JP6472709B2 - Car driving ability judgment device - Google Patents
Car driving ability judgment device Download PDFInfo
- Publication number
- JP6472709B2 JP6472709B2 JP2015099450A JP2015099450A JP6472709B2 JP 6472709 B2 JP6472709 B2 JP 6472709B2 JP 2015099450 A JP2015099450 A JP 2015099450A JP 2015099450 A JP2015099450 A JP 2015099450A JP 6472709 B2 JP6472709 B2 JP 6472709B2
- Authority
- JP
- Japan
- Prior art keywords
- driving
- vehicle
- opening rate
- critical
- band
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 230000000007 visual effect Effects 0.000 claims description 42
- 230000000694 effects Effects 0.000 claims description 15
- 210000004556 brain Anatomy 0.000 claims description 13
- 230000036992 cognitive tasks Effects 0.000 claims description 12
- 210000001152 parietal lobe Anatomy 0.000 claims description 5
- 210000000857 visual cortex Anatomy 0.000 claims description 5
- 238000002474 experimental method Methods 0.000 claims description 2
- 238000006073 displacement reaction Methods 0.000 claims 1
- 238000012360 testing method Methods 0.000 description 9
- 230000007177 brain activity Effects 0.000 description 7
- 238000005259 measurement Methods 0.000 description 7
- 238000010586 diagram Methods 0.000 description 6
- 238000000034 method Methods 0.000 description 6
- 238000012545 processing Methods 0.000 description 3
- 230000004044 response Effects 0.000 description 3
- 230000006399 behavior Effects 0.000 description 2
- 230000001149 cognitive effect Effects 0.000 description 2
- 230000007423 decrease Effects 0.000 description 2
- 230000001936 parietal effect Effects 0.000 description 2
- 239000007787 solid Substances 0.000 description 2
- 208000019901 Anxiety disease Diseases 0.000 description 1
- 206010039203 Road traffic accident Diseases 0.000 description 1
- 206010047571 Visual impairment Diseases 0.000 description 1
- 230000036506 anxiety Effects 0.000 description 1
- 230000000903 blocking effect Effects 0.000 description 1
- 230000003930 cognitive ability Effects 0.000 description 1
- 238000010219 correlation analysis Methods 0.000 description 1
- 230000003247 decreasing effect Effects 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 230000010365 information processing Effects 0.000 description 1
- 238000012886 linear function Methods 0.000 description 1
- 238000012417 linear regression Methods 0.000 description 1
- 230000003340 mental effect Effects 0.000 description 1
- 230000003924 mental process Effects 0.000 description 1
- 230000001737 promoting effect Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000012549 training Methods 0.000 description 1
- 230000003945 visual behavior Effects 0.000 description 1
Images
Landscapes
- Measurement And Recording Of Electrical Phenomena And Electrical Characteristics Of The Living Body (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Description
本発明は、例えば、運転免許教習の受講者、高齢者、事故多発者などを対象に、自動車運転能力を客観的に判定するための自動車運転能力判定装置に関する。 The present invention relates to a vehicle driving capability determination device for objectively determining a vehicle driving capability for, for example, a student who has attended a driving license training, an elderly person, and a person with frequent accidents.
本技術分野の背景技術として、特許文献１、２に開示されるような運転シミュレータを用いた自動車運転能力判定装置が知られている。
As a background art of this technical field, an automobile driving ability determination device using a driving simulator as disclosed in
運転シミュレータは、基本的にディスプレイ上に仮想の運転空間を再現し、ハンドル、ブレーキ、アクセルなどの運転操作の的確性や、事故回避能力といったものを判定するものである。
しかし、こうした運転シミュレータは、多額な設備投資を必要とし、テストに時間を要する。しかも、運転シミュレータによる運転能力の計測は、ステアリング、アクセル、ブレーキなどの操作を計測すること自体が目的となっており、課せられた仮想的な運転状況に対して、安全運転の遂行に大きく関わる認知能力や集中力等の適性能力を客観的に評価することは困難である。
また、運転キャリアに大きく左右されるため、実際の運転時、大雨や、雪、霧さらにはトンネルなど、前方視界が急激に悪化したとき、どの程度の対応能力があるかについて、その優劣や衰えを正確に判定することはできなかった。
The driving simulator basically reproduces a virtual driving space on the display, and determines the accuracy of driving operations such as steering wheel, brake, accelerator, etc., and accident avoidance ability.
However, such a driving simulator requires a large amount of capital investment and requires time for testing. Moreover, the measurement of driving ability by the driving simulator is aimed at measuring the steering, accelerator, brake, etc. itself, and is greatly related to the performance of safe driving against the imposed virtual driving situation. It is difficult to objectively evaluate aptitude ability such as cognitive ability and concentration ability.
In addition, since it depends greatly on the driving carrier, when it is actually driving, heavy rain, snow, fog, and tunnels, etc., when the forward visibility suddenly deteriorates, what level of response capability it has, whether it is superior or inferior Could not be determined accurately.
一方、ドライバーの視認行動の計測として、アイカメラ等を使った方法が考えられるが、視線がある場所にあったとしても、必ずしもそこの情報を処理しているとは限らず、“意識のわき見”といわれるような「見ているけど見えていない」という状態や、ハンドル操作にともなう車両の進行方向や道路との位置関係の変化の予測など、行動に現れない心的な処理を計測することは不可能であった。 On the other hand, a method using an eye camera or the like can be considered as a method for measuring the driver's visual behavior. However, even if there is a line of sight, the information is not always processed. Measure mental processes that do not appear in behavior, such as “seeing but not seeing” states, and predicting changes in the vehicle's direction of travel and the positional relationship with the road due to steering wheel operations. Was impossible.
実際の交通事故の原因は、信号無視、漫然運転、脇見運転、動静不注視、安全不確認等、運転者の注意散漫が大きな割合を占めており、運転キャリアの有無に直接関わりなく、認知能力や集中力の低下などがその大きな要因と考えられている。 The actual causes of traffic accidents are disregarded by drivers, such as ignoring traffic lights, sloppy driving, driving aside, unawareness of safety, unconfirmed safety, etc. It is thought that the major factor is the decline in concentration and concentration.
そこで、本発明の目的は、ドライブシミュレータを使用することなく、三次元立体形状を認知する際の脳波を計測することにより、低コストな設備で、しかも、短時間のテストにより、自動車運転能力や適性を正確に判定することにある。 Therefore, the object of the present invention is to measure the brain waves when recognizing a three-dimensional solid shape without using a drive simulator, thereby reducing the cost of driving the vehicle with low-cost equipment and a short test. It is to accurately determine aptitude.
本発明の自動車運転能力判定装置においては、三次元視空間認知課題を表示するディスプレイと、三次元視空間認知課題の回答を入力する回答入力装置と、被験者に装着する脳波計とを備え、三次元視空間認知課題を出題してから一定時間の間、脳波計が検出する部位のうち、後頭部視覚野、頭頂葉、前頭高次運動野のいずれかで検出したγ帯域(３０Ｈｚ前後)の脳波活動強度を記録し、その最大値と、予め実験により定めた運転能力との関係式により、被験者の運転能力を判定するようにした。 The vehicle driving ability determination device of the present invention includes a display that displays a three-dimensional visual space recognition task, an answer input device that inputs an answer to the three-dimensional visual space recognition task, and an electroencephalograph attached to the subject, Electroencephalograms in the γ band (around 30 Hz) detected in any of the occipital visual cortex, parietal lobe, and frontal higher motor areas among the parts detected by the electroencephalograph for a certain period of time after starting the original visual space cognitive task. The activity intensity was recorded, and the driving ability of the subject was determined based on the relational expression between the maximum value and the driving ability determined in advance by experiment.
本発明によれば、実車での運転や自動車運転シミュレータを使用することなく、脳波の計測だけで、視界が阻害されたときの対応能力などの自動車運転能力を客観的に判定でき、個人の認知的な特性に合わせた安全運転の指導や、免許返納促進などに利用することができる。また、道路環境が悪化した場合の運転者の挙動を、危険な運転状況にさらすことなく予測できるので、運転支援システムや道路環境の設計などに利用することができる。 According to the present invention, it is possible to objectively determine the driving ability of a vehicle such as a response ability when the visibility is obstructed only by measuring an electroencephalogram without using a driving in a real vehicle or a driving simulator. It can be used to provide guidance on safe driving tailored to specific characteristics and to promote license return. Further, since the behavior of the driver when the road environment deteriorates can be predicted without being exposed to a dangerous driving situation, it can be used for designing a driving support system or a road environment.
以下、実施例を図面を用いて説明する。 Hereinafter, examples will be described with reference to the drawings.
本実施例では、自動車運転シミュレータを用いることなく、市販のパーソナルコンピュータ等を用いて、ディスプレイ上に三次元視空間認知課題を出題し、被験者が回答を終了するまで、被験者に装着した脳波計の出力を記録、分析する。 In this example, using a commercially available personal computer or the like without using a car driving simulator, a 3D visual space recognition task is presented on the display, and the electroencephalograph attached to the subject until the subject finishes answering. Record and analyze the output.
具体的には、パーソナルコンピュータ上で、検査スタートボタンを押すと、解析装置から三次元視空間認知課題が出題され、被験者は解答入力装置を介して時間内に解答を行う。
ここで、三次元視空間認知課題は、例えば、図１に示すように、ディスプレイに２個の立体画像を表示し、両者が同一の立体を示すものであるか否かを回答するものである。
被験者がこのような三次元視空間認知課題に回答するためには、一方の立体画像を三次元空間で仮想的に回転させ(Mental rotation)、両者が回転対称の関係にあるか否か判断する必要がある。
なお、三次元視空間認知課題としては、３つ以上の立体画像の中から、同一の立体を示す組み合わせを選択するものも好適であり、とくに、両者の間の回転角度が６０°以上になるものを用いた課題に対する脳活動が、後述する運転能力との相関性が高い。
Specifically, when an examination start button is pressed on a personal computer, a three-dimensional visual space recognition task is given from the analysis device, and the subject answers in time via the answer input device.
Here, the three-dimensional visual space recognition task is, for example, as shown in FIG. 1, displaying two stereoscopic images on a display and answering whether or not both indicate the same solid. .
In order for a subject to answer such a 3D visual space recognition task, one of the stereoscopic images is virtually rotated in 3D space (Mental rotation), and it is determined whether or not the two are rotationally symmetric. There is a need.
As a three-dimensional visual space recognition task, it is also preferable to select a combination showing the same three-dimensional image from three or more three-dimensional images. In particular, the rotation angle between the two is 60 ° or more. The brain activity for the task using things has a high correlation with the driving ability described later.
このように、立体画像を仮想的に三次元空間で回転させる際、活発に活動する脳の領域は、後頭部視覚野、頭頂葉、前頭高次運動野といわれている。これらの部位は、それぞれ視覚的に提示された刺激の形の処理、三次元の物体を仮想的に(心の中で)操作する処理、自らの運動を計画・制御する処理等を司ることが認知脳科学的な研究で明らかにされている。脳内におけるこうした処理は、いずれも視覚的に認知される道路状況を理解し、悪化した視界の中での自らの位置や方向を予測して、次の運転操作を計画・制御するために必要とされる部位である。 As described above, when a stereoscopic image is virtually rotated in a three-dimensional space, regions of the brain that are actively active are called the occipital visual cortex, parietal lobe, and frontal higher motor areas. Each of these parts is responsible for the processing of visually presented stimuli, the processing of virtually operating 3D objects (in the mind), the processing of planning and controlling their own movements, etc. It has been clarified in cognitive brain science research. These processes in the brain are all necessary to understand visually perceived road conditions, predict their position and direction in a degraded view, and plan and control the next driving operation. It is a part considered.
三次元視空間認知課題を出題してからの後頭部(後頭部視覚野)と頭頂部(頭頂葉、前頭高次運動野)における脳波の計測結果は、図２のとおりである。
この図から分かるように、後頭部(図２上)、頭頂部(図２下)とも、３０Ｈｚを中心としたγ帯域で、脳の活動強度が明確に増加しているのが分かる。
The measurement results of the electroencephalogram in the occipital region (occipital visual cortex) and the parietal region (parietal lobe, frontal higher motor area) after giving the three-dimensional visual space cognitive task are as shown in FIG.
As can be seen from this figure, it can be seen that the activity intensity of the brain clearly increases in the γ band centered at 30 Hz in both the occipital region (upper part of FIG. 2) and the crown (lower part of FIG. 2).
一方、自動車を安全に運転するためには、視覚により運転環境の変化を正確に認知する能力が求められている。こうした運転環境認知能力は、天候、昼夜、速度により影響を受け、視界が阻害されたときに、蛇行などのふらつきとなって現れ、事故の原因となる。
例えば、ワイパを最速モードで作動させても、十分な視界を確保できないような雨量の場合、ワイパが１往復する時間に対し、視界が確保される時間は、２０％程度に相当するが、これを視界開放率と定義すると、この視界開放率２０％前後では、多くの運転者でふらつき率が上昇し、場合によっては車線を逸脱しかねない限界値に達している。
On the other hand, in order to drive a car safely, the ability to accurately recognize changes in the driving environment visually is required. Such driving environment recognition ability is affected by the weather, day and night, and speed, and when the visibility is obstructed, it appears as wobbling and causes an accident.
For example, when the rainfall is such that sufficient visibility cannot be ensured even when the wiper is operated in the fastest mode, the time to ensure visibility is equivalent to about 20% of the time for the wiper to make one round trip. Is defined as the visibility opening rate, when the visibility opening rate is around 20%, the wobbling rate increases for many drivers, and in some cases reaches a limit value that may deviate from the lane.
そこで、複数の実験対象者に対し、運転シミュレータが提示する画像表示を一定比率で遮ったとき、ふらつきがどの程度発生するかを調べた。
ここで、例えば、図３に示すように、２秒を１周期、すなわち単位時間として、１６００ｍｓは、自動車運転シミュレータによる映像を提示し、残りの４００ｍｓは、自動車運転シミュレータによる運転環境の映像を遮断して、白、グレーあるいは黒一色の画面とした場合、視界開放率は８０％となる。同様に、自動車運転シミュレータによる映像提示時間が１２００ｍｓ、遮断時間が８００ｍｓであるとすれば、視界開放率は６０％となる。
なお、視界開放率は２０％、集中豪雨時にワイパを最速モードで作動させた状態にほぼ匹敵するものである。
Therefore, it was examined how much fluctuation occurred when the image display presented by the driving simulator was blocked at a certain ratio for a plurality of test subjects.
Here, for example, as shown in FIG. 3, with 2 seconds as one period, that is, unit time, 1600 ms presents an image of the driving simulator, and the remaining 400 ms blocks the driving environment image of the driving simulator. In the case of a white, gray or black screen, the field of view rate is 80%. Similarly, if the video presentation time by the automobile driving simulator is 1200 ms and the cut-off time is 800 ms, the visibility opening rate is 60%.
The visibility opening rate is 20%, which is almost equivalent to the state in which the wiper is operated in the fastest mode during heavy rain.
なお、この実施例では、視界開放／遮断を行う単位時間を２秒とした。この単位時間は、短すぎると、視界開放率を小さくしても、残像により映像情報の変化が取得されるため、運転ディマンドを高めることができない。一方、単位時間を長くすぎると、視界開放率を小さくした場合、次の視界開放まで運転環境の変化が大きすぎて、遮断時間が１.２秒を超えると、いかに優れた運転者でも、次に運転環境が提示された瞬間、大きくふらついてしまい、運転能力が低い者との判別ができなくなってしまう。
この観点で、単位時間は１.２秒から４秒の範囲、好ましくは２秒程度とする。
In this embodiment, the unit time for opening / blocking the field of view is 2 seconds. If this unit time is too short, a change in video information is acquired by an afterimage even if the field-of-view opening rate is reduced, so that driving demand cannot be increased. On the other hand, if the unit time is too long, if the visibility rate is reduced, the change in the driving environment is too large until the next visibility release, and if the shut-off time exceeds 1.2 seconds, no matter how good the driver is, As soon as the driving environment is presented, it fluctuates greatly, making it impossible to discriminate from those with low driving ability.
From this viewpoint, the unit time is in the range of 1.2 to 4 seconds, preferably about 2 seconds.
視界開放率を順次減少させていくと、被験者は、視界開放時の視覚情報に対する注意力、集中力を高め、視界遮断時の間、遮断直前の運転状態を記憶し、次の視界開放時に再現するという、運転時における視覚情報取得要求、いわゆる運転ディマンドが高くなっていく。
運転ディマンドに応じた運転タスクの作業成績を評価するため、実験対象者１８名(平均年齢２３.１歳、男性１６名、女性２名)に対し、視界開放率毎に、車速、車両横位置(センターラインからの距離)の変動幅、ステアリング操作量、車間距離の推移を分析した。特定の視界開放率における走行安定性を評価するため、走行区間におけるそれぞれの標準偏差を各指標に基づいて算出した。
When the visual field opening rate is gradually decreased, the subject increases the attention and concentration of visual information when the visual field is opened, remembers the driving state immediately before the visual field is shut off, and reproduces it when the next visual field is opened. Demand for visual information acquisition during driving, so-called driving demand, increases.
In order to evaluate the work performance of the driving task according to the driving demand, for the 18 test subjects (average age 23.1 years, 16 men, 2 women) We analyzed changes in the fluctuation range (distance from the center line), steering operation amount, and inter-vehicle distance. In order to evaluate the running stability at a specific view opening rate, each standard deviation in the running section was calculated based on each index.
図４は、そのうち、視界開放率(横軸)毎の車両横位置変動幅の標準偏差(縦軸 単位はｍ)を示す。特に、視界開放率６０％と８０％の間で、いわゆるふらつき率が上昇し始めていることが確認できる。そして、ワイパを最速モードで作動させても、十分な視界を確保できないような雨量に相当する視界開放率２０％前後では、すべての実験対象者でふらつき率が上昇し、実験対象者によっては車線を逸脱しかねない限界値に達している。 FIG. 4 shows the standard deviation (m is the unit of the vertical axis) of the vehicle lateral position fluctuation width for each visibility opening rate (horizontal axis). In particular, it can be confirmed that the so-called wandering rate starts to increase between the visibility opening rate of 60% and 80%. And even if the wiper is operated in the fastest mode, when the visibility opening rate is around 20%, which corresponds to the amount of rainfall that cannot secure sufficient visibility, the fluctuation rate increases for all test subjects, and depending on the test subject, the lane The limit value that could deviate from has been reached.
この結果から分かるように、あるグループでは、視界開放率が６０％に到るまで、両横位置変動幅の標準偏差が０.４ｍ弱を維持し、視界開放率が低下するにつれ、両横位置の標準偏差が増加している。
他のグループでは、視界開放率が７０％を下回った付近で、両横位置変動幅の標準偏差が０.４ｍ強から上昇し始め、最初のグループと比較して上昇率も高い。
As can be seen from this result, in a certain group, the standard deviation of both lateral position fluctuation widths is kept less than 0.4 m until the visibility opening ratio reaches 60%, and as the visibility opening ratio decreases, The standard deviation of has increased.
In the other groups, the standard deviation of both lateral position fluctuation widths starts to rise from a little over 0.4 m around the point where the visibility rate is below 70%, and the rate of increase is higher than that of the first group.
視界遮断により発生するふらつきは、視界遮断の間、直前の映像情報を正確に保持することができず、映像情報が得られないことの不安や、次に提示される映像情報に驚いて、ステアリング操作が不安定になったことによるものと考えることができる。
すなわち、ふらつき率が上昇し始める視界開放率が低いほど、視覚情報に対する注意力、集中力が高く、認知情報処理能力の配分を優先的に視覚情報に配分し、豪雨等で視界が遮られたときでも、直前の映像情報を正確に保持していることを意味する。そこで、視界開放率とふらつき率との関係をホッケースティック回帰法(一連のデータのうちのどこかに変曲点があって、それよりも大きい場合と小さい場合とで、線形回帰の傾きが異なる場合に、それぞれの傾きと変曲点を推定する方法)を用いることで、個人毎にふらつき率が上昇し始める視界開放率、すなわち、臨界視界開放率を特定すると、臨界視界開放率が低いほど、高い運転ディマンドに対応できる優れた運転能力を備えた者と評価することができる。
The wobbling caused by the visual field cut-off can not hold the previous video information accurately during the visual cut-off, and is surprised by the anxiety that the video information cannot be obtained and the video information presented next. It can be considered that the operation has become unstable.
In other words, the lower the visibility rate at which the wandering rate starts to increase, the higher the attention and concentration of visual information, and the allocation of cognitive information processing ability is preferentially allocated to visual information, and the view is blocked by heavy rain. Sometimes, it means that the previous video information is held correctly. Therefore, the relationship between the visibility rate and the stagger rate is expressed by the hockey stick regression method (the slope of linear regression differs depending on whether there is an inflection point somewhere in the series of data, and it is larger or smaller). In this case, by using the method of estimating each inclination and inflection point), the visibility opening rate at which the wobbling rate starts to increase for each individual, that is, the critical visibility opening rate is specified. It can be evaluated as a person with excellent driving ability that can cope with high driving demands.
一方、実験対象者の一人に対し、前述の三次元視空間認知課題を出題した際、脳波計のうち頭頂部に位置する電極(Ｐ３位置)における脳活動強度の計測結果を図５に示す。
なお、図５は、計測された脳波信号を、認知課題呈示の前後数百ミリ秒の時間窓で切り出し、短時間ＦＦＴ(Fast Fourier Transform)あるいはウェーブレット変換を用いて時間周波数表現に変換し、時間周波数表現に変換された前頭部の脳波信号のうち、γ帯域(３０Ｈｚ前後)の信号パワーを抽出したものである。横軸は、三次元視空間認知課題を提示してからの時間(ｍｓ)であり、縦軸は、脳活動強度計測値の周波数(Ｈｚ)であり、出題後７００ｍｓ前後から１０００ｍｓ(１秒)にかけて、前頭部γ帯域(３０Ｈｚ前後)の脳波活動強度が最高レベルに達している。
On the other hand, FIG. 5 shows the measurement result of the brain activity intensity at the electrode (P3 position) in the top of the electroencephalograph when the above-mentioned 3D visual space recognition task is given to one of the test subjects.
In FIG. 5, the measured electroencephalogram signal is cut out with a time window of several hundred milliseconds before and after the presentation of the cognitive task, and converted into a time-frequency representation using a short-time FFT (Fast Fourier Transform) or wavelet transform. The signal power in the γ band (around 30 Hz) is extracted from the electroencephalogram signal of the frontal region converted into the frequency expression. The horizontal axis is the time (ms) since the presentation of the three-dimensional visual space cognitive task, and the vertical axis is the frequency (Hz) of the brain activity intensity measurement value, from about 700 ms to 1000 ms (1 second) after the question is given. In the meantime, the electroencephalogram activity intensity in the frontal gamma band (around 30 Hz) has reached the highest level.
前述のように視界開放率とふらつき率を計測した実験対象者すべてに対し、三次元視空間認知課題を出題したときの前頭部γ帯域の最大脳波活動強度(ｄＢ)を計測し、視界開放率を、ほぼすべての実験対象者にとって臨界視界開放率以下となる６０％としたときの車両横位置の標準偏差との関係を図６に示す。
ここで、相関係数(corr coef)は、ピアソンの積率相関係数を指し、認知課題遂行中のγ帯域脳活動強度(最大値)と、臨界視界開放率の間にどの程度線形な関係があるのか、その強さを示す指標であり、一般に相関係数「−０.７５５」は強い負の相関にあることを示している。すなわち、認知課題遂行中のγ帯域脳活動パワーが大きな人は、自動車運転課題での横方向ふらつきが小さいことを裏付けている。
As described above, the maximum brain wave activity intensity (dB) in the frontal gamma band when a 3D visual space cognitive task is presented is measured for all subjects who have measured the visibility rate and the fluctuation rate. FIG. 6 shows the relationship with the standard deviation of the vehicle lateral position when the rate is 60%, which is less than or equal to the critical view opening rate for almost all test subjects.
Here, the correlation coefficient (corr coef) refers to Pearson's product moment correlation coefficient, and how linear the relationship is between the gamma-band brain activity intensity (maximum value) during the cognitive task and the critical visibility opening rate. The correlation coefficient “−0.755” generally indicates a strong negative correlation. That is, it is confirmed that a person with a large γ-band brain activity power during the cognitive task performs a small amount of lateral wobbling in the car driving task.
また、pの値は、まったく相関のない２種類のデータに相関解析を行った場合、偶然、相関係数が得られる確率を表しており、通常、ｐ＜０.０５あるいはｐ＜０.０１の場合に「その相関係数は統計的に有意(偶然でない)」と見なされる。今回の結果は、ｐ＝０.０００２であり、０.０１より十分小さく、二つのデータの間に有意な相関関係があることが裏付けられている。 The value of p represents the probability that a correlation coefficient will be obtained by chance when correlation analysis is performed on two types of data that have no correlation at all. Usually, p <0.05 or p <0.01. In the case of “the correlation coefficient is statistically significant (not coincidental)”. The result of this time is p = 0.0002, which is sufficiently smaller than 0.01, confirming that there is a significant correlation between the two data.
同様に、三次元視空間認知課題を出題したときの前頭部γ帯域の最大脳波活動強度と、臨界視界開放率との関係を図７に示す。この場合、相関係数(corr coef)は、「−０.６２５」、ｐ＝０.０４であり、やはり強い負の相関にあることが分かる。このことは、後頭部で計測したγ帯域脳活動強度についても同様のことがいえる。 Similarly, FIG. 7 shows the relationship between the maximum brain wave activity intensity in the frontal γ band and the critical visual field opening rate when a three-dimensional visual space recognition task is presented. In this case, the correlation coefficient (corr coef) is “−0.625” and p = 0.04, and it can be seen that there is also a strong negative correlation. The same can be said for the γ-band brain activity intensity measured at the back of the head.
なお、三次元視空間認知課題を出題したときの前頭部γ帯域の脳波活動強度と、三次元視空間認知課題を出題したときの反応時間、正答率と、臨界視界開放率との関係についても同様に分析したが、相関係数(corr coef)は、前者で「−０.０６５」、後者で「−０.０３１」となり、有意な相関関係は認められなかった。 Regarding the relationship between the brain wave activity intensity in the frontal γ band when the 3D visual space recognition task is given, the response time, the correct answer rate, and the critical visibility release rate when the 3D visual space recognition task is given The correlation coefficient (corr coef) was “−0.065” in the former and “−0.031” in the latter, and no significant correlation was observed.
以上の結果から、より多くの実験対象者に対し、例えば、視界開放率６０％等、臨界視界開放率以下となる視界開放率でのふらつき率、あるいは、臨界視界開放率を計測し、三次元視空間認知課題を出題したときの前頭部γ帯域の脳波活動強度との関係を最小二乗法などを用いて、関係式(一次関数あるいはさらに高次の関数)を求めることで、被験者が、三次元視空間認知課題を出題したときの前頭部γ帯域の脳波活動強度を計測するだけで、強い相関関係をもって運転能力を推定できることが裏付けられる。
Based on the above results, for a larger number of test subjects, for example, the wobbling rate at the visual field opening rate that is below the critical visual field opening rate, such as the visual
以上説明したように、本発明によれば、実車での運転や自動車運転シミュレータを使用することなく、脳波の計測だけで、視界が阻害されたときの対応能力など、自動車運転能力を客観的に判定できるので、交通安全対策を推進するための基礎データを収集する手段として、広く採用されることが期待される。 As described above, according to the present invention, it is possible to objectively evaluate the driving ability of the vehicle, such as the ability to respond when the field of view is obstructed only by measuring the electroencephalogram without using an actual vehicle or a driving simulator. Since it can be determined, it is expected to be widely adopted as a means of collecting basic data for promoting traffic safety measures.
Claims (3)
前記三次元視空間認知課題の回答を入力する回答入力装置と、
被験者に装着する脳波計とを備え、
前記三次元視空間認知課題を出題してから一定時間の間、前記脳波計が検出する部位のうち、後頭部視覚野、頭頂葉、前頭高次運動野のいずれかで検出したγ帯域の脳波活動強度を記録し、その最大値と、予め実験により定めた運転能力との関係式により、被験者の運転能力を判定するようにしたことを特徴とする自動車運転能力判定装置。 A display for displaying a three-dimensional visual space cognitive task;
An answer input device for inputting an answer to the three-dimensional visual space recognition task;
An electroencephalograph to be worn by the subject,
The γ-band EEG activity detected in any of the occipital visual cortex, parietal lobe, and frontal higher motor areas among the parts detected by the electroencephalograph for a certain period of time after the 3D visual space cognitive task is presented. An automobile driving ability determination device characterized in that the strength is recorded, and the driving ability of the subject is determined by a relational expression between the maximum value and the driving ability determined in advance by experiment.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP2015099450A JP6472709B2 (en) | 2015-05-14 | 2015-05-14 | Car driving ability judgment device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP2015099450A JP6472709B2 (en) | 2015-05-14 | 2015-05-14 | Car driving ability judgment device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| JP2016214311A JP2016214311A (en) | 2016-12-22 |
| JP6472709B2 true JP6472709B2 (en) | 2019-02-20 |
Family
ID=57579424
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP2015099450A Active JP6472709B2 (en) | 2015-05-14 | 2015-05-14 | Car driving ability judgment device |
Country Status (1)
| Country | Link |
|---|---|
| JP (1) | JP6472709B2 (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP7465719B2 (en) | 2020-05-18 | 2024-04-11 | 日産自動車株式会社 | Vehicle driving ability determination device and vehicle driving ability determination method |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114103998B (en) * | 2021-12-03 | 2024-03-19 | 智己汽车科技有限公司 | Intelligent driving vehicle control method, system and device based on driver sight line |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5295491A (en) * | 1991-09-26 | 1994-03-22 | Sam Technology, Inc. | Non-invasive human neurocognitive performance capability testing method and system |
| JP2008006007A (en) * | 2006-06-28 | 2008-01-17 | Toyota Motor Corp | Monitor for driver's biological condition and control system |
| EP2401963B1 (en) * | 2009-10-15 | 2016-09-14 | Panasonic Intellectual Property Management Co., Ltd. | Driving attention amount determination device, method, and computer program |
| JP6051836B2 (en) * | 2012-12-18 | 2016-12-27 | 株式会社オートネットワーク技術研究所 | Driving operation device and virtual driving system |
-
2015
- 2015-05-14 JP JP2015099450A patent/JP6472709B2/en active Active
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP7465719B2 (en) | 2020-05-18 | 2024-04-11 | 日産自動車株式会社 | Vehicle driving ability determination device and vehicle driving ability determination method |
Also Published As
| Publication number | Publication date |
|---|---|
| JP2016214311A (en) | 2016-12-22 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| JP6307629B2 (en) | Method and apparatus for detecting safe driving state of driver | |
| Li et al. | Influence of traffic congestion on driver behavior in post-congestion driving | |
| CA2649731C (en) | An unobtrusive driver drowsiness detection method | |
| US9174652B2 (en) | System and method for reducing driving skill atrophy | |
| Zhenhai et al. | Driver drowsiness detection based on time series analysis of steering wheel angular velocity | |
| Vetturi et al. | Use of eye tracking device to evaluate the driver’s behaviour and the infrastructures quality in relation to road safety | |
| Diederichs et al. | Driver intention algorithm for pedestrian protection and automated emergency braking systems | |
| Wang et al. | What is the difference in driver’s lateral control ability during naturalistic distracted driving and normal driving? A case study on a real highway | |
| Hajiseyedjavadi et al. | Effectiveness of visual warnings on young drivers hazard anticipation and hazard mitigation abilities | |
| DE102014201036A1 (en) | Image-based classification of driver status and / or driver behavior | |
| Mortazavi et al. | Effect of drowsiness on driving performance variables of commercial vehicle drivers | |
| Koh et al. | Smartphone-based modeling and detection of aggressiveness reactions in senior drivers | |
| Lethaus et al. | Do eye movements reflect driving manoeuvres? | |
| Mizoguchi et al. | A new approach to detecting distracted car drivers using eye-movement data | |
| JP6206867B2 (en) | Automobile safety driving ability measurement system | |
| JP6472709B2 (en) | Car driving ability judgment device | |
| DE102013226773A1 (en) | Apparatus, method and computer program for assisting a course change of a vehicle | |
| JP6501114B2 (en) | Vehicle driving ability judgment device | |
| GB2595895A (en) | Method for detecting safety relevant driving distraction | |
| JP6466250B2 (en) | Car driving ability judgment device and car driving ability judgment method | |
| Inman et al. | Cooperative adaptive cruise control human factors study: Experiment 1-workload, distraction, arousal, and trust | |
| Talamonti et al. | Eye glance and head turn correspondence during secondary task performance in simulator driving | |
| JP6582799B2 (en) | Support apparatus and support method | |
| Fuchs et al. | Night vision-reduced driver distraction, improved safety and satisfaction | |
| JP7369776B2 (en) | Operation incident image display system, method and program |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| A621 | Written request for application examination |
Free format text: JAPANESE INTERMEDIATE CODE: A621 Effective date: 20171225 |
|
| A977 | Report on retrieval |
Free format text: JAPANESE INTERMEDIATE CODE: A971007 Effective date: 20181022 |
|
| A131 | Notification of reasons for refusal |
Free format text: JAPANESE INTERMEDIATE CODE: A131 Effective date: 20181106 |
|
| A521 | Request for written amendment filed |
Free format text: JAPANESE INTERMEDIATE CODE: A523 Effective date: 20181226 |
|
| TRDD | Decision of grant or rejection written | ||
| A01 | Written decision to grant a patent or to grant a registration (utility model) |
Free format text: JAPANESE INTERMEDIATE CODE: A01 Effective date: 20190122 |
|
| A61 | First payment of annual fees (during grant procedure) |
Free format text: JAPANESE INTERMEDIATE CODE: A61 Effective date: 20190123 |
|
| R150 | Certificate of patent or registration of utility model |
Ref document number: 6472709 Country of ref document: JP Free format text: JAPANESE INTERMEDIATE CODE: R150 |
|
| R250 | Receipt of annual fees |
Free format text: JAPANESE INTERMEDIATE CODE: R250 |
|
| R250 | Receipt of annual fees |
Free format text: JAPANESE INTERMEDIATE CODE: R250 |
|
| R250 | Receipt of annual fees |
Free format text: JAPANESE INTERMEDIATE CODE: R250 |