JP4466360B2 - Lane departure prevention control device - Google Patents

Description

  The present invention relates to a lane departure prevention control device that prevents a departure when a host vehicle is about to depart from a traveling lane during traveling.

Conventionally, as this type of technology, for example, it is determined whether or not the host vehicle tends to deviate from the driving lane based on the shape of the road white line or curve recognized based on road image information obtained by a camera or the like, and tends to deviate. When it is determined that the vehicle is forcibly steered to prevent departure, and when the departure prevention control is being performed, the accuracy of the camera decreases and sufficient road image information cannot be obtained. Proposed to prevent deviation from the driving lane of the vehicle by estimating the curve shape based on the current steering angle and forcibly steering based on this (For example, Patent Document 1).
Japanese Patent Laid-Open No. 11-180328

As described above, if the detection accuracy of the road image information of the camera is lowered during curve driving and the object is lost, that is, if the curve shape cannot be detected, it will continue to prevent deviation based on the steering angle. For example, when the camera has lost the object immediately after the vehicle has entered the curve and the steering is not sufficiently performed, Depending on the steering angle, it is determined that it is not necessary to generate a steering torque for preventing lane departure even if the possibility of lane departure is determined based on the curve shape estimated from this steering angle. At this point, control for preventing lane departure is stopped, and control for avoiding lane departure may end although it is actually necessary to perform control for avoiding lane departure. There is a problem in that there is.
Accordingly, the present invention has been made paying attention to the above-mentioned conventional unsolved problems, and even when the detection accuracy of the curve shape is lowered, it is possible to accurately carry out prevention control of lane departure. An object of the present invention is to provide a lane departure prevention control device.

In order to achieve the above object, a lane departure prevention control device according to the present invention is a departure prevention control for preventing a departure from the traveling lane of the host vehicle based on a curve shape in front of the host vehicle and a traveling state of the host vehicle. I do.
At this time, the detection accuracy of the curve shape is detected, and the control content by the deviation prevention control is changed according to the detection accuracy of the curve shape.
Here, when the detection accuracy of the curve shape is lowered, when the departure prevention control is performed based on the lowered curve shape, the control accuracy of the departure prevention control is lowered or the control is terminated, etc. However, by taking into account this decrease in control accuracy, etc., the control content of deviation prevention control is changed according to the detection accuracy of the curve shape, and the control is performed in accordance with the detection accuracy of the curve shape. It is possible to accurately perform control within the range in accordance with.
Further, in the present application, the curve shape detection means includes an imaging means for imaging a road ahead of the host vehicle, and detects a curve shape based on imaging information in front of the host vehicle imaged by the imaging means. A curve shape detection means;
A second position detecting means for detecting a curve shape from road shape information around the own vehicle based on the position of the own vehicle detected by the current position detecting means; A curve shape detection means;
Correcting the host vehicle position detected by the current position detection unit based on imaging information captured by the imaging unit, and detecting a curve shape from the road shape information around the host vehicle based on the corrected host vehicle position; Curve shape detecting means,
The curve accuracy detection unit detects the curve detection accuracy based on a curve shape detection status in each of the first curve shape detection unit, the second curve shape detection unit, and the third curve shape detection unit. And
The deviation prevention control means is configured to detect an operation in a yaw moment direction that enhances deviation when the curve accuracy detection means determines that the curve shape is detected only by the third curve shape detection means. Thus, an operation reaction force control for applying an operation reaction force and a deceleration control for generating a deceleration in the vehicle are performed.

As a result, according to the lane departure prevention control device according to the present invention, when performing the departure prevention control for preventing the departure from the traveling lane of the own vehicle according to the curve shape in front of the own vehicle and the traveling state of the own vehicle, Since the deviation prevention control of the control content according to the detection accuracy of the curve shape is performed, the deviation prevention control is canceled during the deviation prevention control due to a decrease in the detection accuracy of the curve shape, or the control accuracy is Thus, it is possible to continue to perform the deviation prevention control within a range corresponding to the detection accuracy of the curve shape.
At this time, since the operation reaction force is controlled according to the detection state of the curve, it is possible to perform the departure prevention control in accordance with the detection accuracy.

Embodiments of the present invention will be described below.
FIG. 1 is a schematic vehicle configuration diagram illustrating an example of a lane departure prevention control apparatus according to the present embodiment. This vehicle is a rear-wheel drive vehicle equipped with an automatic transmission and a conventional differential gear, and the braking device can control the braking force of the left and right wheels independently of the front and rear wheels.

  Reference numeral 1 in FIG. 1 is a brake pedal, 2 is a booster, 3 is a master cylinder, and 4 is a reservoir. Normally, the braking fluid is boosted by the master cylinder 3 in accordance with the amount of depression of the brake pedal 1 by the driver. The pressure is supplied to the wheel cylinders 6FL to 6RR of the wheels 5FL to 5RR. A brake fluid pressure control circuit 7 is interposed between the master cylinder 3 and the wheel cylinders 6FL to 6RR. It is also possible to individually control the brake fluid pressures of the wheel cylinders 6FL to 6RR in the brake fluid pressure control circuit 7.

  The brake fluid pressure control circuit 7 uses a brake fluid pressure control circuit used for, for example, anti-skid control or traction control. In this embodiment, the brake fluid pressures of the wheel cylinders 6FL to 6RR are independently set. It is configured so that the pressure can be increased or decreased. The brake fluid pressure control circuit 7 controls the brake fluid pressures of the wheel cylinders 6FL to 6RR in accordance with a brake fluid pressure command value from a controller 8 described later.

In addition, the vehicle controls the driving torque to the rear wheels 5RL and 5RR, which are driving wheels, by controlling the operating state of the engine 9, the selected transmission ratio of the automatic transmission 10, and the throttle opening of the throttle valve 11. A drive torque control unit 12 is provided. The operating state control of the engine 9 can be controlled, for example, by controlling the fuel injection amount, ignition timing, fuel injection timing, and the like, and at the same time, by controlling the throttle opening, the idle valve opening, and the like. be able to.
The drive torque control unit 12 can independently control the drive torque of the rear wheels 5RL and 5RR that are drive wheels, but when the drive torque command value is input from the controller 8 described above. The drive wheel torque is controlled while referring to the drive torque command value.

  In addition, the vehicle includes a camera 13 and a camera controller 14 that are configured with a CCD camera or the like as a front external environment recognition sensor for detecting the position of the host vehicle in the travel lane for determining departure from the travel lane of the host vehicle. It has. The camera controller 14 detects, for example, a lane marker such as a white line from a captured image in front of the host vehicle captured by the camera 13 to detect a travel lane, and also the yaw angle φ of the host vehicle with respect to the travel lane, that is, the travel lane. The direction of the host vehicle, the lateral displacement X of the host vehicle from the center of the travel lane, the curvature ρ at each point where the distance from the host vehicle in the forward travel lane is different, the travel lane width L, and the like can be calculated. Yes. Furthermore, it is configured to detect a vehicle that is located on the same travel lane as the host vehicle and exists in front of the host vehicle as a preceding vehicle.

The camera controller 14 performs travel lane detection using a travel lane detection area for detecting lane markers and the like, and calculates the data for the detected travel lane. For example, a technique described in Japanese Patent Application Laid-Open No. 11-296660 can be used for detecting the traveling lane.
Specifically, lane markers such as white lines on both sides of the traveling lane in which the host vehicle is traveling are detected, and the traveling lane in which the host vehicle is traveling is detected using the lane marker. Here, if a lane marker such as a white line is detected (scanned) over the entire captured image, the calculation load is large and time is required. Therefore, a smaller detection area (so-called window) is set in an area where a lane marker is likely to exist, and the lane marker is detected in the detection area. Generally, when the direction of the host vehicle with respect to the lane changes, the position of the lane marker displayed in the image also changes. For example, in Japanese Patent Laid-Open No. 11-296660, the direction of the host vehicle with respect to the lane is estimated from the steering angle θ, and the image The detection area is set in the area where the lane marker in the box will be projected.

  Then, for example, a filtering process that makes the boundary between the lane marker and the road surface stand out is performed, and a straight line that seems to be the boundary between the lane marker and the road surface is detected in each lane marker detection region, and one point (lane marker candidate point) on the straight line is detected as the lane marker. It is detected as a representative site. If the lane marker candidate points of each window obtained in this way are continued, it is possible to detect a traveling lane that is deployed ahead of the host vehicle.

  The vehicle also includes an acceleration sensor 15 that detects longitudinal acceleration Xg and lateral acceleration Yg generated in the host vehicle, a yaw rate sensor 16 that detects yaw rate γ generated in the host vehicle, an output pressure of the master cylinder 3, so-called master. A master cylinder pressure sensor 17 that detects the cylinder pressure Pm, an accelerator pedal depression amount, that is, an accelerator opening sensor 18 that detects the accelerator opening Acc, a steering angle sensor 19 that detects the steering angle θ of the steering wheel 21, and each wheel 5FL Are provided with wheel speed sensors 22FL to 22RR for detecting a rotational speed of 5RR, so-called wheel speed Vwi (i = FL to RR), and a direction indicating switch 20 for detecting a direction indicating operation by a direction indicator. Output to the controller 8.

Further, the yaw angle φ of the host vehicle with respect to the travel lane detected by the camera controller 14, the lateral displacement X of the host vehicle from the center of the travel lane, the curvature ρ at each point of the travel lane, the travel lane width L, the drive torque control unit The driving torque Tw on the wheel shaft controlled at 12 is also output to the controller 8 together.
If the detected vehicle traveling state data has left and right directionality, the left direction is the positive direction and the right direction is the negative direction. That is, the yaw rate γ, the lateral acceleration Yg, the steering angle θ, and the yaw angle φ are positive values when turning left and negative values when turning right. Further, the lateral displacement X becomes a positive value when shifted to the left from the center of the traveling lane, and becomes a negative value when shifted laterally. Further, the curvature ρ of the traveling lane becomes a positive value in the case of the left curve, and becomes a negative value in the case of the right curve.

The vehicle is provided with an alarm device 23 for warning the driver when a lane departure is detected by the controller 8. The alarm device 23 includes a speaker and a monitor for generating a sound and a buzzer sound, and issues a warning to the driver by display information and sound information.
Further, the steering shaft 21 a connected to the steering wheel 21 is provided with a steering adjustment device 27 that operates as a means for adjusting a steering reaction force acting on the steering wheel 21 and a means for applying a steering assist force. The steering adjustment device 27 includes, for example, a motor provided on the steering shaft 21a for adjusting a steering reaction force acting on the steering shaft 21a or applying a steering assist force, and a control device for controlling the motor. The steering reaction force acting on the steering shaft 21a is adjusted by driving the motor in response to a command signal from 8, and a steering assist force is applied to the steering shaft 21a.

  The accelerator pedal 28 is provided with an accelerator pedal reaction force control device 29 for adjusting the reaction force acting on the accelerator pedal 28. The accelerator pedal reaction force control device 29 is configured in the same manner as a known accelerator pedal reaction force control device, and includes, for example, a motor provided in the accelerator pedal 28 and a controller that drives and controls the motor. The reaction force acting on the accelerator pedal 28 is adjusted as the accelerator pedal 28 is operated by driving the motor in response to a command signal from 8.

  Furthermore, this vehicle is equipped with a host vehicle position detection device 30 that receives a signal from a GPS satellite (not shown) and detects the current position of the host vehicle on a map. This own vehicle position detection device 30 stores nationwide map information including topographic information such as road routes, curve road radii, slope gradients, etc., and map information around the own vehicle based on the current position of the own vehicle. The road shape information such as the travel route and the travel lane width of the road on which the host vehicle is traveling is acquired and output to the controller 8 as navigation information together with the current position of the host vehicle.

  Further, the host vehicle position detection device 30 performs so-called road-to-vehicle communication with an infrastructure (not shown) provided on the travel road side, and acquires travel path information acquisition device 30a for acquiring environment information and the like of the travel road. The host vehicle position detection device 30 is also configured to output to the braking / driving force controller 8 the environmental information of the travel route acquired by the travel route information acquisition device 30a.

  Next, the processing procedure of the arithmetic processing executed by the controller 8 will be described with reference to the flowchart of FIG. This calculation process is executed by a timer interrupt every predetermined sampling time ΔT (for example, 10 [ms]). In this flowchart, no communication step is provided, but information obtained by the arithmetic processing is updated and stored in the storage device as needed, and necessary information is read out from the storage device as needed.

  In this calculation process, first, the longitudinal acceleration Xg, lateral acceleration Yg, yaw rate γ, wheel speed Vwi (i = 1 to 4), accelerator opening Acc, master cylinder pressure detected by each sensor in the process of step S1. Pm, steering angle θ, direction indication switch signal, yaw angle φ of the host vehicle with respect to the driving lane from the camera controller 14, lateral displacement X of the host vehicle from the center of the driving lane, curvature ρ at each point of the driving lane, driving lane width L, and the driving torque Tw from the driving torque control unit 12 is read. Further, the current position of the host vehicle is read from the host vehicle position detection device 30 as navigation information, and road shape information ahead of the host vehicle is read as data nodes (Xn, Yn, Ln). Xn and Yn represent node position information as shown in FIG. 3, and Ln represents a distance from the current position of the host vehicle 100. Further, the information on the travel lane width at the data node position added to the data node is read together. In addition, you may make it use the road width information acquired by the road-to-vehicle communication by the road information acquisition apparatus 30a for this information on the travel lane width.

Next, the process proceeds to step S2, and the vehicle body speed V of the host vehicle is calculated from the average value of the front left and right wheel speeds VwFL and VwFR which are non-driven wheels among the wheel speeds Vwi (i = FL to RR).
Here, the case where the vehicle body speed V is calculated based on the front left and right wheel speeds VwFL and VwFR has been described. For example, the vehicle is equipped with ABS control means for performing known anti-skid control, When the anti-skid control is performed by the ABS control means, the estimated vehicle speed estimated in the process of the anti-skid control may be used.

Next, the process proceeds to step S3, where the curve shape in front of the host vehicle is detected based on the information from the camera controller 14 and the navigation information from the host vehicle position detection device 30, and the degree of deviation of the host vehicle from the curve in front of the host vehicle is determined. calculate.
First, a curve shape and a deviation degree are calculated based on information from the camera controller 14. The start point of the curve is detected based on the information from the camera controller 14 input in step S1. Specifically, the curve start point is detected based on the transition of the curvature ρ at each point where the distance from the host vehicle in the traveling lane is different.

For example, as described in Japanese Patent Application Laid-Open No. 2001-310719, the travel lane width L detected by the camera controller 14, the lateral displacement X of the host vehicle from the center of the travel lane, and the yaw angle φ with respect to the travel lane Based on this, as shown in FIG. 4, the traveling state of the host vehicle with respect to the traveling lane is grasped, and the predicted time Tout until the host vehicle departs from the lane is calculated from the following equation (1).
Tout = (L / 2−X) / dX (1)
In addition, dX in Formula (1) is the variation | change_quantity per sampling time of the lateral displacement X, as shown in FIG.

  Although the case where the predicted time Tout is calculated based on the travel lane width L from the camera controller 14 has been described here, for example, the vehicle position detection device 30 notifies the vehicle shape information ahead of the current position of the vehicle. The predicted time Tout may be calculated using traveling lane width information. In addition, when the road shape information acquired by the road-to-vehicle communication includes information on the road lane width in the road information acquisition device 30a, the road lane width information acquired by the road-to-vehicle communication may be used. Good.

In addition, here, a case has been described in which the predicted time Tout until the own vehicle deviates is calculated from the lateral displacement X and its change amount dX. However, the present invention is not limited to this. The predicted time Tout until the host vehicle departs from the lane may be calculated based on the yaw angle φ, the transition of the curvature ρ of the traveling lane, the yaw rate γ of the vehicle, the steering angle θ, and the like.
When the predicted time Tout is calculated in this way, the deviation degree OUTcam corresponding to the predicted time Tout is specified from the control map shown in FIG.
In FIG. 5, the horizontal axis represents the predicted time Tout, and the vertical axis represents the deviation degree OUTcam, and the deviation degree OUTcam is set to decrease in proportion to the increase in the predicted time Tout.

Next, the curve shape and the deviation degree are calculated based on the navigation information from the vehicle position detection device 30. First, the curve shape in front of the host vehicle is recognized based on the navigation information from the host vehicle position detection device 30 input in step S1.
Specifically, the curvature βnav of each node point is calculated from the coordinates of each node point notified as road shape information in the navigation information. Here, for example, it is calculated by a known procedure based on the coordinates (Xn-1, Yn-1), (Xn, Yn), (Xn + 1, Yn + 1) of three consecutive points.

  Although the case where the curvature is calculated from the coordinates of three consecutive points has been described here, the present invention is not limited to this. For example, the curvature is calculated using an angle formed by a straight line connecting the preceding and following node points. May be. Here, the curvature is calculated based on the coordinates of each node point, but for example, the curvature of each node point is also stored as node information held as national map information in the vehicle position detection device 30. In this way, the node point at the corresponding location may be searched to obtain the curvature. Note that the curvature of the vehicle position may be calculated in the same manner.

  Further, when the own vehicle passes the curve start point, that is, when it is determined that the own vehicle has entered the curve based on the imaging information obtained by the camera 13, the curvature of each point detected based on the imaging information obtained by the camera 13 is determined. The host vehicle position is corrected by comparing the curve start point detected from the transition of ρ with the curve start point based on the curvature transition of the curvature βnav detected from the road shape information from the host vehicle position detection device 30.

  In other words, in a system that uses GPS information from GPS satellites, the position detection accuracy of the host vehicle when using this GPS information is reduced due to the occurrence of multipath or the inability to capture satellites depending on the terrain. There is a case. For this reason, the curve start based on the road shape information from the own vehicle position detection device 30 due to the difference between the current position of the own vehicle detected by the own vehicle position detection device 30 and the true current position of the own vehicle. There may be a difference between the distance of the point from the host vehicle and the distance of the curve start point from the host vehicle based on the imaging information of the camera 13. Therefore, the current position of the host vehicle is corrected by using a deviation between the curve start point based on the road shape information included in the navigation information from the host vehicle position detection device 30 and the curve start point based on the imaging information of the camera 13. To do.

  Specifically, first, the curve start point is specified based on the transition state of the curvature βnav calculated based on the road shape information of the navigation information. For example, as shown in FIG. 6, when the curvature βnav at each node changes from a state where values near zero continue to a large value, the node Mn at which the curvature βnav changes is specified as the curve start point. In FIG. 6, the horizontal axis is the node, and the vertical axis is the curvature βnav.

  On the other hand, the curvature ρ detected based on the imaging information of the camera 13 is also processed in the same procedure, and the curve start point is detected from the curvature change state. Then, if a node corresponding to the curve start point based on the imaging information of the camera 13 is a node Mc shown in FIG. 7, a curve start point (corresponding to the node Mn) based on the navigation information from the own vehicle position detection device 30 There is a deviation from the curve start point (corresponding to the node Mc) based on the imaging information of the camera 13. In such a case, the curve start point based on the imaging information of the camera 13 is validated, and the difference in the distance between the node Mn and the node Mc corresponding to the curve start point position based on the navigation information from the own vehicle position detection device 30. Only the own vehicle position detected by the own vehicle position detection device 30 is corrected. As a result, the position of the host vehicle serving as a reference for the distance to each node is corrected, so that the curve shape based on the imaging information of the camera 13 is corrected as indicated by the symbol “■” in FIG. In other words, the distance to the curve start point obtained from the navigation information and the distance to the true curve start point substantially coincide.

  That is, the position of the node Mn on the map corresponding to the curve start point position based on the navigation information from the own vehicle position detection device 30 is (Xm, Ym), and the current state of the own vehicle notified as the navigation information up to the node Mn. When the distance from the position is Lm, and the current position of the host vehicle deviates from the true value, the actual distance Lreal from the host vehicle to the curve start point, that is, based on the imaging information of the camera 13 Although the distance to the curve start point and the distance Lm to the node Mn (Xm, Ym) input from the own vehicle position detection device 30 are different, they are recognized by both when the own vehicle enters the curve. The correction is performed so that Lreal = Lm by correcting the own vehicle position by the amount corresponding to the difference between the curve start points. Thus, the current position of the host vehicle detected by the host vehicle position detection device 30 based on the difference between the curve start point based on the imaging information of the camera 13 and the curve start point based on the navigation information from the host vehicle position detection device 30. By correcting the position, the current position of the host vehicle can be obtained with higher accuracy.

  Here, a case has been described in which the curve start point based on the navigation information input from the vehicle position detection device 30 is corrected with the curve start point based on the imaging information of the camera 13, but the present invention is not limited thereto. Instead, for example, instead of a curve start point based on information captured by the camera 13, as described in Japanese Patent Application Laid-Open No. 2003-121181, for example, curve start point information predicted from the vehicle behavior of the preceding vehicle Or obtain the curve start point information from the infrastructure equipment arranged on the roadside, and based on this, the curve start point is corrected based on the navigation information input from the vehicle position detection device 30 You may make it do.

  Further, when navigation information is input from the vehicle position detection device 30, in order to estimate the driver's steering pattern, a curve shape based on the acquired navigation information is changed to a curve shape that can be passed at a steering speed that is lower than a predetermined value. Correct so that That is, the curve passage limit speed is defined so that the lateral acceleration G predicted to occur during the curve passage is equal to or less than a predetermined value.

Specifically, the following procedure is used. First, for each node, based on the curvature βnav calculated based on the navigation information from the vehicle position detection device 30, the steering angle δ required when actually passing through the node having the curvature βnav is set as follows. Based on the equation (2), calculation is performed for each node.
δ = lw × βnav (2)
In addition, lw in Formula (2) is a wheel base.

For example, when traveling on a curved road as shown in FIG. 8, the steering angle calculated from the equation (2) changes in the same manner as the change in curvature βnav at each node, as shown in FIG. 6, for example. It will be.
Subsequently, when passing through the curvature βnav detected at each node, a curve passing upper limit speed V0, which is a vehicle body speed that can pass below a predetermined lateral acceleration limit value Yglim, is calculated from the following equation (3). To do.
V0 = [Yglim × | 1 / βnav |] ^1/2 (3)

  As shown in FIG. 6, the steering speed δv when passing through the curve at the curve passing upper limit speed V0 calculated in this way is equal to or less than a preset steering speed (steering angle change amount) limit value δvlim. The curve shape based on the navigation information from the vehicle position detection device 30 is corrected around the curve start point Mn as shown in FIG. That is, in FIG. 9, the amount of change in curvature βnav is equivalent to the amount of change in steering angle, so in FIG. 9, correction is made so that the inclination of the change is equal to or less than the inclination corresponding to the limit value δvlim. Then, the position where the corrected steering angle (curvature) changes, that is, the node Mn ′ is recognized as the steering start point, that is, the curve start point.

  Note that the limit value δvlim of the steering speed (steering angle change amount) may be changed according to the vehicle body speed V as shown in FIG. In FIG. 10, the horizontal axis is the vehicle speed V, the vertical axis is the steering speed limit value δvlim, and in the region where the vehicle speed V is relatively low, the steering speed limit value δvlim is maintained at a relatively large constant value. As the speed V increases, the steering speed limit value δvlim decreases in inverse proportion to this, and the steering speed limit value δvlim is set to be maintained at a relatively small constant value in a region where the vehicle body speed V is relatively large. . That is, normally, the steerable steering is not performed when the vehicle body speed V is high, and therefore the steering pattern in accordance with the actual operation of the driver is estimated by setting the steering speed limit value δvlim to a small value. ing.

The deviation degree based on the navigation information of the vehicle position detection device 30 is, as shown in FIG. 11, the yaw rate γ detected by the yaw rate sensor 16 (shown by a broken line in FIG. 11), and as shown in FIG. A value obtained by multiplying a difference (shown by a one-dot chain line in FIG. 11) from a yaw rate γref (shown by a solid line in FIG. 11) estimated from the steering angle after correction to a predetermined gain Ky. Is set as the deviation degree OUTnav based on the navigation information of the vehicle position detection device 30. That is, it calculates from following Formula (4).
OUTnav = (γ−γref) × Ky (4)

  Here, as shown in FIG. 11, the case where the deviation degree is calculated based on the difference between the actual yaw rate γ and the estimated yaw rate γref has been described. However, the present invention is not limited to this. Estimating the deviation of the vehicle position estimated from the vehicle body speed V and the yaw rate γ from the curve start point and the actual road shape ahead of the vehicle specified from the navigation information from the vehicle position detection device 30; May be used instead.

Further, instead of comparing the actual yaw rate γ and the estimated yaw rate γref, the actual steering angle δ and the estimated steering angle δref are compared, or the actual steering angle change amount δ ′ and the estimated steering angle change amount δ′ref. Or may be compared. At this time, the gain Ky in the equation (4) may be set so as to increase as the vehicle body speed V increases.
Note that if the vehicle start point cannot be specified based on the imaging information of the camera 13 before the host vehicle enters the curve, the current position of the host vehicle is not corrected and the host vehicle position is not corrected. The yaw rate when passing the curve in consideration of the steering pattern of the driver in the same manner as described above with respect to the curve shape ahead of the host vehicle specified by the navigation information based on the current position of the host vehicle specified by the detection device 30 The change state of γref is estimated, and the deviation degree OUTnav is calculated based on this.

When the deviation degree OUTcam based on the imaging information of the camera 13 and the deviation degree OUTnav based on the navigation information from the vehicle position detection device 30 are calculated in this way, the process proceeds to step S4, and the curve detected in the step S3. The curve recognition state is detected based on the information measurement state.
For example, as shown in FIG. 12 (a), when the vehicle is in a state where the curve shape can be recognized based on the imaging information of the camera 13 before entering the curve, the curve start point position accuracy and the curve It is determined that the shape, that is, the curve radius R predicted from the transition of the curvature at each point can be detected with high accuracy, and the recognition state is set to “level 1” in the best state.

  Further, as shown in FIG. 12B, the curve shape cannot be detected after correcting the vehicle position detected by the vehicle position detection device 30 using the curve start point position based on the imaging information of the camera 13. When the vehicle is in a state where a curve shape based on the navigation information from the vehicle position detection device 30 corrected for the vehicle position detected by the vehicle position detection device 30 can be obtained, the position accuracy of the curve start point However, the accuracy of the curve shape is not necessarily high, and the recognition state is set to “level 2” which is medium.

Furthermore, as shown in FIG. 12C, the road shape cannot be acquired from the imaging information of the camera 13, and the curve shape is estimated based only on the navigation information from the own vehicle position detection device 30. Sometimes, it is determined that both the position accuracy of the curve start point and the accuracy of the curve shape are not necessarily high, and the recognition state is set to “level 3” which is the worst.
In FIGS. 12A to 12C, a portion where the road white line is represented by a broken line indicates that the detection accuracy of the road shape based on the imaging information of the camera 13 is low.

Thus, if the recognition state of the curve shape is grasped in the process of step S4, the process proceeds to step S5, and it is determined whether or not the driver intends to change the lane. This determination is made based on, for example, the operation information of the direction indicating switch 20 and the steering angle from the steering angle sensor 19.
Specifically, the direction indicator is operated, and the indicated direction specified from the operation information matches the departure direction specified by the detection of the departure degree in the process of step S3. Therefore, it is determined that the driver intends to change lanes and that the vehicle is intentionally departing from the lane.

Even when the direction indicator is not operated, the steering angle θ from the steering angle sensor 19 is equal to or greater than the threshold value and the amount of change is equal to or greater than the threshold value. And the departure direction specified in the process of step S3 are determined to be intentional lane departure.
And when it is judged that it is a driver's intentional lane departure, it judges that it is not a lane departure state.

Here, the presence or absence of the driver's intention to change the lane is estimated using the steering angle and the amount of change in the steering angle. However, for example, a steering torque detecting means for detecting steering torque is provided, and the steering angle is detected. Instead of this, the steering torque detected by the steering torque detection means may be used.
Next, the process proceeds to step S6, and it is determined whether or not the lane departure degree is a state in which lane departure avoidance needs to be avoided and lane departure avoidance control needs to be started. That is, it is determined that the vehicle is in a lane departure state when the degree of departure detected in step S3 satisfies a preset control start condition, and lane departure avoidance control is started.

  Specifically, when the recognition state detected in step S4 is “level 1”, that is, when the camera 13 can detect the curve shape, the deviation degree OUTcam based on the imaging information of the camera 13 is calculated. When the preset threshold value OUTth1 is exceeded, it is determined that the lane departure avoidance control is started. On the other hand, when the recognition state detected in step S4 is “level 2” or “level 3” and the curve shape cannot be detected by the camera 13, the vehicle position detection device 30 When the departure degree OUTnav based on the road shape information exceeds a preset threshold value OUTth2, it is determined that the lane departure avoidance control is started.

  At this time, in addition to the threshold values OUTth1 and OUTth2 for determining the start of the lane departure avoidance control, an alarm threshold value smaller than this is set, and the degree of departure is determined according to the recognition state of the curve shape. The alarm device 23 is activated when OUTcam or OUTnav exceeds a predetermined alarm threshold value, and the driver is notified of the tendency to deviate by voice or display before starting the deviation prevention control. It may be.

Next, the process proceeds to step S7, and a specific control method and control amount are set for the yaw moment direction control and the braking / driving force control executed as the lane departure avoidance control.
As the yaw moment direction control, for example, the brake fluid pressure control circuit 7 forcibly controls the brake fluid pressure to the wheel cylinder of each wheel, and controls the distribution of the brake fluid pressure to each wheel, thereby controlling the left and right wheels. The yaw moment is generated in the departure avoidance direction by controlling the braking force acting on the steering wheel, or the steering adjusting device 27 applies the steering assist force to the steering shaft 21a to apply the steering torque to forcibly steer. By doing so, the yaw moment control for generating the yaw moment in the departure avoidance direction or the steering operation reaction force control for adjusting the steering reaction force acting on the steering shaft 21a by the steering adjustment device 27 is performed.

Further, as the braking / driving force control, for example, the braking fluid pressure control circuit 7 forcibly increases the braking fluid pressure to the wheel cylinder, and forcibly applies the braking force, or the accelerator pedal reaction force. The control device 29 performs the accelerator pedal reaction force control for adjusting the reaction force against the depression of the accelerator pedal so that the accelerator pedal is difficult to be depressed.
Then, the control method and control amount of the yaw moment direction control and braking / driving force control are specified from the table shown in FIG. 13 according to the recognition state level detected in step S3.

  That is, when the recognition state is “level 1” and the curve shape can be recognized based on the imaging information of the camera 13, the yaw moment control is performed as the yaw moment direction control, and the braking / driving force Deceleration control is performed as control. Then, the control amounts by these control methods are set so that the yaw moment control amount and the deceleration control amount increase in proportion to the deviation degree OUTcam detected from the imaging information of the camera 13 being larger.

  When the recognition state is “level 2”, steering operation reaction force control is performed as yaw moment direction control, and deceleration control is performed as braking / driving force control. The amount of control by these control methods is such that as the deviation degree OUTnav based on the navigation information from the own vehicle position detection device 30 is larger, the steering operation reaction force control amount and the deceleration control amount are proportionally increased. Set to.

  When the recognition state is “level 3”, as shown in pattern a, steering operation reaction force control is performed as yaw moment direction control, and accelerator pedal reaction force control is performed as braking / driving force control. The amount of control by these control methods increases in proportion to the steering operation reaction force control amount and the accelerator pedal reaction force amount as the deviation degree OUTnav based on the navigation information from the own vehicle position detection device 30 increases. The steering operation reaction force control amount is set to a characteristic equivalent to the characteristic when the recognition state is “level 2”.

  When this recognition state is “level 3”, instead of the pattern a, steering operation reaction force control may be performed as yaw moment direction control, and deceleration control may be performed as braking / driving force control. At this time, the control amounts by these control methods are such that as the deviation degree OUTnav based on the navigation information from the own vehicle position detection device 30 is larger, the steering operation reaction force control amount and the deceleration control amount are proportionally increased. For example, compared with the case where accelerator pedal reaction force control is performed, the deceleration effect obtained when performing deceleration control is greater. The steering operation reaction force control amount may be smaller than the steering operation reaction force control amount, and as shown in pattern c, the steering operation reaction force control is performed as the yaw moment direction control, and the accelerator pedal reaction force control is performed as the braking / driving force control. The control amount by these control methods is based on the navigation information from the own vehicle position detection device 30. As the deviation degree OUTnav is larger, the steering operation reaction force control amount and the accelerator pedal reaction force amount are set to increase in proportion to this, but the steering operation reaction force control amount is recognized as in the case of the pattern b. The control amount may be set to be smaller than the characteristic of the steering operation reaction force control amount when the state is “level 2”.

  That is, in the table shown in FIG. 13, when the recognition state is “level 1” and the curve shape can be grasped with high accuracy, both the yaw moment direction control and the braking / driving force control directly affect the vehicle behavior. In order to reflect this, a yaw moment is generated and a braking force is generated, a steering operation is performed, and a deceleration is generated to actively suppress deviation. Further, when the recognition state is “level 2” and the detection accuracy of the curve shape is medium, the braking force is generated to delay the lane departure timing, and the yaw moment in the departure direction further acts. Control is performed to suppress the departure, and the driver is urged to prevent the departure of the lane. Further, when the recognition state is “level 3” and the detection accuracy of the curve shape is low, the yaw moment is further prevented from acting in the departure direction, and the driver is alerted to prevent lane departure. In addition, the lane departure timing is delayed by suppressing generation of driving force or generating deceleration. That is, as the curve shape recognition accuracy is higher, a sufficient deviation suppression effect can be obtained by performing control so that the vehicle shape is reflected directly. Conversely, when the curve shape recognition accuracy is low, the vehicle The lane is within the controllable range according to the accuracy of the curve shape while preventing the vehicle behavior of the host vehicle from being controlled based on the curve shape with low accuracy by performing the control directly reflected on the behavior. In addition to delaying the departure timing, the driver is urged to operate for lane departure.

  In FIG. 13, the case where the control distribution by the yaw moment direction control and the braking / driving amount control is made constant according to the recognition state of the curve shape has been described. For example, as shown in FIG. The control distribution may be changed according to the approach angle θi of the vehicle. In FIG. 14, (a) shows the case where the approach angle θi is small, and (b) shows the case where the approach angle θi is large.

  For example, the standard distribution shown in FIG. 15A is multiplied by a correction coefficient set according to the magnitude of the approach angle θi to the standard distribution of the control amount by the yaw moment direction control and the braking / driving force control. May be changed. For example, as shown in FIG. 15B, the correction coefficient k1 expressed with the braking / driving force control amount as the numerator and the yaw moment direction control amount as the denominator increases as the approach angle θi increases. In other words, the control of the yaw moment direction is performed by setting the distribution of the braking / driving force control amount to be larger and setting the change degree of the correction coefficient k1 to be steeper as the approach angle θi is larger. The braking / driving force may be controlled to generate a deceleration in the vehicle, and the warning type characteristic may be changed so as to warn of lane departure. Further, for example, as shown in FIG. 15C, the correction coefficient k2 expressed by using the yaw moment direction control amount as the numerator and the braking / driving force control amount as the denominator increases as the approach angle θi increases. That is, rather than controlling the braking / driving force by setting the distribution of the yaw moment direction control amount to be larger and setting the change rate of the correction coefficient k2 to be steeper as the approach angle θi is larger. By changing the yaw moment direction and applying the yaw moment to the vehicle, it may be changed so as to have a support type characteristic that promptly suppresses lane departure.

  When the detection accuracy of various sensors decreases and the curve shape recognition state deteriorates from “level 1” to “level 2”, the control amount of control by “level 1” is gradually increased by a predetermined change amount. While decreasing, the control amount by “level 2” is gradually increased by a predetermined amount, and the control method is smoothly switched. That is, as shown in FIGS. 16A and 16B, when the recognition state changes from “level 1” to “level 2” at time tc, the control method of the yaw moment direction control is shown in FIG. From the table, the yaw moment control is switched to the steering operation reaction force control. However, the control method is not changed at the time tc, but the control amount is decreased by a predetermined change amount after the time tc. On the contrary, the steering operation reaction force control amount is increased by a predetermined change amount after the time point tc.

  As shown in FIG. 16 (a), the duration of the yaw moment control is longer as the yaw moment control amount is larger as shown in FIG. 16 (a). As shown, the smaller the yaw moment control amount, the shorter the duration of the yaw moment control, that is, the longer the control amount at “level 1”, the longer the control at “level 1” continues. Thus, when the control amount is large, that is, when the deviation degree is large, the lane deviation is more actively suppressed for a longer time.

  As described above, when the recognition state deteriorates from “level 1” to “level 2”, the yaw moment control is gradually switched to the steering operation reaction force control as described above, and further, as shown in FIG. In addition, the steering operation reaction force control amount (shown by a broken line in FIG. 17) corresponding to the deviation degree OUTnav at this time is not the steering operation reaction force control amount (see FIG. 17) equivalent to the yaw moment control amount immediately before switching. 17 is indicated by a solid line). Specifically, the deviation degree OUTnav is multiplied by a preset gain to correct the deviation degree, and a control amount corresponding to the corrected deviation degree is generated, thereby increasing the control amount.

When the recognition state is “level 2”, the control amount is determined based on the deviation degree OUTnav based on the navigation information from the own vehicle position detection device 30, and the deviation degree OUTnav is determined based on the yaw direction of the own vehicle. This value is determined according to the state quantity.
As described above, multiplying the departure degree OUTnav by a gain to generate a steering operation reaction force control amount equivalent to the yaw moment control amount, that is, steering operation reaction corresponding to the departure degree OUTcam. This is equivalent to generating a force control amount, that is, it is possible to set a control amount not only according to the state amount in the yaw direction but also according to the degree of deviation considering the lateral displacement with respect to the road white line. In addition, it is possible to suppress deviation avoidance.

If the control method and control amount of the yaw moment direction control and braking / driving force control are specified in the process of step S7 in this way, the process proceeds to step S8. When it is determined in the process of step S6 that it is not necessary to start the lane departure avoidance control, the process proceeds to step S8 described later.
In step S8, a command signal to the target device is generated according to the control method and the control amount set in the process of step S7, and this is output.

  That is, if yaw moment control is specified as the yaw moment direction control, a command signal is output to the brake fluid pressure circuit 7 so as to adjust the brake fluid pressure so as to generate a yaw moment corresponding to the specified control amount. Alternatively, a command signal is output so as to generate a steering torque that can generate a yaw moment corresponding to a designated control amount to the steering adjustment device 27. In addition, if steering operation reaction force control is designated as the yaw moment direction control, a command signal is sent to the steering adjustment device 27 so that the operation reaction force for steering becomes an operation reaction force corresponding to the designated control amount. Output.

  If deceleration control is designated as the braking / driving force control, a command signal for generating a braking force capable of achieving deceleration corresponding to the designated control amount is output to the braking fluid pressure circuit 7, and the accelerator If the pedal reaction force control is designated, a command signal is output to the accelerator pedal reaction force control device 29 so that the reaction force against the depression of the accelerator pedal corresponds to the designated control amount.

Further, when it is determined in step S6 that it is not necessary to start the lane departure avoidance control, if the control is performed by any method as the yaw moment direction control or the braking / driving force control, these controls are performed. A command signal for ending is generated and output.
In this way, if a command signal is output to each part, the process is terminated and the process returns to the main program.

Next, the operation of the present invention will be described.
If the road shape can be detected based on the imaging information from the camera 13 and the curve shape can be detected, the lateral displacement X from the center of the traveling lane of the host vehicle based on the imaging information and the traveling Based on the lane width L, a predicted time Tout until the host vehicle deviates from the lane is calculated. At this time, when the host vehicle is traveling on a straight road or when traveling along a curve, the predicted time Tout is set to a relatively large value. The deviation degree OUTcam determined from is set to a relatively small value. Also, if the vehicle is about to enter the curve without steering, or if the steering amount is small relative to the curve curvature while passing through the curve, the lateral displacement X with respect to the travel lane gradually increases. In addition, since the change amount dX increases, the predicted time Tout until the departure is set to a relatively small value, and the departure degree OUTcam is set to a relatively large value.

  On the other hand, the curvature βnav at each node position is detected based on the road shape information from the vehicle position detection device 30, and based on this, the yaw rate γref according to the driver's steering pattern is estimated, and based on this, the deviation degree OUTnav is estimated. Is calculated. And when the host vehicle is traveling on a straight road, or when traveling along a curve, the difference between the yaw rate γref predicted to be necessary and the current yaw rate γ is small. The deviation degree OUTnav is set to a relatively small value, and when the vehicle is about to enter the curve without steering, or when the steering amount is small with respect to the curve curvature while passing the curve, etc. Since the difference between the yaw rate γref predicted to be necessary and the current yaw rate γ is large, the deviation degree OUTnav is set to a relatively large value (steps S1 to S3). When the host vehicle enters the curve and this is detected based on the imaging information from the camera 13, the curve starting point based on the imaging information and the curve starting point based on the navigation information from the host vehicle position detection device 30. Based on the difference, the current position of the host vehicle is corrected.

In this case, since the road shape ahead of the host vehicle can be recognized based on the imaging information from the camera 13, the curve recognition state is set to "level 1" (step S4), and the driver is directed to the direction at this time. If the indicator is not operated and steering is not performed, it is determined that the driver does not intend to change lanes (step S5).
In this case, since the recognition state is “level 1”, the departure control is determined based on the deviation degree OUTcam and the threshold value OUTth1, and the vehicle travels along the driving lane. When the deviation degree OUTcam is less than or equal to the threshold value OUTth1, it is determined that it is not necessary to perform deviation avoidance control. However, if the deviation degree OUTcam exceeds the threshold value OUTth1 due to a lack of steering amount, the deviation It is determined that it is necessary to start avoidance control (step S6), and from the table in FIG. 13, yaw moment control is specified as yaw moment direction control and deceleration control is specified as braking / driving force control in the recognition state “level 1”. (Step S7). Then, the control amount is set according to the departure degree OUTcam at this time. The larger the departure degree OUTcam, the larger the yaw moment control amount and the deceleration control amount, and the higher the lane departure degree, the more the departure. Thus, a large yaw moment in the direction of avoiding the vehicle acts and a greater braking force acts, and a force corresponding to the degree of lane departure acts, so that lane departure can be avoided accurately.

  If the camera 13 cannot detect an appropriate curve shape while passing through the curve from the state where the yaw moment control and the deceleration control according to the deviation degree OUTcam are performed, the curve recognition state is changed. It changes from “level 1” to “level 2”. Therefore, this time, control is performed based on the deviation degree OUTnav, and from the table shown in FIG. 13, the steering operation reaction force control is performed as the yaw moment direction control, and the deceleration control is performed as the braking / driving force control. The moment direction control is switched from the yaw moment control to the steering operation reaction force control. At this time, as shown in FIG. 17, the steering operation reaction force control amount is increased while the yaw moment control amount is decreased by a predetermined change amount, and at this time, the control amount corresponding to the yaw moment control amount is Since the steering operation reaction force control amount is increased until it becomes, it is possible to switch while maintaining the control amount by the yaw moment direction control, and not only the state amount in the yaw direction but also the lateral displacement with respect to the white road line. Therefore, the control according to the degree of deviation taking into consideration is performed, and the deviation can be suppressed more accurately.

  Further, even when the camera 13 can no longer detect the curve shape while passing through the curve, it is possible to suppress deviation based on the navigation information from the own vehicle position detection device 30 and to perform the curve at the camera 13. As the yaw moment direction control is switched from yaw moment control to steering operation reaction force control in order to perform departure avoidance control based on the curve shape based on the navigation information of the vehicle position detection device 30 that is predicted to be less accurate than the shape. A control method in accordance with the detection state of the curve shape, so that the yaw moment acting in the direction of increasing the lane departure is controlled to be less likely to be exerted from the control that positively generates the yaw moment in the departure avoidance direction, and Deviation avoidance control is continued with the control amount, so control with the control amount without excess or deficiency is performed. It can, can delay the lane departure timing performs operations arousal for lane departure can effectively perform lane departure avoidance control.

  On the other hand, in a state where the curve shape cannot be detected based on the imaging information of the camera 13 before entering the curve, and the curve shape is recognized based only on the navigation information from the vehicle position detection device 30, the curve shape Is recognized as “level 3”, and according to the pattern a in FIG. 13, for example, according to pattern a, steering operation reaction force control is specified as yaw moment direction control, and accelerator pedal reaction force control is specified as braking / driving force control. Control is performed with a control amount corresponding to OUTnav. When the recognition state is “level 3”, since the curve shape cannot be obtained from the imaging information of the camera 13, the current position of the host vehicle cannot be corrected, and the host vehicle position detection device 30. Control is performed based on a curve shape with relatively low detection accuracy based only on navigation information from, but when detection accuracy is low in this way, steering control is performed as yaw moment direction control, In addition, accelerator pedal reaction force control is performed as braking / driving force control, and a yaw moment is generated in a direction to avoid lane departure so as to directly reflect vehicle behavior, or a braking force is actively generated. Rather, the direction of suppressing the yaw moment in the direction of increasing lane departure, and the increase of driving force that leads to increased lane departure. Since the control is performed within the range in accordance with the detection accuracy of the curve shape, for example, the true current position and the own vehicle position detection device 30 are grasped by the detection accuracy of the current position of the own vehicle. Even if it is determined that there is a tendency to depart from the lane even though it is not actually a tendency to deviate from the lane due to an error with the current position of the host vehicle, Since departure prevention control is performed within a range that does not adversely affect the running state of the vehicle, appropriate departure prevention control can be performed in accordance with the detection accuracy of the curve shape. In pattern b, deceleration control is performed as braking / driving force control, but in this case, the amount of control is made smaller than usual in steering operation reaction force control as yaw moment direction control. Therefore, since the entire control amount acting on the vehicle is suppressed by the departure prevention control, the departure prevention control according to the detection accuracy can be performed also in this case.

In pattern c, the accelerator pedal reaction force control is further performed as the braking / driving force control in pattern b, and the increase in driving force that leads to an increase in lane departure is suppressed. Thus, even milder departure prevention control can be performed.
In this way, since the detection accuracy of the curve shape grasped by the host vehicle is estimated and deviation prevention control is performed in accordance with this, even if the detection status of various sensors deteriorates, the curve Deviation prevention control can be continued within a range corresponding to the shape detection accuracy. Therefore, for example, even when the detection accuracy of the curve shape is lowered, such as when imaging information from the camera 13 cannot be obtained while passing through the curve, the departure prevention control can be continued.

  Also, as described above, when the detection accuracy of the curve shape is lowered, the steering departure prevention control is continued within the range in accordance with the detection accuracy, the operation for the lane departure is urged and the lane departure timing is delayed. This can be realized without affecting the vehicle behavior by performing the departure prevention control based on the curve shape with low detection accuracy.

  At this time, the camera 13 that can grasp the curve shape with relatively high accuracy cannot obtain the curve shape, and is based on navigation information from the vehicle position detection device 30 with relatively low accuracy. Although control is performed based on the acquired curve shape, when it is determined that the host vehicle has passed the curve start point based on the imaging information of the camera 13, the current position of the host vehicle is corrected based on the navigation information. However, since the deviation prevention control is performed based on the corrected curve shape based on the current position of the host vehicle, the curve shape is specified from the current position of the host vehicle with relatively low detection accuracy based on the navigation information. In comparison, a more accurate curve shape can be obtained. Therefore, for example, even when the curve shape based on the imaging information of the camera 13 cannot be obtained while passing through the curve, and the curve shape cannot be obtained with high accuracy, the detection accuracy of the curve shape is not obtained. It is possible to avoid the departure prevention control being canceled due to the low value.

At this time, when the curve shape is detected based on the navigation information, the amount of change in the curvature is set to be equal to or less than the threshold value and is estimated in consideration of the driver's steering pattern. Thus, the departure situation with respect to the normal steering situation can be detected, and departure prevention control can be performed without causing the driver to feel uncomfortable.
Also, as shown in the table of FIG. 13, the control content is changed according to the recognition level of the curve shape, so that the camera 13 can no longer grasp the curve shape while passing the curve. Even if it exists, it can avoid that the control amount by the deviation prevention control changes suddenly. At this time, since not only the control amount by the deviation prevention control but also the control method is changed, it is possible to change the control contents step by step within a wider control range according to the recognition level of the curve shape. it can.

In the above embodiment, only when the recognition level changes from “level 1” to “level 2”, the control amount after the change is adjusted according to the control amount before the change. Although described above, the present invention is not limited to this, and the same adjustment may be made when the recognition level changes from “level 2” to “level 3”.
In the above embodiment, the case where the vehicle position detection device 30 holds the road shape information has been described. However, the present invention is not limited to this. For example, a curve from an infrastructure facility arranged on the traveling road side is used. Shape information is transmitted, the curve shape information is acquired by the road-to-vehicle communication means, and based on the curve shape information and the current position of the own vehicle specified based on the information from the GPS satellite, The present invention can be applied even when the curve shape is grasped.

In the embodiment described above, the case where the recognition level is set to three levels has been described. However, the present invention is not limited to this, and can be set to three or more levels.
In the above embodiment, in step S3 of FIG. 2, the process of detecting the curve shape ahead of the host vehicle based on the information from the camera controller 14 and the road shape information from the host vehicle position detection device 30 is performed. Corresponding to the curve shape detecting means, the camera controller 14 calculates the traveling lane width L and the lateral displacement X of the host vehicle from the center of the traveling lane, and the yaw rate sensor 16 corresponds to the traveling condition detecting means, and in step S3 The degree of deviation detected from the curve shape detected based on the information from the camera controller 14, the travel lane width L detected by the camera controller 14, and the lateral displacement X from the center of the travel lane of the host vehicle, and the host vehicle position detection device Detected from curve shape detected based on road shape information from 30 and yaw rate γ detected by yaw rate sensor 16 Processing in step S8 from the process and S5 for detecting a deviation degree that corresponds to the deviation prevention control means, the processing of step S4 corresponds to the curve accuracy detection means.

  Further, the camera 13 corresponds to the imaging means, and the camera controller 14 detects the curve shape based on the imaging information of the camera 13 corresponding to the first curve shape detection means. 2 corresponds to the current position detecting means, and the current position of the own vehicle in the navigation information is corrected when the own vehicle passes the curve start point in the process of step S3 in FIG. The process of estimating the change state of the yaw rate γref according to the curve shape ahead of the host vehicle based on the position corresponds to the third curve shape detecting means, and the current position of the host vehicle in the navigation information is corrected in the process of step S3. The process of estimating the change state of the yaw rate γref according to the curve shape ahead of the host vehicle based on the notified current position of the host vehicle is not performed. This corresponds to the state detection means. Further, the process of step S2 in FIG. 2 corresponds to the speed detection means, and the process of step S8 corresponds to the yaw moment control means and the braking / driving force control means.

It is a schematic block diagram which shows an example of the vehicle carrying the lane departure prevention apparatus in this invention. It is a flowchart which shows an example of the process sequence of the arithmetic processing performed with the controller 8 of FIG. It is explanatory drawing for demonstrating the positional information on a data node. It is explanatory drawing for demonstrating the variation | change_quantity dX of a lateral displacement. It is a characteristic view showing the correspondence between the prediction time Tout until departure and the departure degree OUTcam. It is an example of a change state of the curvature βnav based on road shape information from the vehicle position detection device 30. It is explanatory drawing for demonstrating the correction method of the own vehicle position. It is an example of a curve shape. It is explanatory drawing for demonstrating the correction method of a curve shape. FIG. 6 is a characteristic diagram showing a correspondence between a vehicle speed and a steering speed limit value. It is explanatory drawing for demonstrating the calculation method of the deviation degree based on the road shape information of the own vehicle position detection apparatus. It is explanatory drawing for demonstrating the level of the recognition state of a curve shape. It is a table showing a correspondence with a recognition state, a control method of yaw moment direction control and braking / driving force control, and its control amount. It is explanatory drawing for demonstrating an approach angle. It is explanatory drawing for demonstrating the method in the case of changing control distribution according to an approach angle. It is explanatory drawing for demonstrating the setting method of the controlled variable in case the level of a recognition state changes. It is explanatory drawing for demonstrating the setting method of the controlled variable in case the level of a recognition state changes.

Explanation of symbols

5FL to 5RR Wheel 6FL to 6RR Wheel cylinder 7 Braking fluid pressure control circuit 8 Controller 9 Engine 12 Drive torque control unit 13 Camera 14 Camera controller 15 Acceleration sensor 16 Yaw rate sensor 17 Master cylinder pressure sensor 18 Accelerator opening sensor 19 Steering angle sensor 20 Direction indication switches 22FL to 22RR Wheel speed sensor 23 Alarm device 27 Steering adjustment device 28 Accelerator pedal 29 Accelerator pedal reaction force control device 30 Own vehicle position detection device

Claims (11)

A curve shape detecting means for detecting a curve shape in front of the host vehicle;
A traveling state detecting means for detecting the traveling state of the host vehicle;
Deviation prevention control means for performing deviation prevention control for preventing deviation from the traveling lane of the host vehicle based on detection information of the curve shape detection means and the forward traveling state detection means;
Curve accuracy detection means for detecting the detection accuracy of the curve shape detected by the curve shape detection means,
The departure prevention control unit changes the control content of the departure prevention control based on the curve accuracy detected by the curve accuracy detection unit,
The curve shape detection means includes imaging means for imaging a road ahead of the host vehicle, and first curve shape detection means for detecting a curve shape based on imaging information in front of the host vehicle imaged by the imaging means;
A second position detecting means for detecting a curve shape from road shape information around the own vehicle based on the position of the own vehicle detected by the current position detecting means; A curve shape detection means;
Correcting the host vehicle position detected by the current position detection unit based on imaging information captured by the imaging unit, and detecting a curve shape from the road shape information around the host vehicle based on the corrected host vehicle position; Curve shape detecting means,
The curve accuracy detection unit detects the curve detection accuracy based on a curve shape detection status in each of the first curve shape detection unit, the second curve shape detection unit, and the third curve shape detection unit. And
The deviation prevention control means is configured to detect an operation in a yaw moment direction that enhances deviation when the curve accuracy detection means determines that the curve shape is detected only by the third curve shape detection means. A lane departure prevention control device that performs an operation reaction force control for applying an operation reaction force and a deceleration control for generating a deceleration in the vehicle. Provided with speed detecting means for detecting the vehicle body speed of the host vehicle,
The second and third curve shape detection means change the road curvature of the road shape ahead of the host vehicle specified by the road shape information based on the vehicle body speed detected by the speed detection means. 2. The lane departure prevention control device according to claim 1, wherein the road shape is corrected to a road shape that is equal to or less than a threshold value, and a curve shape in front of the host vehicle is detected based on the corrected road shape. The departure prevention control means includes a yaw moment control means for preventing departure by controlling the yaw moment, and a braking / driving force control means for preventing departure by controlling the braking / driving force,
3. The control degree by the yaw moment control means and the control degree by the braking / driving force control means are changed according to the detection accuracy of the curve shape by the curve precision detection means. The lane departure prevention control device described. The yaw moment control means is configured to be capable of controlling the yaw moment direction by a plurality of different control methods, and the braking / driving force control means is configured to be capable of controlling the braking / driving force by a plurality of different control methods,
The departure prevention control means changes the control method of the yaw moment control means and braking / driving force control means and the control amount by the control method according to the detection accuracy of the curve shape. The lane departure prevention control device according to claim 3. 4. The control method of the yaw moment control means and the braking / driving force control means is changed within a range of control directly reflected in vehicle behavior and control of a driver's operation reaction force. The lane departure prevention control device described. The departure prevention control means is a yaw moment that causes a yaw moment to act on the vehicle in a departure avoidance direction when the curve accuracy detection means determines that the curve shape is detected by the first curve shape detection means. 2. The lane departure prevention control apparatus according to claim 1, wherein moment generation control and deceleration control for generating deceleration in the vehicle are performed. The deviation prevention control means is configured to detect an operation in a yaw moment direction that enhances deviation when the curve accuracy detection means determines that the curve shape is detected only by the second curve shape detection means. The lane departure according to claim 1, wherein an operation reaction force control for applying an operation reaction force and an acceleration reaction force control for applying an operation reaction force to an operation for generating acceleration in the vehicle are performed. Prevention control device. The deviation prevention control means is configured to detect an operation in a yaw moment direction that enhances deviation when the curve accuracy detection means determines that the curve shape is detected only by the second curve shape detection means. Control reaction force control to apply the operation reaction force and deceleration control to generate deceleration in the vehicle,
The control amount according to the operation reaction force control is smaller in a control amount in the yaw moment direction than in a case where a curve shape is detected only by the third curve shape detection unit. Lane departure prevention control device. The deviation prevention control means is configured to detect an operation in a yaw moment direction that enhances deviation when the curve accuracy detection means determines that the curve shape is detected only by the second curve shape detection means. Control reaction force control that applies an operation reaction force and acceleration reaction force control that applies an operation reaction force to an operation that generates acceleration in the vehicle,
The control amount according to the operation reaction force control is smaller in a control amount in the yaw moment direction than in a case where a curve shape is detected only by the third curve shape detection unit. Lane departure prevention control device.   When the detection accuracy of the curve shape detected by the curve accuracy detection unit decreases, the deviation prevention control unit performs control after the detection accuracy decreases as the control amount by the control method before the detection accuracy decreases is larger. 2. The lane departure prevention control device according to claim 1, wherein a timing of switching to the method control is delayed.   When the detection accuracy of the curve shape detected by the curve accuracy detection unit decreases, the departure prevention control unit performs control after the detection accuracy decreases according to the control amount by the control method before the detection accuracy decreases. 2. The lane departure prevention control device according to claim 1, wherein the control amount according to the method is corrected in an increasing direction.

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