JP2005006966A - Support apparatus - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a support apparatus which eliminates troublesomeness of a vehicle driver and precisely calculates the degree of fatigue corresponding to the driver. <P>SOLUTION: The traveling environment of the vehicle is detected with a CCD camera 111 etc., and the degree of fatigue is calculated by using the detected traveling environment. In the case of calculating the degree of fatigue, information about the tropism (extroversion or introversion) of the driver stored in an EEPROM 102 in advance is referred to, and different calculations are performed according to the tropism of the driver. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention relates to assistance technology for a driver who drives a vehicle, and more particularly, to technology for determining the degree of driver fatigue.
[0002]
[Prior art]
In order to support the driver's safe and secure driving in driving the vehicle, it has been proposed to perform an alarm and vehicle control according to the driver's fatigue level. As a premise for providing such support, it is necessary to determine the fatigue level of the driver by some method. However, since the driver's fatigue is also related to the mental state, it is not easy to determine this. As a conventionally proposed method, there is a method in which physiological data such as a driver's heartbeat, skin electricity, and blink is collected, and a fatigue level is determined based on the collected physiological data (for example, Patent Document 1).
[0003]
[Patent Document 1] JP-A-8-140949
[0004]
[Problems to be solved by the invention]
Here, in order to collect physiological data, it is required to attach some measuring device to the driver's body. However, it is troublesome for the driver to attach the measuring instrument to the body every time the vehicle is driven. Therefore, the method of collecting the physiological data and determining the fatigue level is not very practical, and it is not preferable to use this as the main means for determining the fatigue level. In addition, there are various people who drive the vehicle, and the feeling of fatigue varies depending on the person.
[0005]
Accordingly, an object of the present invention is to provide a support device that can eliminate the inconvenience of the driver of the vehicle and can calculate the degree of fatigue more accurately corresponding to each driver.
[0006]
[Means for Solving the Problems]
According to the present invention, there is provided a support device that assists the driver in accordance with the degree of fatigue of the driver of the vehicle, and is detected by the travel environment detection unit that detects the travel environment of the vehicle and the travel environment detection unit. And calculating means for calculating the degree of fatigue of the driver based on the traveling environment, and storage means for storing direction information indicating the direction of the driver, wherein the calculating means is stored in the storage means. A support device is provided that performs different calculations according to the directional information.
[0007]
The present invention focuses on the fact that the driving environment of the vehicle can be a mental load on the driver and is reflected in the degree of fatigue, and that the degree of fatigue due to the driving environment varies depending on the driver's tropism. And this invention eliminates the need for attaching a measuring instrument etc. to a driver | operator's body by calculating a driver | operator's fatigue degree based on the driving | running | working environment of a vehicle with the said calculating means, and eliminates a driver | operator's troublesomeness. Further, by calculating differently depending on the driver's tropism, more accurate calculation of the fatigue level corresponding to each driver can be performed.
[0008]
Examples of the traveling environment include the configuration of roads that are in the driver's field of view, the presence or absence of various structures, the presence or absence of pedestrians, bicycles, and other moving objects, and traffic conditions such as the occurrence of weather and traffic jams. At least some of these driving environments include the above-mentioned driving from an imaging unit that captures a landscape image in front of the vehicle and an image processing unit that performs image processing on the captured image and extracts various objects in the landscape image. It can detect by comprising an environment detection means.
[0009]
Of these driving environments, at least a part of the driving environment includes the output means for outputting radar, radio waves, ultrasonic waves, etc. to the front of the vehicle, and the receiving means for detecting the reflection thereof. This can be detected.
[0010]
In addition, at least some of these driving environments are detected based on the map information by configuring the driving environment detection means from storage means storing map information, represented by a car navigation system. You can also.
[0011]
In addition, at least some of these driving environments are detected based on the received information by configuring the driving environment detecting means from receiving means for receiving various information wirelessly distributed via VICS, the Internet, etc. You can also
[0012]
In addition, the traveling environment detection means can be configured by other vehicle-mounted sensors such as an illuminance sensor that detects the illuminance of the sun.
[0013]
In the present invention, it further comprises selection means for selecting a coefficient of calculation by the calculation means, and the selection means selects the coefficient according to the directional information stored in the storage means, whereby the calculation is performed. Calculations with different means can also be performed. By selecting and calculating a coefficient according to the driver's tropism, it is possible to easily calculate the fatigue level according to the driver's tropism.
[0014]
In the present invention, the calculating means calculates the fatigue degree at the n-th calculation as F._nAnd the calculated value calculated based on the travel information as An and F_n= F_n-1+ A_nThe degree of fatigue is calculated according to the formula:_nIt is also possible to select a coefficient for calculating. When human fatigue is accumulated over time, the fatigue level is calculated to reflect the fatigue accumulation by calculating the current fatigue level by adding the calculated value to the previously calculated fatigue level. Can do.
[0015]
In the present invention, the calculation means includes the fatigue degree F._nWhen the value exceeds a predetermined level, instead of the calculated value An, A determined independently of the tropism information is set.₁F_n= F_n-1+ A₁The degree of fatigue can be recalculated by the following formula. Focusing on the fact that when the fatigue level exceeds a certain level, there is almost no influence of the driver's tropism on the fatigue level, but rather it can be a factor of error, and the fatigue level is independent of the driver's tropism. The degree of fatigue can be calculated more accurately by calculating.
[0016]
In the present invention, the calculation means may calculate the calculated value A when the vehicle speed of the vehicle satisfies a predetermined condition._nInstead of A₂F_n= F_n-1+ A₂The fatigue degree can also be calculated by the following formula. Focusing on the fact that there is almost no influence of the driver's tropism on the degree of fatigue when the vehicle speed is low or high, etc., rather it can be a factor of error, regardless of the driver's tropism By calculating the fatigue level, the fatigue level can be calculated more accurately. In addition, as the predetermined condition, for example, when the vehicle speed of the vehicle exceeds a predetermined value for a certain time, or when the vehicle speed is lower than a predetermined value, or the vehicle speed of the vehicle exceeds a predetermined value. In the case where the ratio of the time or the time under time per unit time exceeds a predetermined value.
[0017]
Further, in the present invention, there is further provided occupant detection means for detecting whether or not another occupant is on the vehicle, and the calculation means has the other occupant boarded by the occupant detection means. Is detected, the calculated value A_nInstead of A₃F_n= F_n-1+ A₃Or by a predetermined value α._n= F_n-1+ Α · A_nThe fatigue degree can also be calculated by the following formula. When passengers are present, the driver's fatigue level may be uniformly moderated regardless of their direction, and the fatigue level is calculated regardless of the driver's direction. By doing or correcting, the degree of fatigue can be calculated more accurately.
[0018]
In the present invention, it further comprises output detection means for detecting whether or not music is being output in the vehicle, and the calculation means detects that the music is being output by the output detection means. If calculated, the calculated value A_nInstead of A₄F_n= F_n-1+ A₄Or by a predetermined value β._n= F_n-1+ Β · A_nThe fatigue degree can also be calculated by the following formula. When the driver is listening to music output from the radio or audio play, the driver's fatigue may be moderately uniform regardless of the orientation, The degree of fatigue can be calculated more accurately by calculating or correcting the degree of fatigue regardless of the driver's orientation.
[0019]
Further, in the present invention, it further includes an imaging unit that images the driver's pupil, and a measurement unit that measures the degree of opening of the pupil from an image captured by the imaging unit, and the calculation unit includes: Different calculations may be performed according to the tropism information stored in the storage means and the degree of pupil opening measured by the measurement means. The driver's pupil opening degree is reflected in the driver's interest in driving, and the driver's fatigue due to the driver's interest in driving is influenced by the tropism. The degree of fatigue can be calculated more accurately by performing different calculations according to the degree of pupil opening and the driver's orientation.
[0020]
Although it can be said that the degree of opening of the driver's pupil is a kind of physiological data, in the present invention, since this is detected by photographing the pupil, it is not necessary to attach any measuring instrument or the like to the driver's body.
[0021]
In the present invention, it further comprises an operation amount detection means for detecting an operation amount per unit time of the driver for the vehicle, wherein the calculation means includes the direction information stored in the storage means and the operation information. Different calculations can be performed in accordance with the operation amount detected by the amount detection means. Focusing on the fact that the amount of driver's operation is reflected in the driver's fatigue level and influenced by its tropism, and different calculations are performed depending on the driver's operation amount and the driver's tropism. By doing so, the degree of fatigue can be calculated more accurately.
[0022]
In the present invention, the traveling environment detecting means can detect a plurality of types of traveling environments. By detecting a plurality of types of driving environments and using them for calculating the fatigue level, the fatigue level can be calculated more accurately.
[0023]
The present invention further includes a table in which a numerical value indicating the degree of influence on the fatigue level of the driver is recorded for each type of the driving environment, and the calculation means is configured to determine the driver's fatigue based on the table. The degree of fatigue can also be calculated. By preparing the table in advance, the degree of fatigue can be calculated more easily.
[0024]
In the present invention, the tropism information is information indicating whether the driver is an extrovert person or an introversion person, and the calculation means is the travel environment detected by the travel environment detection means. Depending on the degree of monotony, if the degree of monotony is high, the degree of fatigue is calculated higher in the case where the tropism information shows introversion than in the case where the tropism information shows introversion, and if the degree of monotony is low It is also possible to calculate the degree of fatigue higher in the case where the directional information indicates introversion than in the case where the directional information indicates extroversion. Focused on the fact that those who are extroverted tend to feel fatigue due to a monotonous load, while those who are introverted tend to feel less tired due to a monotonous load. It is possible to calculate the degree of fatigue according to the driver's tropism.
[0025]
Moreover, in this invention, the alerting | reporting means which alert | reports a driver | operator according to the said fatigue degree calculated by the said calculating means can also be provided. By notifying according to a driver | operator's fatigue degree, a driver | operator with a high fatigue degree can be alerted, for example. Examples of the contents of notification include notification by voice, notification by information display, notification by changing the emission color of the instrument panel, and the like.
[0026]
The present invention may further include an output unit that outputs a control command for the vehicle or a device mounted on the vehicle according to the degree of fatigue calculated by the calculation unit. By controlling the vehicle or the device mounted on the vehicle according to the driver's fatigue level, a driver with a high fatigue level can be supported.
[0027]
Examples of control commands for the vehicle include those related to travel control. For example, when the ACC (Adaptive Cruise Control) is adopted, the set distance is increased or the set speed is decreased. Moreover, when DSC (Dynamic Stability Control) is employ | adopted, the timing at which danger avoidance assistance operates is mentioned early.
[0028]
Examples of control commands for equipment mounted on the vehicle include those related to control that enhances the activity of the driver. For example, it is possible to provide a massage machine in the seat, drive it, and release negative ions from the air conditioner. In addition, the type of information displayed on the car navigation system can be switched to traffic-related information to increase safety, and a break time can be set during the travel planning in the car navigation system to guide the driver to the rest area. For example, changing a travel plan.
[0029]
DETAILED DESCRIPTION OF THE INVENTION
Preferred embodiments of the present invention will be described below with reference to the drawings. FIG. 1 is a schematic diagram of a vehicle (a passenger car is assumed in this embodiment) to which a support device according to an embodiment of the present invention is applied, and FIG. 2 is a block diagram of the support device according to the embodiment of the present invention. Hereinafter, the configuration of the support device of the present embodiment will be described with reference to both the drawings.
[0030]
<Device configuration>
The CPU 101 is a processor that controls the entire support apparatus, and particularly performs processing to be described later. An EEPROM (Electronically Erasable and Programmable Read Only Memory) 102 is a memory for storing fixed data in addition to a program for each process described later. A RAM (Random Access Memory) 103 has a work area for programs processed by the CPU 101 and stores variable data and the like. Needless to say, other storage means may be employed as the ROM 102 and the RAM 103. The clock IC 104 provides time information to the CPU 101.
[0031]
The interface 105 relays input or output of information between the CPU 101 and each device described below, and one or more interfaces 105 are provided depending on the type of each device.
[0032]
The CCD camera 111 for photographing a landscape is a camera that captures a landscape image in front of the vehicle, and is installed so as to be able to generally capture the field of view of the driving vehicle of the vehicle. The image processing circuit 111a is a circuit for processing a landscape image taken by the CCD camera 111 for landscape photography. In this embodiment, various objects in the landscape image, for example, by extracting feature amounts from the landscape image, for example, The presence / absence of road structures, pedestrians, other vehicles, stores and other structures are output.
[0033]
The pupil photographing CCD camera 112 is a camera for photographing the face of the driving vehicle of the vehicle, particularly the pupil, and is installed facing the face of the driving vehicle in the passenger compartment. The image processing circuit 112a is a circuit for processing a pupil image photographed by the pupil photographing CCD camera 112, and measures the pupil diameter and outputs the measurement result in order to measure the degree of opening of the pupil of the driving car.
[0034]
The car navigation device 113 is a device that provides vehicle operation information to the driver of the vehicle, and includes a receiver that receives a signal from a satellite by a GPS system, a display that displays information, an input device, and the like. The car navigation device 113 has a map information DB (database) 113a, and can obtain information on roads being traveled.
[0035]
The VICS information receiver 114 is a receiver that receives traffic information of a VICS system distributed from a beacon. The received traffic information can be output on the display of the car navigation device 113. The telematics device 115 is a device that acquires information distributed over the Internet by wireless communication, and generally can communicate by connecting a mobile phone or the like. The received various information can be output on the display of the car navigation device 113.
[0036]
The laser radar device 116 detects an object ahead of the vehicle by outputting a laser and receiving the reflected wave. The vehicle speed sensor 117 is a sensor that measures the traveling speed of the vehicle. For example, the speed of the engine is detected and converted into a vehicle speed. The steering angle sensor 118 is a sensor that detects the steering angle of the steering wheel, and is one of the sensors that detect the operation amount of the driving vehicle with respect to the vehicle. In addition to this, as a sensor for detecting the operation amount of the driving vehicle with respect to the vehicle, a sensor for detecting the operation amount of the accelerator or the brake may be provided.
[0037]
The illuminance sensor 119 is a sensor that detects the illuminance of sunlight, and the detection result is used for discrimination between day and night. The seating sensor 120 is a sensor that detects whether there is an occupant other than the driver, and is provided in each seat other than the driver's seat, and detects whether there is an occupant in each seat.
[0038]
The audio device 121 is a cassette deck, a CD player, or the like, and outputs music in the passenger compartment. The air conditioner 122 is a device that air-conditions the passenger compartment. The vehicle control device 123 is, for example, ACC or DSC. The massage machine 124 is attached to the driver's seat and massages the driver. The lamps 125 are lamps provided for each instrument of the instrument panel, for example.
[0039]
<Fatigue level judgment principle>
Next, the principle of determination of the fatigue level in this embodiment will be described. In the present embodiment, attention is paid to the fact that the driver's fatigue level, particularly mental fatigue level, when driving the vehicle depends on the traveling environment of the vehicle. In particular, we focus on the fact that the scenery that the driver sees when driving becomes the driver's load depending on the type, and affects the degree of mental fatigue. Therefore, by detecting the driving environment and calculating the degree of fatigue, it is possible to eliminate the need for attaching a measuring instrument or the like to the driver's body and to eliminate the driver's troublesomeness.
[0040]
Although various definitions are possible for such a load, in the present embodiment, three load elements of an attractiveness level, a messy level, and a negative impression level are employed. The degree of attraction is the number of objects that the driver is naturally attracted to, and is the degree to which the driver's attention, concentration, and alertness are raised. The degree of mess is the degree of change and monotony of the driver's landscape. The negative impression level is a negative impression caused by the scenery seen by the driver, for example, a degree of pressure, danger, and irritation.
[0041]
Next, in the present embodiment, these three load elements are quantified in relation to the driving environment so that the driver's fatigue level can be calculated more easily. FIG. 11 is an evaluation value table in which the relationship between load elements and various driving environments is evaluated numerically, and shows the numerical value of the degree of influence of each driving environment on the driver's mental fatigue. In this embodiment, the data of this evaluation value table is stored in the EEPROM 102 and used when calculating the fatigue level.
[0042]
This evaluation value table is created on the basis of a questionnaire for a plurality of subjects who drive a car on a daily basis, which is performed in the creation process of the present invention. This questionnaire presents dozens of types of landscape images, and answers the above-described three load elements received from each landscape image in multiple stages.
[0043]
In the evaluation value table, landscape images presented to the subject are grouped according to the presence or absence of each driving environment element, and evaluation values 0 to 3 are given. The higher the evaluation value, the greater the influence on the fatigue level. The evaluation value is added depending on the presence or absence of each driving environment element in the driving environment.
[0044]
For example, when “curve”, “pedestrian”, “bike”, and “street parking” exist in a certain driving environment, the degree of attraction L1 is 2 + 3 + 3 + 2 = 10 points. The messiness L2 is 2 + 3 + 2 + 3 = 10 points. The negative impression level L3 is 3 + 2 + 2 + 2 = 9 points.
[0045]
According to this evaluation value table, road environmental factors such as the presence of curves, the presence of sidewalks and guardrails affect negative impressions, and surrounding traffic elements such as the presence of pedestrians and bicycles are attractive. It can be seen that the distance between the cars and the congestion such as traffic jams affect the degree of mess, which is close to actual experience. In the above questionnaire, driving environment elements other than those described in the evaluation value table of FIG. 11 are also targeted, but elements that did not affect the evaluation value are deleted.
[0046]
<Driver orientation>
As described above, in this embodiment, the driver's fatigue level is determined based on the driving environment. However, in this embodiment, it is further noted that the fatigue level received from the driving environment varies depending on the driver's tendency. Depending on the operation.
[0047]
There are introverts and extroverts in human tropism, and there is a difference between the direction in which psychological energy works mainly toward the object (outward) or toward the subject (inward). It is extroverted that pays attention to things in the outside world, and that thoughts, emotions, and behaviors tend to work for the outside world. On the other hand, introvert is a habit of being more interested in self than in the outside world and tending to think and fantasize within the inner world.
[0048]
・ Characteristics of extroversion
Physiological aspects:
Has an excitatory nervous system for stimuli and tends to pursue stimuli (high stimulus craving). In response to stimulation, brain activity tends to be activated.
Emotional aspect: emotional expression is free and active, mood flow is fast, and things are not stuck. It's light and I don't give up.
Intentional aspects:
Energetic and independent, with a talent for leadership. They are fast-decisive and powerful, but sometimes they are not thoughtful. It is rough and easy to get tired of, but it is quick to adapt to new situations.
The ideological aspect:
There is no common sense and strange place, and it is generally eclectic. Frankly accept other theories.
Social aspects:
I like to hang out with a wide range of people, chatting fluently with fluent tongues and skillful wit. It can be tricked or fooled by others.
・ Introversion characteristics
Physiological aspects:
Has a nervous system that suppresses stimulation, and does not accept stimulation (low stimulation craving). The brain activity tends to be suppressed in response to the stimulus.
Emotional aspects:
Emotional expression is modest and there is little change in mood. I am shy and intimidating, and I tend to worry.
Intentional aspects:
It's poorly executed but thoughtful and conscientiously persists in what it has begun. It takes time to adapt to new situations due to its stiffness. There is no initiative and it is submissive. He prefers precise, delicate work that is not complicated by human relationships.
The ideological aspect:
He is skeptical and critical, but has a long history of theoretical analysis. He sticks to his own theory and sometimes loses sight of the big picture by sticking to minor things.
Social aspects:
I do not like having various negotiations with others. The friendship range is narrow and it is difficult to make friends. It is sensitive to criticism and opinions from others, and this can easily hurt feelings.
[0049]
Due to the difference in tropism, when the load on the driving environment is large (there is a lot of stimulation), introverts are prone to fatigue due to a large decrease in activity level, whereas extroverts are more active The level is lowered and fatigue is difficult. On the other hand, when the load on the driving environment is small (stimulus is small), the extroverted person tends to get tired due to a large decrease in the activity level, whereas the introverted person does not decrease the activity level so much Become.
[0050]
That is, if the driving environment is monotonous (highly stimulated), extroverts are more fatigued than introverted, and if monotonous is low (stimulated) Introverts are more fatigued than extroverts. In the present embodiment, basically, in the former case, the extrovert person has a high degree of fatigue and the introvert person has a low degree of fatigue, and in the latter case, the opposite is true.
[0051]
For this reason, in this embodiment, the tropism information indicating whether the driver is inward or outward is stored in the EEPROM 102 in advance and used during calculation. Whether the driver is introverted or extroverted, when using the support device of the present embodiment, the driver can perform a personality analysis questionnaire and the like, and the tropic information can be set according to the result. If multiple drivers are scheduled for one vehicle, set the tropism information for each driver, and input the tropism information corresponding to the driver who is the driver during driving. Should be adopted.
[0052]
<Basic flow>
FIG. 3 is a flowchart showing basic processing executed by the CPU 101 in the support apparatus of this embodiment. In S1, an initial value of the fatigue level F to be calculated is set. When driving for the first time, the fatigue value may be 0, for example. On the other hand, for example, when driving is interrupted and resumed, such as after a break in the parking area, it is considered that the driver's fatigue remains, so calculate from the fatigue value at the time of interruption A value reduced from the fatigue value at the time of interruption can be set as the initial value. In this case, for example, since the extrovert is considered to recover faster than the introvert, the initial value of the fatigue level may be set according to the driver's tropism.
[0053]
In S2, it is determined whether it is the calculation timing of the fatigue level. The calculation of the fatigue level can be performed at intervals of several seconds to several tens of seconds, for example. In S3, processing for detecting the traveling environment is performed. Here, each driving environment element of the evaluation value table shown in FIG. 11 is detected. The detection of the driving environment is performed mainly for the landscape photographing CCD camera 111 and the variable shooting environment elements such as pedestrians, bicycles, preceding cars, side cars, inter-vehicle distances, road parking, and road parking. Extraction from a photographed image by the image processing device 111a and detection by the laser radar device 116 are possible. Further, the brightness can be detected by the illuminance sensor 119.
[0054]
On the other hand, fixed driving environment elements such as curves, the number of lanes, sidewalk classifications, guardrails and the like can be detected mainly from the map information DB 113a of the car navigation device 113 and the current position information by the GPS function. Traffic information such as traffic jams can be detected mainly from the VICS information receiver 114. It is also possible to detect some of these from information on the Internet obtained from the telematics device 115.
[0055]
Next, in S4, the degree of fatigue is calculated based on the traveling environment detected in S3. Details will be described later. In S5, it is determined whether or not the degree of fatigue calculated in S4 exceeds a predetermined value. If not, the process returns to S2, and the above-described processing is repeated. If it has exceeded, the process proceeds to S6 to perform driver assistance processing.
[0056]
In the support process of S6, for example, it is possible to notify the driver of caution. As a notification method, for example, a warning sound can be generated from the car navigation device 113, or a warning can be displayed on the display. It is also possible to notify by changing the emission color of the lamps 125 of the instrument panel to red.
[0057]
In the support process of S6, various control commands may be output to the vehicle or the device mounted on the vehicle. As the control command for the vehicle, for example, when the ACC is adopted, the set distance between the vehicles is reduced or the set speed is lowered when the ACC is adopted, which is dangerous when the DSC is adopted. One example is to speed up the timing at which the avoidance support is activated.
[0058]
As a control command for the device mounted on the vehicle, the massage machine 124 can be driven to massage the driver, or the control command can be output so as to release negative ions from the air conditioner 122. Furthermore, when a travel plan is set in the car navigation device 113, for example, a break time is forcibly set, and the travel plan is changed so as to guide the driver to the rest area. .
[0059]
<Fatigue level calculation>
FIG. 4 is a flowchart showing an example of the fatigue level calculation process in S4. In S11, the load element selection counter i is set to an initial value. In the case of this embodiment, the attractiveness (L₁), Mess (L₂), Negative impression (L₃) Is assumed. Therefore, the selection counter i takes a value of 1 to 3, and i = 1 is set first.
[0060]
In S12, the value of the load element selected by the selection counter i is calculated. The load element value is calculated by extracting a score corresponding to the traveling environment detected in S3 from the evaluation value table described above with reference to FIG. In S13, a coefficient of an arithmetic expression for calculating the degree of fatigue is selected based on the load element value calculated in S12. The coefficient is selected according to the driver's tropism information. Details will be described later.
[0061]
In S14, an additional value A (i) of the fatigue level is calculated. In the present embodiment, the added value is calculated as follows.
[0062]
A (i) = a (i)_x・ | Li-Th |
Where a (i)_xIs a coefficient selected in S13, Li is a load element value, and Th is a threshold value. As is apparent from this equation, the coefficient selected in S13 is a gain coefficient for fatigue. For the term | Li-Th |, (Li-Th)²For example, other arithmetic expressions may be used.
[0063]
In this embodiment, the addition value by each load element is determined in this way, and finally, as shown in S18, the fatigue value F of the nth calculation (n is a natural number)._nIs calculated by adding this added value to the fatigue value calculated in the previous calculation. That is,
F_n= F_n-1+ A_n
And When human fatigue is accumulated over time, the fatigue level is calculated by adding the current added value to the previously calculated fatigue level and calculating the current level of fatigue. be able to. In S14, an individual added value based on each load element value is calculated.
[0064]
In S15, it is determined whether or not the added value has been calculated for all load elements. If not, the process proceeds to S16, and one selection counter i is added, and the process returns to S12. If all have been calculated, the process proceeds to S16, and the sum of the added values calculated for each load element is taken. In S18, the present fatigue degree value is calculated by the above formula, and the process is terminated.
[0065]
Next, an example of the coefficient selection process in S13 will be described with reference to FIG. In the present embodiment, four types of coefficients (12 types in total) are facilitated for each load element, and any one is selected by the processing of FIG. In S21, it is determined whether or not the load element value calculated in S12 exceeds a predetermined threshold Th. In the present embodiment, a coefficient is selected based on the threshold Th and the driver's orientation.
[0066]
If it has exceeded, go to S22 and a (i)₁And a (i)₂Select. After the selection, in S24, the directional information stored in the EEPROM 102 is referred to. If the directional information is inward, the process proceeds to S26 and the coefficient a (i)₁Select. On the other hand, in the case of extroversion, the process proceeds to S27 and a (i)₂Select. The relationship between these two coefficients is, for example, a (i)₁>> a (i)₂If ≧ 0, the introvert is calculated with a higher degree of fatigue than the extrovert.
[0067]
Next, when the load element value calculated in S12 in S21 does not exceed the predetermined threshold Th, the process proceeds to S23, and a (i)₃And a (i)₄Select. After the selection, in S25, the directional information stored in the EEPROM 102 is referred to. If the directional information is inward, the process proceeds to S28 and the coefficient a (i)₃Select. On the other hand, in the case of extroversion, the process proceeds to S29 and a (i)₄Select. The relationship between these two coefficients is, for example, a (i)₄>> a (i)₃If ≧ 0, the extrovert is calculated with a higher degree of fatigue than the introvert.
[0068]
The relationship between the above coefficients is that the introvert is calculated with a higher degree of fatigue when the load element value exceeds the threshold, and the extrovert is calculated with a higher fatigue when the load element value does not exceed the threshold. It will be. This means that a high load factor value is much more irritating and less monotonous for the driver, increasing introvert fatigue, while a lower load factor value means that the driver This is based on the idea of increasing the fatigue of extroverts because there is little stimulation and the degree of monotony is high. As described above, the coefficient is selected, and the fatigue level is calculated.
[0069]
As described above, in this embodiment, when calculating the driver's fatigue level based on the traveling environment of the vehicle, different calculations are performed according to the driver's tropism, so that more accurate fatigue corresponding to each driver can be obtained. The degree can be calculated. Further, as in this embodiment, by selecting and calculating a coefficient according to the driver's tropism, and performing a different calculation, it is possible to easily calculate the fatigue degree according to the driver's tropism. it can.
[0070]
<Fatigue degree calculation modification 1>
Next, a modified example of the above-described fatigue level calculation will be described. FIG. 6 is a flowchart showing the processing of this example. When the degree of fatigue exceeds a certain level, there is almost no influence of the driver's tropism on the degree of fatigue, which may rather cause an error. Therefore, in this example, in such a case, the fatigue level is calculated more accurately by calculating the fatigue level regardless of the driver's orientation.
[0071]
First, in S18 of FIG._nAfter calculating the fatigue degree F in S31_nWhether or not exceeds a predetermined threshold. If not exceeded, the process is terminated, and the fatigue value calculated in S18 of FIG. 4 is determined. When it has exceeded, it progresses to S32 and recalculates a fatigue degree value with the following formula which is not influenced by the driver's tropism, and defines this as the present fatigue degree value.
[0072]
F_n= F_n-1+ A_lim
A_limIs a value determined regardless of the driver's direction, and may be a fixed value (for example, 0) or a variable value (for example, a value that depends only on the driving environment). In any case, it is desirable to make it smaller than the fatigue value calculated in S18.
[0073]
<Fatigue degree calculation modification 2>
Next, another modification of the above-described calculation of the fatigue level will be described. FIG. 7 is a flowchart showing the processing of this example. When the vehicle speed is low or high, there is almost no influence of the driver's tropism on the degree of fatigue, which may be a factor of error. Therefore, in this example, the fatigue level is calculated more accurately by calculating the fatigue level regardless of the driver's orientation in such a case.
[0074]
First, in this example, the vehicle speed sensor 117 constantly measures the vehicle speed. Then, in S17 of FIG._nIn S41, the ratio of the time exceeding a predetermined high-speed side threshold value within a certain time is calculated. For example, if the fixed time is set to 10 minutes and the high speed side threshold is set to 80 km / h, if the vehicle travels for 5 minutes at a vehicle speed exceeding this, the rate is 50%. In S <b> 42, similarly, the proportion of time that falls below a predetermined low speed side threshold within a certain time is calculated. For example, if the fixed time is set to 10 minutes and the low speed side threshold is set to 20 km / h, if the vehicle travels for 5 minutes at a vehicle speed lower than this, the ratio is 50%.
[0075]
In S43, it is determined whether or not the high vehicle speed ratio calculated in S41 exceeds a predetermined threshold. If it has exceeded (that is, the high-speed time is long), the process proceeds to S46, and if not, the process proceeds to S44. In S44, it is determined whether or not the low vehicle speed ratio calculated in S42 exceeds a predetermined threshold. If exceeded (that is, the low speed time is long), the process proceeds to S45, and if not, the process returns to S18 (the added value calculated in S17 is used for the calculation of the fatigue level). In S46, as in S44, it is determined whether the low vehicle speed ratio calculated in S42 has exceeded a predetermined threshold. If exceeded (that is, both the high speed and the low speed are long), the process proceeds to S47, and if not (that is, the high speed is long), the process proceeds to S48).
[0076]
In S45, S47, and S48, the added value A calculated in S17, respectively._nIs determined regardless of the driver's tropism._lim-L(For low vehicle speeds), A_lim-LH(For cases where both high and low times are long), A_lim-HReplace with (for the case where the high vehicle speed is long), and return to S18. Each of these values may be a fixed value, for example.
[0077]
<Fatigue degree calculation modification 3>
Next, still another modified example of the calculation of the fatigue level will be described. FIG. 8A is a flowchart showing the processing of this example. If a passenger is present, the fatigue level of the driver may be moderately moderate regardless of the direction of the driver, so the fatigue level should be calculated or corrected regardless of the driver's direction. Thus, the degree of fatigue is calculated more accurately.
[0078]
First, in S17 of FIG._nIn step S51, it is detected whether there is a passenger other than the driver. Other occupants are determined based on the detection result of the seating sensor 120. In S52, based on the detection result in S51, if another occupant is present, the process proceeds to S53, and if not, the process returns to S18 (the added value calculated in S17 is used for the calculation of the fatigue level).
[0079]
In S53, the added value A calculated in S17._nIs defined independently of the tropism information_limOr by a predetermined value α (0 ≦ α <1), α · A_nReplace with In this case, the value may be changed according to the number of passengers.
[0080]
<Fourth Modification of Fatigue Level Calculation>
Next, still another modified example of the calculation of the fatigue level will be described. FIG. 8B is a flowchart showing the processing of this example. When the driver is listening to music output from the radio or audio play, in other words, when the BGM is playing, the driver's fatigue level is uniformly moderate regardless of the direction. In this case, the degree of fatigue is calculated or corrected more accurately by calculating or correcting the degree of fatigue regardless of the driver's orientation.
[0081]
First, in S17 of FIG._nIn step S61, it is detected whether or not music is being output. The output of music is determined by detecting the driving status of the audio device 121. In S62, based on the detection result of S61, if the music is being output, the process proceeds to S63, and if not, the process returns to S18 (the added value calculated in S17 is used for the calculation of the fatigue level).
[0082]
In S63, the addition value A calculated in S17_nIs defined independently of the tropism information_limOr by a predetermined value β (0 ≦ β <1), β · A_nReplace with In this case, the value may be changed according to the volume and type of music (pops, enka, rock, etc.).
[0083]
<Fifth Modification of Fatigue Level Calculation>
Next, still another modified example of the above-described calculation of the fatigue level will be described. FIG. 9 is a flowchart showing the processing of this example. The driver's pupil opening degree is reflected in the driver's interest in driving, and the driver's fatigue due to the driver's interest in driving can be influenced by the tropism, so the driver's pupil opening degree and driving The degree of fatigue is calculated more accurately by performing different calculations according to the person's tropism.
[0084]
First, in this example, the pupil of the driver is photographed by the pupil photographing CCD camera 112, and the pupil diameter is constantly measured by the image processing circuit 112a. Then, in S17 of FIG._nIn step S71, an average value PD of the driver's pupil diameter for a predetermined time is calculated. In S72, whether or not the average value PD of pupil diameters calculated in S71 is in the range of two thresholds (low threshold: a threshold that is regarded as a state of low interest in driving, high threshold: a threshold that is regarded as a state of high interest in driving). Determine. If it is within the range, the process returns to S18 (the added value calculated in S17 is used for the calculation of the fatigue degree value). If not, the process proceeds to S73.
[0085]
In S73, it is determined whether or not the average value PD of the pupil diameter exceeds the high threshold value. When it does not exceed (becomes less than the low threshold), the process proceeds to S74, and when it exceeds, the process proceeds to S77. In S74, it is determined whether the directional information is introverted or extroverted. If it is introverted, the process proceeds to S75, and if it is extroverted, the process proceeds to S76. In S75 and S76, the added value A_nA_L2, A_H1Replace with
[0086]
In S77, it is determined whether the directional information is introverted or extroverted. If it is introverted, the process proceeds to S78, and if it is extroverted, the process proceeds to S79. In S78 and S79, the added value A_nA_H2, A_L1Replace with The relationship between each added value is A_H1> A_L1, A_H2> A_L2It is. In other words, if the person who is interested in driving continues, the extrovert is not added much fatigue level and the introvert is added more. If the person who is not interested in driving continues, the extrovert is added more fatigue level And introverts are not added much.
[0087]
<Modification 6 of Fatigue Level Calculation>
Next, still another modified example of the above-described calculation of the fatigue level will be described. FIG. 10 is a flowchart showing the processing of this example. Since the driver's operation amount is reflected in the driver's fatigue level and can be influenced by the directionality of the driver, it is more accurate to perform different calculations according to the driver's operation amount and the driver's directionality. Is used to calculate the degree of fatigue. In this embodiment, the steering angle of the steering wheel is used as the target operation amount. However, the present invention is not limited to this, and the operation amount of an accelerator, a brake, or the like may be the target.
[0088]
First, in the case of this example, the steering angle of the driver's steering wheel is always measured by the steering angle sensor 119. Then, in S17 of FIG._nIn step S81, the driver's steering wheel operation amount STR for a predetermined time is calculated by integrating the steering angle. In S82, the steering wheel operation amount STR calculated in S81 has two threshold values (low threshold: a threshold for driving almost a straight line and assuming that the stimulus is low, and high threshold: a handle is frequently operated and the stimulus is considered high. It is determined whether it is in the range of (threshold). If it is within the range, the process returns to S18 (the added value calculated in S17 is used for the calculation of the fatigue degree value). Otherwise, the process proceeds to S83.
[0089]
In S73, it is determined whether or not the handle operation amount STR exceeds the high threshold value. When it does not exceed (becomes less than the low threshold), the process proceeds to S84, and when it exceeds, the process proceeds to S87. In S84, it is determined whether the directional information is introverted or extroverted. If it is introverted, the process proceeds to S85, and if it is extroverted, the process proceeds to S86. In S85 and S86, the added value A_nA_L2, A_H1Replace with
[0090]
In S87, it is determined whether the directional information is introverted or extroverted. If it is introverted, the process proceeds to S88, and if it is extroverted, the process proceeds to S89. In S88 and S89, the added value A_nA_H2, A_L1Replace with The relationship between each added value is A_H1> A_L1, A_H2> A_L2It is. In other words, when a state with a lot of stimulation such as frequent operation of the steering wheel continues, an extrovert is not added much fatigue level, an introvert is added more, and the state where there is little stimulation by running almost straight line For extroverts, the degree of fatigue is added more, and introverts are not added much.
[0091]
【The invention's effect】
As described above, according to the present invention, it is possible to eliminate the annoyance of the driver of the vehicle and more accurately calculate the degree of fatigue corresponding to each driver, thereby favorably assisting the driver. be able to.
[Brief description of the drawings]
FIG. 1 is a schematic view of a vehicle to which a support device according to an embodiment of the present invention is applied.
FIG. 2 is a block diagram of a support device according to an embodiment of the present invention.
FIG. 3 is a flowchart showing an example of processing executed by the support apparatus according to the embodiment of the present invention.
FIG. 4 is a flowchart illustrating an example of a fatigue level calculation process.
FIG. 5 is a flowchart illustrating an example of coefficient selection processing.
FIG. 6 is a flowchart showing a modification of the fatigue level calculation process.
FIG. 7 is a flowchart showing another modified example of the fatigue level calculation process.
FIG. 8 is a flowchart illustrating another modified example of the fatigue level calculation process.
FIG. 9 is a flowchart showing another modification of the fatigue level calculation process.
FIG. 10 is a flowchart showing another modification of the fatigue level calculation process.
FIG. 11 is an example of an evaluation value table.
[Explanation of symbols]
101 CPU, 102 EEPROM, 103 RAM, 104 Clock IC, 105 interface, 111 CCD camera for landscape photography, 112 CCD camera for pupil photography, 111a, 112a Image processing circuit, 113 Car navigation device, 113a Map information database, 114 VICS information Receiver, 115 Telematics device, 116 Laser radar device, 117 Vehicle speed sensor, 118 Steering angle sensor, 119 Illuminance sensor, 120 Seat sensor, 121 Audio device, 122 Air conditioner, 123 Vehicle control device, 124 Massage machine, 125 Lamps

Claims (14)

A support device that assists a driver according to the degree of fatigue of the driver of the vehicle,
Traveling environment detection means for detecting the traveling environment of the vehicle;
Based on the travel environment detected by the travel environment detection means, a calculation means for calculating a driver's fatigue level;
Storage means for storing tropism information indicating the tropism of the driver,
The said calculating means performs a different calculation according to the said directional information memorize | stored in the said memory | storage means, The assistance apparatus characterized by the above-mentioned. In addition,
Selecting means for selecting a coefficient of calculation by the calculating means;
The support device according to claim 1, wherein the calculation unit performs a different calculation by the selection unit selecting the coefficient according to the directional information stored in the storage unit. The calculation means sets the fatigue level at the n-th calculation as F _n, and sets the calculated value calculated based on the travel information as An,
F _n = F _n-1 + A _n
The fatigue level is calculated by the following formula:
It said selecting means, support device according to claim 2, characterized by selecting the coefficients for calculating the A _n. When the fatigue degree F _n exceeds a predetermined level, the calculation means replaces the calculated value An with A ₁ defined independently of the directional information,
F _n = F _n-1 + A ₁
The assist device according to claim 3, wherein the fatigue level is recalculated according to the following formula. Said calculating means, when satisfying the vehicle speed of the vehicle is determined in advance, instead of the calculated value A _n, the A ₂ defined independently of the tropism information,
F _n = F _n-1 + A ₂
The assist device according to claim 2, wherein the fatigue level is calculated by the following formula. In addition,
Occupant detection means for detecting whether another occupant is on the vehicle,
When the occupant detection means detects that another occupant is on board, the calculation means
In place of the calculated value A _n, the A ₃ defined independently of the tropism information,
_{F n = F n-1 +} A 3
Or
With a predetermined value α
F _n = F _n-1 + α · A _n
The assist device according to claim 2, wherein the fatigue level is calculated by the following formula. In addition,
Comprising output detection means for detecting whether music is being output in the vehicle;
When the output detecting means detects that the music is being output, the calculating means
In place of the calculated value A _n, the A ₄ defined independently of the tropism information,
_{F n = F n-1 +} A 4
Or
With a predetermined value β
F _n = F _n−1 + β · A _n
The assist device according to claim 2, wherein the fatigue level is calculated by the following formula. In addition,
Photographing means for photographing the driver's pupil;
Measuring means for measuring the degree of opening of the pupil from an image photographed by the photographing means,
The computing means is
2. The support apparatus according to claim 1, wherein different calculations are performed according to the tropism information stored in the storage unit and the degree of opening of the pupil measured by the measurement unit. In addition,
Comprising an operation amount detection means for detecting an operation amount per unit time of a driver for the vehicle;
The computing means is
The support apparatus according to claim 1, wherein different calculations are performed according to the direction information stored in the storage unit and the operation amount detected by the operation amount detection unit. The support apparatus according to claim 1, wherein the traveling environment detection unit detects a plurality of types of traveling environments. In addition,
A table in which numerical values indicating the degree of influence on the fatigue level of the driver is recorded for each type of the driving environment,
The support device according to claim 10, wherein the calculation unit calculates a driver's fatigue level based on the table. The tropism information is information indicating whether the driver is an extroversion person or an introversion person,
The computing means is
If the degree of monotony is high according to the degree of monotony of the running environment detected by the running environment detection means, the degree of fatigue is higher when the orientation information indicates introversion than when it indicates introversion. The degree of fatigue is calculated to be higher when the directional information indicates introversion than when the tropism information indicates extroversion when the degree of monotony is low. The support apparatus according to the above. In addition,
The support device according to any one of claims 1 to 12, further comprising a notification unit that notifies a driver according to the degree of fatigue calculated by the calculation unit. In addition,
The output means which outputs the control command with respect to the said vehicle or the apparatus mounted in the said vehicle according to the said fatigue degree calculated by the said calculating means is provided. Support device.

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