CN102951151A - Lane maintaining auxiliary system for vehicles and method thereof - Google Patents

Lane maintaining auxiliary system for vehicles and method thereof Download PDF

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Publication number
CN102951151A
CN102951151A CN2012103056989A CN201210305698A CN102951151A CN 102951151 A CN102951151 A CN 102951151A CN 2012103056989 A CN2012103056989 A CN 2012103056989A CN 201210305698 A CN201210305698 A CN 201210305698A CN 102951151 A CN102951151 A CN 102951151A
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curvature
radius
lane
vehicle
chassis
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CN102951151B (en
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李俊翰
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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

Abstract

The utility model discloses a lane maintaining auxiliary system which utilizes the lane image information and the chassis data (vehicle speed sensor and the yaw velocity sensor) to calculate the curvature radius of the path and predicts the advancing track of the vehicle by utilizing the path curvature radius calculation function that integrates the two mentioned signal application weighted values. The lane maintaining auxiliary system of the utility model comprises a left-and-right side curvature filter which utilizes the image information obtained from an image apparatus to figure out the curvature radius of the left side lane and the right side lane, a Chassis curvature filter which figures out the chassis curvature radius by utilizing the yaw velocity and the vehicle velocity obtained from the yaw velocity sensor and the vehicle speed sensor, and a curvature condition structure and weighted value structural portion used for figuring out the final curvature value by utilizing the left side and right side lane curvature radius and the chassis curvature radius obtained from the left-and-right side curvature filter and the chassis curvature filter and determining the curvature condition and weighted value conditional value based on the current moving state of the vehicles.

Description

Lane keeping ancillary system and the method thereof of vehicle
Technical field
The present invention relates to lane keeping ancillary system and the method thereof of vehicle, specifically no matter vehicle at motoring condition or outside hindering factor is arranged, measurable vehicle travel tracks and be not subjected to vehicle running state or lane keeping ancillary system and method thereof that outside hindering factor affects all.
Background technology
Lane keeping ancillary system (LKAS:Lane Keeping Assistance System) is to utilize the technology of camera identification track and auto-steering, utilize the image of camera to process, measure the vehicle on lane width, the track the horizontal position, with the track, both sides between distance and track form, road curvature radius, utilize institute's vehicle location that obtains and road information to control vehicle.
No. 7626533, open 2009-0089079 number of Korean Patent, 2010-0005362 number, 2010-0000388 number and US Patent etc. all are the conventional arts of lane keeping control aspect.
But the radius of curvature that described traditional lane keeping control technology is road is take the graphicinformation obtained from camera as the basis, therefore on bend during change lane, be as the criterion with vehicle location, become relative radius of curvature and be that change lane can't be applied with the Back ground Information that is intended to feed back when implementing control.
The method that other conventional art solves described problem is to utilize the road curvature radius that obtains from car speed sensor and yaw-rate sensor.But be that it is large that the variation of deflection angle also becomes thereupon, therefore can not be applied to vehicle control under the motoring condition such as the tortuous bend of Vehicle Driving Cycle from the road curvature radius that car speed sensor and yaw-rate sensor are obtained.
Summary of the invention
Technical task
The present invention creates under described technical background, and its purpose is to provide a kind of and can predicts the vehicle travel track and not be subjected to vehicle running state or lane keeping ancillary system and the method thereof of the vehicle that outside hindering factor affects.
Solution
For solving described problem, the technical solution adopted in the present invention is, utilizing carriageway image information and vehicle Chassis data is the radius of curvature that car speed sensor and yaw-rate sensor are calculated road, uses the travel track of the road curvature radius calculation function prediction vehicle that merges described two signal application weighted values.
The lane keeping ancillary system that one aspect of the present invention relates to is, being connected car speed sensor with yaw-rate sensor with the vehicle image device is connected, the lane keeping ancillary system (LKAS:Lane Keeping Assistance System) of described vehicle auto-steering is implemented in the identification track, its composition comprises: left side and right side curvature filter, utilization is obtained the radius of curvature of left-hand lane and right-hand lane from the graphicinformation that described image device obtains; Chassis curvature filter utilizes from yaw velocity and the speed of a motor vehicle of described yaw-rate sensor and car speed sensor acquisition and obtains the Chassis radius of curvature; The curvature condition consists of and weighted value formation section, utilization is from described left side and right-hand lane radius of curvature and the described Chassis radius of curvature of described left side and right side curvature filter and the acquisition of described Chassis curvature filter, according to determining curvature condition and weighted value condition value when the vehicle in front operating state, obtain final curvature value.
Described left side and right side curvature filter and described Chassis curvature filter are to constitute suitable by the Kalman filter by 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
Figure BDA00002053968100023
Figure BDA00002053968100024
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's covariance, and Q and R are respectively process noise covariance and measurement noise covariance, and K is the kalman gain that calculates by covariance).
The method of prediction vehicle travel track in the lane keeping ancillary system that the present invention relates on the other hand, implementation step comprises: utilize the radius of curvature of obtaining each left-hand lane and right-hand lane from the graphicinformation of vehicle image device acquisition; Utilization is obtained the Chassis radius of curvature from the yaw-rate sensor of described vehicle and yaw velocity and the speed of a motor vehicle of car speed sensor acquisition; Utilization is from described left side and right side curvature filter and the described left side of described Chassis curvature filter acquisition and radius of curvature and the described Chassis radius of curvature of right-hand lane, determine curvature condition and weighted value condition value according to the operating state when vehicle in front, then obtain final curvature value.
Asking the step of final curvature value, the difference of the radius of curvature of described left side and right-hand lane surpasses set critical value, and wherein some when larger in the difference of 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 and described Chassis radius of curvature, the larger side's of difference who from the radius of curvature of the radius of curvature of described left-hand lane and described right-hand lane, gets rid of value and obtain final curvature value.If described yaw velocity surpasses set critical value, then get rid of described Chassis radius of curvature, only utilize the radius of curvature of described left-hand lane and right-hand lane, obtain final curvature value.
Beneficial effect
According to the present invention, can utilize graphicinformation and the vehicle Chassis Data in track is car speed sensor and yaw-rate sensor, calculate the road curvature radius, and utilize to merge the road curvature radius calculation function of described two signal application weighted values, the impact of the outside hindering factors such as prediction vehicle travel track and be not subjected to the special motoring condition of vehicle and track mistake identification/unidentified.
The uncontrollable situation that might occur when specifically, utilizing track radius of curvature information control vehicle by image device also can be implemented to control under the situation in identification/unidentified track by mistake.
Also can implement control under the state that the road curvature radius data that might occur is beated when the deflection angles such as tortuous negotiation of bends change fast.
Moreover, vehicle also can be stablized the radius of curvature that the track is provided when bend changes the track.
Another effect of the present invention is exactly the fail safe function.Be exactly repeatedly to confirm image device and vehicle sensors section, even a side et out of order, also in time isolated fault and all-the-time stable control vehicle.
Description of drawings
Fig. 1 is the sensor fusion curvature compensation building-block of logic that uses in the lane keeping ancillary system of vehicle of the embodiment of the invention.
Fig. 2 is according to the process flow diagram flow chart that determines curvature condition and weighted value condition value when the vehicle in front operating state in the lane keeping ancillary system curvature construction of condition of vehicle of the embodiment of the invention and the weighted value block structure.
The specific embodiment
For the purpose, technical scheme and the advantage that make the embodiment of the invention clearer, below in conjunction with the accompanying drawing in the embodiment of the invention, technical scheme in the embodiment of the invention is clearly and completely described, obviously, described embodiment is the present invention's part embodiment, rather than whole embodiment.Based on the embodiment among the present invention, those of ordinary skills belong to the scope of protection of the invention not making the every other embodiment that obtains under the creative work prerequisite.The term that uses among the present invention in order to embodiment to be described, is not to limit the invention only.Singulative in this specification sheets does not have to comprise plural form under the prerequisite of special suggestion in sentence yet." the comprising (comprises) " of using in the specification sheets or " (comprising) that comprise " do not get rid of the existence of more than one other member, step, action and/or element beyond related member, step, action and/or the element or replenish.
Below in conjunction with accompanying drawing, lane keeping ancillary system and the method thereof of the vehicle of the embodiment of the invention is described in detail.
Fig. 1 is the sensor fusion curvature compensation building-block of logic that uses in the lane keeping ancillary system of vehicle of the embodiment of the invention.
As shown in Figure 1, in the lane keeping ancillary system of the vehicle of the embodiment of the invention, the graphicinformation that the image device 110 from vehicle is obtained is used the radius of curvature (ρ that left side curvature filter 140 and right side curvature filter 150 obtain left-hand lane and right-hand lane LFT, ρ RGT), be yaw velocity to the vehicle Chassis data from yaw-rate sensor 120 and car speed sensor 130 acquisitions
Figure BDA00002053968100041
And the speed of a motor vehicle (V) application Chassis curvature filter 160 obtains Chassis radius of curvature (ρ Chassis).Then determine curvature condition and weighted value condition in curvature structure condition and weighted value block structure 170 according to the operating state when vehicle in front, obtain final curvature value (ρ Master)
The formula of the Kalman filter of using on left side curvature filter 140, right side curvature filter 150 and the Chassis curvature filter 160 is seen 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
Figure BDA00002053968100053
Figure BDA00002053968100054
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's covariance, and Q and R are respectively process noise covariance and measurement noise covariance, and K is the kalman gain that utilizes covariance to calculate.
At curvature construction of condition and weighted value block structure 170, as shown in Figure 2, determine curvature condition and weighted value condition value according to the operating state when vehicle in front.Fig. 2 is according to the process flow diagram flow chart that determines curvature condition and weighted value condition value when the vehicle in front operating state in the lane keeping ancillary system curvature construction of condition of vehicle of the embodiment of the invention and the weighted value block structure 170.
Below in conjunction with accompanying drawing 2, to determining that with the vehicle operating state method of curvature is described in detail.
At first, describe as example to change the track when the negotiation of bends.
The curvature value that when negotiation of bends, changes the left-hand lane that the track then receives from image device and satisfy condition ρ different from the curvature value of right-hand lane Cm＞ρ Th().And with condition ρ LC＞ρ RCThe comparison of (), φ (φ 1Or φ 2) can be closed.
Utilization is obtained ρ according to condition by the value that all the other filters obtain Master
Then, describe as an example of tortuous negotiation of bends example.
When tortuous negotiation of bends, yaw velocity can surpass critical value (), so the φ in the Chassis curvature filter 3Can be closed.
φ 3Be closed, then γ becomes 0, only trusts the value that obtains by left side curvature filter 140 and right side curvature filter 150 thereupon and obtains ρ Master
The below with image device unidentified/mistake is identified as example and describes.
Image device is unidentified/and when mistake was identified a sidecar road, different from the curvature value of right-hand lane from the left-hand lane curvature value of image device input, ρ satisfied condition thereupon Cm＞ρ Th().And along with condition ρ LC＞ρ RCThe comparison of (), the φ of left side or right side curvature filter (140,150) is closed.
Only trust according to condition thereupon and obtain ρ by the value that all the other filters except φ obtain Master
According to the present invention, graphicinformation by the track and the Chassis data of vehicle are the radius of curvature that car speed sensor and yaw-rate sensor are calculated road, utilize the road curvature radius calculation function that merges described two signal application weighted values, predict the travel track of vehicle and be not subjected to the special motoring condition of vehicle and the impact of the mistake identification/outside hindering factors such as unidentified track.
The uncontrollable state that might occur when specifically, utilizing track radius of curvature information control vehicle by image device is unidentified/and mistake identifies under the situation in track and also can implement control.
And also can implement control under the road curvature radius data that when the deflection angles such as tortuous negotiation of bends change fast, might the occur situation of beating.
Moreover, vehicle also can be stablized the radius of curvature that the track is provided when bend changes the track.
Another effect of the present invention is exactly the fail safe function, exactly image device and vehicle sensors section is confirmed at any time repeatedly, even fault partly occurs a side, also in time isolated fault and all-the-time stable realize the control to vehicle.
Above embodiment and particular terms only in order to technical scheme of the present invention to be described, are not intended to limit; Although with reference to previous embodiment the present invention is had been described in detail, those of ordinary skill in the art is to be understood that: it still can be made amendment to the described technical scheme of aforementioned each embodiment, perhaps part technical characterictic wherein is equal to replacement; And these modifications or replacement do not make the essence of appropriate technical solution break away from the scope of the described technical scheme of various embodiments of the present invention.

Claims (6)

1. a lane keeping ancillary system is characterized in that, be connected car speed sensor with yaw-rate sensor with the vehicle image device and be connected, and the identification track implements the lane keeping ancillary system of described vehicle auto-steering, and its composition comprises:
Left side and right side curvature filter utilize the graphicinformation that obtains from described image device, obtain the radius of curvature of left-hand lane and right-hand lane;
Chassis curvature filter utilizes from yaw velocity and the speed of a motor vehicle of described yaw-rate sensor and car speed sensor acquisition and obtains the Chassis radius of curvature;
The curvature condition consists of and weighted value formation section, utilization is from described left side and right-hand lane radius of curvature and the described Chassis radius of curvature of described left side and right side curvature filter and the acquisition of described Chassis curvature filter, according to determining curvature condition and weighted value condition value when the vehicle in front operating state, obtain final curvature value.
2. lane keeping ancillary system according to claim 1 is characterized in that, described left side and right side curvature filter and described Chassis curvature filter are to be made of the Kalman filter according to 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
Figure FDA00002053968000013
Figure FDA00002053968000014
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's covariance, and Q and R are respectively process noise covariance and measurement noise covariance, and K is the kalman gain that calculates by covariance.
3. the method for prediction vehicle travel track in the lane keeping ancillary system, implementation step comprises:
The graphicinformation that utilization obtains from the vehicle image device is obtained the radius of curvature of each left-hand lane and right-hand lane;
Utilization is obtained the Chassis radius of curvature from the yaw-rate sensor of described vehicle and yaw velocity and the speed of a motor vehicle of car speed sensor acquisition;
Utilization is from described left side and right side curvature filter and the described left side of described Chassis curvature filter acquisition and radius of curvature and the described Chassis radius of curvature of right-hand lane, determine curvature condition and weighted value condition value according to the operating state when vehicle in front, then obtain final curvature value.
4. the method for prediction vehicle travel track in the lane keeping ancillary system according to claim 3 is characterized in that,
Obtaining the step of final curvature value, the difference of the radius of curvature of described left side and right-hand lane surpasses set critical value, and wherein some when larger in the difference of 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 and described Chassis radius of curvature, the larger side's of difference who from the radius of curvature of the radius of curvature of described left-hand lane and described right-hand lane, gets rid of value and obtain final curvature value.
5. the method for prediction vehicle travel track in the lane keeping ancillary system according to claim 3 is characterized in that,
In the described step of obtaining final curvature value, if described yaw velocity surpasses set critical value, then get rid of described Chassis radius of curvature, only utilize the radius of curvature of described left-hand lane and right-hand lane, obtain final curvature value.
6. the method for prediction vehicle travel track in each described lane keeping ancillary system in 5 according to claim 3 is characterized in that,
The radius of curvature of described left side and right-hand lane and described Chassis radius of curvature are only used following Kalman filter according to [mathematical expression 1] and are calculated,
[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
Figure FDA00002053968000033
Figure FDA00002053968000034
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's covariance, and Q and R are respectively process noise covariance and measurement noise covariance, and K is the kalman gain that utilizes covariance to calculate.
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* Cited by examiner, † Cited by third party
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CN104670228A (en) * 2013-11-26 2015-06-03 现代摩比斯株式会社 Apparatus and method for controlling lane keeping of vehicle
CN106515740A (en) * 2016-11-14 2017-03-22 江苏大学 Distributed electrically driven automobile travelling status parameter estimation algorithm based on ICDKF
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CN109677415A (en) * 2017-10-18 2019-04-26 现代自动车株式会社 Device and method for estimating the radius of curvature of vehicle
CN109859528A (en) * 2019-02-27 2019-06-07 中国第一汽车股份有限公司 A kind of corner vehicle location classification method based on V2X car networking
CN110647801A (en) * 2019-08-06 2020-01-03 北京汽车集团有限公司 Method and device for setting region of interest, storage medium and electronic equipment
CN111688683A (en) * 2019-03-13 2020-09-22 长沙智能驾驶研究院有限公司 Vehicle driving state control method, device, computer equipment and storage medium
US10875531B2 (en) 2018-08-08 2020-12-29 Ford Global Technologies, Llc Vehicle lateral motion control

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* Cited by examiner, † Cited by third party
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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE10223679A1 (en) * 2002-05-28 2003-12-11 Bosch Gmbh Robert Verifying road curvature involves determining yaw rate of vehicle independently of curvature of road and checking for consistency with curvature of road and speed of vehicle
JP2005140749A (en) * 2003-11-10 2005-06-02 Toyota Motor Corp Curve-estimating apparatus and travel control apparatus using the same
US20070233353A1 (en) * 2006-03-28 2007-10-04 Alexander Kade Enhanced adaptive cruise control system with forward vehicle collision mitigation
JP2010170187A (en) * 2009-01-20 2010-08-05 Toyota Central R&D Labs Inc Driver operation prediction device and program

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE10223679A1 (en) * 2002-05-28 2003-12-11 Bosch Gmbh Robert Verifying road curvature involves determining yaw rate of vehicle independently of curvature of road and checking for consistency with curvature of road and speed of vehicle
JP2005140749A (en) * 2003-11-10 2005-06-02 Toyota Motor Corp Curve-estimating apparatus and travel control apparatus using the same
US20070233353A1 (en) * 2006-03-28 2007-10-04 Alexander Kade Enhanced adaptive cruise control system with forward vehicle collision mitigation
JP2010170187A (en) * 2009-01-20 2010-08-05 Toyota Central R&D Labs Inc Driver operation prediction device and program

Cited By (16)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104554269B (en) * 2013-10-17 2017-06-16 现代摩比斯株式会社 Region of interest area setting device and its method
CN104554269A (en) * 2013-10-17 2015-04-29 现代摩比斯株式会社 Region of interest setting device and method thereof
CN104670228A (en) * 2013-11-26 2015-06-03 现代摩比斯株式会社 Apparatus and method for controlling lane keeping of vehicle
US9889848B2 (en) 2013-11-26 2018-02-13 Hyundai Mobis Co., Ltd. Apparatus and method for controlling lane keeping of vehicle
CN106515740A (en) * 2016-11-14 2017-03-22 江苏大学 Distributed electrically driven automobile travelling status parameter estimation algorithm based on ICDKF
CN107607546B (en) * 2017-09-19 2020-10-23 佛山缔乐视觉科技有限公司 Leather defect detection method, system and device based on photometric stereo vision
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CN109677415A (en) * 2017-10-18 2019-04-26 现代自动车株式会社 Device and method for estimating the radius of curvature of vehicle
CN109677415B (en) * 2017-10-18 2023-07-14 现代自动车株式会社 Apparatus and method for estimating radius of curvature of vehicle
CN108377599A (en) * 2018-04-27 2018-08-07 北京新能源汽车股份有限公司 Vehicle and its lighting system
US10875531B2 (en) 2018-08-08 2020-12-29 Ford Global Technologies, Llc Vehicle lateral motion control
CN109859528B (en) * 2019-02-27 2021-12-10 中国第一汽车股份有限公司 V2X Internet of vehicles-based method for classifying positions of vehicles at curves
CN109859528A (en) * 2019-02-27 2019-06-07 中国第一汽车股份有限公司 A kind of corner vehicle location classification method based on V2X car networking
CN111688683A (en) * 2019-03-13 2020-09-22 长沙智能驾驶研究院有限公司 Vehicle driving state control method, device, computer equipment and storage medium
CN111688683B (en) * 2019-03-13 2021-05-25 长沙智能驾驶研究院有限公司 Vehicle driving state control method, device, computer equipment and storage medium
CN110647801A (en) * 2019-08-06 2020-01-03 北京汽车集团有限公司 Method and device for setting region of interest, storage medium and electronic equipment

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