JP2012227639A - Traveling support device and traveling support method - Google Patents

Traveling support device and traveling support method Download PDF

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JP2012227639A
JP2012227639A JP2011091942A JP2011091942A JP2012227639A JP 2012227639 A JP2012227639 A JP 2012227639A JP 2011091942 A JP2011091942 A JP 2011091942A JP 2011091942 A JP2011091942 A JP 2011091942A JP 2012227639 A JP2012227639 A JP 2012227639A
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predetermined area
vehicle
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JP5724570B2 (en
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Chikao Tsuchiya
千加夫 土谷
Yasuhisa Hayakawa
泰久 早川
Shinya Tanaka
慎也 田中
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Nissan Motor Co Ltd
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Abstract

PROBLEM TO BE SOLVED: To provide a traveling support device that detects a motorcycle traveling just behind a moving body without increasing number of imaging means, and to provide a traveling support method.SOLUTION: A visual line changing part 31 changes a line of sight so as to obtain a bird's eye view image of an image captured by a camera 10. An alignment part 32a aligns an image in a first predetermined area A1 provided from one adjacent lane to the side just behind a vehicle V across a lane marking DL and an image in a second predetermined area A2 provided from the other lane to the side just behind the vehicle V across a lane marking DL, captured at different times where the line of sight is changed, individually. A differential value detection part 32b detects a differential value for each of the aligned image data in the first and second predetermined areas A1 and A2 captured at different times. A following vehicle detection part 33a detects a following motorcycle on the basis of deviation between the detected differential value in the first predetermined area A1 and that in the second predetermined area A2.

Description

本発明は、走行支援装置及び走行支援方法に関する。   The present invention relates to a driving support device and a driving support method.

従来、2つのカメラで自車両の側後方を撮像すると共に、画像内に複数の検出領域を設定し、検出領域毎に2つのカメラにより撮像された画像のずれ量を算出することで、対象物までの距離を算出する車両用障害物検出装置が提案されている。この装置では、画像内に複数の検出領域を設定しているため、後続の二輪車についても検出することができる(特許文献1参照)。   Conventionally, by capturing the rear side of the host vehicle with two cameras, setting a plurality of detection areas in the image, and calculating the shift amount of the images captured by the two cameras for each detection area, A vehicle obstacle detection device that calculates the distance to the vehicle has been proposed. In this apparatus, since a plurality of detection areas are set in the image, it is possible to detect the following two-wheeled vehicle (see Patent Document 1).

特許3077529号公報Japanese Patent No. 3077529

しかし、従来装置では、自車両の側後方に検出領域を設けているため、自車両の真後ろに存在する二輪車については検出することができない。また、二輪車の検出にあたっては2つのカメラにより撮像された画像を処理しなければならず、カメラ等の撮像手段の数が増加してしまう。   However, in the conventional apparatus, since the detection area is provided on the side rear side of the own vehicle, it is not possible to detect a two-wheeled vehicle that exists immediately behind the own vehicle. In addition, when detecting a two-wheeled vehicle, images picked up by two cameras must be processed, and the number of image pickup means such as cameras increases.

本発明はこのような従来の課題を解決するためになされたものであり、その目的とするところは、撮像手段の数を増加させる必要が無く、且つ、移動体の真後ろの二輪車について検出することが可能な走行支援装置及び走行支援方法を提供することにある。   The present invention has been made to solve such a conventional problem, and an object of the present invention is to detect a two-wheeled vehicle directly behind a moving body without increasing the number of imaging means. It is an object to provide a driving support device and a driving support method capable of performing the above.

本発明の走行支援装置においては、第1の所定領域と第2の所定領域とが設定されている。第1の所定領域は、移動体の一方の側後方の隣接車線から区分線を跨いで移動体の直後方側まで設けられている。第2の所定領域は、移動体の他方の側後方の隣接車線から区分線を跨いで移動体の直後方側まで設けられている。そして、視点変換手段は、撮像にて得られた画像を鳥瞰視される状態へ視点変換し、位置合わせ手段は、異なる時刻における、視点変換された第1の所定領域の画像と第2の所定領域の画像とをそれぞれ個別に位置合わせする。差分値検出手段は、位置合わせされた異なる時刻の画像から差分値を検出する。後続車両検出手段は、検出された第1の所定領域の差分値と第2の所定領域の差分値との隔たりから後続の二輪車を検出する。   In the driving support device of the present invention, a first predetermined area and a second predetermined area are set. The first predetermined area is provided from the adjacent lane on the rear side of one side of the moving body to the side just behind the moving body across the dividing line. The second predetermined area is provided from the adjacent lane at the rear of the other side of the moving body to the right side of the moving body across the dividing line. Then, the viewpoint conversion means converts the image obtained by the imaging into a bird's-eye view state, and the alignment means converts the viewpoint-converted first predetermined region image and the second predetermined image at different times. The image of the area is individually aligned. The difference value detection means detects the difference value from the images at different times that have been aligned. The following vehicle detection means detects the following two-wheeled vehicle from the distance between the detected difference value of the first predetermined region and the difference value of the second predetermined region.

本発明によれば、移動体の一方の側後方の隣接車線から区分線を跨いで前記移動体の直後方側まで設けられた第1の所定領域と、移動体の他方の側後方の隣接車線から区分線を跨いで前記移動体の直後方側まで設けられた第2の所定領域との双方の画像について、位置を合わせて差分値を検出し、それぞれの差分値の隔たりから二輪車を検出する。ここで、真後ろの二輪車は車線の一側に寄って走行していることが多く、第1の所定領域と第2の所定領域との差分値は真後ろに二輪車が存在する場合、一方のみが大きな値を示す傾向にある。このため、両者差分値の隔たりから真後ろの二輪車を検出することができる。また、撮像手段により得られた画像の第1の所定領域と第2の所定領域との差分値から二輪車を検出するため、撮像手段を複数備える必要が無い。従って、撮像手段の数を増加させる必要が無く、且つ、移動体の真後ろの二輪車について検出することができる。   According to the present invention, the first predetermined region provided from the adjacent lane on the rear side of one side of the moving body to the immediate rear side of the moving body, and the adjacent lane on the other side of the moving body. The difference value is detected by aligning the positions of both images with the second predetermined area provided up to the right side of the moving body across the lane marking from the distance, and the two-wheeled vehicle is detected from the difference between the difference values. . Here, the two-wheeled vehicle directly behind is often running near one side of the lane, and the difference value between the first predetermined region and the second predetermined region is large only when one motorcycle is present immediately behind. It tends to show a value. For this reason, it is possible to detect the motorcycle immediately behind the difference between the two difference values. Further, since the two-wheeled vehicle is detected from the difference value between the first predetermined area and the second predetermined area of the image obtained by the imaging means, it is not necessary to provide a plurality of imaging means. Therefore, it is not necessary to increase the number of imaging means, and it is possible to detect the two-wheeled vehicle immediately behind the moving body.

本実施形態に係る走行支援装置の概略構成図であって、走行支援装置が車両Vに搭載される場合の例を示している。It is a schematic block diagram of the driving assistance device concerning this embodiment, and shows the example in case the driving assistance device is carried in vehicles. 図1に示した車両の走行状態を示す上面図である。It is a top view which shows the driving state of the vehicle shown in FIG. 図1に示した計算機の詳細を示すブロック図である。It is a block diagram which shows the detail of the computer shown in FIG. 図3に示した位置合わせ部の処理の概要を示す上面図であり、(a)は車両の移動状態を示し、(b)は位置合わせの概要を示している。FIG. 4 is a top view showing an outline of processing of the alignment unit shown in FIG. 3, (a) showing a moving state of the vehicle, and (b) showing an outline of alignment. 図3に示した隣接車両検出部による差分波形の生成の様子を示す概略図である。It is the schematic which shows the mode of the production | generation of the difference waveform by the adjacent vehicle detection part shown in FIG. 本実施形態に係る走行支援方法の一例を示すフローチャートである。It is a flowchart which shows an example of the driving assistance method which concerns on this embodiment.

以下、本発明の好適な実施形態を図面に基づいて説明する。図1は、本実施形態に係る走行支援装置1の概略構成図であって、走行支援装置1が車両Vに搭載される場合の例を示している。図1に示すように、走行支援装置1は、カメラ(撮像手段)10と、車速センサ20と、計算機30と、警報装置40を備えている。   DESCRIPTION OF EXEMPLARY EMBODIMENTS Hereinafter, preferred embodiments of the invention will be described with reference to the drawings. FIG. 1 is a schematic configuration diagram of a driving support device 1 according to the present embodiment, and shows an example in which the driving support device 1 is mounted on a vehicle V. As shown in FIG. 1, the driving support apparatus 1 includes a camera (imaging means) 10, a vehicle speed sensor 20, a calculator 30, and an alarm device 40.

図1に示すカメラ10は、車両Vの後部における高さhの箇所において、光軸が水平から下向きに角度θとなるように取り付けられている。カメラ10は、この位置から自車両Vの後方及び側後方を撮像するようになっている。車速センサ20は、車両Vの走行速度を検出するものであって、例えば車輪に回転数を検知する車輪速センサで検出した車輪速から速度を算出する。計算機30は、車両後方側の隣接車両等を検出するものである。警報装置40は、計算機30により検出された隣接車両が自車両Vに接触する可能性がある場合などに、自車両Vの運転者に警報するものである。   The camera 10 shown in FIG. 1 is mounted so that the optical axis is at an angle θ from the horizontal to the bottom at a height h in the rear part of the vehicle V. The camera 10 images the rear and side rear of the host vehicle V from this position. The vehicle speed sensor 20 detects the traveling speed of the vehicle V, and calculates the speed from the wheel speed detected by, for example, a wheel speed sensor that detects the rotational speed of the wheel. The computer 30 detects an adjacent vehicle on the vehicle rear side. The warning device 40 warns the driver of the host vehicle V when the adjacent vehicle detected by the computer 30 may come into contact with the host vehicle V.

図2は、図1に示した車両Vの走行状態を示す上面図である。図2に示すように、カメラ10は、所定の画角で車両後方側を撮像する。このとき、カメラ10の画角内には自車両Vが走行する車線に加えて、その左右の車線についても撮像可能となっている。   FIG. 2 is a top view showing a traveling state of the vehicle V shown in FIG. As shown in FIG. 2, the camera 10 images the vehicle rear side at a predetermined angle of view. At this time, in addition to the lane in which the host vehicle V travels, the right and left lanes can be imaged within the angle of view of the camera 10.

特に、本実施形態に係る走行支援装置1の計算機30は、第1の所定領域A1と第2の所定領域A2との画像に基づいて、自車両Vの真後ろを走る自動車や二輪車などの後続車両を検出すると共に、第3の所定領域A3と第4の所定領域A4との画像に基づいて、隣接車線を走行する隣接車両を検出する。   In particular, the computer 30 of the driving support device 1 according to the present embodiment is configured so that the following vehicle such as an automobile or a motorcycle running directly behind the host vehicle V based on the images of the first predetermined area A1 and the second predetermined area A2. And an adjacent vehicle traveling in the adjacent lane is detected based on the images of the third predetermined area A3 and the fourth predetermined area A4.

ここで、第1の所定領域A1は、自車両Vの一方の側後方の隣接車線から区分線DLを跨いで自車両Vの直後方側まで設けられている。また、第2の所定領域A2は、自車両Vの他方の側後方の隣接車線から区分線DLを跨いで自車両Vの直後方側まで設けられている。すなわち、第1の所定領域A1と第2の所定領域A2とは、自車両Vが走行する車線(以下自車線という)の略中心を二分するように、走行車線の左右にそれぞれ設定されている。さらに、第3の所定領域A3は自車両Vの一方の側後方の隣接車線に相当する位置に設けられており、第4の所定領域A4は自車両Vの他方の側後方の隣接車線に相当する位置に設けられている。   Here, the first predetermined area A1 is provided from the adjacent lane on the rear side of one side of the host vehicle V to the side immediately behind the host vehicle V across the dividing line DL. Further, the second predetermined area A2 is provided from the adjacent lane on the other side rear side of the host vehicle V to the side immediately behind the host vehicle V across the dividing line DL. That is, the first predetermined area A1 and the second predetermined area A2 are respectively set on the left and right sides of the travel lane so as to bisect the approximate center of the lane in which the host vehicle V travels (hereinafter referred to as the own lane). . Further, the third predetermined area A3 is provided at a position corresponding to an adjacent lane on one side rear of the host vehicle V, and the fourth predetermined area A4 corresponds to an adjacent lane on the other side rear of the host vehicle V. It is provided in the position to do.

図3は、図1に示した計算機30の詳細を示すブロック図である。なお、図3においては、接続関係を明確とするためにカメラ10、車速センサ20及び警報装置40についても図示するものとする。   FIG. 3 is a block diagram showing details of the computer 30 shown in FIG. In FIG. 3, the camera 10, the vehicle speed sensor 20, and the alarm device 40 are also illustrated in order to clarify the connection relationship.

図3に示すように、計算機30は、視点変換部(変換手段)31と、差分検出部32と、移動体検出部33とを備えている。   As illustrated in FIG. 3, the computer 30 includes a viewpoint conversion unit (conversion unit) 31, a difference detection unit 32, and a moving body detection unit 33.

まず、視点変換部31は、カメラ10による撮像にて得られた撮像画像データを入力し、入力した撮像画像データを鳥瞰視される状態の鳥瞰画像データに視点変換するものである。鳥瞰視される状態とは、上空から例えば鉛直下向きに見下ろす仮想カメラの視点から見た状態である。この視点変換は、例えば特開2008−219063号公報に記載さるようにして実行される。   First, the viewpoint conversion unit 31 inputs captured image data obtained by imaging with the camera 10, and converts the input captured image data into a bird's-eye image data in a bird's-eye view state. The state viewed from a bird's-eye view is a state viewed from the viewpoint of a virtual camera looking down from above, for example, vertically downward. This viewpoint conversion is executed as described in, for example, Japanese Patent Application Laid-Open No. 2008-219063.

差分検出部32は、視点変換部31により視点変換された鳥瞰画像データを入力し、時刻の異なる鳥瞰画像データの差分を検出して差分画像データを生成するものである。この差分検出部32は、位置合わせ部(位置合わせ手段)32aと差分値検出部(差分値検出手段)32bとを有している。   The difference detection unit 32 receives the bird's-eye image data converted by the viewpoint conversion unit 31, detects the difference between the bird's-eye image data at different times, and generates difference image data. The difference detection unit 32 includes an alignment unit (alignment unit) 32a and a difference value detection unit (difference value detection unit) 32b.

位置合わせ部32aは、視点変換部31の視点変換により得られた鳥瞰画像データを順次入力し、入力した異なる時刻の鳥瞰画像データの位置を合わせるものである。図4は、図3に示した位置合わせ部32aの処理の概要を示す上面図であり、(a)は車両Vの移動状態を示し、(b)は位置合わせの概要を示している。   The alignment unit 32a sequentially inputs the bird's-eye image data obtained by the viewpoint conversion of the viewpoint conversion unit 31, and aligns the positions of the inputted bird's-eye image data at different times. 4A and 4B are top views showing an outline of the processing of the alignment unit 32a shown in FIG. 3, where FIG. 4A shows the moving state of the vehicle V, and FIG. 4B shows the outline of alignment.

図4(a)に示すように、現時刻の自車両VがV1に位置し、一時刻前の自車両VがV2に位置しているとする。また、自車両Vの後側方向に他車両Vが位置して自車両Vと並走状態にあり、現時刻の他車両VがV3に位置し、一時刻前の他車両VがV4に位置しているとする。さらに、自車両Vは、一時刻で距離d移動したものとする。なお、一時刻前とは、現時刻から予め定められた時間(例えば1制御周期)だけ過去の時刻であっても良いし、任意の時間だけ過去の時刻であっても良い。   As shown in FIG. 4A, it is assumed that the host vehicle V at the current time is located at V1, and the host vehicle V one hour before is located at V2. In addition, the other vehicle V is located in the rear direction of the own vehicle V and is in parallel with the own vehicle V, the other vehicle V at the current time is located at V3, and the other vehicle V one hour before is located at V4. Suppose you are. Furthermore, it is assumed that the host vehicle V has moved a distance d at one time. Note that “one hour before” may be a past time by a predetermined time (for example, one control cycle) from the current time, or may be a past time by an arbitrary time.

このような状態において、現時刻における鳥瞰画像PBは図4(b)に示すようになる。この鳥瞰画像PBでは、路面上に描かれる白線については矩形状となり、比較的正確に上面視された状態となっているが、他車両V3については倒れ込みが発生している。また、一時刻前における鳥瞰画像PBt−1についても同様に、路面上に描かれる区分線については矩形状となり、比較的正確に上面視された状態となっているが、他車両V4については倒れ込みが発生している。 In this state, the bird's-eye image PB t at the current time is as shown in Figure 4 (b). In the bird's-eye image PB t, for the white line drawn on the road surface becomes a rectangular shape, but in a state of being relatively accurately viewed, and tilting for the other vehicle V3 is generated. Similarly, for the bird's-eye view image PB t-1 one hour before, the section line drawn on the road surface is rectangular and is viewed from the top relatively accurately. A fall has occurred.

位置合わせ部32aは、上記のような鳥瞰画像PB,PBt−1の位置合わせをデータ上で実行する。この際、位置合わせ部32aは、一時刻前における鳥瞰画像PBt−1をオフセットさせ、現時刻における鳥瞰画像PBと位置を一致させる。オフセット量d’は、図4(a)に示した移動距離dに対応するだけの量となり、車速センサ20からの信号と一時刻前から現時刻までの時間に基づいて決定される。 The alignment unit 32a performs alignment of the bird's-eye images PB t and PB t−1 as described above on the data. At this time, the alignment unit 32a is offset the bird's-eye view image PB t-1 before one unit time, to match the position and bird's-eye view image PB t at the current time. The offset amount d ′ is an amount corresponding to the moving distance d shown in FIG. 4A, and is determined based on the signal from the vehicle speed sensor 20 and the time from one time before to the current time.

差分値検出部32bは、第1〜第4の所定領域A1〜A4それぞれの差分値を検出するものである。差分値を検出するにあたり、まず差分値検出部32bは、鳥瞰画像PB,PBt−1の差分をとり、差分画像PDのデータを生成する。ここで、差分画像PDの画素値は、鳥瞰画像PB,PBt−1の画素値の差を絶対値化したものでもよいし、照度環境の変化に対応するために当該絶対値が規定値を超えたときに「1」とし、超えないときに「0」としてもよい。 The difference value detector 32b detects the difference values of the first to fourth predetermined areas A1 to A4. In detecting the difference value, first, the difference value detection unit 32b takes the difference between the bird's-eye images PB t and PB t−1 and generates data of the difference image PD t . Here, the pixel value of the difference image PD t may be an absolute value of the difference between the pixel values of the bird's-eye images PB t and PB t−1 , and the absolute value is specified in order to cope with a change in the illuminance environment. “1” may be set when the value is exceeded, and “0” may be set when the value is not exceeded.

そして、以上のような処理の後、差分検出部32bは差分値を検出する。このとき、差分画像PDの画素値が鳥瞰画像PB,PBt−1の画素値の差を絶対値化したものである場合、差分検出部32bは、例えば第1〜第4の所定領域A1〜A4それぞれにおける領域内の全画素について画素値を加算することにより、差分値を検出する。また、差分画像PDの画素値について、鳥瞰画像PB,PBt−1の画素値の差を絶対値化して得られた絶対値が規定値を超えたときに「1」とされている場合、差分値検出部32bは
、例えば第1〜第4の所定領域A1〜A4それぞれにおける領域内において「1」とされている画素数を加算して差分値を検出する。
And after the above processes, the difference detection part 32b detects a difference value. At this time, if the pixel value of the difference image PD t is an absolute value of the difference between the pixel values of the bird's-eye images PB t and PB t−1 , the difference detection unit 32b may, for example, include first to fourth predetermined regions. The difference value is detected by adding the pixel values for all the pixels in the areas A1 to A4. The pixel value of the difference image PD t is set to “1” when the absolute value obtained by converting the difference between the pixel values of the bird's-eye images PB t and PB t−1 to an absolute value exceeds a specified value. In this case, the difference value detection unit 32b detects the difference value by adding the number of pixels set to “1” in each of the first to fourth predetermined areas A1 to A4, for example.

移動体検出部33は、第1〜第4の所定領域A1〜A4内の後続車両や隣接車両を検出するものであって、後続車両検出部(後続車両検出手段)33aと隣接車両検出部(隣接車両検出手段)33bとを有している。   The moving body detection unit 33 detects a subsequent vehicle or an adjacent vehicle in the first to fourth predetermined areas A1 to A4, and includes a subsequent vehicle detection unit (subsequent vehicle detection means) 33a and an adjacent vehicle detection unit ( Adjacent vehicle detection means) 33b.

後続車両検出部33aは、第1の所定領域A1と第2の所定領域A2との差分値に基づいて、後続車両を検出するものである。この際、後続車両検出部33aは、後続車両が自動車であるか、二輪車であるかを判断する。隣接車両検出部33bは、第3の所定領域A3と第4の所定領域A4との差分値に基づいて、隣接車線を走行する隣接車両を検出するものである。なお、隣接車両については差分値から検出する方法の他、差分波形から求める方法もある。   The following vehicle detection unit 33a detects the following vehicle based on a difference value between the first predetermined area A1 and the second predetermined area A2. At this time, the subsequent vehicle detection unit 33a determines whether the subsequent vehicle is an automobile or a two-wheeled vehicle. The adjacent vehicle detection unit 33b detects an adjacent vehicle traveling in the adjacent lane based on a difference value between the third predetermined area A3 and the fourth predetermined area A4. In addition to the method of detecting the adjacent vehicle from the difference value, there is a method of obtaining from the difference waveform.

次に、後続車両検出部33aによる後続車両の検出の詳細について説明する。上記したように、後続車両検出部33aは、差分値検出部32bにより検出された第1の所定領域A1の差分値と、第2の所定領域A2の差分値とを入力する。そして、後続車両検出部33aは、第1の所定領域A1の差分値が所定値以上であるかを判断すると共に、第2の所定領域A2の差分値が所定値以上であるかを判断する。   Next, details of detection of the following vehicle by the following vehicle detection unit 33a will be described. As described above, the subsequent vehicle detection unit 33a inputs the difference value of the first predetermined area A1 and the difference value of the second predetermined area A2 detected by the difference value detection unit 32b. Then, the subsequent vehicle detection unit 33a determines whether the difference value of the first predetermined area A1 is equal to or greater than a predetermined value, and determines whether the difference value of the second predetermined area A2 is equal to or greater than the predetermined value.

次いで、後続車両検出部33aは、第1の所定領域A1と第2の所定領域A2とのうち、いずれか一方のみの所定領域A1,A2における差分値が所定値以上である場合、後続車両が二輪車であると判断し、双方の所定領域A1,A2における差分値が所定値以上である場合、後続車両が自動車であると判断する。また、後続車両検出部33aは、いずれの所定領域A1,A2についても差分値が所定値以上でない場合、後続車両が存在しないと判断する。   Next, when the difference value in only one of the first predetermined area A1 and the second predetermined area A2 is greater than or equal to the predetermined value, the subsequent vehicle detection unit 33a If it is determined that the vehicle is a two-wheeled vehicle and the difference value between the two predetermined areas A1 and A2 is equal to or greater than the predetermined value, it is determined that the following vehicle is an automobile. The subsequent vehicle detection unit 33a determines that there is no subsequent vehicle when the difference value is not greater than or equal to the predetermined value for any of the predetermined areas A1 and A2.

ここで、上記のように判断する理由は以下の通りである。まず、自車両Vの真後ろに後続車両が存在する場合、後続車両が差分となって検出されるため、差分値は大きくなる傾向にある。また、二輪車については車線の一側に寄って走行することが多い。このため、第1及び第2の所定領域A1,A2のうちいずれか一方のみの差分値が大きくなる傾向にある。これに対して、後続車両が自動車である場合、自動車は車線の一側に寄って走行することができないことから、第1及び第2の所定領域A1,A2の双方の差分値が大きくなる傾向にある。   Here, the reason for determining as described above is as follows. First, when there is a subsequent vehicle immediately behind the host vehicle V, the subsequent vehicle is detected as a difference, so the difference value tends to increase. Also, motorcycles often run closer to one side of the lane. For this reason, the difference value of only one of the first and second predetermined areas A1 and A2 tends to increase. On the other hand, when the following vehicle is an automobile, the difference between both the first and second predetermined areas A1 and A2 tends to increase because the automobile cannot travel to one side of the lane. It is in.

このように、本実施形態に係る後続車両検出部33aは、第1及び第2の所定領域A1,A2の差分値の隔たりから後続の二輪車を検出できる構成となっている。   Thus, the subsequent vehicle detection unit 33a according to the present embodiment is configured to be able to detect the subsequent two-wheeled vehicle from the difference between the difference values of the first and second predetermined areas A1 and A2.

また、隣接車両検出部33bによる隣接車両の検出の詳細について説明する。上記したように、隣接車両検出部33bは、差分値検出部32bにより検出された第3の所定領域A3の差分値と、第4の所定領域A4の差分値とを入力する。そして、隣接車両検出部33bは、第3の所定領域A3の差分値が所定の閾値以上であるかを判断すると共に、第4の所定領域A4の差分値が所定の閾値以上であるかを判断する。   Details of detection of an adjacent vehicle by the adjacent vehicle detection unit 33b will be described. As described above, the adjacent vehicle detection unit 33b inputs the difference value of the third predetermined area A3 and the difference value of the fourth predetermined area A4 detected by the difference value detection unit 32b. Then, the adjacent vehicle detection unit 33b determines whether the difference value of the third predetermined area A3 is equal to or greater than a predetermined threshold value, and determines whether the difference value of the fourth predetermined area A4 is equal to or greater than the predetermined threshold value. To do.

次いで、隣接車両検出部33bは、第3の所定領域A3の差分値が所定の閾値以上であると判断した場合、第3の所定領域A3の隣接車両が存在すると判断する。また、第4の所定領域A4の差分値が所定の閾値以上であると判断した場合、第4の所定領域A4の隣接車両が存在すると判断する。   Next, when the adjacent vehicle detection unit 33b determines that the difference value of the third predetermined area A3 is equal to or greater than a predetermined threshold, the adjacent vehicle detection unit 33b determines that there is an adjacent vehicle of the third predetermined area A3. When it is determined that the difference value of the fourth predetermined area A4 is equal to or greater than a predetermined threshold, it is determined that there is an adjacent vehicle in the fourth predetermined area A4.

再度、図3に基づいて計算機30の構成を説明する。計算機30は閾値変更部(閾値変
更手段)34を備えている。閾値変更部34は、隣接車両検出部33bにより隣接車両を検出する際に行われる閾値処理の閾値を変更するものである。
Again, the structure of the computer 30 is demonstrated based on FIG. The computer 30 includes a threshold changing unit (threshold changing means) 34. The threshold value changing unit 34 changes the threshold value of the threshold value processing that is performed when the adjacent vehicle detecting unit 33b detects the adjacent vehicle.

より詳細に、閾値変更部34は、後続車両検出部33aにより後続車両が二輪車であると判断された場合、第3の所定領域A3と第4の所定領域A4のうち、二輪車が存在すると判断された側の領域について、所定の閾値を低くする。ここで、第3の所定領域A3と第4の所定領域A4とのうち、二輪車が存在する側の所定領域では二輪車が存在することにより隣接車両を検出し難くなってしまう。このため、閾値を低くすることにより隣接車両を検出し易くして、隣接車両の検出漏れの頻度を低減させることができる。   More specifically, when the subsequent vehicle detection unit 33a determines that the succeeding vehicle is a two-wheeled vehicle, the threshold value changing unit 34 determines that the two-wheeled vehicle is present in the third predetermined region A3 and the fourth predetermined region A4. The predetermined threshold is lowered for the region on the other side. Here, in the predetermined area on the side where the two-wheeled vehicle is present among the third predetermined area A3 and the fourth predetermined area A4, it is difficult to detect the adjacent vehicle. For this reason, it is easy to detect the adjacent vehicle by lowering the threshold value, and the frequency of detection omission of the adjacent vehicle can be reduced.

なお、隣接車両検出部33bは、以下に記載するように、差分値を波形化して隣接車線を検出するようになっていてもよい。   In addition, as described below, the adjacent vehicle detection unit 33b may detect the adjacent lane by converting the difference value into a waveform.

図5は、図3に示した隣接車両検出部33bによる差分波形の生成の様子を示す概略図である。なお、図5に示す例では、便宜上第3の所定領域A3のみを用いて説明するが、第4の所定領域A4についても同じである。図5に示すように、隣接車両検出部33bは、差分画像PDのうち第3の所定領域A3に相当する部分から、差分波形DWを生成する。この際、隣接車両検出部33bは、視点変換により立体物が倒れ込む方向に沿って、差分波形DWを生成する。 FIG. 5 is a schematic diagram illustrating how the differential waveform is generated by the adjacent vehicle detection unit 33b illustrated in FIG. In the example shown in FIG. 5, only the third predetermined area A3 is described for convenience, but the same applies to the fourth predetermined area A4. As shown in FIG. 5, the adjacent vehicle detection unit 33b generates a differential waveform DW t from a portion corresponding to the third predetermined area A3 in the differential image PD t . At this time, the adjacent vehicle detection unit 33b generates the differential waveform DW t along the direction in which the three-dimensional object falls due to the viewpoint conversion.

具体的に説明すると、まず隣接車両検出部33bは、差分画像DWのデータ上において立体物が倒れ込む方向上の線Laを定義する。そして、隣接車両検出部33bは、線La上において所定の差分を示す差分画素DPの数をカウントする。ここで、差分画像DWの画素値が「0」「1」で表現されているもとし、「1」を示す画素の数がカウントされる。 Specifically, first, the adjacent vehicle detection unit 33b defines a line La in the direction in which the three-dimensional object falls on the data of the difference image DW t . Then, the adjacent vehicle detection unit 33b counts the number of difference pixels DP indicating a predetermined difference on the line La. Here, the pixel value of the difference image DW t is expressed by “0” and “1”, and the number of pixels indicating “1” is counted.

隣接車両検出部33bは、差分画素DPの数をカウントした後、線Laと接地線L1との交点CPを求める。そして、隣接車両検出部33bは、交点CPとカウント数とを対応付け、交点CPの位置に基づいて横軸位置(図5の紙面上下方向軸における位置)を決定し、カウント数から縦軸位置(図5の紙面左右方向軸における位置)を決定する。   The adjacent vehicle detection unit 33b counts the number of difference pixels DP, and then obtains an intersection CP between the line La and the ground line L1. Then, the adjacent vehicle detection unit 33b associates the intersection point CP with the count number, determines a horizontal axis position (a position on the vertical axis in FIG. 5) based on the position of the intersection point CP, and determines the vertical axis position from the count number. (Position on the horizontal axis in FIG. 5) is determined.

以下同様に、隣接車両検出部33bは、立体物が倒れ込む方向上の線を定義して、差分画素DPの数をカウントし、交点CPの位置に基づいて横軸位置を決定し、カウント数(差分画素DPの数)から縦軸位置を決定する。隣接車両検出部33bは、上記を順次繰り返して度数分布化することで差分波形DWを生成する。 Similarly, the adjacent vehicle detection unit 33b defines a line in the direction in which the three-dimensional object falls, counts the number of difference pixels DP, determines the horizontal axis position based on the position of the intersection CP, and counts ( The vertical axis position is determined from the number of difference pixels DP). The adjacent vehicle detection unit 33b generates the differential waveform DW t by sequentially repeating the above and making a frequency distribution.

なお、図5に示すように、立体物が倒れ込む方向上の線Laと線Lbとは第4の所定領域A4と重複する距離が異なっている。このため、第4の所定領域A4が差分画素DPで満たされているとすると、線Lb上よりも線La上の方が差分画素DPの数が多くなってしまう。このため、隣接車両検出部33bは、差分画素DPのカウント数から縦軸位置を決定する場合、立体物が倒れ込む方向上の線La,Lbと検出領域A1とが重複する距離に基づいて正規化する。具体例を挙げると、図5において線La上の差分画素DPは6つあり、線Lb上の差分画素DPは5つである。このため、図5においてカウント数から縦軸位置を決定するにあたり、隣接車両検出部33bは、カウント数を重複距離で除算するなどして正規化する。これにより、差分波形DWに示すように、立体物が倒れ込む方向上の線La,Lbに対応する差分波形DWの値はほぼ同じとなっている。 As shown in FIG. 5, the line La and the line Lb in the direction in which the three-dimensional object collapses have different distances overlapping the fourth predetermined area A4. For this reason, if the fourth predetermined region A4 is filled with the difference pixels DP, the number of difference pixels DP is greater on the line La than on the line Lb. For this reason, when determining the vertical axis position from the count number of the difference pixel DP, the adjacent vehicle detection unit 33b normalizes based on the distance at which the lines La and Lb in the direction in which the three-dimensional object falls and the detection area A1 overlap. To do. As a specific example, in FIG. 5, there are six difference pixels DP on the line La, and there are five difference pixels DP on the line Lb. Therefore, in determining the vertical axis position from the count number in FIG. 5, the adjacent vehicle detection unit 33b normalizes the count number by dividing it by the overlap distance. Thus, as shown in the difference waveform DW t, the line La on the direction the three-dimensional object collapses, the value of the differential waveform DW t corresponding to Lb is substantially the same.

差分波形DWの生成後、隣接車両検出部33bは、差分波形DWのピークが所定の閾値以上であるか否かを判断する。ここで、差分波形DWのピークが所定の閾値以上でない場合、すなわち差分が殆どなく、撮像画像P内には立体物が存在しないと考えられる
。このため、隣接車両検出部33bは、隣接車両が存在しないと判断する。一方、差分波形DWのピークが所定値以上であると判断した場合、立体物検出部33は、隣接車線に隣接車両が走行していると判断する。
After the generation of the differential waveform DW t , the adjacent vehicle detection unit 33b determines whether or not the peak of the differential waveform DW t is equal to or greater than a predetermined threshold value. Here, when the peak of the difference waveform DW t is not equal to or greater than the predetermined threshold, that is, there is almost no difference, and it is considered that there is no three-dimensional object in the captured image P. For this reason, the adjacent vehicle detection unit 33b determines that there is no adjacent vehicle. On the other hand, when it is determined that the peak of the difference waveform DW t is equal to or greater than the predetermined value, the three-dimensional object detection unit 33 determines that the adjacent vehicle is traveling in the adjacent lane.

次に、本実施形態に係る走行支援方法について、フローチャートを参照して説明する。図6は、本実施形態に係る走行支援方法の一例を示すフローチャートである。   Next, the driving support method according to the present embodiment will be described with reference to a flowchart. FIG. 6 is a flowchart showing an example of the driving support method according to the present embodiment.

まず、図6に示すように、計算機30は、車速センサ20からの信号に基づいて、自車両Vが所定速度以下であるか否かを判断する(S1)。自車両Vが所定速度以下であると判断した場合(S1:YES)、位置合わせ部32aは位置合わせを行う。そして、差分値検出部32bは、第3及び第4の所定領域A3,A4の差分を検出する(S2)。   First, as shown in FIG. 6, the computer 30 determines whether or not the host vehicle V is equal to or lower than a predetermined speed based on a signal from the vehicle speed sensor 20 (S1). When it is determined that the host vehicle V is equal to or lower than the predetermined speed (S1: YES), the alignment unit 32a performs alignment. And the difference value detection part 32b detects the difference of 3rd and 4th predetermined area | region A3, A4 (S2).

次いで、隣接車両検出部33bは、第3及び第4の所定領域A3,A4におけるいずれ一方又は双方が所定の閾値以上であるか否かを判断する(S3)。第3及び第4の所定領域A3,A4におけるいずれ一方又は双方が所定の閾値以上であると判断した場合(S3:YES)、隣接車両検出部33bは、隣接車両が存在すると判断し、その旨の信号を警報装置40に送信する。これにより、警報装置40は警報を行い(S4)、図6に示す処理は終了する。   Next, the adjacent vehicle detection unit 33b determines whether one or both of the third and fourth predetermined areas A3 and A4 is equal to or greater than a predetermined threshold (S3). When it is determined that one or both of the third and fourth predetermined areas A3 and A4 are equal to or greater than the predetermined threshold (S3: YES), the adjacent vehicle detection unit 33b determines that there is an adjacent vehicle, and accordingly. Is transmitted to the alarm device 40. Thereby, the alarm device 40 issues an alarm (S4), and the process shown in FIG. 6 ends.

一方、第3及び第4の所定領域A3,A4におけるいずれ一方又は双方が所定の閾値以上でないと判断した場合(S3:NO)、後続車両検出部33aは隣接車両が存在しないと判断する。そして、差分値検出部32bは、第1及び第2の所定領域A1,A2の差分を検出する(S5)。   On the other hand, when it is determined that one or both of the third and fourth predetermined areas A3 and A4 are not equal to or greater than the predetermined threshold (S3: NO), the subsequent vehicle detection unit 33a determines that there is no adjacent vehicle. And the difference value detection part 32b detects the difference of 1st and 2nd predetermined area | region A1, A2 (S5).

その後、後続車両検出部33aは、第1及び第2の所定領域A1,A2におけるいずれ一方又は双方が所定値以上であるか否かを判断する(S6)。第1及び第2の所定領域A1,A2におけるいずれ一方又は双方が所定値以上でないと判断した場合(S6:NO)、閾値変更部34は、隣接車両の判断の際に用いた所定の閾値を「高」に設定する(S7)。その後、図6に示す処理は終了する。   Thereafter, the succeeding vehicle detection unit 33a determines whether one or both of the first and second predetermined areas A1 and A2 are equal to or greater than a predetermined value (S6). When it is determined that one or both of the first and second predetermined areas A1 and A2 are not equal to or greater than the predetermined value (S6: NO), the threshold changing unit 34 sets the predetermined threshold used when determining the adjacent vehicle. “High” is set (S7). Thereafter, the process shown in FIG. 6 ends.

第1及び第2の所定領域A1,A2におけるいずれ一方又は双方が所定値以上であると判断した場合(S6:YES)、後続車両検出部33aは一方のみが所定値以上であるか否かを判断する(S8)。一方のみが所定値以上であると判断した場合(S8:YES)、後続車両検出部33aは自車両Vの真後ろに二輪車が存在すると判断する。そして、閾値変更部34は、隣接車両の判断の際に用いた所定の閾値を「低」に設定する(S9)。その後、図6に示す処理は終了する。ここで、第3の所定領域A3と第4の所定領域A4とのうち、二輪車が存在する側の所定領域では二輪車が存在することにより隣接車両を検出し難くなってしまう。このため、所定の閾値を低くすることにより隣接車両を検出し易くして、隣接車両の検出漏れの頻度を低減させることができる。   When it is determined that one or both of the first and second predetermined areas A1 and A2 are equal to or greater than the predetermined value (S6: YES), the following vehicle detection unit 33a determines whether only one is equal to or greater than the predetermined value. Judgment is made (S8). When it is determined that only one of them is equal to or greater than the predetermined value (S8: YES), the subsequent vehicle detection unit 33a determines that a two-wheeled vehicle is present immediately behind the host vehicle V. Then, the threshold value changing unit 34 sets the predetermined threshold value used in determining the adjacent vehicle to “low” (S9). Thereafter, the process shown in FIG. 6 ends. Here, in the predetermined area on the side where the two-wheeled vehicle is present among the third predetermined area A3 and the fourth predetermined area A4, it is difficult to detect the adjacent vehicle. For this reason, it is easy to detect the adjacent vehicle by lowering the predetermined threshold value, and the frequency of detection omission of the adjacent vehicle can be reduced.

一方、一方のみが所定値以上でないと判断した場合(S8:NO)、すなわち双方が所定値以上である場合、後続車両検出部33aは自車両Vの真後ろに自動車が存在すると判断する。そして、閾値変更部34は、隣接車両の判断の際に用いた所定の閾値を「高」に設定する(S7)。その後、図6に示す処理は終了する。   On the other hand, when it is determined that only one of them is not equal to or greater than the predetermined value (S8: NO), that is, when both are equal to or greater than the predetermined value, the subsequent vehicle detection unit 33a determines that there is an automobile immediately behind the host vehicle V. Then, the threshold value changing unit 34 sets the predetermined threshold value used in the determination of the adjacent vehicle to “high” (S7). Thereafter, the process shown in FIG. 6 ends.

ところで、自車両Vが所定速度以下でないと判断した場合(S1:NO)、位置合わせ部32aは位置合わせを行う。そして、閾値変更部34は、隣接車両の判断の際に用いた所定の閾値を「高」に設定する(S10)。   By the way, when it is determined that the host vehicle V is not below the predetermined speed (S1: NO), the alignment unit 32a performs alignment. Then, the threshold value changing unit 34 sets the predetermined threshold value used in the determination of the adjacent vehicle to “high” (S10).

次に、差分値検出部32bは、第3及び第4の所定領域A3,A4の差分を検出する(
S11)。そして、隣接車両検出部33bは、第3及び第4の所定領域A3,A4におけるいずれ一方又は双方が所定の閾値以上であるか否かを判断する(S12)。第3及び第4の所定領域A3,A4におけるいずれ一方又は双方が所定の閾値以上であると判断した場合(S12:YES)、隣接車両検出部33bは、隣接車両が存在すると判断し、その旨の信号を警報装置40に送信する。これにより、警報装置40は警報を行い(S4)、図6に示す処理は終了する。
Next, the difference value detection unit 32b detects the difference between the third and fourth predetermined areas A3 and A4 (
S11). And the adjacent vehicle detection part 33b judges whether any one or both in 3rd and 4th predetermined area | region A3, A4 is more than a predetermined threshold value (S12). When it is determined that one or both of the third and fourth predetermined areas A3 and A4 are equal to or greater than the predetermined threshold (S12: YES), the adjacent vehicle detection unit 33b determines that there is an adjacent vehicle, and accordingly. Is transmitted to the alarm device 40. Thereby, the alarm device 40 issues an alarm (S4), and the process shown in FIG. 6 ends.

一方、第3及び第4の所定領域A3,A4におけるいずれ一方又は双方が所定の閾値以上でないと判断した場合(S12:NO)、警報は行われることなく、図6に示す処理は終了する。   On the other hand, when it is determined that one or both of the third and fourth predetermined areas A3 and A4 are not equal to or greater than the predetermined threshold (S12: NO), the process shown in FIG.

このようにして、本実施形態に係る走行支援装置1及び走行支援方法によれば、自車両Vの一方の側後方の隣接車線から区分線DLを跨いで自車両Vの直後方側まで設けられた第1の所定領域A1と、自車両Vの他方の側後方の隣接車線から区分線DLを跨いで自車両Vの直後方側まで設けられた第2の所定領域A2との双方の画像について、位置を合わせて差分値を検出し、それぞれの差分値の隔たりから二輪車を検出する。ここで、真後ろの二輪車は車線の一側に寄って走行していることが多く、第1の所定領域A1と第2の所定領域A2との差分値は真後ろに二輪車が存在する場合、一方のみが大きな値を示す傾向にある。このため、両者差分値の隔たりから真後ろの二輪車を検出することができる。また、カメラ10により得られた画像の第1の所定領域A1と第2の所定領域A2との差分値から二輪車を検出するため、カメラ10を複数備える必要が無い。従って、カメラ10の数を増加させる必要が無く、且つ、自車両Vの真後ろの二輪車について検出することができる。   Thus, according to the driving assistance device 1 and the driving assistance method according to the present embodiment, the vehicle is provided from the adjacent lane on the rear side of one side of the host vehicle V to the side immediately behind the host vehicle V across the dividing line DL. Both the first predetermined area A1 and the second predetermined area A2 provided from the adjacent lane on the other side rear side of the host vehicle V to the immediate rear side of the host vehicle V across the dividing line DL. The difference value is detected by matching the positions, and the two-wheeled vehicle is detected from the difference between the difference values. Here, the two-wheeled vehicle directly behind is often running near one side of the lane, and the difference value between the first predetermined region A1 and the second predetermined region A2 is only one when the two-wheeled vehicle is directly behind. Tend to show large values. For this reason, it is possible to detect the motorcycle immediately behind the difference between the two difference values. Further, since the two-wheeled vehicle is detected from the difference value between the first predetermined area A1 and the second predetermined area A2 of the image obtained by the camera 10, there is no need to provide a plurality of cameras 10. Therefore, it is not necessary to increase the number of cameras 10 and it is possible to detect a motorcycle just behind the host vehicle V.

また、第1の所定領域A1と第2の所定領域A2とは、自車両Vが走行する車線の略中心線近傍から二分するように当該車線の左右にそれぞれ設定されているため、例えば真後ろの二輪車が自車両を追い越そうとしている場合など、左右どちら側から追い越しをしてくるのかを予測することができる。   The first predetermined area A1 and the second predetermined area A2 are set on the left and right sides of the lane so as to bisect from the vicinity of the approximate center line of the lane in which the host vehicle V travels. When a two-wheeled vehicle is about to overtake its own vehicle, it can be predicted from which side the vehicle will pass.

また、第1の所定領域A1と第2の所定領域A2とのいずれか一方のみの差分値が所定値以上である場合、後続車両を二輪車と判断し、第1の所定領域A1と第2の所定領域A2との双方の差分値が所定値以上である場合、後続車両を自動車と判断する。ここで、真後ろの二輪車については第1の所定領域A1と第2の所定領域A2との差分値の一方のみが大きな値を示す傾向にあるが、自動車については車線の一側のみに寄って走行することが無く、双方の差分値が所定値以上となる。従って、後続車両が二輪車か自動車かを判断することができる。   Further, when the difference value of only one of the first predetermined area A1 and the second predetermined area A2 is equal to or greater than the predetermined value, the subsequent vehicle is determined to be a two-wheeled vehicle, and the first predetermined area A1 and the second predetermined area A2 When the difference value between the predetermined area A2 and the predetermined area A2 is equal to or greater than the predetermined value, the subsequent vehicle is determined to be an automobile. Here, only one of the difference values between the first predetermined area A1 and the second predetermined area A2 tends to show a large value for a motorcycle at the rear, but the car travels only on one side of the lane. The difference value between the two is not less than a predetermined value. Therefore, it can be determined whether the following vehicle is a two-wheeled vehicle or an automobile.

また、隣接車線に設けられた第3の所定領域A3の画像と第4の所定領域A4の画像とについてそれぞれの差分値を検出し、差分値が所定の閾値以上である場合、隣接車両が存在すると検出する。また、後続車両が二輪車であると判断された場合、第3の所定領域A3と第4の所定領域A4のうち、後続車両が存在すると判断された側の領域について、所定の閾値を低くする。ここで、第3の所定領域A3と第4の所定領域A4とのうち、二輪車が存在する側の所定領域では二輪車が存在することにより隣接車両を検出し難くなってしまう。このため、閾値を低くすることにより隣接車両を検出し易くして、隣接車両の検出漏れの頻度を低減させることができる。   Further, when the difference value is detected for the image of the third predetermined area A3 and the image of the fourth predetermined area A4 provided in the adjacent lane, and the difference value is equal to or greater than a predetermined threshold, there is an adjacent vehicle. Then detect. Further, when it is determined that the following vehicle is a two-wheeled vehicle, a predetermined threshold value is lowered for an area of the third predetermined area A3 and the fourth predetermined area A4 on which the subsequent vehicle is determined to exist. Here, in the predetermined area on the side where the two-wheeled vehicle is present among the third predetermined area A3 and the fourth predetermined area A4, it is difficult to detect the adjacent vehicle. For this reason, it is easy to detect the adjacent vehicle by lowering the threshold value, and the frequency of detection omission of the adjacent vehicle can be reduced.

また、自車両Vの速度が所定速度以下である場合に、第3の所定領域A3と第4の所定領域A4のうち、後続車両が存在すると判断された側の領域について、所定の閾値を低くする。ここで、速度が所定速度以下である場合、真後ろの二輪車は自車両を追い越し易く、二輪車が自車両を追い越そうとして自車両Vと第3の所定領域A3や第4の所定領域A
4との間に位置することが多くなる。このため、隣接車両を検出し難くなってしまうことが多い。よって、自車両Vの速度が所定速度以下である場合のみに所定の閾値を低くすることで、適切に所定の閾値を変更することができる。
In addition, when the speed of the host vehicle V is equal to or lower than the predetermined speed, a predetermined threshold value is lowered for an area of the third predetermined area A3 and the fourth predetermined area A4 on which the subsequent vehicle is determined to exist. To do. Here, when the speed is equal to or lower than the predetermined speed, the two-wheeled vehicle immediately behind the vehicle easily overtakes the own vehicle, and the two-wheeled vehicle tries to overtake the own vehicle V and the third predetermined area A3 or the fourth predetermined area A.
4 is often located between. For this reason, it is often difficult to detect adjacent vehicles. Therefore, the predetermined threshold can be appropriately changed by lowering the predetermined threshold only when the speed of the host vehicle V is equal to or lower than the predetermined speed.

以上、実施形態に基づき本発明を説明したが、本発明は上記実施形態に限られるものでは無く、本発明の趣旨を逸脱しない範囲で、変更を加えてもよい。   As described above, the present invention has been described based on the embodiments, but the present invention is not limited to the above-described embodiments, and modifications may be made without departing from the spirit of the present invention.

例えば、上記実施形態において、自車両Vの車速を速度センサ20からの信号に基づいて判断しているが、これに限らず、異なる時刻の複数の画像から速度を推定するようにしてもよい。この場合、車速センサが不要となり、構成の簡素化を図ることができる。   For example, in the above embodiment, the vehicle speed of the host vehicle V is determined based on a signal from the speed sensor 20, but the present invention is not limited to this, and the speed may be estimated from a plurality of images at different times. In this case, a vehicle speed sensor becomes unnecessary, and the configuration can be simplified.

なお、上記実施形態においては撮像した現時刻の画像と一時刻前の画像とを鳥瞰図に変換し、変換した鳥瞰図の位置合わせを行っているが、これに限定されない。すなわち、現時刻の画像と一時刻前の画像との位置合わせを行い、位置合わせを行った両画像の差分から差分画像PDを生成し、差分画像PDを鳥瞰図に変換するようにしてもよい。 In the above-described embodiment, the captured image at the current time and the image one hour before are converted into a bird's-eye view and the converted bird's-eye view is aligned. However, the present invention is not limited to this. That is, the current image and the previous image are aligned, a difference image PD t is generated from the difference between the aligned images, and the difference image PD t is converted into a bird's eye view. Good.

さらに、上記実施形態においては差分値から隣接車両や後続車両を検出しているが、この差分値は現時刻にて得られた画像と1制御周期前に得られた画像との差分値のみならず、現時刻にて得られた画像と数制御周期前に得られた画像との差分値であってもよいし、得られた差分値を複数回分蓄積して得られた合計値や平均値などであってもよい。   Further, in the above embodiment, the adjacent vehicle and the following vehicle are detected from the difference value. However, if this difference value is only the difference value between the image obtained at the current time and the image obtained before one control cycle. Alternatively, it may be a difference value between an image obtained at the current time and an image obtained before several control cycles, or a total value or an average value obtained by accumulating the obtained difference values for a plurality of times. It may be.

1…走行支援装置
10…カメラ(撮像手段)
20…車速センサ
30…計算機
31…視点変換部(視点変換手段)
32…差分検出部
32a…位置合わせ部(位置合わせ手段)
32b…差分値検出部(差分地検出手段)
33…移動体検出部
33a…後続車両検出部(後続車両検出手段)
33b…隣接車両検出部(隣接車両検出手段)
34…閾値変更部(閾値変更手段)
40…警報装置
A1〜A4…所定領域
CP…交点
DL…区分線
DP…差分画素
DW…差分波形
L1…接地線
La,Lb…立体物が倒れ込む方向上の線
PB…鳥瞰画像
PD…差分画像
V…自車両
DESCRIPTION OF SYMBOLS 1 ... Driving assistance apparatus 10 ... Camera (imaging means)
20 ... Vehicle speed sensor 30 ... Computer 31 ... Viewpoint conversion unit (viewpoint conversion means)
32 ... Difference detection unit 32a ... Positioning unit (positioning means)
32b ... Difference value detection unit (difference place detection means)
33 ... Moving body detection unit 33a ... Subsequent vehicle detection unit (subsequent vehicle detection means)
33b ... Adjacent vehicle detection unit (adjacent vehicle detection means)
34 ... Threshold change unit (threshold change means)
40 ... alarm devices A1 to A4 ... predetermined region CP ... intersection DL ... partition line DP ... difference pixel DW t ... difference waveform L1 ... ground line La, Lb ... line PB t in the direction in which the three-dimensional object collapses ... bird's-eye view image PD t ... Difference image V ... Own vehicle

Claims (6)

移動体後部に搭載され、当該移動体の後方を撮像する撮像手段と、
前記撮像手段による撮像にて得られた画像を鳥瞰視される状態へ視点変換する視点変換手段と、
前記視点変換手段により視点変換された異なる時刻の、前記移動体の一方の側後方の隣接車線から区分線を跨いで前記移動体の直後方側まで設けられた第1の所定領域の画像と、前記移動体の他方の側後方の隣接車線から区分線を跨いで前記移動体の直後方側まで設けられた第2の所定領域の画像とについて、それぞれ個別に位置を合わせる位置合わせ手段と、
前記位置合わせ手段により位置合わせされた異なる時刻の第1の所定領域及び第2の所定領域の画像データそれぞれの差分値を検出する差分値検出手段と、
前記差分値検出手段により検出された第1の所定領域の差分値と第2の所定領域の差分値との隔たりから後続の二輪車を検出する後続車両検出手段と、
を備えることを特徴とする走行支援装置。
An imaging means mounted on the rear of the mobile body and imaging the rear of the mobile body;
Viewpoint conversion means for converting the viewpoint of the image obtained by imaging by the imaging means to a bird's-eye view;
Images of a first predetermined area provided at a different time when the viewpoint is converted by the viewpoint conversion unit, from the adjacent lane on the rear side of the one side of the moving body to a side immediately after the moving body, across the dividing line; Positioning means for individually aligning the positions of the second predetermined area images provided from the adjacent lane on the other side rear side of the moving body to the immediate rear side of the moving body across a dividing line;
Difference value detecting means for detecting difference values of the image data of the first predetermined area and the second predetermined area at different times aligned by the alignment means;
Subsequent vehicle detection means for detecting the following two-wheeled vehicle from the difference between the difference value of the first predetermined area detected by the difference value detection means and the difference value of the second predetermined area;
A driving support apparatus comprising:
前記第1の所定領域と前記第2の所定領域とは、前記移動体が走行する車線の略中心線近傍から二分するように当該車線の左右にそれぞれ設定されている
ことを特徴とする請求項1に記載の走行支援装置。
The first predetermined area and the second predetermined area are respectively set on the left and right sides of the lane so as to be divided into two substantially from the vicinity of the center line of the lane in which the moving body travels. The travel support device according to 1.
前記後続車両検出手段は、前記第1の所定領域と前記第2の所定領域とのいずれか一方のみの差分値が所定値以上である場合、後続車両を二輪車と判断し、前記第1の所定領域と前記第2の所定領域との双方の差分値が所定値以上である場合、後続車両を自動車と判断する
ことを特徴とする請求項2に記載の走行支援装置。
When the difference value of only one of the first predetermined area and the second predetermined area is greater than or equal to a predetermined value, the subsequent vehicle detecting means determines that the subsequent vehicle is a two-wheeled vehicle, and the first predetermined area is the first predetermined area. The driving support device according to claim 2, wherein if the difference value between the area and the second predetermined area is equal to or greater than a predetermined value, the subsequent vehicle is determined to be an automobile.
前記移動体が走行する車線に隣接する隣接車線を走行する隣接車両を検出する隣接車両検出手段と、
前記隣接車両検出手段が隣接車両を検出する際に行われる閾値処理の閾値を変更する閾値変更手段と、をさらに備え、
前記位置合わせ手段は、前記視点変換手段により視点変換された異なる時刻の、前記移動体の一方の側後方の隣接車線に設けられた第3の所定領域の画像と、前記移動体の他方の側後方の隣接車線に設けられた第4の所定領域の画像とについて、それぞれ個別に位置を合わせ、
前記差分値検出手段は、前記位置合わせ手段により位置合わせされた異なる時刻の第3の所定領域及び第4の所定領域の画像データそれぞれの差分値を検出し、
前記隣接車両検出手段は、前記差分値検出手段により検出された第3の所定領域の差分値と第4の所定領域とのいずれか一方の差分値が所定の閾値以上である場合、隣接車両が存在すると検出し、
前記閾値変更手段は、前記後続車両検出手段により後続車両が二輪車であると判断された場合、前記第3の所定領域と前記第4の所定領域のうち、後続車両が存在すると判断された側の領域について、前記所定の閾値を低くする
ことを特徴とする請求項1から請求項3のいずれか1項に記載の走行支援装置。
An adjacent vehicle detecting means for detecting an adjacent vehicle traveling in an adjacent lane adjacent to a lane in which the moving body travels;
Threshold value changing means for changing a threshold value of threshold processing performed when the adjacent vehicle detection means detects an adjacent vehicle; and
The positioning means includes an image of a third predetermined area provided in an adjacent lane at the rear of one side of the moving body at a different time when the viewpoint is converted by the viewpoint converting means, and the other side of the moving body. For the image of the fourth predetermined area provided in the rear adjacent lane, individually align the position,
The difference value detection means detects a difference value of each of the image data of the third predetermined area and the fourth predetermined area at different times aligned by the alignment means,
When the difference value of either the third predetermined area or the fourth predetermined area detected by the difference value detecting means is greater than or equal to a predetermined threshold, the adjacent vehicle detection means Detects that it exists,
The threshold value changing means, when the succeeding vehicle detecting means judges that the succeeding vehicle is a two-wheeled vehicle, of the third predetermined area and the fourth predetermined area on the side where the succeeding vehicle is judged to exist. The driving support device according to any one of claims 1 to 3, wherein the predetermined threshold is lowered for a region.
前記閾値変更手段は、前記移動体の速度が所定速度以下である場合に、前記第3の所定領域と前記第4の所定領域のうち、後続車両が存在すると判断された側の領域について、前記所定の閾値を低くする
ことを特徴とする請求項4に記載の走行支援装置。
When the speed of the moving body is equal to or lower than a predetermined speed, the threshold value changing unit is configured to determine, on the side of the third predetermined area and the fourth predetermined area, on the side where it is determined that a subsequent vehicle exists. The driving support device according to claim 4, wherein the predetermined threshold value is lowered.
移動体後部から、当該移動体の後方を撮像する撮像工程と、
前記撮像工程における撮像にて得られた画像を鳥瞰視される状態へ視点変換する視点変換工程と、
前記視点変換工程において視点変換された異なる時刻の、前記移動体の一方の側後方の隣接車線から区分線を跨いで前記移動体の直後方側まで設けられた第1の所定領域の画像と、前記移動体の他方の側後方の隣接車線から区分線を跨いで前記移動体の直後方側まで設けられた第2の所定領域の画像とについて、それぞれ個別に位置を合わせる位置合わせ工程と、
前記位置合わせ工程において位置合わせされた異なる時刻の第1の所定領域及び第2の所定領域の画像データそれぞれの差分値を検出する差分値検出工程と、
前記差分値検出工程において検出された第1の所定領域の差分値と第2の所定領域の差分値との隔たりから後続の二輪車を検出する後続車両検出工程と、
を有することを特徴とする走行支援方法。
An imaging step of imaging the rear of the moving body from the rear of the moving body;
A viewpoint conversion step of converting the viewpoint of the image obtained by the imaging in the imaging step to a bird's-eye view;
Images of a first predetermined area provided at different times when the viewpoint is converted in the viewpoint conversion step, from adjacent lanes on the rear side of the one side of the moving body to a position just behind the moving body across the dividing line; An alignment step for individually aligning the position of the second predetermined area provided on the other side of the moving body from the adjacent lane on the rear side of the moving body to the immediate rear side of the moving body,
A difference value detection step of detecting a difference value between the image data of the first predetermined region and the second predetermined region at different times aligned in the alignment step;
A succeeding vehicle detecting step of detecting a succeeding two-wheeled vehicle from a gap between the difference value of the first predetermined region and the difference value of the second predetermined region detected in the difference value detecting step;
A driving support method characterized by comprising:
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