Apparatus for Controlling Keeping Lane and Method Thereof

In an embodiment a control apparatus includes a processor configured to calculate a target curvature depending on a target path of a vehicle, calculate a first lateral control value based on a feedforward control by using the target curvature, calculate a second lateral control value based on a feedback control by using vehicle information collected from a sensing device of the vehicle, estimate a disturbance by using the vehicle information collected from the sensing device of the vehicle, and calculate a final lateral control command value by summing the first lateral control value, the second lateral control value, and the disturbance and a storage configured to store data and algorithms driven by the processor.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to and the benefit of Korean Patent Application No. 10-2022-0089621, filed in the Korean Intellectual Property Office on Jul. 20, 2022, the entire contents of which are incorporated herein by reference.

TECHNICAL FIELD

The present disclosure relates to a lane keeping control apparatus and a method thereof, and more particularly, to a lane keeping control technique capable of calculating a lateral control command value in consideration of time delay between a steering-wheel steering angle and a front-wheel steering angle.

BACKGROUND

A lane following assist (LFA) function indicates a technique that controls driving, braking or steering of a vehicle such that the vehicle can travel while maintaining a target path (e.g., a path along a center of a lane or a path following a vehicle in front).

In the case of a conventional lane keeping assistance, after receiving information related to the target path through a camera sensor provided in the vehicle, a front-wheel steering angle required to follow it is generated through control logic. Since most vehicles are not equipped with a front-wheel steering angle sensor, a calculated required front-wheel steering angle is converted into a required steering-wheel steering angle, and then a torque of a steering system is controlled by feedback based on a steering-wheel steering angle obtained through the steering-wheel steering angle sensor.

In the case of a conventional method, in a process of converting the required front-wheel steering angle into the required steering-wheel steering angle, the conversion is simply performed by using a gear ratio between the steering-wheel steering angle and the front-wheel steering angle of the vehicle.

However, in the case of a large vehicle such as a truck, a dynamic time delay may occur between the steering-wheel steering angle and the front-wheel steering angle by hydraulic pressure. In addition, due to a weight change of the vehicle, a dynamic model on which a control design is based often does not match an actual vehicle.

As such, conventionally, not only does it not reflect the time delay of the steering system of a commercial vehicle, but it also fails to overcome when there is an error (disturbing) in a model parameter of lateral dynamics, and thus it may cause oscillation and performance degradation of the vehicle, so it is necessary to develop a technique for ameliorating such problems.

SUMMARY

Embodiments provide a lane keeping control apparatus and a method thereof, capable of greatly ameliorating an oscillation aspect of a lane following assist function and improving performance of a lane keeping function by ameliorating an error caused by a time delay for a steering system of a commercial vehicle and calculating a vehicle lateral control command value based on a dynamic model in which the error is ameliorated.

Further embodiments provide a lane keeping control apparatus including a processor configured to calculate a target curvature depending on a target path of a vehicle, to calculate a first lateral control value based on feedforward control by using the target curvature, to calculate a second lateral control value based on feedback control by using vehicle information collected from a sensing device of the vehicle, to estimate disturbance by using the vehicle information collected from the sensing device of the vehicle, and to calculate a final lateral control command value by summing the first lateral control value, the second lateral control value, and the disturbance; and a storage configured to store data and algorithms driven by the processor.

In an exemplary embodiment of the present disclosure, the processor may be configured to perform lateral control of the vehicle based on the final lateral control command value.

In an exemplary embodiment of the present disclosure, the processor may be configured to calculate the first lateral control value in consideration of a time delay of a steering system of the vehicle.

In an exemplary embodiment of the present disclosure, the processor may be configured to calculate the first lateral control value in consideration of the time delay through a time delay model.

In an exemplary embodiment of the present disclosure, the processor may be configured to calculate the first lateral control value by compensating for the time delay through a differential controller in a Laplace transform process.

In an exemplary embodiment of the present disclosure, the processor may be configured to design the time delay model by using at least one of a wheel base of the vehicle, a vehicle speed, a time constant, a gear ratio of a front-wheel steering angle to a steering-wheel steering angle, the steering-wheel steering angle, or any combination thereof.

In an exemplary embodiment of the present disclosure, the processor, after controlling the vehicle with the final lateral control command value, may be configured to input vehicle information collected from the sensing device of the vehicle into an inverse function that inverses a time delay model, and to obtain disturbance by subtracting an output value of the inverse function and the final lateral control command value therefrom.

In an exemplary embodiment of the present disclosure, the processor may be configured to filter the disturbance through a low-pass filter.

In an exemplary embodiment of the present disclosure, the processor may be configured to sum the filtered disturbance with the first lateral control value and the second lateral control value to output it as the final lateral control command value.

In an exemplary embodiment of the present disclosure, the processor after controlling the vehicle with the final lateral control command value, may be configured to calculate a rotational curvature of the vehicle using vehicle information collected from the sensing device of the vehicle, and to subtract the rotational curvature of the vehicle from the target curvature.

In an exemplary embodiment of the present disclosure, the processor may be configured to multiply a value obtained by subtracting the rotational curvature of the vehicle from the target curvature by a feedback gain.

In an exemplary embodiment of the present disclosure, the processor may be configured to calculate the second lateral control value by multiplying a value obtained by subtracting the rotational curvature of the vehicle from the target curvature by a reciprocal of a gear ratio of a front-wheel steering angle to a steering-wheel steering angle.

An exemplary embodiment of the present disclosure provides a lane keeping control method including: calculating, by a processor, a target curvature depending on a target path of a vehicle, and calculating a first lateral control value based on feedforward control by using the target curvature; calculating, by the processor, a second lateral control value based on feedback control by using vehicle information collected from a sensing device of the vehicle; estimating, by the processor, disturbance by using the vehicle information collected from the sensing device of the vehicle; and calculating, by the processor, a final lateral control command value by summing the first lateral control value, the second lateral control value, and the disturbance.

In an exemplary embodiment of the present disclosure, it may further include performing, by the processor, lateral control of the vehicle based on the final lateral control command value.

In an exemplary embodiment of the present disclosure, the calculating of the first lateral control value includes calculating, by the processor, the first lateral control value in consideration of a time delay of a steering system of the vehicle.

In an exemplary embodiment of the present disclosure, the calculating of the first lateral control value may include: calculating, by the processor, the first lateral control value in consideration of the time delay through a time delay model; and designing, by the processor, the time delay model by using at least one of a wheel base of the vehicle, a vehicle speed, a time constant, a gear ratio of a front-wheel steering angle to a steering-wheel steering angle, the steering-wheel steering angle, or any combination thereof.

In an exemplary embodiment of the present disclosure, the estimating of the disturbance may include: after controlling the vehicle with the final lateral control command value, inputting, by the processor, vehicle information collected from the sensing device of the vehicle into an inverse function that inverses a time delay model; and obtaining, by the processor, disturbance by subtracting an output value of the inverse function and the final lateral control command value therefrom.

In an exemplary embodiment of the present disclosure, the estimating of the disturbance may further include filtering the disturbance through a low-pass filter.

In an exemplary embodiment of the present disclosure, the calculating of the second lateral control value may include: after controlling the vehicle with the final lateral control command value, calculating, by the processor, a rotational curvature of the vehicle by using vehicle information collected from the sensing device of the vehicle; and subtracting, by the processor, the rotational curvature of the vehicle from the target curvature.

In an exemplary embodiment of the present disclosure, the calculating of the second lateral control value may include: multiplying, by the processor, a value obtained by subtracting the rotational curvature of the vehicle from the target curvature by a feedback; and calculating, by the processor, the second lateral control value by multiplying a value multiplied by the feedback gain by a reciprocal of a gear ratio of a front-wheel steering angle to a steering-wheel steering angle.

According to embodiment techniques, it is possible to greatly ameliorate an oscillation aspect of a lane following assist function and improve performance of a lane keeping function by ameliorating an error caused by a time delay for a steering system of a commercial vehicle and calculating a vehicle lateral control command value based on a dynamic model in which the error is ameliorated.

Furthermore, various effects that can be directly or indirectly identified through this document may be provided.

DETAILED DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS

Hereinafter, some exemplary embodiments of the present disclosure will be described in detail with reference to exemplary drawings. It should be noted that in adding reference numerals to constituent elements of each drawing, the same constituent elements have the same reference numerals as possible even though they are indicated on different drawings. Furthermore, in describing exemplary embodiments of the present disclosure, when it is determined that detailed descriptions of related well-known configurations or functions interfere with understanding of the exemplary embodiments of the present disclosure, the detailed descriptions thereof will be omitted.

In describing constituent elements according to an exemplary embodiment of the present disclosure, terms such as first, second, A, B, (a), and (b) may be used. These terms are only for distinguishing the constituent elements from other constituent elements, and the nature, sequences, or orders of the constituent elements are not limited by the terms. Furthermore, all terms used herein including technical scientific terms have the same meanings as those which are generally understood by those skilled in the technical field to which an exemplary embodiment of the present disclosure pertains (those skilled in the art) unless they are differently defined. Terms defined in a generally used dictionary shall be construed to have meanings matching those in the context of a related art, and shall not be construed to have idealized or excessively formal meanings unless they are clearly defined in the present specification.

Hereinafter, various exemplary embodiments of the present disclosure will be described in detail with reference toFIG.1toFIG.7.

FIG.1illustrates a block diagram showing a configuration of a vehicle system including a lane keeping control apparatus according to an exemplary embodiment of the present disclosure, andFIG.2illustrates a view for describing a design process of a vehicle lateral control dynamics model reflecting a dynamic time delay of a lane keeping control system according to an exemplary embodiment of the present disclosure.

The lane keeping control apparatus100according to the present disclosure may be implemented inside or outside the vehicle. In this case, the lane keeping control apparatus may be integrally formed with internal control units of the vehicle, or may be implemented as a separate hardware device to be connected to control units of the vehicle by a connection means. For example, the lane keeping control apparatus100may be implemented integrally with the vehicle, may be implemented in a form that is installed or attached to the vehicle as a configuration separate from the vehicle, or a part thereof may be implemented integrally with the vehicle, and another part may be implemented in a form that is installed or attached to the vehicle as a configuration separate from the vehicle.

For example, the lane keeping control apparatus100may be implemented as a lane following assist (LFA), a lane departure warning (LDW), a lane keeping system (LKS), and a lane keeping assistance device system (LKAS), etc.

The lane keeping control apparatus100may establish a dynamics model in consideration of a time delay of a steering-wheel steering angle and a front-wheel steering angle, and estimate disturbance based on the dynamics model, to use a first lateral control value based on feedforward control and collected vehicle information so as to calculate a second lateral control value based on feedback control and a final lateral control command value including the disturbance. Herein, the disturbance may include a steering angle sensor offset such as a time delay parameter and a gear ratio, and various modeling disturbances.

Referring toFIG.1, the vehicle system according to the exemplary embodiment of the present disclosure may include a lane keeping control apparatus100, a sensing device200, a steering control device300, a braking control device400, and an engine control device500.

The lane keeping control apparatus100may include a communication device110, a storage120, and a processor130.

The communication device110is a hardware device implemented with various electronic circuits to transmit and receive signals through a wireless or wired connection, and may transmit and receive information based on in-vehicle devices and in-vehicle network communication techniques. As an example, the in-vehicle network communication techniques may include controller area network (CAN) communication, local interconnect network (LIN) communication, flex-ray communication, and the like.

As an example, the communication device110may communicate with in-vehicle devices, and may receive a sensing result from the sensing device200. Particularly, the communication device110may receive a distance error from a camera210to a center of a vehicle on a gazing distance.

The storage120may store sensing results of the sensing device200and data and/or algorithms required for the processor130to operate, and the like. For example, the storage120may store a target rotational radius calculated by the processor130, a required front-wheel steering angle, a dynamic model, a formula for calculating the lateral control command value, a first lateral control value, a second lateral control value, estimated disturbance, etc.

The storage120may include a storage medium of at least one type among memories of types such as a flash memory, a hard disk, a micro, a card (e.g., a secure digital (SD) card or an extreme digital (XD) card), a random access memory (RAM), a static RAM (SRAM), a read-only memory (ROM), a programmable ROM (PROM), an electrically erasable PROM (EEPROM), a magnetic memory (MRAM), a magnetic disk, and an optical disk.

The processor130may be electrically connected to the communication device110, the storage120, etc., may electrically control each component, and may process a signal transferred between each constituent element. In addition, the processor130may be an electrical circuit that executes a command of software, thereby performing various data processing and calculations to be described later.

The processor130may be implemented as a microprocessor, but the present disclosure is not limited thereto, and may be, e.g., an electronic control unit (ECU), a micro controller unit (MCU), or other subcontrollers mounted in the vehicle.

The processor130may calculate a target curvature depending on a target path of the vehicle, may calculate a first lateral control value based on feedforward control by using the target curvature, may calculate a second lateral control value based on feedback control by using vehicle information collected from a sensing device of the vehicle, may calculate a second lateral control value based on feedback control using vehicle information collected from a vehicle sensing device to estimate disturbance using the vehicle information collected from the sensing device of the vehicle, and may perform lateral control of the vehicle based on the final lateral control command value.

The processor130may calculate the first lateral control value in consideration of a time delay of a steering system of the vehicle. That is, the processor130may calculate the first lateral control value in consideration of a time delay through a time delay model (Equation 6). In addition, the processor130may calculate the first lateral control value by compensating for the time delay through a differential controller in a Laplace transform process.

The processor130may design a time delay model by using at least one of a wheel base of the vehicle, a vehicle speed, a time constant, a gear ratio of the front-wheel steering angle to the steering-wheel steering angle, the steering-wheel steering angle, or any combination thereof.

The processor130may control the vehicle with the final lateral control command value, and then input vehicle information collected from the sensing device of the vehicle into an inverse function that inverses the time delay model, may obtain disturbance by subtracting an output value of the inverse function and the final lateral control command value therefrom, and may filter the disturbance through a low-pass filter.

The processor130may combine the filtered disturbance with the first lateral control value and the second lateral control value to output it as the final lateral control command value.

The processor130may control the vehicle with the final lateral control command value, and then may calculate a rotational curvature of the vehicle using vehicle information collected from a sensing device of the vehicle, and may subtract the rotational curvature of the vehicle from a target curvature.

In addition, the processor130may multiply a value obtained by subtracting the rotational curvature of the vehicle from the target curvature by a feedback gain K.

In addition, the processor130may calculate the second lateral control value by multiplying the value obtained by subtracting the rotational curvature of the vehicle from the target curvature by a reciprocal of the gear ratio of the front-wheel steering angle to the steering-wheel steering angle.

Hereinafter, a method of calculating the final lateral control value will be described in detail.

The processor130may calculate the target path and the front-wheel steering angle required depending on the target path, based on obtained surrounding information.

As an example, the processor130may detect information related to lanes around the vehicle or information related to a vehicle in front through acquired images around the vehicle in a state where the lane following assist (LFA) function is activated.

For example, the processor130may set a path in a center of opposite lanes to a lane in which the vehicle is traveling or a path following a front vehicle as the target path.

For example, when the opposite lanes to the lane in which the vehicle is traveling are detected, the processor130may set the path in the center of the opposite lanes as the target path, and when the opposite lanes to the lane in which the vehicle is traveling are not detected, may set the path following a front vehicle as the target path.

For example, the processor130may calculate the target rotational radius for maintaining the target path, and may calculate a required front-wheel steering angle in response to the target rotational radius.

The processor130may obtain the target rotational radius as shown in Equation 1 through a lane central distance error yerroron a gazing distance x received from the camera210.

Herein, Rdindicates the target rotational radius, yerrorindicates the lane central distance error, and x indicates the gazing distance.FIG.2illustrates a view for describing a process of calculating a target rotational radius based on a geometry map of a lane keeping control apparatus according to an exemplary embodiment of the present disclosure. As illustrated inFIG.2, the target rotational radius represents a rotational radius for the vehicle to reach the center of the lane.

For example, the processor130may calculate the target rotational radius for maintaining the target path based on a lane error detected through an image acquired by the sensing device200.

For example, when the vehicle deviates from the target path by exceeding a threshold or a heading direction of the vehicle is different from a direction of the target path, the processor130may calculate the target rotational radius depending on steering control for maintaining the target path. Herein, the processor130may calculate the target rotational radius in consideration of a driving speed of the vehicle.

As an example, the processor130may calculate the required front-wheel steering angle through Equations 2 to 4 below, based on the target rotational radius.

First, the processor130may calculate tan(67) from a bicycle geometry model as shown in Equation 2 below.

Herein, δ indicates the required front-wheel steering angle, R indicates a target rotational radius of a front wheel, and L indicates a distance between a front wheel21and a rear wheel22of the vehicle as illustrated inFIG.2as a wheel base between front and rear wheels of the vehicle.

The processor130may calculate the required front-wheel steering angle δ in consideration of understeer gradients.

Herein, Kusindicates an understeer gradient and V indicates a vehicle speed.

The processor130determines may calculate the required front-wheel steering angle δ by dividingL, which is a value obtained by summing a square of the vehicle wheelbase L, the understeer gradient Kusand the vehicle speed V, by the target rotational radius R.

The processor130may calculate the required front-wheel steering angle δ in consideration of the time delay in consideration of the time delay as shown in Equation 4.

Herein, τ indicates a gain depending on the time delay as a time constant, and may be determined as a time delay value through time delay modeling. In addition, θ denotes the steering-wheel steering angle, GR denotes the gear ratio of the front-wheel steering angle to the steering-wheel steering angle, and s denotes a complex number in a Laplace transform.

The processor130may calculate a rotational curvature of the vehicle as shown in Equation 5 below. In this case, the rotational curvature of the vehicle indicates a curvature of the vehicle rotated by a steering wheel steering angle command.

Herein, {dot over (ψ)} indicates a yaw rate of the vehicle, and V is the vehicle speed.

That is, the rotational curvature ρ of the vehicle indicates a value obtained by dividing the yaw rate of the vehicle by the vehicle speed.

A dynamics model in consideration of a dynamic time delay as shown in Equation 6 below may be defined by substituting Equation 4 and Equation 5 into Equation 3.

A relationship between the front-wheel steering angle and the steering angle at which the dynamic delay occurs may be expressed by using a time constant of a first-order transfer function. In this case, k indicates the gear ratio GR.

Hereinafter, a process of calculating a lateral control command value for lane keeping control of a commercial vehicle using a disturbance observer will be described with reference toFIG.3AandFIG.3B.

FIG.3Aillustrates a configuration and operation of a disturbance observer according to an exemplary embodiment of the present disclosure, andFIG.3Billustrates a specific configuration and operation of a lane following assistance system according to an exemplary embodiment of the present disclosure.

A system illustrated inFIG.3Ais a basic disturbance observer, and a controller C(s) outputs a control signal by calculating an input signal yrefand an output signal y outputted from a system G(s). The system G(s) is a lateral control dynamics modeling stem with parametric uncertainty, and Gn(s) is a nominal parametric model.

Assuming that there is an input signal u, u+d is inputted to the system G(s) by adding a disturbance d to the input signal u. In this case, the system G(s) may be an actuator.

Accordingly, the system G(s) outputs the output signal y, and the output signal y is inputted to an inverse function Gn(s)−1of the system Gn(s). In this case, the inverse function Gn(s)−1is for verifying whether an input signal of the system G(s) is the same as an output signal of the inverse function Gn(s)−1by using the output signal y of the system G(s) as an input signal.

That is, when the output signal received from the sensing device200during vehicle driving is y, the inverse function Gn(s)−1is an estimated value u+{circumflex over (d)}, and the disturbance may be estimated by subtracting the input signal u from the estimated value u+{circumflex over (d)}, {circumflex over (d)}, which is an estimate of the disturbance, is transferred to the filter Q(s), the filter Q(s) filters and outputs {circumflex over (d)}, and a value obtained by subtracting the filtered {circumflex over (d)} from the output of the controller C(s) is output as a u value. In this case, the filter Q(s) may be implemented as a low-pass filter.

Referring toFIG.3B, the system according to an exemplary embodiment of the present disclosure may include a target curvature generator201, a lateral controller202, a differential controller203, an arithmetic device204, a feedback controller205, a gear ratio calculator206, an arithmetic device207, an actuator208, and a disturbance observer209.

The target path is inputted to the target curvature generator201, and the target curvature generator201outputs a target curvature ρd. In this case, the target curvature generator201may calculate the target curvature based on Equation 6.

The lateral controller202may calculate the front-wheel steering angle δ pp by using the target curvature as an input. In this case, the lateral controller202may calculate the required front-wheel steering angle δ pp based on pure pursuit geometry.

The differential controller203may differentiate the required front-wheel steering angle δ pp, and the feedback controller205may output a feedback value using a value outputted from the actuator208. In this case, the value outputted from the actuator208may be replaced with a value obtained from the sensing device200in the vehicle while the vehicle is driving.

The arithmetic device204may sum the output value of the differential controller203and the output value of the feedback controller205, and the gear ratio calculator206may multiply the value added by the calculator204by a reciprocal

of the gear ratio. The 3arithmetic device207may output the final lateral control output value (θcmd, steering wheel steering angle command value) by subtracting an output value of the disturbance observer209from a product of a sum of the reciprocal

of the gear ratio and the output value of the differential controller203and the output value of the feedback controller205.

The processor130may develop it as shown in Equations 7 and 8 below by using a dynamics model reflecting a dynamic delay time of Equation 6.

Hereinafter in Equation 7 or below, a required current steering angle θ will be described by substituting it with θcmd.

Equation 8 is an expression of Equation 7 as a transfer function G(s).

In this case, Tτ, k, and L are uncertain parameters.

Equation 7 may be inversed and expressed as Equation 10 below. In this case, Gn(s) is a known nominal model function having a same structure as that of the transfer function G(s). Equation 10 indicates Gn(s)−1.

τn, kn, and Ln are nominal values and may be set to optimal values by experimental values in advance to facilitate controller design.

Equation 10 may be derived as an equation including a known nominal value and an unknown uncertain disturbance d as shown in Equation 11 below.

is a known nominal value, and

becomes the disturbance d, which is an uncertain value whose value is unknown. Equation 11 may be simplified as Equation 12.

From Equation 12, the disturbance d may be summarized as Equation 13 below.

A known nominal model and the disturbance d may be divided through Equations 11 to 13 described above. Hereinafter, the disturbance d is estimated and excluded.

Equation 14 defines Q(s), and Q(s) may be implemented as a first-order low-pass filter.

As shown in equation 15, the steering angle control command (lateral control command) θcmd may be designed such that an actual curvature of the vehicle becomes a required curvature in the presence of disturbance. That is, the steering angle control command θcmd may be divided into an estimated disturbance value and an external controller value.

In addition, as in Equations 16 and 17, a lateral control command value θ0,cmdis a control input of the known nominal model. The controller may be freely designed by separating the disturbance θDOB.

Herein, kn,Ln, and τn indicate average values of values thereof.

Herein, K indicates the feedback gain.

Equation 18 is an equation for confirming controller suitability (lateral error convergence).

Herein, the curvature error is a value obtained by subtracting a current curvature from a required curvature. That is, it is ρe=ρd−ρ It indicates that the error dynamics model is stable when K is designed such that (Ln+K)>o. As a result, the proposed controller may achieve a design goal (ρe=o).

Equation 19 is an equation defining the final steering control command θcmd.

θFFindicates the feedforward control value, θFBindicates the feedback control value, θDOBindicates the disturbance observer.

θFFserves as an upfront compensation for a dynamic delay of the actuator.

θFBis designed to feed back the current rotational radius of the vehicle. This feedback term may compensate for curvature errors in transient phases when the vehicle does not behave depending on a predicted motion model. θFBis designed to compensate for disturbances and modeling errors.

When Equation 19 is expanded, Equation 20 is shown below.

InFIG.3B, the disturbance observer209inputs an output value (output value outputted through Equation 20) outputted from the sensing device200to Gn(s)−1, and subtracts the output value of Gn(s)−1and the input value inputted to G(s), and then filters a subtracted value through Q(s). In this case, the output value of G(s) becomes the input value of Gn(s)−1, and the output value of Gn(s)−1must be the same as the input value of G(s).

Accordingly, a value obtained by subtracting the input value of G(s) from the output value of Gn(s)−1becomes a disturbance d.

The disturbance d is filtered in Q(s), and the filtered disturbance becomes θDOB.

In addition, a rotational curvature calculator215calculates a rotational curvature ρ of the vehicle using the output value output from the sensing device200, and the calculator216subtracts the rotational curvature ρ of the vehicle from a target curvature ρdcalculated by a target curvature generator201.

A gain device217multiplies a value obtained by subtracting the rotational curvature ρ of the vehicle from the target curvature ρdby the feedback gain K.

Accordingly, the system may produce the lateral control command θcmd by summing a value

obtained by multiplying the sum of the output value of the differential controller203and the output value of the feedback controller205by a reciprocal of the gear ratio (1/kn) and

outputted from the disturbance observer209. Then, the optimal lateral control command θcmd may be derived by applying it to the feedback controller205and the disturbance observer209based on vehicle movement information (yaw rate, vehicle speed) depending on the lateral control command θcmd.

The sensing device200may be provided in the vehicle to obtain surrounding information of the vehicle. As an example, the sensing device200may include a camera210that acquires surrounding lane information of the vehicle or an image of a vehicle in front, a yaw rate sensor220that detects a yaw rate of the vehicle, and the like.

For example, the sensing device200may be connected to the processor130through wireless or wired communication, and may directly or indirectly transmit the surrounding lane information of the vehicle or image information related to the front vehicle to the processor130.

The steering control device300may be configured to control a steering angle of a vehicle, and may include a steering wheel, an actuator interlocked with the steering wheel, and a controller controlling the actuator.

The braking control device400may be configured to control braking of the vehicle, and may include a controller that controls a brake thereof.

An engine control device500may be configured to control engine driving of a vehicle, and may include a controller that controls a speed of the vehicle.

Hereinafter, a lane keeping control method according to an exemplary embodiment of the present disclosure will be described in detail with reference toFIG.4.FIG.4illustrates a flowchart for describing a lane keeping control method based on yawrate feedback according to an exemplary embodiment of the present disclosure.

Hereinafter, it is assumed that the lane keeping control apparatus100of the ofFIG.1performs processes ofFIG.4. In addition, in the description ofFIG.4, operations described as being performed by a device may be understood as being controlled by the processor130of the lane keeping control apparatus100.

Referring toFIG.4, the lane keeping control apparatus100receives the lane central distance error ycamto a center of a lane on a gazing distance x from the camera210(S101), and calculates a target rotational radius R for the vehicle to reach the center of the lane by using the lane central distance error ycamfrom the gaze distance x (S102).

It receives vehicle information values such as a vehicle speed and a yaw rate from the in-vehicle sensing device200(S103).

Accordingly, the lane keeping control apparatus100calculates the lateral control command value θcmd based on Equation 20 based on a target rotational radius, vehicle information, and designed parameters (S104).

As such, according to the present disclosure, disturbance may be eliminated by designing a new kinetic model that can take a time delay into account, assuming that disturbances (e.g., time delay parameters, etc.) may also exist in kinetic model parameters, and designing the disturbance observer209based on a dynamics model considering the time delay, and the differential controller203and the rotational radius feedback controller205may be designed based on a known nominal model with the disturbance removed.

That is, according to the present disclosure, a more accurate lateral control command value may be generated by calculating the lateral control command value through the dynamics model reflecting the dynamic time delay, the disturbance observer reflecting the dynamics model, the differential controller, and the feedback controller, thereby performing stable lane keeping control.

FIG.5illustrates a lane keeping control effect on a straight road according to an exemplary embodiment of the present disclosure, andFIG.6illustrates a lane keeping control effect on a complex road (including a straight road and s curved road) according to an exemplary embodiment of the present disclosure.

Referring to a view501ofFIG.5, it can be seen that oscillation severely occurs during lateral control by using an existing pur pursuit method on a straight road, but there is almost no oscillation during lateral control by using the feedback method of the present disclosure. Referring to a view502, it can be seen that an average value of the lateral control error is significantly reduced, and a maximum value of the lateral control error is reduced.

Referring to a view601ofFIG.6, it can be seen that there is a large deviation in a lateral control error during lateral control by using the existing pur pursuit method on a complex road, but the deviation in the lateral control error is small during lateral control by using the feedback method of the present disclosure. Referring to a view602, it can be seen that an average value of the lateral control error is significantly reduced, and a maximum value of the lateral control error is reduced.

FIG.7illustrates a computing system according to an exemplary embodiment of the present disclosure.

Referring toFIG.7, the computing system1000includes at least one processor1100connected through a bus1200, a memory1300, a user interface input device1400, a user interface output device1500, and a storage1600, and a network interface1700.

Accordingly, steps of a method or algorithm described in connection with the exemplary embodiments disclosed herein may be directly implemented by hardware, a software module, or a combination of the two, executed by the processor1100. The software module may reside in a storage medium (i.e., the memory1300and/or the storage1600) such as a RAM memory, a flash memory, a ROM memory, an EPROM memory, an EEPROM memory, a register, a hard disk, a removable disk, and a CD-ROM.

An exemplary storage medium is coupled to the processor1100, which can read information from and write information to the storage medium. Alternatively, the storage medium may be integrated with the processor1100. The processor and the storage medium may reside within an application specific integrated circuit (ASIC). The ASIC may reside within a user terminal. Alternatively, the processor and the storage medium may reside as separate components within the user terminal.

The above description is merely illustrative of the technical idea of the present disclosure, and those skilled in the art to which the present disclosure pertains may make various modifications and variations without departing from the essential characteristics of the present disclosure.

Therefore, the exemplary embodiments disclosed in the present disclosure are not intended to limit the technical ideas of the present disclosure, but to explain them, and the scope of the technical ideas of the present disclosure is not limited by these exemplary embodiments.

The protection range of the present disclosure should be interpreted by the claims below, and all technical ideas within the equivalent range should be interpreted as being included in the scope of the present disclosure.