KR20190080253A - System for prior setting the function of car facilities by the prospect of driver's riding pattern and method therefor - Google Patents

Abstract

The present invention relates to a system to preconfigure convenience functions of a vehicle and a method thereof. More specifically, the system includes: an area departure determining part determining whether a driver departs from a designated area; a boarding prediction part predicting whether the driver is going to use a vehicle if the driver departs from the designated area; a vehicle arrival time calculating part calculating a time for arrival at the vehicle if the driver is predicted to board the vehicle; a pre-operation control part pre-operating convenience functions of the vehicle; and a driver behavior learning part applying processing data of the area departure determining part, the riding prediction part, the vehicle arrival time calculating part and the pre-operation control part to behavioral patterns of the driver later on by learning the processing data.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a system and a method for predicting convenience functions of a vehicle by predicting boarding of a driver,

The present invention relates to a system and a method for setting convenience functions of a vehicle in advance, and more particularly, to a system and method for setting convenience functions of an automobile, A pre-operation control section for pre-activating a convenience function of the vehicle, and an area departure judging section for judging whether or not the boarding prediction And a driver behavior learning unit that learns the process data of the vehicle arrival time calculation unit and the pre-operation control unit and applies the learned data to the behavior pattern of the future driver. ≪ / RTI >

In general, a technique is implemented in which an application program for communicating with an electronic control unit of a vehicle and operating a convenience function such as an air conditioner or a heater of an automobile is installed in a cellular phone of a driver, These technologies are called telematics-based remote vehicle interworking technologies.

However, it is troublesome for the driver of the vehicle to select and operate the menu by executing the application program in order to operate the air conditioner or the heater in advance, thereby making it easier for the user to preset or operate the convenience function of the vehicle It is necessary to develop the technology that can be used.

The present invention has been devised to overcome the above-mentioned problems of the related art, and it is an object of the present invention to apply a learning algorithm based on artificial intelligence technology to telematics-based remote vehicle interworking technology, Provided is a system for predicting a convenience function of a vehicle and a configuration of the method thereof, which can predict the boarding of a driver on the basis of time, and thereby improve the user's convenience by previously operating the convenience function of the vehicle.

According to another aspect of the present invention, there is provided a system for predicting convenience functions of an automobile through a driver's boarding prediction, the system comprising: an area departure determination unit for determining a departure of a designated area from a driver; A pre-operation control unit for previously operating a convenience function of the vehicle, and a control unit for controlling the pre-operation control unit to pre- And a driver behavior learning unit that learns and applies the process data of the departure prediction unit, the vehicle arrival time calculation unit, and the pre-operation control unit to the behavior pattern of the future driver.

The system for predicting convenience functions of a vehicle and the method thereof according to the present invention predicts a driver's usual behavior pattern using a learning algorithm based on artificial intelligence technology, The driver can perform the operation of the vehicle immediately in a pleasant environment at the same time of boarding the vehicle. Thus, the convenience of the user can be improved, .

1 is a block diagram of a convenience function presetting system for a vehicle of the present invention,
FIG. 2 is a flow chart of a convenience function presetting method for a vehicle according to the present invention,
FIG. 3 and FIG. 4 are conceptual diagrams for judging whether or not a designated area is deviated from the convenience function presetting method of the present invention,
FIG. 5 and FIG. 6 are conceptual diagrams for judging whether or not the convenience function presetting method of the vehicle of the present invention is used,
7 is a view showing an example of a menu screen displayed on the cellular phone at the time of presetting the convenience function of the convenience function presetting method of the car of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, a system for predicting convenience functions of a vehicle and a configuration thereof will be described in detail with reference to the accompanying drawings.

It is to be noted, however, that the drawings are provided as examples for allowing a person skilled in the art to sufficiently convey the spirit of the present invention. Accordingly, the present invention is not limited to the following drawings, but may be embodied in other forms.

In addition, unless otherwise defined, the terms used in the description of the present invention have the same meaning as commonly understood by one of ordinary skill in the art to which the present invention belongs. In the following description and the accompanying drawings, A detailed description of known functions and configurations that may be unnecessarily blurred is omitted.

Fig. 1 is a block diagram of a comfort function presetting system of the present invention.

The convenience function presetting system 1 (hereinafter abbreviated as 'presetting system') of the present invention based on driver's boarding prediction includes an area departure determining unit 10 for determining a departure of a designated area by a driver, A boarding predictor 20 for predicting whether or not a driver leaves the designated area as a result of the judgment by the zone departure judging unit 10; A pre-operation control unit (40) for pre-activating a convenience function of the vehicle in accordance with the arrival time calculated by the vehicle arrival time calculation unit (30) And a driver behavior learning unit (50) that learns and applies the process data of the departure determination unit, the board predictor, the vehicle arrival time calculation unit, and the pre-operation control unit to the behavior pattern of the future driver do.

The area departure judging section 10 is a section for judging whether or not the driver leaves the designated area from the designated area, and the designated area is set as a place frequently accessed by the driver.

For example, the area deviating unit 10 may be a GPS (Global Positioning System) built in the user terminal 100 such as a smartphone of a driver, ) Module to determine whether the driver has left the designated area. The information of the designated area is stored in the interlocked database 60.

The board predictor 20 calculates the boarding pattern information of the user learned by the mechanical learning technique using artificial intelligence based on the result of the area departure determination determined by the area departure determiner 10, It is determined whether or not the driver will ride the vehicle on the basis of the user movement information calculated based on the speed of movement toward the point and the movement distance.

The vehicle arrival time calculation unit 30 calculates the arrival time of the user from the designated area to the user's car when the boarding predictor 20 determines that the driver will board the vehicle.

The timing at which the pre-operation control unit 40 starts operating the vehicle convenience facility is determined in accordance with the arrival time calculated by the vehicle arrival time calculation unit 30. [

The pre-operation control unit 40 controls the operation of the air conditioner 200 by the central control unit 200 of the vehicle through the communication network 300 before the user reaches the vehicle according to the arrival time to the user's vehicle calculated by the vehicle arrival time calculation unit 30. [ , Heater, and the like are generated and transmitted.

The driver behavior learning unit 50 collects all the information processed in the inventive preset system and learns the behavior pattern of the driver in the future using the known artificial intelligence based mechanical learning technique.

Specifically, information on whether or not the driver leaves the designated place generated by the region departure determination unit 10, boarding pattern information and user movement information generated by the boarding prediction unit 20, 30, and the timing information for starting the operation of the vehicle convenience facility generated from the pre-operation control unit 40, accumulates the collected information through the computer, analyzes the information, So that the computer automatically analyzes and grasps the behavior pattern of the user through mechanical iterative learning.

As such a mechanical learning technique, there is a known machine learning method such as an ADA Boost algorithm, a Bayesian network, and a neural network.

On the other hand, the information of the user behavior pattern learned by the driver behavior learning unit 50 is stored and managed in the linked database 60.

The communication network 300 is any known wired or wireless communication network that enables the system 1 of the present invention to transmit and receive information to and from the automobile central control unit 200. The present invention is applicable to a wireless Internet It adopts.

The automobile central control unit 200 controls the operation of the automobile comfort devices such as the air conditioner device 210, the heater device 220, and the starting device 230. In addition, examples of convenience devices for automobiles include an audio device, a navigation device, a video device, a seat heating device, and a steering wheel heating device.

The presetting system 1 according to the present invention may be implemented by a computer, a PDA, a tablet computer, etc. Preferably, the presetting system 1 is a user terminal 100 such as a cellular phone owned by a user Preferably, the user terminal 100 is a smart phone capable of installing and executing an application program for executing the preset system of the present invention.

Next, a description will be given of a convenience function pre-setting method for a vehicle through the driver's boarding prediction performed by the preset system of the present invention configured as described above.

The method for predicting convenience functions of a vehicle (hereinafter, abbreviated as "preset method") of the present invention by predicting the boarding of a driver according to the present invention includes an area departure judgment unit 10 for judging a departure of a designated area by a driver, A vehicle arrival time arithmetic unit 30 for calculating the arrival time to the vehicle when the driver is predicted to board the vehicle, A pre-operation control section (40) for pre-operating a convenience function of the vehicle according to the calculated arrival time, and a control section (40) for learning process data of the area departure judging section, the board predictor, the vehicle arrival time calculating section and the pre- And a driver behavior learning unit 50 that applies the behavior pattern to the behavior pattern.

The preset method of the present invention is implemented by executing an application program that performs a preset method installed in the user terminal 100 such as a smart phone.

The presetting method of the present invention is a method in which the boarding pattern and the behavior pattern and the designated area at the time of driving by the driver are previously learned through the driver behavior learning unit 50 for a certain period of time and these information are stored in the database 60 Is preferably performed in a state of "

When the user terminal 100 is driven and an application program is executed, the area departure determination unit 10 determines whether the driver has left the designated area (S1).

The designated area is a house, a workplace, a park, a shop or the like frequently accessed by the driver, and the area departure judging unit 10 generates the area departure judging unit 10 from a Global Position Assistant (GPS) module built in the user terminal 100, It is determined whether or not the driver has deviated from the designated area.

3 and 4 are diagrams for explaining a method for presetting a comfort function of a vehicle according to the present invention. The designation area includes a GPS module of a user terminal 100 owned by a driver, An area having a radius R (m) around a single position (point O in Fig. 3) specified by the area R (m) can be set as a designated area.

In addition, an inner area of at least three positions (point A, point B, and point C in FIG. 4) designated by the GPS module of the user terminal 100 carried by the driver can be set as a designated area, (Point O, point A, point B, and point C) of 4 are assigned polar coordinates (latitude and longitude) by the GPS module.

3 is a formula for determining whether a polarized image (Xo, Yo) of a point O is within a designated area when the designated area is a region having a radius Rm around a single position, and the following equation In the case where the designated area is a designated area centered on three positions, the formula is used to determine whether or not the area is within the geographical area within the polar coordinates (Xa, Ya, Xb, Yb, Xc, Yc) of points A, to be.

For example, if the designated area frequently accessed by the user is a home and a company, an area within a radius R (m) from one polar coordinate of the user's home is set to the designated area 1, and within three polar coordinates Is set in the designation area 2.

The information of the designation area designated as described above is stored in the interlocked database 60. The area departure judgment unit 10 judges whether the position of the user terminal 100 recognized by the GPS module is the designated area It is judged whether or not it has departed.

Next, if it is determined in step S1 that the user has left the designated area, the board predictor 20 determines whether the user approaches the vehicle from the designated area (S2). When the vehicle approaches the vehicle, The probability is calculated (S3).

The steps S2 and S3 will be described in detail as follows.

FIG. 5 is a conceptual diagram for judging whether or not the convenience function presetting method of the present invention is used.

Basically, the determination of whether or not the user approached by the vehicle by the board predictor 20 is based on a speed v = distance r / time T, which is a formula for obtaining the moving speed of the user U m / s), which can be interpreted as follows.

1) Determine whether the user moves at a constant speed

The board predictor 20 determines whether the user is moving at a predetermined speed or higher based on the position information calculated by the GPS module of the user terminal 100 held by the user.

)(m)라 하고, 사용자(U)의 자동차 방향으로의 거리벡터를 차량방향벡터(

)(m)라 하면, 사용자가 일정한 속도 이상으로 움직이는지의 판단은 하기의 수식 1 에 의하여 판단될 수 있다.5, a distance vector in a direction in which the user U is currently moving is referred to as a movement direction vector (

) (m), and the distance vector of the user U in the vehicle direction is referred to as a vehicle direction vector (

) (m), it can be judged by the following expression (1) whether the user moves at a constant speed or more.

(Equation 1)

* Vth: preset speed

2) Judging whether the distance between the user and the vehicle is continuously reduced

If it is determined in step 1) that the user is moving at a speed higher than a predetermined speed, then the board predictor 20 determines whether the distance between the user and the vehicle is continuously reduced, have.

(Equation 2)

* K: preset distance

3) Judging whether the distance from the car is close

Next, if it is determined that the distance between the user and the car is continuously reduced in the above 2), the board predictor 20 determines whether the distance between the user and the vehicle is within a predetermined distance, .

(Equation 3)

< RR pro <

<R

* Rpro: the shortest distance

R: Proximity distance

)(m)값이 최단근접거리(Rpro) 초과 근접거리(R) 미만일 경우 사용자가 자동차에 근접하였다고 판단한다.According to Equation (3), the distance vector in the direction of the vehicle of the user U of the user is defined as the vehicle direction vector

) &lt; / RTI &gt; (m) is less than the shortest proximity distance (Rpro) beyond the proximity distance (R).

Here, the reason for setting the shortest proximity distance Rpro is to exclude an exceptional situation such as a case where the user moves away from the car after parking the car, and then retrieves the forgotten object again.

Next, according to the embodiment of the present invention, the actual values of the moving speed (V) of the user, the distance (K) between the user and the automobile, and the proximity distance (R) , And the collected actual values are classified according to the following conditions.

A1: v <v_th1  B1: K <K1 C1: R < R1

      A2: v_th1 <v <v_th2  B2: K1 <K <K2 C2: R1 <R <R2

A3: v_th2 < v < v_th3  B3: K2 <K <K3 C3: R2 <R <R3

A4: v> v_th3  B4: K> K3 C4: R > R3

* Vth1: first set speed, Vth2: second set speed, Vth3: third set speed

  K1; First set distance, K2: Second set distance, K3: Third set distance

  R1; A first preset proximity distance, R2; Second default proximity distance, R3; Third set proximity distance

Therefore, by using the above-described conditions A1 to C4, a total of 64 combined conditions (4 ^ 3 = 64) are calculated for each condition type and region, and the actual conditions are analyzed for each condition, It analyzes the probability that the vehicle actually starts.

For example, for conditions [A1 and B1 and C1], the probability P (A1 and B1 and C1) of the condition [A1 and B1 and C1] is 500 cases / 100,000 case x 100% = 0.5%.

Then, the individual probability of each of the 64 combined conditions is calculated, and the single condition probability of P (A1), P (A2), ..., P (C4) The probability value is assigned as the evaluation value. For example, if P (A3) = 12%, the evaluation value is assigned as 12.

At this time, standardize each value so that the sum of the highest probabilities is close to 100 or 100. For example, if P (A4), ..., P (D4) are 30%, 40%, 40%, and 30%, the total evaluation value is 30 + 40 + 40 + 30 = The evaluation value is multiplied by 100/140 so that the sum of the probabilities is normalized to a value close to 100 or 100.

Then, the above-described process is performed to calculate evaluation values according to satisfaction degree of each condition as shown in Table 1 below. (The evaluation values shown in the table are examples)

Condition 1 V <Vth1 Vth1 < V < Vth2 3Vth2 < V < Vth3 V> Vth3 Evaluation value 15 20 25 30 Condition 2 K <K1 K1 <K <K2 K2 <K <K3  K> K3 Evaluation value 15 20 25 30 Condition 3 R <R1 R1 <R <R2 R2 <R <R3  R> R3 Evaluation value 15 20 25 30

According to Table 1, for example, in the case of satisfying both of the conditions [V <Vth1 and K <K1 and R <R1] which are the leftmost conditions of Condition 1, Condition 2 and Condition 3 in Table 1, (15 + 15 + 15 = 45), which indicates that the vehicle is approaching the vehicle with a vehicle access probability (P1) of 45%.

In addition to the above-described evaluation value calculated in the step of determining whether the user of step S2 approaches the automobile from the designated area, the boarding predictor 20 of the present invention calculates the vehicle behavior pattern Probability (P2) is used.

That is, as shown in FIG. 6, the driver behavior learning unit 50 refers to the operation pattern information learned using the mechanical learning technique, and calculates the probability of boarding the vehicle on a specific day and a specific time zone.

For example, when the driver's driving pattern information is learned, as shown in the figure, the probability of getting a car at 7:00 am on weekdays is 95%, the probability of getting a car at 10:00 on weekends is 50% At 17:00, the probability of a car crash can be calculated to be 10%, so this is the probability of boarding by time of day.

Therefore, the boarding predictor 20 calculates the vehicle use probability by using the vehicle boarding probability P2 calculated by referring to the vehicle approach probability P1 and the learned operation pattern information calculated in the step S2 (S3 ).

In the embodiment of the present invention, the calculation of the vehicle utilization probability is performed by multiplying the vehicle access probability P1 calculated in step S2 by the vehicle arrival probability P2 to calculate the final vehicle utilization probability.

For example, if the vehicle access probability P1 is 95% and the vehicle boarding probability P2 is 90%, then the vehicle use probability Pc is 0.95 x 0.9 x 100 = 85.5%.

Next, it is determined whether the vehicle use probability Pc calculated in step S3 exceeds a first set value (S4). If it exceeds the first set value (Pc> first set value), it is determined that the driver uses the vehicle, The arrival time calculation unit 30 calculates a time Ta at which the driver reaches the automobile (S7).

On the other hand, if the vehicle use probability Pc calculated in step S3 is less than the second set value exceeding the first set value (S5) (the second set value < Pc & (S6). If the menu screen is in the activated state, it is determined whether the user intends to operate the convenience function of the vehicle And proceeds to step S7 to calculate the time (Ta) at which the driver reaches the automobile by the following equation (4).

(Equation 4)

Ta = Tes + L / V

* Ta: Time the driver reaches the car

  Tes: atypical escape time

  L: Distance between driver and car

  V: Speed of the driver

The calculation of the vehicle arrival time of the driver can be calculated by referring to the position information and the traveling speed of the driver transmitted by the GPS module of the user terminal 100 carried by the driver.

Here, the atypical escape time (Tes) represents an average value of the time required due to a specific action according to a behavior pattern of the driver learned through the driver behavior learning unit 50 although the user's position is stationary on the GPS coordinates For example, the time of boarding the elevator or the time for the driver to separate and collect from the entrance of the apartment.

However, if the vehicle use probability Pc calculated in step S3 is less than the second set value (Pc < second set value), it is determined that the user does not use the vehicle and the driver behavior learning unit 50 Is learned by a mechanical learning technique (S16), and the process returns to step S1.

If it is determined in step S7 that the driver's position of the user terminal 100 on the GPS is the same as the GPS position of the vehicle, the driver's behavior learning unit 50 determines that the driver has actually arrived at the vehicle (S9) The driver's behavior pattern is learned by a mechanical learning technique (S16), and the flow returns to step S1.

Next, if the vehicle arrival time Ta of the driver calculated in step S7 is less than the arrival time set value (S8), it means that the driver is about to arrive at the automobile soon. Operate the convenience functions such as the air conditioner unit and the heater unit in advance.

In the embodiment of the present invention, as a pre-operation of the convenience function, the pre-operation control unit 40 activates the starting device 230 of the vehicle to start the vehicle (S10), and transmits the weather information And receives current outside temperature information from a providing server (not shown) (S11).

Next, if the outside temperature information provided in step S11 is less than the first temperature set value (S12), it is determined that the automobile is located in an area having a cold outside temperature, and the pre-operation control unit (40) 220) is operated to perform the operation of vertically raising the temperature of the automobile room (S14).

On the other hand, if the outside temperature information provided in step S11 is greater than the second temperature setting value (S13), it is determined that the automobile is located in an area having a high temperature outside temperature, and the pre- ) Is operated remotely to perform an operation of vertically lowering the vehicle interior temperature (S15).

7 is a view showing an example of a menu screen displayed on a mobile phone when presetting a convenience function of the comfort function presetting method of the present invention. The user may select a user terminal 100, such as a smart phone, The convenience of the air conditioner or the heater can be proactively activated while the user's boarding probability is displayed without individually operating the convenience functions of the vehicle.

In the example of the drawing, when the vehicle use probability is 95% as in the left part (a), the convenience device is operated in advance, and when the vehicle use probability is 50% as shown in the center part (b) When the probability of use of the vehicle is 10% as shown in the part (c) of the right side, the pre-operation of the convenience device does not occur and it is not required to check whether the convenience device is in operation.

Therefore, according to the system for predicting convenience functions of a vehicle and the method of predicting the boarding of a driver according to the present invention as described above, it is possible to learn the behavior pattern of the driver as usual using a learning algorithm based on artificial intelligence technology, Since the remote start of the vehicle and the convenience functions such as the air conditioner and the heater are preset in advance based on the predicted whether or not the vehicle is to be boarded, the driver can immediately operate the vehicle in a pleasant environment at the same time of boarding the vehicle, . &Lt; / RTI &gt;

Description of the Related Art [0002]
One; The convenience function presetting system of the present invention
10; The region-
20; Boarding predictor
30; The amount-of-
40; The pre-
50; Driver Behavior Learning Department
100; User terminal
200; The automobile central control unit
300; communications network

Claims (15)

A system for presetting a convenience function of a car,
An area departure judging section (10) for judging a departure of the designated area of the driver;
A boarding predictor 20 for predicting whether or not the driver leaves the specified area as a result of the determination by the zone departure determiner 10;
A vehicle arrival time arithmetic unit 30 for calculating the arrival time of the driver to the vehicle if it is predicted that the driver will board the vehicle at the boarding predictor 20;
And a pre-operation control unit (40) for pre-operating a convenience function of the vehicle according to the arrival time calculated by the vehicle arrival time calculation unit (30).
The method according to claim 1,
A driver behavior learning unit 50 for learning the process data of the zone departure determination unit 10, the board predictor 20, the vehicle arrival time calculation unit 30, and the pre-operation control unit 40 by a mechanical learning technique; Further comprising: a convenience function presetting system for a car.
The method according to claim 1,
Wherein the presetting system is implemented by executing an application program executed in the user terminal (10).
3. The method according to claim 2, wherein the determination of whether or not the vehicle is used by the board predictor (20)
Determining whether or not the user is moving at a constant speed, determining whether the distance between the user and the vehicle is continuously reduced, and determining whether the distance from the vehicle is close to the vehicle to calculate the vehicle access probability P1 Convenient function preset system of the car which features.
5. The method according to claim 4, wherein the determination of whether or not the vehicle is used by the board predictor (20)
The vehicle access probability (P1)
Is calculated by calculating the vehicle use probability by the vehicle boarding probability (P2) calculated by referring to the operation pattern information learned by the driver behavior learning unit (50).
The method according to claim 5, further comprising: determining whether the vehicle use probability (Pc) exceeds a first set value, determining that the driver uses the vehicle when the first set value is exceeded,
If the vehicle use probability Pc is less than the second predetermined value, the board predictor 20 checks whether or not the menu screen of the application program of the dictionary function setting system is activated in the user terminal 100,
And when the corresponding menu screen is in the activated state, it is determined that the user intends to operate the convenience function of the vehicle.
2. The method according to claim 1, wherein, in calculating the time to reach the vehicle by the vehicle arrival time calculation unit (30)
The user's position is added to the vehicle arrival time by adding the atypical escape time (Tes), which is the average value of the time required due to the specific action according to the learned behavior of the driver through the driver's behavior learning unit 50, And the time is calculated.
A method for presetting a convenience function of a car,
A step (S1) of judging whether or not the area departure judging section (10) has left the designated area by the driver;
If it is determined that the user has deviated from the designated area, determining whether the boarding predictor 20 approached the vehicle from the designated area by the user (step S2);
Calculating (S3) a vehicle use probability (Pc), which is a probability that a user uses the vehicle when approaching the vehicle;
Determining whether the vehicle use probability Pc exceeds a first set value (S4);
If the first set value is exceeded (Pc> first set value), it is determined that the driver uses the vehicle, and the vehicle arrival time arithmetic unit 30 calculates the time Ta at which the driver arrives at the vehicle (S7);
If the calculated vehicle arrival time Ta of the driver is less than the arrival time set value (S8)
Characterized in that the pre-operation control unit (40) pre-operates the convenience functions of the vehicle.
9. The method of claim 8,
A region having a radius R (m) centered on the single position,
Or an interior region of at least three positions.
The method as claimed in claim 8, wherein the step (S2) of determining whether the user by the board predictor (20)
Determining whether or not the user is moving at a constant speed, determining whether the distance between the user and the vehicle is continuously reduced, and determining whether the distance from the vehicle is close to the vehicle to calculate the vehicle access probability P1 How to pre-set convenience features of a car.
11. The method according to claim 10, wherein step (S3) of calculating a vehicle use probability (Pc), which is a probability that a user uses the automobile when approaching the automobile,
The vehicle access probability (P1)
And calculating the vehicle use probability by the vehicle boarding probability (P2) calculated by referring to the operation pattern information learned by the driver behavior learning unit (50).
12. The method of claim 11, wherein calculating (S3) the vehicle use probability (Pc), which is a probability that the user uses the automobile when approaching the automobile,
Wherein the vehicle use probability is calculated by integrating the vehicle approach probability (P1) and the vehicle boarding probability (P2). 9. The method of claim 8,
If the vehicle use probability Pc calculated in step S3 is less than the second set value first set value (S5)
The board predictor 20 checks whether the menu screen of the application program of the dictionary function setting method is activated in the user terminal 100 (S6)
And when the corresponding menu screen is in the activated state, it is determined that the user intends to operate the convenience function of the vehicle.
9. The method according to claim 8, wherein the step (S7) of calculating the time (Ta) by the vehicle arrival time arithmetic unit (30)
The user's position is added to the vehicle arrival time by adding the atypical escape time (Tes), which is the average value of the time required due to the specific action according to the learned behavior of the driver through the driver's behavior learning unit 50, And calculating the time of the convenience function of the vehicle.
9. The method according to claim 8, wherein the advance operation of the vehicle convenience function by the pre-operation control unit (40)
The pre-operation control unit 40 receives the current outside temperature information from the external weather information providing server through the communication network 300 (S11)
And the air conditioner device or the heater device is remotely activated according to the provided outside temperature information.

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