JP4573076B2 - Information processing apparatus and method, and recording medium - Google Patents

Description

【００６０】
式（７）に従って算出された予測データは、逆動揺生成部１４（図２）に出力される。逆動揺生成部１４は、内部にメモリ（不図示）を備え、そのメモリに自車の車重、バネやダンパなどの特徴を記憶しており、その記憶されている各種のデータを用いて、自車の動揺を低減させるような逆動揺を発生させるための逆動揺データを生成する。逆動揺データは、予測データにより予測された動揺に対して逆方向の、同程度の力を加えるためのデータであり、かつ、上述した自車の車重などを考慮したデータである。
【００６１】
逆動揺生成部１４により生成された逆動揺データは、逆動揺アクチュエータ４に供給される。逆動揺アクチュエータ４は、供給された逆動揺データに基づき、車両１の動揺を制御する。
【００６２】
このように、画像を撮像し、その画像から前車の動揺と自車の動揺を検出することにより、より早く、また精度よく、動揺を検出することができ、その結果、より確実に動揺を低減させることが可能となる。
【００６３】
上述した実施の形態においては、１台の車両１内において、前車の動揺と自車の動揺を検出し、自車の動揺を低減させるための制御を行うようにしたが、２台の車両１において、同様の効果を得られるようにしても良い。そのような場合について以下に説明する。
【００６４】
図１３に示すように、２台の車両１−１，１−２が走行している場合を想定する。車両１−１は、車両１−２の前方を走行している。図１３において、既に説明した部分と同様の部分には、同一の符号を付し、適宜、その説明は省略する。
車両１−１には、撮像部２が搭載されており、前方の画像を撮像するように構成されている。撮像部２により撮像された画像の画像データは、自車動揺検出部１２に出力される。自車動揺検出部１２は、画像データから動揺データを生成し、送信部９１に出力する。送信部９１は、光や電波などの送信手段を用い、入力された動揺データを後続の車両１−２に対して送信する。
【００６５】
車両１−２は、車両１−１の送信部９１により送信された動揺データを受信部９２により受信する。受信部９２により受信された動揺データは、逆動揺生成部９３に出力される。逆動揺生成部９３は、入力された動揺データが示す動揺の逆方向で、同程度の力を車両１−２に加えるための逆動揺データを生成する。逆動揺生成部９３は、自車の車重、バネやダンパなどの特徴を考慮に入れて逆動揺データを生成する。
【００６６】
逆動揺生成部９３により生成された逆動揺データに基づき、逆動揺アクチュエータ４は、車両１−２が受ける動揺が低減されるための制御を行う。
【００６７】
このように、前車が実際に受けた動揺に関する動揺データを後車に送信することにより、後車においては、実際の動揺を受ける前に、その動揺に関する動揺データを取得することが可能となり、その結果、予め受けるであろう動揺に対して、その動揺を低減させるための逆動揺データを生成し、制御することが可能となる。
【００６８】
図１３に示した実施の形態においては、車両１−１と車両１−２は、異なる構成としたが同じ構成としても良い。すなわち、図１４に示すように、車両１−１、車両１−２共に、撮像部２、自車動揺検出部１２、送信部９１、受信部９２、逆動揺生成部９３、および逆動揺アクチュエータ４を備える構成とし、自車が受けた動揺に関する動揺データを後車に送信すると共に、前車から前車が受けた動揺に関する動揺データを受信し、その受信した動揺データに基づいて動揺を低減するための制御を行うようにしても良い。
【００６９】
また、図１３に示した実施の形態においては、車両１−２は、前車が送信した動揺データのみで、自車の動揺を制御する構成であるが、自車の動揺も検出し、その検出した自車の動揺も考慮して逆動揺データを生成するようにしても良い。即ち、図１５に示すように、撮像部２と自車動揺検出部１２を備えることにより、自車の動揺を検出することができ、その検出した動揺に関する動揺データと、受信部９２により受信された前車の動揺データとを用いて、動揺予測部１３で予測データを生成し、その予測データを用いて、逆動揺生成部１４が逆動揺データを生成するようにしても良い。また、図１５に示した構成においては、自車動揺検出部１２からの動揺データは、送信部９１により、後続の他の車両に対して送信される。
【００７０】
なお、上述した実施の形態においては、画像データから動揺データを生成するとしたが、加速度センサなどを用いて動揺データを生成するようにしても良い。
【００７１】
上述した一連の処理は、ハードウェアにより実行させることもできるが、ソフトウェアにより実行させることもできる。一連の処理をソフトウェアにより実行させる場合には、そのソフトウェアを構成するプログラムが専用のハードウェアに組み込まれているコンピュータ、または、各種のプログラムをインストールすることで、各種の機能を実行することが可能な、例えば汎用のパーソナルコンピュータなどに、記録媒体からインストールされる。
【００７２】
この記録媒体は、図１６に示すように、コンピュータとは別に、ユーザにプログラムを提供するために配布される、プログラムが記録されている磁気ディスク１２１（フロッピディスクを含む）、光ディスク１２２（CD-ROM（Compact Disk-Read Only Memory），DVD（Digital Versatile Disk）を含む）、光磁気ディスク１２３（MD（Mini-Disk）を含む）、若しくは半導体メモリ１２４などよりなるパッケージメディアにより構成されるだけでなく、コンピュータに予め組み込まれた状態でユーザに提供される、プログラムが記憶されているROM１０２や記憶部１０８が含まれるハードディスクなどで構成される。
【００７３】
なお、本明細書において、媒体により提供されるプログラムを記述するステップは、記載された順序に従って、時系列的に行われる処理は勿論、必ずしも時系列的に処理されなくとも、並列的あるいは個別に実行される処理をも含むものである。
【００７４】
また、本明細書において、システムとは、複数の装置により構成される装置全体を表すものである。
【００７５】
【発明の効果】
以上の如く本発明によれば、車両が受ける動揺をより確実に低減させることが可能となる。
【図面の簡単な説明】
【図１】本発明を適用した車両１の構成について説明する図である。
【図２】車両１の構成についてさらに説明する図である。
【図３】前車動揺検出部１１の内部構成を示す図である。
【図４】撮像部２により撮像される画像について説明する図である。
【図５】自車動揺検出部１２の内部構成を示す図である。
【図６】特徴情報検出部３１の内部構成を示す図である。
【図７】メモリ４６に記憶されているパターンを示す図である。
【図８】処理される画像を説明する図である。
【図９】算出されるベクトルについて説明する図である。
【図１０】特徴情報処理部３２の内部構成を示す図である。
【図１１】動揺予測部１３の内部構成を示す図である。
【図１２】遅延量、相関係数の算出について説明するための図である。
【図１３】車両１の他の構成について説明する図である。
【図１４】車両１のさらに他の構成について説明する図である。
【図１５】車両１のさらに他の構成について説明する図である。
【図１６】媒体を説明する図である。
【符号の説明】
１ 車両， ２ 撮像部， ３ 車輪， ４ 逆動揺アクチュエータ， ５ 制御部， １１ 前車動揺検出部， １２ 自車動揺検出部， １３ 動揺予測部， １４ 逆動揺生成部， ２１ 前車検出部， ２２ 動きベクトル検出部， ７１ 遅延量算出部， ７２ 遅延器， ７３ 予測器， ７４ 相関算出部， ７５ 重み付け加算部， ９１ 送信部， ９２ 受信部[0001]
BACKGROUND OF THE INVENTION
  The present invention relates to an information processing apparatus and method.,Information processing apparatus and method for reducing fluctuations received by vehicle, particularly regarding recording medium,And a recording medium.
[0002]
[Prior art]
Various technologies have been proposed for safe driving of automobiles. For example, there is a technique for controlling shaking (swaying) using an acceleration sensor or the like.
[0003]
[Problems to be solved by the invention]
The above-described method of controlling a shake using an acceleration sensor has a problem that only a time-delayed control can be performed in order to control the shake after actually sensing the shake.
[0004]
The present invention has been made in view of such a situation, and predicts a shake that will be received from an image captured by a video camera or the like mounted on an automobile so that the shake can be minimized. It is an object to enable safer driving by controlling to the above.
[0005]
[Means for Solving the Problems]
  A first information processing apparatus according to an aspect of the present invention is mounted on a vehicle and includes an imaging unit that captures an image in a traveling direction of the vehicle, and image data of the image captured by the imaging unit. First detection means for detecting a first shake of another vehicle traveling ahead, and a second detection for detecting a second shake received by the vehicle from image data of the image picked up by the image pickup means. And a third shake that the vehicle will receive from the first shake detected by the first detection means and the second shake detected by the second detection means. Predicting means for predicting, and control means for controlling the shaking of the vehicle based on the prediction by the predicting means, the predicting means comprising:Obtained at a given timeThe first shake andHas been detectedThe second upsetDegree of similarityCalculate the first correlation coefficient that representsWhen the first correlation coefficient reaches the maximum value, the time after the first fluctuation is acquired is calculated as the delay amount.The first calculation means, the first predicted value output means for delaying the first fluctuation by the delay amount and outputting it as the first predicted value, and the second fluctuation acquired in the past are used. Based on linear prediction, a second predicted value output means for outputting a second predicted value from the second fluctuation detected by the second detecting means, and the detected by the second detecting means. Second calculating means for calculating a degree of approximation between the second fluctuation and the second predicted value as a second correlation coefficient; the first correlation coefficient; the first predicted value; Generating means for generating prediction data in which the third fluctuation is predicted using the predicted value of 2 and the second correlation coefficient.
[0006]
  A first information processing method according to one aspect of the present invention is an information processing method of an information processing apparatus that is mounted on a vehicle and includes an imaging unit that captures an image in the traveling direction of the vehicle. A first shake of another vehicle traveling in front of the vehicle is detected from the image data of the image, and a second shake received by the vehicle is detected from the image data of the image taken by the imaging means. And predicting a third sway that the vehicle will receive from the first sway and the second sway, and controlling the sway of the vehicle based on the prediction, the prediction comprising:Obtained at a given timeThe first shake andHas been detectedThe second upsetDegree of similarityCalculate the first correlation coefficient that representsWhen the first correlation coefficient reaches the maximum value, the time after the first fluctuation is acquired is calculated as the delay amount.The first fluctuation is delayed by the delay amount, calculated as a first predicted value, and based on linear prediction using the second fluctuation acquired in the past, the second fluctuation is And a degree of approximation between the second fluctuation and the second predicted value is calculated as a second correlation coefficient, the first correlation coefficient, the first predicted value, Using the second predicted value and the second correlation coefficient to generate predicted data in which the third fluctuation is predicted.
[0007]
  A first recording medium according to one aspect of the present invention is a recording in which a computer-readable program that controls an information processing apparatus that is mounted on a vehicle and includes an imaging unit that captures an image in the traveling direction of the vehicle is recorded. In the medium, from the image data of the image picked up by the image pickup means, a first shake of another vehicle traveling in front of the vehicle is detected, and from the image data of the image picked up by the image pickup means, A second shake received by the vehicle is detected, a third shake that the vehicle will receive is predicted from the first shake and the second shake, and the vehicle shake is determined based on the prediction. The prediction includes the step of:Obtained at a given timeThe first shake andHas been detectedThe second upsetDegree of similarityCalculate the first correlation coefficient that representsWhen the first correlation coefficient reaches the maximum value, the time after the first fluctuation is acquired is calculated as the delay amount.The first fluctuation is delayed by the delay amount, calculated as a first predicted value, and based on linear prediction using the second fluctuation acquired in the past, the second fluctuation is And a degree of approximation between the second fluctuation and the second predicted value is calculated as a second correlation coefficient, the first correlation coefficient, the first predicted value, A program for causing a computer to execute processing including a step of generating prediction data in which the third fluctuation is predicted using the second prediction value and the second correlation coefficient is recorded.
[0008]
In the first information processing apparatus and method and the recording medium according to one aspect of the present invention, the first shake of the other vehicle traveling in front of the vehicle and the vehicle received from the image data of the captured image. The second shaking is detected, and the third shaking that the vehicle will receive is predicted from the detected first and second shakings, and the shaking of the vehicle is controlled based on the prediction.
[0009]
  A second information processing apparatus according to an aspect of the present invention is mounted on a vehicle and receives an imaging unit that captures an image of the traveling direction of the vehicle, and a first shake of another vehicle that travels in front of the vehicle. Receiving means, detecting means for detecting a second shake received by the vehicle from image data of the image taken by the imaging means, and the first shake received by the receiving meansSaidPredicting means for predicting third shaking that the vehicle will receive from the second shaking detected by the detecting means, and control means for controlling the shaking of the vehicle based on the prediction by the predicting means. The prediction means comprises:Obtained at a given timeThe first shake andHas been detectedThe second upsetDegree of similarityCalculate the first correlation coefficient that representsWhen the first correlation coefficient reaches the maximum value, the time after the first fluctuation is acquired is calculated as the delay amount.Linear prediction using first calculation means, first prediction value output means for delaying the first fluctuation by the delay amount and outputting the first prediction value, and fluctuation data acquired in the past The second predicted value output means for outputting a second predicted value from the second fluctuation, and the degree of approximation between the second fluctuation and the second predicted value in a second phase relationship. Using the second calculation means for calculating as a number, the first correlation coefficient, the first predicted value, the second predicted value, and the second correlation coefficient, Generating means for generating prediction data predicting the above.
[0010]
A transmission means for transmitting the second fluctuation detected by the detection means can be further provided.
[0011]
  According to a second information processing method of one aspect of the present invention, an imaging unit that is mounted on a vehicle and captures an image of the traveling direction of the vehicle, and a first shake of another vehicle that travels in front of the vehicle are received. In the information processing method of the information processing apparatus including the receiving unit, the second shake received by the vehicle is detected from the image data of the image captured by the imaging unit, and the second received by the receiving unit is detected. Predicting a third shake that the vehicle will receive from the second shake detected as 1 shake and controlling the shake of the vehicle based on the prediction, the prediction comprising:Obtained at a given timeThe first shake andHas been detectedThe second upsetDegree of similarityCalculate the first correlation coefficient that representsWhen the first correlation coefficient reaches the maximum value, the time after the first fluctuation is acquired is calculated as the delay amount.The first fluctuation is delayed by the delay amount, calculated as a first predicted value, and based on linear prediction using the second fluctuation acquired in the past, the second fluctuation is And a degree of approximation between the second fluctuation and the second predicted value is calculated as a second correlation coefficient, the first correlation coefficient, the first predicted value, Using the second predicted value and the second correlation coefficient to generate predicted data in which the third fluctuation is predicted.
[0012]
  A second recording medium according to an aspect of the present invention is mounted on a vehicle and receives an imaging unit that captures an image in the traveling direction of the vehicle and a first sway of another vehicle traveling in front of the vehicle. Detecting a second shake received by the vehicle from image data of the image picked up by the image pickup means in a recording medium recording a computer readable program for controlling an information processing apparatus including a reception means Then, based on the prediction, a third shake that the vehicle will receive is predicted from the first shake detected by the receiving means and the second shake detected, and the shake of the vehicle is controlled based on the prediction. The prediction includes the step of:Obtained at a given timeThe first shake andHas been detectedThe second upsetDegree of similarityCalculate the first correlation coefficient that representsWhen the first correlation coefficient reaches the maximum value, the time after the first fluctuation is acquired is calculated as the delay amount.The first fluctuation is delayed by the delay amount, calculated as a first predicted value, and based on linear prediction using the second fluctuation acquired in the past, the second fluctuation is And a degree of approximation between the second fluctuation and the second predicted value is calculated as a second correlation coefficient, the first correlation coefficient, the first predicted value, A program for causing a computer to execute processing including a step of generating prediction data in which the third fluctuation is predicted using the second prediction value and the second correlation coefficient is recorded.
[0013]
In the second information processing apparatus and method and the recording medium of one aspect of the present invention, the first shake of another vehicle traveling in front of the vehicle is received, and the vehicle is detected from the image data of the captured image. The received second shake is detected, and the third shake that the vehicle will receive is predicted from the received first shake and the detected second shake. Based on the prediction, the shake of the vehicle is detected. Be controlled.
[0014]
DETAILED DESCRIPTION OF THE INVENTION
Embodiments of the present invention will be described below with reference to the drawings. FIG. 1 is a diagram illustrating a vehicle to which the present invention is applied. The vehicle 1 includes an imaging unit 2 that captures an image in the traveling direction. The imaging unit 2 is configured by a video camera or the like. A normal vehicle is provided with four wheels 3-1 to 3-4 on the front, rear, left and right.
[0015]
Each of the wheels 3-1 to 3-4 has a swing actuator 4-1 to 4-4 (hereinafter, if it is not necessary to individually distinguish the swing actuators 4-1 to 4-4, the swing actuator 4 and In addition, other devices are described in the same manner). The imaging unit 2 and the shaking actuator 4 are controlled by the control unit 5.
[0016]
  FIG. 2 is a diagram for further explaining the configuration of the portion of the vehicle 1 relating to the present invention. The image data of the image in the traveling direction of the vehicle 1 imaged by the imaging unit 2 is output to the front vehicle motion detection unit 11 and the own vehicle motion detection unit 12 of the control unit 5. The front vehicle shake detection unit 11 and the own vehicle shake detection unit 12 each generate shake data using the input image data. Front car upsetdetectionPart11The data generated by the vehicle is data related to the vibration received by the previous vehicle.detectionThe shake data generated by the unit 12 is data related to the shake received by the vehicle. In other words, the shake data output from the front vehicle shake detection unit 11 is data related to the shake that the vehicle 1 will receive, and the shake data output from the own vehicle shake detection unit 12 is received by the own vehicle now. It is data about the upset.
[0017]
The motion data generated by the front vehicle motion detection unit 11 and the motion data generated by the host vehicle motion detection unit 12 are each output to the motion prediction unit 13. The motion prediction unit 13 predicts the motion that the vehicle will receive from the two input motion data, and outputs the predicted data to the reverse motion generation unit 14. The reverse shake generation unit 14 generates reverse shake data considering characteristics of the vehicle weight, springs, dampers, and the like according to the input prediction data, and outputs the reverse shake data to the reverse shake actuator 4.
[0018]
FIG. 3 is a diagram illustrating a configuration of the front vehicle shake detection unit 11. As shown in FIG. 3, the front vehicle shake detection unit 11 includes a front vehicle detection unit 21 and a motion vector detection unit 22. An image based on the image data captured by the imaging unit 2 and input to the front vehicle motion detection unit 11 is, for example, an image as shown in FIG. As an image, a road, vehicles traveling on the road, buildings located on both sides of the road, and the like are captured. Among them, the front vehicle detection unit 21 first detects a plurality of vehicles traveling on the road, and detects a vehicle that is located in the central portion of the image in the left-right direction and occupies the largest area as a front vehicle. .
[0019]
The motion vector detection unit 22 detects the detected motion vector of the preceding vehicle. The detected motion vector is assumed to be a shake of the front vehicle, and the shake is considered to be received from the road surface. The motion of the front vehicle may be detected by detecting the full screen motion from the image obtained by the imaging unit 2 and paying attention to a motion vector different from the full screen motion.
[0020]
Image data similar to the image data input to the front vehicle motion detection unit 11 (for example, image data that is the basis of the image as shown in FIG. 4) is also input to the own vehicle motion detection unit 12. The own vehicle shake detection unit 12 detects the shake of the own vehicle from the input image data. The detection method will be described below.
[0021]
  FIG. 5 is a diagram showing an internal configuration of the own vehicle sway detection unit 12. Vehicle shake detectionPart12 includes a feature information detection unit 31 and a feature information processing unit 32. Vehicle shake detectionPartThe image data input to 12 is input to the feature information detection unit 31, feature information described later is detected, and output to the feature information processing unit 32. The feature information processing unit 32 calculates shaking data from the input feature information.
[0022]
FIG. 6 is a block diagram illustrating a configuration of the feature information detection unit 31. The image data input to the feature information detection unit 31 is delayed by one frame by the delay unit 41 and then supplied to the frame buffer 42-1 and also to the frame buffer 42-2. The reading units 43-1 and 43-2 read image data from the corresponding frame buffers 42-1 and 42-2, respectively, according to predetermined patterns stored in the memory 44, and output them to the motion vector detection unit 45. .
[0023]
The motion vector detection unit 45 detects a motion vector from the supplied image data and outputs it to the feature information calculation unit 46. The feature information calculation unit 46 calculates feature information from the input motion vector.
[0024]
  Next, the operation of the feature information detection unit 31 shown in FIG. 6 will be described. At time t, the image data input to the feature information detection unit 31 is supplied to the delay unit 41 and the frame buffer 42-2. The frame buffer 42-2 stores the input image data for one frame. Since the delay unit 41 delays the image data by one frame, at time t, the frame buffer 42-1 stores the image data at time t-1 before time t, that is, one frame before time t. Image data is stored. flamebufferThe image data at time t-1 stored in 42-1 is framed by the reading unit 43-1.bufferThe image data at time t stored in 42-2 is read by the reading unit 43-2.
[0025]
The reading units 43-1 and 43-2 read image data of a portion corresponding to the pattern stored in the memory 44 among the image data stored in the corresponding frame buffers 42-1 and 42-2, respectively. . Here, the patterns stored in the memory 44 will be described with reference to FIG.
[0026]
FIG. 7 is a diagram illustrating an example of a pattern stored in the memory 44. Of the pixels constituting one frame, a portion not related to fluctuation, for example, in the case of image data taken by a video camera attached to a car as shown in FIG. Since it is considered that the region is not related to shaking, the pixel located at the center of the region excluding the region is set as the convergence point P. For example, 25 representative points Q (including the convergence point) are set symmetrically in the vertical and horizontal directions around the convergence point P. For each representative point Q, a block B having a predetermined number of pixels centered on the representative point Q, for example, a reference block B having 33 × 33 pixels is set. In the memory 44, the coordinates of each representative point Q in the screen of such a frame, the size of the reference block B, and the size of a search block made up of 65 × 65 pixels, for example, which are not shown, are shown in the pattern. Is remembered as
[0027]
The reading unit 43-1 includes pixel data corresponding to the above-described pattern stored in the memory 44 among the image data at the time t-1 stored in the frame buffer 42-1, that is, the coordinates of the representative point Q. Based on the size of the block B, the pixel data in each reference block B is read and output to the motion vector detection unit 45 as reference block data. Similarly, the readout unit 43-2 reads out pixel data corresponding to the pattern stored in the memory 44 from the image data at time t stored in the frame buffer 42-2, and sends it to the motion vector detection unit 45. Output as search block data.
[0028]
The motion vector detection unit 45 detects a motion vector at each representative point Q by performing block matching using the input reference block data and search block data. Therefore, in this example, 25 motion vectors are detected.
[0029]
In the present embodiment, since the purpose is to generate motion data, it is not necessary to detect motion vectors for all pixels, so only 25 motion vectors are obtained. As a result, the circuit scale can be reduced and the processing speed can be improved.
[0030]
The feature information calculation unit 46 uses the 25 motion vectors detected by the motion vector detection unit 45 and uses the horizontal component u, vertical component v, and enlargement component v of the shake as the entire frame at time t._zoom, And rotational component v_rotAre calculated based on the following formula.
Horizontal component u = (1 / n) Σu_i  ... (1)
Vertical component v = (1 / n) Σv_i  ... (2)
Expansion component v_zoom= (1 / n) Σv_zoomi/ D_i  ... (3)
Rotational component v_rot= (1 / n) Σv_roti/ D_i    ... (4)
The subscript i is the representative point Q_iIn this example, the number varies from 1 to 25. Since n is the number of representative points, it is 25 in this example.
The values obtained by the equations (1) to (4) are components u, v, v obtained from 25 motion vectors._zoom, V_rotIs the average value.
[0031]
Each component u, v, v described above_zoom, V_rotThe relationship will be described with reference to FIG. Representative point Q to be processed_iThe horizontal component of the motion vector T of_iAnd the vertical component is v_iAnd di is the representative point Q from the convergence point P_iIt is a scalar quantity that represents the distance to. Further, (Px, Py) represents the coordinates of the convergence point P, and the coordinates (Q_ix, Q_iRepresentative point Q of y)_iThe distance to is calculated.
[0032]
The component of this motion vector T (u_i, V_i) Is representative point Q_iThis is the component when is the origin. Convergence point P and representative point Q of motion vector T_iThe component in the direction parallel to the straight line connecting_zoomiAnd convergence point P and representative point Q_iThe component in the direction orthogonal to the straight line connecting_rotiAnd Also, the convergence point P and the representative point Q_iIs an angle formed by a straight line connecting the two and the motion vector T. At this time, v_zoomiAnd v_rotiIs obtained according to the following equation.
v_zoomi= (U_i ²+ V_i ²)^(1/2)COSθ (5)
v_roti = (U_i ²+ V_i ²)^(1/2)SINθ (6)
[0033]
Here, the values of 25 motion vectors are used on average to obtain each component, but each component may be weighted based on the positional relationship on the screen.
[0034]
The feature information calculation unit 46 uses the equations (1) to (4) from the motion vector output from the motion vector detection unit 45 and uses the four component data u, v, v as feature information._zoom, V_rotIs calculated. Calculated four-component data u, v, v_zoom, V_rotIs output to the feature information processing unit 32 (FIG. 5).
[0035]
Four components are detected from the image data by the processing of the feature information detection unit 31, but here, the components are further processed by the feature information processing unit 32 into data that can be handled easily in later processing. The feature information processing unit 32 is a chair-type device provided with a plurality of actuators, and processes the data when the user feels a sense of getting on the vehicle in a pseudo manner. Of course, here, it is not intended to simulate the feeling of getting on the vehicle, so it is not necessary to process such data, but here the processed data is used. The following explanation will be given.
[0036]
Considering what force (sway) should be applied to the chair on which the audience sits when the audience has a simulated experience of riding in the vehicle. The force applied to the chair of the car includes the force to express the forward and backward inclination of the road surface when the car is running on a sloped road such as a slope, the road surface when running on a bumpy road There is a force for expressing the vertical vibration received from the vehicle, a force for expressing the horizontal inclination of the road surface when running on an inclined road surface, and the like.
[0037]
These forces can provide stimuli with the same physical meaning to the audience's chair that observes the image among the stimuli given to the car equipped with the video camera that captured the image. Force, which is referred to herein as a real stimulus. This actual stimulus becomes zero when the value is integrated.
[0038]
On the other hand, the force that expresses the centrifugal force when the car bends the curve, the force that expresses the inertial force when accelerating or decelerating, and the force that expresses the car swinging when the car curves are integrated. The value does not become zero, and it is difficult to give the same physical meaning as the stimulus given to the car due to restrictions on the distance traveled by the chair, restrictions on the direction of movement, etc. This is referred to as an alternative stimulus.
[0039]
The relationship between the force related to the actual stimulus and the alternative stimulus described above, the component of the shaking data actually applied to the audience chair, and the four components calculated by the feature information calculation unit 46 described above will be shown. Of the actual stimulation shown below, the shaking data for the road surface front-rear inclination is one of the shaking data components pitch, and can be represented by a low-frequency component of the vertical components of the motion vector. Here, since the slope of the road surface is considered to change at a slow cycle, a low frequency component is used.
[0040]
Since the inclination is considered to change at a slow cycle and is considered to be a high frequency, the fluctuation data for the vibration received from the road surface uses the high frequency component of the vertical components of the motion vector. This value is the fluctuation data component z. The fluctuation data for the left and right inclination of the road surface is one of the fluctuation data components roll, and as can be seen from FIG. 9, can be represented by a value obtained by adding the rotation component Vroti for 25 motion vectors. The shaking data for the centrifugal force at the time of the curve is one of the shaking data components roll and is represented by the horizontal component u.
[0041]
The fluctuation data for the inertial force due to acceleration / deceleration is one of the fluctuation data components pitch and is represented by a low frequency component of the differential value of the expansion component Vzoom. The reason for the low frequency component is that it is considered that no sensitive operation is required for acceleration / deceleration. The shaking data for the swing of the car at the time of the curve is a shaking data component yaw and is represented by a horizontal component u. In addition, it is because it works as the -u centrifugal force at the time of a curve as -u.
[0042]
Real stimulus
Represented component Motion data component Relationship with 4 components
Low frequency component of road pitch slope Σv
Vibration from road surface High frequency component of z-Σv
Left-right slope of the road roll -Σv_rot
Alternative stimulus
Represented component Motion data component Relationship with 4 components
Centrifugal force roll u at curve
Inertial force due to acceleration / deceleration pitch dv_zoomLow frequency component of / dt
Car swing when turning yaw -u
[0043]
The feature information processing unit 32 generates shaking data using the relationship described above. FIG. 10 is a block diagram illustrating a configuration of the feature information processing unit 32. Of the four components output from the feature information detector 31, the rotation component v_rotIs added to the adder 51-1, the horizontal component u is added to the adder 51-2 and the sign inverter 52-1, and the vertical component v is added to the adder 51-3._zoomAre input to the adder 51-5 and the delay unit 53-3, respectively. The data output from the adder 51-1 is delayed by one clock by the delay unit 53-1 and fed back to the adder 51-1. Similarly, the data output from the adder 51-3 is also fed back to the adder 51-3 after being delayed by one clock by the delay unit 53-2.
[0044]
The data output from the delay unit 53-1 is input to the adder 51-2, and the data output from the delay unit 53-2 is input to the HPF (High Pass Filter) 54 via the sign inverter 52-2. In addition to being output, it is also output to an adder 51-4 via an LPF (Low Pass Filter) 55-1. Expanded component v input to adder 51-5_zoomIs the expanded component v delayed by one clock by the delay unit 53-3_zoomIs subtracted and input to the adder 51-4 via the LPF 55-2.
[0045]
Next, calculation of the shake data components roll, yaw, z, and pitch performed by the feature information processing unit 32 will be described. Rotation component v input to feature information processing unit 32_rotIs input to the adder 51-1. The adder 51-1 receives the rotation component v input at time t._rotAnd the data at time t-1 one frame before output from the delay unit 53-1. The adder 51-1 thus performs the rotation component v_rotIs accumulated (integrated) to obtain a rocking data component roll (Σv_rot) Is calculated. However, the fluctuation data component roll expressing the right and left slope of the road surface is −Σv._rotTherefore, the adder 51-2 uses data obtained by inverting the sign of the data input from the delay unit 53-1, for the calculation.
[0046]
The fluctuation data component roll (horizontal component u) is also used to express the centrifugal force at the time of the curve. Therefore, the adder 51-2 adds the data obtained by inverting the sign of the data input from the delay unit 53-1, and the horizontal component u (subtracts the output of the delay unit 53-1 from the horizontal component u). Thus, the fluctuation data component roll is calculated.
[0047]
Since the swing data component yaw of the car swing at the time of the curve is obtained by inverting the value of the horizontal component u, the feature information processing unit 32 converts the input value of the horizontal component u into the sign inverter 52-1. Thus, the fluctuation data component yaw is calculated by inverting the sign.
[0048]
The adder 51-3 adds the vertical component v input at time t and the vertical component v at time t-1 one frame before output from the delay unit 53-2. In this way, the vertical component v is cumulatively added (integrated) in the adder 51-3. The data cumulatively added by the adder 51-3 and the delay unit 53-2 is input to the sign inverter 52-2, the sign is inverted, and only the high frequency component is extracted by the HPF 54. In this way, the fluctuation data component z expressing the vibration received from the road surface is calculated.
[0049]
Further, the data output from the delay unit 53-2 is also output to the LPF 55-1, and a low frequency component is extracted. In this way, the sway data component pitch expressing the front / rear inclination of the road surface is calculated. The shaking data component pitch is also used as a shaking data component expressing an inertial force due to acceleration / deceleration. Therefore, the fluctuation data component pitch output from the LPF 55-1 is added to the fluctuation data component pitch expressing the inertial force by the adder 51-4.
[0050]
The fluctuation data component pitch expressing the inertial force is an enlarged component v input to the feature information processing unit 32._zoomIs calculated from The enlarged component v input to the feature information processing unit 32_zoomAre input to the adder 51-5 and the delay unit 53-3. The adder 51-5 receives the expanded component v input at time t._zoomt and the expanded component v at time t−1 delayed by one frame by the delay unit 53-3_zoomt-1 is input. The adder 51-5 receives the enlarged component v at the input time t._zoomFrom t, the expanded component v at time t−1_zoomBy subtracting t-1, the expanded component v_zoomIs differentiated. Then, a low-frequency component is extracted by the LPF 55-2 from the value output from the adder 51-5, thereby calculating a sway data component pitch expressing an inertial force due to acceleration / deceleration.
[0051]
The adder 51-4 adds the value output from the LPF 55-1 and the value output from the LPF 55-2, thereby calculating the swaying data component pitch.
[0052]
As described above, since the shake data is calculated from the movement obtained from the image, it is possible to save the trouble of determining and inputting the shake data by confirming the image. Moreover, it is possible to easily generate the shake data from an image for which the shake data is not generated by using a sensor or the like.
[0053]
The shaking data relating to the shaking of the preceding vehicle detected by the preceding vehicle shaking detecting unit 11 and the shaking data relating to the shaking of the own vehicle detected by the own vehicle shaking detecting unit 12 are output to the shaking predicting unit 13. FIG. 11 is a diagram illustrating an internal configuration of the fluctuation prediction unit 13. The motion data output from the front vehicle motion detection unit 11 is input to the delay amount calculation unit 71 and the delay device 72 of the motion prediction unit 13. Similarly, the shake data output from the own vehicle shake detection unit 12 is input to the delay amount calculation unit 71, the predictor 73, and the correlation calculation unit 74.
[0054]
The delay amount calculation unit 71 calculates the delay amount T from the two input shaking data.
The graph shown in FIG. 12 (A) is related to the shake received by the front vehicle (based on the shake data output from the front vehicle shake detection unit 11), and the graph shown in FIG. This is related to the shake received by the own vehicle (based on the shake data output from the own vehicle shake detection unit 12). The shaking of the front vehicle shown in FIG. 12 (A) can be considered to be the shaking that the subject vehicle receives when the time T has elapsed. In other words, it is predicted that the shake received by the preceding vehicle will be the shake received by the own vehicle after being delayed by the delay amount T.
[0055]
From the graphs as shown in FIGS. 12A and 12B, the graph showing the relationship between the correlation coefficient R1 and the delay amount T shown in FIG. Positive constant T_MINA value where the correlation coefficient R1 takes a maximum value in a range exceeding the delay amount T is defined as a delay amount T. If there is no vehicle traveling in front of the host vehicle, the shake data output from the front vehicle shake detection unit 11 and input to the delay amount calculation unit 71 is meaningless data (noise). When a graph as shown in FIG. 12C is created for such data, there is a maximum value, but the value is very small. For this reason, when there is no front vehicle, the correlation coefficient R1 becomes very small, and the information on shaking of the front vehicle is hardly used.
[0056]
The delay device 72 delays the motion data from the front vehicle motion detection unit 11 by the delay amount T from the delay amount calculation unit 71 and outputs the delayed data to the weighted addition unit 75. Here, the data output from the delay device 72 is described as a predicted value D1. As described above, when there is no front vehicle, the correlation coefficient R1 and the delay amount T are very small. Therefore, the predicted value D1 output from the delay unit 72 is emergency even if it is output to the weighted addition unit 75. Is weak. When the correlation coefficient R1 is equal to or less than a predetermined threshold, the predicted value D1 may be set as 0.
[0057]
On the other hand, the predictor 73 receives the shake data from the own vehicle shake detection unit 12, calculates a predicted value D2 from the input shake data, and outputs the calculated value D2. The predictor 73 calculates a predicted value D2 from the input shaking data based on linear prediction using the shaking data acquired in the past.
[0058]
The correlation calculation unit 74 inputs the shake data from the own vehicle shake detection unit 12 and the predicted value D2 from the predictor 73, and calculates a correlation coefficient R2. The correlation coefficient R2 indicates how close the predicted value D2 calculated using past shaking data and the shaking data currently acquired are approximate. The accuracy of the predictor 73 is shown.
[0059]
A correlation coefficient R1 from the delay amount calculation unit 71, a correlation coefficient R2 from the correlation calculation unit 74, a predicted value D1 from the delay unit 72, and a predicted value D2 from the predictor 73 are input to the weighted addition unit 75. Is done. The weighted addition unit 75 performs calculation based on the following equation (7) from these input data, and calculates prediction data to be output to the reverse oscillation generation unit 14.

[0060]
The prediction data calculated according to the equation (7) is output to the reverse oscillation generation unit 14 (FIG. 2). The reverse oscillation generation unit 14 includes a memory (not shown) therein, and stores the characteristics of the vehicle's own vehicle weight, springs, dampers, and the like in the memory. Using the stored various data, Reverse motion data for generating reverse motion that reduces the motion of the host vehicle is generated. The reverse shake data is data for applying the same force in the opposite direction to the shake predicted by the prediction data, and is data in consideration of the vehicle weight described above.
[0061]
The reverse shake data generated by the reverse shake generation unit 14 is supplied to the reverse shake actuator 4. The reverse shake actuator 4 controls the shake of the vehicle 1 based on the supplied reverse shake data.
[0062]
In this way, by taking an image and detecting the shake of the front vehicle and the shake of the host vehicle from the image, it is possible to detect the shake more quickly and accurately. It can be reduced.
[0063]
In the above-described embodiment, in one vehicle 1, the movement of the front vehicle and the movement of the own vehicle are detected and control for reducing the fluctuation of the own vehicle is performed. 1, the same effect may be obtained. Such a case will be described below.
[0064]
As shown in FIG. 13, a case is assumed where two vehicles 1-1 and 1-2 are traveling. The vehicle 1-1 is traveling in front of the vehicle 1-2. In FIG. 13, the same parts as those already described are denoted by the same reference numerals, and the description thereof is omitted as appropriate.
An imaging unit 2 is mounted on the vehicle 1-1 and is configured to capture a front image. Image data of an image captured by the imaging unit 2 is output to the own vehicle sway detection unit 12. The own vehicle shake detection unit 12 generates shake data from the image data and outputs the generated shake data to the transmission unit 91. The transmission part 91 transmits the input shaking data with respect to the following vehicle 1-2 using transmission means, such as light and an electromagnetic wave.
[0065]
The vehicle 1-2 receives the shake data transmitted by the transmission unit 91 of the vehicle 1-1 by the reception unit 92. The shaking data received by the receiving unit 92 is output to the reverse shaking generating unit 93. The reverse shake generation unit 93 generates reverse shake data for applying the same force to the vehicle 1-2 in the reverse direction of the shake indicated by the input shake data. The reverse shake generation unit 93 generates reverse shake data in consideration of the vehicle weight of the own vehicle, features such as a spring and a damper.
[0066]
  ReverseSway generationBased on the reverse shake data generated by the unit 93, the reverse shake actuator 4 performs control for reducing the shake received by the vehicle 1-2.
[0067]
In this way, by transmitting the vibration data related to the vibration actually received by the front vehicle to the rear vehicle, in the rear vehicle, it is possible to obtain the vibration data regarding the vibration before receiving the actual vibration. As a result, it is possible to generate and control reverse oscillation data for reducing the oscillation with respect to the oscillation that will be received in advance.
[0068]
In the embodiment shown in FIG. 13, the vehicle 1-1 and the vehicle 1-2 have different configurations, but may have the same configuration. That is, as shown in FIG. 14, for both the vehicle 1-1 and the vehicle 1-2, the imaging unit 2, the own vehicle oscillation detection unit 12, the transmission unit 91, the reception unit 92, the reverse oscillation generation unit 93, and the reverse oscillation actuator 4. The sway data relating to the sway received by the vehicle is transmitted to the rear vehicle, the sway data relating to the sway received by the front vehicle is received from the front vehicle, and the sway is reduced based on the received sway data. You may make it perform control for this.
[0069]
  Further, in the embodiment shown in FIG. 13, the vehicle 1-2 is configured to control the shaking of the own vehicle only by the shaking data transmitted by the preceding vehicle, but also detects the shaking of the own vehicle. Reverse motion data may be generated in consideration of the detected motion of the host vehicle. That is, as shown in FIG. 15, by providing the imaging unit 2 and the own vehicle shake detection unit 12, it is possible to detect the shake of the own vehicle, and the receiving unit 92 receives the shake data relating to the detected shake. Using the fluctuation data of the preceding vehicle, the fluctuation prediction unit 13 generates prediction data, and using the prediction data,Reverse oscillation generator14 may generate reverse oscillation data. In the configuration shown in FIG. 15, the shake data from the own vehicle shake detection unit 12 is transmitted to another subsequent vehicle by the transmission unit 91.
[0070]
In the embodiment described above, the shaking data is generated from the image data. However, the shaking data may be generated using an acceleration sensor or the like.
[0071]
The series of processes described above can be executed by hardware, but can also be executed by software. When a series of processing is executed by software, various functions can be executed by installing a computer in which the programs that make up the software are installed in dedicated hardware, or by installing various programs. For example, it is installed from a recording medium in a general-purpose personal computer or the like.
[0072]
As shown in FIG. 16, this recording medium is distributed to provide a program to the user separately from the computer, and includes a magnetic disk 121 (including a floppy disk) on which the program is recorded, an optical disk 122 (CD- It is composed only of a package medium comprising a ROM (compact disk-read only memory), a DVD (digital versatile disk), a magneto-optical disk 123 (including MD (mini-disk)), or a semiconductor memory 124. Rather, it is composed of a ROM 102 storing a program and a hard disk including a storage unit 108 provided to the user in a state of being pre-installed in a computer.
[0073]
In this specification, the steps for describing the program provided by the medium are performed in parallel or individually in accordance with the described order, as well as the processing performed in time series, not necessarily in time series. The process to be executed is also included.
[0074]
Further, in this specification, the system represents the entire apparatus constituted by a plurality of apparatuses.
[0075]
【The invention's effect】
  As aboveThe present inventionAccording to,It is possible to more reliably reduce the shaking that the vehicle receives.
[Brief description of the drawings]
FIG. 1 is a diagram illustrating a configuration of a vehicle 1 to which the present invention is applied.
FIG. 2 is a diagram for further explaining the configuration of the vehicle.
FIG. 3 is a diagram showing an internal configuration of a front vehicle fluctuation detection unit 11;
FIG. 4 is a diagram for describing an image captured by the imaging unit 2;
FIG. 5 is a diagram illustrating an internal configuration of the own vehicle sway detection unit 12;
6 is a diagram illustrating an internal configuration of a feature information detection unit 31. FIG.
7 is a diagram showing patterns stored in a memory 46. FIG.
FIG. 8 is a diagram illustrating an image to be processed.
FIG. 9 is a diagram illustrating calculated vectors.
10 is a diagram showing an internal configuration of a feature information processing unit 32. FIG.
FIG. 11 is a diagram showing an internal configuration of a sway prediction unit 13;
FIG. 12 is a diagram for explaining calculation of a delay amount and a correlation coefficient.
13 is a diagram illustrating another configuration of the vehicle 1. FIG.
14 is a diagram illustrating still another configuration of the vehicle 1. FIG.
FIG. 15 is a diagram illustrating still another configuration of the vehicle.
FIG. 16 is a diagram illustrating a medium.
[Explanation of symbols]
DESCRIPTION OF SYMBOLS 1 Vehicle, 2 Imaging part, 3 Wheel, 4 Reverse motion actuator, 5 Control part, 11 Front vehicle motion detection part, 12 Own vehicle motion detection part, 13 Motion prediction part, 14 Reverse motion production | generation part, 21 Front vehicle detection part, 22 motion vector detection unit, 71 delay amount calculation unit, 72 delay unit, 73 predictor, 74 correlation calculation unit, 75 weighted addition unit, 91 transmission unit, 92 reception unit

Claims (12)

An imaging means mounted on a vehicle for capturing an image of the traveling direction of the vehicle;
First detection means for detecting a first sway of another vehicle traveling in front of the vehicle from image data of the image taken by the imaging means;
Second detection means for detecting second shaking received by the vehicle from image data of the image taken by the imaging means;
Prediction means for predicting a third shake that the vehicle will receive from the first shake detected by the first detection means and the second shake detected by the second detection means; ,
Control means for controlling the shaking of the vehicle based on the prediction by the prediction means,
The prediction means includes
A first correlation coefficient representing the similarity between the first fluctuation obtained at a predetermined time and the detected second fluctuation is calculated , and the first correlation coefficient becomes the maximum value. Sometimes, a first calculation means for calculating a time after the first shake is acquired as a delay amount ;
A first predicted value output means for delaying the first fluctuation by the delay amount and outputting the first predicted value as a first predicted value;
Second predicted value output means for outputting a second predicted value from the second fluctuation detected by the second detection means based on linear prediction using the second fluctuation acquired in the past. When,
Second calculating means for calculating, as a second correlation coefficient, a degree of approximation between the second fluctuation detected by the second detecting means and the second predicted value;
Generating means for generating prediction data in which the third fluctuation is predicted using the first correlation coefficient, the first prediction value, the second prediction value, and the second correlation coefficient; An information processing apparatus. The generation means calculates the prediction data based on the following formula: prediction data = (first prediction value) × (first correlation coefficient / (first correlation coefficient + second correlation coefficient) ) + (Second predicted value) × (second correlation coefficient / (first correlation coefficient + second correlation coefficient))
The information processing apparatus according to claim 1. The first detection means detects, from the image, a vehicle that is located in a central portion with respect to the left-right direction of the image and occupies the largest area, and detects a motion vector of the detected vehicle. The information processing apparatus according to claim 1, wherein the fluctuation of 1 is detected. The second detection means includes
Delay means for delaying the image data by one frame;
First storage means for storing the image data delayed by the delay means;
Second storage means for storing the image data;
A third memory storing patterns relating to portions to be read from the first image data stored in the first storage means and the second image data stored in the second storage means, respectively. Means,
First reading means for reading out the first image data of a portion corresponding to the pattern from the first image data stored in the first storage means, and outputting the data as reference block data;
Second reading means for reading out the second image data of a portion corresponding to the pattern from the second image data stored in the second storage means, and outputting it as search block data;
Motion vector detection means for executing a block matching process using the reference block data and the search block data, and detecting a motion vector;
Using the motion vector detected by the motion vector detecting means, the data of a total of four components of the horizontal component, the vertical component, the enlarged component, and the rotational component of the entire motion of the image are calculated , and the second The information processing apparatus according to claim 1, further comprising: a component calculation unit configured to sway the movement . In the pattern, a pixel located in the center of a region from which a portion unrelated to fluctuation is removed among pixels constituting one frame is defined as a convergence point, and the pattern is symmetrical vertically and horizontally about the convergence point. 5. The information according to claim 4, wherein a representative point of a position is set, and a block having a predetermined number of pixels centered on the representative point is set for each representative point. Processing equipment. From the four components calculated by the component calculation means, actual stimulus fluctuation data for controlling the force capable of giving a stimulus in the same physical meaning as when the image data was taken, and physical meaning Further comprising motion data generating means for generating alternative stimulus motion data for controlling forces that are difficult to apply in the same form,
The actual stimulus sway data is composed of slope component data representing the front and back slope of the road surface, component data representing the vibration received from the road surface, and component data representing the left and right slope of the road surface,
The alternative stimulation fluctuation data is composed of component data representing centrifugal force received during a curve, component data representing inertial force due to acceleration / deceleration, and component data representing vehicle swing during a curve,
The component data representing the slope of the road surface is generated from the low frequency component of the value obtained by cumulatively adding the vertical component,
The component data representing the vibration received from the road surface is generated from the high frequency component of the value obtained by cumulatively adding the vertical component,
The data of the component representing the left and right inclination of the road surface is generated by inverting the sign of the value obtained by cumulatively adding the rotation component,
The component data representing the centrifugal force received during the curve is the same data as the horizontal component,
Data of the component representing the inertial force due to the acceleration / deceleration is generated from a low frequency component of a value obtained by differentiating the expansion component,
The information processing apparatus according to claim 4, wherein the component data representing the swing of the vehicle at the time of the curve is generated by inverting the sign of the horizontal component. In an information processing method of an information processing apparatus that is mounted on a vehicle and includes an imaging unit that captures an image of the traveling direction of the vehicle
From the image data of the image captured by the imaging means, a first shake of another vehicle traveling in front of the vehicle is detected,
From the image data of the image picked up by the image pickup means, the second shake received by the vehicle is detected,
Predicting a third sway that the vehicle will experience from the first sway and the second sway;
Based on the prediction, including the step of controlling the shaking of the vehicle,
The prediction is
A first correlation coefficient representing the similarity between the first fluctuation obtained at a predetermined time and the detected second fluctuation is calculated , and the first correlation coefficient becomes the maximum value. Sometimes, the time from when the first shake is acquired is calculated as a delay amount ,
Delaying the first shake by the amount of delay and calculating as a first predicted value;
Based on the linear prediction using the second fluctuation acquired in the past, the second prediction value is calculated from the second fluctuation,
A degree of approximation between the second fluctuation and the second predicted value is calculated as a second correlation coefficient;
Using the first correlation coefficient, the first prediction value, the second prediction value, and the second correlation coefficient to generate prediction data in which the third fluctuation is predicted. Information processing method. In a recording medium that records a computer-readable program mounted on a vehicle and that controls an information processing apparatus that includes an imaging unit that captures an image in the traveling direction of the vehicle.
From the image data of the image captured by the imaging means, a first shake of another vehicle traveling in front of the vehicle is detected,
From the image data of the image picked up by the image pickup means, the second shake received by the vehicle is detected,
Predicting a third sway that the vehicle will experience from the first sway and the second sway;
Based on the prediction, including the step of controlling the shaking of the vehicle,
The prediction is
A first correlation coefficient representing the similarity between the first fluctuation obtained at a predetermined time and the detected second fluctuation is calculated , and the first correlation coefficient becomes the maximum value. Sometimes, the time from when the first shake is acquired is calculated as a delay amount ,
Delaying the first shake by the amount of delay and calculating as a first predicted value;
Based on the linear prediction using the second fluctuation acquired in the past, the second prediction value is calculated from the second fluctuation,
A degree of approximation between the second fluctuation and the second predicted value is calculated as a second correlation coefficient;
Using the first correlation coefficient, the first prediction value, the second prediction value, and the second correlation coefficient to generate prediction data in which the third fluctuation is predicted. A computer-readable recording medium recording a program for causing a computer to execute processing. An imaging means mounted on a vehicle for capturing an image of the traveling direction of the vehicle;
Receiving means for receiving a first shake of another vehicle traveling in front of the vehicle;
Detecting means for detecting second shaking received by the vehicle from image data of the image picked up by the image pickup means;
From said second upset detected by the received first upset and said detecting means by the receiving means, prediction means for predicting a third upset would the vehicle is subjected,
Control means for controlling the shaking of the vehicle based on the prediction by the prediction means,
The prediction means includes
A first correlation coefficient representing the similarity between the first fluctuation obtained at a predetermined time and the detected second fluctuation is calculated , and the first correlation coefficient becomes the maximum value. Sometimes, a first calculation means for calculating a time after the first shake is acquired as a delay amount ;
A first predicted value output means for delaying the first fluctuation by the delay amount and outputting the first predicted value as a first predicted value;
Second predicted value output means for outputting a second predicted value from the second fluctuation based on linear prediction using fluctuation data acquired in the past;
Second calculating means for calculating a degree of approximation between the second fluctuation and the second predicted value as a second correlation coefficient;
Generating means for generating prediction data in which the third fluctuation is predicted using the first correlation coefficient, the first prediction value, the second prediction value, and the second correlation coefficient; An information processing apparatus. The information processing apparatus according to claim 9, further comprising a transmission unit that transmits the second shake detected by the detection unit. In an information processing method for an information processing apparatus, comprising: an imaging unit that is mounted on a vehicle and that captures an image of the traveling direction of the vehicle; and a reception unit that receives a first shake of another vehicle traveling in front of the vehicle.
From the image data of the image picked up by the image pickup means, the second shake received by the vehicle is detected,
Predicting a third shake that the vehicle will receive from the first shake detected by the receiving means and the detected second shake, and controlling the shake of the vehicle based on the prediction. Including
The prediction is
A first correlation coefficient representing the similarity between the first fluctuation obtained at a predetermined time and the detected second fluctuation is calculated , and the first correlation coefficient becomes the maximum value. Sometimes, the time from when the first shake is acquired is calculated as a delay amount ,
Delaying the first shake by the amount of delay and calculating as a first predicted value;
Based on the linear prediction using the second fluctuation acquired in the past, the second prediction value is calculated from the second fluctuation,
A degree of approximation between the second fluctuation and the second predicted value is calculated as a second correlation coefficient;
Using the first correlation coefficient, the first prediction value, the second prediction value, and the second correlation coefficient to generate prediction data in which the third fluctuation is predicted. Information processing method. A computer that controls an information processing device mounted on a vehicle and that includes an imaging unit that captures an image of the traveling direction of the vehicle and a reception unit that receives a first shake of another vehicle traveling in front of the vehicle is read. In a recording medium recording a possible program,
From the image data of the image picked up by the image pickup means, the second shake received by the vehicle is detected,
Predicting a third shake that the vehicle will receive from the first shake detected by the receiving means and the detected second shake, and controlling the shake of the vehicle based on the prediction. Including
The prediction is
A first correlation coefficient representing the similarity between the first fluctuation obtained at a predetermined time and the detected second fluctuation is calculated , and the first correlation coefficient becomes the maximum value. Sometimes, the time from when the first shake is acquired is calculated as a delay amount ,
Delaying the first shake by the amount of delay and calculating as a first predicted value;
Based on the linear prediction using the second fluctuation acquired in the past, the second prediction value is calculated from the second fluctuation,
A degree of approximation between the second fluctuation and the second predicted value is calculated as a second correlation coefficient;
Using the first correlation coefficient, the first prediction value, the second prediction value, and the second correlation coefficient to generate prediction data in which the third fluctuation is predicted. A computer-readable recording medium recording a program for causing a computer to execute processing.

Images