JP3473378B2 - Parking space detection device - Google Patents
Parking space detection deviceInfo
- Publication number
- JP3473378B2 JP3473378B2 JP05831098A JP5831098A JP3473378B2 JP 3473378 B2 JP3473378 B2 JP 3473378B2 JP 05831098 A JP05831098 A JP 05831098A JP 5831098 A JP5831098 A JP 5831098A JP 3473378 B2 JP3473378 B2 JP 3473378B2
- Authority
- JP
- Japan
- Prior art keywords
- obstacle
- parking space
- straight line
- vehicle
- approximate straight
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
- G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
- G01S2013/9314—Parking operations
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
- G01S15/88—Sonar systems specially adapted for specific applications
- G01S15/93—Sonar systems specially adapted for specific applications for anti-collision purposes
- G01S15/931—Sonar systems specially adapted for specific applications for anti-collision purposes of land vehicles
- G01S2015/932—Sonar systems specially adapted for specific applications for anti-collision purposes of land vehicles for parking operations
- G01S2015/933—Sonar systems specially adapted for specific applications for anti-collision purposes of land vehicles for parking operations for measuring the dimensions of the parking space when driving past
- G01S2015/935—Sonar systems specially adapted for specific applications for anti-collision purposes of land vehicles for parking operations for measuring the dimensions of the parking space when driving past for measuring the contour, e.g. a trajectory of measurement points, representing the boundary of the parking space
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
- G01S15/88—Sonar systems specially adapted for specific applications
- G01S15/93—Sonar systems specially adapted for specific applications for anti-collision purposes
- G01S15/931—Sonar systems specially adapted for specific applications for anti-collision purposes of land vehicles
- G01S2015/932—Sonar systems specially adapted for specific applications for anti-collision purposes of land vehicles for parking operations
- G01S2015/933—Sonar systems specially adapted for specific applications for anti-collision purposes of land vehicles for parking operations for measuring the dimensions of the parking space when driving past
- G01S2015/936—Sonar systems specially adapted for specific applications for anti-collision purposes of land vehicles for parking operations for measuring the dimensions of the parking space when driving past for measuring parking spaces extending transverse or diagonal to the driving direction, i.e. not parallel to the driving direction
Landscapes
- Traffic Control Systems (AREA)
- Measurement Of Velocity Or Position Using Acoustic Or Ultrasonic Waves (AREA)
Description
【０００１】[0001]
【発明の属する技術分野】この発明は車両駐車に関して
車両間のスペースに駐車できるかどうかの判断に活用さ
れる駐車空間検出装置に関する。BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a parking space detecting device which is utilized for determining whether or not a vehicle can be parked in a space between vehicles.
【０００２】[0002]
【従来の技術】従来の駐車空間検出装置としては、たと
えば特開平６−１２７３１８号公報のようなものがあ
る。この駐車空間検出装置は車両の前後端に横向きに超
音波センサを設け、それぞれのセンサの指向角の中心を
互いに外広がり方向とすることにより各超音波センサの
距離測定値は駐車車両前端の真横で急変し、車両後端の
超音波センサの距離測定値は駐車車両後端の真横で急変
するから、これらの急変点を用いて駐車スペースの端部
を検出することにより駐車スペースの長さを正確に求め
ようとしていた。2. Description of the Related Art As a conventional parking space detecting device, there is, for example, one disclosed in Japanese Patent Laid-Open No. 6-127318. This parking space detection device is equipped with ultrasonic sensors in the lateral direction at the front and rear ends of the vehicle, and the center of the directional angle of each sensor is set to the outward spreading direction so that the distance measurement value of each ultrasonic sensor is directly beside the front end of the parked vehicle. The distance measurement value of the ultrasonic sensor at the rear end of the vehicle suddenly changes just beside the rear end of the parked vehicle, so the length of the parking space can be determined by detecting the end of the parking space using these sudden change points. I was trying to find out exactly.
【０００３】[0003]
【発明が解決しようとする課題】しかしながら、このよ
うな従来の駐車空間検出装置にあっては、対象物までの
距離しか測定できない対物距離検出手段となっていたた
め、一般駐車場などの車両を斜めに整列して駐車させる
ような駐車場では駐車空間の長さを正確に求めることは
困難であるという問題点があった。この発明は、このよ
うな従来の問題点に着目してなされたもので、対象物ま
での距離および方向角を測距するセンサと自車の移動距
離およびヨー角の変化を検出する手段とを有し、それら
に基づいて対象の形状の一点の位置をセンサのサンプリ
ングタイム毎に計算して求め、さらにそれらの位置のデ
ータ点列から対象の形状を推定して駐車スペースの長さ
を求めることにより、従来の問題点を解決することを目
的としている。However, in such a conventional parking space detecting apparatus, since the object distance detecting means can measure only the distance to the object, the vehicle such as a general parking lot is slanted. There is a problem that it is difficult to accurately determine the length of the parking space in a parking lot that is lined up and parked. The present invention has been made in view of such conventional problems, and includes a sensor for measuring a distance to a target object and a direction angle, and a means for detecting a change in a moving distance and a yaw angle of a vehicle. Based on them, calculate the position of one point of the target shape for each sampling time of the sensor, and further estimate the target shape from the data point sequence of those positions to determine the length of the parking space. Therefore, it is intended to solve the conventional problems.
【０００４】[0004]
【課題を解決するための手段】上述の目的を達成するた
め請求項１記載の発明は、自車両から障害物までの距離
および方向角を検出する対物距離検出手段と、自車両の
移動距離およびヨー角の変化を検出する自車移動量検出
手段と、前記対物距離検出手段で得られた自車両から障
害物までの距離および方向角と前記自車移動量検出手段
で得られた地面に固定した基準座標系での自車両の移動
量に基づいて、障害物の一点の地面に固定した基準座標
系での位置データを演算して求める演算手段と、障害物
の形状を直線近似で推定して複数の近似直線を得るとと
もに、前記複数の近似直線のうちの一つの近似直線であ
る近似直線１を構成する障害物の複数個の位置データを
前記近似直線１の方向を示す単位ベクトル上に正射影し
た長さを求め、それらの長さの最大値を計算する一方、
前記近似直線１を構成する障害物に隣接する障害物の形
状を表す近似直線２を構成する複数個の位置データを前
記近似直線２の方向を示す単位ベクトル上に正射影した
長さを求め、それらの長さの最小値を計算し、この最小
値から前記最大値を減じたものを駐車スペースの幅とす
る演算を行う手段と、を備えることを特徴とする。請求
項２記載の発明は、請求項１記載の駐車空間検出装置に
おいて、前記近似直線１を構成する障害物の複数個の位
置データを前記近似直線１の方向を示す単位ベクトル上
へ正射影した長さを求め、それらの長さの最大値から最
小値を減じたものを障害物の幅とすることを特徴とす
る。請求項３記載の発明は、請求項１または２記載の駐
車空間検出装置において、前記障害物の形状を推定する
手段にハフ（Ｈｏｕｇｈ）変換による直線検出の手法を
用いることを特徴とする。In order to achieve the above object, an invention according to claim 1 is an object distance detecting means for detecting a distance and a direction angle from a vehicle to an obstacle, and a moving distance of the vehicle. Own vehicle movement amount detecting means for detecting a change in yaw angle, distance and direction angle from the own vehicle to the obstacle obtained by the object distance detecting means, and the own vehicle movement amount detecting means. Based on the amount of movement of the vehicle in the reference coordinate system fixed on the fixed ground, the reference coordinates fixed on the ground at one point of the obstacle
Computation means for computing position data in the system and obstacles
When the shape of is estimated by linear approximation and multiple approximate straight lines are obtained,
In general, one of the plurality of approximate straight lines is an approximate straight line.
Position data of multiple obstacles that make up the approximate straight line 1
Orthographically project onto the unit vector indicating the direction of the approximate straight line 1.
While calculating the maximum value of those lengths,
Shape of obstacles adjacent to the obstacles forming the approximate straight line 1
The position data of the approximate straight line 2
Orthogonal projection onto the unit vector indicating the direction of the approximate straight line 2
Find the lengths and calculate the minimum of those lengths
The value obtained by subtracting the maximum value from the above value is the width of the parking space.
And means for performing a calculation . According to a second aspect of the present invention, in the parking space detecting apparatus according to the first aspect, a plurality of position data of obstacles forming the approximate straight line 1 are orthographically projected onto a unit vector indicating the direction of the approximate straight line 1. It is characterized in that the length is obtained and the width of the obstacle is obtained by subtracting the minimum value from the maximum value of those lengths. The invention according to claim 3 is the parking space detecting apparatus according to claim 1 or 2 , wherein the means for estimating the shape of the obstacle uses a straight line detection method by Hough transform.
【０００５】[0005]
【発明の実施の形態】以下、この発明の実施の形態を図
面に基づいて説明する。図１は、本発明の構成を示すブ
ロック図である。まず構成を説明すると、本発明の駐車
距離検出装置は、対象までの距離および方向角を測定す
る対物距離検出手段１と、自車両の移動距離およびヨー
角の変化を検出する自車移動量検出手段２と、前記対物
距離検出手段１および自車移動量検出手段２から得られ
たデータに基づいて対象の形状を推定し、駐車スペース
の長さを演算する演算手段３から構成される。BEST MODE FOR CARRYING OUT THE INVENTION Embodiments of the present invention will be described below with reference to the drawings. FIG. 1 is a block diagram showing the configuration of the present invention. First, the configuration will be described. A parking distance detecting device of the present invention includes an object distance detecting means 1 for measuring a distance to a target and a direction angle, and a moving amount detecting method for detecting a change in a moving distance and a yaw angle of a vehicle. It comprises a means 2 and a computing means 3 for estimating the shape of the object based on the data obtained from the objective distance detecting means 1 and the vehicle moving amount detecting means 2 and calculating the length of the parking space.
【０００６】[0006]
【発明の効果】以上説明してきたように、この発明によ
れば、その構成を、対象物までの距離及び方向角を測距
するセンサと自車の移動量を算出する手段を有し、それ
らに基づいて対象の形状の一点の位置をセンサのサンプ
リングタイム毎に計算して求め、さらに隣接する障害物
同士の間隔は、複数の近似直線のうちのある一つの近似
直線１に属する位置データの、当該近似直線１の単位ベ
クトル上に正射影した値の最大値と、近似直線１が示す
障害物に隣接する障害物形状を示す近似直線２に属する
位置データの、近似直線２の単位ベクトル上に正射影し
た値の最小値との差によって演算する構成としたので、
一般駐車場などで車両が斜めに整列して駐車してある場
合でも駐車空間の長さを正確に求めることができるとい
う効果が得られる。As described above, according to the present invention, the structure thereof has a sensor for measuring a distance to a target object and a direction angle, and means for calculating the movement amount of the own vehicle. determined by calculating the position of a point of the target shape for each sampling time of the sensor based on the further adjacent obstacle
The space between them is the approximation of one of the approximation lines.
The unit vector of the approximate straight line 1 of the position data belonging to the straight line 1.
The maximum value of the values orthographically projected on the cuttle and the approximate straight line 1
Belongs to an approximate straight line 2 indicating the shape of an obstacle adjacent to the obstacle
Orthogonal projection of the position data on the unit vector of the approximate straight line 2
Since it is configured to calculate by the difference between the minimum value and the
Even if the vehicles are diagonally arranged and parked in a general parking lot, the length of the parking space can be accurately obtained.
【０００７】次に図３のフローチャートにより、作用を
説明する。まずドライバからの入力操作によって駐車空
間の推定を開始する。図４に示すように、推定を開始し
た時点ｔ＝０における後車軸点Ｐの位置を地面に固定し
た基準座標系の原点０（０，０）とし、そのときの車両
の進行方向を基準座標系のｘ軸とする（ステップ１１０
〜１２０）。Next, the operation will be described with reference to the flowchart of FIG. First, estimation of the parking space is started by an input operation from the driver. As shown in FIG. 4, the position of the rear axle point P at the time t = 0 when the estimation is started is the origin 0 (0, 0) of the reference coordinate system fixed on the ground, and the traveling direction of the vehicle at that time is the reference coordinate. The x-axis of the system (step 110)
~ 120).
【０００８】サンプリング時刻ｔ＝ｉτ毎に右輪の右車
輪速センサ１４のパルスの増分値ΔＰr （ｉ）および左
輪の左車輪速センサ１５のパルスの増分値ΔＰl （ｉ）
を計測する（ステップ１３０〜１４０）。このとき時刻
ｔ＝ｉτにおける基準座標系に対する自車両の位置Ｐ
（ｉ）（ｘp （ｉ），ｙp （ｉ），θ（ｉ））は、
ｘp （ｉ）＝ｘp （ｉ−１）＋（Ｒr ΔＰr （ｉ）＋Ｒl ΔＰl （ｉ））ｃｏ
ｓθ（ｉ）／２…（１）
ｙp （ｉ）＝ｙp （ｉ−１）＋（Ｒr ΔＰr （ｉ）＋Ｒl ΔＰl （ｉ））ｓｉ
ｎθ（ｉ）／２…（２）
θ（ｉ）＝θ（ｉ−１）＋（Ｒr ΔＰr （ｉ）−Ｒl ΔＰl （ｉ））／Ｔ…（
３）
で与えられる。ここでＲr は右車輪速センサ１４の１パ
ルス分の移動距離、Ｒlは左車輪速センサ１５の１パル
ス分の移動距離、Ｔはトレッド幅である。At each sampling time t = iτ, the pulse increment value ΔP r (i) of the right wheel speed sensor 14 for the right wheel and the pulse increment value ΔP l (i) of the left wheel speed sensor 15 for the left wheel.
Is measured (steps 130 to 140). At this time, the position P of the own vehicle with respect to the reference coordinate system at time t = iτ
(I) (x p (i), y p (i), θ (i)) is expressed as x p (i) = x p (i−1) + (R r ΔP r (i) + R l ΔP l ( i)) co sθ (i) / 2 ... (1) y p (i) = y p (i-1) + (R r ΔP r (i) + R l ΔP l (i)) si nθ (i) / 2 (2) θ (i) = θ (i−1) + (R r ΔP r (i) −R l ΔP l (i)) / T (3) Here, R r is a moving distance of 1 pulse of the right wheel speed sensor 14, R 1 is a moving distance of 1 pulse of the left wheel speed sensor 15, and T is a tread width.
【０００９】センサの取付け位置Ｂ（ｘb （ｉ），ｙb
（ｉ））が後車軸点Ｐから（ａ，ｂ）の位置にあるとす
ると、センサの取付け位置Ｂ（ｘb （ｉ），ｙb
（ｉ））は
、 ｘb （ｉ）＝ｘp （ｉ）＋ａｃｏｓθ（ｉ）−ｂｓｉｎθ（ｉ）…（４）
ｙb （ｉ）＝ｙp （ｉ）＋ａｃｏｓθ（ｉ）＋ｂｓｉｎθ（ｉ）…（５）
となる。Sensor mounting position B (x b (i), y b
Assuming that (i) is at the position (a, b) from the rear axle point P, the sensor mounting position B (x b (i), y b
(I)) is, x b (i) = x p (i) + acosθ (i) -bsinθ (i) ... (4) y b (i) = y p (i) + acosθ (i) + bsinθ (i) ... (5)
【００１０】そのときの超音波センサにより対象物まで
の距離ｌ（ｉ）および方向角Φ（ｉ）を計測する（ステ
ップ１５０）。このとき対象物の位置Ｓ（ｉ）（ｘs
（ｉ），ｙs （ｉ））は、
ｘs （ｉ）＝ｘb （ｉ）＋ｌｃｏｓ（θ（ｉ）＋Φ（ｉ））…（６）
ｙs （ｉ）＝ｙb （ｉ）＋ｌｓｉｎ（θ（ｉ）＋Φ（ｉ））…（７）
で計算される（ステップ１６０）。At this time, the ultrasonic sensor measures the distance l (i) to the object and the direction angle Φ (i) (step 150). At this time, the position of the object S (i) (x s
(I), y s (i)) is x s (i) = x b (i) + l cos (θ (i) + Φ (i)) ... (6) y s (i) = y b (i) + l sin (Θ (i) + Φ (i)) (7) is calculated (step 160).
【００１１】サンプリング時刻ｔ＝ｉτ毎に（６）式お
よび（７）式を計算することによって図５に示すように
対象物の形状を推定するデータ列が得られる。このデー
タ列から対象の形状を推定するために以下のようにハフ
変換の手法を用いる。図６に示すような直線に座標原点
から下ろした垂線の長さρ，ｘ軸とのなす角度αを用い
ると、その直線は以下の（８）式によって表わされる。
ρ＝ｘｃｏｓα＋ｙｓｉｎα…（８）
さて（８）式より対象の形状を推定するためのデータ列
（ｘs （ｉ），ｙs （ｉ））に対して決まる以下の
（９）式はρ，αに関する合成三角関数となりこの正弦
曲線（ハフ曲線）は点（ｘs （ｉ），ｙs （ｉ））を通
過するすべての直線群を表すことになる。
ρ＝ｘs （ｉ）ｃｏｓα＋ｙs （ｉ）ｓｉｎα…（９）
したがって与えられたデータ点列（ｘs （ｉ），ｙs
（ｉ））に対して（９）式を計算し、その都度ρ−α平
面上にハフ曲線を描くとその度数分布が得られる。この
後、ハフ曲線群の交点の度数の高いところを抽出する
と、それらはデータ点列に含まれていた直線または直線
群に相当する（α，ρ）の組となる。実際に行なうステ
ップとしては対象物の位置Ｓ（ｉ）（ｘs （ｉ），ｙs
（ｉ））に対して、αを−１８０°〜１８０°まで刻み
幅Δα°で変化させ、各αに対して（９）式よりρを計
算する（ステップ１７０）。By calculating the equations (6) and (7) at each sampling time t = iτ, a data string for estimating the shape of the object can be obtained as shown in FIG. In order to estimate the target shape from this data string, the Hough transform method is used as follows. If the straight line as shown in FIG. 6 is defined by the length ρ of the perpendicular drawn from the coordinate origin and the angle α formed by the x axis, the straight line is expressed by the following equation (8). ρ = x cos α + y sin α (8) Now, the following formula (9) determined for the data string (x s (i), y s (i)) for estimating the target shape from formula (8) is ρ, α the sine curve becomes synthetic trigonometric function about (Hough curve) point will represent all of the straight lines passing through (x s (i), y s (i)). ρ = x s (i) cosα + y s (i) sinα ... (9) thus given data point sequence (x s (i), y s
When the equation (9) is calculated for (i)) and the Hough curve is drawn on the ρ-α plane each time, the frequency distribution is obtained. After that, when the high frequency points of the intersections of the Hough curve group are extracted, they become a set of (α, ρ) corresponding to the straight line or the straight line group included in the data point sequence. The actual steps include the position S (i) (x s (i), y s of the object.
For (i)), α is changed in steps of Δα ° from −180 ° to 180 °, and ρ is calculated from equation (9) for each α (step 170).
【００１２】次に、求めたρと用意した（α，ρ）の２
次元配列（分解能はΔα，Δρ）の一致する要素に１を
加える（ステップ１８０）。Next, 2 of the obtained ρ and the prepared (α, ρ)
1 is added to the matching elements of the dimensional array (resolution is Δα, Δρ) (step 180).
【００１３】以上の１４０〜１８０のステップをサンプ
リングタイム毎にＮ回繰り返し（ステップ１９０〜２０
０）、（α，ρ）の２次元配列の要素で累積した度数が
極大値となるような要素を抽出し（ステップ２１０）、
図７に示すように得られた極大値の要素群Ｑｊ（αj ，
ρj ）（ｉ＝１，２，‥Ｍ、Ｍは得られた直線あるいは
線分の個数）を障害物の形状を表わす直線と推定する
（ステップ２２０）。The above steps 140 to 180 are repeated N times at each sampling time (steps 190 to 20).
0), (α, ρ) of the elements of the two-dimensional array, the element for which the accumulated frequency has a maximum value is extracted (step 210),
The element group Qj (α j , which has the maximum value obtained as shown in FIG.
ρ j ) (i = 1, 2, ... M, M is the number of obtained straight lines or line segments) is estimated as a straight line representing the shape of the obstacle (step 220).
【００１４】次に得られた障害物の形状を表わす直線群
およびデータ点列Ｓ（ｉ）（ｘs （ｉ），ｙs （ｉ））
から障害物の幅および駐車空間の幅を推定する方法を図
８に基づいて説明する。各Ｑj （αj ，ρj ）（ｊ＝
１，２，‥Ｍ）について、Ｑj に属する対象の位置のデ
ータ点列Ｓ（ｉ）（ｉ＝Ｊ＋１〜Ｊ＋ｍ、ここでＪ＝ｍ
1 ＋ｍ2 ＋…ｍj- 1 ，ｍj は累積度数）について単位ベ
クトルＵj ＝（ｃｏｓ（αj −π／２），ｓｉｎ（αj
−π／２）への正射影の長さｈ（ｉ）（ｉ＝Ｊ＋１〜Ｊ
＋ｍj 、ここでＪ＝ｍ1 ＋ｍ2 ＋…ｍj-1 、ｍj は累積
度数）を求める（ステップ２３０）。求めたｈ（ｉ）の
中から最小値ｈj_min とｈj_max とを求め、対応する障
害物の位置の点をＳj_min とＳj_max とする（ステップ
２４０）。障害物の幅Ｗojは、
Ｗoj＝ｈj_max −ｈj_min …（１０）
で与えられる（ステップ２５０）。Next, a group of straight lines and a data point sequence S (i) (x s (i), y s (i)) representing the shape of the obtained obstacle are obtained.
A method of estimating the width of the obstacle and the width of the parking space from will be described with reference to FIG. Each Q j (α j , ρ j ) (j =
1, 2, ..., M), the data point sequence S (i) (i = J + 1 to J + m, where J = m) of the target position belonging to Q j
Unit vector U j = (cos (α j −π / 2), sin (α j ) for 1 + m 2 + ... m j- 1 , m j is cumulative frequency)
Length h (i) of orthographic projection to −π / 2) (i = J + 1 to J
+ M j , where J = m 1 + m 2 + ... m j-1 , where m j is the cumulative frequency) is calculated (step 230). The minimum values h j_min and h j_max are calculated from the calculated h (i), and the points at the positions of the corresponding obstacles are set as S j_min and S j_max (step 240). The width W oj of the obstacle is given by W oj = h j — max −h j — min (10) (step 250).
【００１５】駐車スペースの傾きの方向はαj （ｊ＝１
〜Ｍ）の中央値αmed から推定する（ステップ２６
０）。駐車スペースの幅Ｗpjについては、Ｑj に隣接す
るＱj+1に属する対象の位置のデータ点列Ｓ（ｉ）（ｉ
＝Ｊ＋ｍj ＋１〜ｊ＋ｍj ＋ｍj+ 1 、ｍj+1 は累積度
数）について上と同様に単位ベクトルＵj+1 ＝（ｃｏｓ
（αj+1 −π／２），ｓｉｎ（αj+1 −π／２））への
正射影の長さｈ（ｉ）（ｉ＝Ｊ＋ｍj ＋１〜ｊ＋ｍj ＋
ｍj+1 、ｍj+1 は累積度数）を求め、求めたｈ（ｉ）の
中から最小値ｈj+1_min と最大値ｈj+1_max を求め、対
応する障害物の位置の点をＳj+1_min とＳj+1_max とす
るとき、
Ｗpj＝ｈj+1_min −ｈj_max …（１１）
で与えられる（ステップ２７０）。（１１）式で求めた
駐車スペースの幅Ｗpjが駐車可能なスペースのしきい値
Ｗth以上であれば駐車可能と判断し（ステップ２８０〜
２９０）、そうでなければ最初のステップ１１０に再度
駐車可能な空間を探索する。The direction of inclination of the parking space is α j (j = 1
~ M) from the median α med (step 26)
0). The width W pj parking space, data point sequence position of the object belonging to Q j + 1 adjacent to Q j S (i) (i
= J + m j +1 to j + m j + m j + 1 , m j + 1 is the cumulative frequency, and the unit vector U j + 1 = (cos
(Α j + 1 -π / 2 ), sin (α j + 1 -π / 2) orthogonal projection length h to) (i) (i = J + m j + 1~j + m j +
m j + 1 and m j + 1 are cumulative frequencies, and the minimum value h j + 1_min and the maximum value h j + 1_max are calculated from the calculated h (i), and the point of the position of the corresponding obstacle is determined. When S j + 1 _min and S j + 1 _max , W pj = h j + 1 _min −h j _max (11) is given (step 270). If the width W pj of the parking space obtained by the equation (11) is equal to or larger than the threshold value W th of the parking space, it is determined that the parking is possible (steps 280 to 280).
290), otherwise search for parking space again in the first step 110.
【００１６】[0016]
【発明の効果】以上説明してきたように、この発明によ
れば、その構成を、対象物までの距離および方向角を測
距するセンサと自車の移動量を算出する手段を有し、そ
れらに基づいて対象の形状の一点の位置をセンサのサン
プリングタイム毎に計算して求め、さらにそれらの位置
のデータ点列から対象の形状を推定して駐車スペースの
長さを演算する構成としたので、一般駐車場などで車両
が斜めに整列して駐車してある場合でも駐車空間の長さ
を正確に求めることができるという効果が得られる。As described above, according to the present invention, the structure thereof includes the sensor for measuring the distance to the object and the direction angle and the means for calculating the movement amount of the own vehicle. Based on the above, the position of one point of the target shape is calculated for each sampling time of the sensor, and the target shape is estimated from the data point sequence at those positions, and the length of the parking space is calculated. Even when the vehicles are diagonally arranged and parked in a general parking lot, the length of the parking space can be accurately obtained.
【図１】本発明の構成を示すブロック図である。FIG. 1 is a block diagram showing a configuration of the present invention.
【図２】実施の形態を示すブロック図である。FIG. 2 is a block diagram showing an embodiment.
【図３】実施の形態のアルゴリズムの流れを示すフロー
チャートである。FIG. 3 is a flowchart showing a flow of an algorithm of the embodiment.
【図４】車両の位置を表わすための地上座標系の定義を
説明するための図である。FIG. 4 is a diagram for explaining the definition of a ground coordinate system for representing the position of a vehicle.
【図５】距離センサから得られた障害物の測距データ点
列を示した図である。FIG. 5 is a diagram showing a distance measurement data point sequence of an obstacle obtained from a distance sensor.
【図６】ハフ変換を説明するための図である。FIG. 6 is a diagram for explaining Hough transform.
【図７】障害物の測距データ点列にハフ変換を施すこと
により得られた（α，ρ）平面上の度数の極大点を示し
た図である。FIG. 7 is a diagram showing the maximum points of the frequency on the (α, ρ) plane obtained by performing Hough transform on the distance measurement data point sequence of the obstacle.
【図８】障害物の形状を表わす直線群およびデータ点列
Ｓ（ｉ）（ｘs （ｉ），ｙs （ｉ））から障害物の幅お
よび駐車空間の幅を推定する方法を説明した図である。FIG. 8 illustrates a method of estimating the width of an obstacle and the width of a parking space from a group of straight lines representing the shape of an obstacle and a sequence of data points S (i) (x s (i), y s (i)). It is a figure.
１ 対物距離検出手段 ２ 自車移動量検出手段 ３ 演算手段 １１ 超音波センサ送・受波子 １２ 超音波センサ受波子 １３ 超音波センサコントロールユニット １４ 右車輪速センサ １５ 左車輪速センサ １６ 演算装置 1 Objective distance detection means 2 Vehicle movement amount detection means 3 computing means 11 Ultrasonic sensor transmitter / receiver 12 Ultrasonic sensor receiver 13 Ultrasonic sensor control unit 14 Right wheel speed sensor 15 Left wheel speed sensor 16 arithmetic unit
Claims (3)
角を検出する対物距離検出手段と、自車両の移動距離お
よびヨー角の変化を検出する自車移動量検出手段と、前
記対物距離検出手段で得られた自車両から障害物までの
距離および方向角と前記自車移動量検出手段で得られた
地面に固定した基準座標系での自車両の移動量に基づい
て、障害物の一点の地面に固定した基準座標系での位置
データを演算して求める演算手段と、障害物の形状を直
線近似で推定して複数の近似直線を得るとともに、前記
複数の近似直線のうちの一つの近似直線である近似直線
１を構成する障害物の複数個の位置データを前記近似直
線１の方向を示す単位ベクトル上に正射影した長さを求
め、それらの長さの最大値を計算する一方、前記近似直
線１を構成する障害物に隣接する障害物の形状を表す近
似直線２を構成する複数個の位置データを前記近似直線
２の方向を示す単位ベクトル上に正射影した長さを求
め、それらの長さの最小値を計算し、この最小値から前
記最大値を減じたものを駐車スペースの幅とする演算を
行う手段と、を備えることを特徴とする駐車空間検出装
置。1. An objective distance detecting means for detecting a distance and a direction angle from the own vehicle to an obstacle, an own vehicle moving amount detecting means for detecting a change of a moving distance and a yaw angle of the own vehicle, and the objective distance detection. The distance and direction angle from the own vehicle to the obstacle obtained by the means and the movement amount detection means by the own vehicle
Based on the amount of movement of the host vehicle in the reference coordinate system fixed on the ground, the calculation means for calculating the position data of one point of the obstacle in the reference coordinate system fixed on the ground, and the shape of the obstacle are directly calculated.
While estimating by line approximation to obtain a plurality of approximate straight lines,
An approximate straight line that is one of a plurality of approximate straight lines
The position data of a plurality of obstacles that make up
Find the length of the orthographic projection on the unit vector indicating the direction of line 1.
Therefore, while calculating the maximum value of those lengths,
The neighborhood that represents the shape of the obstacle that is adjacent to the obstacle that constitutes line 1.
A plurality of position data forming the similar straight line 2 is converted into the approximate straight line.
Find the length that is orthographically projected on the unit vector indicating the direction of 2.
Therefore, calculate the minimum of their lengths and start from this minimum
Calculate the value obtained by subtracting the maximum value as the width of the parking space.
And a means for performing the parking space detection device.
て、前記近似直線１を構成する障害物の複数個の位置デ
ータを前記近似直線１の方向を示す単位ベクトル上へ正
射影した長さを求め、それらの長さの最大値から最小値
を減じたものを障害物の幅とすることを特徴とする駐車
空間検出装置。2. The parking space detection device according to claim 1, wherein a plurality of position data of obstacles forming the approximate straight line 1 are orthographically projected onto a unit vector indicating a direction of the approximate straight line 1. A parking space detection device, wherein the width of the obstacle is obtained by subtracting the minimum value from the maximum value of those lengths.
置において、前記障害物の形状を推定する手段にハフ
（Ｈｏｕｇｈ）変換による直線検出の手法を用いること
を特徴とする駐車空間検出装置。 3. A parking space detecting device according to claim 1 or 2.
Huff is used as a means for estimating the shape of the obstacle.
Use the method of straight line detection by (Hough) transformation
Parking space detection device characterized by:
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP05831098A JP3473378B2 (en) | 1998-03-10 | 1998-03-10 | Parking space detection device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP05831098A JP3473378B2 (en) | 1998-03-10 | 1998-03-10 | Parking space detection device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| JPH11255052A JPH11255052A (en) | 1999-09-21 |
| JP3473378B2 true JP3473378B2 (en) | 2003-12-02 |
Family
ID=13080680
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| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP05831098A Expired - Fee Related JP3473378B2 (en) | 1998-03-10 | 1998-03-10 | Parking space detection device |
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| Country | Link |
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| JP (1) | JP3473378B2 (en) |
Families Citing this family (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2002240661A (en) * | 2001-02-19 | 2002-08-28 | Nissan Motor Co Ltd | Parking support device |
| JP4686934B2 (en) * | 2001-08-14 | 2011-05-25 | 日産自動車株式会社 | Vehicle parking device |
| JP3991731B2 (en) * | 2002-03-14 | 2007-10-17 | 日産自動車株式会社 | Parking direction setting device for vehicles |
| JP4016980B2 (en) * | 2004-10-25 | 2007-12-05 | 株式会社豊田自動織機 | Space-saving parking assistance device |
| JP4179285B2 (en) * | 2005-01-12 | 2008-11-12 | トヨタ自動車株式会社 | Parking assistance device |
| JP2006343309A (en) * | 2005-05-09 | 2006-12-21 | Nippon Soken Inc | Obstacle detector |
| JP2010217193A (en) * | 2005-05-09 | 2010-09-30 | Nippon Soken Inc | Obstacle detection device |
| DE102005045260A1 (en) * | 2005-09-22 | 2007-03-29 | Valeo Schalter Und Sensoren Gmbh | Method for measuring parking spaces |
| JP4645542B2 (en) * | 2006-07-11 | 2011-03-09 | トヨタ自動車株式会社 | Parking space detection device |
| JP5257138B2 (en) * | 2009-02-26 | 2013-08-07 | 日産自動車株式会社 | Parking assistance device and parking assistance method |
| DE102009040375A1 (en) * | 2009-09-07 | 2011-04-07 | Valeo Schalter Und Sensoren Gmbh | Method and device for supporting a parking process of a vehicle |
| KR20130128894A (en) * | 2012-05-18 | 2013-11-27 | 현대모비스 주식회사 | System for controlling parking and method thereof |
| KR20130136078A (en) * | 2012-06-04 | 2013-12-12 | 현대모비스 주식회사 | Appartus and method for controlling aotomatic parking |
| WO2019215788A1 (en) * | 2018-05-07 | 2019-11-14 | 三菱電機株式会社 | Parking support device |
| JP6800395B2 (en) * | 2018-11-28 | 2020-12-16 | 三菱電機株式会社 | Driving support device |
| CN110853399A (en) * | 2019-10-12 | 2020-02-28 | 惠州市德赛西威智能交通技术研究院有限公司 | Parking space identification compensation method based on ultrasonic sensor parking space detection system |
| CN111310663A (en) * | 2020-02-17 | 2020-06-19 | 北京三快在线科技有限公司 | Road fence detection method, device, equipment and storage medium |
| JP2023032737A (en) * | 2021-08-27 | 2023-03-09 | 株式会社デンソー | Object detection device and object detection program |
| CN114572223A (en) * | 2022-02-25 | 2022-06-03 | 智己汽车科技有限公司 | Ultrasonic radar obstacle parking space sensing system and method |
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| JPH06187597A (en) * | 1992-12-16 | 1994-07-08 | Toyota Motor Corp | Parking assistance device |
| JP2799375B2 (en) * | 1993-09-30 | 1998-09-17 | 本田技研工業株式会社 | Anti-collision device |
| JP3961584B2 (en) * | 1996-02-08 | 2007-08-22 | 株式会社デンソー | Lane marking detector |
| JP3600378B2 (en) * | 1996-07-24 | 2004-12-15 | 本田技研工業株式会社 | Vehicle external recognition device |
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