Vehicle and method of controlling the same

Abstract

A vehicle and a control method thereof are provided. A vehicle determining a dangerous state of a user by classifying the state of the user into a plurality of stages includes a communicator configured to receive sleep time data of the user and terminal use data of the user from a user terminal, a first sensor configured to acquire image data of surroundings of the vehicle, a second sensor configured to acquire driving time data of the vehicle and heading data of the vehicle, an alarm, and a controller. The controller is configured to acquire relaxation data of the user, calculate a danger value, classify a fatigue state of the user, identify a plurality of vehicle driving states, and assign different weights to each of the vehicle driving states according to a danger type to determine whether the user is in a dangerous state, and provide a danger alarm when it is determined that the user is in a dangerous state.

Description

Technical Field

[0001] This disclosure relates to a vehicle and a method for controlling it that can provide an alert by determining a user's dangerous state. Background Technology

[0002] In the automotive industry, Driver Attention Warning (DAW) technology originated in the late 2000s and by the early 2010s, it had evolved into a system that detects inattention through vehicle behavior patterns and issues warnings separately on the instrument cluster. Subsequently, with the development of camera technology, DAW technology incorporated Driving State Warning (DSW) technology, which can issue warnings more directly by recognizing the driver's face. However, with FCA's legalization of DAW, it has a significant advantage in cost reduction and is expected to continue to be used in mass-produced vehicles in the future.

[0003] This technology adds information, such as whether a smartphone is being used or sleep time, to DAW technology, which determines inattention solely based on Controller Area Network (CAN) signals, thus overcoming the fundamental shortcoming of inattention detection in DAW technology. Summary of the Invention

[0004] This disclosure provides a vehicle and a control method thereof, which can determine the user's dangerous state by classifying the user's state into multiple stages and assigning different weights to each driving state value according to the danger value corresponding to each stage, and provide an alarm.

[0005] Other aspects of this disclosure will be set forth in part in the description which follows, and in part will be apparent from the description or may be learned by practice of this disclosure.

[0006] According to one aspect of this disclosure, a vehicle is provided, comprising: a communicator configured to receive user sleep time data and user terminal usage data from a user terminal; a first sensor configured to acquire image data of the vehicle's surroundings; a second sensor configured to acquire vehicle travel time data and vehicle heading data; an alarm; and a controller configured to: acquire user relaxation data based on the sleep time data and travel time data; calculate a hazard value based on at least one of the sleep time data, terminal usage data, relaxation data, and travel time data; classify the user's fatigue state into multiple hazard types based on the hazard value; identify multiple vehicle travel states based on the image data of the vehicle's surroundings and the vehicle heading data; and assign different weights to each vehicle travel state according to the hazard type to determine whether the user is in a dangerous state, and when it is determined that the user is in a dangerous state, output a control signal to provide a hazard warning via the alarm.

[0007] The controller can be configured to: assign a hazard level to sleep time data and assign a hazard level to driving time data that is lower than the hazard level assigned to sleep time data, and calculate a hazard value based on user sleep time data and driving time data with assigned hazard levels.

[0008] The controller can be configured to: assign a hazard level to user relaxation time data and assign a hazard level to driving time data that is lower than the hazard level assigned to user relaxation time data, and calculate a hazard value based on the user relaxation data and driving time data with assigned hazard levels.

[0009] The controller can be configured to: when it is determined, based on terminal usage data, that the user terminal is activated during driving due to receiving a user input command, or when it is determined that a user input command is detected within a predetermined input time after the user terminal is activated without user input, acquire data on the number of times a specific function of the user terminal is commanded and the usage time data within a predetermined operating time starting from the time the user input command is received, and calculate a danger value based on the acquired number of times data and usage time data.

[0010] The controller can be configured to output a control signal to provide an alarm when the time from which the user terminal receives the input command exceeds a predetermined reference time.

[0011] The controller can be configured to: acquire lateral movement distance data of the vehicle relative to the lane based on image data of the vehicle's surroundings and the vehicle's heading data, and assign different weights to the lateral movement distance data according to the type of hazard to determine the user's hazard status.

[0012] The controller can be configured to acquire lane occupancy distance data of the vehicle based on image data of the vehicle's surroundings and the vehicle's heading data, and assign different weights to the lane occupancy distance data according to the type of danger to determine the user's danger status.

[0013] The controller can be configured to acquire vehicle steering angle data based on image data of the vehicle's surroundings and the vehicle's heading data, and assign different weights to the steering angle data and lateral movement distance data according to the type of danger to determine the user's dangerous state.

[0014] The controller can be configured to: acquire lateral direction conversion count data related to the number of times the vehicle converts the lateral direction within a predetermined conversion time, based on lateral movement distance data, and assign different weights to the lateral direction conversion count data according to the type of hazard, in order to determine the user's hazard status.

[0015] According to another aspect of this disclosure, a vehicle control method is provided, the method comprising: receiving user sleep time data and user terminal usage data from a user terminal; acquiring image data of the vehicle's surroundings; acquiring vehicle travel time data and vehicle heading data; acquiring user relaxation data based on the sleep time data and travel time data; calculating a hazard value based on at least one of the sleep time data, terminal usage data, relaxation data, and travel time data; classifying the user's fatigue state into multiple hazard types based on the hazard value; identifying multiple vehicle travel states based on the image data of the vehicle's surroundings and vehicle heading data; and assigning different weights to each vehicle travel state according to the hazard type to determine whether the user is in a dangerous state, and outputting a control signal to provide a hazard warning when it is determined that the user is in a dangerous state.

[0016] Calculating hazard values ​​may include: assigning hazard levels to sleep time data and assigning hazard levels to driving time data that are lower than those assigned to sleep time data, and calculating hazard values ​​based on user sleep time data and driving time data with assigned hazard levels.

[0017] Calculating hazard values ​​may include: assigning hazard levels to user relaxation time data and assigning a lower hazard level to driving time data than the hazard level assigned to user relaxation time data, and calculating hazard values ​​based on the user relaxation data and driving time data assigned hazard levels.

[0018] Calculating the hazard value may include: when it is determined, based on terminal usage data, that the user terminal is activated due to receiving a user input command during driving, or when it is determined that a user input command is detected within a predetermined input time after the user terminal is activated without user input, acquiring data on the number of times a specific function of the user terminal is commanded and usage time data within a predetermined operation time starting from the time point from the time the user input command is received, and calculating the hazard value based on the acquired number of times data and usage time data.

[0019] Providing a danger alert may include: providing a danger alert when the time from the time the user terminal receives the input command exceeds a predetermined reference time.

[0020] Determining a user's hazardous status can include: acquiring lateral movement distance data of the vehicle relative to the lane based on image data of the vehicle's surroundings and the vehicle's heading data, and assigning different weights to the lateral movement distance data according to the type of hazard.

[0021] Determining a user's hazardous status may include: obtaining lane occupancy distance data of the vehicle based on image data of the vehicle's surroundings and the vehicle's heading data, and assigning different weights to the lane occupancy distance data according to the type of hazard.

[0022] Determining a user's dangerous status can include: acquiring vehicle steering angle data based on image data of the vehicle's surroundings and the vehicle's heading data, and assigning different weights to the steering angle data and lateral movement distance data according to the type of danger.

[0023] Determining a user's hazardous status may include: acquiring lateral direction conversion count data related to the number of times the vehicle changes lateral direction within a predetermined conversion time, based on lateral movement distance data, and assigning different weights to the lateral direction conversion count data according to the type of hazard. Attached Figure Description

[0024] These and / or other aspects of this disclosure will become apparent and more readily understood from the following description of embodiments in conjunction with the accompanying drawings, in which:

[0025] Figure 1 This is a diagram illustrating the operation of providing an alarm by determining that a user is in a dangerous state, according to an embodiment;

[0026] Figure 2 This is a control block diagram according to an embodiment;

[0027] Figure 3 This is a diagram illustrating the operation of determining a user's dangerous state by assigning different weights to the lateral movement distance of the vehicle according to the type, according to an embodiment;

[0028] Figure 4 This is a diagram illustrating the operation of determining a user's dangerous state by assigning different weights to the vehicle's lane encroachment distance according to type, according to an embodiment.

[0029] Figure 5 This is a diagram illustrating the operation of determining a dangerous situation for a user when the vehicle is moving laterally without the user operating the steering wheel, according to an embodiment.

[0030] Figure 6 This is a diagram illustrating the operation of determining a user's dangerous state by assigning different weights to the vehicle's steering wheel angle according to the type, according to an embodiment;

[0031] Figure 7 This is a diagram illustrating the operation of determining a user's dangerous state by assigning different weights based on the number of times the vehicle changes lateral direction according to the type, according to an embodiment; and

[0032] Figure 8 This is a flowchart based on an embodiment. Detailed Implementation

[0033] Throughout this specification, the same numbers denote the same elements. Not all elements of the embodiments of the invention are described, and descriptions of content known in the art or overlapping in the embodiments are omitted. Terms such as “~part,” “~module,” “~component,” and “~block” used throughout this specification can be implemented in software and / or hardware, and multiple “~parts,” “~modules,” “~components,” or “~blocks” can be implemented in a single element, or a single “~part,” “~module,” “~component,” or “~block” can include multiple elements.

[0034] It should also be understood that the term “connection” or its derivatives refer to both direct and indirect connections, with indirect connections including connections made through wireless communication networks.

[0035] It will be further understood that, when used in this specification, the terms “comprising” and / or “including” specify the presence of the said features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements.

[0036] It should be understood that in this specification, when a component is referred to as being "above / below" another component, it can be directly above / below the other component, or there may be one or more intermediate components.

[0037] Although terms such as "first," "second," "A," and "B" can be used to describe various components, the term does not limit the corresponding component, but is only used to distinguish one component from another.

[0038] As used herein, the singular forms “a,” “one,” and “the” are also intended to include the plural forms, unless the context clearly indicates otherwise.

[0039] The reference numerals used in the drawings for method steps are for illustrative purposes only and are not intended to restrict the order of steps. Therefore, unless the context clearly specifies otherwise, the written order may be practiced in other ways.

[0040] The principles and embodiments of this disclosure will now be described with reference to the accompanying drawings.

[0041] Figure 1 This is a diagram illustrating the operation of providing an alarm by determining that a user is in a dangerous state, according to an embodiment. Figure 2 This is a control block diagram according to an embodiment.

[0042] Reference Figure 1 and Figure 2 Vehicle 1 includes: a communicator 100 configured to receive sleep time data and terminal usage data of user 10 from a user terminal; a first sensor 300 configured to acquire image data around vehicle 1; a second sensor 400 configured to acquire travel time data and heading direction data of vehicle 1; an alarm 500; and a controller 200. The controller 200 is configured to: acquire relaxation data of user 10 based on sleep time data and travel time data; calculate a hazard value based on at least one of sleep time data, terminal usage data, relaxation data, and travel time data; classify user 10's fatigue state into multiple hazard types based on the hazard value; identify multiple vehicle travel states based on image data around vehicle 1 and heading direction data of vehicle 1; and assign different weights to each vehicle travel state according to the hazard type to determine whether user 10 is in a dangerous state, and when user 10 is determined to be in a dangerous state, output a control signal to provide a hazard warning through the alarm 500.

[0043] The communicator 100 can receive sleep time data and terminal usage data of user 10 from the user terminal. Sleep time data can refer to data representing the sleep time of user 10 via the user terminal. Terminal usage data can refer to usage data related to user 10's use of the user terminal. The first sensor 300 can refer to a camera. Vehicle 1 driving time data can refer to data recording the time user 10 drives vehicle 1. Vehicle 1 heading data can refer to changes in the direction of vehicle 1 traveling in a straight line. For example, there may be lanes, and the amount of angle of movement when vehicle 1 moves left or right relative to a lane can refer to heading data. Alarm 500 can refer to a device that provides an alarm via a cluster or audio-visual navigation (AVN) system, or a device that provides an alarm to user 10 in various other ways. Relaxation data can refer to a value obtained by subtracting sleep time and vehicle 1 driving time from 24 hours. Hazard value can refer to a value obtained by quantifying the degree of fatigue felt by user 10 while driving. Hazard values ​​can be calculated based on at least one of the following: sleep time, terminal usage time, relaxation time, and travel time. Hazard values ​​can be calculated by assigning different hazard levels to each of these factors.

[0044] A hazard level can refer to a value assigned to sleep time data, driving time data, relaxation data, and user terminal usage data. Hazard values ​​can be calculated by assigning different or the same hazard level to each of these data types. Alternatively, a hazard level can be assigned to sleep time data, and a lower hazard level can be assigned to driving time data, with the hazard value calculated based on both the assigned hazard levels. For example, a hazard value can be calculated by multiplying the sleep time data by a hazard level of 2 and the driving time data by a hazard level of 1.5.

[0045] The assignment of hazard levels can be arbitrarily specified by user 10, or it can be performed based on a general calculation method. Furthermore, a higher hazard level can be assigned to user 10's relaxation data than to driving time data, and a hazard value can be calculated based on the relaxation data and driving time data with assigned hazard levels. In this case, a higher hazard level can be assigned to the relaxation data than to the sleep time data. Additionally, when it is determined, based on terminal usage data, that the user terminal was activated during driving due to receiving an input command from user 10, or when it is determined that an input command from user 10 is detected within a predetermined input time after the user terminal was activated without user input, the controller 200 can acquire data on the number of times a specific function of the user terminal was commanded and usage time data within a predetermined operation time starting from the time the input command from the user was received, and calculate a hazard value based on the acquired number of times and usage time data.

[0046] Furthermore, if the time elapsed since the user terminal received the input command exceeds a predetermined reference time, the controller 200 can provide a hazard alarm. Based on the magnitude of the hazard value, multiple hazard types can be identified. A hazard value can refer to a value ultimately determined by assigning different hazard levels to multiple data points. Dividing into multiple types can mean dividing the hazard value into multiple ranges to distinguish multiple types. For example, suppose a hazard level of -4 is assigned to the user's sleep time, a hazard level of -8 to relaxation time, and a hazard level of 2 to driving time, with a default hazard level of 50. Assuming the user's sleep time is 2 hours, relaxation time is 1 hour, and driving time is 10 hours, the hazard value is obtained by multiplying the time value of each data point by its hazard level and adding the product to the default hazard level; that is, a hazard value of 54 is obtained. If the hazard type is divided into three types based on the hazard value, such as hazard type 1 (hazard value less than or equal to 50), hazard type 2 (hazard value greater than 50 and less than 70), and hazard type 3 (hazard value greater than or equal to 70 and less than 90), then the user's fatigue state belongs to hazard type 2. Based on this result, the weights corresponding to hazard type 2 are assigned to the vehicle's driving state to determine the hazard state.

[0047] The method for calculating hazard values ​​can be set in various ways, and the type based on the range of hazard values ​​can be set in various ways. Furthermore, the method for assigning weights can be set in various ways. Based on image data surrounding vehicle 1 and heading data of vehicle 1, multiple driving states of vehicle 1 can be distinguished. The driving states of vehicle 1 will be described in detail below. In this case, different weights are assigned to each driving state of vehicle 1 according to the type of hazard, thereby determining the hazard state of user 10. A hazard state can refer to a state that requires an alert to notify user 10 of the danger. Weights can be assigned predetermined values ​​to reference values ​​to determine whether user 10 is in a hazard state in each driving state of vehicle 1. For example, when vehicle 1 moves laterally in a driving state without user 10 manipulating the steering wheel, the reference value can be the amount by which the vehicle moves laterally without manipulating the steering wheel. In this scenario, based on the weighted reference values, if user 10 corresponds to a hazard type with a very high hazard value, a lateral movement of 1 meter (1m) can be identified as a hazard state; if user 10 corresponds to a hazard type with a medium hazard value, a lateral movement of 1.5m can be identified as a hazard state; and if user 10 corresponds to a hazard type with a low hazard value, a lateral movement of 2m can be used as a reference for determining the hazard state. That is, in the driving state where vehicle 1 is moving laterally without steering, the reference value can be the lateral movement distance, and the weight can refer to the correction value assigned to the reference value to determine the notification state. Depending on the driving state of vehicle 1, the reference value and weight can be different variables, and the degree of weighting also varies depending on the driving state of vehicle 1.

[0048] The controller 200 is a processor that controls the overall operation of the vehicle 1, and may also be a processor of an electronic control unit (ECU) that controls the overall operation of the powertrain system. Furthermore, the controller 200 can control the operation of various modules, devices, etc., built into the vehicle 1. According to an embodiment, the controller 200 can control the operation of each component by generating control signals for controlling the various modules, devices, etc., built into the vehicle 1.

[0049] Furthermore, the controller 200 may include a memory and a processor. The memory stores programs for performing the operations described above and below, as well as various related data, and the processor executes the programs stored in the memory. Additionally, the controller 200 may be integrated into a System-on-Chip (SOC) built into the vehicle 1 and can be operated by a processor. However, since multiple SOCs can be embedded in the vehicle 1 instead of just one, the controller 200 is not limited to integration into a single SOC.

[0050] The communicator may include one or more components capable of communicating with external devices, and may include at least one of a short-range communication module and a wireless communication module.

[0051] Short-range communication modules can include various short-range communication modules that use wireless communication networks to send and receive signals over short distances, such as Bluetooth modules, infrared communication modules, radio frequency identification (RFID) communication modules, wireless local area network (WLAN) communication modules, NFC communication modules, and Zigbee communication modules.

[0052] Wireless communication modules may include wireless communication modules that support various wireless communication methods, such as Wifi modules, wireless broadband (Wibro) modules, Global System for Mobile Communications (GSM) modules, Code Division Multiple Access (CDMA) modules, Wideband Code Division Multiple Access (WCDMA) modules, Universal Mobile Telecommunications System (UMTS) modules, Time Division Multiple Access (TDMA) modules, Long Term Evolution (LTE) modules, etc.

[0053] The wireless communication module may include a wireless communication interface, which includes an antenna and a transmitter for transmitting signals. Furthermore, the wireless communication module may also include a signal conversion module for converting digital control signals output from the control unit via the wireless communication interface into wireless signals in analog form, under the control of the control unit.

[0054] The wireless communication module may include a wireless communication interface, which includes an antenna and a receiver for receiving signals. Furthermore, the wireless communication module may also include a signal conversion module for demodulating the wireless signals received through the wireless communication interface from analog signal form into digital control signals.

[0055] The controller 200 may be implemented using at least one of the following types of storage media: flash memory, hard disk, multimedia card micro / card-type memory (e.g., SD or XD memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic storage, magnetic disk, and optical disk. However, the controller 200 is not limited to these, and may be implemented in any other form known in the art.

[0056] At least one component can be added or omitted to correspond to Figure 2 The performance of the components of the device shown. Furthermore, the relative positions of the components can be varied to correspond to the performance or structure of the system.

[0057] Figure 2Some of the components shown may refer to software components and / or hardware components, such as field-programmable gate arrays (FPGAs) and application-specific integrated circuits (ASICs).

[0058] Figure 3 This is a diagram illustrating the operation of determining a user's dangerous state by assigning different weights to the lateral movement distance of the vehicle according to the type, according to an embodiment.

[0059] Specific reference Figure 3 Based on image data surrounding vehicle 1-1a and its heading data, the lateral movement distance D1 of vehicle 1-1a relative to the lane is acquired. Different weights are assigned to this lateral movement distance D1 data according to its type to determine the user's dangerous state. For example, when categorized into three types based on hazard value, even if the lateral movement distance D1 of vehicle 1-1a is the same, the dangerous state can be determined based on the different types. For instance, based on the type, a lateral movement distance D1 of 3 meters, 2 meters, and 1 meter can be respectively identified as a dangerous state for the user. In this case, the user might move 1.5 meters laterally, and if the user's state belongs to the second or third type based on the hazard value (i.e., based on the hazard value state), the user can be determined to be in a dangerous state; however, if the user's state corresponds to the first type, the user can be determined not to be in a dangerous state.

[0060] Figure 4 This is a diagram illustrating the operation of determining a user's dangerous state by assigning different weights to the vehicle's lane encroachment distance according to type, according to an embodiment.

[0061] Specific reference Figure 4 The controller can be configured to acquire lane occupancy distance data of vehicles 1-2 based on image data surrounding vehicles 1-2 and their heading data, and assign different weights to the lane occupancy distance data according to type to determine the user's hazard status. For example, if the user of vehicle 1-2 corresponds to the hazard type with the highest hazard value, it is immediately identified as a hazard status and a hazard warning needs to be provided even if the lane occupancy distance D2 is small. If the user of vehicle 1-2 corresponds to a hazard type with a medium hazard value, a hazard warning can be provided in response to the lane occupancy distance D2 being greater than the lane occupancy distance of the highest hazard type, and if the user of vehicle 1-2 corresponds to a hazard type with the lowest hazard value, a hazard status can be determined and a hazard warning provided in response to the lane occupancy distance D2 being greater than the lane occupancy distance of the medium hazard type.

[0062] Figure 5This diagram illustrates the operation of determining a user's dangerous situation when the vehicle is moving laterally without the user operating the steering wheel, according to an embodiment.

[0063] Specific reference Figure 5 If, without steering wheel manipulation, the heading of vehicles 1-3 corresponds to the lateral direction rather than the straight direction relative to the lane, the controller can determine that the user's hazard level is high. Even in this case, the level used to determine the need for an alert can vary depending on the amount of lateral movement of vehicles 1-3. That is, the type of hazard is determined based on the user's hazard level, and different weights are assigned according to the hazard type when vehicles 1-3 move laterally without the user manipulating the steering wheel, thus issuing an alert based on the amount of lateral movement of the vehicle. For example, even if vehicles 1-3 do not move laterally like... Figure 3 While lateral movement may not be as extensive as shown, it can also be a factor to consider when determining if the user is in a dangerous situation if the lateral movement is performed without the user manipulating the steering wheel. In this case, even if the vehicle does not move as much in the lateral direction as shown... Figure 3 As shown, the vehicle moves laterally as much as it would in a typical hazard class. However, if the user is classified as a high-hazard type, the system can also determine if the user is in a dangerous situation and provide a hazard warning if the vehicle moves laterally to a certain extent without steering wheel input. Similarly, if the user is classified as a low-hazard type, the system can determine if the user is in a dangerous situation and provide a hazard warning if the vehicle moves laterally by a greater amount than in a high-hazard class. Steering wheel input can be determined using steering sensors within the vehicle.

[0064] Figure 6 This is a diagram illustrating the operation of determining a user's dangerous state by assigning different weights to the vehicle's steering wheel angle according to the type, according to an embodiment.

[0065] Specific reference Figure 6 The controller can acquire the steering wheel angle 40 of vehicle 1-4a based on image data of the area surrounding vehicle 1-4a and the heading data of vehicle 1-4a. It can also assign different weights to the steering wheel angle data and lateral movement distance data of vehicle 1-4a according to the type to determine the user's dangerous state. In this case, when the steering wheel angle 40 of vehicle 1-4a is greater than or equal to a reference angle determined according to the type, the user can be determined to be in a dangerous state. Furthermore, by assigning different weights based on the type of danger value, the user's state can be determined to be dangerous. For example, in the case of a danger type with a high danger value, even a slight turn of the steering wheel angle can be determined to be a dangerous state and an alarm can be issued.

[0066] Figure 7 This is a diagram illustrating the operation of determining a user's dangerous state by assigning different weights to the number of times the vehicle is turned laterally according to the type, according to an embodiment.

[0067] Specific reference Figure 7 The controller can be configured to acquire lateral direction change count data related to the number of times the vehicle changes lateral direction within a predetermined change time, based on lateral movement distance data, and assign different weights to the lateral direction change count data according to type to determine the user's dangerous state. For example, even if the lateral movement distance D4 along the vehicle is greater than... Figure 3 The distance traveled is short, but if the vehicle's steering wheel is continuously turned while changing direction, the user's state can be determined to be dangerous. In this case, if the situation is divided into three types based on the degree of danger, an alarm can be issued when the lateral direction is changed twice for the highest degree of danger; an alarm can be issued when the lateral direction is changed three times for the medium degree of danger; and an alarm can be issued when the lateral direction is changed four times for the lowest degree of danger.

[0068] Figure 8 This is a flowchart based on an embodiment.

[0069] Specific reference Figure 8 At step 1001, the controller can acquire multiple data points. As mentioned above, these data points may include user sleep time data, user terminal usage data, image data of the vehicle's surroundings, vehicle travel time data, and vehicle heading data, and may also include relaxation data. Next, at step 1002, the controller can calculate a hazard value. As mentioned above, the hazard value can refer to a value obtained by quantifying the user's perceived level of fatigue. Next, at step 1003, the type can be classified according to the magnitude of the hazard value. In the accompanying figure, the type can refer to the hazard type, and can be broadly divided into three types: stage one, stage two, and stage three. Classification can also refer to classifying the user's fatigue state into multiple types based on the hazard value. Next, at step 1004, different weights can be assigned to the vehicle's driving mode data according to each stage. In this case, image data can be considered together with the vehicle's driving mode. Next, at step 1005, the user's hazardous state can be determined, and if the user is determined to be in a hazardous state, an alarm can be provided at step 1006. In the accompanying figure, the alarm can refer to a hazard alarm.

[0070] Furthermore, the disclosed embodiments can be implemented in the form of a recording medium storing computer-executable instructions. The instructions can be stored as program code, and when executed by a processor, the instructions can generate program modules to perform the operations of the disclosed embodiments. The recording medium can be a computer-readable recording medium.

[0071] Computer-readable recording media include all kinds of recording media that store instructions that can be decoded by a computer, such as read-only memory (ROM), random access memory (RAM), magnetic tape, magnetic disk, flash memory, optical data storage devices, etc.

[0072] As is evident from the above, the vehicle and its control method according to the embodiments can improve user safety by classifying the user's state into multiple stages and assigning different weights to each driving state of the vehicle according to the danger value corresponding to each stage.

[0073] While embodiments of this disclosure have been described for illustrative purposes, those skilled in the art will understand that various modifications, additions, and substitutions are possible without departing from the scope and spirit of this disclosure. Therefore, embodiments of this disclosure are not described for limiting purposes.

Claims

1. A vehicle comprising: The communicator receives user sleep time data and user terminal usage data from the user terminal. The first sensor acquires image data of the vehicle's surroundings; The second sensor acquires vehicle travel time data and vehicle heading data; Alarm; as well as The controller is configured as follows: Based on the sleep time data and the driving time data, obtain the user's relaxation time data; The danger value is calculated based on at least one of the sleep time data, the terminal usage data, the user relaxation time data, and the driving time data. Based on the aforementioned risk values, the user's fatigue state is classified into multiple risk types; Based on image data around the vehicle and the vehicle's heading data, the driving status of multiple vehicles is identified; as well as Different weights are assigned to each vehicle driving state according to the type of danger to determine whether the user is in a dangerous situation, and when it is determined that the user is in a dangerous situation, a control signal is output to provide an alarm through the alarm. The controller is further configured to assign a hazard level to at least one of the sleep time data, terminal usage data, user relaxation time data, and driving time data, and to calculate the hazard value by multiplying the data of the sleep time data, terminal usage data, user relaxation time data, and driving time data with the assigned hazard level, generating at least one product result, and adding the at least one product result to a baseline hazard level.

2. The vehicle according to claim 1, wherein, The controller is configured to: Assign hazard levels to the sleep time data, and assign a lower hazard level to the driving time data than the hazard level assigned to the sleep time data; and The danger value is calculated based on user sleep time data and driving time data assigned to danger levels.

3. The vehicle according to claim 1, wherein, The controller is configured to: Assign a hazard level to the user relaxation time data, and assign a lower hazard level to the driving time data than the hazard level assigned to the user relaxation time data; and The hazard value is calculated based on user relaxation time data and driving time data assigned to hazard levels.

4. The vehicle according to claim 1, wherein, The controller is configured to: When it is determined, based on the terminal usage data, that the user terminal is activated during driving due to receiving a user input command, or when it is determined that a user input command is detected within a predetermined input time after the user terminal is activated without user input, the system acquires data on the number of times a specific function of the user terminal is commanded and the usage time data within a predetermined operation time starting from the time point from the time the user input command is received, and calculates the danger value based on the acquired data on the number of times and the usage time data.

5. The vehicle according to claim 4, wherein, The controller is configured to: If the time from the moment the user terminal receives the input command exceeds a predetermined reference time, a control signal is output to provide a danger alarm.

6. The vehicle according to claim 1, wherein, The controller is configured to: Based on image data of the vehicle's surroundings and the vehicle's heading data, lateral movement distance data relative to the lane is obtained, and different weights are assigned to the lateral movement distance data according to the hazard type to determine the user's hazard status.

7. The vehicle according to claim 1, wherein, The controller is configured to: Based on image data of the vehicle's surroundings and the vehicle's heading data, lane occupancy distance data of the vehicle is obtained, and different weights are assigned to the lane occupancy distance data according to the type of danger to determine the user's danger status.

8. The vehicle according to claim 6, wherein, The controller is configured to: Based on image data of the vehicle's surroundings and the vehicle's heading data, the vehicle's steering wheel angle data is obtained, and different weights are assigned to the steering wheel angle data and the lateral movement distance data according to the type of danger, in order to determine the user's dangerous state.

9. The vehicle according to claim 6, wherein, The controller is configured to: Based on the lateral movement distance data, lateral direction conversion count data related to the number of times the vehicle changes lateral direction within a predetermined conversion time is obtained, and different weights are assigned to the lateral direction conversion count data according to the hazard type to determine the user's hazard status.

10. A method for controlling a vehicle, comprising: Receive user sleep time data and user terminal usage data from the user terminal; Acquire image data of the area surrounding the vehicle; Acquire vehicle travel time data and vehicle heading data; Based on the sleep time data and the driving time data, obtain the user's relaxation time data; The danger value is calculated based on at least one of the sleep time data, the terminal usage data, the user relaxation time data, and the driving time data. Based on the aforementioned risk values, the user's fatigue state is classified into multiple risk types; Based on image data around the vehicle and the vehicle's heading data, various vehicle driving states are identified; as well as Different weights are assigned to each vehicle driving state based on the type of hazard to determine whether the user is in a dangerous situation, and when a dangerous situation is determined, a control signal is output to provide a hazard warning. The calculation of the hazard value includes: assigning a hazard level to at least one of the sleep time data, terminal usage data, user relaxation time data, and driving time data; multiplying the data of the sleep time data, terminal usage data, user relaxation time data, and driving time data with the assigned hazard level to generate at least one product result; and adding the at least one product result to the baseline hazard level to calculate the hazard value.

11. The method according to claim 10, wherein, Calculating the hazard value includes: Assign hazard levels to the sleep time data, and assign a lower hazard level to the driving time data than the hazard level assigned to the sleep time data; and The danger value is calculated based on user sleep time data and driving time data assigned to danger levels.

12. The method according to claim 10, wherein, Calculating the hazard value also includes: Assign a hazard level to the user's relaxation time data, and assign a lower hazard level to the driving time data than the hazard level assigned to the user's relaxation time data; and The hazard value is calculated based on user relaxation time data and driving time data assigned to hazard levels.

13. The method according to claim 10, wherein, Calculating the hazard value also includes: When, based on the terminal usage data, it is determined that the user terminal was activated during driving due to receiving a user input command, or when it is determined that a user input command was detected within a predetermined input time after the user terminal was activated without user input, Acquire data on the number of times a specific function of the user terminal is commanded and the usage time data within a predetermined operation period starting from the time the input command from the user is received; and The danger value is calculated based on the number of times data and usage time data obtained.

14. The method of claim 10, wherein, Providing the aforementioned danger alert includes: The danger alarm is provided when the time from the moment the user terminal receives the input command exceeds a predetermined reference time.

15. The method according to claim 10, wherein, Determining the user's dangerous state includes: Based on image data of the vehicle's surroundings and the vehicle's heading data, lateral movement distance data of the vehicle relative to the lane is obtained, and different weights are assigned to the lateral movement distance data according to the type of hazard.

16. The method of claim 10, wherein, Determining the user's dangerous state includes: Based on the image data around the vehicle and the vehicle's heading data, lane encroachment distance data of the vehicle is obtained, and different weights are assigned to the lane encroachment distance data according to the hazard type.

17. The method according to claim 15, wherein, Determining the user's dangerous state includes: Based on the image data around the vehicle and the vehicle's heading data, the vehicle's steering wheel angle data is obtained, and different weights are assigned to the steering wheel angle data and the lateral movement distance data according to the type of danger.

18. The method according to claim 15, wherein, Determining the user's dangerous state includes: Based on the lateral movement distance data, lateral direction conversion frequency data related to the number of times the vehicle changes lateral direction within a predetermined conversion time is obtained, and different weights are assigned to the lateral direction conversion frequency data according to the hazard type.

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