AVOIDING OR ALLEVIATING TRAVEL SICKNESS IN A VEHICLE

Abstract

The disclosure relates to a method and a device for avoiding or alleviating travel sickness in a vehicle, wherein the vehicle exhibits an automated driving mode in which the vehicle moves along at least partly in automated manner. A method according to the disclosure comprises the following steps: estimating at least one parameter that is characteristic of the probability of the occurrence of travel sickness in an occupant of the vehicle, establishing, on the basis of this parameter, at least one measure that is suitable for the alleviation or avoidance of travel sickness in the occupant of the vehicle, and communicating an item of information relating to this at least one measure to the driver.

Claims

1-11. (canceled)

12. A method, comprising: operating a vehicle in an automated driving mode in which the vehicle moves at least partly in automated manner; estimating at least one parameter that is characteristic of a probability of an occurrence of travel sickness in an occupant of the vehicle; establishing, on the basis of the at least one parameter, at least one measure to alleviate travel sickness in the occupant of the vehicle; and communicating an item of information relating to the at least one measure to the occupant.

13. The method of claim 12, wherein establishing the at least one measure is undertaken upon determining that the parameter exceeds a predetermined threshold value.

14. The method of claim 12, wherein the at least one measure includes one of terminating the automated driving mode and avoiding a change-over to the automated driving mode.

15. The method of one of claims 12, wherein the at least one measure further includes at least one of the following: changing or terminating an activity currently being carried out by the occupant, changing a seat position of the occupant, and changing the setting of at least one window covering of the vehicle.

16. The method of claim 12, wherein estimating the at least one parameter that is characteristic of the probability of the occurrence of travel sickness is carried out based on data relating to the occupant.

17. The method of claim 16, wherein the items of information or data relating to the driver comprise one or more of a type of an activity currently being carried out by the occupant, a duration of a previously undertaken instance of the activity currently being carried out by the occupant, a duration of a previously undertaken journey of the vehicle in the automated driving mode, and health data pertaining to the occupant.

18. The method of claim 12, wherein estimating the at least one parameter that is characteristic of the probability of the occurrence of travel sickness is carried out based on one or more of data relating to a current environment of the vehicle and data relating to an expected future environment of the vehicle.

19. The method of claim 18, wherein the data relating to the current environment of the vehicle and to the expected future environment of the vehicle relate to one or more of a curviness of a route being driven, existing speed limits and changes of altitude of the route being driven.

20. The method of claim 12, wherein estimating the at least one parameter that is characteristic of the probability of the occurrence of travel sickness is carried out based on data relating to an operating condition of the vehicle.

21. The method of claim 20, wherein the data relating to the operating condition of the vehicle relate to one or more of vehicle acceleration data and an excitation of the vehicle by the roadway surface.

22. A device for avoiding or alleviating travel sickness in a vehicle, comprising a computer programmed to: operate a vehicle in an automated driving mode in which the vehicle moves at least partly in automated manner; estimate at least one parameter that is characteristic of a probability of an occurrence of travel sickness in an occupant of the vehicle; establish, on the basis of the at least one parameter, at least one measure to alleviate travel sickness in the occupant of the vehicle; and communicate an item of information relating to the at least one measure to the occupant.

23. The device of claim 22, the computer further programmed to determine that the parameter exceeds a predetermined threshold value, wherein establishing the at least one measure is undertaken upon determining that the parameter exceeds the predetermined threshold value.

24. The device of claim 22, wherein the at least one measure includes one of terminating the automated driving mode and avoiding a change-over to the automated driving mode.

25. The device of one of claims 22, wherein the at least one measure further includes at least one of the following: changing or terminating an activity currently being carried out by the occupant, changing a seat position of the occupant, and changing the setting of at least one window covering of the vehicle.

26. The device of claim 22, the computer further programmed to estimate the at least one parameter that is characteristic of the probability of the occurrence of travel sickness based on data relating to the occupant.

27. The device of claim 26, wherein the items of information or data relating to the driver comprise one or more of a type of an activity currently being carried out by the occupant, a duration of a previously undertaken instance of the activity currently being carried out by the occupant, a duration of a previously undertaken journey of the vehicle in the automated driving mode, and health data pertaining to the occupant.

28. The device of claim 22, the computer further programmed to estimate the at least one parameter that is characteristic of the probability of the occurrence of travel sickness based on one or more of data relating to a current environment of the vehicle and data relating to an expected future environment of the vehicle.

29. The device of claim 28, wherein the data relating to the current environment of the vehicle and to the expected future environment of the vehicle relate to one or more of a curviness of a route being driven, existing speed limits and changes of altitude of the route being driven.

30. The device of claim 22, the computer further programmed to estimate the at least one parameter that is characteristic of the probability of the occurrence of travel sickness based on data relating to an operating condition of the vehicle.

31. The device of claim 30, wherein the data relating to the operating condition of the vehicle relate to one or more of vehicle acceleration data and an excitation of the vehicle by the roadway surface.

Description

[0027] The disclosure will be elucidated in more detail in the following on the basis of an exemplary embodiment with reference to the appended illustration.

[0028] The single FIG. 1 shows a diagram for elucidating the possible sequence of a method according to the disclosure.

[0029] According to FIG. 1, it is assumed that a driver or occupant, denoted by “10”, of the vehicle sets an automated driving mode in his/her vehicle for (at least partial) automated driving and activates a prediction unit for predicting a probability of travel sickness (that is to say, the probability of the occurrence of travel sickness), which is denoted by “30”, or that this prediction unit 30 has already been activated in advance as standard.

[0030] This prediction of the probability of travel sickness is undertaken according to FIG. 1 on the basis of a function 40, with reference to which the probability of nausea can be ascertained on the basis of a large number of data items. In the exemplary embodiment shown in FIG. 1, these data include (but are not limited to) map data (for example curviness, speed restrictions, changes of altitude), driver-activity data and driver-state data (for example, type of driver activity, last duration of the activity, last duration of automated driving, seat configuration, health data, previous history etc.) as well as vehicle data (acceleration data, excitation of the vehicle by roadway surface etc.).

[0031] On the basis of the aforementioned data, according to FIG. 1 an appropriate parameter is ascertained on the basis of the estimate of the probability of nausea. Then, in a step 50, the query is undertaken as to whether this parameter exceeds a predetermined threshold value (which, for instance, was ascertained on the basis of practical tests or field trials). If this is the case, according to step 20 a warning (for example, a visual or acoustic warning), which may be associated with appropriately suitable suggestions, is given to the driver. These suggestions may involve, in merely exemplary manner, the transition to the manual driving mode or, where appropriate, the retention thereof, refraining from certain activities, changing certain activities, the change of the seat position or the change of a visual configuration (for example, the opening or closing of window blinds).