JP2010018062A - Vehicle driving support device - Google Patents

Abstract

[PROBLEMS] To change a risk distribution of a host vehicle to a driving lane according to a situation, and to enable driving support without a sense of incongruity / anxiety that matches a driver's driving feeling.
A current risk function Dline for a white line is calculated from necessary data such as road white line data and solid object data (S102), and a current risk function Dobstacle for a solid object is calculated (S103). . At this time, for example, when there is an obstacle in front of the lane of the host vehicle, the risk distribution for the white line is set so that the risk value becomes lower at the end of the white line. Then, the total risk function D is calculated from the risk functions Dline and Dobstacle (S106), and the steering control is performed with the avoidance route set based on the predicted value of the time change of the total risk function D, the predicted value of the time change of the vehicle position, and the like. And brake control are executed to provide driving assistance that does not feel uncomfortable or anxious according to the driving sensation of the driver.
[Selection] Figure 8

Description

  The present invention relates to a driving support apparatus for a vehicle that sets a risk in the surrounding environment of the host vehicle and performs driving support of the host vehicle based on the risk.

  In recent years, in vehicles such as automobiles, on-board cameras and laser radar devices are used to detect the driving environment in the outside world to recognize obstacles and three-dimensional objects such as preceding vehicles, and perform various controls such as alarms, automatic braking, and automatic steering. Technologies that avoid collisions and improve safety by executing them have been developed and put to practical use.

For example, in Patent Document 1 (Japanese Patent Application Laid-Open No. 2004-110346), an obstacle existing around the own vehicle is detected, a current risk potential for the obstacle of the own vehicle is calculated, and based on this risk potential. In addition, a technique for controlling the operation of the vehicle device so as to prompt the driver to perform driving operations related to the front-rear motion and the left-right motion of the host vehicle and limiting the control of the vehicle device to only one of the front-rear direction and the left-right direction is disclosed. ing.
JP 2004-110346 A

  However, in the conventional technology disclosed in Patent Document 1, depending on the risk to an obstacle and the traveling state such as the speed and acceleration of the host vehicle, a route set for collision avoidance is a normal driver's driving. There is a possibility of not meeting the intention. For example, it is set as a route to avoid obstacles on the right side once from the right to the left, or when there is an oncoming vehicle, or the risk of deviating from the driving lane due to a curved curve etc. Even when the value of the driver increases, a route that does not match the driver's feeling may be set, which may cause the driver to feel uncomfortable or uneasy.

  The present invention has been made in view of the above circumstances, and changes the risk distribution of the host vehicle with respect to the driving lane according to the situation, and enables driving support without a sense of incongruity / anxiety that matches the driving sensation of the driver. The object is to provide a driving assistance device.

  In order to achieve the above object, a driving support apparatus for a vehicle according to the present invention sets a risk in the surrounding environment of the host vehicle and provides driving support for the host vehicle based on the risk. A travel environment recognition unit for recognizing a travel environment of the vehicle and a risk distribution for the travel lane of the host vehicle are variably set according to the presence of a three-dimensional object in the travel environment recognized by the travel environment recognition unit or the lane shape of the host vehicle. And a risk distribution variable setting unit.

  According to the present invention, by changing the risk distribution with respect to the driving lane of the own vehicle according to the presence of a three-dimensional object or the lane shape of the own vehicle, driving assistance without a sense of incongruity / anxiety that matches the driving sensation of the driver. Can be made possible.

  Embodiments of the present invention will be described below with reference to the drawings. 1 to 10 relate to a first embodiment of the present invention, FIG. 1 is a schematic configuration diagram of a driving support device mounted on a vehicle, FIG. 2 is an explanatory diagram showing a risk distribution with respect to a normal lane, and FIG. FIG. 4 is an explanatory diagram showing the risk distribution for the lane when there is an obstacle in the lane, FIG. 4 is an explanatory diagram showing the risk distribution for the lane when there is a solid object outside the lane, and FIG. 5 is a pedestrian. FIG. 6 is an explanatory diagram showing the risk distribution with respect to the lane when there is a guardrail outside the lane, and FIG. 7 is a lane when there is a continuous oncoming vehicle. FIG. 8 is a flowchart of the driving support control process, FIG. 9 is an explanatory diagram showing an example of the risk distribution set ahead, and FIG. 10 is an explanatory diagram showing an example of the avoidance route to be generated is there.

  In FIG. 1, reference numeral 1 denotes a vehicle such as an automobile (own vehicle), and the vehicle 1 is equipped with a driving support device 2 that recognizes an external traveling environment and performs driving support for a driver. In the present embodiment, the driving support device 2 includes a stereo camera 3, a stereo image recognition device 4, a control unit 5 including a microcomputer and the like as main parts, and an automatic brake control device 22 and an automatic steering control device 23. And the like, and the driving environment is recognized based on the captured image of the external environment, and driving assistance control such as assistance for avoidance steering and warning for three-dimensional objects existing inside and outside the lane where the host vehicle runs I do.

  The stereo image recognition device 4, the control unit 5, the automatic brake control device 22, the automatic steering control device 23, and the like are each configured as a control unit composed of a single or a plurality of computer systems, and communicate with each other via a communication bus. Exchange each other.

  The own vehicle 1 is provided with a vehicle speed sensor 11 for detecting the own vehicle speed V, a yaw rate sensor 12 for detecting the yaw rate, a main switch 13 to which an ON-OFF signal for driving support control is input, and the like. The stereo image recognition device 4 and the control unit 5 are input, the yaw rate is input to the control unit 5, and the driving support control ON-OFF signal and the like are input to the control unit 5.

  The stereo camera 3 and the stereo image recognition device 4 function as a travel environment recognition unit that recognizes a travel environment outside the host vehicle 1, and the stereo camera 3 as a recognition sensor is a solid-state image sensor such as a CCD or a CMOS. The stereo image recognition device 4 includes a pair of (left and right) cameras using elements, and includes a processing unit that recognizes a three-dimensional object or a lane shape by including an image processing engine that processes an image captured by the stereo camera 3 at high speed. It is configured as. A set of cameras constituting the stereo camera 3 is attached with a fixed baseline length in front of the ceiling in the vehicle interior, and subjects the object outside the vehicle to stereo imaging from different viewpoints, and inputs image data to the stereo image recognition device 4.

  Image processing in the stereo image recognition device 4 is performed as follows, for example. First, distance information is obtained from a pair of stereo image pairs taken in the traveling direction of the host vehicle 1 captured by the stereo camera 3 from a corresponding positional shift amount, and a distance image is generated. Then, based on this data, a well-known grouping process is performed and compared with frames (windows) such as three-dimensional road shape data, side wall data, and three-dimensional object data stored in advance. Side wall data such as guardrails and curbs that exist along the road are extracted, and three-dimensional objects are classified and extracted into other three-dimensional objects such as two-wheeled vehicles, ordinary vehicles, large vehicles, pedestrians, and utility poles.

  Each of the recognized data is calculated by calculating the position in the coordinate system in which the own vehicle 1 is the origin, the front-rear direction of the own vehicle 1 is the X axis, and the width direction is the Y axis. In the vehicle data of a large vehicle, the length in the front-rear direction is preliminarily estimated as 3 m, 4.5 m, 10 m, etc., and the width direction uses the center position of the detected width. The currently existing center position is calculated with the coordinates of (Xobstacle, Yobstacle). In addition, when the longitudinal length of the vehicle can be obtained with high accuracy by inter-vehicle communication or the like, the above-described center position may be calculated using the length data.

  Further, in the three-dimensional object data, the relative speed with respect to the own vehicle 1 is calculated from the change in the X-axis direction and the change in the Y-axis direction of the distance from the own vehicle 1, and the vector V is taken into consideration for the speed V of the own vehicle 1 in this relative speed. Thus, the X-axis direction speed and the Y-axis direction speed (Vxobstacle, Vyobstacle) of each three-dimensional object are calculated. Each information obtained in this way, that is, white line data, guard rails existing along the road, side walls such as curbs, and three-dimensional object data (type, distance from own vehicle 1, center position (Xobstacle, Yobstacle), speed Each data such as (Vxobstacle, Vyobstacle) is input to the control unit 5.

  In this embodiment, an example in which the surrounding environment is recognized based on a stereo image will be described. However, the surrounding environment may be recognized using another recognition sensor such as a monocular camera or a millimeter wave radar. Also good.

  The control unit 5 includes the vehicle speed sensor 11 to the own vehicle speed V, the yaw rate sensor 12 to the yaw rate, the stereo image recognition device 4 to the white line data, the guard rails existing along the road, side walls such as curbs, and three-dimensional object data (type Each data such as a distance from the host vehicle 1, a center position (Xobstacle, Yobstacle), a speed (Vxobstacle, Vyobstacle), and the like is input.

  The control unit 5 sets a degree of risk (risk) in the surrounding environment of the host vehicle, and executes driving support control such as braking support, steering support and warning for the driver based on this risk. Specifically, the lane formed by the white line of the road is set as the traveling lane of the own vehicle, and the risk for the white line (the traveling lane of the own vehicle), the forward direction of the own vehicle (traveling direction) based on each input signal described above The risk for the obstacle (three-dimensional object) existing in () is functionalized and set as the risk functions Dline and Dobstacle, and the risk distribution in the XY coordinates with the vehicle 1 as the origin is obtained.

Then, these risk functions Dline and Dobstacle are added and integrated as shown in the following equation (1) to set the current total risk function D, and based on this total risk function D, an avoidance route for obstacles Is output to the automatic steering control device 23 and the automatic brake control device 22. When signals are output to the automatic brake control device 22 and the automatic steering control device 23, the signals are visually displayed on the display 21 to notify the driver.
D = Dline + Dobstacle (1)

Here, the risk function Dobstacle set for an obstacle (two-dimensional vehicle, ordinary vehicle, large vehicle, pedestrian, other three-dimensional object such as a utility pole) is set by the following equation (2).
Dobstacle = Kobstacle · exp (− ((Xobstacle−x) ² / (2 · σxobstacle ² )) − ((Yobstacle−y) ² / (2 · σyobstacle ² ))) (2)
Where Kobstacle: preset gain
σxobstacle: Pre-set variance in the X-axis direction
σyobstacle: Pre-set target dispersion in the Y-axis direction

  The variances σxobstacle and σyobstacle are set according to the recognition accuracy and presence status of the obstacle. For example, the lower the recognition accuracy by the stereo camera 3, the larger the variance σxobstacle, σyobstacle is set, and the larger is the case where the target type is a pedestrian or a two-wheeled vehicle based on the case of a normal vehicle or a large vehicle. It may be set to a small value in the case of other three-dimensional objects. Furthermore, you may make it set according to the lap | wrap rate of the width direction of the own vehicle 1 and the target solid object.

Further, the risk function Dline set for the traveling lane (white line) of the host vehicle is a function that leads to a larger risk value as the distance from the center of the lane is closer to the end position (white line), for example, (3) It is set by a function as shown in the equation. Note that Dh in the equation (3) is a correction coefficient for changing the risk distribution.
Dline = Dh · exp (aR · y ⁴ ) −1 (3)
However, aR = (2 / WR) ⁴ · log (Ds + 1)
Dh = 1 + Dobj · exp (−ax (x−Xobj) ² −ay (y−Yobj) ² )
WR: Lane width
Ds: Risk at the lane edge (y = ± WR / 2)
Dobj: Correction parameter by solid object
ax: Correction parameter in the X direction
ay: Y direction correction parameter
Xobj: X coordinate position of the three-dimensional object
Yobj: Y coordinate position of the solid object

  This risk function Dline is calculated as Dobj = 0, that is, Dh = 1, Ds = predetermined constant value in a situation where there is no three-dimensional object that hinders traveling in the traveling lane of the host vehicle, and is shown in FIG. Risk distribution like this. In other words, in the situation where there is no solid object that obstructs driving in the driving lane, the risk for the driving lane (white line) is uniformly increased at both ends of the lane compared to the center of the lane. Based on the distribution, steering assist or the like in traveling of the host vehicle is performed, and reliable lane keeping is possible.

The risk function Dline may be derived as a higher-order function of quadratic or higher. For example, when a quadratic function is used, a predetermined gain Kline is set as shown in the following equation (3 ′). Can be a risk function.
Dline = Dh · Kline · y ² (3 ')

  On the other hand, when there are obstacles in the lane and solid objects such as oncoming vehicles, pedestrians, and guardrails exist outside the lane, the calculation parameters of the risk function Dline are changed depending on the presence of these three-dimensional objects, and the driving environment Appropriate risk distribution according to That is, the control unit 5 has a function as a risk distribution variable setting unit that variably sets the risk distribution for the traveling lane of the host vehicle, and calculates the risk function Dline according to the presence of the three-dimensional object in the traveling environment. By changing at least one of the correction coefficient Dh at the time and the risk value Ds at the lane edge, it is possible to perform steering support and warning without a sense of discomfort and anxiety to the driver.

  Below, the example shown in the following (a)-(c) is demonstrated as a representative example about the example which changes the risk distribution with respect to a driving | running | working lane according to the presence condition of the solid object in driving environment.

(A) A situation in which a three-dimensional object exists in the lane As shown in FIG. 3A, when a three-dimensional object (obstacle) 10 is detected in the traveling lane ahead of the host vehicle 1, Dobj = 0 is set. Thus, the risk on the lane edge side (white line side) is reduced by setting the correction term Dh in the equation (3) to 1 and setting the risk value Ds to be smaller. In this case, the risk value Ds is set to a value that is, for example, about 30% smaller than a fixed value that is set when there is no solid object in the travel lane of the host vehicle 1. As a result, as shown in FIG. 3B, the risk function Dline has a risk distribution in which the risk at the lane edge side (white line side) is slightly higher than the risk at the center of the lane. Steering control toward the outside of the lane becomes easy, and smooth avoidance control that does not give the driver a sense of incongruity becomes possible.

(B) Situation where a solid object exists outside the lane As shown in FIG. 4A, when there is a three-dimensional object 50 such as an oncoming vehicle or an obstacle in the oncoming lane adjacent to the traveling lane of the host vehicle 1, 3) The correction parameters Dobj, ax, ay of the correction coefficient Dh in the equation are set to positive values larger than zero, and the risk function Dline is calculated. At this time, the correction parameter ax is set smaller as the x-direction component vx of the speed of the three-dimensional object 50 is faster.

  Thereby, the risk distribution with respect to the travel lane of the host vehicle 1 becomes higher as the risk on the side where the three-dimensional object 50 exists is closer to the three-dimensional object 50 as shown in FIG. Deviations can be avoided reliably. The same applies to the case where there is a pedestrian on the lane side of the host vehicle. As shown in FIG. 5, the risk of the side where the pedestrian is present increases as the pedestrian approaches, and abnormal approach to the pedestrian occurs. It can be surely prevented.

  Here, in the present embodiment, the correction parameters Dobj, ax, ay of the correction coefficient Dh are set as variable values according to the speed of the three-dimensional object. Specifically, the correction parameter Dobj is set to a larger value and the correction parameter ax is set to a smaller value as the x-direction component vx of the speed of the three-dimensional object 50 is faster. Further, the correction parameter ay is set to be smaller as the y-direction component vy of the speed of the three-dimensional object 50 is faster. Note that both the x-direction component vx and the y-direction component vy of the speed of the three-dimensional object 50 have positive values on the side approaching the host vehicle 1 as shown in FIG.

  Thereby, the approach from the own vehicle 1 can be prevented more reliably with respect to the three-dimensional object approaching toward the own vehicle 1 from the outside of the lane.

(C) Situation where there is a continuous solid object outside the lane If there is a continuous solid object outside the lane of the host vehicle, such as a guardrail or curbstone provided on the roadside, or a plurality of oncoming vehicles, the correction parameter The risk function Dline is calculated by setting ax to 0 and setting the correction parameters Dobj and ay to positive values larger than zero.

  Thereby, the risk distribution on the side where the three-dimensional object exists is increased, and the lane departure in the direction where there is a possibility of collision is surely prevented. At the same time, the closer the distance to the three-dimensional object, the higher the risk distribution on the side where the three-dimensional object exists. For example, as shown in FIG. 6A, when the guard rail 51 exists on the left side in the traveling direction of the host vehicle 1, the risk on the guard rail side over the section where the guard rail 51 exists as shown in FIG. 6B. The risk distribution is such that the value increases, and contact with the guard rail 51 can be reliably prevented.

  As shown in FIG. 7 (a), when there are a plurality of oncoming vehicles 52,... Continuously in the oncoming lane, the risk distribution on the traveling lane has an oncoming vehicle as shown in FIG. 7 (b). The distribution becomes higher on the side of 52,..., And lane departure in the direction where there is a possibility of collision can be reliably prevented.

  Here, in the present embodiment, when a continuous solid object exists outside the lane, the correction parameter ay is set to a predetermined constant value, while the correction parameter Dobj is set to the x-direction component vx of the speed of the solid object. A faster value is a variable value that is set to a larger value. When there are a plurality of oncoming vehicles 52,... In the oncoming lane, the x-direction component vx of the speed is obtained from the average speed of the oncoming vehicles 52,.

  As described above, the calculation of the risk function Dline is performed by appropriately changing the correction parameters of the lane edge risk value Ds and the correction coefficient Dh, and the correction parameter of the correction coefficient Dh depends on the presence of the three-dimensional object. It is changed in a complex and selective manner.

  Next, program processing related to driving support control executed by the driving support device 2 will be described with reference to the flowchart of FIG.

  In this program processing, first, in the first step S101, necessary parameters, specifically, white line data, side walls data such as guardrails and curbs existing along the road, and three-dimensional object data (type, from the vehicle 1) Distance, center position (Xobstacle, Yobstacle), speed (Vxobstacle, Vyobstacle), etc.) are read.

  Next, the process proceeds to step S102, where the current risk function Dline for the white line is calculated (see the above equation (3)), and in step S103, the current risk function Dobstacle for the obstacle is calculated ( (See equation (2) above). At this time, for example, when there is an obstacle in front of the lane of the host vehicle 1, the risk functions Dobstacle, Dline have a distribution as shown in FIG. 9, and the risk distribution for the white line has no obstacle. The risk value is set to be lower at the end of the white line compared to the risk distribution in this case (indicated by a broken line in FIG. 9).

In step S104, the current total risk function D is calculated from the previously calculated risk functions Dline and Dobstacle (see the above formula (1)). In step S105, the position of the three-dimensional object (Xobstacle (t), Yobstacle (t)) after t seconds is estimated by the following equation (5), for example.
(Xobstacle (t), Yobstacle (t)) = (Xobstacle + Vxobstacle · t, Yobstacle + Vyobstacle · t) (5)

  In the subsequent step S106, the position of the three-dimensional object (Xobstacle (t), Yobstacle (t)) estimated in step S105 is substituted for x and y of the total risk function D calculated in step S104. Then, by setting the total risk function D (Xobstacle (t), Yobstacle (t)) after t seconds, the time change of the total risk function D is predicted.

  Thereafter, the process proceeds to step S107, and an avoidance route for avoiding the three-dimensional object is set based on the predicted value of the time change of the total risk function D, the predicted value of the time change of the vehicle position, and the like. This avoidance route is set as follows, for example. That is, based on the temporal change of the total risk function D, a local minimum point in the Y-axis direction at the vehicle position for each time is calculated, and the deviation between the lateral position and the local minimum point of the vehicle 1 for each time and the turn An objective function for each time is created with the controlled variable. Then, the turn control amount for each time that minimizes the objective function is calculated as the turn control amount of the own vehicle 1, and the risk function for each route when the own vehicle 1 moves with the turn control amount for each time. The route having the smallest maximum value or cumulative value is set as the final avoidance route.

  When the avoidance route is set as described above, the process proceeds to step S108, and a control command is output to the automatic steering control device 23 and the automatic brake control device 22 based on the turning control amount of the avoidance route to execute the steering control and the brake control. , Exit the program. At this time, a signal is simultaneously output to the display 21 to notify the driver that the avoidance control is being executed.

  FIG. 10 shows an example of an avoidance route set by using a risk function Dline for the white line and a risk function Dobstacle for the obstacle ahead of the host vehicle 1. In this example, since the risk distribution at the end of the white line is set low, an avoidance route that prioritizes collision avoidance in front of the eyes by reducing the movement to stay in the lane is set.

  As described above, in the present embodiment, when a risk is set in the surrounding environment of the host vehicle, and the driving support is performed based on the risk, the risk distribution with respect to the traveling lane of the host vehicle can be changed according to the presence state of the three-dimensional object. Therefore, it is possible to realize driving support control that does not cause a sense of incongruity or anxiety that matches the natural driving sensation of a driver who tries to avoid a three-dimensional object.

  In particular, when the presence of a three-dimensional object is recognized in the traveling lane of the host vehicle, the risk distribution for the traveling lane of the host vehicle is set lower than the current risk distribution, thereby reducing the movement to stay in the lane. Thus, it is possible to quickly shift to control giving priority to avoiding a collision with a three-dimensional object.

  Even if the presence of a three-dimensional object is recognized outside the driving lane of the host vehicle, the risk distribution in the direction of the three-dimensional object is set higher than the current risk distribution. Avoiding avoidance control. In addition, in situations where there are continuous three-dimensional objects outside the lane, the risk distribution on the three-dimensional object side is set high over the range of the three-dimensional object, ensuring lane departure in the direction where there is a possibility of collision. Can be prevented.

  In the above-described embodiment, when three-dimensional objects are discontinuously present in the lane, all of the correction parameters Dobj, ax, and ay are set to variable values. Any one or two of them may be set as variable values, and the rest may be set as predetermined constant values. Further, the correction parameters Dobj, ax, and ay may be set to variable values according to the acceleration of the three-dimensional object, and the three-dimensional object approaching the host vehicle may approach from the own vehicle 1. Can be reliably prevented. Further, the correction parameter Dobj may be set to a different value depending on the type of the three-dimensional object.

  Next, a second embodiment of the present invention will be described. 11 and 12 relate to the second embodiment of the present invention, FIG. 11 is an explanatory diagram showing the lane shape and the line-of-sight distance, and FIG. 12 is an explanatory diagram showing the risk distribution for the lane in the situation of FIG.

  In the first embodiment described above, the example in which the risk distribution with respect to the traveling lane of the host vehicle is changed according to the presence of the three-dimensional object has been described. On the other hand, in the second embodiment, the risk distribution is changed according to the lane shape. It is variable.

  That is, as shown in FIG. 11, when it is detected from the recognition result by the stereo camera 3 as an in-vehicle recognition sensor that the traveling lane of the host vehicle 1 is curved forward with a radius of curvature R from the current position, the curvature is Accordingly, the risk of white lines is set higher. Specifically, as the curvature 1 / R of the curve increases, the lane edge risk value Ds in the risk function Dline of equation (3) is increased (the correction coefficient Dh is 1), and the white line side as shown in FIG. Increase risk distribution. In FIG. 12, the risk distribution along the curve is converted into a straight line for display so that the display is easy to understand.

  In this case, when the distance through which the curve can be seen by the recognition sensor (stereo camera 3) is known, the risk value Ds may be changed according to the line-of-sight distance. As shown in FIG. 11, the line-of-sight distance is the maximum distance between the left and right white lines detected by the recognition sensor. The smaller the maximum distance is represented by the line-of-sight distance. The risk value Ds for the left and right white lines may be changed separately according to the left and right line-of-sight distance.

  Note that when the risk value Ds is changed according to the curvature 1 / R of the curve or the line-of-sight distance, the speed V of the host vehicle may be taken into account. The risk value Ds is set so as to increase as the value increases.

  In the second mode, even in a situation where the driver's blind spot becomes large due to a curve with a large curvature, etc., the control to keep the own vehicle in the driving lane and avoid lane departure works more strongly, so the driver feels uncomfortable. As well as not giving, driving support that can give the driver a sense of security is possible.

The schematic block diagram of the driving assistance device mounted in the vehicle according to the first embodiment of the present invention. Same as above, explanatory diagram showing risk distribution for normal lane Same as above, explanatory diagram showing the risk distribution for the lane when there are obstacles in the lane As above, an explanatory diagram showing the risk distribution for the lane when there is a solid object outside the lane Same as above, explanatory diagram showing the risk distribution for the lane in the presence of pedestrians Same as above, explanatory diagram showing the risk distribution for the lane when there is a guardrail outside the lane Explanatory drawing which shows the risk distribution with respect to a lane in the situation where an oncoming vehicle exists continuously same as the above Same as above, flowchart of driving support control processing Explanatory drawing which shows an example of risk distribution set ahead as above As above, an explanatory diagram showing an example of a generated avoidance route Explanatory drawing which shows lane shape and line-of-sight distance in connection with 2nd Embodiment of this invention. Same as above, explanatory diagram showing the risk distribution for the lane in the situation of FIG.

Explanation of symbols

1 Vehicle 2 Driving support device 3 Stereo camera
4 Stereo image recognition device (running environment recognition unit)
5 Control unit (risk distribution variable setting part)
Dline Risk function for driving lanes

Claims (10)

In a driving support device for a vehicle that sets a risk in the surrounding environment of the host vehicle and supports driving of the host vehicle based on the risk,
A driving environment recognition unit for recognizing a driving environment outside the host vehicle;
A variable risk distribution setting unit that variably sets a risk distribution for the traveling lane of the host vehicle in accordance with the presence of a three-dimensional object in the driving environment recognized by the driving environment recognition unit or the lane shape of the host vehicle. A vehicle driving support device.   The vehicle according to claim 1, wherein the risk distribution variable setting unit sets the risk distribution of the traveling lane lower than the current risk distribution when recognizing the presence of a three-dimensional object in the traveling lane. Driving assistance device.   When the risk distribution variable setting unit recognizes the presence of a three-dimensional object outside the driving lane, the risk distribution on the side where the three-dimensional object of the driving lane exists is set to be higher than the current risk distribution. The driving support apparatus for a vehicle according to claim 1.   When the risk distribution variable setting unit recognizes the presence of a continuous three-dimensional object outside the driving lane, the risk distribution on the side where the three-dimensional object of the driving lane exists is set uniformly higher than the current risk distribution. The driving support apparatus for a vehicle according to claim 1.   When the risk distribution variable setting unit recognizes the presence of a solid object outside the travel lane, the risk distribution variable setting unit determines the risk distribution of the travel lane according to at least one of the position, speed, and acceleration of the recognized solid object. The vehicle driving support device according to claim 1, wherein the vehicle driving support device is set to be higher than the risk distribution of the vehicle.   The vehicle driving support device according to any one of claims 3 to 5, wherein the three-dimensional object outside the travel lane is a guard rail or a curb installed outside the road white line.   2. The vehicle driving support device according to claim 1, wherein the risk distribution variable setting unit variably sets the risk distribution of the travel lane according to the curvature of the curve of the travel lane.   2. The vehicle driving support device according to claim 1, wherein the risk distribution variable setting unit variably sets the risk distribution of the travel lane according to the line-of-sight distance of the curve of the travel lane.   2. The vehicle driving support apparatus according to claim 1, wherein the risk distribution variable setting unit variably sets the risk distribution of the traveling lane according to the line-of-sight distance of the curve of the traveling lane and the speed of the host vehicle. .   The vehicle driving support device according to any one of claims 1 to 9, wherein the travel lane is a lane formed by a road white line.

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