JP2009116790A - Vehicular driving support apparatus and driving support method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a driving support apparatus that performs appropriate driving support even in a scene where the motion of target moving obstacles is predicted to change under the effect of other obstacles. <P>SOLUTION: The vehicular driving support apparatus includes a vehicle state detection means 11 for detecting running states of an associated vehicle, an obstacle detection means 12 for detecting obstacles existing around the vehicle, a moving obstacle identification means 13 for identifying the detected obstacles as moving obstacles and stationary obstacles, a course calculation means 20 for calculating a course in which the vehicle will not contact any of the detected moving and stationary obstacles, and a driving support means for providing driving support according to the calculated course. The course calculation means 20 first calculates courses of the moving obstacles and then calculates the course of the vehicle according to the calculated courses of the moving obstacles. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to a driving support device for a vehicle.

  Conventionally, the relative path of a moving obstacle is estimated by a regression curve based on the detection history of the distance between the moving obstacle and the vehicle detected by the sensor, the relative speed, etc., and the possibility of collision is determined based on the estimated path. The technique is disclosed in Patent Document 1. In the technique disclosed in Patent Document 1, when the collision possibility determination is performed based on the estimated course, the least square method is applied after increasing the weighting coefficient for the detection data with high accuracy when calculating the regression curve. It is a feature.

JP 2006-168628 A

  However, in the technique described in Patent Document 1, since the path is estimated by applying the past detection history to the regression curve, the movement state of the target moving obstacle is influenced by another obstacle. In situations where changes are expected, there was a problem that appropriate driving assistance could not be performed.

  A problem to be solved by the present invention is a driving support device that enables appropriate driving support even in a situation where the motion state of a target moving obstacle is expected to change due to another obstacle. Is to provide.

  The present invention is characterized in that, after calculating the travel path of a moving obstacle detected around the host vehicle, the travel path of the host vehicle is calculated based on the calculated travel path of the moving obstacle.

  According to the present invention, even when a moving obstacle is expected to change its motion state due to interference with other moving obstacles other than the moving obstacle and stationary obstacles, appropriate driving assistance is performed. be able to.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings.

<< First Embodiment >>
FIG. 1 is a plan view schematically showing the vehicle 1 according to the first embodiment, and FIG. 2 is a functional block diagram of a driving support apparatus installed in the vehicle 1 according to the first embodiment.

  As shown in FIG. 1, a vehicle 1 includes, in the vehicle 1, devices constituting the driving support device of the present embodiment, that is, a camera 2, a vehicle speed sensor 3, a turning angle sensor 4, an acceleration sensor 5, and a yaw rate sensor. 6, a microprocessor 7, and a speaker 8 are provided.

  The camera 2 is disposed in the vehicle interior of the vehicle 1 and can image the front of the vehicle 1, thereby photographing the road situation in front of the vehicle and displaying obstacles, road boundaries, white lines, and the like. To detect. In this embodiment, two cameras 2 are provided as a pair on the left and right sides, and an image is generated from an image signal from the camera 2 by a sensor information processing unit 10 of a microprocessor 7 to be described later. This information is processed in three dimensions, and for example, the distance between the vehicle 1 and the obstacle can be detected.

  In this embodiment, the vehicle speed sensor 3 is composed of a rotary encoder attached to the wheel of the vehicle 1 and measures the vehicle speed by detecting a pulse signal generated in proportion to the rotation of the wheel.

  The yaw rate sensor 4 is provided at the center of the vehicle 1 and detects a yaw rate generated in the vehicle 1 using a known device using a crystal resonator or a semiconductor.

  The acceleration sensor 5 detects acceleration in a specific direction generated in the vehicle 1 using a known device configured using a piezoelectric element or the like. In this embodiment, the structure which detects the acceleration which generate | occur | produces especially in the horizontal direction of the vehicle 1 is assumed. The acceleration sensor 5 is provided at an appropriate location of the vehicle 1.

  The turning angle sensor 6 measures the actual turning angle value by detecting the rack stroke amount of the steering device of the vehicle 1.

  The microprocessor 7 is an integrated circuit including an A / D conversion circuit, a D / A conversion circuit, a central processing unit, a memory, and the like. The microprocessor 7 processes signals detected by various sensors (camera 2, vehicle speed sensor 3, yaw rate sensor 4, acceleration sensor 5, turning angle sensor 6) according to the program stored in the memory, and the traveling path of the own vehicle. The calculation is performed, and it is determined whether or not a warning is presented to the driver, and the result is output to the speaker 8.

  The speaker 8 amplifies the signal sent from the microprocessor 7 with an amplifier and produces sound, thereby giving a warning or information to the driver.

  FIG. 2 is a functional block diagram showing each device constituting the driving support device installed in the vehicle 1 according to its function. As shown in FIG. 2, the signals detected by the sensors installed in the vehicle 1, specifically, the camera 2, the vehicle speed sensor 3, the yaw rate sensor 4, the acceleration sensor 5, and the turning angle sensor 6, The sensor information processing unit 10 of the microprocessor 7 is taken in.

  Here, as shown in FIG. 2, the microprocessor 7 includes a sensor information processing unit 10, a travel route calculation unit 20, and a warning necessity determination unit 30. The sensor information processing unit 10 takes in sensor signals from the respective sensors and processes them in an integrated manner, thereby reconstructing the information on the motion state of the host vehicle, the arrangement / motion state of surrounding obstacles, and road boundaries. I do. The travel route calculation unit 20 calculates the travel route of the host vehicle and the moving obstacle based on the information captured and processed by the sensor information processing unit 10. The warning necessity determination unit 30 determines the necessity of warning to the driver from the calculation result of the travel route obtained by the travel route calculation unit 20. As a result of the determination by the warning necessity determination unit 30, when it is determined that a warning is necessary, a warning is presented to the driver through the speaker 8 connected to the microprocessor 7.

  In the first embodiment, the vehicle state detector 11 is the vehicle state detector of the present invention, the obstacle detector 12 is the obstacle detector of the present invention, and the moving obstacle identification unit 13 is of the present invention. The travel path calculation unit 20 corresponds to the obstacle detection means, and corresponds to the travel path calculation means.

  Next, the first embodiment of the present invention will be specifically described assuming the scene example shown in FIG. FIG. 3 is a plan view schematically showing an example of a scene to which the first embodiment is applied. In FIG. 3, when the own vehicle H is traveling on a straight road 600 partitioned on both sides by a fence 700. Furthermore, the oncoming vehicle C is approaching from the front, and there is a stop vehicle P between the host vehicle H and the oncoming vehicle C at the right end of the road (the side on which the oncoming vehicle C is traveling). Shows the situation. Note that the road 600 on which the host vehicle H and the oncoming vehicle C are traveling is partitioned on both sides by fences 700, and it is physically impossible to deviate from the road 600.

  As described above, the sensor information processing unit 10 of the microprocessor 7 performs processing to reconfigure the information into the motion state of the own vehicle, the arrangement / motion state of surrounding obstacles, and the road boundary. A detection unit 11, an obstacle detection unit 12, a moving obstacle identification unit 13, and a road boundary information processing unit 14 are provided.

  The own vehicle state detection unit 11 detects the movement state of the own vehicle H based on signals from the camera 2, the vehicle speed sensor 3, the turning angle sensor 4, the acceleration sensor 5, and the yaw rate sensor 6. Specifically, based on these signals, the position of the vehicle H with respect to the road H, the information on the yaw angle θ of the vehicle H, the information on the yaw rate γ generated in the vehicle H, and the information on the slip angle β generated in the vehicle H. , And information on the traveling speed v of the host vehicle H is detected. Here, the yaw angle θ refers to an angle formed by the direction in which the vehicle H travels with respect to the direction of the road 600, that is, the direction in which the running shape of the road 600 extends. In addition, the slip angle β is an angle formed by the direction in which the vehicle H actually travels with respect to the travel direction of the vehicle H predicted based on actual steering.

  The position of the host vehicle H can be detected by subjecting the image signals output from the pair of cameras 2 to image processing by the host vehicle state detection unit 11.

  Further, if it is assumed that the road 600 is a straight line, the yaw angle θ is an angle formed by the boundary between the road 600 and the fence 700 detected by the road boundary information processing unit 14 and the direction in which the vehicle H is facing. The image signal output from the camera 2 can be estimated by performing image processing. Alternatively, it may be calculated by determining an appropriate initial value and integrating the output value from the yaw rate sensor 6. The initial value in this case may be the traveling direction of the vehicle H traveling in the direction of the road 600, for example.

  The yaw rate γ and the traveling speed v can be detected from signals output from the yaw rate sensor 6 and the vehicle speed sensor 3.

The slip angle beta, the longitudinal speed of the vehicle H v _x, when the width direction of the velocity of the vehicle H was v _y, can be determined by the following formula (1).

In this case, for example, in the vehicle H, it is considered that the speed component in the width direction is sufficiently smaller than the speed component in the front-rear direction, and v _x is set as the traveling speed v detected by the vehicle speed sensor 3. Further, v _y can be obtained by integrating the output of the acceleration sensor 5. Then, using these results, an approximate value of the slip angle β can be obtained from the above equation (1). In addition to this method, a known technique for estimating the slip angle more accurately by an observer from signals such as the wheel speed from the vehicle speed sensor 3, the yaw rate from the yaw rate sensor 6, and the lateral acceleration from the acceleration sensor 5 is also known. Therefore, the slip angle β may be obtained using such a method.

  The obstacle detection unit 12 receives the image signals input from the pair of cameras 2, performs image processing, determines whether an obstacle that can hinder the traveling of the vehicle is detected, and detects the obstacle. If so, the detected obstacle information is processed. For example, in the scene example shown in FIG. 3, an oncoming vehicle C and a stopped vehicle P are detected as obstacles.

And when an obstacle is detected, based on the information on the own vehicle H and the information on the obstacle detected by the own vehicle state detection unit 11, the information on the own vehicle H and the obstacle are displayed on the ground coordinate system. expand. The ground coordinate system may be arbitrarily set. For example, in the scene example shown in FIG. 3, as shown in FIG. 4, the X axis along the direction of the road 600 is perpendicular to the X axis, that is, the road 600. The Y axis can be set in the width direction. FIG. 4 is a diagram showing a method for setting the ground coordinate system in the scene example shown in FIG. In addition, although the coordinate origin in the ground coordinate system can also be arbitrarily set and is not particularly limited, as shown in FIG. 4, in the present embodiment, the current position of the vehicle H is the origin of the X coordinate (X = 0). The middle point of the left and right road boundaries formed by the road 600 and the fence 700 can be set as the origin of the Y coordinate (Y = 0). Further, as shown in FIG. 4, the position of the road boundary between the road 600 and the fence 700 is y = ± y _B, and the positions of the host vehicle H, the oncoming vehicle C as an obstacle, and the stop vehicle P are respectively The own vehicle H is (X, Y) = (x _H , y _H ), the oncoming vehicle C is (X, Y) = (x _C , y _C ), and the stopped vehicle is (X, Y) = (x _P , y _P ). The position of the road boundary is detected by a road boundary information processing unit 14 described later. In addition, since many methods are disclosed as a well-known technique about the obstacle detection method by image processing, the detailed description is abbreviate | omitted here.

  The moving obstacle identification unit 13 takes in information on the obstacle detected by the obstacle detection unit 12 and is an obstacle moving on the ground coordinate system among the obstacles detected by the obstacle detection unit 12. A moving obstacle is distinguished from a stationary obstacle that is an obstacle that has not moved substantially. Specifically, the determination that the obstacle is a moving obstacle or a stationary obstacle is performed as follows. That is, first, the movement speed of the detected obstacle is estimated from the obstacle detection history detected by the obstacle detection unit 12. When the estimated moving speed exceeds a predetermined threshold value, specifically, when the estimated moving speed exceeds a minute apparent speed level that can occur due to a detection error, the obstacle is in the ground coordinate system. It is determined that the vehicle is moving above and is determined to be a moving obstacle. On the other hand, an obstacle that has not been determined to be a moving obstacle is determined to be a stationary obstacle. For example, in the scene example shown in FIG. 3, since it is clearly detected that the oncoming vehicle C is approaching the host vehicle H, it is determined that the oncoming vehicle C is a moving obstacle. On the other hand, since the position of the stopped vehicle P does not change, it is determined that it is not a moving obstacle but a stationary obstacle.

And about the obstacle determined as the moving obstacle by the moving obstacle identification part 13, the moving speed is converted into a ground speed, and is recorded. In this embodiment, denoted the ground speed of the oncoming vehicle C in the example scene shown in Figure 3 and V _x ^C. Note that the position information of the stationary obstacle is recorded as it is.

The road boundary information processing unit 14 detects the position of the road boundary between the road 600 and the fence 700 by performing image processing on the signals detected by the pair of cameras 2. Incidentally, the obstacle detection unit 12, when the obstacle is detected, on the ground coordinate system shown in FIG. 4, and thus is expressed as y = ± y _B. Moreover, since many methods are disclosed as a publicly known technique for detecting a road boundary by image processing, detailed description thereof is omitted here.

  Further, the travel route calculation unit 20 of the microprocessor 7 calculates the travel route of the host vehicle H and the moving obstacle based on the information captured and processed by the sensor information processing unit 10. A route calculating unit 21 and a host vehicle traveling route calculating unit 22 are provided.

  The moving obstacle travel path calculating unit 21 calculates the travel path of the moving obstacle determined by the moving obstacle identifying unit 13. For example, in the example of the scene shown in FIG. 3, the oncoming vehicle C corresponds to a moving obstacle and is a target for calculating the travel route, and the travel route is calculated as follows.

  First, a model that expresses the motion dynamics of the oncoming vehicle C that is a moving obstacle is assigned. Here, although the oncoming vehicle C is a vehicle, for the sake of simplicity, the dynamics is expressed by a mass point model such as the following equation (2).

Here, v _x ^C and v _y ^C are the speed in the front-rear direction and the speed in the width direction of the oncoming vehicle C, respectively, and the signal detected by the camera 2 is imaged by the moving obstacle identification unit 13. It can obtain | require by utilizing the result. Further, a _x ^C and a _y ^C are vertical and lateral accelerations acting on the oncoming vehicle C as the oncoming vehicle C is steered and accelerated / decelerated, respectively. It is assumed that the restrictions shown in the following formula (3) are imposed on a _x ^C and a _y ^C.

ただし、ａ_ｘ ^ｍａｘ、ａ_ｙ ^ｍａｘは、それぞれ前後方向および幅方向の加速度の最大値を表し、通常の運転で発揮される加速度の水準を考慮して適当な値が設定される。

However, a _x ^max and a _y ^max represent the maximum values of acceleration in the front-rear direction and the width direction, respectively, and appropriate values are set in consideration of the level of acceleration exhibited in normal driving.

Then, a x ^_C, obtaining the time-series signal a _y ^C, it is possible to obtain a traveling path of the oncoming vehicle C by integrating the above formula (2). In the present embodiment, an evaluation function for evaluating the traveling route of the oncoming vehicle C is introduced in order to obtain time series signals expected as a _x ^C and a _y ^C as the traveling state of the oncoming vehicle C. . Specifically, an evaluation function generally represented by the following formula (4) is assumed.

上記式（４）を対向車Ｃに適用する場合において、ｕ（ｔ）、ｕ（τ）は、ｕ_ｃ＝（ａ_ｘ ^Ｃ，ａ_ｙ ^Ｃ）^Ｔであり、ｘ（τ）は、ｘ_ｃ＝（ｘ_ｃ，ｖ_ｘ ^Ｃ，ｙ_ｃ，ｖ_ｙ ^Ｃ）であり、ｔ_０は現在時間、Ｔは進行経路算出時間長、τは進行経路算出時間内における時間を表す積分変数、Ｌは進行経路算出の基準となる評価式である。

In the case where the above equation (4) is applied to the oncoming vehicle C, u (t) and u (τ) are u _c = (a _x ^C , a _y ^C ) ^T , and x (τ) is x _c = (X _c , v _x ^C , y _c , v _y ^C ), t ₀ is the current time, T is the travel path calculation time length, τ is an integral variable representing the time within the travel path calculation time, and L is the progress It is an evaluation formula used as a reference for route calculation.

And in this embodiment, the evaluation formula L is comprised from the evaluation term reflecting the basic request | requirement with respect to the following three exercise | movement actions. That is,
Request item 1: Reduce acceleration acting on the vehicle body as much as possible.

Request item 2: Do not get too close to the road boundary.

Request item 3: Keep away from other stationary obstacles and other moving objects.

  Of the above, the request item 1 indicates the acceleration acting on the oncoming vehicle C. For example, the evaluation term shown in the following formula (5) can be used.

上記式（５）において、ｗ_ｘ、ｗ_ｙは、それぞれ前後方向の加速度ａ_ｘ ^Ｃおよび幅方向の加速度ａ_ｙ ^Ｃに対する評価重みを表すパラメータである。

In the above equation (5), w _x and w _y are parameters representing evaluation weights for the acceleration a _x ^{C in the} front-rear direction and the acceleration a _y ^{C in the} width direction, respectively.

  Request item 2 indicates the approaching state of the oncoming vehicle C to the road boundary that is the boundary between the road 600 and the fence 700, and a function that increases in value as the distance between the oncoming vehicle C and the road boundary decreases, for example, The function shown in the following formula (6) can be used. Information detected by the road boundary information processing unit 14 of the sensor information processing unit 10 can be used as the road boundary information.

上記式（６）において、Δは道路境界への接近の余裕幅を指定するパラメータであり、Δの値が大きいほど、対向車Ｃと道路境界との接近距離の余裕を大きくとる進行経路が算出されることとなる。

In the above equation (6), Δ is a parameter for designating the margin of approach to the road boundary, and the larger the value of Δ, the greater the travel route that takes the margin of the approach distance between the oncoming vehicle C and the road boundary is calculated. Will be.

  Request item 3 indicates the proximity state between the oncoming vehicle C and other obstacles and other moving objects, and a function whose value increases as the distance from the other obstacles and other moving objects decreases. For example, a function represented by the following formula (7) can be used.

上記式（７）において、ｉは進行経路算出対象となる移動障害物である対向車Ｃ以外の他の障害物および他の移動体を識別するインデックスであり、図３に示す場面例においては、自車Ｈと停止車両Ｐとが評価対象となるため、ｉ＝｛Ｈ，Ｐ｝となる。σ_ｘｉ、σ_ｙｉは、それぞれ、他の障害物および他の移動体（図３に示す場面例においては、自車Ｈ、停止車両Ｐ）のＸ軸方向の幅に応じた値、Ｙ軸方向の幅に応じた値が設定される。ただし、奥行き方向であるＸ軸方向の情報が得られない場合には、σ_ｘｉ＝σ_ｙｉと設定する。また、ｗ_ｉは、他の障害物および他の移動体（図３に示す場面例においては、自車Ｈ、停止車両Ｐ）に対する評価重みである。

In the above formula (7), i is an index for identifying obstacles other than the oncoming vehicle C that is a moving obstacle to be traveled route calculation target and other moving objects. In the example of the scene shown in FIG. Since the own vehicle H and the stopped vehicle P are to be evaluated, i = {H, P}. σ _xi and σ _yi are values according to the widths in the X-axis direction of other obstacles and other moving bodies (in the example of the scene shown in FIG. 3, the own vehicle H and the stopped vehicle P), respectively. A value corresponding to the width of is set. However, when information in the X-axis direction that is the depth direction cannot be obtained, σ _xi = σ _yi is set. Moreover, w _i is an evaluation weight for other obstacles and other moving bodies (in the example of the scene shown in FIG. 3, the own vehicle H and the stopped vehicle P).

  And the evaluation formula L is calculated | required by following formula (8) using the above three evaluation formulas (Formula (5)-Formula (7)).

上記式（８）における、Ｌ_Ｒ、Ｌ_Ｏは、対地座標系に展開された道路６００上に、自車Ｈ、停止車両Ｐ、および道路境界の位置への到達リスクを反映したリスクポテンシャルを定義することとなる。これら評価項Ｌ_Ｒ、Ｌ_Ｏを足し合わせて得られる関数（Ｌ_Ｒ＋Ｌ_Ｏ）に、道路境界の情報を加えた関数をＸ−Ｙ座標上にプロットしたグラフを図５に示す。なお、図５は図３に示す場面例におけるポテンシャルフィールド表現を、対向車Ｃ側から対向車Ｃの進行方向を見た場合におけるグラフである。図５においては、道路６００における通行が望ましいほど値が低いポテンシャルフィールドとして、視覚的に表現可能となる。そして、対向車Ｃの進行経路は、ポテンシャルフィールドの値が低い領域を可能な限り通過するように形成されることになるので、図５より、対向車Ｃは、最初に右方向に移動して停止車両Ｐを避けた後で、自車Ｈを避けるために左方向に移動するような経路が得られることが予想される。

In the above equation (8), L _R and L _O define a risk potential reflecting the arrival risk to the position of the own vehicle H, the stopped vehicle P, and the road boundary on the road 600 developed in the ground coordinate system. Will be. FIG. 5 shows a graph in which a function obtained by adding road boundary information to the function (L _R + L _O ) obtained by adding these evaluation terms L _R and L _O is plotted on the XY coordinates. FIG. 5 is a graph showing the potential field expression in the scene example shown in FIG. 3 when the traveling direction of the oncoming vehicle C is viewed from the oncoming vehicle C side. In FIG. 5, it can be visually expressed as a potential field whose value is so low that traffic on the road 600 is desirable. The traveling path of the oncoming vehicle C is formed so as to pass as much as possible through the region where the value of the potential field is low. From FIG. 5, the oncoming vehicle C first moves rightward. It is expected that after avoiding the stop vehicle P, a route that moves to the left in order to avoid the host vehicle H is obtained.

When calculating the travel route of the oncoming vehicle C, a _x ^C and the value that minimizes the value of the equation (4) under the constraints of the equations (2) and (3). The traveling route of the oncoming vehicle C is calculated by regarding the optimum control problem for obtaining a _y ^C. Since several known techniques for solving the optimal control problem is known, by using any of them, a _{x C} where the value of the evaluation function is minimized in the above formula ^(4), a _y A combination of ^C time series signals {a _x ^C (t), a _y ^C (t) | t ₀ ≦ t ≦ t ₀ + T} can be obtained. Here, {a _x ^C (t), a _y ^C (t) | t ₀ ≦ t ≦ t ₀ + T} is a signal of each of a _x ^C and a _y ^C at time t _{0 to} t ₀ + T. It is a combination. The time series signal ^{_{{a x C (t),}} a y C (t) | t 0 ≦ t ≦ t 0 + T} by integrating the above formula (2), opposite at time _t 0 _~t 0 + _T The time series signal {x _c (t), y _c (t) | t ₀ ≦ t ≦ t ₀ + T} of the position of the vehicle C on the ground coordinate system, that is, the traveling path can be converted. As a result, a travel route as shown in FIG. 6 can be obtained as the travel route of the oncoming vehicle C. FIG. 6 is a diagram showing an example of calculating the traveling route of the oncoming vehicle C in the example of the scene shown in FIG.

  The own vehicle travel route calculation unit 22 calculates the travel route of the own vehicle H based on the travel route calculated by the travel obstacle travel route calculation unit 21 (the route shown in FIG. 6).

  First, a model expressing the motion dynamics of the own vehicle H is assigned. Here, with respect to the oncoming vehicle C as a moving obstacle, the dynamics is expressed by a mass point model, but the motion dynamics of the host vehicle H in the host vehicle travel route calculation unit 22 is for calculating a more accurate travel route. The two-wheel model represented by the vehicle model, specifically, the following formulas (9) to (16) can be used.

上記式において、前述したようにθは自車Ｈのヨー角（姿勢角）であり、βは滑り角、ｖ_Ｈは走行速度、γはヨーレートである。また、ｍは自車Ｈの重量、Ｉは自車Ｈに生じる車両ヨー慣性モーメント、ｌ_ｆは車両重心から前輪軸までの距離、ｌ_ｒは車両重心から後輪軸までの距離、ωは転舵および加減速指令値δ^＊、ａ^＊に対するアクチュエータ（転舵および加減速）の追従時定数（の逆数）を表す。また、Ｙ_ｆは前輪のタイヤ横力を表し、かつＹ_ｒは後輪のタイヤ横力を表す関数であり、それぞれ前輪すべり角β_ｆ、後輪すべり角β_ｒの関数であると仮定している。なお、β_ｆ、β_ｒは、下記式（１７）、（１８）で表すことができる。

In the above formula, as described above, θ is the yaw angle (posture angle) of the vehicle H, β is the slip angle, v _H is the traveling speed, and γ is the yaw rate. M is the weight of the vehicle H, I is the vehicle yaw moment of inertia generated in the vehicle H, l _f is the distance from the vehicle center of gravity to the front wheel axis, l _r is the distance from the vehicle center of gravity to the rear wheel axis, and ω is the steering And the following time constant (reciprocal number) of the actuator (steering and acceleration / deceleration) with respect to the acceleration / deceleration command values δ ^* and a ^* . Further, the Y _f represents the tire lateral force of the front wheel, and Y _r is a function representing a tire lateral force of the rear wheel, the front wheel slip angle beta _{f respectively,} assuming a function of the rear wheel slip angle beta _r Yes. Β _f and β _r can be represented by the following formulas (17) and (18).

そして、このようなタイヤ横力の関数は、一般に図７に示すような形状となることが知られており、たとえば、具体的な関数の表現形態としてマジックフォーミュラ等のタイヤモデルが知られており、本実施形態では、それらの関数を使用することができる。なお、図７はタイヤ横力関数の一例を示すグラフである。

Such a tire lateral force function is generally known to have a shape as shown in FIG. 7. For example, a tire model such as a magic formula is known as a specific function expression form. In the present embodiment, these functions can be used. FIG. 7 is a graph showing an example of the tire lateral force function.

  When the above-described two-wheel model is used as a model that expresses the motion dynamics of the host vehicle H, the state vector representing the motion state of the host vehicle H is an eight-dimensional vector as shown in the following equation (19).

上記式（９）〜（１６）で表現されるモデルは、転舵指令値δ^＊、および加減速指令値δ^＊、ａ^＊を入力とする非線形微分方程式となる。上記の状態ベクトルＸ_Ｈの値を得るために用いられる自車Ｈの位置ｘ_Ｈ、ｙ_Ｈ、ヨー角θ、速度ｖ_Ｈ、すべり角β、ヨーレートγは、各センサの信号に基づき、センサ情報処理部１０の自車状態検出部により検出された情報を利用すればよい。

The model expressed by the above formulas (9) to (16) is a nonlinear differential equation having the steering command value δ ^* and the acceleration / deceleration command values δ ^* and a ^* as inputs. The position x _H , y _H , yaw angle θ, velocity v _H , slip angle β, and yaw rate γ of the host vehicle H used to obtain the value of the state vector X _H are based on sensor information. Information detected by the vehicle state detection unit of the processing unit 10 may be used.

Next, the traveling path of the host vehicle H can be calculated by obtaining time series signals of δ ^* and a ^* and integrating them. At this time, the own vehicle travel route calculation unit 22 can use the evaluation function represented by the above-described equation (4), similarly to the above-described moving obstacle travel route calculation unit 21. However, when calculating the travel route of the host vehicle H in the host vehicle travel route calculation unit 22, a model different from the case of the moving obstacle travel route calculation unit 21 is adopted as a model expressing motion dynamics. Therefore, the evaluation term L _U is different. Specifically, the evaluation term L _u is configured as shown in the following formula (20). In the following formula (20), w _d and w _a are parameters representing evaluation weights.

また、評価項Ｌ_Ｒは、移動障害物進行経路算出部２１の場合と同様に、下記式（２１）を用い、Ｌ_Ｒ（ｘ_Ｈ，ｙ_Ｈ）を評価項とする。

In addition, as in the case of the moving obstacle travel route calculation unit 21, the evaluation term L _R uses the following formula (21) and uses L _R (x _H , y _H ) as an evaluation term.

さらに、評価項Ｌ_Ｏについても、移動障害物進行経路算出部２１の場合と同様に、下記式（２２）を用い、Ｌ_Ｏ（ｘ_Ｈ，ｙ_Ｈ）を評価項とする。

Further, for the evaluation term L _O as well, the following equation (22) is used, and L _O (x _H , y _H ) is used as the evaluation term, as in the case of the moving obstacle travel route calculation unit 21.

ここで、上記式（２２）において、自車Ｈの進行経路を算出する際には、対向車Ｃと、停止車両Ｐとが評価対象となるため、これらを識別するインデックスであるｉを、ｉ＝｛Ｃ，Ｐ｝として、評価項Ｌ_Ｏを求める。ただし、自車Ｈの進行経路を算出する際において、対向車Ｃに係るｉ＝Ｃに対応する（ｘ_ｉ，ｙ_ｉ）については、移動障害物進行経路算出部２１により算出された移動障害物としての対向車Ｃの対地座標系上の位置の時系列信号｛ｘ_ｃ（ｔ），ｙ_ｃ（ｔ）｜ｔ_０≦ｔ≦ｔ_０＋Ｔ｝を利用して、移動障害物としての対向車Ｃの経路を参照した形で、評価項の計算を行う。一方、静止障害物である停止車両Ｐに係るｉ＝Ｐに対応する（ｘ_ｉ，ｙ_ｉ）については、障害物検出部１２で検出され、移動障害物識別部１３に記録された対地座標系上の位置の情報を用いる。

Here, in the above equation (22), when calculating the travel route of the host vehicle H, the oncoming vehicle C and the stop vehicle P are subject to evaluation. = {C, P}, an evaluation term L _O is obtained. However, when calculating the travel route of the host vehicle H, for the (x _i , y _i ) corresponding to i = C related to the oncoming vehicle C, the moving obstacle calculated by the moving obstacle travel route calculating unit 21 The oncoming vehicle as a moving obstacle using the time series signal {x _c (t), y _c (t) | t ₀ ≦ t ≦ t ₀ + T} of the position on the ground coordinate system of the oncoming vehicle C as The evaluation term is calculated with reference to the path of C. On the other hand, (x _i , y _i ) corresponding to i = P related to the stopped vehicle P that is a stationary obstacle is detected by the obstacle detection unit 12 and recorded in the moving obstacle identification unit 13. Use the location information above.

FIG. 8 shows a graph in which a function obtained by adding road boundary information to the function (L _R + L _O ) obtained by adding the evaluation terms L _R and L _O is plotted on the XY coordinates. 8 is a graph of the potential field expression in the example of the scene shown in FIG. 3 when the traveling direction of the host vehicle H is viewed from the host vehicle H side (a graph when viewed from the opposite side to FIG. 5). Here, when calculating the traveling route of the host vehicle H, the calculation result of the traveling route of the oncoming vehicle C as the moving obstacle by the moving obstacle traveling route calculation unit 21 is used. As shown, the potential field setting is such that the peak of the potential field corresponding to the oncoming vehicle C moves within the prediction interval.

When calculating the traveling route of the host vehicle H, optimal control for obtaining δ ^* and a ^* is performed in the same manner as the method of calculating the traveling route of the oncoming vehicle C as the moving obstacle in the moving obstacle traveling route calculation unit 21. Returning to the problem, the traveling route of the vehicle H is calculated. That is, a combination of time series signals {δ ^* (t), a ^* (t) | t ₀ δ ^* and a ^* that minimizes the value of the evaluation function of the above equation (4) using the solution of the optimal control problem. ≦ t ≦ t ₀ + T} is obtained. By integrating this time series signal of the position on the ground coordinate system of the vehicle H at time _{t 0 ~t 0 + T {x} H (t), y H (t) | t 0 ≦ t ≦ t ₀ + T}, that is, it can be converted into a traveling path.

  As a result, as the travel route of the host vehicle H, for example, a travel route as shown in FIG. 9 can be obtained. FIG. 9 is a diagram showing an example of a travel route calculation result of the own vehicle H in the scene example shown in FIG. Here, as the traveling path of the host vehicle H, it is predicted that the oncoming vehicle C moves in the lateral direction to avoid the parked vehicle P, and moves to the left end of the road 600 while decelerating. You will get a way to go. In FIG. 9, the traveling directions of the host vehicle H and the oncoming vehicle C are indicated by arrows, and the movement locus of the oncoming vehicle C is indicated by a dotted line.

The warning necessity determination unit 30 performs processing for determining the necessity of assistance to the driver based on the calculation result of the route of the host vehicle H by the host vehicle travel route calculation unit 22. In this embodiment, it is calculated at the same time as the state of the vehicle H detected by the vehicle state detection unit 11 and {x _C (t), y _C (t) | t ₀ ≦ t ≦ t ₀ + T}. Focusing on the turning angle and acceleration {δ (t), a _H ^x (t) | t ₀ ≦ t ≦ t ₀ + T}, the necessity of support is determined by whether these physical quantities exceed a predetermined threshold. judge. That is, when it is determined that a large change in the operation amount is expected to travel along the calculated traveling route, a warning is given to the driver by the speaker 8 connected to the microprocessor 7. It is configured to prompt and take necessary operations at an early stage. For example, when it is determined that a large change in the operation amount is expected, the vehicle, for example, travels so that all detected moving obstacles and stationary obstacles approach a predetermined level or more. For example, when a route is obtained. Further, as a warning method for the driver, there is a method of urging the driver to travel along the travel route of the host vehicle H calculated by the travel route calculation unit 20 using the speaker 8.

  10 and 11 show an example of the calculation result of the traveling route of the host vehicle H, and an example in the case where the necessity of warning by the warning necessity determination unit 30 is determined. 10 and 11, the horizontal axis represents time, and the vertical axis represents the amount and acceleration of the turning angle determined to be necessary at each time, based on the travel path calculation result at each time. It is. As is clear from FIGS. 10 and 11, in this case, the operation amount exceeding the set threshold value is calculated for both the turning angle and the acceleration, so that it is determined that a warning to the driver is necessary. become. In fact, as shown in FIG. 9, in this example of the scene, it is expected that the oncoming vehicle C will protrude in front of the own vehicle H in order to avoid the stop vehicle P, and correspondingly, deceleration and leftward movement are expected. Since this is a scene where steering is expected to be necessary, in such a situation, it is considered appropriate to give a warning to the driver.

  Next, the driving support process by the driving support apparatus according to the first embodiment will be described along the flowchart shown in FIG. FIG. 12 is a flowchart showing a process of driving support by the driving support apparatus according to the first embodiment. FIG. 3 shows that the oncoming vehicle C approaches from the front when the host vehicle H is traveling on a straight road 600 partitioned on both sides by a fence 700, and further, the host vehicle H and the oncoming vehicle C In the figure, a stopped vehicle P is present at the right end of the road (the side on which the oncoming vehicle C is traveling).

  First, in step S101, signals detected by the sensors (camera 2, vehicle speed sensor 3, turning angle sensor 4, acceleration sensor 5, yaw rate sensor 6) provided in the host vehicle H are stored in the memory of the microprocessor 7. The information on the road 600 and the information on the own vehicle H are acquired by reading the data into the sensor information processing unit 10. Information about the host vehicle H is processed by the host vehicle state detection unit 11 of the sensor information processing unit 10.

Next, in step S102, the image signal input from the pair of cameras 2 is input from the information acquired by the obstacle detection unit 12 into the sensor information processing unit 10, and image processing is performed. It is determined whether or not an obstacle that can hinder the traveling of the vehicle H is detected. If an obstacle is detected, the process proceeds to step S103 in order to provide driving assistance for avoiding the obstacle. On the other hand, if no obstacle is detected on the road 600, the process is terminated, and after a predetermined time has elapsed, the process is started again from step S101. At this time, the travel route calculation unit 20 sets the current time (t ₀ ) when the obstacle is detected as the travel route calculation start time t ₀ . In the scene example shown in FIG. 3, since the oncoming vehicle C and the parked vehicle P are detected as obstacles, the process proceeds to step S103.

  In step S103, based on the information on the own vehicle H detected by the own vehicle state detection unit 11 and the information on the oncoming vehicle C and the parked vehicle P as obstacles detected by the obstacle detection unit 12, FIG. As shown, these pieces of information are developed on the ground coordinate system.

  In step S104, the moving obstacle identifying unit 13 is substantially stationary with the moving obstacle that is moving on the ground coordinate system among the obstacles detected by the obstacle detecting unit 12. A moving obstacle is extracted based on the result. In the present embodiment, the process proceeds to step S105 regardless of whether or not a moving obstacle is extracted. In the scene example shown in FIG. 3, the oncoming vehicle C is extracted as a moving obstacle, while the parked vehicle P is determined to be a stationary obstacle.

  In step S105, among the moving obstacles extracted in step S104, the moving obstacle travel route calculation unit 21 selects a travel obstacle that has not yet been calculated as a travel route, and sets it as a travel route calculation target. Then, the process proceeds to step S106 in order to calculate the travel route. Here, when a plurality of moving obstacles are detected in step S104, an appropriate order may be given and the order selected. If no moving obstacle is extracted in step S104, the process proceeds to step S106 without selecting a moving obstacle for which the travel route is to be calculated. In the example of the scene shown in FIG. 3, since the moving obstacle extracted in step S104 is only the oncoming vehicle C, the oncoming vehicle C is selected as an object for calculating the travel route.

  In step S <b> 106, the travel path calculation unit 21 calculates the travel path for the travel obstacle that has not been calculated in the travel path selected in step S <b> 105. If no moving obstacle is extracted in step S104, the process proceeds to step S107 without calculating the travel route. In the example of the scene shown in FIG. 3, the travel route is calculated for the oncoming vehicle C selected in step S105. For example, the travel route as shown in FIG. 6 can be obtained. If two or more moving obstacles have been detected and the traveling path has already been calculated for other moving obstacles, the traveling path of the moving obstacle that is the target of the traveling path calculation In the calculation, the calculation result of the travel route already calculated for other moving obstacles is used. Thereby, the travel route of the moving obstacle can be calculated with higher accuracy. In addition, an increase in calculation amount can be suppressed.

  In step S107, with respect to all the moving obstacles extracted in step S104, in step S106, the moving obstacle progression route calculation unit 21 determines whether or not the calculation of the progression route has been completed. As a result, when the calculation of the travel route is completed for all the moving obstacles extracted in step S104, the information detected by each sensor and the calculation result of the travel route of the moving obstacle are displayed. Based on this, the process proceeds to step S108 to calculate the vehicle route. On the other hand, when there are a plurality of moving obstacles extracted in step S104 and there are still moving obstacles for which the traveling route has not been calculated yet, in order to calculate the traveling route of such a moving obstacle. Returning to step S105. If no moving obstacle is extracted in step S104, it is considered that the calculation of the travel route has been completed for all the moving obstacles, and the process proceeds to step S108. In the example of the scene shown in FIG. 3, since the moving obstacle is only the oncoming vehicle C, the process proceeds to step S108.

  In step S <b> 108, the travel route of the host vehicle H is calculated by the host vehicle route calculation unit 22 based on the information obtained in the above steps. Specifically, in step S108, the information of the own vehicle H acquired and processed by the own vehicle state detection unit 11 of the sensor information processing unit 10 in step S101, detected in step S102, and in step S104, a stationary fault is detected. Based on the information of the obstacle determined to be an object, and the information of the calculated route of the moving obstacle calculated by the moving obstacle progress route calculating unit 21 in step S106, the host vehicle route calculating unit 22 The traveling route of the host vehicle H is calculated. That is, in the example of the scene shown in FIG. 3, based on the information on the motion state of the own vehicle H, the information on the parked vehicle P that is a stationary obstacle, and the information on the oncoming vehicle C that is a moving obstacle, The travel route of the vehicle H is calculated.

  In step S109, the warning necessity determining unit 30 performs processing for determining the necessity of assistance to the driver based on the travel route calculation result of the host vehicle H by the host vehicle travel route calculating unit 22 in step S108. If it is determined that the driver needs assistance, the speaker 8 connected to the microprocessor 7 gives a warning to the driver and prompts the driver to take necessary operations at an early stage. Provide assistance to the driver.

  And in 1st Embodiment, the said calculation period is repeatedly performed for every predetermined time interval, and, thereby, assistance is provided with respect to a driver | operator.

  According to the first embodiment, when calculating the travel route of a moving obstacle, the moving obstacle is prevented from contacting other moving obstacles other than the moving obstacle, stationary obstacles and the own vehicle. Since this is based on a route plan that imposes conditions, the moving obstacle is expected to change its motion state due to interference with other moving obstacles other than the moving obstacle and stationary obstacles. However, it is possible to calculate a realistic and accurate travel route in consideration of such interference as an expected travel route, and thereby perform appropriate driving assistance.

  In addition, according to the first embodiment, when calculating the traveling path of the moving obstacle, by reflecting the approaching degree with other moving obstacles other than the moving obstacle, stationary obstacles and the own vehicle, Conditions for avoiding contact with other moving obstacles, stationary obstacles, and the own vehicle can be easily expressed, and the process of calculating the travel route can be easily executed. Further, when calculating the traveling route of the moving obstacle and the traveling route of the own vehicle, it is possible to calculate the traveling route so as not to deviate from the road by considering the degree of approach with the road boundary.

<< Second Embodiment >>
A second embodiment of the present invention will be described with reference to FIG. FIG. 13 is a diagram showing a method for setting an obstacle ground coordinate system in the second embodiment.

  In the second embodiment, except that the method of calculating the traveling route of the moving body (oncoming vehicle C) and the own vehicle (own vehicle H) by the moving obstacle traveling route calculation unit 21 and the own vehicle traveling route calculation unit 22 is different. The configuration of the devices installed in the vehicle 1 (own vehicle H) shown in FIGS. 1 and 2, the functions of the devices, and the driving support process shown in FIG. 12 are the same as those in the first embodiment described above. Explanation of overlapping parts is omitted.

That is, in the first embodiment, when the traveling path of the oncoming vehicle C that is a moving obstacle is calculated by the moving obstacle traveling path calculation unit 21, the stopped vehicle P is represented by the potential field shown in the above equation (7). Although expressed, the second embodiment is characterized in that the stopped vehicle P is expressed by an inequality region. That is, as shown in FIG. 13, the stop vehicle P is expressed by a region P represented by the following equation (23) with respect to the detected position coordinates (x _P , y _P ), and based on this, the oncoming vehicle C Calculate the progression path.

ここで、ｌ_ｘ、ｌ_ｙは、それぞれ車両の占有領域の長さおよび幅を表す。このように、停止車両Ｐを不等式領域で表現することにより、より厳密に、停止車両Ｐとの接触判定に基づく進行経路を算出することができる。

Here, l _x and l _y represent the length and width of the occupied area of the vehicle, respectively. In this way, by representing the stopped vehicle P in the inequality region, it is possible to calculate the travel route based on the contact determination with the stopped vehicle P more strictly.

Here, the method of expressing the stop vehicle P in the inequality area as described above when calculating the travel route of the oncoming vehicle C is illustrated, but when calculating the travel route of the oncoming vehicle C, the stop vehicle P is stopped. In addition to the vehicle P, the own vehicle H may be expressed by such an inequality region to calculate the travel route. Furthermore, when the traveling route calculation unit 22 calculates the traveling route of the own vehicle H, the traveling route may be calculated by expressing the oncoming vehicle C and the stopped vehicle P in such an inequality area. Good. In these cases, in the travel route calculation of the oncoming vehicle C and the host vehicle H, a travel route that does not enter the occupied area other than the travel route calculation target is calculated. As a method for calculating a travel route that does not enter an occupied area other than the travel route calculation target, for example, literature: Mukai et al., “Approach to obstacle avoidance of vehicles by model predictive control” (No. 49 2006). The travel route can also be calculated by using the method described in this document. Therefore, in this case, from the evaluation function (see the formulas (4) and (8)) shown in the first embodiment, L _O The corresponding term will be excluded, but even if the term corresponding to L 2 _O is excluded, a travel route that does not come into contact with other obstacles or other moving objects is calculated in the same manner as in the first embodiment. be able to.

<< Third Embodiment >>
A third embodiment of the present invention will be described with reference to FIGS. 14, 15, and 16A to 16C. FIG. 14 is a flowchart showing a process of driving support by the driving support apparatus according to the third embodiment. FIG. 15 is a diagram showing an example of calculating a traveling route of the vehicle H according to the third embodiment in the scene example shown in FIG. 16A to 16C are diagrams showing a calculation process of the traveling route of the host vehicle H shown in FIG.

  In the third embodiment, an apparatus installed in the vehicle 1 (host vehicle H) shown in FIGS. 1 and 2 except that the process shown in FIG. 14 is adopted instead of the driving support process shown in FIG. The configuration and the function of each device are the same as those in the first embodiment described above, and the description of overlapping parts is omitted.

  The driving support process by the driving support apparatus according to the third embodiment will be described along the flowchart shown in FIG. 14 by exemplifying the scene example shown in FIG. FIG. 14 is a flowchart illustrating a process of driving support by the driving support apparatus according to the third embodiment.

  First, steps S301, S302, and S303 are the same as steps S101, S102, and S103 in the first embodiment. In step S301, information on the road 600 and information on the vehicle H are obtained from signals detected by the sensors. To get. In step S302, if an obstacle is detected by the obstacle detection unit 12, the process proceeds to step S303. On the other hand, if no obstacle is detected, the obstacle is displayed on the road 600. Is not detected, the process is terminated, and after a predetermined time has elapsed, the process is started again from step S301. And in step S303, based on the information of the own vehicle H and the information of the oncoming vehicle C and the parked vehicle P, these information are expand | deployed on a ground coordinate system.

  In step S304, the same loop processing as in steps S104, S105, S106, and S107 in the first embodiment is performed. That is, a moving obstacle is extracted (step S104), a moving obstacle that has not yet been calculated as a travel route is selected, and is calculated as a travel route (step S105), and the travel route of the selected moving obstacle is selected. Is calculated (step S106), and it is determined whether or not the calculation of the travel route has been completed for all moving obstacles (step S107).

  In step S304, after the calculation of the travel routes of all moving obstacles is completed, the process proceeds to step S305. In step S305, similar to step S108 in the first embodiment, the vehicle state detection unit 11 of the sensor information processing unit 10 acquires and processes the information of the vehicle H acquired and processed, and the obstacle determined to be a stationary obstacle. Based on the information on the object and the information on the calculation route of the moving obstacle calculated by the moving obstacle travel route calculation unit 21, the travel route of the host vehicle H is calculated by the host vehicle route calculation unit 22.

Here, in the first embodiment, the calculation of the travel route, which has been performed only once for each moving obstacle and the own vehicle, is repeated a plurality of times in the third embodiment. In this respect, the third embodiment is different from the first embodiment. That is, in step S305, the host vehicle route calculation unit 22 calculates the host vehicle route, and then proceeds to step S306. In step S306, it is determined whether or not the repetition end condition is satisfied, and the repetition end condition is satisfied. If it is determined that there is, the process proceeds to step S307. On the other hand, if it is determined that the repetitive end condition is not satisfied, the process proceeds to step S304, and the travel route of each moving obstacle and the travel route of the host vehicle are calculated again. However, in the third embodiment, in the second and subsequent iteration loops, when the traveling route of the moving obstacle is calculated, the evaluation reflecting the traveling route of the other moving body including the own vehicle calculated in the immediately preceding iteration loop. A function is set. For example, in the scene example shown in FIG. 3, the ground coordinate value of the current position of the vehicle H as x _H and y _H in the above equation (7), which is an evaluation function set in the calculation of the traveling route of the oncoming vehicle C. Instead, {x _H (t), y _H (t) | t ₀ ≦ t ≦ t ₀ + T}, which is the traveling route of the vehicle H calculated in step S305, is used.

  As the iteration end condition in step S306, the number of iterations may be determined in advance, and a condition may be set such that the iteration is terminated when the predetermined number of iterations is reached, or calculated for moving obstacles and the own vehicle. In the case where the progress path is almost unchanged before and after the iterative operation, it is possible to set a condition such that the iterative operation is regarded as having converged and the iteration is aborted.

  In step S307, as in step S109 in the first embodiment, the driver is determined based on the travel route calculation result of the host vehicle H by the host vehicle travel route calculation unit 22 in step S305 by the warning necessity determination unit 30. A process for determining the necessity of assistance for the vehicle is performed, and if necessary, a warning is given to the driver to prompt the driver to take the necessary operation, thereby providing assistance to the driver.

  And also in 3rd Embodiment, the said calculation period is repeatedly performed for every predetermined time interval similarly to 1st Embodiment, and, thereby, assistance is provided with respect to a driver | operator.

  In the third embodiment, by adopting the driving support device capable of realizing the driving support process shown in FIG. 14, in particular, by providing step S306 and looping step S304 and step S305, the travel path of the oncoming vehicle C When calculating, the calculation result of the traveling route of the host vehicle H can be reflected. As a result, the following operational effects can be obtained.

  That is, in the above-described first embodiment, the processing procedure of calculating the traveling route of the host vehicle H after calculating the traveling route of the oncoming vehicle C that is a moving obstacle is employed. In the stage of calculating the travel route of, the travel route of the host vehicle H is not calculated. Therefore, in the first embodiment, the traveling route of the oncoming vehicle C is calculated without reflecting the traveling route of the host vehicle H.

  For example, in the example of the scene shown in FIG. 3, as shown in FIG. 15, a road width that allows two vehicles to pass is secured to the side of the stop vehicle P, and the vehicle H and the oncoming vehicle In a scene where two vehicles can pass each other when C takes a good course, the following results may be considered depending on the setting of the evaluation function in the first embodiment. That is, when the traveling route of the oncoming vehicle C is calculated without considering the traveling route of the host vehicle H, depending on the setting of the evaluation function in the first embodiment, for example, as shown in FIG. As the travel route, a travel route that secures a side passage margin with respect to the stopped vehicle P larger than necessary is calculated, and as a result, a travel route that forces the host vehicle H to be decelerated may be calculated. In other words, an unnecessarily conservative travel route may be calculated for the vehicle H. On the other hand, in the third embodiment, by adopting a driving support device capable of realizing the driving support process as shown in FIG. 14, it is possible to calculate a non-conservative progress route even in such a situation. To do. In FIG. 15, the traveling directions of the own vehicle H and the oncoming vehicle C are indicated by arrows, and the movement trajectories of the own vehicle H and the oncoming vehicle C are indicated by dotted lines (the same applies to FIGS. 16A to 16C). ).

  Here, in the third embodiment, first, when calculating the travel route of the oncoming vehicle C, the calculation result of the travel route of the host vehicle H is not taken into consideration. The travel route indicated by “C1” is calculated, and for the host vehicle H, the travel route indicated by “H1” in FIG. 16A is calculated based on the result.

  In the next iterative loop, the travel route “H1” of the host vehicle H is taken into account when calculating the travel route of the oncoming vehicle C, so that the distance between both the stopped vehicle P and the host vehicle H is maintained. A travel route is calculated. As a result, as shown in FIG. 16B, the traveling path of the oncoming vehicle C is a stopped vehicle P rather than the travel path “C1” calculated first (indicated by a dotted arrow in FIG. 16B). The travel route “C2” approaching is calculated.

  Further, based on the calculated travel route “C2” of the oncoming vehicle C, the travel route of the host vehicle H is calculated. At this time, the oncoming vehicle C is stopped when compared to the time when the first travel route is calculated. Since the vehicle is closer to the P side, the traveling route of the vehicle H is closer to the center of the road than the first calculated traveling route “H1” (indicated by a dotted arrow in FIG. 16C). The route “H2” is calculated. Then, by repeating such calculation, the traveling routes of the oncoming vehicle C and the host vehicle H converge to the traveling route as shown in FIG. And according to 3rd Embodiment, since it will be able to continue driving | running | working without repeating the movement state of the own vehicle H by the repeated calculation of such a calculation of the advancing path, it is more than necessary with respect to a driver | operator. The situation where a warning is given can be avoided.

  As described above, according to the third embodiment, the iterative calculation of the travel route calculation is performed within the same calculation cycle (the calculation cycle shown in FIG. 14), and therefore, it depends on the initial setting of the travel route calculation in the process of the iterative calculation. The error to be absorbed is absorbed, and it is possible to calculate the traveling path with higher accuracy.

<< 4th Embodiment >>
A fourth embodiment of the present invention will be described with reference to FIGS. FIG. 17 is a functional block diagram of the driving support apparatus installed in the vehicle 1 according to the fourth embodiment, FIG. 18 is a flowchart showing a driving support process by the driving support apparatus according to the fourth embodiment, and FIG. FIG. 20 is a plan view schematically illustrating an example of a scene to which the embodiment is applied, FIG. 20 is a diagram illustrating an example of processing by a travel path calculation target specifying unit in the fourth embodiment, and FIG. 21 is a travel path recording unit in the fourth embodiment. 22 is a diagram showing an example of the update process, FIG. 22 is a diagram showing an example of the procedure of the arithmetic processing in the fourth embodiment, FIG. 23 is a diagram showing an example of the travel route calculation result in the scene example shown in FIG. 19, and FIG. 19 is a diagram showing another example of the travel route calculation result in the scene example shown in FIG. 19, FIG. 25 is a graph showing the amount of turning angle determined to be necessary at each time in the case shown in FIG. 24, and FIG. When shown in That is a graph showing the acceleration is determined to be necessary at each time.

  In the fourth embodiment, unlike the first to third embodiments described above, the travel route calculation unit 20a in the microprocessor 7 includes a travel route calculation target designating unit 23, a travel route calculation unit 24, and a travel route recording unit. Thus, the driving support device capable of realizing the driving support process shown in FIG. 18 is adopted. By adopting such a configuration, in the first to third embodiments described above, the travel route is calculated for all the moving bodies (moving obstacles and the own vehicle) within one calculation cycle. Whereas the configuration of finishing is adopted, the fourth embodiment adopts a configuration in which the calculation of the travel route of each moving body (moving obstacle and own vehicle) is distributed over each calculation cycle. That is, in the fourth embodiment, for one moving body (moving obstacle and own vehicle), the travel route is calculated in one calculation cycle (the calculation cycle shown in FIG. 18), and then another moving body. Is for calculating the travel path in yet another calculation cycle (the calculation cycle shown in FIG. 18), and this is different from the first to third embodiments described above.

  The fourth embodiment of the present invention will be described in detail below. The microprocessor 7 is the same as the above-described first embodiment except for the travel route calculation unit 20a and the driving support process, and the description of the overlapping parts is omitted. Here, in the following description, it will be specifically described assuming the scene example shown in FIG. FIG. 19 is a plan view schematically showing an example of a scene to which the fourth embodiment is applied. In FIG. 19, the host vehicle H is traveling on a straight road 600 partitioned on both sides by a fence 700. In addition, the two-wheeled vehicle B is traveling in front of the host vehicle H, and the stop vehicle P is present at the right end of the road ahead (the side on which the host vehicle H and the two-wheeled vehicle B are traveling), and the front This shows a situation where the oncoming vehicle C is approaching.

  As shown in FIG. 17, in the fourth embodiment, the travel route calculation unit 20 a includes a travel route calculation target designating unit 23, a travel route calculation unit 24, and a travel route recording unit 25.

  The travel route calculation target designating unit 23 selects a mobile body from which the travel route calculation unit 24 calculates a travel route. In the example of the scene shown in FIG. 19, there are three moving bodies for which the travel route is calculated, that is, the motorcycle B, the oncoming vehicle C, and the own vehicle H. For these three, the travel route is calculated. Therefore, an appropriate order is assigned, and the travel route calculation unit 24 calculates the travel route based on this order. For example, when the travel route calculation target designating unit 23 sets the travel route calculation target in the order of the motorcycle B → the oncoming vehicle C → the own vehicle H, the order of travel route calculation is set in the buffer as shown in FIG. First, the identifier stored in the head buffer (in FIG. 20, the identifier corresponding to the two-wheeled vehicle B) is determined as a travel route calculation target, and is recorded later (FIG. 18). The travel route calculation unit 24 calculates the travel route, the travel route recording unit 25 records the travel route calculated, and the warning necessity determination unit 30 determines the necessity of warning. It will be. Then, the shift calculation is performed on the buffer by the next calculation cycle, and the rank of the travel route calculation is updated (the lower state of FIG. 20). The identifier stored in the second buffer is It is stored in the first buffer (in FIG. 20, an identifier corresponding to the oncoming vehicle C), and is a target for calculation of the travel route in the next calculation cycle. Such processing is repeated, and the two-wheeled vehicle B, the oncoming vehicle C, and the host vehicle H are sequentially subject to calculation of the travel route.

  The travel route calculation unit 24 calculates a travel route for the mobile body that is subject to the travel route calculation by the travel route calculation target designating unit 23.

Further, the travel route recording unit 25 records the travel route of each moving body (the motorcycle B, the oncoming vehicle C, and the own vehicle H in the example of the scene shown in FIG. 19) calculated by the travel route calculation unit 24. When the travel route is recorded, if the travel route information already calculated by the travel route calculation unit 24 and recorded in the travel route recording unit 25 exists, a process of updating to the new information is performed. Is called. For example, when the travel route calculation result of the motorcycle B at the time t ₀ is already recorded, the travel route recording unit when the travel route calculation unit 24 newly calculates the travel route of the motorcycle B at the time t ₃ . An example of the update process is shown in FIG. In FIG. 21, the j-th sampling point of the traveling path of the moving object “* (* is B, C, or H)” calculated at time t _i is expressed as x _* (j; t _i ), The travel route calculation results of the motorcycle B, the oncoming vehicle C, and the host vehicle H at the times t ₀ , t ₁ , and t ₂ are recorded, respectively, and the travel route of the motorcycle B is newly calculated at the time t ₃ . An example of the case is shown. Note that the right end data of the travel path recording unit is missing due to the shift operation, but the missing part is dealt with by extrapolating by performing an appropriate extrapolation process. In FIG. 21, the sampling point calculated by extrapolation is represented as x _* ′ (j; t _i ).

  When the travel route is calculated by the travel route calculation unit 24, the two-wheeled vehicle B and the oncoming vehicle C that are harmful to the moving obstacle are the same as those in the moving obstacle travel route calculating unit 21 in the first embodiment described above. What is necessary is just to calculate according to said Formula (2)-(8), Moreover, about the own vehicle H, said Formula (9)-(like the case in the own vehicle advancing route calculation part 22 in the above-mentioned 1st Embodiment). 22).

In addition, when a travel path has already been calculated for a mobile body other than the mobile body that is the target of travel path calculation, and the information is recorded in the travel path recording unit 25, the travel path is recorded. The travel path is calculated using the travel path thus determined. That is, for example, when calculating the travel route for the oncoming vehicle C, since the two-wheeled vehicle B, the host vehicle H, and the stopped vehicle P are evaluated as the above-described equation (7) that is an evaluation function, i = {B, H , P}, and when the travel routes of the motorcycle B and the host vehicle H have already been calculated and the travel route calculation result is recorded in the travel route recording unit 25, the evaluation function is X _B , y _B and x _H , y _H in Equation (7) are not the ground coordinate values of the current position of the two-wheeled vehicle B and the own vehicle H, but the two-wheeled vehicle B and the own vehicle H recorded in the travel route recording unit 25. {X _B (t), y _B (t) | t ₀ ≦ t ≦ t ₀ + T} and {x _H (t), y _H (t) | t ₀ ≦ t ≦ t ₀ + T} Is used.

  In the fourth embodiment, the travel route calculation target specifying unit 23 corresponds to the travel route calculation target specifying unit of the present invention, and the travel route recording unit 25 corresponds to the travel route recording unit of the present invention.

  Next, a driving support process by the driving support apparatus according to the fourth embodiment will be described along the flowchart shown in FIG. Also in the fourth embodiment, as in the first to third embodiments described above, if no obstacle is detected, the process is immediately terminated, and after a predetermined time has elapsed, the same process is performed again. It is necessary to switch the processing according to the detection status of the stationary obstacle / moving obstacle, which may be the same as in the first to third embodiments. Therefore, in the fourth embodiment, description of processing corresponding to a situation where a new stationary obstacle / moving obstacle is detected or a stationary obstacle / moving obstacle that has already been detected is not detected is omitted. In the following, a process of driving support in the case where a moving obstacle is extracted by performing the same processing as steps S101 to S104 of the first embodiment will be described.

  In step S401, as in step S101 of the first embodiment, information on the road 600 and information on the own vehicle H are acquired from signals detected by the sensors.

  In step S402, as in step S103 of the first embodiment, the information on the own vehicle H and the information on each obstacle (two-wheeled vehicle B, oncoming vehicle C, and parked vehicle P) are converted to ground coordinates. Deploy on the system.

  In step S <b> 403, the travel route calculation target designating unit 23 selects a mobile body from which the travel route is to be calculated among the detected mobile bodies (two-wheeled vehicle B, oncoming vehicle C, and host vehicle H). As described above, the travel route calculation target designating unit 23 may assign an appropriate order for calculating the travel route to the three-wheeled vehicle B, the oncoming vehicle C, and the host vehicle H. In this case, first, in step S404, the traveling route of the motorcycle B is calculated.

  In step S <b> 404, the travel route calculation unit 24 calculates a travel route for the mobile body that is the target of the travel route calculation selected by the travel route calculation target designating unit 23. For example, when the two-wheeled vehicle B is selected in step S403, the travel route is calculated for only the two-wheeled vehicle B.

  In step S405, the travel route information calculated by the travel route calculation unit 24 is recorded in the travel route recording unit 25. As described above, when there is already a travel route information recorded in the travel route recording unit 25, a process of updating to the travel route information newly calculated by the travel route calculation unit 24 is performed. Will be done.

  In step S406, similar to step S109 in the first embodiment, the warning necessity determination unit 30 is based on the travel route calculation result of the host vehicle H among the travel route calculation results of each moving body recorded in step S405. Thus, a process for determining the need for assistance to the driver is performed, and if necessary, a warning is given to the driver to prompt the driver to take the necessary operation, thereby assisting the driver. Do. Note that the determination by the warning necessity determination unit 30 is not performed at a stage where the progress accounting calculation result of the own vehicle H is not recorded in the travel route recording unit 25.

  Then, by repeating the processing based on FIG. 18 as described above at every predetermined calculation cycle, the processing as shown in FIG. 22 is sequentially performed in the microprocessor 7. That is, first, as shown in FIG. 18, for motorcycle B, as shown in FIG. 18, acquisition of information from signals detected by each sensor (step S401), development on the ground coordinate system (step S402), and selection of a travel route calculation target (Step S403), calculation of the travel route (Step S404), and recording of the travel route (Step S405). Next, steps S401 to S405 shown in FIG. Next, for the own vehicle H, in addition to steps S401 to S405 shown in FIG. 18, determination of necessity of warning (step S406) is performed. These are repeatedly executed in a form added with the determination of the necessity of warning (step S406).

  As described above, in the fourth embodiment, unlike the above-described first to third embodiments, calculation of the travel route of each moving body (moving obstacle and own vehicle) is performed over each calculation cycle. The configuration is distributed. For this reason, each calculation cycle can be shortened, which makes it possible to reduce the calculation load. Further, as described below, it is possible to quickly cope with a change in situation.

  FIG. 23 shows an example of a travel route calculation result of each moving body (two-wheeled vehicle B, oncoming vehicle C, own vehicle H) in the scene example in FIG. Here, a travel route “B1” in which the motorcycle B decelerates to pass the host vehicle H is adopted, and thus, the host vehicle H is predicted to continue traveling by lightly steering in the right direction “H1”. Is calculated.

  However, on the other hand, since the travel route obtained in FIG. 23 is only a prediction, it cannot be denied that the two-wheeled vehicle B and the oncoming vehicle C may move differently from the prediction. That is, as shown in FIG. 23, the prediction that the two-wheeled vehicle B passes over the own vehicle H and decelerates is such that the driver of the two-wheeled vehicle B recognizes the existence of the own vehicle H, and the own vehicle H stops first. When it is determined that it is better to pass the side of P, the prediction is accurate. However, if any one of the assumptions does not apply, the movement of the two-wheeled vehicle B may be different from the travel route “B1” shown in FIG. For example, there is a possibility that the traveling route “B2” in which the motorcycle B passes the side of the parked vehicle P without considering the host vehicle H as shown in FIG. On the other hand, according to the fourth embodiment, even in such a case, such a situation change can be achieved by configuring the travel route calculation target designating unit 23 and the travel route calculation unit 24 as follows. It can respond quickly.

  That is, in addition to the processing described above, the travel path calculation unit 24 compares the travel path of each mobile unit recorded in the travel path recording unit 25 with the actual movement of each mobile unit for each calculation cycle. Then, as a result of comparison, the predicted state of each moving body predicted by the travel path recording unit 25 and the predicted state of each mobile body calculated by the travel path calculating unit 24 based on the result actually detected by the sensor When the error of, becomes larger than a predetermined level, a process of increasing the travel path calculation order is performed for a moving object with a large error.

  For example, as shown in FIG. 23, although the traveling route “B1” is calculated based on the prediction that the two-wheeled vehicle B decelerates, the two-wheeled vehicle starts to move laterally without decreasing the speed, and the own vehicle H When the sign that the vehicle passes by the side of the parked vehicle P is detected without taking into account the traveling route calculation target designating unit 23, the traveling route update order of the motorcycle B recorded in the buffer is lower. Even so, the buffer is rewritten so that the update order of the motorcycle B is the highest. As a result, the process immediately updates the traveling route of the motorcycle B. In this case, since there is a possibility that the motorcycle B does not correctly recognize the existence of the host vehicle H, the progress of the host vehicle H is calculated in the travel route calculation of the two-wheeled vehicle B in the travel route calculation unit 24. Processing is performed so that the route is not reflected in the evaluation function. Specifically, in the evaluation function represented by the above equation (7), the subject vehicle H, the obstacle P, and the oncoming vehicle C are evaluated, and i = {H, P, C}. Only the oncoming vehicle C is evaluated and i = {P, C}.

  Then, by making such a correction in the travel route calculation unit 24, the presence of the host vehicle H is ignored in the travel route calculation of the two-wheeled vehicle B. As a result, as the travel route of the two-wheeled vehicle B, as shown in FIG. 24, the travel route “B2” shown in FIG. 24 is calculated instead of the travel route “C1” shown in FIG. 23, and the travel route “C2” shown in FIG. In addition, the travel route of the host vehicle H is also calculated as a travel route “H2” shown in FIG. 24 instead of the travel route “H1” shown in FIG. With respect to the own vehicle H, since a greatly different result is obtained between the travel route “H1” shown in FIG. 23 and the travel route “H2” shown in FIG. 24, as shown in FIG. 25 and FIG. In addition, although the operation amount exceeding the set threshold value is not calculated for the turning angle, the operation amount exceeding the set threshold value is calculated for the acceleration, so it is determined that a warning to the driver is necessary. A warning will be given. 25 and 26 are graphs in which time is taken on the horizontal axis and the amount and acceleration of the turning angle determined to be necessary at each time based on the travel route calculation result at each time on the vertical axis. is there.

<< 5th Embodiment >>
A fifth embodiment of the present invention will be described. In the above-described first to fourth embodiments, an example in which the traveling path of each moving body is performed for each moving body has been shown. However, in the fifth embodiment, the traveling path is calculated for each moving body at once. Is to do. In the fifth embodiment, for example, in the scene example shown in FIG. 19, when calculating the travel route of the oncoming vehicle C, the movement model of the oncoming vehicle C is assumed to be the model shown in the above equation (2). an operation input of the formula ^{_{(2) a x C, a}} y with ^C to the calculated by the optimization calculation, for the motorcycle B, and the operation input based on the same model as in the above formula (2) a _x ^{B 1} and a _y ^B are calculated. Then, together these two motion _{^{model, a x B, a y B}} , a x C, in the form of simultaneous optimization four operating amount of _a ^{y C,} to formulate the problem of traveling path calculation. In this case, the traveling route between the oncoming vehicle C and the two-wheeled vehicle B is calculated at the same time, and the route is calculated alternately with the host vehicle H. According to the fifth embodiment, the travel routes of a plurality of moving obstacles (the oncoming vehicle C and the two-wheeled vehicle B) are calculated at once, thereby calculating the travel routes one by one for each moving obstacle. The travel route can be calculated more efficiently than the travel.

<< 6th Embodiment >>
A sixth embodiment of the present invention will be described. In the sixth embodiment, in addition to the first to fifth embodiments described above, the obstacle attribute detected by the camera 2 is determined when calculating the travel route of each moving object, and the obstacle attribute is determined. The travel route is calculated according to.

  In particular, by adopting a method of detecting an obstacle by the camera 2 as in this embodiment, the position of the obstacle can be specified, and at the same time, the attribute of the obstacle can be determined. For example, pedestrians and bicycles and automobiles have greatly different running speed ranges. However, in each of the above formulas, there is no element that expresses the distinction according to the attribute of such an obstacle. Therefore, even if the target is a pedestrian or a bicycle, the target is treated as a target having athletic ability similar to that of a car, and there is a possibility that a travel route that cannot actually occur is calculated. Therefore, in the sixth embodiment, a condition as shown in the following formula (24) is imposed on the traveling speed in order to reflect the distinction by attribute.

上記式（２４）において、「＊」は、対象となる移動障害物の識別子であり、ｖ
_ｍａｘ ^＊は対象となる移動障害物に応じて設定される移動速度の最大値である。このような条件を導入することにより、上記式（２４）の条件を満たす範囲内で、移動障害物の進行経路が算出されることとなるため、各移動障害物の属性に応じた進行経路の算出が可能となり、これにより算出される進行経路の精度を高めることができる。

In the above formula (24), “*” is an identifier of the target moving obstacle, and v
_max ^* is the maximum value of the moving speed set according to the target moving obstacle. By introducing such a condition, the traveling path of the moving obstacle is calculated within the range satisfying the condition of the above formula (24), and therefore the traveling path corresponding to the attribute of each moving obstacle is calculated. Calculation is possible, and the accuracy of the travel path calculated thereby can be increased.

<< 7th Embodiment >>
A seventh embodiment of the present invention will be described with reference to FIG. FIG. 27 is a plan view schematically showing a vehicle 1a according to the seventh embodiment.

  In the seventh embodiment, unlike the above-described first to sixth embodiments, as shown in FIG. 27, the vehicle 1a further includes a turning angle servo controller 100, a turning motor 200, and a brake pressure control system 300. This is what makes it possible to provide direct support. That is, in the seventh embodiment, as shown in FIG. 27, actuators (steering angle servo controller 100, steering motor 200, and brake pressure control system 300) that control steering and braking are equipped on the vehicle side, Is controlled through the microprocessor 7, so that traveling along the traveling path can be automatically realized. In the seventh embodiment, the driving support process can be the same as that in the first to sixth embodiments described above. However, instead of the warning necessity determination process in steps S109, S307, and S407 of each driving support process shown in FIGS. 12, 14, and 18, a process of calculating the actuator operation amount is performed.

<< Eighth Embodiment >>
An eighth embodiment of the present invention will be described with reference to FIG. FIG. 28 is a plan view schematically showing a vehicle 1b according to the eighth embodiment.

  In the eighth embodiment, unlike the first to sixth embodiments described above, as shown in FIG. 28, the vehicle 1b further includes a reaction force torque controller 400 and a reaction force motor 500. By applying a reaction torque to the steering wheel, it is possible to provide support for realizing traveling along the traveling path calculated by the microprocessor 7. That is, in the eighth embodiment, as shown in FIG. 28, by providing the reaction force torque controller 400 and the reaction force motor 500, a steering operation is required to travel on the travel route calculated by the microprocessor 7. In this case, the reaction force torque is generated by the motor in accordance with the direction and magnitude of the steering amount, thereby prompting the driver to steer. In the eighth embodiment, when the brake operation is necessary, the driver is warned through a speaker. In the eighth embodiment, the driving support process can be the same as that in the first to sixth embodiments described above. However, in addition to the warning necessity determination process in steps S109, S307, and S407 of each driving support process shown in FIGS. 12, 14, and 18, a process of calculating the reaction torque operation amount is performed.

1 is a plan view schematically showing a vehicle 1 according to a first embodiment. It is a functional block diagram of the driving assistance device installed in vehicle 1 concerning a 1st embodiment. It is a top view which shows typically the example of a scene to which 1st Embodiment is applied. It is a figure which shows the setting method of the ground coordinate system in the example of a scene shown in FIG. It is a graph at the time of seeing the potential field expression in the scene example shown in FIG. 3 from the oncoming vehicle C side. It is a figure which shows the example of advancing path | route calculation of the oncoming vehicle C in the example of a scene shown in FIG. It is a graph which shows an example of a tire lateral force function. It is a graph at the time of seeing the potential field expression in the example of a scene shown in FIG. 3 from the own vehicle H side. It is a figure which shows an example of the advancing path | route calculation result of the own vehicle H in the example of a scene shown in FIG. It is a graph which shows the quantity of the turning angle judged to be necessary in each time in the case shown in FIG. It is a graph which shows the acceleration judged to be necessary in each time in the case shown in FIG. It is a flowchart which shows the process of the driving assistance by the driving assistance device which concerns on 1st Embodiment. It is a figure which shows the setting method of the ground coordinate system of the obstruction in 2nd Embodiment. It is a flowchart which shows the process of the driving assistance by the driving assistance device which concerns on 3rd Embodiment. It is a figure which shows the advancing route calculation example of the own vehicle H which concerns on 3rd Embodiment in the example of a scene shown in FIG. It is a figure which shows the calculation process of the advancing path | route of the own vehicle H shown in FIG. It is a figure which shows the calculation process of the advancing route of the own vehicle H shown in FIG. 15, and is a figure which shows the process following FIG. 16A. It is a figure which shows the calculation process of the advancing path | route of the own vehicle H shown in FIG. 15, and is a figure which shows the process following FIG. 16B. It is a functional block diagram of the driving assistance device installed in vehicle 1 concerning a 4th embodiment. It is a flowchart which shows the process of the driving assistance by the driving assistance device which concerns on 4th Embodiment. It is a top view which shows typically the example of a scene to which 4th Embodiment is applied. It is a figure which shows an example of the process by the advancing route calculation target designation | designated part in 4th Embodiment. It is a figure which shows an example of the update process of the progress path | route recording part in 4th Embodiment. It is a figure which shows an example of the procedure of the arithmetic processing in 4th Embodiment. It is a figure which shows an example of the advancing path | route calculation result in the example of a scene shown in FIG. It is a figure which shows the other example of the advancing path | route calculation result in the example of a scene shown in FIG. It is a graph which shows the quantity of the turning angle judged to be necessary in each time in the case shown in FIG. It is a graph which shows the acceleration judged to be necessary in each time in the case shown in FIG. It is a top view showing typically vehicle 1a concerning a 7th embodiment. It is a top view which shows typically the vehicle 1b which concerns on 8th Embodiment.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1, 1a, 1b ... Vehicle 2 ... Camera 3 ... Vehicle speed sensor 4 ... Steering angle sensor 5 ... Acceleration sensor 6 ... Yaw rate sensor 7 ... Microprocessor 8 ... Speaker 10 ... Sensor information processing part 11 ... Own vehicle state detection part 12 ... Obstacle detection unit 13 ... moving obstacle identification unit 14 ... road boundary information processing unit 20 ... travel route calculation unit 21 ... moving obstacle travel route calculation unit 22 ... own vehicle travel route calculation unit 20a ... travel route calculation unit 23 ... travel Route calculation target designation unit 24... Travel path calculation unit 25... Travel path recording unit 30 .. warning necessity determination unit 100... Turning angle servo controller 200 .. steering motor 300 .. brake pressure control system 400. … Reaction force motor 600… Straight road 700… 塀

Claims (16)

Own vehicle state detecting means for detecting the traveling state of the own vehicle;
Obstacle detection means for detecting obstacles around the vehicle;
Among the detected obstacles, a moving obstacle identifying means for identifying a moving obstacle that is a moving obstacle and a stationary obstacle that is stationary,
A travel route calculation means for calculating a travel route so that the vehicle does not touch all detected obstacles;
A vehicle driving support device comprising driving support means for performing driving support based on the calculated travel route,
The travel route calculating means calculates a travel route of a moving obstacle, and then calculates a travel route of the host vehicle based on the calculated travel route of the moving obstacle. .   The travel path calculating means reflects the degree of approach between the moving obstacle for calculating the traveling path and an obstacle other than the moving obstacle when calculating the traveling path of the moving obstacle. The vehicle driving support device according to claim 1, wherein a travel route of an object is calculated. Road boundary detecting means for detecting a road boundary portion that is a boundary portion between a range in which the vehicle can travel on a road on which the vehicle travels and a range in which the vehicle cannot travel;
The traveling path calculation means calculates the traveling path of the moving obstacle by reflecting the degree of approach between the moving obstacle and the road boundary when calculating the traveling path of the moving obstacle. The vehicle driving support apparatus according to 1 or 2.   When the travel route calculating means calculates the travel route of the moving obstacle, if the travel route has already been calculated for another moving obstacle other than the moving obstacle, The vehicle driving support device according to claim 1, wherein the traveling path of the moving obstacle is calculated by reflecting the traveling path of the obstacle. The travel route calculation means includes
A first calculation process for calculating travel paths of all detected moving obstacles;
A second calculation process for calculating a traveling route of the vehicle based on the calculated traveling routes of all moving obstacles;
A third calculation process for recalculating the travel routes of all moving obstacles based on the calculated travel route of the vehicle;
A fourth calculation process that recalculates the travel route of the host vehicle based on the travel routes of all the calculated moving obstacles,
The vehicle driving support device according to claim 1, wherein the first calculation process to the fourth calculation process are executed in this order.   The vehicle driving support device according to claim 5, wherein the third calculation process and the fourth calculation process are repeated a plurality of times. The travel route calculation means includes a travel route calculation target designating means for designating the order of calculation targets for all detected moving obstacles and the travel route of the host vehicle,
A travel route recording means for recording the calculation results of the travel routes of all the moving obstacles and the own vehicle;
The calculation of all the detected moving obstacles and the traveling route of the own vehicle is performed according to the order specified by the traveling route calculation target specifying means, and all the calculated moving obstacles and the own vehicle are calculated. The travel route is recorded or updated in the travel route recording unit, and the driving support unit performs driving support based on the travel route recorded or updated in the travel route recording unit. The vehicle driving support device according to any one of the above.   The travel path calculation target designating means compares the travel path of the moving obstacle calculated by the travel path calculation means with the actual travel path of the subsequent moving obstacle, and the path error is a predetermined level or more. The vehicle driving support device according to claim 7, wherein the order of calculation of the travel route is changed so that the travel route of the moving obstacle is preferentially calculated. The travel route calculation means includes surrounding recognition state estimation means for estimating a recognition state of the detected moving obstacle with respect to other obstacles other than the moving obstacle existing around the moving obstacle and the own vehicle. ,
The travel route calculation means, when it is estimated that the recognition state of the moving obstacle is low for any of the other obstacles and the own vehicle existing around the moving obstacle, the recognition state is low. The vehicle driving support apparatus according to claim 7 or 8, wherein the estimated other obstacle or the own vehicle is not reflected in the calculation of the travel route of the moving obstacle.   The travel path calculation means groups a plurality of detected moving obstacles, executes a travel path calculation process for each grouped group, and simultaneously calculates travel paths for all the moving obstacles in the group. The vehicle driving support device according to claim 1.   The vehicle obstacle according to any one of claims 1 to 10, wherein the moving obstacle identifying means discriminates an attribute of the detected obstacle and assigns a constraint condition for calculating a moving obstacle according to the determined attribute. Driving assistance device.   The said driving assistance means alerts a driver | operator, when the progress path | route which changes the present exercise state largely as a progress path | route of the own vehicle is obtained. Vehicle driving support device.   The driving support means alerts the driver when a traveling route is obtained such that the vehicle and all detected obstacles approach a predetermined level or more. The vehicle driving assistance device according to any one of 1 to 12.   The vehicle according to any one of claims 1 to 13, wherein the driving support means presents information prompting the driver to travel along the traveling route of the host vehicle calculated by the traveling route calculating means. Driving support device.   The vehicle driving support according to any one of claims 1 to 14, wherein the driving support means controls the vehicle to support traveling along the traveling route of the host vehicle calculated by the traveling route calculating means. apparatus. When a moving obstacle is detected around the vehicle, the travel route of the moving obstacle is calculated,
A driving support method for calculating a traveling route of the host vehicle based on a calculation result of the traveling route of the moving obstacle, and performing driving support of the host vehicle based on the calculated traveling route of the host vehicle.

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