Vehicle and method of controlling a vehicle

Abstract

The present invention relates to a vehicle and a method of controlling a vehicle. According to an embodiment, a vehicle is provided, which includes a sensor unit, one or more processors, and a memory configured to store one or more programs executed by the one or more processors, wherein the sensor unit detects driving data of the vehicle and biometric information of an occupant of the vehicle; the processor analyzes a correlation between regenerative braking information of the driving data of the vehicle, acceleration information generated during the regenerative braking, and the biometric information, analyzes a car sickness risk of the occupant based on the correlation analysis, and generates and outputs a car sickness alleviation feedback signal according to the car sickness risk. The car sickness alleviation feedback signal can include at least one of a sound signal and a vibration signal.

Description

[0001] Cross-references to related applications

[0002] This application claims the benefit of Korean Patent Application No. 10-2025-0040163, filed with the Korean Intellectual Property Office on March 28, 2025, the entire contents of which are incorporated herein by reference. Technical Field

[0003] This invention relates to embodiments concerning vehicles and methods for controlling vehicles. Background Technology

[0004] With increasing focus on environmentally friendly vehicles, the supply of electric vehicles is expanding, and various technologies are being developed to maximize their energy efficiency. Unlike internal combustion engine vehicles, electric vehicles are driven by electric motors and can perform regenerative braking by converting the drive motor into a generator when decelerating during operation.

[0005] Regenerative braking is a method of converting a vehicle's kinetic energy into electrical energy during deceleration and storing that energy in a battery. Regenerative braking can provide braking force to slow a vehicle down or bring it to a complete stop without using traditional friction brakes. Therefore, by reusing the energy stored in the battery during acceleration, unnecessary energy loss can be reduced and the vehicle's energy efficiency improved.

[0006] However, the characteristics / feel of regenerative braking differ from that of conventional braking (e.g., braking performed in a conventional internal combustion engine vehicle). This difference may cause some occupants to experience motion sickness. In particular, when regenerative braking is applied strongly, when the vehicle's deceleration patterns are inconsistent, or when rapid acceleration and deceleration are repeated, occupants are more likely to experience motion sickness due to the mismatch between vestibular and visual information. This phenomenon is especially pronounced for occupants sitting in the rear seats, as the perception of acceleration and deceleration is more intense in the rear compared to the front seats. Summary of the Invention

[0007] Various aspects of the present invention provide a vehicle and a method for controlling the vehicle, wherein a customized feedback system can be provided to prevent and mitigate motion sickness that may occur due to the regenerative braking characteristics of an electric vehicle, so as to improve occupant comfort and maximize the energy efficiency of the vehicle.

[0008] According to an implementation scheme, a vehicle is provided, comprising a sensor unit, one or more processors, and a memory configured to store one or more programs executed by the one or more processors, wherein the sensor unit detects vehicle driving data and biometric information of vehicle occupants; the processor analyzes the correlation between regenerative braking information of the vehicle driving data, acceleration information generated during regenerative braking, and biometric information, analyzes the occupant's motion sickness risk based on the correlation, and generates and outputs a motion sickness mitigation feedback signal based on the motion sickness risk.

[0009] Motion sickness relief feedback signals may include at least one sound signal and a vibration signal.

[0010] Biometric information may include at least one of the occupant's heart rate, respiratory information, skin stimulation information, and motion information.

[0011] Regenerative braking information may include regenerative braking stage information.

[0012] The processor may include a motion sickness prediction model, which analyzes the risk of motion sickness by analyzing the correlation between regenerative braking information, acceleration information and biometric information.

[0013] Motion sickness prediction models can learn from changes in biometric information, including regenerative braking phase and acceleration information, within regenerative braking information.

[0014] Motion sickness prediction models can predict the risk of motion sickness based on changes in biometric information.

[0015] The processor can generate and output motion sickness mitigation feedback signals at each stage based on the risk of motion sickness.

[0016] The processor can generate and output an audible signal for stabilizing the heart rate based on the acceleration generated during regenerative braking within a first threshold range.

[0017] The processor can generate and output an acoustic signal for stabilizing the breathing pattern based on the acceleration generated during regenerative braking within a second threshold range.

[0018] The processor can adjust the intensity and pattern of the vibration signal based on the risk of motion sickness.

[0019] According to an implementation scheme, a method for controlling a vehicle executed by a computing device is provided, the computing device including a sensor unit, one or more processors, and a memory configured to store one or more programs executed by the one or more processors. The method includes: detecting vehicle driving data and biometric information of vehicle occupants by the sensor unit; analyzing the correlation between regenerative braking information of the vehicle driving data, acceleration information generated during regenerative braking, and biometric information by the processors; analyzing the occupants' motion sickness risk based on the correlation by the processors; and generating and outputting a motion sickness mitigation feedback signal by the processors based on the motion sickness risk.

[0020] Motion sickness relief feedback signals may include at least one sound signal and a vibration signal.

[0021] Biometric information may include at least one of the occupant's heart rate, respiratory information, skin stimulation information, and motion information.

[0022] Regenerative braking information may include regenerative braking stage information.

[0023] The processor may include a motion sickness prediction model, which analyzes the risk of motion sickness by analyzing the correlation between regenerative braking information, acceleration information and biometric information.

[0024] Analyzing the correlation between regenerative braking information, acceleration information, and biometric information can include: learning changes in biometric information based on the regenerative braking phase and acceleration information included in the regenerative braking information by a motion sickness prediction model.

[0025] Analyzing motion sickness risk can include using motion sickness prediction models to predict the risk of motion sickness based on changes in biometric information.

[0026] Generating and outputting motion sickness relief feedback signals can include: generating and outputting motion sickness relief feedback signals for each stage based on motion sickness risk.

[0027] Generating and outputting motion sickness relief feedback signals may include: generating and outputting an audible signal for stabilizing heart rate based on the acceleration generated during regenerative braking within a first threshold range.

[0028] Generating and outputting motion sickness relief feedback signals may include generating and outputting sound signals for stabilizing breathing patterns based on acceleration generated during regenerative braking within a second threshold range.

[0029] Generating and outputting motion sickness mitigation feedback signals can include adjusting the intensity and pattern of vibration signals based on the risk of motion sickness. Attached Figure Description

[0030] The foregoing and other aspects, features, and advantages, as well as the following detailed description of embodiments, will be better understood when read in conjunction with the accompanying drawings. However, the invention is not intended to be limited to the details shown in the drawings, and various modifications and structural changes can be made therein without departing from the spirit of the invention and within the scope and limits of its equivalents. The same reference numerals and identifiers in the various drawings denote the same elements.

[0031] Figure 1 An exemplary schematic diagram of a vehicle configured to communicate with another device to send and receive data, according to an exemplary embodiment of the present invention, is shown.

[0032] Figure 2 A schematic diagram of modules constituting a vehicle according to an exemplary embodiment of the present invention is shown.

[0033] Figure 3 A system configured to enable a user to view driving content in a virtual environment, according to an exemplary embodiment of the present invention, is shown.

[0034] Figure 4 A schematic diagram of a seat including a vibrator according to an exemplary embodiment of the present invention is shown.

[0035] Figure 5 An illustrative system for operating a vehicle according to an exemplary embodiment of the present invention is shown.

[0036] Figure 6 A schematic diagram of a vehicle configured to perform regenerative braking according to an exemplary embodiment of the present invention is shown.

[0037] Figure 7 A flowchart of a method for controlling a vehicle according to an exemplary embodiment of the present invention is shown. Detailed Implementation

[0038] The following will describe in detail exemplary embodiments of the present invention. These exemplary embodiments are based on the technical solutions of the present invention and illustrate specific implementation methods and specific operation processes, but the scope of protection of the present invention is not limited to the following exemplary embodiments.

[0039] The following specific embodiments are provided by way of example only and are not restrictive. Furthermore, they are not intended to be construed as being bound by any express or implied theories presented in the foregoing background or the following specific embodiments.

[0040] Reference will now be made in detail to various exemplary embodiments of this subject matter, examples of which are illustrated in the accompanying drawings. While various embodiments are discussed herein, it should be understood that the embodiments are not intended to be limited to these embodiments. Rather, the presented embodiments are intended to cover alternatives, modifications, and equivalents that may be included within the spirit and scope of the various embodiments defined in the appended claims. Furthermore, in the detailed description, numerous specific details are set forth to provide a comprehensive understanding of the embodiments of this subject matter. However, the embodiments may be practiced without these specific details. In other instances, well-known methods, processes, components, and circuits have not been described in detail to avoid unnecessarily obscuring aspects of the described embodiments.

[0041] Some parts described in detail below are presented from the perspective of data processing procedures, logic blocks, processing, and other symbolic representations within an electrical device. These descriptions and representations are the means by which those skilled in the art of data processing most effectively communicate their work to others skilled in the art. In this application, procedures, logic blocks, processing, etc., are considered as one or more self-consistent processes or instructions that lead to a desired result. These processes are those that require physical manipulation of physical quantities. Typically (although not necessarily), these physical quantities may take the form of electrical or magnetic signals that can be stored, transmitted, combined, compared, and otherwise manipulated in electronic systems, devices, and / or components.

[0042] However, it should be remembered that these and similar terms are to be associated with appropriate physical quantities and are merely convenient labels applied to those quantities. Unless otherwise explicitly stated in the following discussion, it will be understood that throughout the description of the implementation, discussions using terms such as “determine,” “communicate,” “acquire,” “compare,” “monitor,” “calibrate,” “estimate,” “start,” “provide,” “receive,” “control,” “send,” “isolate,” “generate,” “align,” “synchronize,” “identify,” “hold,” “display,” “switch,” etc., refer to the actions and processing of electronic products such as processors, sensor processing units (SPUs), processors of sensor processing units, application processors of electronic devices / systems, etc., or combinations thereof. This product operates and converts data represented as physical (electronic and / or magnetic) quantities in registers and memory into other data similarly represented as physical quantities in memory or registers or other such information storage, transmission, processing, or display components.

[0043] It should be understood that, as used herein, the terms "vehicle" or "of a vehicle" or other similar terms generally include motor vehicles, such as passenger vehicles including sport utility vehicles (SUVs), buses, trucks, various commercial vehicles, vessels including various boats and ships, aircraft, etc., and include hybrid vehicles, electric vehicles, plug-in hybrid electric vehicles, hydrogen-powered vehicles, and other alternative fuel vehicles (e.g., fuels derived from non-petroleum energy sources). As referred to herein, a hybrid vehicle is a vehicle having two or more power sources, such as a vehicle powered by both gasoline and electricity. In various respects, a vehicle may include the internal combustion engine system disclosed herein.

[0044] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the invention. Unless the context clearly indicates otherwise, the singular forms used herein are intended to include the plural forms as well. These terms are intended only to distinguish one component from another, and these terms do not limit the nature, order, or sequence of the components. It should be further understood that when the terms “comprising” and / or “including” are used in this specification, they indicate the presence of the stated features, values, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, values, steps, operations, elements, components, and / or combinations thereof. As used herein, the term “and / or” includes any and all combinations of one or more of the associated listed items. Throughout the specification, unless explicitly stated otherwise, the word “comprising” and variations such as “including” and “including” will be understood to imply the inclusion of the stated elements, but do not exclude any other elements. Furthermore, the terms “unit,” “device,” “component,” and “module” described in the specification refer to a unit for performing at least one function and operation, and can be implemented by hardware components or software components and combinations thereof.

[0045] While exemplary embodiments are described as utilizing multiple units to perform exemplary processes, it should be understood that exemplary processes can also be performed by one or more modules. Furthermore, it should be understood that the term controller / control unit refers to a hardware device including memory and a processor and specifically programmed to perform the processes described herein. The memory is configured to store modules, and the processor is specifically configured to execute the modules to perform one or more processes further described below.

[0046] Furthermore, the control logic of the present invention can be implemented as a non-transitory computer-readable medium containing executable program instructions that are executed by a processor, controller, etc. Examples of computer-readable media include, but are not limited to, ROM, RAM, optical disc (CD)-ROM, magnetic tape, floppy disk, flash drive, smart card, and optical data storage device. The computer-readable medium can also be distributed across a network-connected computer system, enabling it to be stored and executed in a distributed manner, for example, via a telematics server or a controller area network (CAN).

[0047] Unless otherwise specified or obvious from the context, as used herein, the term "approximately" is understood to mean within the normal tolerance range in the field, such as within the standard deviation of two means. "Approximately" can be understood as within 10%, 9%, 8%, 7%, 6%, 5%, 4%, 3%, 2%, 1%, 0.5%, 0.1%, 0.05%, or 0.01% of the specified value. Unless the context clearly specifies otherwise, all numerical values ​​provided herein are modified by the term "approximately".

[0048] The embodiments described herein can be discussed in the general context of processor-executable instructions (such as program modules) existing on some form of non-transitory processor-readable medium, which are executed by one or more computers or other devices. Typically, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. In various embodiments, the functionality of program modules can be combined or distributed as needed.

[0049] In the figures, a single box can be described as performing one or more functions; however, in practice, the one or more functions performed by the box may be performed in a single component or across multiple components, and / or may be performed using hardware, software, or a combination of hardware and software. To clearly illustrate this interchangeability of hardware and software, various illustrative components, boxes, modules, logic, circuits, and steps have been generally described according to their functions. Whether such functionality is implemented in hardware or software depends on the specific application and the design constraints imposed on the entire system. Those skilled in the art can implement the described functions in different ways for each specific application, but such implementation decisions should not be construed as causing a departure from the scope of the invention. Furthermore, the exemplary device vibration sensing system and / or electronic device described herein may include components other than those shown, including well-known components.

[0050] Unless specifically described as implemented in a particular manner, the various techniques described herein can be implemented in hardware, software, firmware, or any combination thereof. Any feature described as a module or component can also be implemented together as an integrated logic device or separately as a discrete but interoperable logic device. If implemented in software, these techniques can be implemented at least in part through a non-transitory processor-readable storage medium comprising instructions that, when executed, perform one or more of the methods described herein. The non-transitory processor-readable data storage medium can form part of a computer program product that may include encapsulation material.

[0051] Non-transitory processor-readable storage media may include random access memory (RAM) such as synchronous dynamic random access memory (SDRAM), read-only memory (ROM), non-volatile random access memory (NVRAM), electrically erasable programmable read-only memory (EEPROM), flash memory, and other known storage media. Alternatively, these technologies may be implemented at least in part through processor-readable communication media that carry or transmit code in the form of instructions or data structures and can be accessed, read, and / or executed by a computer or other processor.

[0052] The various implementations described herein can be executed by one or more processors (such as one or more motion processing units (MPUs), sensor processing units (SPUs), main processors or their cores, digital signal processors (DSPs), general-purpose microprocessors, application-specific integrated circuits (ASICs), application-specific instruction set processors (ASIPs), field-programmable gate arrays (FPGAs), programmable logic controllers (PLCs), complex programmable logic devices (CPLDs), discrete gate or transistor logic, discrete hardware components, or any combination thereof) or other equivalent integrated or discrete logic circuits designed to perform the functions described herein. As used herein, the term "processor" can refer to any of the above-described structures or any other structures suitable for implementing the techniques described herein. As used in this specification, the term "processor" can generally refer to any computing processing unit or device, including but not limited to single-core processors; single-processors with software multithreading capabilities; multi-core processors; multi-core processors with software multithreading capabilities; multi-core processors with hardware multithreading technology; parallel platforms; and parallel platforms with distributed shared memory. Furthermore, processors can utilize nanoscale architectures, such as, but not limited to, molecular and quantum dot-based transistors, switches, and gates, to optimize space utilization or improve the performance of user devices. Processors can also be implemented as combinations of computing units.

[0053] Furthermore, in some aspects, the functionality described herein can be provided within dedicated software or hardware modules configured as described herein. Moreover, these techniques can be fully implemented in one or more circuit or logic elements. The general-purpose processor can be a microprocessor, but alternatively, the processor can be any processor, controller, microcontroller, or state machine. The processor can also be implemented as a combination of computing devices, such as a combination of an SPU / MPU and a microprocessor, multiple microprocessors, one or more microprocessors combined with an SPU core, an MPU core, or any other such configuration. One or more components of the SPU or electronic device described herein can be implemented in one or more forms such as a “chip,” a “package,” or an integrated circuit (IC).

[0054] In the following description, embodiments will be described in detail with reference to the accompanying drawings, and regardless of the reference numerals, the same or corresponding components will be indicated by the same reference numerals and repeated descriptions will be omitted.

[0055] Figure 1 This is an exemplary schematic diagram illustrating a vehicle 100 configured to communicate with another device 400 to send and receive data. Figure 2 This is a schematic diagram illustrating the modules constituting a vehicle according to an exemplary embodiment of the present invention. (Refer to...) Figure 1 and Figure 2 Describe the vehicle.

[0056] Reference Figure 1 Vehicle 100 can be configured to be driven by either electricity or fossil fuels. In the case of electricity, vehicle 100 can be, for example, a pure battery vehicle driven solely by a high-voltage battery, or it can employ a gas-based fuel cell as its energy source. Furthermore, the fuel cell can utilize various forms of gas capable of generating electricity, which can be, for example, liquefied and charged into vehicle 100. Here, the gas can be, for example, hydrogen. However, the invention is not limited to this, and various gases can be used. In the case of fossil fuels, vehicle 100 can be driven by fuels such as gasoline, diesel, or liquefied petroleum gas, and is equipped with an internal combustion engine that drives the actuation unit 116 by burning fuel. From the perspective of providing the driving rotational force to the wheel drive unit 118, the engine can be included in the energy generation unit 110. As another example, vehicle 100 can be configured to selectively utilize energy from a fossil fuel-based internal combustion engine and a battery to drive the actuation unit 116, and / or it can be a hybrid vehicle.

[0057] Vehicle 100 may include a mobile device. Vehicle 100 may include a ground vehicle configured to travel on the ground, and may include typical passenger cars or commercial vehicles, purpose-built vehicles (PBVs), etc. Vehicle 100 may be a four-wheeled vehicle (e.g., a passenger car, SUV, or minivan) or a vehicle with more than four wheels (e.g., a bus, large truck, container truck, heavy equipment vehicle, etc.). Here, ground vehicle may refer not only to vehicles that move on land, but also to vehicles that move underground. Vehicle 100 may be a robot in the broad sense, such as a vehicle, and the robot may move using wheels, tracks, or other mobility modules. In this invention, ground mobility devices such as ground vehicles are described primarily; however, unless contradicted by this invention, this embodiment may also be applied to air mobility devices such as advanced air mobility (AAM), aircraft, etc., and water mobility devices such as ships, submarines, etc.

[0058] Vehicle 100 can be configured to operate under autonomous driving control, which can be either semi-autonomous or fully autonomous. Fully autonomous driving provides automatic movement where, even in uncertain driving conditions, the processor 130 of vehicle 100 has complete control without user intervention. Semi-autonomous driving provides automatic movement where driver intervention is required depending on the specific driving situation. Semi-autonomous driving can be achieved by disabling autonomous driving in the aforementioned situations and transferring control to the user, enabling manual driving. According to the levels of autonomous driving defined by the Society of Automotive Engineers (SAE), semi-autonomous driving corresponds to levels 1 through 4, and fully autonomous driving corresponds to level 5.

[0059] Vehicle 100 may be configured to communicate with one or more other devices 200, 300 and / or another vehicle 400. These other devices may include, for example, a server 200, an intelligent transportation system (ITS) device 300, various types of user devices, etc. The server 200 is configured to support various controls, status management, and driving functions of vehicle 100, and the ITS device 300 is configured to receive information from the ITS. The server 200 may include, for example, an external device operated by the vehicle manufacturer or set up to provide autonomous driving services, and may be configured to receive networked data from vehicle 100 or send data required for autonomous driving. To support autonomous driving and various services of vehicle 100, server 200 may be configured to send various types of information and / or software modules that can be used to control vehicle 100 in response to requests and data sent from vehicle 100 and user devices.

[0060] The ITS device 300 may include, for example, a roadside unit (RSU) and can be configured to exchange vehicle identification data, driving control and status data, vehicle surrounding environment data, map data, etc., with vehicle 100 via vehicle-to-infrastructure (V2I) technology. The V2I configuration is intended to assist or support the driver of vehicle 100 in autonomous driving. Vehicle 100 can be configured to exchange the data listed above with another vehicle 400 via vehicle-to-vehicle (V2V) technology to support manual or autonomous driving.

[0061] Vehicle 100 can be configured to communicate with another vehicle or / or other device based on cellular communication, wireless access invehicular environment (WAVE) communication, dedicated short range communication (DSRC), short-range communication or another communication method.

[0062] For example, in order to communicate with server 200, ITS device 300, and another vehicle 400, vehicle 100 can be configured to use a cellular communication network such as Long Term Evolution (LTE) or 5G, Wi-Fi, or WAVE. As another example, DSRC or similar technologies used in vehicle 100 can be used for inter-vehicle communication. The communication methods between vehicle 100, server 200, ITS device 300, another vehicle 400, and user equipment are not limited to the above embodiments.

[0063] Figure 2 A schematic diagram showing the modules constituting a vehicle according to an exemplary embodiment of the present invention is shown.

[0064] The vehicle 100 may include a first sensor unit 102, a control unit 106, a display 108, a load device 114, a transceiver 112 and / or other suitable components.

[0065] The first sensor unit 102 may include various types of detectors for detecting various states and conditions occurring in the external environment, internal systems, user control, and passenger space of the vehicle 100.

[0066] Specifically, the first sensor unit 102 may include an externally facing camera 104a, a lidar sensor 104b, a radar sensor 104c, etc., to identify dynamic and static objects present outside the vehicle 100. The camera 104a may be configured to recognize external objects as images when used in the vehicle 100, generate image data, and send the image data to the processor 130. The lidar sensor 104b may be configured to generate point cloud data as data for the identified external objects and send the point cloud data to the processor 130 to generate at least three-dimensional spatial information identifying the shape of the external objects. The radar sensor 104c may be configured to emit radio waves of a specific frequency towards the periphery of the vehicle 100 to generate radar data through radio waves reflected from external objects, thereby identifying the presence, relative distance, speed, direction, etc., of external objects. In this invention, the lidar sensor 104b is provided as an example; however, in another example, the lidar sensor 104b may not be installed.

[0067] The first sensor unit 102 can be configured to generate object recognition information based on sensing data. The object recognition information may include information about the presence of an object, the object's location, the distance between the vehicle 100 and the object, and the relative speed between the vehicle 100 and the object. In this embodiment, the external object may include various objects related to the movement of the vehicle 100.

[0068] The second sensor unit 103 may include a positioning sensor 104d, a wheel sensor 104e, an attitude sensor 104f, etc., to determine the vehicle's position, speed, and driving attitude. The attitude sensor 104f may include a gyroscope sensor, an angular velocity sensor, an accelerometer, etc. The attitude sensor may include an inertial measurement unit (IMU) sensor, and may include a 3-axis accelerometer and a 3-axis angular velocity sensor. The attitude sensor may be configured to measure the vehicle 100's acceleration in the forward direction x, lateral direction y, and vertical direction z, as well as yaw, pitch, and roll as the vehicle's angular velocity.

[0069] The second sensor unit 103 can be configured to generate vehicle driving information based on sensing data. The vehicle driving information may include information generated based on data detected by various sensors installed in the vehicle. For example, vehicle driving information may include vehicle attitude information, vehicle speed information, vehicle tilt information, vehicle weight information, vehicle direction information, vehicle battery information, vehicle fuel information, vehicle tire pressure information, vehicle steering information, vehicle interior temperature information, vehicle interior humidity information, pedal position information, vehicle engine temperature information, etc.

[0070] In addition, vehicle driving information may include route information. Route information may include information generated based on the destination input by the vehicle user through the control unit 106. When a destination is set, route information may include information displaying the driving route from the vehicle's current location to the destination on a map. When no destination is set, route information may include information containing the road the vehicle is currently traveling on and the future driving route that includes that road.

[0071] Biometric data collectors can be installed on head-mounted devices and vibrating seats, and can collect biometric information from occupants experiencing virtual driving environments.

[0072] The biometric data acquisition device can be installed on the vibrating seat and can be configured to measure the occupant's heart rate.

[0073] The biometric information acquisition device can be installed in the vibrating seat. The biometric information acquisition device may include at least one of a photoplethysmography (PPG) sensor, an electrocardiography (ECG) sensor, and an acoustic sensor.

[0074] A PPG sensor can consist of a light-emitting diode (LED) and a light sensor. The PPG sensor can be configured to measure blood volume using light. The PPG sensor can be configured to measure heart rate based on the principle that light is emitted from the LED towards the skin, and the light is reflected as it passes through the skin and blood vessels; the amount of reflected light varies depending on the blood volume.

[0075] An ECG sensor may include one or more electrodes attached to the skin and signal processing circuitry. The ECG sensor can be configured to detect electrical activity that occurs during a heartbeat via the electrodes attached to the skin.

[0076] Acoustic sensors can include high-sensitivity microphones and signal processing systems. An acoustic sensor can be configured to use the microphone to record and analyze heartbeat sounds to measure heart rate.

[0077] In addition, biometric data collectors can be installed on the backrests and cushions of vehicle seats to measure occupant load.

[0078] The control unit 106 can be configured as a module operated by a user for driving. For example, the control unit 106 may be a steering wheel for manual driving, an automatic or manual transmission, an accelerator pedal, a brake pedal, etc. The control unit 106 may further include an interface for detailed functions of using, deactivating, and selecting user-requested autonomous driving modes, so that the user can use the autonomous driving functions. To receive various requests related to autonomous driving, the control unit 106 may include, for example, a hardware interface located at a predetermined location within the vehicle 100 or a software interface that can be touched on the display 108. Depending on the specifications of the autonomous vehicle, at least one of the steering wheel, transmission, and pedals may be omitted. As another example, in addition to driving control, the control unit 106 may also include a module for receiving user control requests for the load device 114.

[0079] Display 108 can be configured to serve as a user interface. Display 108 can be configured to be controlled by processor 130 to display the vehicle 100's operating status, control status, route / traffic information, remaining energy information, driver requests, etc. Furthermore, display 108 can be configured as a touchscreen capable of detecting driver input to receive requests from the driver instructing processor 130.

[0080] The load device 114 may be mounted on the vehicle 100 and may be a non-drive electrical device that does not include a drive power system (such as wheel drive unit 118). The load device 114 may include auxiliary devices configured to receive electricity from the energy generation unit 110, and may be, for example, various devices mounted on the air conditioning system, lighting system, seating system, and vehicle 100. In this invention, a cooling / heating system may be further included for cooling or heating at least one of the battery, fuel cell, internal combustion engine, air conditioning system, and specific parts of the vehicle 100.

[0081] Transceiver 112 can be configured to support communication with server 200, ITS device 300, another vehicle 400, etc. Transceiver 112 may include, for example, modules for handling cellular communication, WAVE, DSRC communication, etc. In this invention, transceiver 112 can be configured to send data generated or stored during driving to server 200 and receive data and software modules sent from server 200. Transceiver 112 can be configured to support communication with the electronic devices of occupants in vehicle 100. In this invention, vehicle 100 can be configured to send and receive data used in the method according to the invention with external devices via transceiver 112.

[0082] For example, transceiver 112 may be configured to receive traffic signal information from a traffic signal controller and provide that traffic signal information to processor 130. Furthermore, transceiver 112 may be configured to receive control signal information from a traffic signal controller and provide that control signal to processor 130.

[0083] In addition, the vehicle 100 may include an energy generation unit 110 and an actuation unit 116.

[0084] Energy generation unit 110 can be configured to generate and supply power and electricity used in drive and non-drive power systems, such as actuation unit 116. The non-drive power system may include, for example, a first sensor unit 102, a control unit 106, a display 108, a load device 114, a transceiver 112, etc., but is not limited thereto, and may include various components for realizing sensing, interface, communication, and convenience functions, other than those directly involved in driving operations. When vehicle 100 is electrically driven, energy generation unit 110 can be configured as, for example, a battery charged from an external source, or as a combination of a battery and a fuel cell that charges the battery. In the case of a battery and fuel cell combination, energy generation unit 110 may include a tank storing materials (e.g., liquefied hydrogen) used to generate electricity from the fuel cell. When vehicle 100 is fossil fuel driven, energy generation unit 110 may be composed of an internal combustion engine. Furthermore, when vehicle 100 is a hybrid, energy generation unit 110 may be configured as a combination of an internal combustion engine and a battery.

[0085] Actuation unit 116 may include at least one module for implementing driving operations and performs at least one driving operation, including longitudinal control (e.g., acceleration and deceleration) and lateral control (e.g., steering), based on user requests from control unit 106. To execute driving operations based on manual user control or instructions from the autonomous driving processor 130, actuation unit 116 may include wheel drive unit 118 and mechanical components and electronic modules for implementing driving operations of wheel drive unit 118. When vehicle 100 operates on electric power, actuation unit 116 may include components for sending requested driving operations to wheel drive unit 118. When vehicle 100 operates on fossil fuel power, actuation unit 116 may include a transmission and gear module for transmitting power from the internal combustion engine.

[0086] The wheel drive unit 118 may include multiple wheels, a drive force generating module for generating drive force to apply or transmit drive force to the wheels, a braking module for decelerating the drive of the wheels, a steering module for achieving lateral control of the wheels, etc. When the vehicle 100 is driven by electric power, the drive force generating module may be configured as a motor assembly that generates drive force based on electricity output from a battery. The braking module of the electric vehicle 100 may further include regenerative braking functionality.

[0087] The navigation system 122 can be configured to provide navigation information. The navigation information may include at least one of the following: map information, set destination information, route information set according to the destination, information about various objects on the route, lane information, and the vehicle's current location information.

[0088] The navigation system 122 can be configured to receive information from external devices via transceiver 112 and update previously stored information. According to an embodiment, the navigation system 122 can be classified as a sub-component of the control unit 106.

[0089] In addition, vehicle 100 may include memory 120 and processor 130.

[0090] The memory 120 can be configured to store applications for controlling the vehicle 100 and various types of data, and to load applications or read or write data according to the request of the processor 130.

[0091] Processor 130 can be configured to perform overall control of vehicle 100. Processor 130 can be configured to execute application programs and instructions stored in memory 120.

[0092] In the implementation scheme, in addition to the above description, the components may have different functions and capabilities, and include other components besides those described below. Furthermore, in one implementation scheme, the various components may be implemented using one or more physically separate means, or by one or more processors 130 or a combination of the one or more processors 130 and software, and unlike the example shown, the various components may not be clearly distinguishable in actual operation.

[0093] Memory 120 may include a database (DB). Additionally, memory 120 may include a non-transitory storage medium for storing instructions executed by processor 130. Memory 120 may include at least one of random access memory (RAM), static RAM (SRAM), read-only memory (ROM), programmable ROM (PROM), electrically erasable programmable ROM (EEPROM), erasable programmable ROM (EPROM), hard disk drive (HDD), solid-state drive (SSD), embedded multimedia card (eMMC), universal flash memory (UFS), and / or network memory.

[0094] The processor 130 may include at least one processing device such as an application-specific integrated circuit (ASIC), a digital signal processor (DSP), a programmable logic device (PLD), a field-programmable gate array (FPGA), a central processing unit (CPU), a microcontroller, and / or a microprocessor.

[0095] Figure 3 This is a schematic diagram illustrating the environment used to provide virtual driving content according to the implementation scheme. (Refer to...) Figure 3 The virtual content according to this implementation plan can be applied to users of autonomous vehicles who wear head-mounted displays (HMDs) to experience virtual environment content in metaverse environments, etc.

[0096] In one implementation, the HMD 10 may include a display device placed in a vehicle and worn on the user's head. The HMD 10 may be configured primarily for virtual reality (VR) and augmented reality (AR) applications and may be configured to provide an immersive visual experience through a display placed in front of the user's eyes.

[0097] The HMD 10 may include a display panel that provides images to the user using two small screens or one large screen, and a lens located between the display and the user's eyes that adjusts the image according to the eyes.

[0098] The HMD 10 can be configured to use head-tracking technology, implemented through gyroscopes, accelerometers, magnetic field sensors, etc., to track the user's head movements and adjust the screen's field of view.

[0099] HMD 10 can be configured to provide virtual environment driving content to the wearer. In some implementations, the virtual environment driving content may include virtual images and virtual sounds generated based on the vehicle driver's driving environment.

[0100] Figure 4 This is a schematic diagram illustrating the operation of the vibrator according to the implementation scheme. (Refer to...) Figure 4 The vibrator 140 can be disposed on the backrest and seat cushion of the seat and can output vibration signals independently. The vibrator 140 can be configured to be embedded in the gap between the backrest and seat cushion of the seat, wherein two vibrators 141 and 142 can be disposed on the backrest at a predetermined distance from each other, and two vibrators 143 and 144 can be disposed on the seat cushion at a predetermined distance from each other. The vibrators 141 to 144 can be configured to operate independently under the control of the processor 130 and output predetermined vibration signals.

[0101] Each vibrator 140 may include an outer frame, a voice coil mounted within the frame that generates a magnetic field when an electrical signal is applied, at least one magnet that interacts with the voice coil through its magnetic field and vibrates at a predetermined frequency, and a vibrating body that transmits the vibration of the magnet to the human body. When an electrical signal is applied to the voice coil of the vibrator 140 under the control of a processor, the voice coil generates a magnetic field proportional to the intensity of the electrical signal. When this magnetic field interacts with the magnet, the magnet vibrates vertically at a predetermined frequency. When this vibration signal is output through the vibrating body and transmitted to the human body, the human body recognizes the predetermined sound signal.

[0102] Figure 5 It is a schematic diagram used to describe the operation of the vehicle according to the implementation plan.

[0103] Reference Figure 5 The sensor unit 210 can be configured to detect vehicle driving data and biometric information of vehicle occupants. Figure 5 The sensor unit 210 may include Figure 2 The second sensor unit 103 and the biometric information collector are components.

[0104] Biometric information may include at least one of the occupant's heart rate, respiratory information, skin stimulation information, and motion information.

[0105] Regenerative braking information may include regenerative braking stage information.

[0106] Sensor unit 210 may include an IMU sensor for acquiring vehicle driving data. The IMU sensor may consist of a three-axis accelerometer, a three-axis gyroscope, and a magnetometer, and may be configured to detect vehicle motion. The three-axis accelerometer may be configured to measure changes in the vehicle's acceleration in the x-direction (forward / backward), y-direction (left / right), and z-direction (vertical), and analyze dynamic changes during deceleration. Specifically, the IMU sensor may be configured to measure deceleration during regenerative braking operations and detect abrupt changes in speed. Furthermore, the three-axis gyroscope may be configured to measure the vehicle's rotation (tilt, pitch, yaw) information and detect sudden changes in direction during deceleration. Additionally, the magnetometer may be configured to correct the vehicle's orientation and motion, providing more accurate data. Therefore, the vehicle's deceleration pattern can be accurately identified, and the likelihood of motion sickness can be assessed.

[0107] Furthermore, embodiments of the present invention can be configured to provide feedback for mitigating motion sickness in conjunction with a regenerative braking control system. (See also...) Figure 6 Regenerative braking control systems can be configured to adjust deceleration intensity in stages, typically in electric vehicles, with three or five stages. When regenerative braking is applied forcefully, sudden deceleration increases the likelihood of motion sickness; therefore, detecting this moment and providing immediate feedback is crucial. For example, synchronized vibrations can be provided to the seat during moments of high regenerative braking intensity to induce sensory correction, or soft background sounds can be provided when deceleration varies irregularly to alleviate occupant discomfort. Furthermore, by analyzing regenerative braking patterns based on machine learning, it is possible to predict and appropriately address situations where specific deceleration patterns cause motion sickness.

[0108] Passenger biometrics are a crucial factor in detecting motion sickness. Therefore, sensor unit 210 can be configured to monitor physiological changes in real time using heart rate sensors (PPG and ECG), a respiration sensor, and a galvanic skin response (GSR) sensor. The heart rate sensor assesses the likelihood of motion sickness by utilizing the increased heart rate caused by sympathetic nerve activation during motion sickness. The PPG sensor can be attached to the wrist, fingers, ear, etc., to detect changes in blood flow, and the ECG sensor can be configured to detect the increased heart rate caused by sympathetic nerve activation during motion sickness through more precise heart rate rhythm analysis.

[0109] A breathing sensor utilizes the characteristic of changes in breathing patterns during motion sickness. Typically, motion sickness is characterized by short, rapid breaths, which can be detected to determine the likelihood of motion sickness. The breathing sensor can be configured to be worn on the chest as a chest strap or built into the vehicle seat, and can be configured to compare normal breathing patterns with those observed during motion sickness to determine if any abnormalities are present.

[0110] GSR sensors detect occupants' anxiety and stress responses and assess the likelihood of motion sickness. GSR sensors measure minute changes in the electrical conductivity of the skin on the palms or fingers; skin conductivity increases when sweating in the palms increases due to sympathetic nerve activation. Using this method, stress and anxiety can be measured, providing immediate feedback when skin conductivity exceeds a predetermined threshold.

[0111] Furthermore, sensor unit 210 may include an in-vehicle camera for capturing images of the vehicle's interior. The in-vehicle camera may be configured to capture images of the vehicle's interior, including motion information of the vehicle occupants, and generate image data.

[0112] The processor 220 can be configured to determine the correlation between regenerative braking information of the vehicle's driving data, acceleration information generated during regenerative braking, and biometric information, and analyze the occupant's motion sickness risk based on the correlation, and generate and output a motion sickness mitigation feedback signal of at least one sound signal and vibration signal according to the motion sickness risk. Figure 5 The processor 220 can be with Figure 2 It uses the same components as the processor 130.

[0113] The processor 220 can be configured to analyze the correlation between regenerative braking information, acceleration information generated during regenerative braking, and biometric information in the vehicle's driving data, and analyze the risk of motion sickness of the occupants based on the correlation.

[0114] The processor 220 can be configured to analyze the correlation between regenerative braking information, acceleration information and biometric information, and analyze the risk of motion sickness.

[0115] Motion sickness prediction models can be configured to learn changes in biometric information based on regenerative braking phase and acceleration information contained in regenerative braking information.

[0116] The processor 220 can be configured to determine the relationship between the vehicle driving environment and the occupants' biological responses by applying machine learning techniques, specifically by using an algorithm based on the Transformer model to predict the risk of motion sickness.

[0117] Regenerative braking in a vehicle is the process of converting kinetic energy into electrical energy during deceleration. During this process, the acceleration may vary to different degrees depending on the vehicle's deceleration mode. These changes in acceleration directly affect the occupants' physical condition, and under certain conditions, the likelihood of motion sickness may increase.

[0118] The processor 220 can be configured to analyze the regenerative braking phase and the corresponding acceleration information, while assessing its correlation with occupant biometric information and predicting the risk of motion sickness.

[0119] Motion sickness prediction models can be configured to learn changes in biometric information based on regenerative braking phases and vehicle acceleration. As mentioned above, biometric information can include physiological signals of the occupant such as heart rate, GSR, skin temperature, and breathing patterns, which are closely related to whether the user experiences motion sickness. Motion sickness prediction models can be configured to analyze changes in this biometric information and, based on this, to determine the occupant's risk of motion sickness.

[0120] Motion sickness prediction models utilize the encoder-decoder structure of the Transformer model to predict motion sickness, thus effectively mapping the regenerative braking phase of the vehicle and the occupants' biometric information to predict sensory conflicts.

[0121] A motion sickness prediction model can consist of an encoder and a decoder. The encoder can be configured to receive regenerative braking information from the vehicle and biometric information of the occupants, convert them into a feature space, and based on this, the decoder can be configured to output the motion sickness risk. Specifically, the encoder can be configured to learn the biometric information of the occupants to generate sensory conflict, and the decoder can be configured to derive a motion sickness prediction result based on this sensory conflict.

[0122] Furthermore, motion sickness prediction models can improve accuracy by applying an attention mechanism to the encoder-decoder architecture. An attention mechanism is a method of weighting important components of the input data, thus effectively extracting factors that significantly influence motion sickness from the vehicle's regenerative braking information. For example, when a specific regenerative braking pattern significantly affects an occupant's biometric responses, the attention mechanism can be configured to increase the weight of that pattern, allowing the motion sickness prediction model to reflect it more accurately.

[0123] Furthermore, processor 220 can be configured to assess the stage of cyber motion sickness and user sensitivity by comparing a motion sickness prediction model with user sensory conflicts and analyzing the comparison results. Cyber ​​motion sickness is motion sickness that occurs when using a VR environment or an in-vehicle digital interface and may be caused by factors different from those causing regular vehicle motion sickness. Processor 220 can be configured to analyze user sensory conflict data to identify the stage of cyber motion sickness and user-specific sensitivities, thereby providing a tailored motion sickness mitigation solution for each user.

[0124] The processor 220 can be configured to generate and output motion sickness mitigation feedback signals, including sound signals, based on the risk of motion sickness.

[0125] The processor 220 can be configured to generate and output motion sickness mitigation feedback signals for each stage based on motion sickness risk.

[0126] When the acceleration generated during regenerative braking is within a first threshold range, the processor 220 can be configured to generate an audible signal for stabilizing the heart rate and output the generated audible signal to a speaker 230 in the vehicle.

[0127] When the acceleration generated during regenerative braking is within the second threshold range, the processor 220 can be configured to generate and output an acoustic signal for stabilizing the breathing pattern.

[0128] The processor 220 can be configured to control the physiological responses of occupants and alleviate motion sickness by generating sound signals corresponding to the acceleration changes generated during the vehicle's regenerative braking process.

[0129] The processor 220 can be configured to generate an audible signal for stabilizing heart rate when the acceleration generated during the regenerative braking process is within a first threshold range (0.1g to 0.29g), and to generate an audible signal for stabilizing breathing pattern when the acceleration is within a second threshold range (above 0.3g), and output the generated audible signal to a speaker in the vehicle.

[0130] The processor 220 can be configured to provide stage-specific musical content based on acceleration data from regenerative braking by applying data integration and conversion functions. In other words, the processor 220 can be configured to generate sound signals using heart rate-related piano playing techniques when the acceleration change is relatively small (0.1g to 0.29g) and heart rate stability is required, and to generate sound signals using cello playing techniques that induce prolonged breathing when the acceleration change is large (above 0.3g) and breathing pattern stability is required.

[0131] Heart rate synchronization is based on the physiological principle of synchronizing the body's biological rhythms with external stimuli. It is a technology that uses sound signals of specific rhythms or frequencies to influence and control the rhythms of human organs. In this implementation, the goal is to induce a heart rate of approximately 65 bpm within the normal range (60 to 100 bpm). To achieve this, the processor 220 can be configured to utilize piano playing. The piano playing employs the Ab major mode, which combines with the user's heart rate to provide a sense of stability, and uses low-complexity whole-tone harmonies to create an auditoryally comfortable environment. Ab major is a mode that conveys a "slow" feeling, providing a gradual decrease in heart rate. Furthermore, whole-tone harmonies help to achieve a natural heartbeat sensation, allowing the user to maintain a more stable heartbeat pattern.

[0132] Simultaneously, cello playing techniques related to prolonged breathing provide psychological stability by maintaining the user's breathing for an extended period. Processor 220 can be configured to musically transform and apply the prolonged breathing method used in meditation techniques. In one implementation, processor 220 can be configured to utilize legato techniques in cello playing. Legato is a playing style that connects notes smoothly and without interruption, naturally inducing prolonged breathing in the listener. In another implementation, processor 220 can be configured to utilize cello playing techniques, combined with the user's breathing patterns, to maintain a long and gentle melody, and to provide a constant rhythm and a soft timbre by minimizing positional movement when producing high-pitched sounds.

[0133] Processor 220 can be configured to analyze motion sickness risk, generate motion sickness mitigation feedback signals for each stage, and output appropriate sound signals based on the progression of motion sickness. For example, processor 220 can be configured to prioritize piano playing to regulate heart rate during the initial stage of motion sickness, and additionally provide cello playing to stabilize breathing when motion sickness is severe. Therefore, processor 220 can be configured to provide a motion sickness mitigation solution optimized for each user's biological response.

[0134] The processor 220 can be configured to generate a motion sickness mitigation feedback signal including a vibration signal based on the risk of motion sickness, and output the generated motion sickness mitigation feedback signal including a vibration signal through the vibration unit 240 in the vehicle.

[0135] The processor 220 can be configured to adjust the intensity and pattern of the vibration signal based on the risk of motion sickness.

[0136] The processor 220 can be configured to adjust the intensity and pattern of the vibration signal taking into account the occupant's biological response and motion sickness risk, and to provide more effective motion sickness relief by applying a sound-based tactile solution.

[0137] Motion sickness that occurs while the vehicle is in motion is caused by a sensory conflict between vision, the vestibular system (balance of the ears), and somatosensory perception (detection of body movement). The processor 220 can be configured to generate a vibration signal that minimizes the sensory conflict.

[0138] The processor 220 can be configured to assess motion sickness risk in real time, and therefore can be configured to generate and output motion sickness mitigation feedback signals, including vibration signals. Furthermore, the processor 220 can be configured to perform optimized responses for individual users by adjusting the intensity and pattern of the vibration signals according to the severity of motion sickness.

[0139] The processor 220 can be configured to utilize dynamic content generation capabilities to provide sound-related tactile and vibrational solutions based on the risk of motion sickness among occupants. To this end, vehicles according to the implementation scheme may be equipped with air pressure tactile technology based on an ergomotion seat and vibration units 240 based on a vibratory music seat.

[0140] Ergonomic seats can be configured to correct the posture of rear-seat occupants and alleviate motion sickness by using seven airbags to regulate air pressure. Tactile feedback from the air pressure helps prevent motion sickness by automatically correcting the occupant's posture according to the vehicle's movement, and is particularly effective in reducing discomfort caused by unnatural postures during long journeys. Furthermore, ergonomic seats can be configured to provide a massage function using airbags located in the backrest, thereby relieving muscle tension that may be caused by motion sickness and inducing relaxation in the occupant.

[0141] The vibrating music seat can be configured to generate vibrations using four to eight actuators, thereby minimizing sensory conflict and enhancing immersion in VR-based content. Processor 220 can be configured to provide vibratory tactile stimulation using methods that minimize the mismatch between imagery and body movement to reduce sensory conflict. For example, when a user looks forward during vehicle deceleration, processor 220 can be configured to visually perceive the vehicle as coming to a stop, but the vestibular system can still detect the decelerating movement. This mismatch can lead to motion sickness; in this case, processor 220 can reduce the mismatch between sensory information by providing vibrations of a specific frequency according to the vehicle's deceleration pattern.

[0142] Furthermore, the vibrating music seat can be configured to provide customized vibrations that enhance immersion in VR content. In a VR environment, the mismatch between the user's movement and visual information can cause motion sickness. The processor 220 generates vibration signals that match the movement of the VR content in such an environment, allowing the occupant to be more naturally immersed. For example, when acceleration occurs in the VR content, the processor 220 can be configured to increase the intensity of the seat's vibration to simulate the acceleration of a real vehicle.

[0143] The processor 220 can be configured to analyze the risk of motion sickness and provide optimal tactile feedback based on the severity of the motion sickness. In the initial stages of motion sickness, the processor 220 can be configured to induce posture correction and muscle relaxation using an ergonomic seat. When motion sickness is severe, the processor 220 can be configured to provide vibrational signals to alleviate sensory conflict through a vibrating music seat. Therefore, occupants can remain more comfortable while the vehicle is moving, and the discomfort caused by motion sickness can be minimized.

[0144] Figure 7This is a flowchart illustrating a method for controlling a vehicle according to an implementation scheme. (Refer to...) Figure 7 The sensor unit detects the vehicle's driving data and the biometric information of the vehicle occupants (S701).

[0145] The processor analyzes the correlation between regenerative braking information, acceleration information generated during regenerative braking, and biometric information in the vehicle's driving data (S702).

[0146] The processor analyzes the passenger's risk of motion sickness based on the correlation.

[0147] In other words, the processor can be configured to analyze motion sickness risk by utilizing a motion sickness prediction model to analyze the correlation between regenerative braking information, acceleration information, and biometric information. The motion sickness prediction model can be configured to analyze the motion sickness risk of each passenger by learning changes in biometric information based on the regenerative braking phase and acceleration information included in the regenerative braking information (S703).

[0148] The processor generates an audio signal based on the risk of motion sickness (S704).

[0149] The processor outputs the generated sound signal through the speakers in the vehicle (S705).

[0150] In addition, the processor generates a vibration signal based on the risk of motion sickness (S706).

[0151] The processor outputs the generated vibration signal through the vibration unit of the vehicle seat (S707).

[0152] As used in this embodiment, the term "unit" refers to a software or hardware component, such as an FPGA or ASIC, that plays a specific role. However, a "unit" is not limited to software or hardware. A "unit" can be located in an addressable storage medium and configured to be reproduced by one or more processors. Thus, by way of example, a "unit" includes components (such as software components, object-oriented software components, class components, and task components), processes, functions, attributes, programs, subroutines, program code segments, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays, and variables. The functionality provided in components and "units" can be combined into fewer components and "units" or separated into additional components and "units." Furthermore, components and "units" can be implemented to reproduce one or more CPUs in a device or secure multimedia card.

[0153] Based on the vehicle and the method of controlling the vehicle according to the implementation plan, the impact of regenerative braking during the operation of electric vehicles can be analyzed, thereby alleviating motion sickness of passengers based on the analyzed impact.

[0154] Therefore, situations where motion sickness is more likely can be predicted in advance, and motion sickness-reducing feedback can be provided based on sound and vibration to alleviate motion sickness.

[0155] In addition, providing motion sickness relief solutions can improve the comfort of electric vehicle occupants.

[0156] In addition, it can alleviate motion sickness and create a comfortable environment inside the vehicle.

[0157] Furthermore, by applying motion sickness mitigation solutions, the regenerative braking function of electric vehicles can be used more proactively, thereby maximizing the vehicle's energy efficiency.

[0158] Although the invention has been described above with reference to exemplary embodiments, those skilled in the art will understand that various modifications and changes can be made to the invention without departing from the spirit and scope of the invention as described in the appended claims.

Claims

1. A vehicle comprising: Sensor unit; One or more processors; as well as A memory configured to store one or more programs executed by the one or more processors; in: The sensor unit is configured to detect: Vehicle driving data; and Biometric information of vehicle occupants; The processor is configured as follows: Determine the correlation between regenerative braking information from vehicle driving data, acceleration information generated during regenerative braking, and biometric information; The risk of motion sickness among passengers is determined based on the aforementioned correlation; Generate and output motion sickness relief feedback signals based on the risk of motion sickness.

2. The vehicle according to claim 1, wherein, The biometric information includes at least one of the occupant's heart rate, respiratory information, skin irritation information, and movement information.

3. The vehicle according to claim 1, wherein, The regenerative braking information includes regenerative braking stage information.

4. The vehicle according to claim 1, wherein, The processor includes a motion sickness prediction model configured to analyze motion sickness risk by analyzing the correlation between regenerative braking information, acceleration information, and biometric information.

5. The vehicle according to claim 4, wherein, The motion sickness prediction model is configured as follows: Learn the changes in biometric information based on the regenerative braking stage and acceleration information included in the regenerative braking information; Predicting motion sickness risk based on changes in biometric information.

6. The vehicle according to claim 1, wherein, The motion sickness relief feedback signal includes at least one sound signal and a vibration signal.

7. The vehicle according to claim 1, wherein, The processor is configured to generate and output motion sickness mitigation feedback signals for each stage based on motion sickness risk.

8. The vehicle according to claim 7, wherein, The processor is configured to generate and output an acoustic signal for stabilizing heart rate based on the acceleration generated during regenerative braking within a first threshold range.

9. The vehicle according to claim 7, wherein, The processor is configured to generate and output an acoustic signal for stabilizing breathing patterns based on the acceleration generated during regenerative braking within a second threshold range.

10. The vehicle according to claim 6, wherein, The processor is configured to adjust the intensity and pattern of the vibration signal based on the risk of motion sickness.

11. A method for controlling a vehicle executed by a computing device, the computing device including a sensor unit, one or more processors, and a memory configured to store one or more programs executed by the one or more processors, the method comprising: The sensor unit detects the vehicle's driving data and the biometric information of the vehicle's occupants; The processor analyzes the correlation between regenerative braking information, acceleration information generated during regenerative braking, and biometric information in the vehicle's driving data. The processor analyzes the risk of motion sickness among passengers based on the aforementioned correlation. The processor generates and outputs motion sickness relief feedback signals based on the risk of motion sickness.

12. The method according to claim 11, wherein, The biometric information includes at least one of the occupant's heart rate, respiratory information, skin irritation information, and movement information.

13. The method according to claim 11, wherein, The regenerative braking information includes regenerative braking stage information.

14. The method according to claim 11, wherein, The processor includes a motion sickness prediction model, which analyzes the risk of motion sickness by analyzing the correlation between regenerative braking information, acceleration information, and biometric information.

15. The method of claim 14, wherein: Analyzing the correlation between regenerative braking information, acceleration information, and biometric information includes: learning changes in biometric information based on the regenerative braking stage and acceleration information included in the regenerative braking information by the motion sickness prediction model; Analyzing motion sickness risk includes using motion sickness prediction models to predict motion sickness risk based on changes in biometric information.

16. The method according to claim 11, wherein, The motion sickness relief feedback signal includes at least one sound signal and a vibration signal.

17. The method according to claim 11, wherein, The generation and output of motion sickness relief feedback signals include: generating and outputting motion sickness relief feedback signals at each stage based on motion sickness risk.

18. The method according to claim 17, wherein, The generation and output of motion sickness relief feedback signals include: generating and outputting an audible signal for stabilizing heart rate based on the acceleration generated during regenerative braking within a first threshold range.

19. The method of claim 17, wherein, The generation and output of motion sickness relief feedback signals include: generating and outputting sound signals for stabilizing breathing patterns based on the acceleration generated during regenerative braking within a second threshold range.

20. The method of claim 16, wherein, Generating and outputting motion sickness mitigation feedback signals includes adjusting the intensity and pattern of vibration signals based on the risk of motion sickness.

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