KR20150051548A

KR20150051548A - Driver assistance systems and controlling method for the same corresponding to dirver's predisposition

Info

Publication number: KR20150051548A
Application number: KR1020130133126A
Authority: KR
Inventors: 배상진; 신승환
Original assignee: 현대오트론 주식회사
Priority date: 2013-11-04
Filing date: 2013-11-04
Publication date: 2015-05-13

Abstract

The present invention relates to a driver assistance system and a control method for the same corresponding to dirver′s predisposition. The control method for the driver assistance system corresponding to dirver′s predisposition according to an embodiment of the present invention comprises: a step where the driver of a vehicle is recognized; a step where a learning threshold value calculated from the relative distance and speed between the vehicle and a target object when a brake signal is input is set according to the recognized driver based on an expected collision time; a step of notifying the driver of the vehicle of the danger in accordance with the expected collision time, which is calculated from the learning threshold value and the relative distance and speed between the vehicle and a new target object; and a step of braking the vehicle in accordance with the expected collision time, which is calculated from the learning threshold value and the relative distance and speed between the vehicle and the new target object.

Description

Technical Field [0001] The present invention relates to a driver assistance system and a control method thereof,

BACKGROUND OF THE INVENTION 1. Field of the Invention [0002] The present invention relates to a driving assistance system that reflects a tendency of a driver and a control method thereof, and more particularly, to a driving assistance system that reflects a braking input tendency of a driver and a control method thereof.

The driver assistance system is a safety device that detects the danger and notifies the driver of the risk of an accident through visual, auditory and tactile factors, as well as a vehicle safety device that actively performs speed reduction or braking for avoiding frontal collision to be. In addition, the driving assistance system can perform lane departure warning, blind spot monitoring, and improved rearward surveillance.

The driving assist system is divided into various types according to its functions. The Forward Collision Warning System (FCW) is a system that provides visual, auditory, and tactile warning to drivers for the purpose of avoiding collision with the forward vehicle by detecting the vehicle in the same direction ahead of the driving lane to be.

The Advanced Emergency Braking System (AEBS) detects the possibility of collision with an automobile located in front of the driving lane and warns the driver. If the driver does not respond or it is determined that a collision is inevitable, It is a system for automatically decelerating the vehicle for the purpose of making it possible.

The Adaptive Cruise Control (ACC) automatically detects the vehicle in the same direction in front of the driving lane according to the driver's setting conditions and automatically adjusts and decelerates according to the speed of the vehicle and maintains the safety distance And automatically runs at the target speed.

Such a driving assist system operates according to a certain standard of the manufacturer, and thus the driving habits of the driver are not reflected.

SUMMARY OF THE INVENTION [0006] The present invention provides a driver assistance system and a control method thereof, which reflect a tendency of a driver.

The problems of the present invention are not limited to the above-mentioned problems, and other problems not mentioned can be clearly understood by those skilled in the art from the following description.

According to an aspect of the present invention, there is provided a method of controlling a driver assistance system that reflects a driver's tendency according to an embodiment of the present invention includes: recognizing a driver driving a vehicle; Setting a learning threshold value for each recognized driver based on a collision estimated time calculated from a relative distance and a relative velocity with respect to a target object when a braking signal of the vehicle is input; Warning the driver of the vehicle according to the collision estimated time calculated from the relative distance between the set learning threshold value and the new target object and the relative speed; And braking the vehicle according to a collision expected time calculated from a relative distance between the set learning threshold and a new target object and a relative speed.

According to an aspect of the present invention, there is provided a method of controlling a driver assistance system that reflects a driver's tendency according to an embodiment of the present invention includes: recognizing a driver driving a vehicle; Calculating a collision expected time from a relative distance and a relative speed with respect to the target object; Storing a calculated collision prediction time when the calculated collision prediction time is less than a set value when a braking signal of the vehicle is input; And calculating and storing a learning threshold value for each recognized driver from the stored estimated collision time.

According to an aspect of the present invention, there is provided a driving assistance system including a radar module for sensing a relative distance and a relative speed with respect to an object, A camera module for capturing an image outside the vehicle and recognizing a target object; A driver recognition module for recognizing a driver driving the vehicle; A braking input module for outputting a braking signal for braking the vehicle in response to a driver's operation; And calculating a collision predicted time from a relative distance and a relative speed with respect to the target object detected by the radar module, and based on the calculated collision estimated time when the braking signal is input from the braking input module, And a controller for setting a learned threshold value for each recognized driver.

The details of other embodiments are included in the detailed description and drawings.

According to the driving assistance system and the control method of the present invention, one or more of the following effects can be obtained.

First, there is an advantage that an automatic emergency braking system and / or an adaptive cruise control system that reflects the driver's braking input tendency can be implemented.

Second, there is an advantage that the driver's tendency can be accurately reflected by calculating the learning threshold value from the collision prediction time calculated from the relative distance and the relative velocity with the target object in the braking of the driver.

Third, there is an advantage in that even if a driver operates a vehicle by setting a learning threshold value for each driver, the driver's tendency can be reflected.

The effects of the present invention are not limited to the effects mentioned above, and other effects not mentioned can be clearly understood by those skilled in the art from the description of the claims.

1 is a block diagram of a driving assistance system according to an embodiment of the present invention.
2 is a diagram illustrating the operation of a vision module and a radar module of a driving assistance system according to an embodiment of the present invention.
3 is a flowchart illustrating a method of learning a learning threshold value in a driving assistance system control method according to an embodiment of the present invention.
FIG. 4 is a flowchart illustrating an automatic emergency braking method using a learning threshold value in a driving assistance system control method according to an exemplary embodiment.

BRIEF DESCRIPTION OF THE DRAWINGS The advantages and features of the present invention and the manner of achieving them will become apparent with reference to the embodiments described in detail below with reference to the accompanying drawings. The present invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art. To fully disclose the scope of the invention to those skilled in the art, and the invention is only defined by the scope of the claims. Like reference numerals refer to like elements throughout the specification.

Hereinafter, the present invention will be described with reference to the drawings for explaining a driving assistance system and a control method thereof according to embodiments of the present invention.

FIG. 1 is a block diagram of a driving assistance system according to an embodiment of the present invention, and FIG. 2 is a diagram illustrating an operation of a vision module and a radar module of a driving assist system according to an embodiment of the present invention.

A driving assist system according to an embodiment of the present invention includes a radar module 132 for detecting a relative distance and a relative speed with respect to an object, a vision module 131 for photographing an image outside the vehicle and recognizing a target object, A braking input module 122 for outputting a braking signal for braking the vehicle in response to a driver's operation and a relative distance between a target object sensed by the radar module 132 when the braking signal is inputted from the braking input module 122 And a controller 111 for calculating a predicted collision time from the relative speed and setting a learning threshold value based on the calculated collision prediction time.

The acceleration input module 121 is an operation device of the driver for increasing the speed of the vehicle. The acceleration input module 121 increases the power of the power / brake module 192 to increase the speed of the vehicle. Generally, the acceleration input module 121 increases the speed of the vehicle by increasing the rotation of the vehicle engine. The acceleration input module 121 is generally provided as an accelerator pedal in the form of a pedal below the driver's seat of the vehicle.

The acceleration input module 121 can input the acceleration degree according to the operation of the driver. If the acceleration input module 121 is an accelerator pedal, the degree of acceleration may be input according to the pedestrian pressure.

When the driver operates the acceleration input module 121, the acceleration input module 121 outputs an acceleration signal including the acceleration degree to the controller 111. [ The controller 111 controls the power / braking module 192 according to the input acceleration signal to accelerate the vehicle. According to the embodiment, the acceleration input module 121 can directly control the power / braking module 192 to accelerate the vehicle.

The brake input module 122 is an operation device of the driver for reducing the speed of the vehicle or stopping the vehicle. The braking input module 122 reduces the power of the power / braking module 192 or generates a braking force to decelerate or stop the vehicle. Generally, the braking input module 122 operates a brake that applies a frictional force to a disk of a vehicle's wheel to reduce the speed of the vehicle. Depending on the embodiment, the braking input module 122 may directly reduce the rotation of the vehicle engine or operate a reduction device such as a retarder. The braking input module 122 is generally provided as a brake pedal in the form of a pedal below the driver's seat of the vehicle.

The braking input module 122 can be inputted with the degree of deceleration according to the operation of the driver. When the braking input module 122 is a brake pedal, the degree of deceleration may be inputted according to the pedal pressure.

When the driver operates the braking input module 122, the braking input module 122 outputs the braking signal including the degree of deceleration to the controller 111. [ The controller 111 controls the power / braking module 192 according to the input braking signal to decelerate or stop the vehicle. The braking input module 122 may directly control the power / braking module 192 to decelerate or stop the vehicle.

The speed detection module 141 detects the current speed of the vehicle. The speed sensing module 141 senses the rotation speed of the wheels of the vehicle or senses the rotation speed of the output shaft of the transmission connected to the engine of the vehicle to calculate the current speed of the vehicle. The speed sensing module 141 may include a speed sensor for sensing the rotation speed and a processor for calculating the current speed value of the vehicle.

The speed detection module 141 outputs the sensed speed value of the vehicle to the controller 111. [

The posture sensing module 142 senses the posture variation of the vehicle. The posture sensing module 142 senses a variation of at least one of a pitch axis, a yaw axis, and a roll axis and senses a yaw rate in the present embodiment. That is, in the present embodiment, the attitude sensing module 142 senses the yaw rate of the vehicle and senses the degree of rotation of the vehicle. The posture detection module 142 may include a gyro sensor or an acceleration sensor for detecting attitude variation, a processor for calculating a variation value, and the like.

The posture detection module 142 outputs the detected posture variation value of the vehicle to the controller 111. [

The driver recognition module 151 recognizes and distinguishes the driver who is currently driving the vehicle. The driver recognition module 151 can recognize the driver of the vehicle in various ways. The driver recognition module 151 recognizes the driver according to the vehicle smart key, the FOB key, and the remote controller for the vehicle owned by the driver, or recognizes the driver according to the driver's seat setting.

The driver recognition module 151 outputs the recognized driver information to the controller 111. [

The vision module 131 is a device for recognizing an object outside the vehicle by photographing an image outside the vehicle and discriminating the type of the object. The vision module 131 is generally disposed at the front end of the vehicle and photographs an image of the front of the vehicle.

As shown in FIG. 2 (a), the vision module 131 can distinguish the road R and recognize various objects O on the road R to recognize and distinguish the objects. The vision module 131 can recognize whether the object O is a vehicle, a person, or a simple object by recognizing the shape of the object O. In the case of a vehicle, the vision module 131 can discriminate whether it is a passenger car, a truck or a two-

The vision module 131 can recognize the lane L on the road R and discriminate whether the lane L is a general lane or a center line or a curb line or a separate lane. In addition, the vision module 131 can recognize and distinguish a curb or a walk on the road.

The vision module 131 can recognize the lane N between the lane L and the lane L through the recognized lane L. [ The vision module 131 can recognize the lane N in which the subject vehicle H equipped with the vision module 131 is running. The subject vehicle H is a vehicle equipped with the driving assistance system of the present invention. The vision module 131 may also recognize which lane N the recognized object O is located on or the recognized object O lies on the lane L. [

The recognition and the discrimination of the object O can be performed in the vision module 131 itself or in the controller 111 through the image photographed by the vision module 131. [

The vision module 131 has a constant field of view. As shown in FIG. 2 (a), the vision module 131 photographs the objects O in the clock F. FIG. According to the embodiment, the vision module 131 can change the shooting direction up and down and / or left and right. That is, the vision module 131 can change the center of the clock F up and down and / or right and left.

The vision module 131 may include a camera that captures an image, a processor that processes the captured image, and a memory that stores data. According to the embodiment, the vision module 131 may include a driving device capable of changing the photographing direction of the camera.

The vision module 131 may output the photographed image data to the controller 111 or output information of the recognized object O to the controller 111. [

The radar module 132 is a device that emits an electromagnetic wave to a specific object O and then receives an electromagnetic wave reflected from the object O and senses a distance, a position, a direction, and a speed with respect to the object O. The radar module 132 is generally disposed at the front end of the vehicle to calculate a distance to a specific object O in front of the vehicle and the like. According to an embodiment, the radar module 132 may be a lidar that fires a laser at the object O. [

The radar module 132 detects the distance, the position, the direction, the speed, and the like to the target object T which is a specified one among the various objects O as shown in FIG. 2 (b). The target object T is selected from the data detected by the radar module 132 and the vision module 131 as the object O to be tracked by the controller 111 and is generally set to the radar module 132 and the vision module 131, Is an object O recognized as a vehicle at a distance closest to the front of the subject vehicle H on the lane N in which the subject vehicle H is installed. The radar module 132 can sense the relative distance and the relative speed with respect to the target object T. [

The radar module 132 may include a radar that emits electromagnetic waves, a processor that processes information about the electromagnetic waves received by the radar, and a memory that stores data.

The radar module 132 may output information such as the distance to the object O, the position, the direction, and the velocity to the controller 111. In this embodiment, And the relative speed to the controller 111.

The warning module 191 is a device for giving a warning to the driver who drives the vehicle. The warning module 191 can warn various audiences visually, audibly and tactually according to the embodiment. The warning module 191 may display a warning on the dash panel of the driver's seat, head-up display, navigation, integrated information display device and the like. The warning module 191 can aloud a warning through the speaker of the vehicle. The warning module 191 can warn the driver by vibrating the handle of the vehicle or tightening the seat belt.

The warning module 191 may operate under the control of the controller 111 to alert the driver.

The power / brake module 192 is a device that accelerates, decelerates, or brakes the vehicle. The power / brake module 192 may include an engine and / or a motor that generates a rotational force to rotate the wheels of the vehicle, and a transmission that changes the rotation ratio of the engine and / or the motor. The power / brake module 192 may include a brake and / or retarder that generates a braking force or reduces rotation of the engine and / or motor.

The power / braking module 192 may operate under the control of the controller 111 or may be operated by the acceleration input module 121 or the braking input module 122.

Memory 112 stores programs, instructions, and data. The controller 111 stores data in the memory 112 or calls programs, commands, or data stored in the memory 112. [

The controller 111 includes an acceleration input module 121, a braking input module 122, a vision module 131, a radar module 132, a velocity detection module 141, a posture detection module 142, And controls the warning module 191 and the power / brake module 192 according to the processed result. The controller 111 may include a communication device such as a CAN (Controller Area Network) for data communication with each module.

The controller 111 calculates the collision predicted time from the relative distance and the relative speed with respect to the target object T sensed by the radar module 132. [ The controller 111 calculates the collision estimated time tc from the relative distance D with the target object T and the relative velocity V between the target object T as follows.

(Tc) = relative distance (D) / relative speed (V)

The controller 111 continuously calculates the collision expected time tc for the target object T for various functions of the driving assistance system.

The controller 111 stores the collision prediction time in the memory 112 when the collision prediction time tc when the braking signal is inputted from the braking input module 122 is smaller than the set value. The set value is preliminarily set as the reference collision anticipated time value and stored in the memory 112. The controller 111 calls the set value stored in the memory and compares it with the calculated collision expected time tc.

The controller 111 calculates a collision prediction time each time a braking signal is input from the braking input module 122, and stores the calculated collision prediction time in the memory 112 when the calculated collision prediction time is smaller than the set value. Accordingly, the memory 112 stores a plurality of expected collision times.

The controller 111 calculates a learning threshold value from the collision predicted time tc stored in the memory 112. [ The controller 111 may calculate the learning threshold value in various ways based on the estimated collision time tc stored in the memory 112. In this embodiment, The moving average for the estimated time tc is calculated, and the calculated moving average value is set as the learning threshold value. For example, the controller 111 sets an average of 10 recently estimated collision times as learning thresholds.

The controller 111 preferably calculates a learning threshold value for each driver recognized by the driver recognition module 151. [ The controller 111 stores the estimated collision time calculated when the driver recognized by the driver recognition module 151 operates the braking input module 122 in the memory 112 as the collision expected time of the corresponding driver. The controller 111 calculates the learning threshold value of each driver from the estimated collision time stored for each driver.

The controller 111 stores the calculated learning threshold value in the memory 112. [ The controller 111 preferably stores the learning threshold value for each driver recognized by the driver recognition module 151 in the memory 112. [

The controller 111 operates the warning module 191 according to the estimated collision time T 'with the new target object T' and the set learning threshold value to warn the driver or operates the power / braking module 192 Brakes the vehicle. The new target object T 'may be the same as or different from the above-described target object T as the target object being tracked by the current controller 111.

The controller 111 preferably calls the learning boundary value from the memory 112 according to the driver recognized by the driver recognition module 151. [

The controller 111 calculates the collision estimated time tc 'from the relative distance and the relative speed with respect to the new target object T' sensed by the radar module 132. The controller 111 operates the warning module 191 to warn the driver when the collision estimated time tc 'for the new target object T' is less than the value obtained by adding the warning weight to the learning threshold value. The controller can compare the learning threshold value with the estimated collision time tc 'by adding or multiplying the warning weight value. In this embodiment, the learning threshold value is multiplied by the warning weight value and compared with the estimated collision time tc'.

The controller 111 operates the power / braking module 192 to brake the vehicle when the collision estimated time tc 'for the new target object T' is less than the learning threshold value multiplied by the braking weight.

The warning weight and the braking weight are preset and stored in the memory 112, and the warning weight is set to a value larger than the braking weight.

3 is a flowchart illustrating a method of learning a learning threshold value in a driving assistance system control method according to an embodiment of the present invention.

The driver recognition module 151 recognizes the driver (S210). The driver recognition module 151 can recognize the driver of the vehicle in various ways. In this embodiment, the driver recognition module 151 recognizes the driver according to the vehicle smart key owned by the driver. The driver recognition module 151 outputs the recognized driver information to the controller 111 and the controller 111 stores the driver information in the memory 112. [

The radar module 132 detects the relative distance and the relative speed with respect to the target object T recognized by the vision module 131 (S220). The target object T is selected from the data detected by the radar module 132 and the vision module 131 as the object O to be tracked by the controller 111 and is generally set to the radar module 132 and the vision module 131, Is an object O recognized as a vehicle at a distance closest to the front of the subject vehicle H on the lane N in which the subject vehicle H is installed.

The radar module 132 outputs the relative distance and the relative speed to the detected target object T to the controller 111. [

The controller 111 calculates the collision expected time tc from the relative distance and the relative velocity with the target object T (S230). The controller 111 calculates the collision estimated time tc from the relative distance D between the target object T and the target object T and the relative velocity V between the target object T and the target object T as follows.

(Tc) = relative distance (D) / relative speed (V)

The controller 111 determines whether the estimated collision time tc calculated at the time of inputting the braking signal is smaller than the set value (S240). When the driver operates the braking input module 122, the braking input module 122 outputs a braking signal to the controller 111, and the controller 111 determines that the estimated collision time tc when the braking signal is input is set Value.

If the calculated collision expected time tc is equal to or greater than the set value, the controller 111 continues to calculate the collision estimated time tc (S230).

If the calculated collision prediction time tc is smaller than the set value, the controller 111 stores the calculated collision prediction time tc in the memory 112 (S250). The controller 111 calculates a collision prediction time each time a braking signal is input from the braking input module 122, and stores the calculated collision prediction time in the memory 112 when the calculated collision prediction time is smaller than the set value. Accordingly, the memory 112 stores a plurality of expected collision times.

The controller 111 preferably stores the estimated collision time for each driver by using the driver information stored in the memory 112. [ The controller 111 preferably stores the estimated collision time for the driver recognized by the driver recognition module 151 as the collision expected time of the corresponding driver.

According to the embodiment, the controller 111 determines whether the collision expected time tc when the braking signal is input is less than or equal to the set value, and when the collision estimated time tc is less than or equal to the set value, (tc) may be stored in the memory 112.

The controller 111 stores the moving average value for the estimated collision time as a learned threshold value of the recognized driver (S260). In the embodiment, the controller 111 calculates a moving average of a plurality of collision estimated time tc stored in the memory 112, and sets the calculated moving average value as a learning threshold value. For example, the controller 111 sets an average of 10 recently estimated collision times as learning thresholds.

The controller 111 calculates a learning threshold value for each driver recognized by the driver recognition module 151. [ The controller 111 calculates the learning threshold value of each driver from the estimated collision time stored for each driver.

The controller 111 stores the calculated learning threshold value in the memory 112. [ The controller 111 stores the learning threshold value for each driver recognized by the driver recognition module 151 in the memory 112. [

FIG. 4 is a flowchart illustrating an automatic emergency braking method using a learning threshold value in a driving assistance system control method according to an exemplary embodiment.

The driver recognition module 151 recognizes the driver (S310). The driver recognition module 151 outputs the recognized driver information to the controller 111 and the controller 111 stores the driver information in the memory 112. [

The controller 111 determines whether the driving assist system is operating (S320). The controller 111 judges whether the automatic emergency braking system among the driving assist systems is in operation.

When the driving assist system is in operation, the radar module 132 senses the relative distance and the relative speed with respect to the target object T 'recognized by the vision module 131 (S330). The target object T 'may be the same as or different from the above-described target object T as the target object being tracked by the current controller 111. The radar module 132 outputs the relative distance and the relative speed to the detected target object T 'to the controller 111.

The controller 111 calculates the collision expected time tc from the relative distance and the relative speed with respect to the target object T '(S330). The controller 111 calculates the collision estimated time tc 'from the relative distance D between the target object T' and the target object T as follows.

The estimated collision time (tc ') = relative distance (D) / relative speed (V)

The controller 111 continuously calculates the collision expected time tc 'for the target object T' in order to realize the function of the driving assist system.

The controller 111 calls the learning threshold of the recognized driver (S350). The controller 111 calls the driver information stored in the memory 112 and calls the learning threshold of the driver from the memory 112. [

This step may be performed simultaneously with step S310. For example, the controller 111 may call the learning boundary value from the memory 112 according to the driver recognized by the driver recognition module 151. [

The controller 111 determines whether the estimated collision time tc 'is smaller than a value obtained by multiplying the learning threshold value by the warning weight (S360). According to the embodiment, the controller 111 can determine whether the collision estimated time tc 'is less than the learning threshold value plus the weight.

The controller 111 continues to calculate the estimated collision time tc 'at step S340 when the estimated collision time tc' is equal to or greater than the value obtained by multiplying the learning threshold value by the warning weight. The warning weight is preset and stored in the memory 112. The controller 111 calls the alert weight stored in the memory 112, multiplies it by the learning threshold value, and compares it with the estimated collision time tc '.

The controller 111 operates the warning module 191 to warn the driver when the collision estimated time tc 'is smaller than the learning threshold value multiplied by the warning weight (S370). The warning module 191 displays a warning on the instrument panel of the driver's seat, a head-up display, a navigation system, an integrated information display device, a warning sound through the speaker of the vehicle, a vibration of the steering wheel of the vehicle, I can warn you.

According to an embodiment, the controller 111 may alert the driver by operating the warning module 191 if the collision prediction time tc 'is less than or equal to the learning threshold multiplied by the warning weight.

The controller 111 determines whether the estimated collision time tc 'is smaller than the learning threshold multiplied by the braking weight (S380). The braking weight is preset and stored in the memory 112. The controller 111 calls the braking weight stored in the memory 112, multiplies it by the learning threshold, and compares it with the estimated collision time tc '. The braking weight is preferably smaller than the warning weight.

The controller 111 continues to calculate the collision estimated time tc '(S340) when the estimated collision time tc' is equal to or greater than the value obtained by multiplying the learning threshold value by the braking weight.

The controller 111 operates the power / braking module 192 to brake the vehicle when the estimated collision time tc 'is smaller than the value obtained by multiplying the learning threshold value by the braking weight value (S390). The brake and / or retarder of the power / brake module 192 reduces the rotation of the engine and / or the motor under the control of the controller 111 or generates a braking force to brake the vehicle. The controller 111 controls the power / braking module 192 when the collision expected time tc 'is smaller than the value obtained by multiplying the learning threshold value by the braking weight, even when the braking signal is not output from the braking input module 122 Automatically brakes the vehicle.

According to the embodiment, the controller 111 may operate the power / braking module 192 to brake the vehicle when the estimated collision time tc 'is less than or equal to the learning threshold value multiplied by the braking weight.

According to the embodiment, when the adaptive cruise control system is in operation, the controller 111 may determine whether the collision expected time tc 'is less than the learning threshold multiplied by the deceleration weight. If the estimated collision time tc 'is smaller than the learning threshold value multiplied by the deceleration weight, the power / braking module 192 can be operated to decelerate or brak down the vehicle. The deceleration weight is preferably larger than the braking weight.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments, but, on the contrary, It should be understood that various modifications may be made by those skilled in the art without departing from the spirit and scope of the present invention.

Claims

A control method of a driving assist system reflecting a tendency of a driver,
Recognizing a driver driving the vehicle;
Setting a learning threshold value for each recognized driver based on a collision estimated time calculated from a relative distance and a relative velocity with respect to a target object when a braking signal of the vehicle is input;
Warning the driver of the vehicle according to the collision estimated time calculated from the relative distance between the set learning threshold value and the new target object and the relative speed; And
And braking the vehicle in accordance with the estimated collision time calculated from the relative distance between the set learning threshold value and the new target object and the relative speed.

The method according to claim 1,
Wherein the step of warning the driver of the vehicle alerts the driver of the vehicle when the estimated collision time is less than a value obtained by multiplying the learning threshold by the warning weight,
The step of braking the vehicle may include braking the vehicle if the expected collision time is less than a value obtained by multiplying the learning threshold value by the braking weight,
Wherein the warning weight is greater than the braking weight.

A control method of a driving assist system reflecting a tendency of a driver,
Recognizing a driver driving the vehicle;
Calculating a collision expected time from a relative distance and a relative speed with respect to the target object;
Storing a calculated collision prediction time when the calculated collision prediction time is less than a set value when a braking signal of the vehicle is input; And
And calculating and storing a learning threshold value for each of the recognized drivers from the stored estimated collision time.

The method of claim 3,
Wherein the target object is selected from a radar module that detects a distance and a speed between a vision module for capturing an image of the outside of the vehicle and an object,
Wherein the relative distance to the target object and the relative speed are detected from the radar module.

The method of claim 3,
Calculating a collision expected time with a new target object;
Warning the driver of the vehicle when the collision expected time is less than the learning threshold multiplied by the warning weight; And
And braking the vehicle if the estimated collision time is less than a value obtained by multiplying the learning threshold value by the braking weight value.

6. The method of claim 5,
Wherein the warning weight is greater than the braking weight.

A driver assistance system reflecting driver's propensity,
A radar module for sensing a relative distance and a relative speed with the object;
A camera module for capturing an image outside the vehicle and recognizing a target object;
A driver recognition module for recognizing a driver driving the vehicle;
A braking input module for outputting a braking signal for braking the vehicle in response to a driver's operation; And
Calculating a collision predicted time from a relative distance and a relative speed with respect to the target object sensed by the radar module, and based on the calculated collision estimated time when the braking signal is input from the braking input module, And a controller for setting a learning threshold for each recognized driver.

8. The method of claim 7,
A warning module for warning a driver driving the vehicle; And
Further comprising a power / brake module for braking the vehicle,
Wherein the controller operates the warning module according to the estimated collision time between the set learning threshold value and a new target object recognized by the camera module, and operates the power / brake module to brake the vehicle.

9. The method of claim 8,
Wherein the controller operates the warning module if the expected collision time is less than a value obtained by multiplying the learning threshold by an alert weight and if the expected collision time is less than a value obtained by multiplying the learning threshold by a braking weight, Operating the module to brake the vehicle,
Wherein the warning weight is greater than the braking weight.