TWI819885B - Prompting method for induction of motion sickness - Google Patents

Abstract

The present application provides a prompt method for induction of motion sickness. The method calculates a first-axis accumulated induced value according to a first-axis input value and calculates a second-axis accumulated induced value according to a second-axis input value; and calculates at least one output value based on the first-axis accumulated induced value and/or the second-axis accumulated induced value. The calculation of the first-axis accumulated induced value includes weighting the first-axis input value according to a first-axis frequency weighted function and a first-axis weighting coefficient, wherein the first-axis frequency weighted function is corresponding to the axis of the first-axis input value. The calculation of the second-axis accumulated induced value includes weighting the second-axis input value according to a second-axis frequency weighted function and a second-axis weighting coefficient, wherein the second-axis frequency weighted function is corresponding to the axis of the second-axis input value. By using this application, a warning can be timely transmitted before motion sickness is induced on a passenger.

Description

Tips for inducing motion sickness

The present application relates to the technical field of vehicle management, and in particular to a prompting method for inducing motion sickness.

During driving of vehicles such as cars, motion sickness is one of the main problems for drivers, passengers and other occupants. The causes of motion sickness are complex, including the individual or interactive effects of personal physique, vehicle vibration and other factors. At present, drugs are generally used to alleviate the problem of motion sickness among passengers. However, passengers need to predict the possibility of motion sickness and prepare and take the drugs in advance. Therefore, the applicable scenarios are limited and it is inconvenient to use.

In addition, autonomous driving technology has gradually been implemented in cars. Self-driving vehicles may not only drive differently, for example, it is not yet easy to drive as smoothly as humans, but also have more flexibility in seat configuration, such as the front and rear rows can sit face to face. Driving in a manner that is not smooth enough or with passengers facing rearward may make motion sickness more likely to occur or become more severe.

In view of this, it is necessary to provide a method for inducing motion sickness, which can provide timely warnings before the occurrence of motion sickness in the occupants, and improve it by providing driving suggestions, thereby reducing the dose value of motion sickness (also known as "motion sickness"). The accumulation of "induced cumulative value") thereby improves the comfort of the occupants. The dose value is because the original English text is Motion Sickness Dosage Value (MSDV for short), which is translated into cumulative value and is derived from its integral operation.

The motion sickness inducing prompting method includes: receiving a set of input values, the set of input values include a first axis input value and a second axis input value, the first axis input value and the second axis input value The values are the acceleration value of movement along the first axis, the acceleration value of movement along the second axis, the acceleration value of movement along the third axis, and the angular velocity of rotation around the first axis sensed by the sensor. Or two of the angular acceleration value, the angular velocity or angular acceleration value of rotation around the second axis, and the angular velocity or angular acceleration value of rotation around the third axis, wherein the first axis, the second axis The axial direction and the third axial direction are independent vectors; the first axis induced cumulative value is calculated, and the calculation of the first axis induced cumulative value includes a first axis frequency weighting function corresponding to the axial direction corresponding to the first axis input value and A first axial weighting coefficient weights the first axis input value; calculating a second axis induced cumulative value, the calculating the second axis induced cumulative value includes based on a second axial direction corresponding to the second axis input value The axis frequency weighting function and the second axis weighting coefficient weight the second axis input value; and based on the result of the calculation of the first axis induced cumulative value and/or the calculation of the second axis induced cumulative value, calculate at least one Output value.

Optionally, the second axial weighting coefficient is not equal to the first axial weighting coefficient and/or the second axis frequency weighting function and the first axis frequency weighting function are different functions.

Optionally, the first axis frequency weighting function and the second axis frequency weighting function are obtained by conducting experiments on a plurality of subjects, and based on the results of the plurality of subjects in the first axial frequency weighting function and the The second axial frequency weighting function is obtained by statistically analyzing the results of motion sickness induced by different axial motion frequencies corresponding to each other.

Optionally, the ratio of the first axial weighting coefficient and the second axial weighting coefficient is determined by conducting experiments on multiple subjects. On the axis corresponding to the coefficient, the relationship between different cumulative induction values and the proportion of motion sickness among the plurality of subjects is calculated respectively, and the change in the proportion between the two is obtained.

Optionally, the set of input values also includes a third axis input value, a fourth axis input value, a fifth axis input value, and a sixth axis input value. The first axis input value, the second axis input value , the third axis input value, the fourth axis input value, the fifth axis input value, and the sixth axis input value are respectively the acceleration value of the movement along the first axis, the acceleration value of the movement along the second axis, and the acceleration value along the second axis. The acceleration value of the third axial movement, the angular velocity or angular acceleration value of rotation around the first axis, the angular velocity or angular acceleration value of rotation around the second axis, and the angular velocity of rotation around the third axis Or the angular acceleration value, the method further includes: calculating the third-axis induced cumulative value, the calculating the third-axis induced cumulative value includes based on the third-axis frequency weighting function corresponding to the axial direction of the third-axis input value and The third axial weighting coefficient weights the third axis input value; calculating the fourth axis induced cumulative value, the calculating of the fourth axis induced cumulative value includes based on the fourth axial direction corresponding to the fourth axis input value. The axis frequency weighting function and the fourth axial weighting coefficient weight the fourth axis input value; calculate the fifth axis induced cumulative value, and the calculation of the fifth axis induced cumulative value includes based on the value corresponding to the fifth axis input value. The fifth-axis frequency weighting function and the fifth-axis weighting coefficient in the axial direction weight the fifth-axis input value; the sixth-axis induced cumulative value is calculated, and the calculation of the sixth-axis induced cumulative value includes the basis corresponding to the first The sixth-axis frequency weighting function and the sixth-axis weighting coefficient of the six-axis input values weight the sixth-axis input value; and the calculating of at least one output value includes calculating a total induced cumulative value, the total induced cumulative value The induced cumulative value is the sum of the first-axis induced cumulative value, the second-axis induced cumulative value, the third-axis induced cumulative value, the fourth-axis induced cumulative value, the fifth-axis induced cumulative value, and the sixth-axis induced cumulative value. .

Optionally, the method further includes: determining whether the total induced cumulative value exceeds a preset total induced threshold, and when the total induced cumulative value exceeds the total induced threshold, sending a prompt instruction to an output device, so that the output device prompts relevant suggestions in a human-perceivable manner.

Optionally, the method further includes: receiving an indication and storing the total induced cumulative value as a total induced threshold value in response to the instruction.

Optionally, the method further includes: associating the total induction threshold with a reference value, where the reference value includes user identification information, vehicle identification information, vehicle dynamic parameter history information, and movement path. At least one of the historical information.

Optionally, the calculation of at least one output value further includes calculating a cumulative value of related factors, and the cumulative value of related factors is the first-axis induced cumulative value, the second-axis induced cumulative value, the third-axis induced cumulative value, One of the fourth axis induced cumulative value, the fifth axis induced cumulative value, and the sixth axis induced cumulative value, or at least the sum of both.

Optionally, the calculation of at least one output value further includes calculating a complex correlation factor cumulative value, each of the complex correlation factor cumulative values being the first axis induced cumulative value, the second axis induced cumulative value, and the third axis induced cumulative value. One or at least the sum of two of the axis induced cumulative value, the fourth axis induced cumulative value, the fifth axis induced cumulative value, and the sixth axis induced cumulative value, the method further includes: determining the cumulative value of the plurality of related factors The largest of the values; and based on the largest of the cumulative values of the plurality of related factors, transmit a prompt command to an output device, so that the output device prompts the cumulative value of the plurality of related factors in a human-perceivable manner. Driving advice for the greatest value.

The above-mentioned motion sickness induction prompt method provided by the embodiments of the present application starts from the perspective of dynamic design of the vehicle and assists the driver and passengers through the calculation and accumulation of motion sickness dose values and the setting of the motion sickness threshold value. Real-time monitoring of the cumulative value of motion sickness induction, and prompt driving suggestions for improving the driving style before an occupant induces motion sickness, so that the driver can change the driving style according to the provided driving suggestions to slow down the accumulation of motion sickness dose value. This can improve the comfort of the passengers while riding in the car, and further reduce the negative feeling of motion sickness through the human body's adaptation and recovery mechanism.

It can be understood that this application can not only be used to calculate the state that may induce motion sickness based on the data of the inertial sensor, and send out timely signals to remind the need to stop and take a rest, it can also be used to control the movement of the vehicle to reduce motion sickness. chance of it happening, or by combining map information to plan in advance the route with the lowest possibility of inducing motion sickness. In addition, dizziness and discomfort caused by screen changes in virtual reality (VR) applications are also problems that need to be solved urgently. Based on the experimental method and calculation model of this application, the relationship between the parameters related to screen changes and the subject's occurrence of dizziness can also be analyzed by conducting experiments and results statistics on multiple subjects, and based on the same or similar formula ( The model of 1) calculates the possibility that the user will become dizzy after playing a VR game for a period of time, and then reminds the user to take a rest or reduce the speed and amplitude of head movement. Such experimental data and calculation models can also be used as a reference when designing dynamic images for VR applications, so as to avoid image changes that can easily make users dizzy.

In order to more clearly understand the above objects, features and advantages of the present application, the present application will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, as long as there is no conflict, the embodiments of the present application and the features in the embodiments can be combined with each other.

Many specific details are set forth in the following description to facilitate a full understanding of the present application. The described embodiments are only some, rather than all, of the embodiments of the present application. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of this application.

Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the technical field to which this application belongs. The terms used in the description of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application.

Refer to Figure 1, which is an application environment diagram of the motion sickness inducing prompting method provided by the preferred embodiment of the present application.

In one embodiment, the motion sickness inducing prompting method provided by this application can be applied to the vehicle-mounted device 3, or can also be applied to the vehicle-mounted device 3, cloud server 4 and terminal shown in Figure 1 that are connected by communication with each other. In the application environment composed of device 5. The motion sickness induction prompting method is used to calculate the motion sickness induction cumulative value in each axis of the vehicle 100 through the vehicle-mounted device 3, and analyze the factors causing motion sickness based on the motion sickness induction cumulative value in each axis. , and provide driving suggestions to the driver of the vehicle 100 based on the factors causing motion sickness. The driver can change the driving style according to the driving suggestions to improve the comfort of the occupants and reduce the bad feeling of motion sickness. It can be understood that this embodiment can also be applied to autonomous vehicles. For example, the cumulative value of motion sickness induction or the factors causing motion sickness can be used as input signals of the autonomous driving control system to control the driving of the vehicle. Reference information. Specific details are introduced below.

In this embodiment, the vehicle-mounted device 3 is installed on the vehicle 100 . The vehicle-mounted device 3 may be, for example, a vehicle-mounted computer, including a memory 31 electrically connected to each other, at least one processor 32 , an inertial sensor 33 , a communication device 34 , and a display screen 35 .

In this embodiment, the inertial sensor 33 may be a six-axis inertial sensor, and may be used to sense six-axis driving parameters of the vehicle 100 . As shown in FIG. 2 , in one embodiment, the six-axis driving parameters include: acceleration in the X-axis (longitudinal direction, that is, the traveling axis of the plane on which the vehicle travels), Y-axis (lateral, The acceleration in the Z-axis direction (vertical, the axis orthogonal to the plane in which the vehicle is traveling), the angular velocity or angular acceleration around the X-axis (rolling , roll), angular velocity or angular acceleration around the Y-axis (pitch, pitch), angular velocity or angular acceleration around the Z-axis (sway, yaw). In other embodiments, the inertial sensor 33 may also be a nine-axis inertial sensor. In addition, sensors of different specifications can also be used according to actual needs, such as three-axis accelerometers or gyroscopes.

In this embodiment, the vehicle-mounted device 3 establishes a communication connection with the cloud server 4 and the terminal device 5 through the communication device 34 . The communication device 34 may be a wireless communication device.

In this embodiment, the display screen 35 may be a touch display screen, used to display various types of data of the vehicle-mounted device 3 such as navigation information. The display screen 35 may provide an interactive interface to enable interaction between a user, such as a driver of the vehicle 100 , and the vehicle-mounted device 3 .

In one embodiment, the terminal device 5 may be a portable electronic device such as a mobile phone or a tablet computer of an occupant (such as a driver or passenger of the vehicle 100 ).

Persons skilled in the art should understand that the structures of the vehicle-mounted device 3, cloud server 4, and terminal equipment 5 shown in Figure 1 do not constitute a limitation of the embodiments of the present application. The vehicle-mounted device 3, cloud server 4, and terminal The device 5 may also include more or less other hardware or software than in Figure 1, respectively, or a different arrangement of components. For example, the vehicle-mounted device 3 may also include speakers, microphones, indicator lights, speed sensors and other equipment. The cloud server 4 may include a memory, a processor, a display, etc. The terminal device 5 includes a display screen, a speaker, a microphone and other equipment.

It should be noted that the vehicle-mounted device 3, cloud server 4 and terminal equipment 5 are only examples. Other existing or future vehicle-mounted devices and cloud servers that may be applicable to this application shall also be included in this application. are within the scope of this publication and are incorporated herein by reference.

In some embodiments, the memory 31 can be used to store program codes and various data of computer programs. For example, the memory 31 can be used to store the motion sickness induction reminder system 30 installed in the vehicle-mounted device 3 , and realize high-speed and automatic access to programs or data during the operation of the vehicle-mounted device 3 . The memory 31 may include read-only memory (Read-Only Memory, ROM), programmable read-only memory (Programmable Read-Only Memory, PROM), erasable programmable read-only memory (Erasable Programmable Read-Only Memory (EPROM), One-time Programmable Read-Only Memory (OTPROM), Electronically Erasable Programmable Read-Only Memory (Electrically-Erasable Programmable Read-Only Memory, EEPROM), Compact Disc Read-Only Memory (CD-ROM) or other optical disk memory, magnetic disk memory, tape memory, or any other non-volatile computer capable of carrying or storing data Readable storage media.

In some embodiments, the at least one processor 32 may be comprised of integrated circuits. For example, it can be composed of a single packaged integrated circuit, or it can be composed of multiple integrated circuits packaged with the same function or different functions, including one or more central processing units (CPUs), microprocessors processor, digital processing chip, graphics processor and various control chip combinations, etc. The at least one processor 32 is the control core (Control Unit) of the vehicle-mounted device 3. It uses various interfaces and lines to connect various components of the entire vehicle-mounted device 3, and executes programs or modules stored in the memory 31. Or instructions, and call the data stored in the memory 31 to perform various functions and process data of the vehicle-mounted device 3, for example, perform the function of inducing motion sickness prompts (see Figure 4 and Figure 9 below for details) introduction).

In this embodiment, the motion sickness inducing prompt system 30 can be divided into one or more modules, and the one or more modules are stored in the memory 31 and processed by one or more A processor (such as the processor 32) is executed to implement the functions provided by this application. Referring to FIG. 3 , in this embodiment, the motion sickness induction prompting system 30 can be divided into a sensing module 301 and an execution module 302 . The module referred to in this application is a computer program segment that can complete a specific function. It is understandable that individual modules may also be stored in different devices or hardware and operate together through communication methods such as the Internet. The detailed functions of each module will be described in detail below with reference to Figures 4 and 9.

In one embodiment, the above-mentioned software function module includes one or more computer-readable instructions. At least one processor 32 of the vehicle-mounted device 3 implements various implementations of the present application by executing the one or more computer-readable instructions. Example method steps, such as the motion sickness induction prompting method shown in Figures 4 and 9.

In a further embodiment, referring to FIG. 3 , the at least one processor 32 can execute the operating system of the vehicle-mounted device 3 and various applications (such as the motion sickness induction prompt system 30 ), etc.

In a further embodiment, the memory 31 stores program code of a computer program, and the at least one processor 32 can call the program code stored in the memory 31 to perform related functions. For example, each module of the motion sickness induction reminder system 30 in FIG. 3 is a program code stored in the memory 31 and executed by the at least one processor 32 to implement each module. function to achieve the purpose of inducing motion sickness prompts (see the description of Figure 4 and Figure 9 for details). Figures 4 and 9 are flow charts of the motion sickness inducing prompting method provided by the preferred embodiment of the present application.

In this embodiment, the motion sickness inducing prompting method can be applied to the vehicle-mounted device 3. For the vehicle-mounted device 3 that needs to be prompted for motion sickness inducing, the vehicle-mounted device 3 can be directly integrated with the information provided by this application. The function for inducing motion sickness prompts may be run on the vehicle-mounted device 3 in the form of a software development kit (SDK).

As shown in Figure 4, the motion sickness induction prompting method specifically includes the following steps. According to different needs, the order of the steps in the flow chart can be changed, and some steps can be omitted.

Step S1: When the vehicle 100 is traveling, the sensing module 301 uses the inertial sensor 33 to sense multiple axial driving parameters of the vehicle 100.

In one embodiment, the inertial sensor 33 is a six-axis inertial sensor, and the multiple axial driving parameters include: acceleration along the X-axis translation, acceleration along the Y-axis translation, acceleration along the Z-axis translation Two or more of the acceleration, the angular velocity or angular acceleration around the X-axis, the angular velocity or angular acceleration around the Y-axis, the angular velocity or angular acceleration around the Z-axis. It can be understood that in other embodiments, only one or several axial driving parameters may be sensed or output. In addition, the above-mentioned X, Y, and Z axes based on the rectangular coordinate system are only examples. The coordinate system applicable to this application is not limited to this, as long as the three axes are independent vectors or linearly independent vectors (that is, where A vector cannot be represented by a linear combination of two other vectors). Part or all of the translational motion in these three axes and the rotational motion around these three axes can be used as sensing or input driving parameters.

Step S2: The execution module 302 calculates the accumulated value of motion sickness induction in each axis based on the driving parameters in each of the plurality of axes. It can be understood that in other embodiments, only partial axial motion sickness induced cumulative values may be calculated.

In one embodiment, calculating the motion sickness-induced cumulative value in each axis based on the driving parameters in each of the multiple axes includes: calculating based on the acceleration along the X-axis translation Obtaining a first motion sickness induction cumulative value; calculating a second motion sickness induction cumulative value based on the acceleration along the Y-axis translation; calculating a third motion sickness induction cumulative value based on the acceleration along the Z-axis translation; A fourth motion sickness induction cumulative value is calculated based on the angular acceleration around the X-axis; a fifth motion sickness induction cumulative value is calculated based on the angular acceleration around the Y-axis; and based on the rotation around the Z-axis The angular acceleration is calculated to obtain the sixth motion sickness induced cumulative value.

In one embodiment, the execution module 302 calculates the accumulated value of motion sickness induction in each axis according to the following formula (1):

(1)

Among them, is the cumulative value of motion sickness induction in the corresponding axial direction; is the weight coefficient of the corresponding axial direction; T is the total time for calculating the cumulative value of motion sickness induction (for example, the unit is seconds); is the frequency weighting of the corresponding axial direction. The following driving parameters; are the six axes respectively. In other words, it represents the different influence degrees of motion or vibration in different axial directions on inducing motion sickness, which is a numerical value; and represents the relationship between different vibration frequencies in the axial direction and inducing motion sickness, which is a function of frequency. For example, it can express is a curvilinear relationship.

In the existing technology, although the international standard ISO 2631-1 has the concept of describing the cumulative value of motion sickness induced based on the boating situation, it only considers the vertical axis in equation (1), that is, similarly, different frequencies have different effects on the induced motion sickness. The impact of sickness naturally only considers the vertical axis, that is. Since only a single axis is considered, ISO 2631-1 naturally lacks the concept of different weight coefficients for different axes. For these reasons, the data or relationship curves provided by ISO 2631-1 may not be directly applicable to other axes, nor may they be directly applicable to all scenarios, such as different vehicles (such as the ratio of longitudinal and transverse vibrations when a vehicle is driving) Much larger than a ship), different races, and differences in the definition of symptoms of motion sickness during experiments (such as subjects experiencing different symptoms such as vomiting, headache, dizziness, or nausea), etc. Further re-experiments are needed to confirm, correct, and Supplement the data or relationship curves revealed in ISO 2631-1.

For example, the motion sickness experiment can be performed according to the ISO-2631-1 specification and statistics can be obtained to obtain the frequency weighted function calculation of human motion sickness corresponding to the axial direction and different frequencies (the subscript w refers to the frequency weighted ) calculation), and then obtain the weight coefficient of the corresponding axis based on the relationship between the cumulative value of motion sickness induction in different axes (which can be calculated by the human motion sickness frequency weighting function) and the symptoms of motion sickness. The method of obtaining the weight coefficient corresponding to each axial direction includes: obtaining multiple sets of experimental data corresponding to each axial direction, wherein each set of experimental data in the multiple sets of experimental data corresponding to each axial direction includes: each of the The cumulative value of motion sickness induction corresponding to the axial direction and the proportion of people with symptoms of motion sickness; set an origin, take the cumulative value of motion sickness induction corresponding to each axis as the horizontal axis, and use the cumulative value of motion sickness induction corresponding to each axis as the horizontal axis. The proportion of people experiencing symptoms of motion sickness is used to establish a rectangular coordinate system for the vertical axis; based on the multiple sets of experimental data corresponding to each axis and the established coordinate system, multiple coordinate points corresponding to each axis are obtained; using The preset fitting algorithm performs curve fitting through the origin for multiple coordinate points corresponding to each axis to obtain a fitting line corresponding to each axis; based on the slope of the fitting line corresponding to each axis Ratio to obtain the weight coefficient of each axis. Among them, linear fitting is only an example, and fitting of a quadratic curve or other statistical curves may also be used as needed.

In order to clearly illustrate the present application, refer to Figure 5. The rectangular coordinate system on the left side of Figure 5 illustrates the cumulative value of motion sickness induction and the symptoms of motion sickness based on translation along the X-axis, Y-axis, and Z-axis respectively. The scatter point coordinates corresponding to the proportion of people, and the fitting line fitted based on the scatter point coordinates corresponding to each axis. The rectangular coordinate system on the right side of Figure 5 illustrates the scatter point coordinates corresponding to the cumulative value of motion sickness induced by rotation around the X-axis, Y-axis, and Z-axis and the proportion of people experiencing motion sickness symptoms, as well as the The fitting line obtained by fitting the scatter point coordinates corresponding to each axis. In one embodiment, the preset fitting algorithm may be a minimum error square method. After obtaining the fitting line corresponding to each axis, the weight coefficient of each axis can be obtained based on the slope of the fitting line corresponding to each axis. Specifically, the value of the weight coefficient corresponding to the Z-axis translation can be set to 1. According to the slope corresponding to the Z-axis translation and the weight coefficient 1 and the slopes corresponding to the other five axes, the weights corresponding to the other five axes can be obtained. The value of the coefficient. Taking the results shown in Figure 5 as an example, the weight coefficients corresponding to the six axes are , , , , , respectively.

Step S3: The execution module 302 analyzes the factors causing motion sickness based on the cumulative value of motion sickness induction in each axis. In one embodiment, the factors causing motion sickness may include: steering factors, speed control (acceleration and deceleration) factors, and road surface factors.

In one embodiment, the analysis of factors causing motion sickness based on the cumulative value of motion sickness induction in each axis includes: based on the motion sickness corresponding to the first specified axis among the plurality of axes. Calculate a first reference value based on the cumulative symptom-inducing value, and use the first reference value as a reference value for motion sickness caused by the steering factor; based on the motion sickness corresponding to the second designated axis among the plurality of axes Calculating a second reference value based on the induced cumulative value, using the second reference value as a reference value for motion sickness caused by the speed control factor; and based on the motion sickness corresponding to a third specified axis among the plurality of axes. Calculate a third reference value based on the symptom-inducing cumulative value, and use the third reference value as a reference value for motion sickness caused by the road surface factor. For example, if only the motion in the three axes of x, y, and z is considered, the cumulative values of motion sickness induction in the x, y, and z axes can be designated as reference values for speed control factors, steering factors, and road surface factors respectively. In specific applications, for example, the reference value can be directly used as the output value, the proportion of the reference value in the sum of the cumulative motion sickness induction values in all axes can be calculated, or the reference value can be compared with a specific preset value, etc. .

In one embodiment, the analysis of factors causing motion sickness based on the cumulative value of motion sickness induction in each axis includes: calculating the second cumulative value of motion sickness induction, the fourth cumulative value of motion sickness induction. The first reference value is obtained by summing the value and the sixth cumulative value of motion sickness induction, and the first reference value is used as the reference value for motion sickness caused by steering factors; the first cumulative value of motion sickness induction and the fifth cumulative value of motion sickness are calculated. The second reference value is obtained by summing the motion sickness induced cumulative values, and the second reference value is used as the reference value for motion sickness caused by the speed control factor; and the third motion sickness induced cumulative value and the fourth motion sickness induced cumulative value are calculated. The third reference value is obtained from the sum of the cumulative symptom-inducing value and the fifth motion sickness-inducing cumulative value, and the third reference value is used as the reference value for motion sickness caused by road factors. For example, if motion in six axes is considered, the accumulated motion sickness-inducing values in the x and pitch axes can be specified as the reference value for the speed control factor, and the accumulated motion sickness-inducing values in the y, roll, and yaw axes can be specified. The reference value for the steering factor is specified, and the cumulative value of motion sickness induction in the z, roll, and pitch axes is designated as the reference value for the road surface factor. In specific applications where multiple axes are used as reference values for the same factor, for example, the reference values in each axis can be summed or averaged before further processing, or the reference values in different axes can be given different weights as needed before summing. wait.

Step S4: The execution module 302 provides driving advice to the driver of the vehicle 100 based on the factors causing motion sickness.

In one embodiment, providing driving advice to the driver of the vehicle 100 based on the factors causing motion sickness includes: calculating the first reference value, the second reference value and the third reference value. The proportion of the steering factor, the proportion of the speed control factor and the proportion of the road surface factor; determine a maximum value from the proportion of the steering factor, the proportion of the speed control factor and the proportion of the road surface factor ; Taking the factors causing motion sickness corresponding to the maximum value as the main factors causing motion sickness; and providing driving suggestions to the driver based on the main factors.

In one embodiment, the execution module 302 calculates the sum of the first reference value, the second reference value and the third reference value to obtain a total reference value; calculates the ratio of the first reference value to the total reference value. Obtain the proportion of the steering factor; calculate the ratio of the second reference value to the total reference value to obtain the proportion of the speed control factor; calculate the ratio of the third reference value to the total reference value to obtain the road surface factor proportion. In one embodiment, when the main factor causing motion sickness is steering, the driving suggestions provided by the execution module 302 include, but are not limited to: do not turn the steering wheel suddenly and reduce the vehicle speed when turning; when motion sickness is caused When the main factor is the speed control factor, the driving suggestions provided by the execution module 302 include, but are not limited to: do not accelerate or decelerate rapidly; and when the main factor causing motion sickness is road surface factors, the execution module 302 The driving suggestions provided by 302 include, but are not limited to: changing routes or reducing the speed of the vehicle. If the vehicle you are riding has an adjustable damping suspension system, it can also recommend corresponding damping adjustments. It can be understood that in the context of autonomous driving, in addition to adjusting the driving parameters of the vehicle based on the accumulated value of motion sickness in at least one axis, the vehicle acceleration, deceleration and attitude can also be adjusted based on different factors that cause motion sickness. control.

In one embodiment, the execution module 302 can also use a preset graphic such as a circle chart to display the proportion of the steering factor, the proportion of the speed control factor and the proportion of the road surface factor, for example, see Figure 6 . The execution module 302 can display the preset graphics on the display screen 35 of the vehicle-mounted device 3 for immediate reference by the driver of the vehicle 100 .

In one embodiment, the execution module 302 can also calculate a cumulative total value of motion sickness based on the cumulative value of motion sickness induction in each axis; when the cumulative total value of motion sickness is greater than the threshold value At a preset percentage, an outer ring is displayed around the circle. See Figure 7 for example. The execution module 302 shown can display the outer ring 6 when the cumulative total value of motion sickness is greater than a preset percentage of the threshold.

In one embodiment, when the cumulative total value of motion sickness is greater than a preset percentage of a threshold, the color of the outer ring may change as the cumulative total value of motion sickness increases.

In one embodiment, the execution module 302 can also make real-time statistics on the accumulated motion sickness-induced values corresponding to the steering factors and the speed control factors corresponding to the predetermined time period (for example, within the first 3 to 5 seconds). The cumulative value of motion sickness induction, and the cumulative value of motion sickness induction corresponding to the road surface factors; using a bar chart to display real-time statistics of the cumulative value of motion sickness induction corresponding to the steering factor within the predetermined time period, A cumulative motion sickness induction value corresponding to the speed control factor, and a cumulative motion sickness induction value corresponding to the road surface factor. Referring to FIG. 8 , the execution module 302 uses a bar chart to instantly update and display the cumulative value of motion sickness induction within the previous 3 to 5 seconds. As a result, the driver can make immediate corrections to his current driving behavior.

In one embodiment, the execution module 302 also calculates a cumulative total value of motion sickness induction based on the cumulative value of motion sickness induction in each axis; when the total cumulative value of motion sickness induction is greater than a threshold value When a preset percentage (for example, 90%) is reached, driving suggestions are provided to the driver based on the main factors causing motion sickness, so that driving suggestions are provided to the driver before the threshold is reached for the driver to drive according to It is recommended to change the driving style to avoid motion sickness or reduce the discomfort of motion sickness. In addition, all or part of the motion sickness-inducing prompts can be enabled or disabled based on specific conditions. For example, when the vehicle speed is below 30 km/h, the recommendation to reduce the vehicle speed can be disabled.

In one embodiment, the threshold can be set based on user input.

In one embodiment, the execution module 302 also displays the driving suggestion on the preset graphic. In other embodiments, the execution module 302 may also use a speaker to play the driving advice via voice. It is understandable that providing relevant information such as tips or suggestions to drivers or passengers can be achieved through different methods in existing technologies, such as screen display, augmented reality (AR), sound, steering wheel vibration, etc.

In one embodiment, the execution module 302 calculates the cumulative total value of motion sickness induction according to the following formula (2):

(2)

Among them, represents the total cumulative value of motion sickness induced, represents the cumulative value of motion sickness induced by the corresponding X-axis translation; represents the cumulative value of motion sickness induced by the corresponding Y-axis translation; represents the corresponding Z-axis translation. represents the accumulated value of motion sickness induced by translation; represents the accumulated value of motion sickness induced by the corresponding X-axis rotation; represents the accumulated value of motion sickness induced by the corresponding Y-axis rotation; represents the accumulated value of motion sickness induced by the corresponding Z-axis rotation. The resulting cumulative value of motion sickness induction.

In one embodiment, the execution module 302 can also use preset graphics, such as circular charts, to real-time and dynamically display the accumulated motion sickness induction values and the motion sickness induction generated by the movements in the multiple axes. Cumulative total value.

In one embodiment, the execution module 302 can also obtain the current location information of the vehicle 100 when the cumulative total value of motion sickness induction is greater than a preset percentage of the threshold; The current location information, the current cumulative total value of motion sickness induction and/or the individual cumulative value of motion sickness induction in each axis, the threshold value and the history information of the vehicle are associated and stored locally ( For example, a vehicle-mounted device or other storage medium) or uploaded to the cloud server 4, so that the vehicle-mounted device can subsequently further optimize the motion sickness induction prompt of this application based on the cumulative total value of motion sickness induction and location information and threshold values uploaded in history. method. In one embodiment, the history information includes, but is not limited to, the driving parameters and command parameters (such as steering wheel rotation degrees, throttle parameters, braking parameters, etc.) during driving of the vehicle 100 .

In one embodiment, the execution module 302 responds to the motion sickness threshold signal sent by the passenger using the terminal device 5 and updates the threshold value to the current cumulative total value of motion sickness induction. Since different people have different motion sickness conditions, updating the threshold value according to the actual motion sickness condition of the occupants makes the motion sickness induction prompt method provided by this application more close to the real situation of the occupants, and further improves the riding experience.

For example, when a passenger currently feels motion sickness or is about to suffer from motion sickness, the passenger can use the terminal device 5 to send a signal to the vehicle-mounted device 3 in the preset operating interface, so that the execution module 302. After the vehicle-mounted device 3 receives the signal, it updates the threshold value to the current cumulative total value of motion sickness induction, and provides driving suggestions to the driver based on the current main factors causing motion sickness. In this way, the driver can change the driving style according to the driving suggestions, thereby improving the comfort of the passengers in the car.

In one embodiment, in addition to real-time dynamic display of the cumulative value of motion sickness induced by each axial movement and the cumulative total value of motion sickness, the execution module 302 can also display the motion sickness induced cumulative value. The total induced cumulative value is compared with the threshold value set by the passenger. When the cumulative total value induced by motion sickness is close to the threshold value set by the passenger, the execution module 302 will issue a prompt to stop and rest and the corresponding driving style improvement. suggestion. In addition, according to the needs of different passengers, the execution module 302 can flexibly adjust and set multiple sets of different thresholds for the passengers to choose, so as to avoid the situation that only setting a single threshold cannot satisfy all passengers. The execution module 302 also According to the thresholds set by different occupants, relevant prompts will be issued in a timely manner, such as prompts to stop and take a rest, prompts to change the driving style, etc.

In one embodiment, the execution module 302 can also store the cumulative total value of motion sickness induced by the passenger's wishes and the threshold set by the passenger, as well as the driving advice corresponding to the total cumulative value of motion sickness induced. Locally or uploaded to the cloud server 4, the prompt method can be optimized based on the cumulative total value and threshold value of motion sickness induction uploaded in history, combined with the human body's adaptation and recovery mechanism, so that the interpretation of occupant motion sickness and driving recommendations are closer The individual needs of drivers and passengers.

In one embodiment, the execution module 302 can also store driving routes frequently used by the occupants (i.e. routes with relatively fixed road conditions and driving times, such as the occupants’ driving routes to and from work, commuting to and from class, and visiting relatives and friends). (current driving route), corresponding driving suggestions are directly given for the frequently used driving routes to reduce the probability of occupants suffering from motion sickness. For example, driving suggestions are given for the occupants' driving routes when commuting to and from get off work; driving suggestions are given for the occupants when commuting to and from class; driving suggestions are given for the occupants when visiting relatives and friends, etc.

In one embodiment, the motion sickness inducing prompting system 30 can activate the motion sickness inducing prompting function provided by the present application according to the occupant's preference or in response to the occupant's input signal. In addition, the motion sickness induction prompt system 30 can also set corresponding thresholds and provide driving suggestions for the occupants in different situations. For example, the corresponding threshold value is set and driving suggestions are provided when the occupants are traveling; the corresponding threshold value is set and driving suggestions are provided when the occupants are on a business trip; the corresponding threshold value is set and driving suggestions are provided when the occupants are driving on mountain roads.

In conjunction with the introduction of Figure 4, refer to Figure 9, which is a second flow chart of the motion sickness induction prompting method provided by the embodiment of the present application. According to different needs, the order of steps in the flow chart can be changed, and some steps can be omitted.

Step S21: The execution module 302 receives a set of input values. The set of input values includes a first axis input value and a second axis input value. The first axis input value and the second axis input value are obtained by The acceleration value of movement along the first axis, the acceleration value of movement along the second axis, the acceleration value of movement along the third axis, the angular velocity or angular acceleration value of rotation around the first axis sensed by the sensor , two of the angular velocity or angular acceleration value of rotation around the second axial direction, and the angular velocity or angular acceleration value of rotation around the third axial direction, wherein the first axial direction, the second axial direction and the third axial direction The three axes are independent vectors.

In one embodiment, the first axial direction, the second axial direction, and the third axial direction may refer to the X-axis direction, the Y-axis direction, and the Z-axis direction respectively. In one embodiment, the sensor may be an inertial sensor 33 . Specifically, the sensing module 301 can obtain the set of input values through the inertial sensor 33 .

In other embodiments, the set of input values also includes a third axis input value, a fourth axis input value, a fifth axis input value, and a sixth axis input value, and the first axis input value, the second axis input value The input value, the third axis input value, the fourth axis input value, the fifth axis input value, and the sixth axis input value are respectively the acceleration value of the movement along the first axis and the acceleration value of the movement along the second axis. , the acceleration value of movement along the third axis, the angular velocity or angular acceleration value of rotation around the first axis, the angular velocity or angular acceleration value of rotation around the second axis, and rotation around the third axis Angular velocity or angular acceleration value.

Step S22, the execution module 302 calculates the first-axis induced cumulative value. The calculation of the first-axis induced cumulative value includes a first-axis frequency weighting function corresponding to the axial direction of the first-axis input value and a first-axis direction. The weighting coefficient weights the first axis input value.

Step S23, the execution module 302 calculates the second-axis induced cumulative value. The calculation of the second-axis induced cumulative value includes a second-axis frequency weighting function corresponding to the axial direction of the second-axis input value and a second-axis direction. The weighting coefficient weights the second axis input value. The first axial and second axial weighting coefficients in steps S22 and S23 correspond to the aforementioned weighting coefficients and depend on the results of experiments and statistics, so they may be any value, or they may be 1.

In one embodiment, the second axial weighting coefficient is not equal to the first axial weighting coefficient and/or the second axis frequency weighting function and the first axis frequency weighting function are different functions.

In one embodiment, the first axis frequency weighting function and the second axis frequency weighting function are obtained by conducting experiments on a plurality of subjects, and based on the results of the plurality of subjects in the first axis frequency weighting function The results of motion sickness induced by different axial movement frequencies corresponding to the second axial frequency weighting function are obtained by statistics.

In one embodiment, the ratio of the first axial weighting coefficient to the second axial weighting coefficient is determined by conducting experiments on multiple subjects. Along the axis corresponding to the weighting coefficient, calculate the relationship between different cumulative induction values and the proportion of motion sickness among the plurality of subjects, and compare the changes in the proportions of the two.

In step S24, the execution module 302 calculates at least one output value based on the result of calculating the induced cumulative value of the first axis and/or the calculated induced cumulative value of the second axis.

In one embodiment, the at least one output value is the sum of the first axis induced cumulative value and the calculated second axis induced cumulative value.

In other embodiments, the execution module 302 also performs the following steps:

Calculating the third-axis induced cumulative value, the calculating the third-axis induced cumulative value includes weighting the third axis according to the third-axis frequency weighting function and the third axial weighting coefficient corresponding to the axis of the third-axis input value. Axis input values are weighted;

Calculating the fourth axis induced cumulative value, the calculating of the fourth axis induced cumulative value includes weighting the fourth axis according to the fourth axis frequency weighting function and the fourth axial weighting coefficient corresponding to the axis of the fourth axis input value. Axis input values are weighted;

Calculating the fifth-axis induced cumulative value, the calculating of the fifth-axis induced cumulative value includes calculating the fifth-axis frequency weighting function and the fifth-axis weighting coefficient based on the axis corresponding to the fifth-axis input value. Axis input values are weighted;

Calculate the sixth axis induced cumulative value, the calculation of the sixth axis induced cumulative value includes weighting the sixth axis according to the sixth axis frequency weighting function and the sixth axial weighting coefficient corresponding to the axis of the sixth axis input value. Axis input value weighting; and

The calculation of at least one output value includes calculating a total induced cumulative value, and the total induced cumulative value is the first axis induced cumulative value, the second axis induced cumulative value, the third axis induced cumulative value, and the fourth axis induced cumulative value. value, the sum of the fifth-axis induced cumulative value and the sixth-axis induced cumulative value.

In other embodiments, the execution module 302 also determines whether the total induced cumulative value exceeds a preset total induced threshold. When the total induced cumulative value exceeds the total induced threshold, a prompt command is sent to a An output device, so that the output device prompts relevant suggestions in a human-perceivable manner. Among them, human-perceivable methods include, but are not limited to, graphics or text display on a display, light or sound warnings, vibrations of steering wheels or seats, etc.

In other embodiments, the execution module 302 further receives an instruction and stores the total induced cumulative value as a total induced threshold in response to the instruction. For example, when one of the vehicle's occupants has symptoms of motion sickness, the total induced cumulative value calculated at this time can be stored as the total induced threshold value through, for example, a user interface operation.

In other embodiments, the execution module 302 also associates the total induced threshold with a reference value, where the reference value includes user identification information, vehicle identification information, vehicle dynamic parameter history information, and movement At least one of the path history information. In other words, motion sickness may be induced by different users or members (for example, the susceptibility to motion sickness may vary from person to person), different vehicles (for example, vehicles with different suspension characteristics), and different vehicle dynamics (for example, different vehicle dynamics). There are differences due to the driver's driving habits) and different movement paths (such as different degrees of bumps). Here, the total induction threshold value is associated with the above reference value, which will help to prevent motion sickness under different usage conditions or situations in the future. Possible indications of disease induction.

In one embodiment, the calculation of at least one output value further includes calculating a cumulative value of related factors. The cumulative value of related factors is the first-axis induced cumulative value, the second-axis induced cumulative value, and the third-axis induced cumulative value. value, one of the fourth axis induced cumulative value, the fifth axis induced cumulative value, and the sixth axis induced cumulative value, or at least the sum of both. For example, in the aforementioned embodiment, considering the motion of six axes in the rectangular coordinate system, the accumulated motion sickness-inducing values in the x and pitch axes can be designated as the reference values of the speed control factors, and the y, roll and yaw axes can be designated as reference values. The accumulated value of motion sickness induction is specified as the reference value of the steering factor, or the accumulated value of motion sickness induction in the z, roll, and pitch axes is designated as the reference value of the road factor. When only considering the driving parameters of three axial translational motions, the cumulative value of motion sickness induction in the x-axis can be designated as the reference value of the speed control factor, and the cumulative value of motion sickness induction in the y-axis can be designated as The reference value of the steering factor or the accumulated motion sickness induction value in the z-axis direction is specified as the reference value of the road factor.

In one embodiment, the calculating of at least one output value further includes calculating a complex correlation factor cumulative value, each of the complex correlation factor cumulative values being the first axis induced cumulative value, the second axis induced cumulative value, One or at least the sum of two of the third axis induced cumulative value, the fourth axis induced cumulative value, the fifth axis induced cumulative value, and the sixth axis induced cumulative value.

In other embodiments, the execution module 302 also determines the largest cumulative value of the plurality of correlation factors; and sends a prompt command to an output device based on the largest cumulative value of the plurality of correlation factors, so that all The output device prompts a driving suggestion corresponding to a maximum of the accumulated values of the plurality of relevant factors in a human-perceivable manner.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application and are not limiting. Although the present application has been described in detail with reference to the above preferred embodiments, those of ordinary skill in the art will understand that the technical solutions of the present application can be modified. The technical solution may be modified or equivalently substituted without departing from the spirit and scope of the technical solution of the present application.

100:Transportation 3: Vehicle-mounted device 32: Processor 31:Memory 30: Motion sickness induced prompt system 301: Sensing module 302:Execute module 33:Inertial sensor 34:Communication equipment 35:Display screen 5:Terminal equipment 4:Cloud server 6: Outer ring S21~S24: Steps

Figure 1 is an application environment diagram of the motion sickness induction prompting method provided by the embodiment of the present application. Figure 2 illustrates the axial definition of an inertial sensor. Figure 3 is a functional module diagram of the motion sickness induction prompting system provided by the embodiment of the present application. Figure 4 is a first flowchart of a motion sickness induction prompting method provided by an embodiment of the present application. Figure 5 illustrates linear fitting. Figure 6 illustrates the use of a circular chart to display the proportions of the three factors causing motion sickness. Figure 7 illustrates an example of displaying an outer ring around a circular diagram. Figure 8 illustrates the use of a bar chart to display real-time updates of the cumulative value of motion sickness induced by three factors within a preset period. Figure 9 is a second flow chart of the motion sickness induction prompting method provided by the embodiment of the present application. The following specific embodiments will further describe the present application in conjunction with the above-mentioned drawings.

without

S21~S24: Steps

Claims (10)

A prompting method for inducing motion sickness, wherein the method includes: Receive a set of input values. The set of input values includes a first axis input value and a second axis input value. The first input value and the second input value are the first edge along the first axis sensed by the sensor. The acceleration value of axial movement, the acceleration value of movement along the second axis, the acceleration value of movement along the third axis, the angular velocity or angular acceleration value of rotation around the first axis, rotation around the second axis Both of the angular velocity or angular acceleration value and the angular velocity or angular acceleration value of rotation around the third axis, wherein the first axial direction, the second axial direction and the third axial direction are independent vectors; Calculating the first axis induced cumulative value, the calculating the first axis induced cumulative value includes weighting the first axis according to the first axis frequency weighting function and the first axial weighting coefficient corresponding to the axis of the first axis input value. Axis input values are weighted; Calculating the second axis induced cumulative value, the calculating the second axis induced cumulative value includes weighting the second axis according to the second axis frequency weighting function corresponding to the axial direction of the second axis input value and the second axial weighting coefficient. Axis input value weighting; and At least one output value is calculated based on a result of the calculation of the first-axis induced cumulative value and/or the calculated result of the second-axis induced cumulative value. The motion sickness inducing prompting method according to claim 1, wherein the second axial weighting coefficient is not equal to the first axial weighting coefficient and/or the second axial frequency weighting function is different from the first axial weighting function. The axis frequency weighting function is a function of difference. The motion sickness induction prompting method according to claim 1, wherein the first axis frequency weighting function and the second axis frequency weighting function are obtained by conducting experiments on a plurality of subjects. The results of motion sickness induced by different motion frequencies in the axial directions corresponding to the first axial frequency weighting function and the second axial frequency weighting function are obtained by statistics. The method for inducing motion sickness as claimed in claim 1, wherein the ratio of the first axial weighting coefficient to the second axial weighting coefficient is determined by conducting experiments on a plurality of subjects. In the axial direction corresponding to the axial weighting coefficient and the second axial weighting coefficient, calculate the relationship between different cumulative induction values and the proportion of motion sickness among the plurality of subjects, and compare the changes in the proportions of the two. obtain. The method for inducing motion sickness as described in claim 1, wherein the set of input values also includes a third axis input value, a fourth axis input value, a fifth axis input value, and a sixth axis input value, so The input value of the first axis, the input value of the second axis, the input value of the third axis, the input value of the fourth axis, the input value of the fifth axis, and the input value of the sixth axis are respectively the acceleration values of the movement along the first axis. , the acceleration value of movement along the second axis, the acceleration value of movement along the third axis, the angular velocity or angular acceleration value of rotation around the first axis, the angular velocity or angular acceleration value of rotation around the second axis , and the angular velocity or angular acceleration value of rotation around the third axis, the method further includes: Calculating the third-axis induced cumulative value, the calculating the third-axis induced cumulative value includes weighting the third axis according to the third-axis frequency weighting function and the third axial weighting coefficient corresponding to the axis of the third-axis input value. Axis input values are weighted; Calculating the fourth axis induced cumulative value, the calculating of the fourth axis induced cumulative value includes weighting the fourth axis according to the fourth axis frequency weighting function and the fourth axial weighting coefficient corresponding to the axis of the fourth axis input value. Axis input values are weighted; Calculating the fifth-axis induced cumulative value, the calculating of the fifth-axis induced cumulative value includes calculating the fifth-axis frequency weighting function and the fifth-axis weighting coefficient based on the axis corresponding to the fifth-axis input value. Axis input values are weighted; Calculate the sixth axis induced cumulative value, the calculation of the sixth axis induced cumulative value includes weighting the sixth axis according to the sixth axis frequency weighting function and the sixth axial weighting coefficient corresponding to the axis of the sixth axis input value. Axis input value weighting; and The calculation of at least one output value includes calculating a total induced cumulative value, and the total induced cumulative value is the first axis induced cumulative value, the second axis induced cumulative value, the third axis induced cumulative value, and the fourth axis induced cumulative value. value, the sum of the fifth-axis induced cumulative value and the sixth-axis induced cumulative value. The method for inducing motion sickness as described in claim 5, wherein the method further includes: Determine whether the total induced cumulative value exceeds a preset total induced threshold value. When the total induced cumulative value exceeds the total induced threshold value, a prompt command is sent to an output device, thereby causing the output device to use human Prompt relevant suggestions in a perceptible way. The method for inducing motion sickness as described in claim 5, wherein the method further includes: An instruction is received and the total induction cumulative value is stored as a total induction threshold in response to the instruction. The method for inducing motion sickness as described in claim 7, wherein the method further includes: The total induction threshold is associated with a reference value, where The reference value includes at least one of user identification information, vehicle identification information, vehicle dynamic parameter history information, and movement path history information. The method for inducing motion sickness as described in claim 5, wherein said calculating at least one output value further includes calculating a cumulative value of related factors, and the cumulative value of related factors is the first axis induced cumulative value, the second One or at least the sum of two of the axis-induced cumulative value, the third-axis induced cumulative value, the fourth-axis induced cumulative value, the fifth-axis induced cumulative value, and the sixth-axis induced cumulative value. The method for inducing motion sickness as claimed in claim 5, wherein said calculating at least one output value further includes calculating a plurality of accumulated values of related factors, and each of said accumulated values of plural related factors is the first axis induced The sum of one or at least two of the cumulative value, the second-axis induced cumulative value, the third-axis induced cumulative value, the fourth-axis induced cumulative value, the fifth-axis induced cumulative value, and the sixth-axis induced cumulative value, so The above methods also include: Determine the largest cumulative value among the plurality of relevant factors; and According to the maximum cumulative value of the plurality of relevant factors, a prompt command is sent to an output device, so that the output device prompts the driver corresponding to the maximum cumulative value of the plurality of correlation factors in a human-perceivable manner. suggestion.