and yaw angle Velocity sensor calculates the radius of curvature of road, utilizes the road curvature radius calculation merging said two signal application weighted value Function, it was predicted that the travel track of vehicle and not by the special transport condition of vehicle and misrecognition/unidentified track etc. outside hinder because of The impact of element.
Specifically, be likely to occur when utilizing the lane curvature radius information control vehicle by image device cannot Controlled state is the most unidentified/situation in misrecognition track under can also implement to control.
And the road curvature radius data being likely to occur when steering angle Rapid Variable Design such as tortuous negotiation of bends is jumped Can also implement under dynamic situation to control.
Moreover, the radius of curvature in track can also be stably provided when vehicle changes track on bend.
Another effect of the present invention is exactly fail safe function, it is simply that to image device and vehicle sensors portion the most repeatedly Confirm, though side section failure, it is also possible in time isolated fault and all-the-time stable realizes the control to vehicle.
Above example and particular terms only in order to technical scheme to be described, are not intended to limit；Although reference The present invention has been described in detail by previous embodiment, it will be understood by those within the art that: it still can be right Technical scheme described in foregoing embodiments is modified, or wherein portion of techniques feature is carried out equivalent；And these Amendment or replacement, do not make the essence of appropriate technical solution depart from the scope of technical scheme described in various embodiments of the present invention.

Claims (4)

1. a track keeps aid system, it is characterised in that with vehicle image device and yaw-rate sensor and car Speed sensor connects, and identifies that the track holding aid system of described vehicle auto-steering is implemented in track, and its composition includes:
Left side and right side curvature wave filter, utilize the image information obtained from described image device, obtain left-hand lane and right side The radius of curvature in track；
Chassis curvature wave filter, utilizes the yaw velocity obtained from described yaw-rate sensor and vehicle speed sensor Chassis radius of curvature is obtained with speed；
Curvature condition is constituted and weighted value constituting portion, utilizes from described left side and right side curvature wave filter and described Chassis Described left side that curvature wave filter obtains and right-hand lane radius of curvature and described Chassis radius of curvature, according to current vehicle Operating state determines curvature condition and weighted value condition value, obtains final curvature value；
Described left side and right side curvature wave filter and described Chassis curvature wave filter are by the card according to following [mathematical expression 1] Thalmann filter is constituted,
[mathematical expression 1]
P is system covariance, Q and R is process noise covariance respectively and measures noise covariance, and K is to be calculated by covariance Kalman gain.
2. the method predicting vehicle travel track during track keeps aid system, implementation step includes:
The image information obtained from vehicle image device is utilized to obtain the radius of curvature of each left-hand lane and right-hand lane；
Yaw velocity and speed that utilization obtains from yaw-rate sensor and the vehicle speed sensor of described vehicle are obtained Chassis radius of curvature；
Utilize the described left side and right side obtained from described left side and right side curvature wave filter and described Chassis curvature wave filter The radius of curvature in track and described Chassis radius of curvature, determine curvature condition according to the operating state of Current vehicle and add Weights condition value, then obtains final curvature value；
Described left side and the radius of curvature of right-hand lane and described Chassis radius of curvature are only applied following according to [mathematical expression 1] Kalman filter calculate,
[mathematical expression 1]
P is system covariance, Q and R is process noise covariance respectively and measures noise covariance, and K is to utilize covariance to calculate Kalman gain.
The method that track the most according to claim 2 keeps predicting vehicle travel track in aid system, it is characterised in that
Obtaining the step of final curvature value, the difference of the radius of curvature of described left side and right-hand lane exceedes set marginal value, And the described radius of curvature of left-hand lane and the difference of described Chassis radius of curvature and described right-hand lane radius of curvature and institute When stating that in the difference of Chassis radius of curvature, wherein some is bigger, from radius of curvature and the described right side car of described left-hand lane The value of the bigger side of difference got rid of in the radius of curvature in road and obtain final curvature value.
The method that track the most according to claim 2 keeps predicting vehicle travel track in aid system, it is characterised in that
In the described step obtaining final curvature value, if described yaw velocity exceedes set marginal value, then get rid of described Chassis radius of curvature, only utilizes the radius of curvature of described left-hand lane and right-hand lane, obtains final curvature value.
CN201210305698.9A 2011-08-24 2012-08-24 The track of vehicle keeps aid system and method thereof Active CN102951151B (en)

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KR1020110084606A KR101818539B1 (en) 2011-08-24 2011-08-24 Lane Keeping Assistance System of vehicle and method thereof

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CN103693042A (en) * 2013-12-03 2014-04-02 重庆交通大学 Method for forecasting automobile running speed on mountain complicated road based on foresight track curvature
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CN106080596B (en) * 2016-06-03 2018-06-12 中国人民解放军海军大连舰艇学院 A kind of lane line sliding formwork keeping method based on position and angular velocity measurement
CN106515740B (en) * 2016-11-14 2018-10-09 江苏大学 Distributed electrical based on ICDKF drives vehicle driving state parameter estimation algorithm
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KR102375149B1 (en) * 2017-10-18 2022-03-16 현대자동차주식회사 Apparatus and method for estimating redius of curvature of vehicle
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