KR101930163B1 - Apparatus and method for lane Keeping control - Google Patents

Abstract

Disclosed are an apparatus and a method for lane keeping control, capable of estimating a lateral speed of a vehicle. The apparatus for the lane keeping control includes: a measurement unit for measuring lane information and vehicle motion information by using at least one of a camera sensor and an inertial measurement sensor; and a backstepping controller for performing lateral motion control for keeping a lane of a vehicle by using the lane information and the vehicle motion information, wherein the backstepping controller calculates a steering torque of the vehicle by using a dynamic lateral motion model that takes into consideration a look-ahead distance of the vehicle, and performs the lateral motion control by using the calculated steering torque, the dynamic lateral motion model is produced as a reduced quadratic model, and the backstepping controller is generated through a backstepping process for the reduced quadratic dynamic lateral motion model.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention [0001]

The present invention relates to a lane keeping control device and method.

Control issues of autonomous vehicles for Advanced Driver Assistance System (ADAS) have been actively studied in the automotive industry. These advanced driver assistance systems and autonomous vehicles make driving safer and more convenient.

Control of advanced driver assistance systems and autonomous vehicles can be classified into two types: longitudinal control and lateral control. Many longitudinal control applications have been introduced to the market, including adaptive cruise control and autonomous emergency brakes. On the other hand, since lateral control is closely related to vehicle stability, it has not been developed as much as longitudinal control, but only a few supporting applications are available that the driver can use to control the lateral position. These applications included the functions of blind spot detection, lane maintenance / change support, and lane departure warning. Recently, an angle control method of an electric power steering system has been developed for autonomous vehicles.

Various lateral control methods for lateral motion control, such as the LKS (Lane Keeping System) and LXS (LXS), are described in Level 4 (high automation) and defined in the Society of Automotive Engineers (SAE) Internationa 5 (fully automated).

For example, the Lyapunov-based lateral control algorithm was proposed by Rossetter and Gerdes in 2006, while the background control theory was presented in 2003 for the automatic lane change technique. Taylor proposed a lead-lag control method for lateral motion in 1999. Also, gain scheduling fuzzy control was proposed in 2008 by Wu et al. Naranjo developed a fuzzy controller in 2008 that mimics human behavior and response during overtaking operations. On the other hand, the performance of four lateral control methods was compared and studied by Chaib in 2004.

Recently, multi-ratio lateral control techniques have been proposed by Son and Kang in 2016 and 2015, respectively, to reduce yaw rate ripple and lateral offset error.

A lateral application using a kinematic vehicle model has also been proposed.

Although these methods have improved lateral control performance, system and modeling uncertainties have not been considered. In practice, it is difficult to measure the lateral velocity even if the controller is able to use most of the methods described above.

The present invention relates to a lane keeping control device and method for controlling a lateral motion of a vehicle using a dynamic lateral motion model of a vehicle for lane keeping and estimating a lateral velocity of the vehicle will be.

According to an aspect of the present invention, a lane keeping controller is disclosed.

A lane keeping control device according to an embodiment of the present invention includes a measurement unit for measuring lane information and vehicle motion information using at least one of a camera sensor and an inertial measurement sensor, And a backstepping controller for performing a lateral motion control for maintaining the vehicle by the vehicle, wherein the backstepping controller includes a dynamic lateral motion model considering a look-ahead distance of the vehicle, calculates a steering torque of the vehicle using a dynamic lateral motion model, and performs the lateral motion control using the calculated steering torque, and the dynamic lateral motion model is generated as a reduced second-order model , The back stepping controller generates a back stepping process for the reduced second order dynamic lateral motion model The.

및 상기 무게중심에서의 헤딩 각도 오차(heading angle error)

를 포함하고, 상기 차량 모션 정보는 요레이트 오차(yaw rate error)

를 포함한다.Wherein the lane information includes a lateral lane center offset at the center of gravity of the vehicle,

And a heading angle error at the center of gravity.

Wherein the vehicle motion information includes a yaw rate error,

.

를 포함하며, 상기 축소된 2차의 다이나믹 횡방향 모션 모델의 시스템 상태 함수는 3차 곡선 차로에 대한 전방 주시 지점(look-ahead point)에서의 횡방향 오프셋 e_yL을 상태 함수 z로 적용하여 하기 수학식으로 정의된다.The systematic state function of the dynamic lateral motion model includes a state vector

_Wherein the system state function of the reduced second order dynamic lateral motion model is obtained by applying a lateral offset e _yL at a look-ahead point to a cubic curve lane as a state function z, Is defined by a mathematical expression.

(= x₁)는 상기 차량의 무게중심에서의 횡방향 차로 중심 오프셋(lateral lane center offset)이고,

(= x₂)는 횡방향 속도 오차이고,

(= x₃)는 상기 무게중심에서의 헤딩 각도 오차(heading angle error)이고,

(= x₄)는 상기 차량 모션 정보는 요레이트 오차(yaw rate error)이고, L은 상기 전방 주시 거리이고, z₂는 z₁을 미분한 것임here,

(= x ₁ ) is the lateral lane center offset at the center of gravity of the vehicle,

(= x ₂ ) is the lateral velocity error,

(= x ₃ ) is a heading angle error at the center of gravity,

(= x ₄ ), the vehicle motion information is a yaw rate error, L is the forward viewing distance, and z ₂ is a derivative of z ₁

The transverse offset e _yL is approximated by the following equation.

Z ₁ is represented by the following equation.

는 차량의 무게중심으로부터 턴(turn) 중심까지의 거리이고,

는 차량 무게중심에서의 종방향(longitudinal) 차량 속도이고,

는 차량 무게중심에서의 사이드 슬립 각도(side slip angle)임here,

Is the distance from the center of gravity of the vehicle to the center of the turn,

Is the longitudinal vehicle speed at the center of gravity of the vehicle,

Is the side slip angle at the center of gravity of the vehicle

이되,remind

However,

로부터

이 도출되며,remind

from

Lt; / RTI >

remind Is applied to z ₁ .

If the convergence to a lateral offset (z ₁₎ at the front watch point (look-ahead point) 0, heading angle error of the center of gravity lateral drive center offset (x ₁₎ and the weight of the of the vehicle center (x ₃ ) converge to zero.

And a sliding mode observer for estimating the lateral velocity error.

The sliding mode observer estimates the lateral velocity error to converge the lateral velocity error to zero, and when the lateral velocity error converges to zero, the error of the back stepping controller converges to zero.

According to another aspect of the present invention, a lane keeping control method is disclosed.

The present invention provides a lane keeping control method comprising the steps of measuring lane information and vehicle motion information using at least one of a camera sensor and an inertial measurement sensor, Wherein the step of performing lateral motion control comprises the step of providing a backstepping controller with a look-ahead distance of the vehicle, The dynamic lateral motion model is calculated using the calculated steering torque and the lateral motion control is performed using the calculated dynamic steering torque and the dynamic lateral motion model is reduced , And the back stepping controller is configured to generate a backscatter signal for the reduced second order dynamic lateral motion model, Tapping process.

An apparatus and a method for controlling a lane keeping control according to an embodiment of the present invention are provided for controlling a lateral motion of a vehicle using a dynamic lateral motion model of a vehicle for lane keeping, Can be estimated.

BRIEF DESCRIPTION OF THE DRAWINGS Fig. 1 is a diagram showing a lateral motion of a vehicle by a lane keeping control device according to an embodiment of the present invention; Fig.
2 is a diagram illustrating a schematic configuration of a lane keeping controller according to an embodiment of the present invention.
3 is a flow chart of a lane keeping control method according to an embodiment of the present invention;
Figs. 4 to 14 show simulation results of a lane keeping control apparatus according to an embodiment of the present invention; Fig.

As used herein, the singular forms "a", "an" and "the" include plural referents unless the context clearly dictates otherwise. In this specification, the terms " comprising ", or " comprising " and the like should not be construed as necessarily including the various elements or steps described in the specification, Or may be further comprised of additional components or steps. Also, the terms " part, " " module, " and the like described in the specification mean units for processing at least one function or operation, which may be implemented in hardware or software or a combination of hardware and software .

Before describing embodiments of the present invention, various terms such as parameters and subscripts described in the present specification will be defined as follows.

: 차량의 무게중심으로부터 턴(turn) 중심까지의 거리

: Distance from the center of gravity of the vehicle to the center of the turn

: 차로 중심으로부터 턴 중심까지의 거리

: Distance from the center of the car to the center of the turn

: 차량 무게중심에서의 횡방향 차로 중심 오프셋(lateral lane center offset)

: Lateral lane center offset at the vehicle center of gravity

: 전방 주시 지점(look-ahead point)에서의 횡방향 차로 중심 오프셋

: The lateral lane center offset at the look-ahead point

: 전방 주시 거리(look-ahead distance)

: Look-ahead distance

: 차로 중심의 요 각도 기울기(yaw angle slope)

: Yaw angle slope at the center of the car

: 전방 주시 지점에서의 차로 중심의 요 각도 기울기

: The center yaw angle slope at the front sight point

: 차량 무게중심에서의 헤딩 각도 오차(heading angle error)

: Heading angle error at the vehicle center of gravity

: 전방 주시 지점에서의 헤딩 각도 오차

: Heading angle error at forward viewing point

: 요레이트(yaw rate)

: Yaw rate

: 차량 무게중심에서의 차량 속도

: Vehicle speed at the center of gravity of the vehicle

: 타이어 슬립 각도(tire slip angle)

: Tire slip angle

: 차량 무게중심에서의 사이드 슬립 각도(side slip angle)

: Side slip angle at the vehicle center of gravity

: 타이어의 코너링 강성(cornering stiffness)

: Cornering stiffness of a tire

: 횡방향 타이어 힘

: Lateral tire force

: 차량의 요 관성(yaw inertia)

: Yaw inertia of vehicle

: 차량의 총 중량

: Total weight of vehicle

: 차량의 무게중심과 타이어간 거리

: Distance between the center of gravity of the vehicle and the tire

: 제어 입력(=

: 스티어링 각도)

: Control input (=

: Steering angle)

: 전방(front)

: Front

: 후방(rear)

: Rear

: 종방향(longitudinal)

: Longitudinal

: 횡방향(lateral)

: Lateral

: desired

: desired

Hereinafter, various embodiments of the present invention will be described in detail with reference to the accompanying drawings.

1 is a view showing a lateral motion of a vehicle by a lane keeping control device according to an embodiment of the present invention, Fig. 2 is a diagram illustrating a schematic configuration of a lane keeping control device according to an embodiment of the present invention And FIG. 3 is a flowchart showing a lane keeping control method according to an embodiment of the present invention.

2, a lane keeping controller 200 according to an embodiment of the present invention includes a measuring unit 210, a backstepping controller 220, and a sliding mode observer 230 do.

Hereinafter, the function of each component and the process performed in each step will be described in detail with reference to FIG. 1 to FIG.

First, in step S310, the measuring unit 210 measures lane information and vehicle motion information.

과 차량 무게중심에서의 헤딩 각도 오차

는 카메라 센서를 이용하여 측정될 수 있으며, 요레이트 오차

는 관성 측정 센서를 이용하여 측정될 수 있다.For example, the measurement unit 210 may include a camera sensor and an inertial measurement sensor, and may measure information on a car using a camera sensor and measure vehicle motion information using an inertial measurement sensor. That is, in Fig. 1, the lateral lane center offset at the center of gravity of the vehicle

And the heading angle error at the vehicle center of gravity

Can be measured using a camera sensor, and the yaw rate error

Can be measured using an inertia measurement sensor.

Next, in step S320, the back stepping controller 220 performs lateral motion control for maintaining the vehicle by using the car information and the vehicle motion information.

That is, the back stepping controller 220 according to the embodiment of the present invention calculates the steering torque of the vehicle using a dynamic lateral motion model that takes into consideration the forward viewing distance of the vehicle, and calculates the calculated steering torque It is possible to perform the lateral motion control for maintaining the vehicle by the vehicle.

Here, the dynamic lateral motion model may be generated as a reduced second-order model, and the back stepping controller 220 may be generated through a back stepping process for a reduced second-order dynamic lateral motion model.

Hereinafter, the design of the back stepping controller 220 will be described.

The system state function for the dynamic lateral motion model of the vehicle can be generated as a function of the lateral position of the vehicle and the error of the speed.

, 제어 입력

및 외부 신호

에 관하여 하기 수학식과 같이 나타낼 수 있다.First, the generalized dynamic transverse motion model consists of the lateral position error and the yaw angle error for the road, and the system state function of this model is the state vector

, Control input

And external signals

Can be expressed by the following equation.

here,

The lateral offset at the forward viewing point can be expressed by the following equation according to the clothoidal constraints in the third order polynomial.

The cubic curve can be approximated as a straight line with small curvature or small forward viewing distance. The lateral offset at the forward viewing point of Equation (2) can be approximated by the following equation.

In order to use the approximated e _yL , the state z is newly defined as the following equation.

From Equations (1) and (4), a dynamic model of z ₂ having a constant velocity can be obtained as the following equation.

here,

As a result, the second-order model in which the normal-form is reduced for the lateral control becomes as follows.

The reduced quadratic model exists in the form of a normal form. Thus, system functions and parameters are only present in the z ₂ dynamic model.

The back stepping controller 220 for the reduced second order model is generated through a back stepping process, which will be described below.

를 하기 수학식과 같이 정의하기로 한다.Tracking error

Is defined as the following equation.

The dynamic model of the tracking error can be expressed by the following equation.

In consideration of the tracking error dynamic model of Equation (8), it is assumed that the back stepping controller 220 is designed by the following equation.

Where k ₁ , k _2, and k _s are positive numbers, and the origin of the tracking error dynamic model in equation (8) is exponentially stable.

When Equation (9) for the back stepping controller (220) is applied to the tracking error dynamic model of Equation (8), the following equation is calculated.

The Lyapunov candidate function V _e2 for stability analysis is defined by the following equation.

When this is differentiated with respect to time, the following equation is calculated.

On the other hand, V _e1 is defined by the following equation.

When this is differentiated with respect to time, the following equation is calculated.

In Equation (8), if e ₂ is defined as an input and e ₁ is defined as an output, Equation (14) can be expressed as Equation

Equation 15, which shows the relationship between e ₁ and e ₂ , is strictly output-passive. Then, e ₁ can be observed in the zero state. Thus, the origin of the tracking error dynamic model of Equation (8) is exponentially stable.

In Equation (9) with respect to the back stepping controller 220, the sign function sgn (e ₂ ) is necessary for robustness of model and parameter uncertainty. All state variables in all real systems are physically limited. Thus, uncertainties in parameters and systems have limitations. If the control gain k _s is large enough to suppress the uncertainty of the parameters and the system, the uncertainties of the parameters and of the system can be compensated.

와 같은 상위 한계

가 존재한다. 또한, 차량의 횡방향 가속은 매우 작다.In a typical highway driving situation, as in car maintenance, advanced driver assistance systems are designed to maintain the riding comfort of the driver and to satisfy the stability of the vehicle motion. so,

Upper limits such as

Lt; / RTI > Further, the lateral acceleration of the vehicle is very small.

과 헤딩 각도 오차

는 둘다 작은 범위 안에서 조정된다.If the approximated forward viewing distance z ₁ converges exponentially to zero, then a lateral offset

And heading angle error

Are both adjusted within a small range.

이기 때문에, 다이나믹 횡방향 모션 모델로부터 하기 수학식이 획득된다.

, The following equation is obtained from the dynamic transverse motion model.

Then, z ₁ can be expressed by the following equation.

이다. 그래서, x₁은 기하급수적으로 제로로 수렴하며, 결과적으로 균일한 한계를 가진다. 결과적으로, x₃도 균일한 한계를 가진다.

가 작기 때문에, x₁과 x₃는 작은 범위 내에서 조정된다.As described above, z ₁ converges to zero exponentially. In steady-state,

to be. Thus, x ₁ converges exponentially to zero, resulting in a uniform limit. As a result, x ₃ also has a uniform limit.

Is small, x ₁ and x ₃ are adjusted within a small range.

Next, in step S330, the sliding mode observer 230 estimates the lateral velocity error of the vehicle to compensate for the uncertainty of the parameter.

에서

(=

)를 추정할 수 있다. That is, the sliding mode observer 230 calculates a state vector

in

(=

) Can be estimated.

Hereinafter, the design of the sliding mode observer 230 will be described.

The sliding mode observer 230 is designed by estimating all states. The system state function of Equation (1) with the following measurement matrix is considered.

및

는 차선 검출용 카메라 센서를 이용하여 측정되고,

는 차량 모션 측정용 관성 측정 센서를 이용하여 측정된다.here,

And

Is measured using a camera sensor for lane detection,

Is measured using an inertial measurement sensor for vehicle motion measurement.

The sliding mode observer 230 for state observation is designed by the following equation.

The system state function of Equation 19 for the sliding mode observer 230 can be transformed into a canonical form using the transformation matrix as shown in the following equation.

here,

는 측정 행렬의 널(null) 공간을 나타낸다. 정규형 모델을 획득하기 위하여 정규형 변환 행렬 T_c가 적용되면, 하기의 수학식이 획득될 수 있다.

Represents the null space of the measurement matrix. When a normalized transformation matrix T _c is applied to obtain a normal model, the following equation can be obtained.

here,

The following equation is defined.

In the reaching mode, the transformation matrix T _s is applied so that the discontinuous shape appears.

The error dynamic model for the new coordinates is obtained by the following equation.

here,

이다.About sliding mode

to be.

을 충족하는 표면

에서와 같이,

이다.The purpose of the sliding mode observer 230 is to determine an accessibility condition

Surface to meet

As in,

to be.

의 다이나믹 모델을 고려하기로 한다. 슬라이딩 표면에서 하기 수학식이 획득된다.In Equation 25,

And the dynamic model of FIG. The following equation is obtained on the sliding surface.

가 된다.L _o is determined,

.

The error system for the ranging mode can be represented by the following equation with linear output error feedback.

과

(

)가 선택되면, 하기 수학식이 산출된다.

and

(

) Is selected, the following equation is calculated.

와

가 결정되어,

일 때

이 된다.

Wow

Lt; / RTI >

when

.

는 하기 수학식으로 정의된다.Lyapunov candidate function for stability analysis

Is defined by the following equation.

If this is differentiated with respect to time, the following equation is calculated.

는 하기 수학식으로 정의된다.Lyapunov candidate function for stability analysis

Is defined by the following equation.

If this is differentiated with respect to time, the following equation is calculated.

는 입력으로,

는 출력으로 정의하면, 수학식 32는 하기와 같이 나타낼 수 있다.In equation (28)

As input,

Is defined as an output, Expression (32) can be expressed as follows.

와

사이의 관계를 보여주는 수학식 33은 엄격하게 출력 수동적이다. 그리고,

는 제로 상태로 관찰될 수 있다. 따라서, 수학식 28의 오차 다이나믹 모델의 오리진은 기하급수적으로 안정적이다.

Wow

Lt; / RTI > is strictly output-passive. And,

Can be observed in a zero state. Thus, the origin of the error dynamic model of equation (28) is exponentially stable.

가 사용된다. 그래서, 수학식 10의 오차 다이나믹 모델은 하기 수학식으로 변경될 수 있다.In practice, it is difficult to measure e ₂ . Thus, instead of e ₂ , in equation (9) for back stepping controller 220

Is used. Thus, the error dynamic model of Equation (10) can be changed to the following equation.

이다.here,

to be.

The closed loop system can be expressed by the following equation from the equation (34) and the equation (28).

는 한계를 가진다.

로부터 e₁ 및 e₂까지의 수학식 10의 오차 다이나믹 모델은 입력 상태가 안정적이다. 추정 오차

와

는 제로로 수렴하는 것으로 판명된다. 그래서,

가 제로로 수렴하여

가 되기 때문에,

는 제로로 수렴한다. 결론적으로, e₁ 및 e₂는 제로로 수렴한다.In Equation (35)

Have limitations.

The error dynamic model of Equation (10) from e _{1 to} e ₂ has a stable input state. Estimation error

Wow

Is converged to zero. so,

Converge to zero

As a result,

Converges to zero. Consequently, e ₁ and e ₂ converge to zero.

4 to 14 are diagrams showing simulation results of the lane keeping control apparatus according to the embodiment of the present invention.

CarSim and MATLAB / Simulink were used for the simulation. CarSim and MATLAB / Simulink were implemented as dynamic vehicle motion solvers and were executed for back stepping controller 220 and sliding mode observer 230, respectively. In the simulation, the vehicle speed was set at 80 km / h, and the vehicle traveled according to the following two cases.

Case 1: Straight and Circular Road Segments

Case 2: S-curve road satisfying clause constraint

The parameters used in the simulation are the nominal values of a small SUV (sports utility vehicle). The effect of the forward viewing distance can be verified in the back stepping controller 220 under various forward viewing distances.

)에 대하여 근사적으로 선형화되었기 때문에, 오프셋 오차를 가진다. 그럼에도 불구하고, 본 발명의 실시예에 따른 차로 유지 제어 장치(200)는 도 8에서 직선 도로 및 일정 곡률을 가지는 도로에서 0.01m 내의 횡방향 오프셋을 가지는 상당히 타당한 성능을 보여준다.FIGS. 4-6 show the vehicle motion data of the back stepping controller 220 in Case 1, and FIGS. 7 and 8 show the performance of the back stepping controller 220 in Case 1. FIG. 6 shows the performance of the sliding mode observer 230. FIG. On roads with constant curvature, the observer can determine that the model used in equation (28) is a small side slip angle

), It has an offset error. Nevertheless, the lane keeping controller 200 according to the embodiment of the present invention exhibits a fairly reasonable performance with a lateral offset within 0.01 m in a straight road and a road with a certain curvature in Fig.

In practice, the use of the high gain k _s in equation (9) is undesirable. A high K _s value causes chattering at the steering angle. Thus, an uncomfortable yaw rate occurs. However, when the vehicle moves out of the circular road to a straight lane, z ₁ begins to converge to zero. In order to eliminate this excessive chattering, a sliding mode observer 230 for disturbance observation may be added to the back stepping controller 220.

The transient between the two segments does not satisfy the clause constraint because the road segment of Case 1 is straight and circular. Therefore, ripples of the yaw rate and the steering angle can be observed in Figs. 4 to 8, respectively. Indeed, the highway is designed to meet the clause constraints, so that no vibrations occur as shown in Figs. 4-8.

과 등가이다. 전방 주시 거리 L을 이용한 횡방향 모션 제어는 실제로 차량의 종방향 속도에 따라 L을 결정한다. 이 L의 변화는 시스템 제로의 위치에 영향을 주어 주극점(dominant pole)의 댐핑 레이셔(damping ratio)가 영향을 받는다. L은 차량 앞에서 가깝다. 그래서, 댐핑 레이셔는 상당히 감소한다. 또한, 도 9는 본 발명의 실시예에 따른 차로 유지 제어 장치(200)의 전방 주시 거리의 댐핑 효과를 나타낸다.9 shows the steering wheel angle with respect to the front sight distance L used for the back stepping access control. The transient response is the sum of the step response

. The lateral motion control using the forward viewing distance L actually determines L according to the longitudinal speed of the vehicle. This change in L affects the position of the system zero so that the damping ratio of the dominant pole is affected. L is near the front of the vehicle. Thus, the damping ratio decreases considerably. 9 shows the damping effect of the front view distance of the lane keeping controller 200 according to the embodiment of the present invention.

)가 사용되었기 때문에, 증가된 곡률로 인하여 더 커진다.FIGS. 10 to 12 show the vehicle motion data of the back stepping controller 220 in Case 2, and FIGS. 13 and 14 show the performance of the back stepping controller 220 in Case 2. 12 shows the performance of the sliding mode observer 230. FIG. The offset error of the sliding mode observer 230 is an approximate linearized side slip angle < RTI ID = 0.0 >

) Is used, it becomes larger due to the increased curvature.

Although there is an offset error in the sliding mode observer 230, the lane keeping control device 200 according to the embodiment of the present invention is significantly superior to the conventional linear quadratic (LQ) control method Show reasonable performance. The lane keeping controller 200 according to the embodiment of the present invention carries out lane keeping within 0.1 m on a road with a curve satisfying the clause constraint in Fig.

On the other hand, the components of the above-described embodiment can be easily grasped from a process viewpoint. That is, each component can be identified as a respective process. Further, the process of the above-described embodiment can be easily grasped from the viewpoint of the components of the apparatus.

In addition, the above-described technical features may be implemented in the form of program instructions that can be executed through various computer means and recorded in a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, and the like, alone or in combination. The program instructions recorded on the medium may be those specially designed and constructed for the embodiments or may be available to those skilled in the art of computer software. Examples of computer-readable media include magnetic media such as hard disks, floppy disks and magnetic tape; optical media such as CD-ROMs and DVDs; magnetic media such as floppy disks; Magneto-optical media, and hardware devices specifically configured to store and execute program instructions such as ROM, RAM, flash memory, and the like. Examples of program instructions include machine language code such as those produced by a compiler, as well as high-level language code that can be executed by a computer using an interpreter or the like. The hardware device may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

It will be apparent to those skilled in the art that various modifications, additions and substitutions are possible, without departing from the spirit and scope of the invention as defined by the appended claims. Should be regarded as belonging to the following claims.

200: Lane keeping control device
210:
220: Back stepping controller
230: Sliding mode observer

Claims (10)

A measurement unit for measuring information on a vehicle and motion information of the vehicle using at least one of a camera sensor and an inertial measurement sensor; And
And a backstepping controller for performing lateral motion control for maintaining the vehicle by using the lane information and the vehicle motion information,
Wherein the back stepping controller calculates a steering torque of the vehicle using a dynamic lateral motion model that takes into account a look-ahead distance of the vehicle, Performs the lateral motion control,
The dynamic lateral motion model is generated as a reduced quadratic model,
Wherein the back stepping controller is generated through a back stepping process for a reduced second-order dynamic lateral motion model.
The method according to claim 1,
Wherein the lane information includes a lateral lane center offset at the center of gravity of the vehicle,

And a heading angle error at the center of gravity.

Lt; / RTI >
Wherein the vehicle motion information is a yaw rate error,

And a control unit for controlling the vehicle.
The method according to claim 1,
The systematic state function of the dynamic lateral motion model includes a state vector

/ RTI >
The system state function of the reduced second order dynamic lateral motion model is defined by applying the lateral offset e _yL at the look-ahead point for the cubic curve lane to the state function z, And a control unit for controlling the vehicle.

here,

(= x ₁ ) is the lateral lane center offset at the center of gravity of the vehicle,

(= x ₂ ) is the lateral velocity error,

(= x ₃ ) is a heading angle error at the center of gravity,

(= x ₄ ) is the yaw rate error of the vehicle motion information, L is the forward viewing distance, and z ₂ is the derivative of z ₁ .
The method of claim 3,
_Wherein the transverse offset e _{y L} is approximated by the following equation:

The method of claim 3,
Wherein z ₁ is expressed by the following equation.

here,

Is the distance from the center of gravity of the vehicle to the center of the turn,

Is the longitudinal vehicle speed at the center of gravity of the vehicle,

Is the side slip angle at the center of gravity of the vehicle
6. The method of claim 5,
remind

However,
remind

from

Lt; / RTI >
remind

Keeping car, characterized in that said z ₁ is applied to the control device.
6. The method of claim 5,
If the convergence to a lateral offset (z ₁₎ at the front watch point (look-ahead point) 0, heading angle error of the center of gravity lateral drive center offset (x ₁₎ and the weight of the of the vehicle center (x ₃₎ is maintained, characterized in that drive to converge to zero the controller.
The method of claim 3,
Further comprising a sliding mode observer for estimating said lateral velocity error.
9. The method of claim 8,
Wherein the sliding mode observer estimates the lateral velocity error to converge the lateral velocity error to zero,
And an error of the back stepping controller converges to 0 when the lateral speed error converges to zero.
Measuring vehicle information and vehicle motion information using at least one of a camera sensor and an inertial measurement sensor; And
Performing lateral motion control for maintaining the vehicle by a lane using the lane information and the vehicle motion information,
Wherein performing the lateral motion control comprises:
A backstepping controller calculates a steering torque of the vehicle using a dynamic lateral motion model in which a look-ahead distance of the vehicle is taken into account, and the calculated steering torque is calculated To perform the lateral motion control,
The dynamic lateral motion model is generated as a reduced quadratic model,
Wherein the back stepping controller is generated through a back stepping process for a reduced second-order dynamic lateral motion model.

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