JP6905367B2 - Vehicle travel control device - Google Patents

Description

The present invention relates to a vehicle travel control device that controls traveling following a target route on which the own vehicle travels.

In vehicles such as automobiles, the driving lane of the own vehicle and the preceding vehicle in front of the own vehicle are detected by a camera, radar, etc., the distance between the preceding vehicle and the preceding vehicle is controlled to an appropriate distance, and the own vehicle is in the center position of the lane or ahead. A follow-up travel control technique that controls the vehicle to travel along a target route with the center position of the vehicle as a locus has been put into practical use.

In this follow-up driving control, the steering angle is controlled so that the traveling locus of the own vehicle matches the target path, but if a disturbance such as a crosswind suddenly is applied to the own vehicle, the steering correction for this sudden disturbance is delayed. This may give the driver a feeling of anxiety or discomfort.

Therefore, for example, in Patent Document 1, the driver of the own vehicle detects the change pattern of the lateral position of the preceding vehicle from the image in front of the own vehicle and determines the instability of the preceding vehicle from the change pattern of the lateral position of the preceding vehicle. The technology for notifying the vehicle and changing the control state of the follow-up control for the preceding vehicle is disclosed.

Japanese Unexamined Patent Publication No. 2004-220348

However, the technique disclosed in Patent Document 1 increases the target inter-vehicle distance or decelerates control when the unstable running state of the preceding vehicle itself is detected with respect to the follow-up control that follows the preceding vehicle at a constant inter-vehicle distance. The follow-up control state is changed to a state in which only the follow-up control is performed or the follow-up control is canceled, and it is difficult to cope with the disturbance suddenly applied to the own vehicle and maintain smooth running.

The present invention has been made in view of the above circumstances, and is a vehicle travel control device capable of mitigating the influence of disturbances suddenly applied to the own vehicle during traveling following a target route and maintaining stable and smooth travel. Is intended to provide.

The vehicle travel control device according to one aspect of the present invention is a vehicle travel control device that generates a target route on which the own vehicle travels and controls the follow-up travel to the target route, and is a travel control device for a vehicle in front of the own vehicle. The behavior change is calculated as the amount of change in the lateral position with respect to the average value of the lateral position with respect to the center position of the lane of the other vehicle for a predetermined time, and the disturbance that predicts the disturbance applied to the own vehicle based on the amount of the lateral position fluctuation is predicted. When the prediction unit and the disturbance prediction unit predict that a disturbance will be applied to the own vehicle, the control gain of the target steering angle that causes the traveling locus of the own vehicle to follow the target path is set before the disturbance acts on the own vehicle. It is provided with a follow-up control gain correction unit that corrects with the feed-forward control gain with respect to the curvature of the target path.

According to the present invention, it is possible to mitigate the influence of disturbances suddenly applied to the own vehicle during traveling following a target route and maintain stable and smooth traveling.

Configuration diagram of the driving control system Explanatory diagram of follow-up travel control for the target route Explanatory drawing showing the behavior change of the preceding vehicle due to the disturbance Explanatory drawing which shows the lateral position fluctuation amount of the preceding vehicle in FIG. Explanatory drawing showing the behavior change of the preceding vehicle and the oncoming vehicle due to the disturbance Explanatory drawing which shows the lateral position fluctuation amount of the preceding vehicle and the oncoming vehicle in FIG. Explanatory drawing showing behavior when there is no disturbance to the preceding vehicle and the oncoming vehicle Explanatory drawing which shows the lateral position fluctuation amount of the preceding vehicle and the oncoming vehicle in FIG. Flowchart of driving control processing Flowchart of target steering angle setting process

Hereinafter, embodiments of the present invention will be described with reference to the drawings. In FIG. 1, reference numeral 1 is a travel control system for a vehicle such as an automobile, which implements travel control including autonomous automatic driving of the vehicle. The travel control system 1 is centered on the travel control device 100, and includes an external environment recognition device 10, a positioning device 20, a map information processing device 30, an engine control device 40, a transmission control device 50, a brake control device 60, and a steering control device. The 70, the alarm control device 80, and the like are connected to each other via a communication bus 150 forming an in-vehicle network.

The external environment recognition device 10 uses in-vehicle camera unit 11, detection information of objects around the own vehicle by various devices such as radar devices 12 such as millimeter wave radar and laser radar, and infrastructure communication such as road-to-vehicle communication and vehicle-to-vehicle communication. The external environment around the own vehicle is recognized from the acquired traffic information, the position information of the own vehicle positioned by the positioning device 20, the map information from the map information processing device 30, and the like.

Hereinafter, as the external environment recognition process in the external environment recognition device 10, a process of processing an image captured by the camera unit 11 to recognize the external environment will be mainly described. The camera unit 11 is, for example, a stereo camera composed of two cameras that image the same object from different viewpoints, and is composed of a shutter-synchronized camera having an image sensor such as a CCD or CMOS. The camera unit 11 is configured by, for example, two cameras arranged on the left and right in the vehicle width direction with a predetermined baseline length in the vicinity of the rear-view mirror inside the front window in the upper part of the vehicle interior.

For the pair of left and right images captured by the camera unit 11 as a stereo camera, for example, the amount of pixel shift (parallax) at the corresponding position of the left and right images is obtained by stereo matching processing, and the amount of pixel shift is converted into brightness data or the like. A distance image is generated. Based on the principle of triangular survey, the points on this distance image are points in real space with the vehicle width direction, that is, the left-right direction as the X-axis, the vehicle height direction as the Y-axis, and the vehicle length direction, that is, the distance direction as the Z-axis. The coordinates are converted to, and the white line (lane) of the road on which the own vehicle travels, obstacles, the vehicle traveling in front of the own vehicle, and the like are three-dimensionally recognized.

A road white line as a lane can be recognized by extracting a point cloud that is a candidate for a white line from an image and calculating a straight line or a curve connecting the candidate points. For example, in the white line detection area set on the image, an edge whose brightness changes by a predetermined value or more is detected on a plurality of search lines set in the horizontal direction (vehicle width direction), and one set of white lines is set for each search line. The start point and the white line end point are detected, and the region between the white line start point and the white line end point is extracted as a white line candidate point.

Then, a model that approximates the left and right white lines is calculated by processing the time series data of the spatial coordinate positions of the white line candidate points based on the amount of vehicle movement per unit time, and the white lines are recognized by this model. As the approximate model of the white line, an approximate model in which the linear components obtained by the Hough transform are connected, or a model approximated by a curve such as a quadratic equation can be used.

The positioning device 20 mainly performs positioning by satellite navigation that positions its own vehicle based on signals from a plurality of satellites, and is affected by multipath due to the capture state of signals (radio waves) from satellites and the reflection of radio waves. When the positioning accuracy deteriorates, positioning is performed by autonomous navigation in which the self-position is positioned based on the orientation and moving distance of the own vehicle. The positioning device 20 may be integrally provided with a communication unit that acquires traffic information by infrastructure communication such as road-to-vehicle communication and vehicle-to-vehicle communication.

In positioning by satellite navigation, for example, a signal including information on orbit and time transmitted from a plurality of navigation satellites such as GPS satellites is received, and the self-position of the own vehicle is set to a three-dimensional absolute position based on the received signal. Positioning as. In addition, positioning by autonomous navigation is relative to the calculated position (own vehicle position) based on the traveling direction of the own vehicle detected by the directional sensor and the moving distance of the own vehicle calculated from the vehicle speed pulse output from the vehicle speed sensor. Position your vehicle's position as a change.

The map information processing device 30 includes a map database DB, and identifies and outputs the position of the map database DB on the map data from the position data of the own vehicle positioned by the positioning device 20. In the map database DB, for example, map data for navigation, which is mainly referred to when displaying the route guidance of vehicle traveling and the current position of the vehicle, and driving support control including automatic driving, which is more detailed than this map data, are stored. The map data for driving control that is referred to when performing the operation is retained.

In the map data for navigation, the previous node and the next node are linked to the current node via links, and information on traffic lights, road signs, buildings, etc. is stored in each link. ing. On the other hand, the high-definition map data for travel control has a plurality of data points between one node and the next node. In this data point, road shape data such as the curvature of the road on which the own vehicle travels, lane width, road shoulder width, and driving control data such as road azimuth angle, road white line type, number of lanes, etc. are used as data reliability. It is retained together with attribute data such as the date of data update.

The map information processing device 30 collates the positioning result of the position of the own vehicle with the map data, and presents the travel route guidance and traffic information based on the collation result to the driver via a display device (not shown). Further, the map information processing device 30 communicates road shape data such as the curvature, lane width, and road shoulder width of the road on which the own vehicle travels, and map information for travel control such as road azimuth angle, road white line type, and number of lanes. It is transmitted via the bus 150. The map information for travel control is mainly transmitted to the travel control device 100, but is also transmitted to other control devices as needed.

Further, the map information processing device 30 performs maintenance and management of the map database DB, tests nodes, links, and data points of the map database DB to always maintain the latest state, and also covers an area where no data exists in the database. Also create and add new data to build a more detailed database. The data update of the map database DB and the addition of new data are performed by collating the position data positioned by the positioning device 20 with the data stored in the map database DB.

The engine control device 40 controls the operating state of the engine (not shown) based on signals from various sensors that detect the operating state of the engine and various control information transmitted via the communication bus 150. The engine control device 40 includes fuel injection control, ignition timing control, and electronically controlled throttle based on, for example, intake air amount, throttle opening degree, engine water temperature, intake air temperature, air-fuel ratio, crank angle, accelerator opening degree, and other vehicle information. Engine control is performed mainly for valve opening control and the like.

The transmission control device 50 supplies the oil pressure to the automatic transmission (not shown) based on signals from sensors that detect the shift position, vehicle speed, etc. and various control information transmitted via the communication bus 150. It controls and controls the automatic transmission according to preset shifting characteristics.

The brake control device 60 controls the four-wheel brake device (not shown) independently of the driver's brake operation, based on, for example, a brake switch, four-wheel wheel speed, steering wheel angle, yaw rate, and other vehicle information. do. Further, the brake control device 60 calculates the brake fluid pressure of each wheel based on the braking force of each wheel, and performs anti-lock braking system, side slip prevention control, and the like.

The steering control device 70 controls the steering torque by an electric power steering motor (not shown) provided in the steering system based on, for example, vehicle speed, driver steering torque, steering wheel angle, yaw rate, and other vehicle information. As will be described later, in the steering control via the electric power steering motor, when the own vehicle is automatically driven following the target path, the steering control is controlled against the disturbance expected to be applied at a predetermined forward position. The gain is adjusted in advance.

The alarm control device 80 is a device that generates an alarm when an abnormality occurs in various devices of the vehicle. For example, a visual output of a monitor, a display, an alarm lamp, or the like, and an auditory output of a speaker, a buzzer, or the like. Warning / notification is given using at least one of. In addition, when the driving support control including automatic driving is suspended by the driver's operation, the current driving state is notified to the driver.

Next, the travel control device 100, which is the core of the travel control system 1, will be described. The travel control device 100 generates a target route on which the own vehicle travels based on the recognition result of the external environment by the external environment recognition device 10, the own vehicle position information and the traffic information from the positioning device 20 and the map information processing device 30. , The traveling control is executed via the engine control device 40, the transmission control device 50, the brake control device 60, and the steering control device 70 so as to follow the traveling along the target path.

In the follow-up travel control to the target route, the travel control device 100 determines the state of the disturbance occurring in front of the own vehicle from the change in the traveling state of the other vehicle in front of the own vehicle, and will join the own vehicle from now on. Predict possible disturbances. Then, when a sudden disturbance to the own vehicle is predicted, the control gain of the steering amount for following the traveling locus of the own vehicle to the target path is corrected in advance, and the following to the target path is followed according to the predicted disturbance. Adjust the sex.

As other vehicles in front of the own vehicle, the disturbance to the own vehicle is predicted by monitoring the behavior of the preceding vehicle, mainly the preceding vehicle in front of the vehicle traveling in the same direction in the driving lane of the own vehicle. Even if the preceding vehicle is not detected, the behavior of the oncoming vehicle is monitored if there is an oncoming vehicle in front of the oncoming vehicle traveling in the oncoming lane adjacent to the driving lane of the own vehicle toward the own vehicle. By doing so, it is possible to predict the disturbance that will be applied to the own vehicle from now on.

Therefore, the travel control device 100 has a target route generation unit 101, a target steering angle setting unit 102, a disturbance prediction unit 103, a follow-up control gain correction unit 104, and a control unit 105 as functional units related to follow-up travel control to the target route. It has. With these functional parts, the running condition of the own vehicle is adjusted in advance in preparation for the disturbance that will be applied to the own vehicle in the future, and the influence when the disturbance is actually applied to the own vehicle is mitigated to maintain stable and smooth running. It becomes possible to do.

Specifically, the target route generation unit 101 calculates the trajectory of the target point to be followed by the own vehicle based on the recognition result of the external environment by the external environment recognition device 10 and the high-definition map data. The locus of the target point is set as the target route. As shown in FIG. 2, the target point to be followed is set at the center position of the left and right white lines as the lane marking line in the road width direction so that the traveling position of the own vehicle is in the center of the lane. Is controlled by.

Here, an example will be described in which a route whose target point is the center position of the left and right white lines recognized from the captured image of the camera unit 11 in the road width direction is identified by a quadratic approximate curve and used as the target route. When the target path based on the white line information is generated, the candidate points of the white line detected on the image are mapped to the coordinate system in the real space with respect to the image coordinate system. The white line candidate points on this image are, for example, candidate points from about 7 to 8 m on the front side to about 100 m on the distant side, and all these white line candidate points are mapped in the real space.

Then, the white line candidate points detected on the image and the past white line data estimated based on the movement amount of the own vehicle are combined, and for those data point groups, for example, the least squares method is applied to the second order. Find the locus of white line candidate points represented by a curve. The locus of the white line candidate points is obtained as a left and right curve corresponding to the left and right white lines, and as shown by the following equation (1), the locus at the center position obtained from the left and right curves is used as the target path.
X = A ・ Z ² ＋ B ・ Z ＋ C… (1)

Here, in the equation (1), the coefficients A, B, and C represent the route components constituting the target route. The coefficient A represents the curvature component of the target path, the coefficient B is the yaw angle component of the target path with respect to the own vehicle (the angle component between the front-rear axis of the own vehicle and the target path (tangent line)), and the coefficient C is with respect to the own vehicle. It represents a position component (horizontal position component) in the lateral direction (X-axis direction) of the target path.

The target steering angle setting unit 102 sets the target steering angle αref of the follow-up control that matches the center position of the own vehicle in the vehicle width direction with the target point on the target path. As shown in the following equation (2), the target steering angle αref to the target path is the feedback (FF) controlled steering angle αff for tracing the path corresponding to the curvature κ of the target path and the target path. It is calculated by adding up the lateral position deviation of the own vehicle and the steering angle αfb of the feedback control for eliminating the yaw angle deviation of the own vehicle with respect to the target route.
αref ＝ αff ＋ αfb… (2)

Specifically, the steering angle αff of the feedforward control is calculated by multiplying the curvature κ of the target path by predetermined coefficients Gff and Dh, for example, by the following equation (3).
αff ＝ Dh ・ Gff ・ κ… (3)

For example, as shown in FIG. 2, the curvature κ in the equation (3) can be obtained by applying the value of the coefficient A when the target path is approximated by the quadratic equation shown in the equation (1). The coefficient Gff in Eq. (3) is the gain in feedforward control, and a map is created in advance by obtaining the optimum gain according to the curvature κ by experiments, simulations, etc., and is set with reference to this map. ..

Further, the coefficient Dh in the equation (3) is a correction coefficient set by the follow-up control gain correction unit 104, and is usually set to Dh = 1.0, and the gain Gff is set by the map value. As will be described later, when it is expected that a disturbance will be applied to the own vehicle after a predetermined time, Dh> 1.0 or Dh <1.0 is set, and the gain Gff of the map setting is corrected to the target route. The followability, that is, the convergence of the traveling locus of the own vehicle to the target path is adjusted.

On the other hand, the steering angle αfb of the feedback control is a lateral position with respect to the target path of the own vehicle at a predetermined distance ZL when traveling at the current steering angle, as shown in the following equations (4-1) to (4-4). Proportional control term αp for deviation δ'(see FIG. 2), integral control term αi for lateral position deviation δ (see FIG. 2) with respect to the target path of the own vehicle, yaw angle deviation θy with respect to the target path of the own vehicle (see FIG. 2) It is a steering angle including the proportional control term αy with respect to and the differential control term αr of the yaw angle deviation θy with respect to the target path of the own vehicle, and as shown in the following equation (5), these control terms αp, αi, αy, αr. Is set as the total steering angle.
αp ＝ Gp ・ δ'… (4-1)
αi ＝ Gi ・ ∫δdt… (4-2)
αy ＝ Gy ・ θy… (4-3)
αr = Gr · dθy / dt… (4-4)
αfb ＝ αp ＋ αi ＋ αy ＋ αr
= Gp ・ δ'+ Gi ・ ∫δdt + Gy ・ θy ＋ Gr ・ dθy / dt… (5)
However, Gp: proportional gain with respect to lateral position deviation
Gi: Integral gain for lateral deviation
Gy: Proportional gain for yaw angle deviation
Gr: Derivative gain for yaw angle deviation

Here, the proportional control term αp shown in the equation (4-1) is a control term for making the deviation 0 in proportion to the deviation of the lateral position between the target route and the own vehicle. This proportional control term αp is calculated by multiplying the lateral position deviation δ'by the proportional gain Gp.

The lateral position deviation δ'is estimated (or detected by a sensor) from the vehicle speed, the stability factor peculiar to the vehicle, the wheelbase, the steering gear ratio, etc., of the lateral position of the own vehicle at a predetermined distance when traveling at the current steering angle. It can be calculated from the yaw rate of the own vehicle) and obtained as the deviation between the estimated lateral position of the own vehicle and the lateral position of the target route ahead. The horizontal position of the target route can be obtained by applying the value of the coefficient C, for example, when the target route is approximated by the quadratic equation shown in the equation (1).

The proportional control term αp may be a control term proportional to the lateral position deviation δ with respect to the current target route of the own vehicle according to conditions such as the type of the tracking target and the traveling speed, and the lateral position deviation δ. It may be a control term including both a proportional control amount and a control amount proportional to the lateral position deviation δ'.

The integral control term αi shown in Eq. (4-2) is different from the target value due to the deviation that constantly occurs between the output of proportional control and the target value, and the disturbance such as crosswind or cross slope (cant) of the road surface. It compensates for the deviation that occurs between them, and prevents the own vehicle from traveling at an offset with respect to the target route. This integral control term αi is calculated by multiplying the integral value obtained by integrating the lateral position deviation δ by a predetermined integral gain Gi.

The proportional control term αy shown in Eq. (4-3) is a control term for feedback-controlling the yaw angle of the own vehicle to the yaw angle along the target path, and is obtained by multiplying the yaw angle deviation θy by the proportional gain Gy. Calculated. The yaw angle deviation θy can be obtained by applying the value of the coefficient B, for example, when the target path is approximated by the quadratic equation shown in Eq. (1). Further, the differential control term αr shown in Eq. (4-4) is a control term for converging the yaw angle of the own vehicle to the yaw angle along the target path with good responsiveness, and the differential gain Gr is set to the yaw angle deviation θy. Is calculated by multiplying.

The disturbance prediction unit 103 determines the state of disturbance in front of the own vehicle due to crosswinds, road ruts, etc., based on changes in the behavior of other vehicles in front of the own vehicle, such as a preceding vehicle traveling in front of the own vehicle and an oncoming vehicle traveling in the oncoming lane. Estimate and predict the disturbance that will be added to your vehicle. As a change in the behavior of the preceding vehicle or the oncoming vehicle, the amount of change in the lateral position in the lane width direction is detected.

The lateral position of the preceding vehicle or the oncoming vehicle can be calculated based on the image captured by the camera unit 11 as well as the lateral position of the own vehicle with respect to the target route, and is calculated as, for example, a deviation from the center position of the lane. Then, the deviation of the preceding vehicle or the oncoming vehicle with respect to the center position of the lane is sampled over a predetermined time, and the amount of change in the lateral position with respect to the average value of the obtained time series data is calculated as the amount of lateral position variation.

In the disturbance prediction unit 103, the lateral position fluctuation amount of the other vehicle in front deviates from the lateral position fluctuation amount of the own vehicle by more than a predetermined set value, and the lateral position fluctuation amount of the other vehicle sets a predetermined threshold value. If it exceeds the limit, it is judged that a sudden disturbance due to a crosswind or a rut on the road has occurred in front of the vehicle. Then, it predicts that a disturbance will suddenly act on the own vehicle when the own vehicle passes the corresponding position after a predetermined time, and outputs an instruction to correct the control gain of the target steering angle αref to the follow-up control gain correction unit 104. ..

Here, as shown in FIG. 3, a disturbance caused by a crosswind W that blows through between adjacent buildings D1 and D2 along the road RD at predetermined intervals will be described as an example. FIG. 3 illustrates a situation in which an oncoming vehicle is not detected in the oncoming lane P2 adjacent to the traveling lane P1 of the own vehicle CR1 and only the preceding vehicle CR2 is detected in front of the own vehicle CR1 in the traveling lane P1.

In such a situation, when the preceding vehicle CR2 passes between the side of the building D1 and the building D2, it staggers due to the crosswind W and the lateral position in the lane fluctuates. As shown in FIG. 4, the lateral position fluctuation amount Δδ2 of the preceding vehicle CR2 becomes maximum in the time zone when passing between the building D1 and the building D2, and then converges toward the original lateral position. go.

Therefore, the disturbance prediction unit 103 monitors the lateral position fluctuation amount Δδ2 of the preceding vehicle CR2 and compares it with the lateral position fluctuation amount of the own vehicle to estimate the state of the disturbance that suddenly occurs in front of the own vehicle. It is possible to predict the disturbance acting on the own vehicle after a predetermined time. Even if there is a road rut in front of the own vehicle, it is possible to estimate the occurrence of disturbance by the lateral position change of the preceding vehicle CR2, but the lateral position change due to the road rut is the lateral position change due to the crosswind. The time it fluctuates is relatively long.

Further, in FIG. 5, the preceding vehicle CR2 is detected in the traveling lane P1, the oncoming vehicle CR3 is detected in the oncoming lane P2, and the preceding vehicle CR2 and the oncoming vehicle CR3 are detected in the building D1 and the building D2 at about the same time. It shows a situation that passes between and. In FIG. 5, since the crosswind W is blown from the side of the oncoming vehicle, the preceding vehicle CR2 and the oncoming vehicle CR3 are simultaneously affected by the crosswind W, and the lateral positions change in the same direction.

In this case, as shown in FIG. 6, the lateral position fluctuation amount Δδ2 of the preceding vehicle CR2 is slightly smaller than the lateral position fluctuation amount Δδ3 of the oncoming vehicle CR3, but the same behavior change occurs at about the same time. Therefore, the disturbance prediction unit 103 can predict that the preceding vehicle CR2 and the oncoming vehicle CR3 are subject to disturbance due to crosswinds or the like from the same direction, and that the disturbance also acts on the own vehicle at a predetermined forward position. Moreover, since the disturbance is determined from the behavior change of both the preceding vehicle and the oncoming vehicle as compared with the case of only the preceding vehicle, the disturbance can be predicted with higher reliability.

If the lateral position of the preceding vehicle and the oncoming vehicle change in different directions, or if the lateral position of the oncoming vehicle does not change even if the lateral position of the preceding vehicle changes, a disturbance other than the crosswind, for example, the own vehicle It can be inferred that the disturbance is caused by ruts on the road on the side of the driving lane. In addition, the lateral position of the preceding vehicle does not change, and if the lateral position of the oncoming vehicle fluctuates, factors such as the positional relationship between the preceding vehicle and the oncoming vehicle, the direction of fluctuation, and the driving environment in front of the own vehicle are taken into consideration. It is possible to determine whether or not the disturbance affects the running of the own vehicle.

On the other hand, as shown in FIG. 7, the preceding vehicle CR2 is detected in the traveling lane P1 and the oncoming vehicle CR3 is detected in the oncoming lane P2, but the building D3 is continuously arranged on the side of the road RD. When the crosswind W does not occur from the gap between the building D1 and the building D2, neither the preceding vehicle CR2 nor the oncoming vehicle CR3 sways unless there is a particular abnormality. That is, as shown in FIG. 8, the lateral position fluctuation amount Δδ2 of the preceding vehicle CR2 and the lateral position fluctuation amount Δδ3 of the oncoming vehicle CR3 are within the range of normal traveling, although there are some fluctuations.

In this way, the disturbance prediction unit 103 can determine whether it is a driver operation of any vehicle or a disturbance such as a crosswind by monitoring a change in the behavior of another vehicle in front of the own vehicle such as a preceding vehicle or an oncoming vehicle. .. In the present embodiment, when the lateral position fluctuation amount of the other vehicle deviates from the lateral position fluctuation amount of the own vehicle by a set value or more and exceeds a predetermined threshold value, the disturbance prediction unit 103 runs in front of the own vehicle. It is judged that a disturbance that affects the is occurring. Then, in order to deal with the disturbance in front of the own vehicle, an instruction for correcting the control gain of the target steering angle αref is output to the follow-up control gain correction unit 104.

In this case, if it is determined from the recognition result of the driving environment outside the own vehicle by the external environment recognition device 10 and the amount of lateral position fluctuation of the other vehicle that the disturbance is caused by ruts due to snowfall or the like, the disturbance due to the crosswind As shown above, the control gain of the target steering angle αref is not corrected in the direction of strengthening the followability to the target path, but is corrected in the direction of weakening the followability to the target path. As a result, it is possible to avoid interference with the ruts and run the own vehicle following the ruts.

In the present embodiment, the threshold value of the disturbance determination for the lateral position fluctuation amount is set according to the height of the recognized vehicle, for example, the threshold value δH of the disturbance determination for the vehicle having a high vehicle height and the vehicle having a low vehicle height. It is set in two stages with the threshold value δL for determining the disturbance. Normally, the taller the vehicle, the more susceptible it is to disturbances, so set δH> δL. The height of the vehicle may be divided into two stages, H, which is higher than the set value, and L, which is lower than the set value. However, by comparing the relative height with the own vehicle, H (high) and L ( It may be divided into (low) and.

The follow-up control gain correction unit 104 corrects the control gain of the target steering angle αref when the disturbance prediction unit 103 predicts that the disturbance will be applied to the own vehicle after a predetermined time and is instructed to correct the control gain of the target steering angle αref. do. In the present embodiment, the gain Gff of the feedforward control with respect to the curvature of the target path is corrected as the control gain of the target steering angle αref. Therefore, the follow-up control gain correction unit 104 sets the correction coefficient Dh in the above equation (3) to Dh> 1.0 or Dh <1.0 and outputs it to the target steering angle setting unit 102 to set the map. Correct the gain Gff.

In the present embodiment, the gain Gff at the steering angle αff of the feedforward control is corrected as the control gain of the target steering angle αref, but the gains Gp, Gi, Gy at the steering angle αfb of the feedback control are corrected. Gr may also be corrected as appropriate. For example, the gain Gff of the feedforward control may be corrected, and the differential gain of the yaw angle deviation θy with respect to the target path may be corrected in advance to adjust the follow-up response to the target path at the time of disturbance.

The control unit 105 calculates the deviation Δα (Δα = αref−αr) between the target steering angle αref set by the target steering angle setting unit 102 and the actual steering angle αr detected by the steering angle sensor or the like, and calculates the following (6-−). As shown in the equations 1), (6-2), and (6-3), the proportional control steering torque Tp, the differential control steering torque Td, and the integral control steering torque Ti are calculated.
Tp = Kp · Δα… (6-1)
Td = Kd · dΔα / dt… (6-2)
Ti ＝ Ki ・ ∫Δαdt… (6-3)

Then, as shown in the following equation (7), these steering torques Tp, Td, and Ti are added up, and the target for matching the actual steering angle αr with the target steering angle αref by feedback control based on the steering angle deviation Δα. Calculate the steering torque Tfb. This target steering torque Tfb is output to the steering control device 70 and executed as current control of the electric power steering motor. If there is no override by the driver's steering wheel operation, the proportional gain Kp optimally set in advance by experiments or simulations is performed. , The differential gain Kd, and the integrated gain Ki control the drive current of the electric power steering motor by PID control.
Tfb = Tp + Ti + Td
= Kp ・ Δα ＋ Kd ・ dΔα / dt ＋ Ki ・ ∫Δαdt… (7)

At this time, if it is predicted that a disturbance will act on the own vehicle at a predetermined forward position based on the fluctuation of the traveling state of both or one of the preceding vehicle and the oncoming vehicle, the target steering is performed before reaching the corresponding position. Since the control gain of the angle αref is corrected in advance, it is possible to reduce the influence on the vehicle behavior when a disturbance is actually applied, and it is possible to realize stable driving.

Next, the running control program processing by each of the above functional units will be described with reference to the flowcharts shown in FIGS. 9 and 10. The travel control process shown in the flowchart of FIG. 9 is the main process of travel control, and the target steering angle setting process shown in the flowchart of FIG. 10 is a sub-process in the travel control process.

The travel control device 100 reads the recognition result of the external environment by the external environment recognition device 10 in the first step S1 of the main process of the travel control, and whether or not there is a preceding vehicle in front of the own vehicle (whether or not it is detected). ). Then, when there is no preceding vehicle, the process proceeds to the process after step S2, and when there is a preceding vehicle, the process proceeds to the process after step S10.

In the case of no preceding vehicle, in step S2, it is further investigated whether or not there is an oncoming vehicle, and in the case of no oncoming vehicle, a mode (including a mode without correction) for correcting the control gain of the target steering angle is set in step S3. Set the indicated flag FLG. The flag FLG stores the presence / absence of the preceding vehicle, the height of the preceding vehicle, the presence / absence of the oncoming vehicle, and the height of the oncoming vehicle for each bit of the bit field, for example.

After the flag FLG is set without the preceding vehicle and the oncoming vehicle in step S3, the process proceeds to step S4 to execute the target steering angle setting process shown in FIG. 10 as a sub-process to determine the target steering angle αref. Next, the process proceeds from step S4 to step S20, and steering control is performed via the steering control device 70 so that the actual steering angle αr matches the target steering angle αref. By this steering control, the electric power steering motor is driven by the target steering torque Tfb that makes the actual steering angle αr match the target steering angle αref.

Here, the sub-processing for setting the target steering angle in FIG. 10 will be described. In the first step S101 of the target steering angle setting process, the travel control device 100 refers to the value of the flag FLG, reads information relating to the presence / absence of the preceding vehicle, the presence / absence of the oncoming vehicle, and the height of the vehicle, and faces the preceding vehicle. Check if at least one of the vehicles is detected. If neither the preceding vehicle nor the oncoming vehicle is detected, the process proceeds from step S101 to step S106 so that the control gain of the target steering angle is not corrected, and the target steering angle αref is set in step S107.

In the sub-process of setting the target steering angle executed in step S4 of the travel control process, neither the preceding vehicle nor the oncoming vehicle is detected, so that the normal target steering angle αref corresponding to the disturbance detected from the behavior of the own vehicle is obtained. It will be set. The control gain at this time is set to no gain correction because the correction coefficient Dh in the above equation (3) is set to Dh = 1.0 in the follow-up control gain correction unit 104.

Then, in the target steering angle setting unit 102, the target steering is performed by the steering angle αff of the feedforward control by the gain Gff of the map setting according to the curvature κ of the target path and the steering angle αfb of the feedback control represented by the equation (5). The angle αref is set. In the steering control by the target steering angle αref, the disturbance due to the current crosswind and the cross slope (cant) of the road surface is compensated by the integral control term αi at the steering angle αfb.

On the other hand, if both or one of the preceding vehicle and the oncoming vehicle is detected in step S101, the process proceeds from step S101 to step S102, and the amount of lateral position fluctuation of the corresponding vehicle in the X-axis direction (lane width direction). To calculate. Further, in step S103, the threshold value for determining the disturbance with respect to the lateral position fluctuation amount of the corresponding vehicle is set according to the height of the corresponding vehicle. As described above, in the present embodiment, the threshold value δH is set when the vehicle height is high, and the threshold value δL is set when the vehicle height is low (δH> δL).

Then, in step S104, it is checked whether or not the amount of lateral position fluctuation is equal to or greater than the threshold value. When the lateral position fluctuation amount is less than the threshold value, it is determined that there is no particular disturbance in front of the own vehicle, and the control gain of the target steering angle is not corrected by proceeding from step S104 to the above-mentioned step S106, and in the above-mentioned step S107. Set the normal target steering angle αref. On the other hand, when the lateral position fluctuation amount is equal to or more than the threshold value, the process proceeds from step S104 to step S105, the correction amount of the control gain of the target steering angle corresponding to the disturbance in front of the own vehicle is set, and the disturbance in front is changed in step S107. The target steering angle αref is set with the control gain corrected in preparation.

Next, returning to the main process of the traveling control, if there is an oncoming vehicle in step S2, the process proceeds from step S2 to step S5, and the vehicle height of the oncoming vehicle is compared with the set value to check whether it is H (high) or not. .. When the vehicle height of the oncoming vehicle is H, in step S6, the flag FLG is set to the vehicle height H (high) of the oncoming vehicle with no preceding vehicle and the oncoming vehicle, and the vehicle height of the oncoming vehicle is L (low). In the case of, in step S7, the flag FLG is set to the vehicle height L (low) of the oncoming vehicle without the preceding vehicle and with the oncoming vehicle.

After that, the process proceeds to step S8, the state of disturbance is detected from the relative behavior of the oncoming vehicle with respect to the own vehicle, the target steering angle αref is set by the sub-processing of the target steering angle setting in FIG. conduct. For example, when the own vehicle and the oncoming vehicle in front of the own vehicle cause lateral position fluctuation in the same direction, and the lateral position fluctuation amount of the oncoming vehicle and the lateral position fluctuation amount of the own vehicle are less than the set value, a crosswind or the like. Assuming that the disturbance of is continuously generated from the current position to the front position, steering control is performed at the target steering angle according to the current disturbance without correcting the control gain especially in preparation for a sudden disturbance in the front. implement.

On the other hand, when the lateral position fluctuation amount of the oncoming vehicle and the lateral position fluctuation amount of the own vehicle deviate from each other by the set value or more and are equal to or more than the threshold value for disturbance determination (threshold value δH or δL), the disturbance occurs. It judges that it will suddenly join the own vehicle at the front position and corrects the control gain of the target steering angle to prepare for sudden disturbance at the front position. When the target steering angle αref at this time is determined to be a disturbance due to a crosswind, the correction coefficient Dh in the above equation (3) is set to Dh> 1.0, and the gain Gff of the feedforward control is set to a target higher than usual. Correct in the direction of strengthening the followability to the route. If it is determined that the disturbance is caused by a rut on the road, the correction coefficient Dh is set to Dh <1.0, and the gain Gff of the feedforward control is corrected in a direction that greatly weakens the followability to the target route. , Enables driving that follows ruts.

On the other hand, if there is a preceding vehicle in the first step S1, the process proceeds from step S1 to step S10, and the vehicle height of the preceding vehicle is compared with the set value to check whether or not it is H (high). Then, when the vehicle height of the preceding vehicle is H, in step S11, the flag FLG is set to the vehicle height H (high) of the preceding vehicle with the preceding vehicle, and the process proceeds to step S13. When the vehicle height of the preceding vehicle is L (low), the flag FLG is set to the vehicle height L (low) of the preceding vehicle with the preceding vehicle in step S12, and the process proceeds to step S13.

In step S13, it is checked whether or not there is an oncoming vehicle, and if there is no oncoming vehicle, the process proceeds to step S14, and the flag FLG is added with the information that there is no oncoming vehicle, and the process proceeds to step S15. In step S15, the disturbance is detected from the relative behavior of the preceding vehicle with respect to the own vehicle, the target steering angle αref is set by the sub-processing of the target steering angle setting in FIG. 10, and the steering control is performed in step S20. Since the target steering angle αref at this time is a mode in which there is a preceding vehicle and there is no oncoming vehicle, the disturbance in front of the own vehicle is predicted only from the relative behavior of the preceding vehicle with respect to the own vehicle, and the vehicle is suddenly in front of the own vehicle. When it is predicted that a disturbance will be applied, the gain Gff of the feedforward control at the target steering angle is corrected by the correction coefficient Dh as in step S8 described above.

On the other hand, in step S13, when there is an oncoming vehicle, the process proceeds from step S13 to step S16, and the vehicle height of the oncoming vehicle is compared with the set value to check whether or not it is H (high). When the vehicle height of the oncoming vehicle is H, in step S17, the flag FLG is set to the vehicle height H or L of the preceding vehicle, the vehicle height H or L of the preceding vehicle, the vehicle height H of the oncoming vehicle, and the vehicle of the oncoming vehicle. When the height is L, in step S18, the flag FLG is set to the vehicle height H or L of the preceding vehicle, the vehicle height L of the oncoming vehicle, and the vehicle height L of the preceding vehicle.

After setting the flag FLG in step S17 or step S18, the process proceeds to step S19 to detect disturbance from the relative behavior of the preceding vehicle and the oncoming vehicle with respect to the own vehicle, and by the sub-processing of setting the target steering angle in FIG. Set the target steering angle αref. Then, the process proceeds from step S19 to step S20 to perform steering control.

Since the target steering angle αref in step S19 is a mode in which both the preceding vehicle and the preceding vehicle are present, the state of disturbance can be compared with the mode of only the oncoming vehicle in step S8 or the mode of only the preceding vehicle in step S15. It is possible to judge with higher reliability. Therefore, when the gain Gff of the feedforward control is corrected in step S19, the correction amount of the gain Gff can be made larger than that of steps S8 and S15.

For example, a sudden disturbance due to a crosswind is predicted from the lateral position fluctuation amount of either the preceding vehicle or the oncoming vehicle, and the preceding vehicle is compared with the case where the gain Gff of the feedforward control is corrected with Dh = 1.1. When a sudden disturbance due to a crosswind is predicted from the amount of lateral position fluctuation of both the vehicle and the oncoming vehicle, Dh = 1.2 and the gain Gff of the feedforward control is set so that the followability to the target path becomes stronger. To correct.

As described above, in the present embodiment, the state of the disturbance occurring in front of the own vehicle is determined from the behavior change of the other vehicle in front of the own vehicle, and the disturbance applied to the vehicle is predicted. Then, when a disturbance to the own vehicle is predicted, the control gain of the steering amount that causes the traveling locus of the own vehicle to follow the target path is corrected, and the traveling state of the own vehicle is adjusted in advance in preparation for the disturbance. As a result, it is possible to mitigate the influence when a disturbance is actually applied to the own vehicle and maintain stable and smooth running, and it is possible to give the driver a comfortable driving feeling.

1 Travel control system 10 External environment recognition device 70 Steering control device 100 Travel control device 101 Target route generation unit 102 Target steering angle setting unit 103 Disturbance prediction unit 104 Follow-up control gain correction unit 105 Control unit αref Target steering angle Gff Feedforward control Gain Dh correction coefficient

Claims (5)

A vehicle travel control device that generates a target route on which the own vehicle travels and controls follow-up travel to the target route.
The change in the behavior of the other vehicle in front of the own vehicle is calculated as the amount of change in the lateral position with respect to the center position of the lane of the other vehicle with respect to the average value of the predetermined time, and the own vehicle is calculated based on the amount of the lateral position fluctuation. The disturbance prediction unit that predicts the disturbance that will be added to
When the disturbance prediction unit predicts that a disturbance will be applied to the own vehicle, the control gain of the target steering angle that causes the traveling locus of the own vehicle to follow the target path is set to the control gain of the target path before the disturbance acts on the own vehicle. A follow-up control gain correction unit that corrects with the feed-forward control gain for the curvature,
A vehicle travel control device comprising. The traveling of the vehicle according to claim 1, wherein the other vehicle includes not only a preceding vehicle traveling in the same direction in front of the own vehicle but also an oncoming vehicle traveling from the front of the own vehicle toward the own vehicle. Control device. The vehicle travel control according to claim 2 , wherein the disturbance prediction unit predicts a disturbance applied to the own vehicle based on the lateral position fluctuation amount of at least one of the preceding vehicle and the oncoming vehicle. Device. Any one of claims 1 to 3, wherein the disturbance prediction unit sets a threshold value for determining a disturbance with respect to the lateral position fluctuation amount according to the vehicle height of the other vehicle in front of the own vehicle. The vehicle travel control device according to. Any one of claims 1 to 4, wherein the follow-up control gain correction unit corrects the control gain of the target steering angle in a direction that enhances the followability of the own vehicle to the target path. The vehicle travel control device according to.

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