KR20220097756A - Driving method or road designing method for preventing dizziness for passengers - Google Patents

Abstract

The present invention relates to a driving method or a road designing method of a boarding apparatus capable of stable driving to prevent motion sickness. An objective of the present invention is to reduce motion sickness of a passenger and shaking of an object in a vehicle by designing a trajectory of the vehicle or a track of a road which appropriately gives a driving route and a speed of autonomous driving. According to the present invention, dynamic characteristics of the vehicle are analyzed, and main factors causing motion sickness are quantified and then expressed as a cost function, a reward function, etc. Therefore, learning and optimization of dynamic programming, alternative computing, and so on, or the trajectory of the vehicle or the track of the road are derived.

Description

Driving method and road design method of a boarding device that can prevent motion sickness and ensure stable driving { Driving method or road designing method for preventing dizziness for passengers }

The development of artificial intelligence technology is positioned as a new field in unmanned automobile technology. In fact, in the self-driving vehicle learning site that is conducted as a web service, various factors can be learned as scores by using the distance from the midline of the vehicle, the direction angle of the vehicle, and the steering angle.

Drivers feel less motion sickness than other passengers. The main cause of motion sickness is that the difference between visual information and vestibular organ information is felt. Since the driver controls the physical characteristics of the vehicle, visual information and information of the vestibular system can be predicted in advance. In this way, the information gap can be reduced and motion sickness is less felt. If the passenger learns more about the driver's driving habits, the passenger can also reduce motion sickness.

If autonomous driving technology is installed, there will be one driving habit to learn, so autonomous driving itself can help prevent motion sickness. In addition, it is possible to learn driving habits optimized for motion sickness prevention. Reportedly, blind people also experience motion sickness. This means that without visual information, motion sickness can be sufficiently felt by the action of the vestibular system. Therefore, devices to prevent this are often researched and developed. For example, the Galvanic Vestibular Stimulation device emits negative ions to the vestibular organ and artificially inserts a signal into the vestibular organ to create an illusion in the brain that it is experiencing acceleration. There has also been a study on a device to reduce motion sickness by wearing it on the head and riding in a car. However, when an electric potential is given from the vestibular system unit, not only the brain but also the reflexes react, so that the body can tilt to balance itself or the eyes can automatically rotate. And above all else, you have to buy and wear the device. Returning to the essence of the problem, if driving habits are optimized from the beginning, there will be no need to use other devices, so this technology can be a big breakthrough.

According to one research institute, if you are exposed to different accelerations for more than an hour, you may feel motion sick to adapt to them. That is, the magnitude of the linear acceleration is not important when riding in a relatively instantaneous vehicle. The rate of change of the linear acceleration is important.

The main reason we feel motion sickness is caused by the difference between visual information and balance sensory information. The body stops rotating, but the lymph fluid continues to rotate, resulting in motion sickness due to an error with the visual information. When playing around the elephant's nose, you may feel particularly dizzy when it is finished and stopped.

Electronic device for relieving motion sickness and method for relieving motion sickness using same Application No. 1020180053927

What Causes Spacesickness in Astronauts The ScineceTimes G-Shock Trainer Lesson Plan: What Causes Dizziness? SPACEPORT AMERICA

It is intended to reduce motion sickness of occupants and shaking of objects in the vehicle by designing the trajectory of the vehicle or the trajectory of the road that gives an appropriate driving path and speed for autonomous driving.

When a car enters a curved path from a straight path, the curvature cannot instantaneously enter from infinity to a constant constant. Of course, it will be possible if you stop the model car on a curved ramp (circle in the drawing above), turn the servo, and start again. can That is, there is no perfect trajectory that enters a curved path without stopping.

Assuming that the center of rotation of the model car is on the rear wheel axis, the trajectory drawn by the vehicle is as shown in the figure. In FIG. 4 , when the safety factor is the distance between the vehicle and the lane, it can be said that the vehicle is driven most safely when the distance to both lanes is the same, and it can be seen that this is discontinuous. Therefore, there is no right answer in vehicle driving, and the task of optimization is necessary. Of course, the safety factor or curvature difference (the difference between the current curvature and the curvature of the road) can also be optimized and applied as a compensation function.

By analyzing the dynamic characteristics of the vehicle, the main factors that cause motion sickness are digitized and expressed as a cost function, a reward function, etc. to derive the trajectory or the trajectory of the vehicle that has been optimized for learning and optimization such as dynamic programming and alternative computing.

Autonomous driving is rapidly emerging as a result of the 4th industrial revolution era. In this way, it is possible to reinforce the disadvantages of a situation in which a person is directly driving. The degree of motion sickness varies depending on the driver's habits. These parts can be reinforced using the development of technology. Currently, various attempts have been made to exclude motion sickness itself. Now, by using autonomous driving technology, driving itself can prevent motion sickness.

It will no longer be necessary to take medical drugs or attach medical devices for car sickness. Also, it can be an opportunity to take a positive approach to the car for those who do not ride a car because they hate car sickness.

In addition, it will be possible to maintain a more stable environment for luggage in the vehicle. If the luggage keeps hitting the wall again, falling over, and overturning, there may be inconveniences such as damage.

1 is a view showing a balance organ in the ear of the human body. The vestibular organ is an organ in the body for which our body measures balance. The saccule senses vertical acceleration, the utricle senses horizontal acceleration, and the three semicircular canals: detect rotational movement in three directions.
FIG. 2 is a diagram of a Galvanic Vestibular Stimulator device, which is a device that wears a band on the head and sends an optical illusion signal to the nerve through the band.
3 illustrates a rotation center and curvature of a vehicle. It is a diagram expressing that the turning curvature of the road is discontinuous.
4 illustrates that the vehicle trajectory that minimizes the distance between the vehicle and the lane on the road is discontinuous.
5 is
There are four degrees of freedom (Θ,Δr, ρ, Θs).
Θ : The angle between the road and the model car
Δr : Distance of the optimal trajectory from the center of the model car
ρ: the curvature of the optimal trajectory
s : servo motor angle
To analyze the model difference for control purposes, we can take Θ or Δr or both as input and put Θs as output.
6 is a diagram illustrating characteristics of a driving road and a vehicle.
7 is a view in which the driving road and the vehicle of FIG. 6 are gathered in one place, and is a moment when the rotational center of the vehicle and the rotational center of the road do not coincide.

는 어느 탑승객 위치를 중심으로 잡느냐에 따라 변경할 수 있다. 보조석 혹은 후방석 등 멀미에 특히 취약한 탑승객의 자리를 기준으로 최적화시킬 수 있겠다. 아래와 같이 동역학적 수식으로 표현할 수 있다.Assuming that the vehicle always rotates with respect to the center point, it can be interpreted as polar coordinates. radius r, angle

can be changed depending on which passenger position is centered. It can be optimized based on the seat of passengers who are particularly vulnerable to motion sickness, such as the passenger seat or the rear seat. It can be expressed as a dynamic equation as follows.

, 또는

등의 값이 중요하게 작용하며 이는 우리의 감각기관중 선형적인 방향의 가속에 관련된 기관들이 있기 때문이다. 이값이 크면 멀미가 더많이 날 것이다.

, or

The value of etc. is important because some of our sensory organs are related to acceleration in a linear direction. The higher this value, the more motion sickness will occur.

는 r 과 v 즉 핸들과 v 에 관련된 함수이다.where r is the angle determined by the handle angle,

is a function related to r and v, that is, a handle and v .

The power P is expressed and expanded as follows.

Through this, power P and steering wheel angles can be interpreted as inputs.

The rotating car can be viewed as the sun, and the rotation sensory organs of the passengers in the car can be interpreted as planets and expressed as follows.

Planer p, sun s

We start with the moment of inertia formula.

의 값이 중요하며 이는 우리의 감각기관중 회전방향의 가속에 관련된 기관들이 있기 때문이다. 마찬가지로 이값이 크면 멀미가 더많이 날 것이다.|

The value of is important because some of our sensory organs are involved in the acceleration of the rotational direction. Likewise, the higher this value, the more motion sickness will occur.

,|

등을 사용하여 최적함수 즉, cost function J or reward function R, 등에 사용해 최적화를 시킬 수 있다.these variables;

,|

It can be optimized by using the optimal function, i.e., cost function J or reward function R, etc.

: A

: A

: B

: B

: C

: C

7 control variables

7 control variables

As above, there are 3 equations and 7 control variables, which means that there are possible methods equivalent to the fourth power of infinity in linear algebra.

We propose a model that can be used for self-driving.

If the horizontal axis is Δr as the input and the vertical axis is s as the output, the control model can be drawn as shown below. Note that the origin is ( ρ, (ρ)[ s] ).

형태의 기함수로 표현할 수 있다. 기함수인 이유는 주행이 좌우 대칭해야하기 때문이다. 갈색의 함수는 입력값에 따라 경우의 수로 나눠서 제어하는 함수이다. 삼차함수로 나타낸 이유는 기함수 테일러 급수의 두번 째 항까지만 사용한 것이다.

It can be expressed as an odd function of the form. The reason for the odd function is that the driving must be symmetrical. The brown function is a function that is controlled by dividing the number of cases according to the input value. The reason why it is expressed as a cubic function is that only the second term of the odd Taylor series is used.

If only Δr is received as an input, even if the camera sees the approaching road, it is not possible to respond in advance. As a graph, it looks like the above. To make this possible, a function g(t) that calculates the information on the optimal trajectory of the approaching roadway is required in advance. g(t) must be integrated from 0, which is your position, to a specific distance α.

Suppose that the above delta function is measured. It would be better if the degree of turning the direction deepens with time. To do this, the closer the delta function is to the origin, the greater the weight should be. Therefore, we put the term for α - s.

Final expression:

In the existing method, there are many studies that control the control method using PID. Of course, you can also try adjusting the variables you want to control here, and you can try loading the forecasting algorithm like the block diagram above.

- Optimization of driving

If the responsiveness is too high due to poor optimization, it may deviate from the path even in a simple straight line like the one above. Therefore, it is necessary to optimize these constant values.

Here, learning the constants to be optimized by physically demonstrating them directly consumes a lot of time and effort in every episode. This is a graphic simulation that can speed up the episodes and teach them. After that, if the learned neural network model is input to the model car, the optimized driving algorithm will be available. If there is a problem in learning, k1, k4, k5 can be removed and then optimized one by one, which can be tried with a much simpler dichotomy. In the case of PID control, KP, KI, and KD values can be learned.

- Mapping

을 통해 추적할 수 있다. 따라서 Mapping m = m

으로 표현할 수 있으며 이는 테일러급수 일차미분까지만 표현한 것이다.Looking at the picture on the left, the previous trajectory cannot be known only from the information of the camera itself. If there is no information on whether the previous trajectory was a straight road like a dotted line or a curved road like a solid line, the kinematic control is disrupted due to the uncertainty of the Δr value. To compensate for this, information extracted from the camera can be recorded. The positions of the points recorded in this way should be updated in every state, which is a dynamic analysis.

can be tracked through So Mapping m = m

It can be expressed as , which is expressed only up to the first derivative of the Taylor series.

Of course, as a method necessary for driving, in addition to the above model, a model that determines the output by CNN for camera data can be used.

The vehicle control unit may be attached to the vehicle and sold and distributed.

You can purchase the vehicle control unit and attach it to the vehicle.

By installing a receiver and transmitter in the vehicle and implementing the vehicle control technology over a network, it is possible to send a driving signal to the vehicle.

In composing a roadway, it is possible to optimize and use possible roads with a computer in advance.

으로 표현될 수 있으며 s 는 sun이다.
201 : 탑승장치가 움직이는 방향으로

단위벡터로 표현될 수 있다.
203 : 경로가 가지는 최적궤적의 표현으로 탑승장치와 도로사이의 거리를 최소화 할 수 있는 탑승장치의 궤적으로 원궤도기반 커브길 진입로에서 불연속적인게 특징이다.
204 : 탑승자 혹은 기준자의 반고리관 속 회전체 (otholith 등) 회전으로

로 표현된다. p 는 planar으로서 상기 sun 과 구별된다.100: As a passenger or standard person, it becomes the standard for motion sickness calculation.
101: A vehicle, but not limited to a four-wheel drive vehicle.
200: It is the center of rotation of the vehicle and follows the large arrow. The distance to the reference numeral 101 may be expressed as r. The rotation of the vehicle is

can be expressed as , where s is the sun.
201: in the direction in which the vehicle moves

It can be expressed as a unit vector.
203: This is the expression of the optimal trajectory of the path, and it is the trajectory of the vehicle that can minimize the distance between the vehicle and the road.
204: Rotation of a rotating body (otholith, etc.) in the semicircular canal of the occupant or reference person

is expressed as p is a planar, distinct from the sun.

Claims (7)

Optimize driving or lane design by using information on the linear acceleration change rate or angular velocity second-order derivative of the coordinate system corresponding to a specific part of the vehicle. Here, optimization means solving Bellman equations, dynamic programming, neural network learning, optimal control LQR, reinforcement learning, etc.
Optimize driving or lane design using information on the linear acceleration change rate and angular velocity second-order derivative of the coordinate system corresponding to a specific part of the vehicle. The vehicle according to claim 1, wherein the vehicle may be a four-wheel drive device. The method according to claim 1, wherein the vehicle may be a two-wheel drive device. The method according to claim 1, wherein the vehicle may be a flying object through three-dimensional analysis. The method according to claim 1, wherein the reference point of the coordinate system can change the seating arrangement, so that it is possible to provide a more optimized stable driving and motion sickness prevention to a desired person. In the learning of claim 1, time, path deviation, etc. can be optimized and learned as well.

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