EP4013643A1 - Automatisches anpassen einer fahrzeug-sitzposition zum vermeiden von reiseübelkeit - Google Patents
Automatisches anpassen einer fahrzeug-sitzposition zum vermeiden von reiseübelkeitInfo
- Publication number
- EP4013643A1 EP4013643A1 EP20746640.0A EP20746640A EP4013643A1 EP 4013643 A1 EP4013643 A1 EP 4013643A1 EP 20746640 A EP20746640 A EP 20746640A EP 4013643 A1 EP4013643 A1 EP 4013643A1
- Authority
- EP
- European Patent Office
- Prior art keywords
- vehicle
- trajectory
- seat
- predicted
- sensor
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Withdrawn
Links
- 201000003152 motion sickness Diseases 0.000 title claims abstract description 21
- 208000037175 Travel-Related Illness Diseases 0.000 title claims abstract description 20
- 238000000034 method Methods 0.000 claims abstract description 24
- 230000033001 locomotion Effects 0.000 claims description 13
- 230000006870 function Effects 0.000 claims description 11
- 230000005484 gravity Effects 0.000 claims description 6
- 238000010801 machine learning Methods 0.000 claims description 6
- 238000004393 prognosis Methods 0.000 claims description 5
- 239000000725 suspension Substances 0.000 claims description 3
- 230000008859 change Effects 0.000 description 14
- 238000012937 correction Methods 0.000 description 9
- 238000006243 chemical reaction Methods 0.000 description 5
- 238000011161 development Methods 0.000 description 5
- 230000018109 developmental process Effects 0.000 description 5
- 230000000694 effects Effects 0.000 description 5
- 238000013459 approach Methods 0.000 description 4
- 238000013213 extrapolation Methods 0.000 description 4
- 206010028813 Nausea Diseases 0.000 description 3
- 230000007274 generation of a signal involved in cell-cell signaling Effects 0.000 description 3
- 230000008693 nausea Effects 0.000 description 3
- 230000001953 sensory effect Effects 0.000 description 3
- 230000000007 visual effect Effects 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 2
- 230000003111 delayed effect Effects 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 230000006978 adaptation Effects 0.000 description 1
- 238000013528 artificial neural network Methods 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 230000001413 cellular effect Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000011157 data evaluation Methods 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 230000000977 initiatory effect Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000012821 model calculation Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000001629 suppression Effects 0.000 description 1
- 230000002123 temporal effect Effects 0.000 description 1
- 238000013519 translation Methods 0.000 description 1
- 230000001720 vestibular Effects 0.000 description 1
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
- B60R16/00—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for
- B60R16/02—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for electric constitutive elements
- B60R16/037—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for electric constitutive elements for occupant comfort, e.g. for automatic adjustment of appliances according to personal settings, e.g. seats, mirrors, steering wheel
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60N—SEATS SPECIALLY ADAPTED FOR VEHICLES; VEHICLE PASSENGER ACCOMMODATION NOT OTHERWISE PROVIDED FOR
- B60N2/00—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles
- B60N2/02—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles the seat or part thereof being movable, e.g. adjustable
- B60N2/0224—Non-manual adjustments, e.g. with electrical operation
- B60N2/0244—Non-manual adjustments, e.g. with electrical operation with logic circuits
- B60N2/0278—Non-manual adjustments, e.g. with electrical operation with logic circuits using sensors external to the seat for measurements in relation to the seat adjustment, e.g. for identifying the presence of obstacles or the appropriateness of the occupants position
- B60N2/0279—Non-manual adjustments, e.g. with electrical operation with logic circuits using sensors external to the seat for measurements in relation to the seat adjustment, e.g. for identifying the presence of obstacles or the appropriateness of the occupants position for detecting objects outside the vehicle, e.g. for user identification
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
- B60W40/06—Road conditions
Definitions
- the invention relates to a method for automatically adjusting a seat position in a vehicle (in particular in a motor vehicle and also in particular in a passenger vehicle or a truck) in order to avoid travel sickness.
- the invention also relates to an arrangement for providing control signals for the automatic adjustment of a seat position in a vehicle (according to any of the above types) in order to avoid travel sickness.
- Travel sickness which can also be referred to as motion sickness or kinetosis, typically occurs in vehicle occupants as a result of a sensory conflict between the visual and vestibular systems of the vehicle occupant.
- a sensory conflict can occur when the person's body is exposed to movements of the vehicle, whereas, for example, the visual system perceives no or alternative movements. This can be the case, for example, when the visual system is not focused on the environment, for example due to not looking out of the vehicle windows, but instead on other objects, such as text, a display device or a handheld device (e.g. a smartphone ).
- An independent seat system for a motor vehicle is known from EP 2 540560 B1, which, on the basis of a currently recognized trajectory, adjusts a seat inclination angle to reduce a centrifugal force acting on an occupant.
- DE 102014221 337 A1 teaches the collection of data to determine whether a travel sickness limit has been exceeded, it being possible to adjust a vehicle component, such as a vehicle seat, when this limit is exceeded. It has been shown that such approaches cannot always avoid the occurrence of travel sickness to the desired extent.
- One object of the present invention is therefore to improve the avoidance of travel sickness in vehicles.
- the proposed solution is initially characterized in that road information relating to unevenness in the road can be taken into account. Furthermore, not only are real-time states of the motor vehicle recorded and taken into account (but this is at least partially also possible), but vehicle states are at least partially determined in advance. More precisely, a trajectory of the vehicle is predicted so that vehicle states associated therewith can also be predicted accordingly. It can therefore be determined in advance which vehicle states will be present and then in good time the initiation of countermeasures and, more precisely, the adjustment of a seat position can be started. This ensures that countermeasures to avoid travel sickness are not subject to the above-mentioned latency chain, or at least only to a lesser extent.
- a countermeasure can be initiated immediately or have been initiated in advance in good time.
- the invention proposes the automatic (ie driver-autonomous and in particular by means of at least one actuator, for example at least one electric motor) adjusting the seat position of a vehicle occupant.
- at least one actuator for example at least one electric motor
- this can take place in that a vehicle seat as such is rotated, tilted, raised, lowered or displaced.
- the vehicle seat can stand still and, for example, air cushions in the seat can be inflated or made smaller.
- Forecasting (e.g. computationally and / or data-based) a trajectory of the motor vehicle
- the lane information can be recorded with a sensor explained below and then transmitted, for example, to an arrangement and / or a control device of the type explained below.
- the road information can describe a height profile or can be derived from such a profile.
- the height profile can describe height values of a roadway or a roadway surface, e.g. in comparison to a mean value and / or a plane assumed as the base plane.
- the trajectory can describe a movement path of the vehicle.
- the prognosis can be carried out on the basis of variables which describe the previous trajectory of the vehicle and / or a current vehicle state.
- the forecasting can be carried out on the basis of an extrapolation of any state variables mentioned herein or also vehicle variables in general.
- a model-based forecast explained below can be carried out, in particular by means of a machine learning model.
- the seat position can be adjusted automatically to the extent that no specific driver actuations are required for this (ie the adjustment can be carried out autonomously by the driver).
- a degree of adaptation, but also the degree of freedom with respect to which the seat position is adapted, can be determined (automatically) as a function of the lane information received and the predicted trajectory.
- the procedure described is advantageous in that the seating position is at least partially adjusted beforehand.
- the inventors have also recognized that a significant influence on travel sickness can be traced back to uneven road surfaces. According to the invention, this is taken into account in the form of the lane information so that an effective suppression of travel nausea and / or at least a delay in the occurrence of travel nausea can be achieved.
- the prediction of the trajectory of the motor vehicle can generally take place by means of a computer-aided calculation process.
- the lane information can be received via a digital communication connection, for example for connection to a vehicle bus.
- Any computer functions or computer properties described herein can be provided by an arrangement according to the invention and in particular any control device of this arrangement.
- At least one driving dynamics variable (for example of the vehicle) is forecast (in particular by computer-aided calculation and e.g. by extrapolation or model calculation) and the seat position is adjusted depending on this driving dynamics variable.
- the driving dynamics variable can describe body movements of the vehicle, for example changes in a pitch angle, a roll angle, a yaw angle and / or changes in the position of a vehicle's center of gravity (in particular lifting movements thereof).
- the driving dynamics variables can be converted into changes of at least one comparable angle of the vehicle seat or changes in the position of the center of gravity of the vehicle seat, for example if the coordinates of the seat within the vehicle are known.
- driving dynamics variables of the seat are calculated directly.
- a vehicle dynamics model can be used to determine the driving dynamics variable, as is already used in the prior art. Examples include a single-track model, a two-track model, a half-vehicle model, a full-vehicle model, or a combination of these models.
- the vehicle dynamics model can use the recorded or determined lane information and also receive further information, such as a current position of the vehicle, the predicted trajectory or any control specifications of the driver.
- vehicle-specific data that can be taken into account are, for example, weight, weight distribution, wheelbase, mass moments of inertia or a center of gravity.
- the driving dynamics model can take into account design data of the vehicle, in particular a spring and / or damper characteristic of the chassis and properties of other chassis components. Examples include the buffer stop of the damper and the translation required by installing the spring and damper at an angle.
- the relationships shown in the vehicle dynamics model are generally mathematical in nature and / or describe the translational and rotational degrees of freedom of the vehicle body.
- the vehicle body and / or all of the (spatially) comprised components that are carried or supported by the spring and damper system of the vehicle and that are above the wheels or the chassis and / or the corresponding spring and suspension system can be counted as part of the vehicle body Damper system are positioned.
- the vehicle interior can be assigned to the vehicle body.
- the vehicle dynamics model can be used to determine longitudinal, transverse and / or vertical dynamics of the vehicle or driving dynamics variables that describe such dynamics can be determined.
- the determined driving dynamics variable can be used to determine a degree of adjustment of the seat position and / or the degree of freedom that is to be adjusted.
- correction values can be determined in order to compensate for the vehicle dynamics variable and in particular its effect on a vehicle occupant. These correction values can be used to change the sitting position.
- it can be provided that when the driving dynamics variable relates to or results from a change in the above-mentioned angle values or center of gravity, correction values are determined which have the same or at least comparable (change) amount but an opposite sign exhibit.
- the adjustment of the seat position can therefore generally take place in the opposite direction to the determined changes in the driving dynamics variable (s) of the vehicle.
- correction values for compensating for vehicle movements are determined by adapting the seat position, and based on this, the seat position is then automatically adapted.
- the arrangement according to the invention can comprise a computing unit for calculating corresponding correction values.
- movements of the vehicle can be calculated in particular in the form of the explained driving dynamics variables and the correction values can be selected in such a way that these driving dynamics variables are at least partially compensated by adjusting the seat position (in particular by moving in opposite directions and / or changing the seat position in opposite directions).
- a further development provides that a time difference by which a prognosis of the trajectory (or, in other words, the prognosis of the trajectory) and / or the movement quantity leads a current point in time, is less than 1 second or less than 0.5 seconds.
- the time difference can also be less than 300 milliseconds. It has been shown that such a period of time can be sufficient to determine the necessary adjustments to the seat position within this time difference (e.g. in the form of the correction values explained above) and then to implement them using an actuator.
- a temporal and / or spatial detection area or a detection scope can be limited by the quantities and information described herein. For example, it can be sufficient to determine lane information for lane sections that are only so far away or ahead of them that they can be reached within the mentioned time difference. This distinguishes the present solution from solutions for autonomous driving, in which environmental areas that are significantly further ahead must be recorded and / or forecasts must be directed significantly further into the future in order to achieve sufficient driving safety. Since the longer the forecast period or the time difference increases, so does the uncertainty as to whether events occurring in the meantime endanger the forecast, the comparatively short time difference proposed according to the invention (or
- the seat position is adjusted by adjusting the vehicle seat by an actuator.
- the actuator can be at least one electric motor.
- a specially assigned electric motor can be provided for each degree of freedom to be adjusted.
- An actuator can be positioned below the seat and / or move a seat surface of the seat accordingly.
- actuators within a seat upholstery that raise, lower or rotate a seat surface and / or backrest surface in such a way (e.g. by inflating air cushions or the like) that a driver sitting on it is moved in an analogous manner as if the entire seat The seat would be twisted and / or lifted. Both of these named variants can be used within the scope of this invention to adapt the seat position of the vehicle occupant.
- a further development provides that at least one of the following degrees of freedom of the vehicle seat can be adjusted: a pitch angle; a roll angle and / or a center of gravity lift.
- a pitch angle a roll angle and / or a center of gravity lift.
- a yaw angle it is also possible to adjust a yaw angle. It has been shown, however, that this has comparatively little effect on the occurrence of travel sickness or, with the exception of any emergency situations, generally cannot be subject to any significant changes from the driver's point of view.
- a change in the pitch angle has proven to be more relevant, but this can be specifically detected by taking into account the uneven road information according to the invention.
- the trajectory is predicted on the basis of at least one of the following variables:
- current position information for example in the form of GPS coordinates or differential GPS coordinates
- the trajectory can be predicted in the form of current or expected steering specifications of the driver (e.g. signaled by the mentioned steering torque or the steering angle).
- the wheel speed and / or the yaw rate can also be recorded as a vehicle reaction. In principle, however, it is sufficient to determine only the driver's control specifications and not necessarily also the vehicle reaction to determine the trajectory, for example in the form of the steering torque, a steering angle or a predetermined driving speed.
- the trajectory is predicted by means of a model predictive control or by means of a machine learning model.
- the machine learning model can be a neural network and / or a rule-based model. This can predict at least one output variable based on input variables.
- the input variables can be any of the variables explained above, on the basis of which the trajectory can be predicted.
- the output variable can then be output as the trajectory (which can generally define a description of the vehicle location over time or a change in this location over time), in particular taking into account a desired forecast duration or a previously explained time difference in the forecast. It can therefore be specified which location the vehicle will occupy at a point in time that is spaced apart from a current point in time by the corresponding time difference.
- a model-predictive control can be understood to mean any approach and any component and / or function used for this purpose, with which a current state can be predicted on the basis of current state variables.
- a Kalman filter can be used (ie the trajectory can generally be predicted by means of a Kalman filter).
- a prognosis using, for example, linear extrapolation is alternatively possible.
- the comparatively short time difference of the forecast mentioned above is advantageous, since any inaccuracies in the extrapolation can then be accepted or have less of an effect on the forecast quality. Taking correspondingly short forecast time differences as a basis can therefore enable a simplified forecast, which can reduce the expenditure on sensors, signal processing and / or the computing power of the control devices used.
- the lane information is determined from data from at least one sensor of the vehicle or from map data.
- the map data can describe a height profile of the roadway. They can be stored in a memory device of the vehicle or, for example, can be read out from an external memory device (for example a so-called cloud).
- a sensor of the vehicle can be a camera, a lidar sensor, a radar sensor, a laser scanner, a suspension level sensor or an ultrasonic sensor.
- the invention also relates to an arrangement for providing control signals (or also adjustment signals) for the automatic adjustment of a seat position in a vehicle in order to avoid travel sickness with:
- One e.g. digital and / or signal-receiving input for receiving road information representing unevenness in the road ahead of the vehicle;
- a control signal generating unit for generating control signals as a function of the lane information and the predicted trajectory, with the control signals being able to control at least one actuator for automatically adjusting the seat position of a vehicle occupant sitting on the vehicle seat.
- the arrangement can comprise at least one control device or be designed as such.
- the control device can comprise at least one microprocessor which is set up to execute program instructions. By executing these program instructions, any function described in connection with the arrangement can be provided, but also any method measure and / or any method step explained herein.
- the arrangement can also comprise a storage device for preferably digital information.
- the program instructions and / or the aforementioned map data can be stored on this memory device.
- the possible control device can also include the input, the trajectory unit and / or the control signal generation unit.
- the trajectory unit and the control signal generating unit can be used as software applications or software components be designed, which are carried out by the control unit.
- the arrangement can also include at least one sensor for detecting the lane information.
- the arrangement can also include the actuator and / or the vehicle seat. This can be the case in particular if the arrangement is installed in a vehicle and, for example, any control device in the arrangement is connected to this actuator via a signal line (e.g. by means of a vehicle bus).
- the control signals for controlling the actuator can have a predetermined data format and / or other predetermined signal properties so that the actuator can be controlled accordingly.
- the control signals can include information on target angle values that the actuator is to set, or generally target degrees of freedom values that are to be achieved with the actuator, or generally information on movements of the actuator so that the desired changes are implemented. This information can also be or contain (electrical) required operating parameters of the actuator.
- the arrangement can comprise any further feature, any further unit and any further component in order to provide all of the functions, operating states, interactions, method steps or even effects described herein.
- the arrangement can comprise any further feature in order to carry out a method in accordance with all aspects described herein.
- Fig. 1 shows a vehicle comprising an arrangement according to a
- Fig. 2 shows a flow chart of a method according to the invention, as it is with the
- the arrangement 1 shows a vehicle 100 which comprises an arrangement 1 according to an exemplary embodiment of the invention.
- the arrangement 1 comprises a control device 10 with at least one processor device (not shown separately) and a digital storage device.
- Program instructions are stored in the memory device, which the processor device can perform.
- software applications are stored in the memory device with which a trajectory unit 21 and / or control signal generating unit 23 described herein is provided.
- the vehicle 100 includes a sensor 12, for example in the form of a camera or an ultrasonic sensor. Further examples of possible sensors were given in the general part of the description.
- the sensor 12 detects a region of the roadway 14 lying ahead in the direction of travel F of the vehicle 100 and, more precisely, from a roadway surface.
- the sensor 12 detects road information describing unevenness in the road 14. This can be done, for example, in such a way that the lane information is a height profile of the lane 14 detected by the sensor 12.
- This information is made available to control device 10 via an input 13 or is received via this input 13. This can take place, for example, via a vehicle bus 104, so that the input 13 can also be a connection to such a vehicle bus 104.
- the lane information can be determined from map data or transmitted as such.
- a cloud server 18 can be accessed, e.g. via a cellular connection shown in dashed lines.
- position information such as that from a position determination unit 16, which can include a GPS sensor, is taken into account.
- the control device 10 can therefore access both the position determination unit 16 and the cloud server 18 at least indirectly in order to read out the lane information relevant to a current location or lane information ahead of the current location.
- control device 10 also includes executable software applications that form a trajectory unit 21 and a control signal generation unit 23.
- signals from sensors connected to a steering handle 102 or the vehicle wheels 103 can be fed into the schematically indicated vehicle bus 104, which the control unit 10 can access.
- the control unit 10 can thus have any variable of the type explained above that can be used to predict a trajectory of the vehicle 100. Sensors to be provided for these variables, such as a yaw rate sensor, a wheel speed sensor, a steering angle or steering torque sensor, are not shown.
- a vehicle seat 105 is shown by way of example in FIG. 1, on which a vehicle occupant (not shown separately) sits while driving.
- An actuator 108 which is connected to the control unit 10 via a control signal line, is located below the vehicle seat.
- the actuator 108 is an electric motor that can be controlled by the control device 10 by means of control signals.
- the actuator 108 is set up to adapt (ie to change or adjust) at least one degree of freedom of the seat 105 in accordance with the control signals received.
- a plurality of actuators 108 for example one for each degree of freedom to be adjusted, can also be provided.
- the degree of freedom can be a pitch angle, so that the vehicle seat 105 can be rotated about a schematically indicated axis A which is perpendicular to the plane of the sheet.
- FIG. 2 shows a schematic process sequence as can be carried out with the arrangement from FIG. 1.
- step S1 road information relating to unevenness of road 14 lying ahead is recorded (preferably continuously).
- step S2 which can also be carried out before and / or in a temporally overlapping manner with step S1, a trajectory of the vehicle 100 with trajectory unit 21 from FIG. 1 is forecast.
- quantities currently obtained for this purpose e.g. quantities obtained via the vehicle bus 104 from FIG. 1 can be extrapolated, to be precise as a function of a predetermined forecast period or time difference at a current point in time.
- a schematically indicated machine learning model 200 that can be executed with control device 10 from FIG. 1 or a Kalman filter 202 that can also be executed by control device 10 can be used, which can also receive the corresponding variables and predict the trajectory based thereon. It is also possible to combine several of these approaches with each other and then, for example, to check a trajectory that has been determined for plausibility or, for example, to calculate an average value.
- a step S3 the lane information from step S1 and the predicted trajectory from step S2 are used in order to feed them into a driving dynamics model 204.
- the driving dynamics model 204 can be executed by the control device 10 and / or stored in a memory device not shown separately, which the control device accesses or which is included in the control device 10.
- the vehicle dynamics model 204 can describe relationships between state and / or operating variables and dynamic variables of the vehicle resulting therefrom. By doing In particular, relationships between the road information (e.g. bumps in road 14 and / or a general height profile of road 14) and the predicted trajectory and the resulting driving dynamics variables of vehicle 100 can be described or defined by driving dynamics model 204.
- the trajectory can contain predicted location information or coordinates, and the lane information can contain unevenness or height values of the roadway 14 associated with these coordinates or location information. It can therefore be determined whether the vehicle 100 is traveling over unevenness and how these are pronounced. It can also be determined in which driving dynamics variables this results. Both of these tasks can be taken over by the driving dynamics model 204.
- a step S4 the control unit 10 then again determines which adjustments to the seat position and, more precisely, the degree of freedom of the seat 105's pitch angle are required in order to compensate for the determined driving dynamics changes or driving dynamics variables of the vehicle 100 in such a way that the risk of travel nausea is reduced becomes.
- Threshold criteria can be defined for this, e.g. to only intervene in the event of significant changes or values.
- a pitch angle of the vehicle and in particular its predicted change or rate of change at a predetermined point in time can be determined as a driving dynamics variable merely as an example. How the pitch angle of the vehicle seat 105 must be changed (at the same point in time) in order to compensate for this pitch angle change of the vehicle 100 can then be determined as a correction value. For example, the same amount of the vehicle pitch angle can be selected, but with an opposite sign.
- the control device 10 can then generate corresponding control signals with which the actuator 108 can be activated in order to implement a corresponding change in the pitch angle of the vehicle seat 105.
- the corresponding adjustment of the vehicle seat pitch angle can take place at the point in time at which the actual change in the pitch angle of the vehicle 100 takes place.
- the change in the seat position is carried out in a step S5 accomplished. In the example shown, this position of the vehicle occupant is changed in that the entire vehicle seat 105 is tilted in the manner described.
- the lane information which is also determined in a forward-looking manner, is considered, as is the predicted trajectory. If it is determined at certain points in time that one or more driving dynamics variables (e.g. a pitch angle) exceed a predetermined limit and in particular that changes thereof are inadmissibly high, the seat position can be adjusted in the manner described.
- one or more driving dynamics variables e.g. a pitch angle
- the time difference or also the forecast period is selected in such a way that latencies and / or actuation periods of the actuator 108 turn out to be such that timely adjustments are possible. For example, it can be determined experimentally or computationally that a time difference in the forecast of 500 milliseconds, for example, results in the required adjustments to the seating position being always implemented approximately when the predicted event (which is 500 milliseconds in the future) or when the predicted one Change in driving dynamics occur.
Landscapes
- Engineering & Computer Science (AREA)
- Mechanical Engineering (AREA)
- Transportation (AREA)
- Aviation & Aerospace Engineering (AREA)
- Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Mathematical Physics (AREA)
- Seats For Vehicles (AREA)
Abstract
Description
Claims
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| DE102019212082.2A DE102019212082A1 (de) | 2019-08-13 | 2019-08-13 | Automatisches Anpassen einer Fahrzeug-Sitzposition zum Vermeiden von Reiseübelkeit |
| PCT/EP2020/071143 WO2021028206A1 (de) | 2019-08-13 | 2020-07-27 | Automatisches anpassen einer fahrzeug-sitzposition zum vermeiden von reiseübelkeit |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| EP4013643A1 true EP4013643A1 (de) | 2022-06-22 |
Family
ID=71833347
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| EP20746640.0A Withdrawn EP4013643A1 (de) | 2019-08-13 | 2020-07-27 | Automatisches anpassen einer fahrzeug-sitzposition zum vermeiden von reiseübelkeit |
Country Status (3)
| Country | Link |
|---|---|
| EP (1) | EP4013643A1 (de) |
| DE (1) | DE102019212082A1 (de) |
| WO (1) | WO2021028206A1 (de) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115092017B (zh) * | 2022-06-27 | 2023-08-25 | 重庆长安汽车股份有限公司 | 一种驾驶座椅自动调节系统、方法及存储介质 |
| DE102023000479B3 (de) | 2023-02-13 | 2024-06-20 | Mercedes-Benz Group AG | Verfahren zur Verringerung oder Vermeidung von Kinetose |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102010046205A1 (de) * | 2010-09-21 | 2012-03-22 | Audi Ag | Verfahren zur Ansteuerung einer zur Verkippung eines Sitzes eines Kraftfahrzeugs ausgebildeten Aktorik und Kraftfahrzeug |
| TWI436911B (zh) | 2011-06-29 | 2014-05-11 | Univ Nat Taiwan Science Tech | 汽車全自主座椅系統及其執行方法 |
| US9145129B2 (en) | 2013-10-24 | 2015-09-29 | Ford Global Technologies, Llc | Vehicle occupant comfort |
| KR102484148B1 (ko) * | 2015-06-03 | 2023-01-03 | 클리어모션, 아이엔씨. | 차체 모션 및 승객 경험을 제어하기 위한 방법 및 시스템 |
-
2019
- 2019-08-13 DE DE102019212082.2A patent/DE102019212082A1/de not_active Withdrawn
-
2020
- 2020-07-27 EP EP20746640.0A patent/EP4013643A1/de not_active Withdrawn
- 2020-07-27 WO PCT/EP2020/071143 patent/WO2021028206A1/de not_active Ceased
Also Published As
| Publication number | Publication date |
|---|---|
| DE102019212082A1 (de) | 2021-02-18 |
| WO2021028206A1 (de) | 2021-02-18 |
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