Vehicle sneeze control system and method

Abstract

To provide systems and methods for controlling a vehicle system when the vehicle system is under control of user.SOLUTION: In one embodiment, the method includes predicting a start of a user sneezing episode. The method includes identifying a plurality of phases in the user sneezing episode, and controlling the vehicle system based on which one of the plurality of phases is active.SELECTED DRAWING: Figure 4

Description

Technical Field

[0001] The subject matter described in this specification generally relates to systems and methods for controlling a vehicle system when the vehicle system is under user control.

Background Art

[0002] The background description is provided to generally present the context of the present disclosure. Neither the inventors' research within the scope that may be described in this background section nor aspects of the description that might not otherwise be recognized as prior art at the time of filing are expressly or implicitly admitted as prior art to this technology.

[0003] Some vehicles have been equipped with one or more driver assistance systems and / or have been able to operate the vehicle in an autonomous mode or a semi-autonomous mode. The driver assistance system can be manually enabled or disabled by the user. Similarly, the user can manually select from an autonomous mode, a semi-autonomous mode, and a non-autonomous mode.

Summary of the Invention

[0004] This summary of the invention is a general overview of the disclosure and does not comprehensively describe its full scope or all its features.

[0005] In one embodiment, a method for controlling a vehicle system when the vehicle system is under user control is disclosed. The method includes predicting the onset of a user's sneezing episode. The method includes identifying a plurality of stages of the user's sneezing episode and controlling the vehicle system based on which stage of the plurality of stages is active.

[0006] Another embodiment discloses a system for controlling a vehicle system when the vehicle system is under the control of a user. This system comprises a processor and memory that communicates with the processor. The memory stores a prediction module containing instructions, which, when executed by the processor, cause the processor to predict the onset of a user's sneezing fit. The memory stores a stage identification module containing instructions, which, when executed by the processor, cause the processor to identify multiple stages of a user's sneezing fit. The memory stores a vehicle system control module containing instructions, which, when executed by the processor, cause the processor to control the vehicle system based on which of the multiple stages is active.

[0007] Another embodiment discloses a non-transient computer-readable medium that includes instructions for controlling the vehicle system when it is under the user's control, and for causing the processor to perform one or more functions when executed by the processor. The instructions include instructions for predicting the onset of a user's sneezing fit, identifying multiple stages of the user's sneezing fit, and controlling the vehicle system based on which of the multiple stages is active. [Brief explanation of the drawing]

[0008] The accompanying drawings incorporated herein and forming part thereof illustrate various systems, methods, and other embodiments of the present disclosure. It will be understood that the illustrated element boundaries (e.g., boxes, groups of boxes, or other shapes) represent one embodiment of the boundary. In some embodiments, one element may be designed as multiple elements, or multiple elements may be designed as a single element. In some embodiments, an element shown as an internal component of another element may be implemented as an external component, or vice versa. Furthermore, elements may not be drawn in exact proportions.

[0009] [Figure 1] This diagram shows a block diagram of a vehicle incorporating a vehicle-mounted sneeze control system. [Figure 2]This is a more detailed block diagram of the vehicle sneeze control system shown in Figure 1. [Figure 3] This diagram illustrates an example of how to control a vehicle system when it is under user control. [Figure 4] This is a diagram illustrating an example of vehicle sneeze control. [Modes for carrying out the invention]

[0010] This document discloses systems, methods, and other embodiments relating to controlling a vehicle system when the vehicle system is under the user's control. A user who sneezes while operating a vehicle may lose control of the vehicle or cause unintended movements during the sneeze, potentially endangering the user and other road users. Therefore, in one embodiment, the disclosed approach is a vehicle sneeze control system that controls the vehicle system when the vehicle system is under the user's control and the user sneezes. The vehicle sneeze control system can help the user maintain smooth operation of the vehicle during a sneezing fit.

[0011] A vehicle may be equipped with one or more vehicle systems, such as a steering system, a throttle system, and a braking system. A vehicle system may have an input unit for human-machine interaction, a functional unit, and a mechanism that can make the translation ratio between the input unit and the functional unit variable. The mechanism may be an electrical system, an electronic system, or an electromechanical system. As an example, a steering system may have a mechanism that allows for a variable translation ratio between the steering wheel and the steering rack, such as a steer-by-wire system. As another example, a throttle system may have a mechanism that electronically connects the accelerator pedal to the throttle, such as a throttle-by-wire system or a gas-by-wire system. A throttle system is an input system for controlling vehicle speed and acceleration. As yet another example, a braking system may have an electrical mechanism between the brake pedal and the brake actuator, such as a brake-by-wire system. In one embodiment, the input unit of the vehicle system may be mechanically separated from the functional unit of the vehicle system.

[0012] The vehicle may be equipped with one or more driver assistance systems, such as a lane keeping system and a collision avoidance system. The vehicle may be capable of operating in autonomous mode, semi-autonomous mode and / or manual mode.

[0013] A vehicle may be equipped with one or more sensors. Sensors may be located inside and / or outside the vehicle, such as inside the vehicle. Sensors may include cameras that can monitor the user, the user's actions, and the user's facial expressions. Sensors may include microphones that can detect sounds inside the vehicle, such as sounds made by the user. Sensors may include air quality detectors that determine the concentration of allergens in the air, such as pollen, dust, and animal fur. Sensors may include light level detectors that can determine whether the light level is bright enough to cause sneezing.

[0014] For example, a vehicle sneeze control system can receive sensor data from sensors. Based on visual and / or auditory cues in the sensor data, the vehicle sneeze control system can determine whether the user is about to sneeze, i.e., whether the user is about to start a sneeze attack. In addition, the vehicle sneeze control system may consider environmental conditions such as allergen concentration and / or light level when predicting the onset of a user sneeze attack. For example, the vehicle sneeze control system may use environmental conditions to determine a confidence level when predicting the onset of a user sneeze attack.

[0015] When a vehicle sneeze control system anticipates the onset of a user's sneeze attack, it can use visual and / or auditory cues to determine multiple stages of the user's sneeze attack based on the sneeze reflex. The sneeze reflex has two stages: the initial spasmodic inspiratory stage and the subsequent oral and nasal exhalation stage. For example, a vehicle sneeze control system can determine the spasmodic inspiratory stage, the nasal and oral exhalation stage, the waiting stage, and the normal stage. The duration of one or more stages can be set to zero.

[0016] A vehicle sneeze control system can determine which vehicle system, driver assistance system, and / or driving mode to operate based on one or more of the following: the effective stage, vehicle speed, vehicle position, relative position of the vehicle, handwheel position, handwheel rotation speed, objects adjacent to the vehicle, and the reliability of predicting the user's sneeze attack. The vehicle sneeze control system can control the vehicle in a first mode at one stage and in a second mode at another. The first and second modes may differ in function, intensity, and duration. For example, a functional difference might be adjusting the translation ratio between the steering wheel and the steering rack to two different values, an intensity difference might be adjusting the active parameters of the lane centering system, and a time difference might be two different response times between the input unit and the function unit of the vehicle system. The vehicle sneeze control system can use any appropriate algorithm to determine which mode to select and which vehicle system, driver assistance system, and / or driving mode to operate.

[0017] For example, a vehicle sneeze control system can activate the lane keeping system during the inhalation phase, activate the autonomous mode during the exhalation phase, maintain the lane keeping system in an active state and keep the vehicle in autonomous mode during the standby phase, and then deactivate the lane keeping system and autonomous mode during the normal phase.

[0018] Detailed embodiments are disclosed herein. However, it should be understood that the disclosed embodiments are intended only as examples. For this reason, the specific structural and functional details disclosed herein should not be construed as limiting, but merely as representative grounds to teach those skilled in the art how to use the embodiments herein in various ways in virtually any appropriately detailed structure, in addition to being the basis for the claims. Furthermore, the terms and phrases used herein are not intended to be limiting, but rather to provide an understandable description of possible implementations. Although various embodiments are illustrated, the embodiments are not limited to the illustrated structures or uses.

[0019] It will be understood that, in order to simplify and clarify the examples, reference numbers are repeated between different figures where necessary to indicate corresponding or similar elements. Furthermore, numerous specific details are given in order to provide a complete understanding of the embodiments described herein. However, it will be understood by those skilled in the art that the embodiments described herein can be carried out without such specific details.

[0020] Referring to Figure 1, a block diagram of a vehicle 102 incorporating a vehicle sneeze control system 100 is shown. Vehicle 102 includes various elements. It will be understood that in various embodiments, vehicle 102 may not have all the elements shown in Figure 1. Vehicle 102 may have any combination of the various elements shown in Figure 1. Furthermore, vehicle 102 may have additional elements beyond those shown in Figure 1. In some configurations, vehicle 102 may be implemented without one or more of the elements shown in Figure 1. Although Figure 1 shows the various elements located within vehicle 102, it will be understood that one or more of these elements may be located outside vehicle 102. Furthermore, the illustrated elements may be separated by a large physical distance. For example, as considered, one or more components of the disclosed system may be implemented within the vehicle, while additional components of the system may be implemented in a cloud computing environment.

[0021] Some possible elements of the vehicle 102 are shown in Figure 1 and described in conjunction with the subsequent figures. However, for the sake of brevity, a description of many of the elements in Figure 1 is provided after the discussion of Figures 2-4. Furthermore, it will be understood that, in order to simplify and clarify the illustrations, reference numbers are repeated between different figures where necessary to indicate corresponding or similar elements. Furthermore, in the discussion, many specific details are outlined in order to provide a complete understanding of the embodiments described herein. However, those skilled in the art will understand that the embodiments described herein may be carried out using various combinations of such elements. In any case, as shown in the embodiment of Figure 1, the vehicle 102 includes a vehicle sneeze control system 100 which is implemented to perform methods and other functions disclosed herein relating to controlling the vehicle system when the vehicle system is under the user's control and the user is having a sneeze attack. As an example, in various embodiments, the vehicle sneeze control system 100 may be partially implemented within the vehicle 102 and may further exchange communication with additional embodiments of the vehicle sneeze control system 100 located away from the vehicle 102 in supporting the disclosed functions. Therefore, although Figure 2 generally shows that the vehicle sneeze control system 100 is self-contained, in various embodiments the vehicle sneeze control system 100 may be implemented in a plurality of separate devices, some of which may be located away from the vehicle 102.

[0022] Referring to Figure 2, a more detailed block diagram of the vehicle sneeze control system 100 is shown. The vehicle sneeze control system 100 may include a processor 110. Thus, the processor 110 may be part of the vehicle sneeze control system 100, or the vehicle sneeze control system 100 may access the processor 110 via a data bus or another communication path. In one or more embodiments, the processor 110 is an application-specific integrated circuit that can be configured to implement functions related to the prediction module 220, the stage identification module 230, and / or the vehicle system control module 240. More generally, in one or more embodiments, the processor 110 is an electronic processor such as a microprocessor that can perform various functions as described herein when reading modules 220-240 and executing encoded functions related to the modules.

[0023] The vehicle sneeze control system 100 may include a memory 210 for storing a prediction module 220, a stage identification module 230, and a vehicle system control module 240. The memory 210 may be random access memory (RAM), read-only memory (ROM), a hard disk drive, flash memory, or other suitable memory for storing modules 220-240. Modules 220-240 are computer-readable instructions that, when executed by a processor 110, cause the processor 110 to perform various functions disclosed herein. In one or more embodiments, modules 220-240 are instructions embodied in the memory 210, but in additional embodiments, modules 220-240 include hardware such as processing components (e.g., controllers), circuits, etc., for independently performing one or more of the above functions.

[0024] The vehicle sneezing control system 100 may include a data store 250 for storing one or more types of data. For this purpose, even when the data store 250 is part of the vehicle sneezing control system 100, or when the vehicle sneezing control system 100 accesses the data store 250 via a data bus or another communication path. In one embodiment, the data store 250 is an electronic-based data structure for storing information. In at least one approach, the data store 250 is stored in the memory 210 or another suitable medium and is composed of routines that can be executed by the processor 110 for analyzing the stored data, providing the stored data, sorting the stored data, etc. In any case, in one embodiment, the data store 250 stores data used by the modules 220-240 when performing various functions. In one embodiment, the data store 250 may be able to store sensor data 260, vehicle information data 270, environmental information data 280, and / or other information used by the modules 220-240.

[0025] The data store 250 may include volatile and / or non-volatile memory. Examples of suitable data stores 250 include RAM (Random Access Memory), flash memory, ROM (Read Only Memory), PROM (Programmable Read Only Memory), EPROM (Erasable Programmable Read Only Memory), EEPROM (Electrically Erasable Programmable Read Only Memory), registers, magnetic disks, optical disks, hard drives, or any other suitable storage medium, or any combination thereof. The data store 250 may be a component of the processor 110 or may be operably connected to the processor 110 and used by the same processor. The terms "operably connected" or "communicating" used throughout this description may include direct or indirect connections, including connections without direct physical contact.

[0026] In one or more configurations, the data store 250 can include sensor data 260. The sensor data 260 can originate from the sensor system 120 of the vehicle 102. The sensor data 260 can include data from visual sensors, audio sensors, and / or any other suitable sensors within the vehicle 102.

[0027] In one or more configurations, the data store 250 can include vehicle information data 270. The vehicle information data 270 can include driver information such as user identification and user history. The user history can include the user's physiological functions and driving style. The user's physiological functions can include allergens to which the user reacts, such as pollen, dust, or bright light, the way the user reacts to such sneezes, and characteristics of the user's sneeze reflex, such as the behavior at the start of the user's sneeze, the length of time the user spends in the first inhalation phase, the length of time the user spends in the exhalation phase, and whether the user makes a plurality of sneezes rapidly and continuously. The user's driving style can include whether the user lightly or strongly presses the brake pedal and / or accelerator pedal, and whether the user performs sharp turns, gentle turns, sudden turns, or slow turns during steering operations.

[0028] The vehicle information data 270 includes information regarding the current control mode of the vehicle 102. As an example, the vehicle 102 can be in a non-autonomous mode, a semi-autonomous mode, or an autonomous mode. As another example, one or more of the vehicle systems 140 within the vehicle 102 can be in various levels of manual or autonomous control. In such an example, one or more of the steering system 143, throttle system 144, and / or braking system 142 can be under manual control, autonomous control, or some control in between.

[0029] In one or more configurations, the data store 250 may include environmental information data 280. The environmental information data 280 may include information about the environment surrounding the vehicle 102, such as the location and condition of the path the vehicle is traveling on. The location of the path may include the geographic coordinates of the path and the location of the path relative to the destination. The condition of the path may include the traffic volume on the path as well as traffic rules based on the jurisdiction of the location of the path. The condition of the path may include information about the physical condition of the path, such as the presence of potholes, road debris, vegetation, closures and / or road visual guides such as lane markers, road edge markers, traffic signs, signals and transmission roadside units. The location, dimensions and condition of the path may be described as a path type.

[0030] In addition to and / or separately therefrom, the environmental information data 280 may include environmental conditions such as weather conditions, road conditions, air quality, light levels, and / or timestamps. Weather conditions may include, for example, the presence of precipitation such as snow, rain, and / or hail. Weather conditions may further include weather effects such as fog levels, snowfall levels (i.e., amount of snow on the ground), and / or flooding. Air quality may include the concentration of dust and pollen in the air. Light levels may include the luminosity of light inside and / or around the vehicle. The environmental information data 280 may be updated regularly and / or on demand. Sensor data 260, vehicle information data 270, and environmental information data 280 may be digital data describing information used by the vehicle sneeze control system 100 to control the vehicle system 140.

[0031] In one embodiment, the prediction module 220 may include an instruction, which, when executed by the processor 110, causes the processor 110 to predict the onset of a user sneezing fit. For example, the prediction module 220 may further include an instruction, which, when executed by the processor 110, causes the processor 110 to predict the onset of a user sneezing fit based on one or more visual cues, auditory cues, and environmental conditions.

[0032] The prediction module 220 may receive sensor data 260 and / or environmental information data 280 from the data store 250. As described above, the prediction module 220 can determine the onset of a user's sneezing fit based on visual cues. For example, the prediction module 220 may receive sensor data 260 indicating the position of the user's head, face, and hands, as well as the user's facial expression. Based on the received sensor data 260, the prediction module 220 may determine whether the user is about to sneeze. For example, the prediction module 220 may determine that the user is about to sneeze if the sensor data 260 indicates that the user's head is tilted back, their mouth is open, their eyes are closed or narrowed, and / or the user's hands are moving toward the user's face.

[0033] As described above, the prediction module 220 can determine the onset of a user's sneezing attack based on an audible cue. For example, the prediction module 220 may receive sensor data 260 that includes sounds generated inside the vehicle. Based on the received sensor data 260, the prediction module 220 may determine whether the user is about to sneeze. For example, the prediction module 220 may determine that the user is about to sneeze if the sensor data 260 includes inhalation sounds and / or sounds associated with sneezing, such as "ah!".

[0034] As described above, the prediction module 220 can determine the onset of a user sneeze based on environmental conditions. For example, the prediction module 220 may receive environmental information data 280, including the air quality and light levels inside and / or around the vehicle 102. Based on the received environmental information data 280, the prediction module 220 may determine whether the user is about to sneeze. In one embodiment, the prediction module 220 may determine whether the user is about to sneeze using, for example, the concentration of dust and / or pollen in the air, the luminosity of light, the user's past responses to dust, pollen, and light levels, and a combination of visual and auditory cues. In another embodiment, the prediction module 220 may use the received environmental information data 280 to determine whether conditions exist that could trigger a user sneeze, and may begin monitoring for visual and auditory cues when such conditions exist. Separately, the prediction module 220 may monitor for visual and / or auditory cues to determine whether the prediction module 220 has determined whether there are conditions that could trigger a sneezing fit in the user. The prediction module 220 can predict the onset of a sneezing fit in the user using any appropriate algorithm, such as a machine learning algorithm or an artificial intelligence process. In addition to and / or separately, the prediction module 220 can predict the onset of a sneezing fit in the user using user history.

[0035] In one embodiment, the stage identification module 230 may include an instruction, which, when executed by the processor 110, causes the processor 110 to identify multiple stages of a user's sneezing fit. These stages may include one or more of the inspiratory, expiratory, standby, and normal stages. The inspiratory stage of a user's sneezing fit occurs when the user inhales and is related to the initial spasmodic inspiratory stage of the sneeze reflex. The expiratory stage of a user's sneezing fit occurs when the user exhales and is related to the oral and nasal expiratory stages of the sneeze reflex. The standby stage of a user's sneezing fit occurs after the expiratory stage. The standby stage is a waiting period from the end of the sneeze until the vehicle returns to a normal, sneeze-free driving mode. The duration of the standby stage can vary and can be set to any appropriate period, including a zero period. In the normal stage, the user is not sneezing and can operate the vehicle.

[0036] For example, the stage identification module 230 can receive a signal from the prediction module 220 indicating the onset of a user sneeze attack, and the stage identification module 230 can monitor the stage of the user sneeze attack using sensor data 260. The stage identification module 230 can identify stages using visual cues and / or auditory cues. As an example of using visual and auditory cues, the stage identification module 230 can identify the inspiratory stage when sensor data 260 indicates that the user has their eyes closed, their mouth open, and is making breathing sounds such as "ha!". In such an example, the stage identification module 230 can identify the expiratory stage when sensor data 260 indicates that the user has their eyes closed, their mouth open, and is making breathing sounds such as "choo!". The stage identification module 230 can identify the standby stage based on the end of the expiratory stage and the duration allocated to the standby stage. Based on the end of the standby stage, the stage identification module can identify the normal stage when there is no signal from the prediction module 220 indicating the onset of a user sneeze attack.

[0037] The stage identification module 230 can identify the stage of a user's sneezing fit using any appropriate algorithm, such as a machine learning algorithm or an artificial intelligence process. In addition to this, and / or separately, the stage identification module 230 can identify the stage of a user's sneezing fit using user history. The stage identification module 230 can output a stage signal indicating which stage of the user's sneezing fit is valid for the vehicle system control module 240.

[0038] In one embodiment, the vehicle system control module 240, when executed by the processor 110, may include instructions that cause the processor 110 to control the vehicle system 140 based on which stage of the stage is active. For example, the vehicle system control module 240 may receive an onset signal from a prediction module 220 indicating the start of a user sneeze attack, and may receive a stage signal from a stage identification module 230 indicating which stage of the user sneeze attack is active. The vehicle system control module 240 may determine a user defect in one or more stages and control the vehicle system 140 to compensate for that defect. For example, the vehicle system control module 240 may determine, based on sensor data 260 and / or user history, that the user's eyes are open during the inhalation stage and closed during the exhalation stage. Accordingly, the vehicle system control module 240 may activate or increase the sensitivity of the vehicle environment sensors during the exhalation stage to compensate for the user's eyes being closed. The vehicle system control module 240 can deactivate or reduce the sensitivity of the vehicle environment sensor 122 during standby or normal operation.

[0039] The vehicle system control module 240 may further include instructions, which, when executed by the processor 110, cause the processor 110 to control the vehicle system 140 based on one or more of the following: vehicle speed, vehicle position, relative position of vehicle 102, handwheel position, handwheel rotation speed, objects adjacent to vehicle 102, and sneeze prediction reliability. In addition to and / or separately, the vehicle system control module 240 may control the vehicle system 140 based on one or more of the following: user history, user driving style, and / or environmental information data 280. As previously stated, the vehicle system control module 240 may control one or more of the steering system 143, throttle system 144, and braking system 142. In one or more stages, the vehicle system control module 240 may control, enable, or disable the vehicle system 140 when the stage is enabled.

[0040] As an example, the vehicle system control module 240 can detach the steering wheel from the steering rack during the exhalation phase. As another example, the vehicle system control module 240 can adjust the damping coefficient between the steering wheel and the steering rack. In such an example, the vehicle system control module 240 can increase the damping coefficient during the exhalation phase so that sudden clockwise or counterclockwise movements of the steering wheel are absorbed by the buffer between the steering wheel and the steering rack and do not affect the steering rack. As yet another example, the vehicle system control module 240 can reduce the advance of the steering wheel. In such an example, a 30-degree turn of the steering wheel may result in a 10-degree turn of the steering rack. As yet another example, the vehicle system control module 240 can adjust the smoothing coefficient between the steering wheel and the steering rack. The smoothing coefficient can smooth inputs such as a rate of change and / or degree of change. The rate of change may be the amount of change the user makes by turning the steering wheel. In such a case, the vehicle system control module 240 can use the smoothing coefficient to average the rate at which the steering rack rotates in response to the steering wheel, based on the previous rate of change. The degree of change may be a measurement of the steering angle. In such cases, the vehicle system control module 240 can use a smoothing factor to average the angle by which the steering rack rotates in response to the steering wheel, based on the previous degree of change.

[0041] As an example, the vehicle system control module 240 can disconnect the accelerator pedal from the throttle during the intake phase. As another example, the vehicle system control module 240 can disconnect the brake pedal from the brake actuator. Similar to the steering system 143 described above, the vehicle system control module 240 can adjust the damping coefficient between the accelerator pedal and the throttle and / or between the brake pedal and the brake actuator. In such an example, the vehicle system control module 240 can increase the damping coefficient so that inputs such as depressing the accelerator pedal or brake pedal are absorbed by the shock absorber so that the response by the throttle or brake actuator is minimized, respectively. As yet another example, similar to the steering system 143, the vehicle system control module 240 can reduce the gain of the inputs to the throttle system 144 and / or the braking system 142. As yet another example, the vehicle system control module 240 can adjust the smoothing coefficient between the input unit and the function unit for the throttle system 144 and / or the braking system 142.

[0042] The vehicle system control module 240 may further include instructions, which, when executed by the processor 110, cause the processor 110 to control the vehicle system in a first mode when one of the stages is active, and to control the vehicle system 140 in a second mode when another of the stages is active. In such cases, the first mode is different from the second mode. As an example, the vehicle system control module 240 can adjust the damping coefficient between the accelerator pedal and the throttle to a first value for the intake stage, a second value for the exhalation stage, a third value for the standby stage, and a fourth value for the normal stage.

[0043] The vehicle system control module 240 can control one or more vehicle systems 140 at one stage, but cannot control one or more vehicle systems 140 at another stage. As another example, the vehicle system control module 240 can control the vehicle system 140 at one stage with a first level of involvement or intensity, and control the vehicle system 140 at another stage with a second level of involvement or intensity.

[0044] As an example, the vehicle system control module 240 can switch the driving mode of the vehicle 102. In such an example, the vehicle system control module 240 can switch the vehicle 102 to a semi-autonomous mode in one stage and to a fully autonomous mode in another stage. Similarly, the vehicle system control module 240 can enable, disable, and / or adjust the parameters of any appropriate driver assistance system. As an example, the vehicle system control module 240 can adjust the parameters of the lane centering assistance system by narrowing or widening the center lane area. As another example, the vehicle system control module 240 can adjust the parameters of the lane centering assistance system so that the lane centering assistance system can keep the vehicle within the lane edge more gradually or more abruptly based on time and / or applied force.

[0045] Figure 3 shows a method 300 for controlling the vehicle system 140 when it is under user control. Method 300 will be described in terms of the vehicle 102 in Figure 1 and the vehicle sneeze control system in Figure 2. However, method 300 may not necessarily be implemented by the vehicle in Figure 1 and / or the vehicle sneeze control system in Figure 2, but may be configured to be implemented in any one of several different situations.

[0046] In step 310, the prediction module 220 may cause the processor 110 to predict the onset of the user's sneezing attack. As previously mentioned, the prediction module 220 may predict the onset of the user's sneezing attack based on sensor data 260, vehicle information data 270 and / or environmental information data 280. The prediction module 220 may output an onset signal indicating the onset of the user's sneezing attack.

[0047] In step 320, the stage identification module 230 may cause the processor 110 to identify multiple stages in the user's sneezing fits. For example, the stage identification module 230 may receive an onset signal indicating the start of the user's sneezing fit and then identify the stages of the user's sneezing fit based on the sensor data 260 as described above. The stage identification module 230 may output a stage signal indicating which of the stages is currently active.

[0048] In step 330, the vehicle system control module 240 may cause the processor 110 to control the vehicle system 140 based on which of the stages is active. As described above, the vehicle system control module 240 can control one or more vehicle systems 140, such as the steering system 143, throttle system 144, braking system 142, driver assistance system and / or autonomous driving system 160.

[0049] Here, in relation to Figure 4, one or more non-limiting examples and / or methods of operation of the vehicle sneeze control system 100 during multiple stages of a user's sneeze attack will be described. Figure 4 shows an example of a vehicle sneeze control situation.

[0050] Figure 4 shows a user driving vehicle 102. Vehicle 102 is equipped with driver assistance systems, such as a lane keeping system and a collision avoidance system, which are currently disabled. As shown in the figure, in the normal stage 410 of the user's sneezing attack, the user is not sneezing and is operating vehicle 102 and / or one or more vehicle systems 140. The vehicle sneeze control system 100 is not controlling vehicle 102 and / or one or more vehicle systems 140.

[0051] In normal stage 410, one or more sensors, such as camera 126, sound sensor 127, and air quality sensor 128, monitor objects and / or events within the vehicle 102. The vehicle sneeze control system 100, more specifically the prediction module 220, can periodically evaluate sensor data 260 received from the sensors to determine whether the onset of a sneeze attack by the user has been detected. For example, as shown in the figure, the prediction module 220 can determine the onset of a sneeze attack by the user based on sensor data 260 indicating that the user's head is tilted back, the user's eyes are closed, the user's mouth is open, and the user makes a "ha!" sound. The prediction module 220 can then output an onset signal indicating the onset of a sneeze attack by the user.

[0052] The vehicle sneeze control system 100, more specifically the stage identification module 230, can receive a start signal from the prediction module 220 and determine that the current stage of a sneeze attack is the inhalation stage 420 based on sensor data 260 indicating that the user's head is tilted back, the user's eyes are closed, the user's mouth is open, and the user makes a "ha!" sound. The stage identification module 230 can output a stage signal indicating that the current stage is the inhalation stage 420. In the inhalation stage 420, for example, the vehicle system control module 240 can reactivate a previously disabled lane keeping system based on sensor data 260, vehicle information data 270, and / or environmental information data 280.

[0053] The stage identification module 230 can determine that the current stage of a sneezing fit is the exhalation stage 430 based on sensor data 260 indicating that the user's head is tilted forward, the user's eyes are closed, the user's mouth is pursed, and the user makes a "choo!" sound. The stage identification module 230 can output a stage signal indicating that the current stage is the exhalation stage 430. In the exhalation stage 430, for example, the vehicle system control module 240 can reactivate a previously disabled collision avoidance system based on sensor data 260, vehicle information data 270, and / or environmental information data 280.

[0054] The stage identification module 230 can determine that the current stage of a sneezing fit is standby stage 440 based on sensor data indicating that the user's head is upright, the user's eyes are open and facing the road, and the user's mouth is closed. For example, the stage identification module 230 may remain in standby stage 440 for 5 seconds. The stage identification module 230 can output a stage signal indicating that the current stage is standby stage 440. In standby stage 440, for example, the vehicle system control module 240 can keep the lane keeping system and collision avoidance system active based on sensor data 260, vehicle information data 270, and / or environmental information data 280.

[0055] The stage identification module 230 can determine that the current stage of the sneezing fit is the normal stage 410 when the 5-second standby stage 440 has expired. The stage identification module 230 can output a stage signal indicating that the current stage is the normal stage 410. In the normal stage 410, for example, the vehicle system control module 240 can disable the lane keeping system and collision avoidance system and return the vehicle system 140 to the settings prior to the user's sneezing fit.

[0056] Here, Figure 1 is considered in great detail as an exemplary environment in which the systems and methods disclosed herein may operate. In some cases, the vehicle 102 is configured to selectively switch between autonomous mode, one or more semi-autonomous operating modes and / or manual mode. Such switching can be carried out in appropriate methods known now or to be developed later. "Manual mode" means that all or most of the vehicle's navigation and / or steering is carried out in accordance with input received from a user (such as a human driver). In one or more configurations, the vehicle 102 may be a conventional vehicle configured to operate only in manual mode.

[0057] In one or more embodiments, the vehicle 102 is an autonomous vehicle. As used herein, “autonomous vehicle” means a vehicle operating in autonomous mode. “Autonomous mode” means controlling the vehicle 102 with minimal or no input from a human driver, by using one or more computing systems to navigate and / or steer the vehicle 102 along a travel route. In one or more embodiments, the vehicle 102 is highly automated or fully automated. In one embodiment, the vehicle 102 is configured to have one or more semi-autonomous operating modes in which one or more computing systems perform part of the navigation and / or steering of the vehicle along a travel route, and a vehicle operator (i.e., driver) provides input to the vehicle to perform part of the navigation and / or steering of the vehicle 102 along a travel route.

[0058] Vehicle 102 may be equipped with one or more processors 110. In one or more configurations, processor 110 may be the main processor of vehicle 102. For example, processor 110 may be an electronic control unit (ECU). Vehicle 102 may be equipped with one or more data stores 115 for storing one or more types of data. Data stores 115 may include volatile and / or non-volatile memory. Examples of suitable data stores 115 include RAM (random access memory), flash memory, ROM (read-only memory), PROM (programmable read-only memory), EPROM (erasable programmable read-only memory), EEPROM (electrically erasable programmable read-only memory), registers, magnetic disks, optical disks, hard drives, or any other suitable storage medium, or any combination thereof. Data stores 115 may be components of processor 110, or data stores 115 may be operably connected to processor 110 for use by processor 110. As used throughout this description, the term “operably connected” may include direct or indirect connections, including connections without direct physical contact.

[0059] In one or more configurations, one or more data stores 115 may include map data 116. Map data 116 may include maps of one or more geographic areas. In some cases, map data 116 may include information or data about roads, traffic control devices, road markings, structures, features and / or landmarks in one or more geographic areas. Map data 116 can be in any suitable format. In some cases, map data 116 may include aerial photographs of the area. In some cases, map data 116 may include ground views of the area, including 260-degree ground views. Map data 116 may include measurements, dimensions, distances and / or information of one or more items included in map data 116 and / or relative measurements, dimensions, distances and / or information with respect to other items included in map data 116. Map data 116 may include digital maps with information about road shapes. Map data 116 may be of high quality and / or very detailed.

[0060] One or more data stores 115 may contain sensor data 119. In this context, “sensor data” means any information relating to sensors equipped in the vehicle 102, including information relating to the capabilities of such sensors. As described below, the vehicle 102 may include a sensor system 120. The sensor data 119 may relate to one or more sensors of the sensor system 120. For example, in one or more configurations, the sensor data 119 may include information relating to one or more vehicle sensors 121 and / or environmental sensors 122 of the sensor system 120.

[0061] In some cases, at least a portion of the map data 116 and / or sensor data 119 can be placed in one or more data stores 115 mounted on the vehicle 102. Separately from, or in addition to, at least a portion of the map data 116 and / or sensor data 119 can be placed in one or more data stores 115 located away from the vehicle 102.

[0062] As described above, the vehicle 102 may be equipped with a sensor system 120. The sensor system 120 may comprise one or more sensors. "Sensor" means a device, component and / or system that can detect and / or sense something. One or more sensors may be configured to detect and / or sense in real time. As used herein, "real time" means a level of processing responsiveness that is fast enough for a user or system to perform a particular process or decision, or that allows a processor to keep up with some external process.

[0063] In a configuration where the sensor system 120 comprises multiple sensors, the sensors can operate independently of each other. Alternatively, two or more sensors can be operated in combination. In such a case, the two or more sensors can form a sensor network. The sensor system 120 and / or one or more sensors can be operably connected to the processor 110, the data store 115, and / or other elements of the vehicle 102 (including any of the elements shown in Figure 1). The sensor system 120 can acquire data from the internal environment of the vehicle 102 (e.g., a nearby vehicle), as well as data from at least some of the external environment.

[0064] The sensor system 120 may comprise any suitable type of sensor. Various examples of different types of sensors are described herein. However, it will be understood that embodiments are not limited to the specific sensors described. The sensor system 120 may comprise one or more vehicle sensors 121. The vehicle sensors 121 may detect, determine, and / or sense information about the vehicle 102 itself. In one or more configurations, the vehicle sensors 121 may be configured to detect and / or sense changes in the position and orientation of the vehicle 102, for example, based on inertial acceleration. In one or more configurations, the vehicle sensors 121 may include one or more accelerometers, one or more gyroscopes, inertial measuring units (IMUs), dead reckoning systems, global navigation satellite systems (GNSS), global positioning systems (GPS), navigation systems 147, and / or other suitable sensors. The vehicle sensors 121 may be configured to detect and / or sense one or more characteristics of the vehicle 102. In one or more configurations, the vehicle sensor 121 may include a speedometer for determining the current speed of the vehicle 102.

[0065] Separately, or in addition to, the sensor system 120 may include one or more environmental sensors 122 configured to acquire and / or sense data inside and around the vehicle. Sensor data inside the vehicle may include information about target objects, including one or more users inside the vehicle's interior. Sensor data around the vehicle may include information about the external environment in which the vehicle is located, or one or more parts thereof.

[0066] As an example, one or more environmental sensors 122 may be configured to detect, quantify, and / or sense objects and / or information / data about such objects within at least a portion of the environment inside and / or outside the vehicle 102.

[0067] In the internal environment of the vehicle 102, one or more environmental sensors 122 may be configured to detect, measure, quantify, and / or sense human users and their facial expressions inside the vehicle 102. In the external environment, one or more environmental sensors 122 may be configured to detect, measure, quantify, and / or sense objects in the external environment of the vehicle 102, such as lane markers, signs, traffic lights, road signs, lanes, crosswalks, curbs adjacent to the vehicle 102, objects outside the road, and electronic roadside devices.

[0068] This specification describes various examples of sensors in the sensor system 120. The exemplary sensors may be part of one or more environmental sensors 122 and / or one or more vehicle sensors 121. However, it will be understood that the embodiments are not limited to the specific sensors described.

[0069] As an example, in one or more configurations, the sensor system 120 may comprise one or more radar sensors 123, one or more LiDAR sensors 124, one or more sonar sensors 125, one or more cameras 126, and / or one or more sound sensors 127. In one or more configurations, one or more cameras 126 may be high dynamic range (HDR) cameras or infrared (IR) cameras. The sound sensor 127 may be a microphone and / or any suitable recording device. Any sensor in the sensor system 120 suitable for detecting and observing humans and / or human facial expressions may be used in the vehicle 102 to observe the user. Furthermore, the sensor system 120 may comprise one or more air quality sensors 128 for detecting allergens such as pollen, dust, and / or fur in the air inside the vehicle. The sensor system 120 may comprise one or more light sensors 129 for measuring the light level inside the vehicle.

[0070] Vehicle 102 may be equipped with an input system 130. The “input system” includes devices, components, systems, elements, configurations, or groups thereof that enable information / data to be input into the machine. The input system 130 may receive input from a user (e.g., a driver or a passenger). Vehicle 102 may be equipped with an output system 135. The “output system” includes any devices, components, or configurations, or groups thereof that enable information / data to be presented to a user (e.g., a person, a passenger, etc.), such as a display interface.

[0071] Vehicle 102 may comprise one or more vehicle systems 140. Various examples of one or more vehicle systems 140 are shown in Figure 1. However, vehicle 102 may comprise more, fewer, or different vehicle systems 140. While specific vehicle systems are defined separately, it should be understood that each or any of the systems or parts thereof may be otherwise combined or separated via hardware and / or software within vehicle 102. Vehicle 102 may comprise a propulsion system 141, a braking system 142, a steering system 143, a throttle system 144, a transmission system 145, a signaling system 146, and / or a navigation system 147. Each of such systems may comprise one or more devices, components, and / or combinations thereof, which are currently known or will be developed later.

[0072] The navigation system 147 may comprise one or more currently known or later developed devices, applications, and / or combinations thereof configured to determine the geographical location of the vehicle 102 and / or the travel route of the vehicle 102. The navigation system 147 may comprise one or more mapping applications for determining the travel route of the vehicle 102. The navigation system 147 may include a global positioning system, a local positioning system, or a geolocation information system.

[0073] The vehicle 102 may be equipped with one or more autonomous driving systems 160. The autonomous driving system 160 may comprise one or more currently known or later developed devices, applications, and / or combinations thereof configured to control the movement, speed, steering, direction of travel, orientation, etc., of the vehicle 102. The autonomous driving system 160 may comprise one or more driver assistance systems, such as a lane keeping system, a lane centering system, a collision avoidance system, and / or a driver monitoring system.

[0074] The autonomous driving system 160 can be configured to receive data from the sensor system 120 and / or from any other type of system capable of capturing information related to the vehicle 102 and / or the external environment of the vehicle 102. In one or more configurations, the autonomous driving system 160 can use such data to generate one or more driving scenario models. The autonomous driving system 160 can determine the position and speed of the vehicle 102. The autonomous driving system 160 can determine the position of obstacles, obstacles, or other environmental features including traffic signs, trees, shrubs, adjacent vehicles, pedestrians, etc.

[0075] The autonomous driving system 160 may be configured to receive and / or determine the location information of obstacles in the external environment of the vehicle 102 for use by the processor 110, and / or one or more of the modules described herein for estimating the position and orientation of the vehicle 102, the vehicle's position in global coordinates based on signals from multiple satellites, or any other data and / or signals that may be used to determine the position of the vehicle 102 relative to its environment for use in determining the current state of the vehicle 102, or when creating a map or determining the position of the vehicle 102 with respect to map data.

[0076] The autonomous driving system 160 can be configured to determine, independently or in combination with the vehicle sneeze control system 100, data from any other appropriate source of information, such as the travel route, the current autonomous driving operation of the vehicle 102, future autonomous driving operations and / or modifications to the current autonomous driving operation based on data acquired by the sensor system 120, a driving scenario model, and / or determinations from sensor data 119. “Driving operation” means one or more actions that affect the movement of the vehicle. Examples of driving operations, to name a few, include acceleration, deceleration, braking, turning, lateral movement of the vehicle 102, changing lanes, merging into lanes, and / or reversing. The autonomous driving system 160 can be configured to perform the determined driving operation. The autonomous driving system 160 can be made to perform such autonomous driving operations directly or indirectly. As used herein, “to cause” or “to make something happen” means to cause, command, instruct, and / or enable an event or action, or at least put into a state where such an event or action could occur directly or indirectly. The autonomous driving system 160 can be configured to perform various vehicle functions and / or transmit data to the vehicle 102 or one or more of its systems (e.g., one or more of the vehicle systems 140), receive data from the vehicle or systems, interact with the vehicle or systems, and / or control the vehicle or systems.

[0077] The processor 110, the vehicle sneeze control system 100, and / or the autonomous driving system 160 can be operationally connected to communicate with various vehicle systems 140 and / or their individual components. For example, returning to Figure 1, the processor 110, the vehicle sneeze control system 100, and / or the autonomous driving system 160 can communicate to send and / or receive information from various vehicle systems 140 to control the movement, speed, steering, direction, and other aspects of the vehicle 102. The processor 110, the vehicle sneeze control system 100, and / or the autonomous driving system 160 may be partially or entirely autonomous, as they may control some or all of such vehicle systems 140.

[0078] The processor 110, the vehicle sneeze control system 100, and / or the autonomous driving system 160 may be capable of controlling the navigation and / or steering of the vehicle 102 by controlling the vehicle system 140 and / or one or more of its components. For example, when operating in autonomous mode, the processor 110, the vehicle sneeze control system 100, and / or the autonomous driving system 160 can control the direction and / or speed of the vehicle 102. As another example, the processor 110, the vehicle sneeze control system 100, and / or the autonomous driving system 160 can enable, disable, and / or adjust the parameters (or settings) of one or more driver assistance systems. The processor 110, the vehicle sneeze control system 100, and / or the autonomous driving system 160 can accelerate the vehicle 102 (for example, by increasing the fuel supply to the engine), decelerate it (for example, by decreasing the fuel supply to the engine and / or by applying the brakes), and / or change direction (for example, by turning the two front wheels). As used in this document, "to cause" or "to make something happen" means to cause, propel, force, guide, command, instruct, and / or enable an event or action, or at least put into a state where such an event or action could occur, directly or indirectly.

[0079] The vehicle 102 may be equipped with one or more actuators 150. The actuators 150 may be any element or combination of elements that can operate to modify, adjust, and / or change one or more of the vehicle system 140 or its components and / or the autonomous driving system 160 in response to receiving signals or other inputs from the processor 110. Any suitable actuator can be used. For example, one or more actuators 150 may include, to name a few, motors, pneumatic actuators, hydraulic pistons, relays, solenoids and / or piezoelectric actuators.

[0080] The vehicle 102 may comprise one or more modules. At least some of these modules are described herein. A module may be implemented as computer-readable program code that, when executed by the processor 110, executes one or more of the various processes described herein. One or more of the modules may be components of the processor 110, or one or more of the modules may run on and / or be distributed across other processing systems to which the processor 110 is operablely connected. A module may contain instructions (e.g., program logic) that can be executed by one or more processors 110. Separately from, or in addition to, one or more data stores 115 may contain such instructions.

[0081] In one or more configurations, one or more of the modules described herein may include artificial intelligence elements or computational intelligence elements, such as neural networks, fuzzy logic, or other machine learning algorithms. Furthermore, in one or more configurations, one or more of the modules may be distributed among multiple modules described herein. In one or more configurations, two or more of the modules described herein may be combined into a single module.

[0082] Detailed embodiments are disclosed herein. However, it should be understood that the disclosed embodiments are intended to be illustrative only. Therefore, the specific structural and functional details disclosed herein should not be construed as limiting, but merely as representative grounds to teach those skilled in the art how to employ various aspects of this specification in virtually any appropriately detailed structure, in addition to serving as the basis for the claims. Furthermore, the terms and phrases used herein are not intended to be limiting, but to provide an understandable description of possible implementations. Various embodiments are shown in Figures 1- Figure 4As shown, the embodiments are not limited to the illustrated structure or use.

[0083] The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. Furthermore, it should be noted that in some alternative implementations, the functions shown in the blocks may occur in a different order than shown in the diagram. For example, two blocks shown consecutively may actually be executed substantially simultaneously, or they may be executed in reverse order depending on the functions they relate to.

[0084] The systems, components, and / or processes described herein can be implemented in hardware or a combination of hardware and software, and may be implemented centrally in a single processing system or distributed across several interconnected processing systems. Any type of processing system or other device configured to carry out the methods described herein is suitable. A typical combination of hardware and software may be a processing system comprising computer-readable program code that, when loaded and executed, controls the processing system to carry out the methods described herein. Other systems, components, and / or processes may be incorporated into computer-readable storage devices, such as computer program products or other data program storage devices, which are machine-readable and explicitly embody a program of machine-executable instructions for carrying out the methods and processes described herein. Other such elements may be embedded in application products that, when loaded into a processing system, include all the functions necessary to carry out the methods described herein and can carry out such methods.

[0085] Furthermore, the configurations described herein may take the form of a computer program product embodied in a computer-readable medium having, for example, stored computer-readable program code embedded therein. Any combination of one or more computer-readable mediums may be used. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The phrase "computer-readable storage medium" means a non-temporary storage medium. The computer-readable storage medium may be, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or apparatus, or any suitable combination thereof. Further specific examples (not exhaustive) of computer-readable storage mediums include: portable computer diskettes, hard disk drives (HDDs), solid-state drives (SSDs), read-only memory (ROMs), erasable programmable read-only memory (EPROMs or flash memory), portable compact disc read-only memory (CD-ROMs), digital multi-purpose discs (DVDs), optical storage devices, magnetic storage devices, or any suitable combination thereof. In the context of this document, a computer-readable storage medium may be any tangible medium that can contain or store programs for use by, or in connection with, an instruction execution system, device, or apparatus.

[0086] Generally, modules used herein include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific data type. In additional embodiments, memory generally stores the above-mentioned modules. Memory associated with a module may be a buffer or cache embedded within a processor, RAM, ROM, flash memory, or another suitable electronic storage medium. In yet another embodiment, the modules envisioned by this disclosure are implemented as application-specific integrated circuits (ASICs), system-on-a-chip (SoC) hardware components, programmable logic arrays (PLAs), or another suitable hardware component into which a set of configurations (e.g., instructions) defined for performing the disclosed functions is embedded.

[0087] Program code embodied on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, cable, RF, or any suitable combination thereof. Computer program code for performing operations of this configuration may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java®, Smalltalk, and C++, and conventional procedural programming languages ​​such as the C programming language or a similar programming language. The program code may run as a standalone software package, either entirely on the user's computer, partially on the user's computer, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case where the entire program runs on a remote computer or server, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or wide area network (WAN), or to an external computer (for example, via the Internet using an Internet service provider).

[0088] As used herein, the terms “a” and “an” are defined as one or more. As used herein, the term “plural” is defined as two or more. As used herein, the term “another” is defined as at least the second or subsequent one. As used herein, the terms “equip” and / or “have” are defined as including (i.e., open language). As used herein, the phrase “at least one of… and…” refers to and includes any possible combination of one or more of the related enumerated items. For example, the phrase “at least one of A, B and C” includes A only, B only, C only, or any combination thereof (e.g., AB, AC, BC, or ABC).

[0089] Aspects of this specification can be embodied in other forms without departing from its spirit or essential attributes. For this reason, the following claims, rather than the aforementioned specification, should be used to indicate the scope of this specification. The inventions disclosed herein include the following embodiments: [Aspect 1] A method for controlling a vehicle system while the vehicle system is under the control of a user, A step to predict the onset of the user's sneezing attack, The steps include identifying multiple stages of the user's sneezing episode, A step of controlling the vehicle system based on which of the aforementioned multiple steps is active, Methods that include... [Aspect 2] The method according to embodiment 1, wherein the vehicle system includes an input unit and a functional unit, and the input unit is separated from the functional unit. [Aspect 3] The method according to embodiment 1, wherein the vehicle system is one or more of a steering system, a throttle system, and a braking system. [Aspect 4] The method according to embodiment 1, wherein the step of predicting the onset of the user's sneezing attack is based on one or more of visual cues, auditory cues, and environmental conditions. [Aspect 5] The method according to embodiment 1, wherein the plurality of stages include one or more of the inhalation stage, exhalation stage, standby stage, and normal stage. [Aspect 6] The method according to embodiment 1, further comprising the step of controlling the vehicle system based on one or more of the following: vehicle speed, vehicle position, relative position of the vehicle, handwheel position, handwheel rotation speed, objects adjacent to the vehicle, and the reliability of sneeze prediction. . [Aspect 7] A step of controlling the vehicle system in a first mode when one of the aforementioned multiple steps is active, The method according to embodiment 1, further comprising the step of controlling the vehicle system in a second mode when another of the aforementioned multiple stages is active, wherein the first mode is different from the second mode. [Aspect 8] The method according to embodiment 7, wherein the first mode and the second mode differ based on one or more of the function, intensity and duration. [Aspect 9] A system for controlling a vehicle system while the vehicle system is under the control of a user, Processor and A memory that communicates with the aforementioned processor, A prediction module having an instruction, when executed by the processor, that causes the processor to predict the onset of a user's sneezing attack, A stage identification module having instructions, when executed by the processor, that cause the processor to identify multiple stages of the user's sneezing fits, A vehicle system control module having instructions, when executed by the processor, that cause the processor to control the vehicle system based on which of the plurality of stages is active, and a memory including: A system that is equipped with [the following]. [Aspect 10] The vehicle system includes an input unit and a functional unit, wherein the input unit is separated from the functional unit, according to embodiment 9. [Aspect 11] The system according to embodiment 9, wherein the vehicle system is one or more of a steering system, a throttle system, and a braking system. [Aspect 12] The system according to embodiment 9, wherein the prediction module, when executed by the processor, further includes an instruction causing the processor to predict the onset of the user's sneezing fit based on one or more of visual cues, auditory cues, and environmental conditions. [Aspect 13] The system according to embodiment 9, wherein the plurality of stages include one or more of the inhalation stage, exhalation stage, standby stage, and normal stage. [Aspect 14] The system according to embodiment 9, wherein the vehicle system control module, when executed by the processor, further includes instructions causing the processor to control the vehicle system based on one or more of the following: vehicle speed, vehicle position, relative position of the vehicle, handwheel position, handwheel rotation speed, objects adjacent to the vehicle, and the reliability of sneeze prediction. [Aspect 15] The system according to embodiment 9, wherein the vehicle system control module, when executed by the processor, further includes instructions causing the processor to control the vehicle system in a first mode when one of the plurality of stages is enabled, and to control the vehicle system in a second mode when another of the plurality of stages is enabled, wherein the first mode is different from the second mode. [Aspect 16] The system according to embodiment 15, wherein the first mode and the second mode differ based on one or more of the function, intensity, and duration. [Aspect 17] A non-temporary computer-readable medium containing instructions, which, when executed by a processor, controls the vehicle system while the vehicle system is under the user's control, and the instructions are transmitted to the processor. To predict the onset of a user's sneezing attack, To identify multiple stages of the user's sneezing episode, The vehicle system is controlled based on which of the aforementioned multiple stages is active. Non-temporary computer-readable media. [Aspect 18] The vehicle system includes an input unit and a functional unit, wherein the input unit is separated from the functional unit, the non-temporary computer-readable medium according to embodiment 17. [Aspect 19] The non-temporary computer-readable medium according to embodiment 17, wherein the vehicle system is one or more of a steering system, a throttle system, and a braking system. [Aspect 20] The non-temporary computer-readable medium according to embodiment 17, wherein the prediction of the onset of the user's sneezing episode is based on one or more of visual cues, auditory cues, and environmental conditions.

Claims

1. A method for controlling a vehicle system while the vehicle system is under the control of a user, A step to predict the onset of a user's sneezing attack, The steps include identifying multiple stages of the user's sneezing episode, A step of controlling the vehicle system based on which of the aforementioned multiple steps is active, Includes, A method comprising at least three of the aforementioned steps.

2. The method according to claim 1, wherein the vehicle system includes an input unit for human-machine interaction and a functional unit for mechanically controlling either vehicle speed, acceleration, or braking, the input unit being separated from the functional unit by a mechanism which is at least one of an electrical system, an electronic system, and an electromechanical system.

3. The method according to claim 1, wherein the vehicle system is one or more of a steering system, a throttle system, and a braking system.

4. The method according to claim 1, wherein the step of predicting the onset of the user's sneezing episode is based on one or more of a visual cue, an auditory cue, and an environmental condition.

5. The method according to claim 1, wherein the plurality of stages include one or more of an inhalation stage, an exhalation stage, a standby stage, and a normal stage.

6. The method according to claim 1, further comprising the step of controlling the vehicle system based on one or more of the following: vehicle speed, vehicle position, relative position of the vehicle, handwheel position, handwheel rotation speed, objects adjacent to the vehicle, and the reliability of sneeze prediction.

7. A step of controlling the vehicle system in a first mode when one of the aforementioned multiple steps is active, The method according to claim 1, further comprising the step of controlling the vehicle system in a second mode when another of the aforementioned multiple stages is active, wherein the first mode is different from the second mode.

8. The method according to claim 7, wherein the first mode and the second mode differ based on one or more of the function, intensity and duration.

9. A system for controlling a vehicle system while the vehicle system is under the control of a user, Processor and A memory that communicates with the aforementioned processor, A prediction module having an instruction, when executed by the processor, that causes the processor to predict the onset of a user's sneezing attack, A stage identification module having instructions, when executed by the processor, that cause the processor to identify multiple stages of the user's sneezing fits, A vehicle system control module having instructions, when executed by the processor, that cause the processor to control the vehicle system based on which of the plurality of stages is active, and a memory including: It is equipped with, The aforementioned multiple stages include at least three stages in the system.

10. The vehicle system according to claim 9, comprising an input unit for human-machine interaction and a functional unit for mechanically controlling either vehicle speed, acceleration, or braking, wherein the input unit is separated from the functional unit by a mechanism which is at least one of an electrical system, an electronic system, and an electromechanical system.

11. The system according to claim 9, wherein the vehicle system is one or more of a steering system, a throttle system, and a braking system.

12. The system according to claim 9, wherein the prediction module, when executed by the processor, further includes an instruction causing the processor to predict the onset of the user's sneezing fit based on one or more of visual cues, auditory cues, and environmental conditions.

13. The system according to claim 9, wherein the plurality of stages include one or more of an inhalation stage, an exhalation stage, a standby stage, and a normal stage.

14. The system according to claim 9, wherein the vehicle system control module, when executed by the processor, further includes instructions causing the processor to control the vehicle system based on one or more of the following: vehicle speed, vehicle position, relative position of the vehicle, handwheel position, handwheel rotation speed, objects adjacent to the vehicle, and the reliability of sneeze prediction.

15. The system according to claim 9, wherein the vehicle system control module, when executed by the processor, further includes instructions causing the processor to control the vehicle system in a first mode when one of the plurality of stages is enabled, and to control the vehicle system in a second mode when another of the plurality of stages is enabled, wherein the first mode is different from the second mode.

16. The system according to claim 15, wherein the first mode and the second mode differ based on one or more of the function, intensity and duration.

17. A non-temporary computer-readable medium containing instructions, which, when executed by a processor, controls the vehicle system while the vehicle system is under the user's control, and the instructions are transmitted to the processor. To predict the onset of a user's sneezing attack, To identify multiple stages of the user's sneezing episode, The vehicle system is controlled based on which of the aforementioned multiple stages is active. The aforementioned multiple stages include at least three stages, and the medium is non-temporary.

18. The vehicle system includes an input unit for human-machine interaction and a functional unit for mechanically controlling either vehicle speed, acceleration, or braking, wherein the input unit is separated from the functional unit by a mechanism which is at least one of an electrical system, an electronic system, and an electromechanical system, the non-temporary computer-readable medium according to claim 17.

19. The non-temporary computer-readable medium according to claim 17, wherein the vehicle system is one or more of a steering system, a throttle system, and a braking system.

20. The non-temporary computer-readable medium according to claim 17, wherein the prediction of the onset of the user's sneezing episode is based on one or more of visual cues, auditory cues, and environmental conditions.

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