KR102216775B1 - Driving assistant apparatus for older driver - Google Patents

Abstract

A driver driving assistance apparatus and method are disclosed. The driver's driving assistance apparatus of the present invention includes a photographing unit for photographing a driver; A driver determination unit that analyzes the image captured by the photographing unit to determine whether the driver is an elderly driver or a general driver; A driver recognition unit that recognizes a driver by analyzing the image captured by the photographing unit; And a driving support system based on at least one of a driver's driving propensity data previously stored and driver driving propensity profile data of a driver recognized by the driver recognition unit according to whether the driver is determined to be an elderly driver by the driver determination unit. It characterized in that it comprises a control module to control.

Description

Driver driving support device and method {DRIVING ASSISTANT APPARATUS FOR OLDER DRIVER}

The present invention relates to an apparatus and method for supporting driver driving, and more particularly, to an apparatus and method for supporting driver driving based on machine learning for preventing an accident of an elderly driver.

In general, elderly drivers are characterized by inferior physical abilities, including muscle strength, vision, and hearing, and cognitive abilities such as short-term memory and spatial perception, compared to general drivers.

In recent years, many traffic accidents of elderly drivers have occurred. The total number of traffic accident deaths has decreased, but the number of elderly traffic accident deaths is increasing. In particular, traffic accidents for elderly drivers over 65 years of age are on a relatively large increase, so safety management needs to be strengthened.

Accordingly, in order to prevent accidents caused by elderly drivers, a plan for aging drivers to voluntarily return their licenses or to shorten the driver's license renewal cycle for elderly drivers is proposed, but a system that determines and supports driving as a vehicle convenience service. Is not presented.

The background technology of the present invention is disclosed in Korean Patent Laid-Open Publication No. 10-1172049 (2012.08.01)'a safety alarm system that generates a vehicle safety warning sound for an elderly driver'.

The present invention was invented to improve the above-described problem, and an object according to an aspect of the present invention is to recognize whether a driver is an elderly driver or a general driver by analyzing an image photographed of a driver, and to control a driving assistance system according to the recognition result. It is to provide a driver driving assistance device and method.

A driver driving assistance device according to an aspect of the present invention includes a photographing unit for photographing a driver; A driver determination unit that analyzes the image captured by the photographing unit to determine whether the driver is an elderly driver or a general driver; A driver recognition unit that recognizes a driver by analyzing the image captured by the photographing unit; And a driving support system based on at least one of a driver's driving propensity data previously stored and driver driving propensity profile data of a driver recognized by the driver recognition unit according to whether the driver is determined to be an elderly driver by the driver determination unit. It characterized in that it comprises a control module to control.

The driver determination unit of the present invention is characterized in that it determines whether the driver is an elderly driver or a general driver by analyzing the image captured by the photographing unit based on a machine learning method.

The control module of the present invention comprises: a driving tendency fusion value generating unit for generating a driving tendency fusion value by fusing the elderly driver driving tendency data and the driver driving tendency profile data; An action risk prediction unit for predicting an action risk of a vehicle according to a driving situation and a surrounding situation based on the driving tendency fusion value generated by the driving tendency fusion value generating unit; A simulation unit that simulates a vehicle behavior in advance according to an action risk of the vehicle predicted by the action risk prediction unit; And when the driver is determined to be an elderly driver by the driver determination unit, the driving tendency fusion value generation unit is controlled to generate a driving tendency fusion value, and the action risk prediction unit is used to predict the action risk of the vehicle, and then the simulation unit is simulated. It characterized in that it comprises a control unit for controlling the driving support system according to the result.

The action risk prediction unit of the present invention is characterized in that the action risk of the vehicle is predicted by dividing it into a longitudinal action risk of the vehicle and a lateral action risk of the vehicle.

The control unit of the present invention is characterized in that the control unit determines an operation priority of the driving support system according to a simulation result of the simulation unit and controls the driving support system according to the determined operation priority.

The control module of the present invention includes an action risk prediction unit for predicting an action risk of a vehicle according to a vehicle driving situation and surrounding conditions based on driver driving propensity profile data of a driver recognized by the driver recognition unit; A simulation unit that simulates a vehicle behavior in advance according to an action risk of the vehicle predicted by the action risk prediction unit; And a control unit configured to determine the action risk of the vehicle through the action risk prediction unit when the driver is determined to be a general driver by the driver determination unit, and then control the driving support system according to a simulation result of the simulation unit. To do.

The action risk prediction unit of the present invention is characterized in that the action risk of the vehicle is predicted by dividing it into a longitudinal action risk of the vehicle and a lateral action risk of the vehicle.

The control unit of the present invention is characterized in that the control unit determines an operation priority of the driving support system according to a simulation result of the simulation unit and controls the driving support system according to the determined operation priority.

The present invention is characterized in that it further comprises a driver driving propensity detector for detecting a driver's driving propensity for each driver according to a driver recognized by the driver recognition unit, and storing and updating the detected driver driving propensity data in a database.

A driver driving assistance method according to an aspect of the present invention includes: a photographing unit photographing a driver; Determining whether the driver is an elderly driver or a general driver by analyzing the image captured by the photographing unit by a driver determination unit; Recognizing a driver by analyzing the image captured by the photographing unit by a driver recognition unit; And the control module drives based on at least one of the driving propensity data for the elderly driver previously stored according to whether the driver is recognized as an elderly driver by the driver determination unit and the driver driving propensity profile data of the driver recognized by the driver recognition unit. It characterized in that it comprises the step of controlling the support system.

The driver determination unit of the present invention is characterized in that it determines whether the driver is an elderly driver or a general driver by analyzing the image captured by the photographing unit based on a machine learning method.

In the controlling of the driving support system of the present invention, when the driver is recognized as an elderly driver by the driver determination unit, the elderly driver driving tendency data and the driver driving tendency profile data are fused to generate a driving tendency fusion value, and the generated driving After determining the action risk of the vehicle according to the vehicle driving situation and the surrounding situation based on the propensity fusion value, the driving support system is controlled according to the simulation result by simulating the vehicle behavior in advance according to the action risk of the vehicle. .

In the controlling of the driving assistance system of the present invention, the action risk of the vehicle is predicted by dividing it into a longitudinal action risk of the vehicle and a lateral action risk of the vehicle.

The control unit of the present invention is characterized in that it controls the driving support system according to the determined operation priority by determining an operation priority of the driving support system according to a simulation result.

The controlling of the driving assistance system of the present invention includes: an action risk prediction unit for determining an action risk of a vehicle according to a vehicle driving situation and surrounding conditions based on the driver driving tendency profile data of the driver recognized by the driver recognition unit; A simulation unit that simulates a vehicle behavior in advance according to an action risk of the vehicle predicted by the action risk prediction unit; And if the driver is recognized as a general driver by the driver determination unit, the action risk of the vehicle is determined based on the driver's driving tendency profile data recognized by the driver recognition unit, and then the vehicle behavior is preliminarily determined according to the action risk of the vehicle. It is characterized in that by simulating and controlling the driving support system according to the simulation result.

In the controlling of the driving assistance system of the present invention, the action risk of the vehicle is predicted by dividing it into a longitudinal action risk of the vehicle and a lateral action risk of the vehicle.

In the controlling of the driving support system of the present invention, the driving support system is controlled according to the determined operation priority by determining an operation priority of the driving support system according to a simulation result.

The present invention further comprises the step of detecting the driver's driving tendency for each driver according to the driver recognized by the driver recognition unit, and accumulating and storing the detected driver's driving tendency data in a database to update the driver driving tendency detection unit. do.

A driver's driving support apparatus and method according to an aspect of the present invention provides safe driving and driving convenience suitable for an elderly driver, and thereby prevents a traffic accident of an elderly driver.

1 is a block diagram of a driver driving assistance apparatus according to an embodiment of the present invention.
2 is a block diagram of a control module according to an embodiment of the present invention.
3 is a flowchart of a driver driving assistance method according to an embodiment of the present invention.

Hereinafter, an apparatus and method for supporting driver safety according to an embodiment of the present invention will be described in detail with reference to the accompanying drawings. In this process, the thickness of the lines or the size of components shown in the drawings may be exaggerated for clarity and convenience of description. In addition, terms to be described later are terms defined in consideration of functions in the present invention, which may vary according to the intention or custom of users or operators. Therefore, definitions of these terms should be made based on the contents throughout the present specification.

1 is a block diagram of a driver driving assistance apparatus according to an embodiment of the present invention, and FIG. 2 is a block diagram of a control module according to an embodiment of the present invention.

1 is a driver driving support device according to an embodiment of the present invention, a photographing unit 10, a driver determination unit 20, a driver recognition unit 30, a database unit 40, a control module 50, driving support It includes a system 60 and a driver's driving tendency detection unit 70.

The photographing unit 10 is installed inside the vehicle to photograph the driver's face. The photographing unit 10 may be a Charge-Coupled Device (CCD) camera or an Infra-Red (IR) camera. In addition, the photographing unit 10 is not particularly limited as long as it is an image sensor capable of photographing a driver's face.

The driver determination unit 20 infers the driver from the image captured by the photographing unit 10 to determine whether the driver is an elderly driver or a general driver.

An elderly driver is a driver with a relatively large age, and the driver's age is not particularly limited. General drivers are the rest of the drivers except for elderly drivers.

The driver determination unit 20 uses a machine learning method, for example, a deep learning method, to determine whether the driver is an elderly driver or a general driver by inferring the driver. According to the deep learning method, the driver determination unit 20 receives images of a plurality of general drivers and images of an elderly driver, respectively, divides each of these images, repeats convolution, and detects features of the image. A weight for each feature is detected in the layer, and based on this weight, it is determined whether the corresponding driver is an elderly driver or a general driver.

Meanwhile, in the present embodiment, the use of the deep learning method of the machine learning method as a method of determining whether the driver is an elderly driver or a general driver is described as an example, but the technical scope of the present invention is not limited thereto.

The driver recognition unit 30 recognizes the driver by analyzing the image captured by the photographing unit 10. The driver recognition unit 30 recognizes each driver to identify each driver, and various methods including the machine learning method described above can be used.

The database unit 40 stores driving propensity data for an elderly driver and driver driving propensity profile data.

The driving propensity data for an elderly driver is data on a driving state of an elderly driver and a vehicle state accordingly in various conditions or situations when driving an elderly driver.

Typically, the causes of most accidents of elderly drivers include failure to comply with the duty of safe driving, violation of the signal, non-secure safety distance, and violation of the center line. Accordingly, the elderly driver's driving propensity data may further include a driving operation state and a vehicle state of the elderly driver in each of the above-described situations.

The driver driving tendency profile data is the driving tendency profile data of each driver. That is, the driver drives according to his or her will according to various driving environments or situations, and the driver driving propensity profile data may include a driving operation state and a vehicle state in each of these cases.

Here, the driver may include both an elderly driver and a general driver, and is stored in advance for each driver. Accordingly, in the case of an elderly driver, driver driving propensity profile data of a corresponding elderly driver may be prepared, and in the case of a general driver, driver driving propensity profile data of a corresponding general driver may be prepared.

Accordingly, in the case of an elderly driver, not only the elderly driver driving tendency data for the elderly driver, but also driver driving tendency profile data reflecting the driving tendency of the elderly driver may be provided.

When a corresponding driver is recognized by the driver recognition unit 30, the driver driving propensity detector 70 detects the driver driving propensity for each recognized driver. In addition, the driver driving tendency detection unit 70 accumulates and updates the driver driving tendency data detected for each driver in the database unit 40.

The Driver Assistance System 60 makes it possible to improve driving stability of a vehicle and secure driver's convenience.

Driving assistance system 60 includes Smart Cruise Control (SCC), Advanced Smart Cruse Control (ASCC), Lane Keeping Assist System (LKAS), and SPAS. , Smart Parking Assist System), Intelligent Parking Assist System (ASPAS, Advanced Smart Parking Assist System), TJA (Traffic Jam Assist), Autonomous Emergency Braking System (AEB), Highway Driving Assist System (HAD, Highway) driving assist), Forward Collision-Avoidance Assist (FCA), Forward Collision Warning System (FCWS), Emergency Stop System (ESS), and prevention device (HAC, Hill) Start Assist Control System), Lane Departure Warning System (LDWS), Blind Spot Detection (BSD), and Narrow Path Assist (NPA) may be included.

The control module 50 is based on whether the driver is judged as an elderly driver or a general driver by the driver determination unit 20, and the driver recognized by the driver recognition unit 30 The driving assistance system 60 is controlled based on at least one of the driver's driving tendency profile data.

Referring to FIG. 2, the control module 50 includes a driving propensity fusion value generating unit 51, an action risk predicting unit 52, a simulation unit 53 and a control unit 54.

The driving propensity fusion value generation unit 51 generates a driving propensity fusion value by fusing the driving propensity data of the elderly driver and the driver driving propensity profile data.

When the driver is recognized as an elderly driver by the driver determination unit 20, the driving propensity fusion value generating unit 51 creates a driving propensity fusion value by fusing the elderly driver driving propensity data and the driver driving propensity profile data. In this case, the driving tendency fusion value generating unit 51 may add up and average each of the elderly driver driving tendency data and the driver driving tendency profile data to calculate a driving tendency fusion value as an average value of these data.

The action risk prediction unit 52 predicts the action risk of the vehicle based on the driver's driving tendency.

That is, when the driver is determined to be an elderly driver by the driver determination unit 20, the action risk prediction unit 52 is the driving situation of the vehicle based on the driving tendency fusion value generated by the driving tendency fusion value generation unit 51. And predicts the action risk of the vehicle according to the surrounding situation.

On the other hand, when the driver is determined to be a general driver by the driver determination unit 20, the action risk prediction unit 52 drives the vehicle based on the driver's driver driving propensity profile data recognized by the driver recognition unit 30. Predict the vehicle's action risk according to the situation and surrounding conditions.

In this case, the action risk predictor 52 predicts the action risk of the vehicle by dividing it into a longitudinal action risk of the vehicle and a lateral action risk of the vehicle, respectively. That is, the action risk prediction unit 52 predicts the action risk by classifying the action risk of the vehicle into a longitudinal action risk of a vehicle such as a front collision and a rotational action risk such as a lane departure.

The simulation unit 53 simulates the vehicle behavior in advance according to the action risk of the vehicle predicted by the action risk prediction unit 52.

The control unit 54 controls the driving support system 60 based on at least one of the elderly driver driving tendency data and the driver driving tendency profile data according to whether the driver is an elderly driver or a general driver by the driver determination unit 20 do.

That is, when the driver is determined to be an elderly driver by the driver determination unit 20, the control unit 54 generates a driving tendency fusion value by controlling the driving tendency fusion value generation unit 51, and the action risk prediction unit 52 After predicting the action risk of the vehicle based on the driving propensity fusion value, the driving support system 60 is controlled according to the simulation result of the simulation unit 53 based on the action risk of the vehicle.

On the other hand, if the driver is determined to be a normal driver by the driver determination unit 20, the control unit 54 predicts the action risk of the vehicle through the action risk prediction unit 52, and the simulation result of the simulation unit 53 Controls the driving assistance system 60 according to.

In this case, the control unit 54 determines an operation priority of the driving support system 60 according to the simulation result of the simulation unit 53 and controls the operation according to the determined operation priority. That is, before actually controlling the driving assistance system 60, the control unit 54 performs a simulation for the corresponding control through the simulation unit 53, and according to the simulation result, the elderly driver or general driver needs the most priority. The operation is performed first, and various warnings are output based on the current driver's driving operation, so that optimal driving support can be provided.

Hereinafter, a driver driving assistance method according to an embodiment of the present invention will be described with reference to FIG. 3.

3 is a flowchart of a driver driving assistance method according to an embodiment of the present invention.

Referring to FIG. 3, first, the photographing unit 10 is installed in the interior of the vehicle to photograph the driver's face (S10).

As the driver's face is photographed by the photographing unit 10, the driver recognition unit 30 recognizes the driver by analyzing the image captured by the photographing unit 10 (S20).

Then, the driver driving propensity detection unit 70 monitors the driving operation state or vehicle state of the driver recognized by the driver recognition unit 30 (S30), thereby detecting the driver driving propensity data of the corresponding driver (S40), and the control unit ( 54), the driver's driver driving tendency data is accumulated and stored in the database unit 40 and updated (S50).

Meanwhile, as the driver's face is photographed by the photographing unit 10 in step S10, the driver determination unit 20 infers the driver by analyzing the image photographed by the photographing unit 10, so that the driver is an elderly driver. Whether or not it is a general driver is determined (S60, S70).

In this case, the driver determination unit 20 may use a machine learning method, for example, deep learning, to determine whether the driver is an elderly driver or a general driver.

As a result of the determination in step S70, if the driver is an elderly driver, the control unit 54 controls the driving propensity fusion value generating unit 51 to detect the elderly driver driving propensity data from the database unit 40 (S80).

Meanwhile, the control unit 54 generates a driving tendency fusion value according to whether the driver is an elderly driver or a general driver (S90).

That is, if the driver is an elderly driver, the controller 54 inputs the driving tendency data and the driver driving tendency profile data to the driving tendency fusion value generating unit 51 to generate the driving tendency fusion value. Accordingly, the driving tendency fusion value generation unit 51 generates a driving tendency fusion value by fusion of the elderly driver’s driving tendency data and the driver’s driving tendency profile data, and inputs the generated driving tendency fusion value to the action risk prediction unit 52 do.

On the other hand, if the driver is a general driver, the controller 54 inputs driver driving propensity profile data to the action risk prediction unit 52.

Then, the control unit 54 controls the action risk prediction unit 52 to predict the action risk of the vehicle based on the driver's driving tendency (S100). In this case, the action risk prediction unit 52 determines the action risk of the vehicle The risk of longitudinal action and the risk of transverse action of the vehicle are classified and predicted.

Here, if the driver is an elderly driver, the action risk prediction unit 52 predicts the action risk of the vehicle according to the driving situation of the vehicle and the surrounding situation based on the driving tendency fusion value generated by the driving tendency fusion value generation unit 51. .

On the other hand, when it is determined that the driver is a general driver, the action risk predictor 52 predicts the action risk of the vehicle according to the vehicle driving situation and the surrounding situation based on the driver driving tendency profile data of the corresponding driver.

As the action risk of the vehicle is predicted by the action risk prediction unit 52, the control unit 54 controls the simulation unit 53 to move the vehicle according to the action risk of the vehicle predicted by the action risk prediction unit 52. Simulate in advance (S110).

In this case, the control unit 54 determines the operation priority of the driving support system 60 according to the simulation result of the simulation unit 53, and controls the operation according to the determined operation priority (S120).

That is, before actually controlling the driving support system 60, the control unit 54 performs a simulation to eliminate the risk of the action through the simulation unit 53, and according to the simulation result, the elderly driver or general driver First, a necessary operation is performed first, and various warnings are output based on the current driver's driving operation, so that optimal driving assistance can be achieved.

As described above, the driver's driving support apparatus and method according to an embodiment of the present invention provides safe driving and driving convenience suitable for an elderly driver, thereby preventing a traffic accident of an elderly driver.

The present invention has been described with reference to the embodiments shown in the drawings, but these are only exemplary, and those of ordinary skill in the art to which the present technology pertains, various modifications and other equivalent embodiments are possible. I will understand. Therefore, the true technical protection scope of the present invention should be determined by the following claims.

10: filming department
20: driver judgment unit
30: driver recognition unit
40: database unit
50: control module
51: driving tendency fusion value generation unit
52: action risk prediction unit
53: simulation unit
54: control unit
60: driving assistance system
70: driver driving tendency detection unit

Claims (18)

A photographing unit for photographing the driver;
A driver determination unit that analyzes the image captured by the photographing unit to determine whether the driver is an elderly driver or a general driver;
A driver recognition unit that recognizes a driver by analyzing the image captured by the photographing unit; And
The driving situation and surroundings of the vehicle based on at least one of the driver's driving propensity data previously stored according to whether the driver is determined to be an elderly driver by the driver determination unit and the driver's driving propensity profile data recognized by the driver recognition unit. Driver driving assistance device including a control module that predicts the risk of action of the vehicle according to the situation, simulates the behavior of the vehicle according to the risk of action of the vehicle, and controls the driving assistance system according to the simulation result.
The apparatus of claim 1, wherein the driver determination unit determines whether the driver is an elderly driver or a general driver by analyzing the image captured by the photographing unit based on a machine learning method.
The method of claim 1, wherein the control module
A driving tendency fusion value generator configured to generate a driving tendency fusion value by fusing the elderly driver driving tendency data and the driver driving tendency profile data;
An action risk prediction unit that predicts an action risk of a vehicle according to a driving situation and surrounding conditions based on the driving tendency fusion value generated by the driving tendency fusion value generation unit;
A simulation unit that simulates a vehicle behavior in advance according to an action risk of the vehicle predicted by the action risk prediction unit; And
If the driver is determined to be an elderly driver by the driver determination unit, the driving tendency fusion value generation unit is controlled to generate a driving tendency fusion value, and the action risk prediction unit is used to predict the action risk of the vehicle, and the simulation result of the simulation unit And a control unit for controlling the driving assistance system according to the driver's driving assistance device.
The apparatus of claim 3, wherein the action risk prediction unit predicts the action risk of the vehicle by dividing it into a longitudinal action risk of the vehicle and a lateral action risk of the vehicle.
The driver driving assistance apparatus of claim 3, wherein the control unit determines an operation priority of the driving support system according to a simulation result of the simulation unit and controls the driving support system according to the determined operation priority.
The method of claim 1, wherein the control module
An action risk prediction unit for predicting an action risk of a vehicle according to a vehicle driving situation and a surrounding situation based on the driver driving tendency profile data of the driver recognized by the driver recognition unit;
A simulation unit that simulates a vehicle behavior in advance according to an action risk of the vehicle predicted by the action risk prediction unit; And
And a control unit configured to determine the action risk of the vehicle through the action risk prediction unit when the driver is determined to be a general driver by the driver determination unit, and then control the driving assistance system according to the simulation result of the simulation unit. Driver driving assistance device.
The apparatus of claim 6, wherein the action risk prediction unit predicts the action risk of the vehicle by dividing it into a longitudinal action risk of the vehicle and a lateral action risk of the vehicle.
The driver driving assistance apparatus of claim 6, wherein the control unit determines an operation priority of the driving assistance system according to a simulation result of the simulation unit and controls the driving assistance system according to the determined operation priority.
The method of claim 1, further comprising a driver driving tendency detecting unit for detecting a driver driving tendency for each driver according to a driver recognized by the driver recognition unit and accumulating and storing the detected driver driving tendency data in a database unit for updating. Driver's driving support device.
Photographing a driver by a photographing unit;
Determining whether the driver is an elderly driver or a general driver by analyzing the image captured by the photographing unit by a driver determination unit;
Recognizing a driver by analyzing the image captured by the photographing unit by a driver recognition unit; And
The control module drives the vehicle based on at least one of the driving propensity data for the elderly driver previously stored according to whether the driver is recognized as an elderly driver by the driver determination unit and the driver driving propensity profile data of the driver recognized by the driver recognition unit A driver driving assistance method comprising the step of predicting an action risk of a vehicle according to a situation and surrounding circumstances, simulating a vehicle behavior according to the action risk of the vehicle, and controlling a driving assistance system according to a simulation result.
The method of claim 10, wherein the driver determination unit determines whether the driver is an elderly driver or a general driver by analyzing the image captured by the photographing unit based on a machine learning method.
The method of claim 10, wherein controlling the driving assistance system
When the driver is recognized as an elderly driver by the driver determination unit, a driving tendency fusion value is generated by fusing the elderly driver driving tendency data and the driver driving tendency profile data, and the vehicle driving situation and surrounding situation based on the generated driving tendency fusion value. After determining the action risk of the vehicle according to the method, the driving support system is controlled according to the simulation result by pre-simulating the vehicle behavior according to the action risk of the vehicle.
The method of claim 12, wherein the controlling of the driving assistance system predicts the action risk of the vehicle by dividing it into a longitudinal action risk of the vehicle and a lateral action risk of the vehicle.
The driver driving assistance system of claim 12, wherein the controlling of the driving assistance system comprises determining an operation priority of the driving assistance system according to a simulation result, and controlling the driving assistance system according to the determined operation priority. Way.
The method of claim 12, wherein controlling the driving assistance system
An action risk prediction unit that determines an action risk of a vehicle according to a driving situation and a surrounding situation based on the driver driving tendency profile data of the driver recognized by the driver recognition unit;
A simulation unit that simulates a vehicle behavior in advance according to an action risk of the vehicle predicted by the action risk prediction unit; And
When the driver is recognized as a general driver by the driver determination unit, the action risk of the vehicle is determined based on the driver's driving tendency profile data recognized by the driver recognition unit, and then the vehicle behavior is determined in advance according to the action risk of the vehicle. A driver driving assistance method, characterized in that by simulating and controlling the driving assistance system according to a simulation result.
16. The method of claim 15, wherein the controlling of the driving assistance system predicts an action risk of the vehicle by dividing it into a longitudinal action risk of the vehicle and a lateral action risk of the vehicle.
The driver driving assistance system of claim 15, wherein the controlling of the driving support system comprises determining an operation priority of the driving support system according to a simulation result, and controlling the driving support system according to the determined operation priority. Way.
The method of claim 10, further comprising: a driver driving tendency detecting unit detecting a driver driving tendency for each driver according to a driver recognized by the driver recognition unit, accumulating and storing the detected driver driving tendency data in a database unit, and updating the driving tendency. Driver driving assistance method, characterized in that.

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