Apparatus for estimating motion of vehicle occupant and method therefor
An apparatus for estimating a motion of a vehicle occupant, and a method therefor, can store motion estimating models of a vehicle occupant, collect behavior data of a vehicle, determine a traveling mode of the vehicle based on a longitudinal acceleration among the behavior data of the vehicle, and estimate a motion of the vehicle occupant using at least one of the motion estimating models corresponding to the traveling mode of the vehicle. The motion estimating models can include a first model corresponding to a dynamic mode of the vehicle and a second model corresponding to a steady state mode of the vehicle.
1 . An apparatus comprising:
one or more processors; and
a non-transitory storage medium storing a plurality of motion estimating models corresponding to different traveling modes and computer-readable instructions that, when executed by the one or more processors, enable the one or more processors to collect behavior data of a vehicle, determine a traveling mode of the vehicle based on a longitudinal acceleration among the behavior data of the vehicle, select a first motion estimating model corresponding to the traveling mode of the vehicle from among the plurality of motion estimating models, and estimate a motion of a vehicle occupant using the first motion estimating model corresponding to the traveling mode of the vehicle.
2 . The apparatus of claim 1 , wherein at least one of the plurality of motion estimating models estimates the motion of the vehicle occupant corresponding to the behavior data of the vehicle.
3 . The apparatus of claim 1 , wherein the plurality of motion estimating models include the first motion estimating model corresponding to a dynamic mode of the vehicle and a second motion estimating model corresponding to a steady state mode of the vehicle.
4 . The apparatus of claim 3 , wherein the instructions further enable the one or more processors to estimate an acceleration of a head of the vehicle occupant corresponding to the behavior data of the vehicle using the first motion estimating model, based on a determination that the longitudinal acceleration deviates from a first threshold range, and
wherein the instructions further enable the one or more processors to estimate an acceleration of a head of the vehicle occupant corresponding to the behavior data of the vehicle using the second motion estimating model, based on a determination that the longitudinal acceleration is within the first threshold range and is within a second threshold range.
5 . The apparatus of claim 4 , wherein the instructions further enable the one or more processors to determine that the acceleration of the head of the vehicle occupant is a value between a first acceleration of the head of the vehicle occupant estimated using the first motion estimating model and a second acceleration of the head of the vehicle occupant estimated using the second motion estimating model, based on a determination that the longitudinal acceleration is within the first threshold range and deviates from the second threshold range.
6 . The apparatus of claim 3 , wherein the instructions further enable the one or more processors to collect, as the behavior data of the vehicle, one of or any combination of three-axis accelerations, three-axis speeds, a roll angle, a roll angle rate, a pitch angle, and a pitch angle rate.
7 . The apparatus of claim 6 , wherein the instructions further enable the one or more processors to remove noise from the behavior data of the vehicle.
8 . The apparatus of claim 7 , wherein the instructions further enable the one or more processors to normalize the behavior data of the vehicle from which the noise is removed.
9 . The apparatus of claim 1 , wherein the instructions further enable the one or more processors to predict motion sickness of the vehicle occupant based on the motion of the vehicle occupant.
10 . A method comprising:
collecting behavior data of a vehicle;
determining a traveling mode of the vehicle based on a longitudinal acceleration among the behavior data of the vehicle;
selecting a first motion estimating model corresponding to the traveling mode of the vehicle from among a plurality of motion estimating models that each correspond to a different traveling mode; and
estimating a motion of a vehicle occupant using the first motion estimating model corresponding to the traveling mode of the vehicle.
11 . The method of claim 10 , wherein at least one of the plurality of motion estimating models estimates the motion of the vehicle occupant corresponding to the behavior data of the vehicle.
12 . The method of claim 10 , wherein the plurality of motion estimating models comprise the first motion estimating model corresponding to a dynamic mode of the vehicle, and a second motion estimating model corresponding to a steady state mode of the vehicle.
13 . The method of claim 12 , wherein the estimating of the motion of the vehicle occupant includes:
estimating an acceleration of a head of the vehicle occupant corresponding to the behavior data of the vehicle using the first motion estimating model, based on a determination that the longitudinal acceleration deviates from a first threshold range; and
estimating an acceleration of the head of the vehicle occupant corresponding to the behavior data of the vehicle using the second motion estimating model, based on a determination that the longitudinal acceleration is within the first threshold range and is within a second threshold range.
14 . The method of claim 13 , wherein the estimating of the motion of the vehicle occupant further includes determining that the acceleration of the head of the vehicle occupant is a value between a first acceleration of the head of the vehicle occupant estimated using the first motion estimating model and a second acceleration of the head of the vehicle occupant estimated using the second motion estimating model, based on a determination that the longitudinal acceleration is within the first threshold range and deviates from the second threshold range.
15 . The method of claim 12 , wherein the collecting of the behavior data of the vehicle includes collecting as the behavior data of the vehicle one of or any combination of three-axis accelerations, three-axis speeds, a roll angle, a roll angle rate, a pitch angle, and a pitch angle rate.
16 . The method of claim 15 , wherein the collecting of the behavior data of the vehicle further includes removing noise from the behavior data of the vehicle.
17 . The method of claim 16 , wherein the collecting of the behavior data of the vehicle further includes normalizing the behavior data of the vehicle from which the noise is removed.
18 . The method of claim 10 , further comprising predicting motion sickness of the vehicle occupant based on the motion of the vehicle occupant.
19 . The method of claim 10 , wherein:
the collecting of the behavior data of the vehicle further includes collecting at least one of three-axis accelerations, three-axis speeds, a roll angle, a roll angle rate, a pitch angle, and a pitch angle rate of the vehicle; and
the method further comprises removing noise from the collected behavior data of the vehicle and normalizing the behavior data of the vehicle from which the noise is removed before determining the traveling mode of the vehicle.
20 . A method comprising:
collecting behavior data of a vehicle, the behavior data including at least a longitudinal acceleration of the vehicle;
determining a traveling mode of the vehicle based on whether the longitudinal acceleration deviates from a first threshold range, wherein the traveling mode is determined to be a dynamic mode when the longitudinal acceleration deviates from the first threshold range and is determined to be a steady state mode when the longitudinal acceleration is within the first threshold range;
selecting a first motion estimating model corresponding to the determined traveling mode of the vehicle from among a plurality of motion estimating models, wherein the plurality of motion estimating models includes a first model corresponding to the dynamic mode and a second model corresponding to the steady state mode; and
estimating a motion of a head of a vehicle occupant using the selected first motion estimating model, wherein the estimating includes determining three-axis accelerations of the head of the vehicle occupant based on the behavior data of the vehicle.