KR20190063971A - Activity convenience system for personalized custom - Google Patents

Abstract

The present invention relates to an active convenience system and, more specifically, relates to an active convenience system for personalized custom to provide convenience for personalized custom in accordance with a passenger state and an internal state of a vehicle. According to the present invention, a fusion sensor module having a thermal infrared sensor module, an RGB sensor module, and a depth sensor module is used to more accurately acquire passenger information and vehicle interior information. Moreover, according to the present invention, Moreover, according to the present invention, the fusion sensor module is used to accurately acquire passenger information and vehicle interior information different in accordance with a passenger and a situation to actively provide convenience for personalized custom.

Description

[0001] ACTIVITY CONVENIENCE SYSTEM FOR PERSONALIZED CUSTOM [0002]

The present invention relates to an active component system, and more particularly, to a personalized active component system that provides personalized comfort based on occupant status and internal state of the vehicle using a fusion sensor.

A car, that is, a vehicle, means a means of transportation used to carry people or cargo. Such a vehicle is provided with a seat on which the occupant sits and an air conditioning system for enabling the occupant to travel in a pleasant environment, in addition to the power source necessary for the movement.

Conventionally, the air conditioning system and the seat of the vehicle have to be manually operated by passengers. Recently, however, technology for automatically controlling the air conditioning system and the seat has been applied so that the occupant can only care about driving. However, these air conditioning systems and seats are so complicated and diverse that the individual characteristics of the passengers remain so that they provide a convenient level of service that provides a mode in which passengers can select and store the values set by the passengers , There is a limit to automatically providing the optimum convenience for each passenger.

Korean Patent Laid-Open Publication No. 10-2012-0046909 (published May 11, 2012)

SUMMARY OF THE INVENTION It is an object of the present invention to provide a convenience system that actively fits in accordance with a passenger.

According to an aspect of the present invention, there is provided a method of modifying a thermal image, the method comprising: (a) combining a thermal infrared sensor module, a RGB sensor module, and a depth sensor module; An image fusion module; an image processing module for processing the image fused in the image fusion module to generate vehicle interior temperature information and occupant information; and a control unit for controlling the state of the occupant based on the vehicle interior temperature information and the occupant information generated by the image processing module An application module for determining a pattern of a passenger and a vehicle interior temperature, and a vehicle control module for controlling the vehicle according to a result determined by the application module.

The application module includes a passenger attitude determination module for determining an attitude by detecting an occupant in the image processing module, a passenger behavior pattern determination module for accumulating a behavior pattern of the passenger to determine a normal behavior pattern and an abnormal behavior pattern, A passenger's body temperature judging module for detecting the body temperature of the occupant, a passenger boarding judging module for judging whether a passenger is present in the vehicle, an air conditioning control pattern judging module for judging the air conditioning control pattern manually adjusted by the passenger, A seat adjustment pattern determination module for determining a pattern, and a driving pattern determination module for determining an abrupt steering wheel steering of a passenger.

Wherein the image processing module comprises: a merged image table generation module for generating a plurality of merged image tables according to a time flow of the merged image generated by the merged image table generation module, a plurality of merged images generated by the merged image table generation module, A conversion table generation module for extracting a pixel area changed based on the table to generate a conversion table, a data averaging module for averaging the pixel data of the conversion table, and an averaging module for applying the averaged conversion table to the merged image table And an offset application module.

The vehicle control module includes an air conditioning control module for controlling the vehicle air conditioning based on at least one of the passenger body temperature, the vehicle interior temperature, and the occupant temperature determined by the passenger body temperature determination module, And a seat control module for controlling the seat of the vehicle based on the posture, the body shape of the occupant, and the behavior pattern of the occupant determined by the occupant behavior pattern determination module.

The vehicle control module determines whether the occupant is holding the steering wheel by hand, determines whether the head of the occupant is heading in the traveling direction, determines whether the occupant is responsive to an external stimulus, And a DWD warning module.

The present invention can more accurately acquire occupant information and vehicle interior information by using a fusion sensor module including a thermal infrared sensor module, an RGB sensor module, and a depth sensor module.

In addition, the present invention can actively provide personalized convenience by accurately acquiring different passenger information and vehicle interior information according to the occupant and the situation using the fusion sensor module.

1 is a block diagram of a personalized active comfort system in accordance with the present invention;
2 is a perspective view of a fusion sensor module of a personalized active component system in accordance with the present invention.
3 is an exemplary view of a merged image table according to the present invention;
4 is a conceptual diagram for explaining an initial merged image table comparison module according to the present invention;
5 to 7 are conceptual diagrams for explaining an arithmetic processing region according to the present invention.
8 and 9 are conceptual diagrams for explaining a later merged image table comparison module according to the present invention.
10 is a conceptual diagram for explaining a data averaging operation module according to the present invention;
11 and 12 are conceptual diagrams for explaining an offset application module according to the present invention.

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

It will be understood by those of ordinary skill in the art that the present invention may 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, It is provided to inform. Like reference numerals refer to like elements throughout.

1 is a block diagram of a personalized active pacing system in accordance with the present invention.

1, the personalized active convenience system according to the present invention includes a fusion sensor module 100, an image fusion module 200 for merging images acquired by the fusion sensor module 100 to generate a fusion image, An image processing module 300 for processing the merged merged image in the image fusion module 200 to generate the vehicle interior temperature information and the occupant information, the vehicle interior temperature information and the occupant information generated by the image processing module 300, An application module 400 for determining a state of a passenger, a pattern of a passenger and a vehicle interior temperature, and a vehicle control module 500 for controlling the vehicle according to a result determined by the application module 400. Here, the occupant information includes occupant attitude information, occupant behavior pattern information, and occupant body temperature information. In addition, when there is a passenger, the passenger information may include passenger attitude information, passenger behavior pattern information, and passenger temperature information.

2 is a perspective view of a fusion sensor module of a personalized active component system according to the present invention.

The fusion sensor module 100 acquires heat and light in the vehicle to generate a thermal infrared image and an RGB image and a depth image. 2, the fusion sensor module 100 includes a thermal infrared sensor module 110 for acquiring temperature information on the vehicle, an RGB sensor module 120 for acquiring RGB information in the vehicle, And a depth (3D-Depth) sensor module 130 for acquiring depth information.

The thermal infrared sensor module 110 irradiates infrared rays in the vehicle to obtain temperature information. The temperature information obtained here includes occupant temperature information and vehicle room temperature information. In addition, if there is a passenger, it also includes passenger temperature information.

The RGB sensor module 120 acquires RGB information in the vehicle. Accordingly, the RGB information includes the occupant and the indoor brightness information.

The depth sensor module 130 acquires in-vehicle depth information, and the depth information includes occupant status information, occupant figure information, and occupant attitude information.

The image fusion module 200 includes the thermal infrared image generation module 210 obtained by the thermal infrared sensor module 110, the RGB sensor module 120, the RGB image generation module 220, the depth image generation module 230, And an image merge module 240 for merging the thermal infrared image with the RGB image and the depth image.

The thermal infrared image generation module 210 generates a thermal infrared image based on the temperature information acquired by the thermal infrared sensor module 110. This can be performed by digitizing thermal infrared information obtained by the thermal infrared sensor module 110. [

The RGB image generation module 220 digitizes the RGB information obtained from the RGB sensor module 120 to generate an RGB image.

The depth image generation module 230 generates a depth image based on the depth information acquired by the depth sensor module 130. Here, the depth image generation module 230 also performs the depth information obtained by the depth sensor module 130 by digitizing the depth information.

The image merge module 240 merges the thermal infrared image with the RGB image and the depth image.

The image processing module 300 processes the merged image generated by the image merging module 240. [ The image processing module 300 includes a merged image table generation module 310, a conversion table generation module 320, an operation processing area extension module 326, a data averaging operation module 330, and an offset application module 340 .

3 is an exemplary view of a merged image table according to the present invention.

The merged image table generation module 310 generates a merged image table formed based on the merged image generated by the merged image generation module. Here, the merged image table is obtained by digitizing the temperature information, the RGB information, and the depth information in the merged image merged by the image merging module 240. In this embodiment, as shown in FIG. 3, , Position information according to the vertical position is displayed, and the pixel includes the merged temperature information, RGB information, and depth information. It also illustrates that a single merged image table includes a total of 1024 pixels, with 32 pixels horizontally and 32 pixels vertically. However, the present invention is not limited to this, and the number of pixels included in one merged image table may be less than 1024 pixels or more than 1024 pixels as necessary. The merged image table generation module 310 generates a plurality of merged image tables in accordance with the passage of time, and the generated plurality of merged image tables are transferred to a conversion table generation module 320 to be described later. Here, in the present embodiment, for convenience of description, four consecutive merged image tables generated by the merged image table generation module 310, i.e., a first merged image table and a second merged image table, a third merged image table, A merge image table is illustrated.

The conversion table generation module 320 compares the generated merged image tables with each other. Here, the conversion table generation module 320 includes an initial merged image table comparison module 321 for comparing the first merged image table and the second merged image table, and an initial merged image table comparison module 321 for specifying an operation processing area in the initial merged image table comparison module 321 An initial conversion table generation module 323 for generating an initial conversion table as an operation processing area designated by the operation processing area designation module 322, an initial conversion table generation module 323 for generating a second merging image table A late merged image table comparing module 324 for comparing the generated merged image tables and extracting the converted data, a late conversion table 323 for generating a late conversion table as the converted data extracted by the late merged image table comparison module 324, Generation module 325.

4 is a conceptual diagram for explaining an initial merged image table comparison module according to the present invention.

The initial merged image table comparison module 321 compares the first merged image table T1 and the second merged image table T2 as shown in FIG. 4, and compares the first merged image table T1 with the 1024 pixels And the 1024 pixels of the second merged image table T2 are all compared. The initial merge image table comparison module 321 compares the first merged image table T1 and the second merged image table T2 and compares the first merged image table T1 with the second merged image table T1 T2, i.e., the converted data. Here, the present invention extracts conversion data by comparing only the merged image tables, and controls the air conditioner based on the extracted conversion data. However, the merged image change is detected more quickly through the operation processing area designation module 322 to be described later.

5 to 7 are conceptual diagrams for explaining an arithmetic processing region according to the present invention.

When the initial merged image table comparison module 321 determines that there is conversion data, the operation processing area designation module 322 designates the corresponding area as the operation processing area CS as shown in Figs. 5 to 7 . 5, the first merged image table and the second merged image table are compared to designate an area having the converted data as an operation processing area CS and extract it as shown in FIG. 6 . Further, as shown in Fig. 7, the extracted conversion data is determined. Such an operation processing area CS may be formed in a rectangular shape including non-converted data located between all converted data and all converted data, or may be formed into a shape including only all converted data. In this case, as shown in FIG. 6, when a pixel is formed in a rectangular shape, a pixel located at the edge of the transformed data is vertically and horizontally extended to form a rectangular transformed image including all transformed data and non- Thereby forming an arithmetic processing area.

The initial conversion table creation module 323 creates a first conversion table which is an initial conversion table into the operation processing area extracted by the operation processing area designation module 322. [

8 and 9 are conceptual diagrams for explaining a later merged image table comparison module according to the present invention.

8, the late merged image table comparison module 324 includes an Nth conversion table and a merged image table generated after the second merged image table, that is, an (N + 2) Is a natural number). That is, the first conversion table generated by the initial conversion table generation module 323 is compared with the third merged image table T3, and the second merged image table T3 generated by comparing the first converted table and the third merged image table T3, The conversion table is compared with the fourth merged image table. Here, the second conversion table is obtained by designating conversion data as an operation processing area (CS) in the same manner as the first conversion table. That is, in the present invention, the first conversion table is generated by comparing the entire area of the first merged image table and the second merged image table, but as shown in FIG. 9, the entire area of the merged image table Only the changed areas are compared without comparing.

The late conversion table generation module 325 generates an (N + 1) conversion table. That is, the initial conversion table generation module 323 generates a first conversion table by comparing the first merged image table and the second merged image table, that is, the initial merged image table, and the latter conversion table generation module 325 The conversion table is compared with the merged image table to generate the conversion table. For example, the late conversion table generation module 325 generates a second conversion table by comparing the first conversion table and the third merging image table, compares the second conversion table and the fourth merging image table, Create a table.

In the present invention, when thermal sensing is performed on a fixed arithmetic processing region, it is possible to expand the arithmetic processing region in order to solve the problem that a merged image change occurring in an area other than the arithmetic processing region can not be detected. In addition, for this purpose, the present invention may include a computation processing region extension module 326. [

The operation processing area extension module 326 expands the area designated as the operation processing area. The arithmetic processing area is an area where a change occurs in the merged image, and when a change occurs, the arithmetic processing area widenes gradually to the periphery in the changed area. Thus, the present invention extends the area of a given pixel around an arithmetic processing region to extend the arithmetic processing region, where certain pixels may be, for example, three pixels. However, the present invention is not limited thereto, and a predetermined pixel may be less than three pixels or more than three pixels. In addition, if the number of pixels remaining around the arithmetic processing region out of 1024 pixels is less than 3 pixels, only the remaining pixels are designated as the extended region.

10 is a conceptual diagram for explaining a data averaging operation module according to the present invention.

The data average operation module 330 averages the conversion table to determine a final conversion table. This, as shown in FIG. 10, obtains pixel data average only for overlapping pixels in the conversion table.

11 and 12 are conceptual diagrams for explaining an offset application module according to the present invention.

After the final conversion table is finalized, the offset application module 340 applies the offset to the merged image table of 1024 pixels by the calculation processing area CS shown in FIG. 11, corrects the offset as shown in FIG. 12, . Here, the table generated by the offset application module 340 becomes the final data to be output to the application module 400. For example, the application module 400 can grasp the change in the heat distribution in the vehicle based on the received final data, and cool the area where the temperature is high, to keep the vehicle comfortably. At this time, the output of the table generated by the offset application module 340 can be transmitted through the CAN bus.

The application module 400 determines the posture of the occupant, the behavior pattern, the body temperature, the seat adjustment pattern, the starting pattern, the air conditioning adjustment pattern, the occupant boarding, the temperature in the vehicle, and the driving environment according to the change in the image processed in the image processing module. Accordingly, the application module 400 includes a passenger attitude determination module 410, a passenger behavior pattern determination module 420, a passenger body temperature determination module 430, a passenger boarding determination module 440, an air conditioning adjustment pattern determination module 450 A seat adjustment pattern determination module 460, a travel pattern determination module 470, and a start pattern determination module 480. [0052]

The occupant's posture determination module 410 detects the occupant in the image processed by the image processing module and determines the posture of the occupant detected. This can be done by artificial intelligence learning. The occupant's posture determined by the occupant's posture determination module 410 is used in the seat control module 520 and the DWD warning module 530, which will be described later.

The occupant behavior pattern determination module 420 detects the occupant in the image processed by the image processing module, and continuously senses the change in the motion of the occupant to determine the behavior pattern. Here, the occupant behavior pattern determination module 420 continuously detects the change in the motion of the occupant, determines the behavior pattern, and accumulates the same to distinguish the normal behavior pattern of the occupant from the abnormal behavior pattern. This can be done by determining the rider's behavior pattern as a normal behavior pattern. Of course, the occupant behavior pattern determination module 420 should determine whether the occupant is the same occupant as the previous occupant or not, through the body shape or the like. Also, the occupant behavior pattern determined by the occupant behavior pattern determination module 420 is used in the seat control module 520 and the DWD warning module 530, which will be described later.

The occupant temperature determining module 430 detects the occupant in the image processed by the image processing module and determines the body temperature of the occupant. This can be determined by applying the offset in the above-described offset application module 340 and correcting it by performing temperature arithmetic processing. The body temperature of the passenger judged by the passenger body temperature judging module 430 is used in the air conditioning control module 510 to be described later. On the other hand, the occupant temperature determining module 430 determines not only the body temperature of the passenger but also the indoor temperature of the vehicle. Furthermore, if the occupant temperature determination module 430 detects the passenger in the passenger boarding determination module 440, the body temperature of the passenger can be determined.

The passenger boarding determination module 440 detects the passenger in the image processed by the image processing module. Offset Based on thermal infrared and RGB and depth information in the applied image. That is, the outline of the passenger, that is, the boundary, can be determined through the above-described information to determine whether or not the passenger is boarding the passenger.

The air conditioning adjustment pattern determination module 450 determines the air conditioning adjustment pattern manually operated by the passenger. In addition, the air conditioning adjustment pattern determination module 450 determines an average value of the time, the temperature, and the intensity, and determines whether the wind is directly blown or indirectly sprayed to the passenger. This is because even if the vehicle air conditioning system is automatically operated based on the occupant's body temperature and the vehicle interior temperature, it may not fit the passenger. Therefore, the present invention judges the manually adjusted pattern and reflects it when the air conditioning system is operated later.

Similar to the air conditioning adjustment pattern determination module 450, the seat adjustment pattern determination module 460 determines a pattern in which the occupant manually adjusts the seat. That is, even if the seat is automatically adjusted in accordance with the body shape of the occupant, the occupant may be uncomfortable. In this case, the occupant manually adjusts the automatically adjusted seat, and the seat adjustment pattern determination module 460 determines the seat adjustment pattern so as to adjust the seat of the occupant, .

The travel pattern determination module 470 determines the vehicle travel pattern of the passenger. This is used to determine whether or not the DWD warning module 530, which will be described later, performs the DWD warning. For certain passengers, the vehicle driving pattern may be unusual. This may include, for example, an abrupt operation accompanied by a sudden steering wheel steering, and the abrupt steering wheel steering may determine that steering wheel steering of a predetermined angle or more within a predetermined time is performed by a reference number of times or more. The driving pattern determination module 470 determines the corresponding case and applies it to the traveling pattern of the occupant so that the DWD warning module 530 reflects the steering operation DWD when determining the steering operation DWD.

The start-up pattern determination module 480 determines the start pattern and predicts the time when the occupant boarding the vehicle, and automatically adjusts air conditioning, seat, and the like in advance.

The vehicle control module 500 determines whether or not the vehicle is traveling on the basis of the posture and behavior pattern of the occupant determined through the application module 400, the body temperature, the seat adjustment pattern, the starting pattern, the air conditioning adjustment pattern, Controls air conditioning and seats, and performs DWD warnings. To this end, the vehicle control module 500 includes an air conditioning control module 510, a seat control module 520, and a DWD warning module 530.

The air conditioning control module 510 controls the air conditioning of the vehicle based on the occupant body temperature (including the occupant temperature and the vehicle interior temperature) determined by the occupant body temperature determination module 430 and the air conditioning adjustment pattern determined by the air conditioning adjustment pattern determination module 450 And controls the system.

The seat control module 520 controls the seat of the vehicle based on the occupant's posture determined by the occupant's posture determination module 410 (including the occupant's body type) and the occupant's behavior pattern determined by the occupant's behavior pattern determination module 420. [ Here, the automatic adjustment of the vehicle seat according to the occupant behavior pattern may be performed by adjusting the seat by reflecting the behavior of the occupant traveling the specific action, for example, the one arm across the armrest or the vehicle door, The sitting position of the occupant can be determined and performed.

The DWD warning module 530 judges the visual DWD and the physical DWD of the occupant, and calls attention to the occupant. Here, the dispersion factor and level during operation according to each judgment item are as shown in Table 1 below.

DWD  step Judgment priority Explanation 1. Distraction of visual attention 2. Physical
Dispersion of attention 3. Distraction of attention  Cumulative time Level 0 none none - Focusing on driving Level 1 2 seconds
Within 2 seconds
Within - Simple manipulation with the hand, adjusting the radio, drinking from the open container, Level 2 2 seconds
More than 12 seconds
Within A handful of complicated behaviors, hand-held phone calls (Reaching for non-moving objects), eating (Eating), etc. Level 3 12 seconds
More than In the process of performing several steps, media controller manipulation (Inserting and / or retrieving CD), makeup (makeup) etc. Level 4 2 seconds
More than 2 seconds
Within - Reading situations, looking at external objects, etc., which do not take long time frontal gazing, etc. Level 5 2 seconds
More than - Insect in vechicle, Reaching for a moving object, etc., while continuing with complicated actions using the body. Level 6 The driver can analyze the upper body motion and vision, and the steering angle pattern of the steering wheel, so that it is impossible to operate the steering wheel and the steering wheel in unusual non-driving state (sleep) Level 7 If the driver's posture is completely collapsed, the handle becomes inoperable, and the driver is unable to operate in a serious condition (such as a sickness or heart attack) that does not respond to a warning. Element Explanation example Distraction of visual attention A behavior in which the driver does not constantly monitor the road ahead to perform secondary tasks in the vehicle Movement of eyes due to air conditioner, convenience device, navigation, smartphone operation, etc. Distributing physical attention During the driving, the driver uses one or both hands to perform the secondary task in the vehicle, Food intake, operation of in-vehicle devices, removal of something from a purse or bag, etc.

Based on this, Level 1 means that the occupant is operating the steering wheel, so that there is no problem in handling the steering wheel, and there is no problem in the head movement, such as gazing at the driving direction. Therefore, since level 0 is a normal running state, no warning is required. In the case of level 1 to level 5, warning is given to the passengers when the conditions are met. In the case of level 6 and level 7, the occupant can not control the vehicle. Therefore, a safer area . Here, the warning to the passenger can be performed through seat / steering wheel vibration, cluster warning light, AVN (audio / video / navigation, navigation integration module) sound warning, and the like. Also, in Table 1, the cumulative cumulative cumulative cumulative time means a sum of the cumulative visual distraction time and the physical attention cumulative time.

In the meantime, the present invention is exemplified to perform judgment through the application module 400 provided in the vehicle, but the present invention is not limited thereto. For example, in the present invention, the image data is transmitted to the cloud server through the smart device application, and after the personalization learning by the artificial intelligence learning engine, the learned value is transmitted to the application module 400 through the smart device application again, The more accurate the learning can be achieved.

Although the present invention has been fully described by way of example with reference to the accompanying drawings, it is to be understood that the invention is not limited to the disclosed embodiments, but, on the contrary, is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.

100: Fusion sensor module 110: Thermal infrared sensor module
120: RGB sensor module 130: Depth sensor module
200: Image fusion module
210: Thermal infrared image generation module
220: RGB image generation module 230: depth image generation module
240: Image fusion module 300: Image processing module
310: Merge image table generation module
320: Convert Table Generation Module
321: Initial Merge Image Table Comparison Module
322: Operation processing area designation module
323: initial conversion table generation module
324: Late Merge Image Table Comparison Module
325: late conversion table generation module 326: operation processing area extension module
330: Data average operation module 340: Offset application module
400: Application module 410: Occupant attitude determination module
420: occupant behavior pattern judgment module 430: occupant body temperature judgment module
440: passenger boarding judging module 450: air conditioning control pattern judging module
460: Seat adjustment pattern determination module 470: Travel pattern determination module
480: Startup pattern determination module 500: Vehicle control module
510: air conditioning control module 520: seat control module
530: DWD Warning Module

Claims (5)

A fusion sensor module including a thermal infrared sensor module, an RGB sensor module and a depth sensor module,
An image fusion module for fusing the thermal infrared image obtained from the fusion sensor module with the RGB image and the depth image,
An image processing module processing the fused image in the image fusion module to generate vehicle room temperature information and occupant information,
An application module for determining a state of a passenger, a pattern of a passenger and a vehicle interior temperature based on the vehicle interior temperature information and the occupant information generated by the image processing module,
And a vehicle control module that controls the vehicle according to the result determined by the application module. The method according to claim 1,
The application module comprising:
A passenger behavior pattern determination module for determining a normal behavior pattern and an abnormal behavior pattern by accumulating the behavior pattern of the passenger, and a vehicle occupant behavior pattern determination module for detecting a body temperature of the occupant A passenger temperature determination module, a passenger boarding determination module for determining whether a passenger is present in the vehicle, an air conditioning adjustment pattern determination module for determining an air conditioning adjustment pattern manually controlled by the passenger, An adjustment pattern determination module, and a driving pattern determination module for determining a steerable steering wheel steering of a passenger. 3. The method of claim 2,
The image processing module comprising:
A merged image table generation module for generating a plurality of merged image tables according to the flow of time of the merged image generated by the merged image table generation module,
A conversion table generation module for extracting the changed pixel area based on the plurality of merged image tables generated by the merged image table generation module to generate a conversion table,
A data average operation module for averaging pixel data of the conversion table, and
And an offset applying module for offsetting the averaged calculated conversion table to a merged image table. The method of claim 3,
The vehicle control module includes:
An air conditioning control module for controlling the vehicle air conditioning based on at least any one of a passenger's body temperature, a vehicle room temperature, and a passenger's body temperature determined by the passenger's temperature determining module;
And a seat control module for controlling the seat of the vehicle based on the occupant's posture determined by the occupant's posture determination module, the body shape of the occupant, and the behavior pattern of the occupant determined by the occupant's behavior pattern determination module. The method of claim 3,
The vehicle control module includes:
A DWD warning module for determining that the occupant is holding the steering wheel by hand, determining whether the head of the occupant is heading in the traveling direction, and determining whether the occupant is responsive to an external stimulus to call attention of the occupant A personalized active comfort system.

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