U.S. patent application number 16/943100 was filed with the patent office on 2021-02-11 for driving support apparatus, control method of vehicle, and non-transitory computer-readable storage medium.
The applicant listed for this patent is HONDA MOTOR CO., LTD.. Invention is credited to Yuji YASUI.
Application Number | 20210039638 16/943100 |
Document ID | / |
Family ID | 1000005020298 |
Filed Date | 2021-02-11 |
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United States Patent
Application |
20210039638 |
Kind Code |
A1 |
YASUI; Yuji |
February 11, 2021 |
DRIVING SUPPORT APPARATUS, CONTROL METHOD OF VEHICLE, AND
NON-TRANSITORY COMPUTER-READABLE STORAGE MEDIUM
Abstract
A driving support apparatus in a vehicle, includes: an
information acquisition unit configured to acquire peripheral
information of the vehicle; a risk prediction unit configured to
predict a risk region on the periphery of the vehicle using the
peripheral information; a sight line specifying unit configured to
specify a position of a sight line of a driver of the vehicle in
the peripheral information; and a control unit configured to switch
driving support control based on a degree of deviation between the
risk region predicted by the risk prediction unit and the position
of the sight line specified by the sight line specifying unit.
Inventors: |
YASUI; Yuji; (Wako-shi,
JP) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
HONDA MOTOR CO., LTD. |
Tokyo |
|
JP |
|
|
Family ID: |
1000005020298 |
Appl. No.: |
16/943100 |
Filed: |
July 30, 2020 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
B60W 40/08 20130101;
B60W 50/14 20130101; B60W 2050/146 20130101; B60W 2556/10 20200201;
B60W 30/095 20130101; B60W 2540/225 20200201 |
International
Class: |
B60W 30/095 20060101
B60W030/095; B60W 40/08 20060101 B60W040/08; B60W 50/14 20060101
B60W050/14 |
Foreign Application Data
Date |
Code |
Application Number |
Aug 8, 2019 |
JP |
2019-146795 |
Claims
1. A driving support apparatus in a vehicle, comprising: an
information acquisition unit configured to acquire peripheral
information of the vehicle; a risk prediction unit configured to
predict a risk region on the periphery of the vehicle using the
peripheral information; a sight line specifying unit configured to
specify a position of a sight line of a driver of the vehicle in
the peripheral information; and a control unit configured to switch
driving support control based on a degree of deviation between the
risk region predicted by the risk prediction unit and the position
of the sight line specified by the sight line specifying unit.
2. The apparatus according to claim 1, further comprising an
estimation unit configured to estimate the position of the sight
line in the peripheral information using a learned model learned
using data of the position of the sight line of the driver having a
specific attribute at the time of driving, wherein the control unit
further switches the driving support control based on the degree of
deviation between the position of the sight line estimated by the
estimation unit and the position of the sight line specified by the
sight line specifying unit.
3. The apparatus according to claim 1, wherein the control unit
switches contents of a notification to the driver based on the
degree of deviation.
4. The apparatus according to claim 3, wherein switching of the
contents of the notification includes change of one of a volume, a
notification timing, an utterance speed, and a tone.
5. The apparatus according to claim 3, wherein switching of the
contents of the notification includes change of words for directly
notifying contents of a risk and words for indirectly notifying the
contents of the risk.
6. The apparatus according to claim 3, wherein the contents of the
notification include words used to guide the sight line of the
driver to the risk region.
7. The apparatus according to claim 1, wherein the control unit
switches a threshold for a control parameter of the driving support
control based on the degree of deviation.
8. The apparatus according to claim 1, further comprising a
decision unit configured to decide a threshold for the degree of
deviation in accordance with information of the driver, wherein the
control unit switches the driving support control using the
threshold decided by the decision unit.
9. The apparatus according to claim 8, wherein the information of
the driver includes one of an operation mode of the vehicle set by
the driver, a driving history of the driver, and attribute
information of the driver.
10. The apparatus according to claim 1, further comprising a unit
configured to predict, using the peripheral information of the
vehicle, a collision possibility between the vehicle and a target
represented by the peripheral information, wherein the control unit
switches the driving support control in accordance with the
predicted collision possibility.
11. The apparatus according to claim 10, wherein if the predicted
collision possibility exceeds a predetermined threshold, the
control unit operates a collision safety device before
collision.
12. A control method of a vehicle, comprising: acquiring peripheral
information of the vehicle; predicting a risk region on the
periphery of the vehicle using the peripheral information;
specifying a position of a sight line of a driver of the vehicle in
the peripheral information; and switching driving support control
based on a degree of deviation between the risk region predicted in
the predicting and the position of the sight line specified in the
specifying.
13. A non-transitory computer-readable storage medium storing a
program configured to cause a computer mounted in a vehicle to
function as: an information acquisition unit configured to acquire
peripheral information of the vehicle; a risk prediction unit
configured to predict a risk region on the periphery of the vehicle
using the peripheral information; a sight line specifying unit
configured to specify a position of a sight line of a driver of the
vehicle in the peripheral information; and a control unit
configured to switch driving support control based on a degree of
deviation between the risk region predicted by the risk prediction
unit and the position of the sight line specified by the sight line
specifying unit.
Description
CROSS-REFERENCE TO RELATED APPLICATION(S)
[0001] This application claims priority to and the benefit of
Japanese Patent Application No. 2019-146795 filed on Aug. 8, 2019,
the entire disclosure of which is incorporated herein by
reference.
BACKGROUND OF THE INVENTION
Field of the Invention
[0002] The present invention relates to a control technique of a
vehicle.
Description of the Related Art
[0003] In driving support control of a vehicle, there is known
control of automatically executing various traveling functions. For
example, it is known to perform appropriate driving support or a
notification to a driver in accordance with the state of the
driver.
[0004] Japanese Patent Laid-Open No. 2008-168845 describes
appropriately notifying a steering state in accordance with the
steering situation of wheels by a driver when parking/stopping a
vehicle. Japanese Patent Laid-Open No. 2018-97398 describes
detecting the sight line of a driver and estimating a feature of
the detected sight line.
[0005] On the vehicle side, when providing driving support control,
some drivers want to avoid excessive notifications and driving
support.
SUMMARY OF THE INVENTION
[0006] It is an object of the present invention to perform
appropriate driving support control for a driver in consideration
of the sight line of the driver and the peripheral environment of a
road during traveling.
[0007] According to an aspect of the present invention, there is
provided a driving support apparatus in a vehicle, comprising: an
information acquisition unit configured to acquire peripheral
information of the vehicle; a risk prediction unit configured to
predict a risk region on the periphery of the vehicle using the
peripheral information; a sight line specifying unit configured to
specify a position of a sight line of a driver of the vehicle in
the peripheral information; and a control unit configured to switch
driving support control based on a degree of deviation between the
risk region predicted by the risk prediction unit and the position
of the sight line specified by the sight line specifying unit.
[0008] Further features of the present invention will become
apparent from the following description of exemplary embodiments
(with reference to the attached drawings).
BRIEF DESCRIPTION OF THE DRAWINGS
[0009] FIG. 1 is a block diagram of a vehicle control apparatus
according to an embodiment of the present invention;
[0010] FIGS. 2A to 2C are views for explaining potential risk
prediction according to an embodiment of the present invention;
[0011] FIGS. 3A and 3B are views for explaining estimation of a
gazing point of a skilled driver according to an embodiment of the
present invention;
[0012] FIGS. 4A and 4B are views for explaining specifying of the
sight line of a driver according to an embodiment of the present
invention;
[0013] FIGS. 5A and 5B are views for explaining comparison
processing according to an embodiment of the present invention;
[0014] FIG. 6 is a flowchart of processing according to the first
embodiment of the present invention;
[0015] FIGS. 7A to 7C are views for explaining examples of direct
guidance and indirect guidance according to an embodiment of the
present invention;
[0016] FIGS. 8A to 8C are views for explaining examples of direct
guidance and indirect guidance according to an embodiment of the
present invention;
[0017] FIGS. 9A to 9C are views for explaining examples of direct
guidance and indirect guidance according to an embodiment of the
present invention;
[0018] FIG. 10 is a flowchart of processing according to the second
embodiment of the present invention; and
[0019] FIG. 11 is a flowchart of threshold setting processing
according to the third embodiment of the present invention.
DESCRIPTION OF THE EMBODIMENTS
[0020] Hereinafter, embodiments will be described in detail with
reference to the attached drawings. Note that the following
embodiments are not intended to limit the scope of the claimed
invention, and limitation is not made an invention that requires
all combinations of features described in the embodiments. Two or
more of the multiple features described in the embodiments may be
combined as appropriate. Furthermore, the same reference numerals
are given to the same or similar configurations, and redundant
description thereof is omitted.
First Embodiment
[0021] [Vehicle Arrangement]
[0022] FIG. 1 is a block diagram of a vehicle control apparatus
according to an embodiment of the present invention and controls a
vehicle 1. FIG. 1 shows the outline of the vehicle 1 by a plan view
and a side view. The vehicle 1 is, for example, a sedan-type
four-wheeled vehicle.
[0023] A vehicle control apparatus of FIG. 1 includes a control
unit 2. The control unit 2 includes a plurality of ECUs 20 to 29
communicably connected by an in-vehicle network. Each ECU includes
a processor represented by a CPU, a storage device such as a
semiconductor memory, an interface with an external device, and the
like. The storage device stores programs to be executed by the
processor, data to be used by the processor for processing, and the
like. Each ECU may include a plurality of processors, storage
devices, and interfaces.
[0024] The functions and the like provided by the ECUs 20 to 29
will be described below. Note that the number of ECUs and the
provided functions can be appropriately designed, and they can be
subdivided or integrated as compared to this embodiment.
[0025] The ECU 20 executes control associated with automated
driving of the vehicle 1. In automated driving, at least one of
steering and acceleration/deceleration of the vehicle 1 is
automatically controlled. Both steering and
acceleration/deceleration are automatically controlled in the
control example to be described later.
[0026] The ECU 21 controls an electric power steering device 3. The
electric power steering device 3 includes a mechanism that steers
front wheels in accordance with a driving operation (steering
operation) of a driver on a steering wheel 31. In addition, the
electric power steering device 3 includes a motor that generates a
driving force to assist the steering operation or automatically
steer the front wheels, and a sensor that detects the steering
angle. If the driving state of the vehicle 1 is automated driving
or driving support, the ECU 21 automatically controls the electric
power steering device 3 in correspondence with an instruction from
the ECU 20 and controls the direction of travel of the vehicle
1.
[0027] The ECUs 22 and 23 perform control of detection units 41 to
43 that detect the peripheral state of the vehicle and information
processing of detection results. Each detection unit 41 is a camera
(to be sometimes referred to as the camera 41 hereinafter) that
captures the front side of the vehicle 1. In this embodiment, the
cameras 41 are attached to the windshield inside the vehicle cabin
at the front of the roof of the vehicle 1. When images captured by
the cameras 41 are analyzed, the contour of a target or a division
line (a white line or the like) of a lane on a road can be
extracted.
[0028] The detection unit 42 is Light Detection and Ranging (LiDAR)
(to be sometimes referred to as the LiDAR 42 hereinafter), and
detects a target around the vehicle 1 or measures the distance to a
target. In this embodiment, five LiDARs 42 are provided; one at
each corner of the front portion of the vehicle 1, one at the
center of the rear portion, and one on each side of the rear
portion. The detection unit 43 is a millimeter wave radar (to be
sometimes referred to as the radar 43 hereinafter), and detects a
target around the vehicle 1 or measures the distance to a target.
In this embodiment, five radars 43 are provided; one at the center
of the front portion of the vehicle 1, one at each corner of the
front portion, and one at each corner of the rear portion.
[0029] The ECU 22 performs control of one camera 41 and each LiDAR
42 and information processing of detection results. The ECU 23
performs control of the other camera 41 and each radar 43 and
information processing of detection results. Since two sets of
devices that detect the peripheral state of the vehicle are
provided, the reliability of detection results can be improved. In
addition, since detection units of different types such as cameras,
LiDARs, and radars are provided, the peripheral environment of the
vehicle can be analyzed multilaterally.
[0030] The ECU 24 performs control of a gyro sensor 5, a GPS sensor
24b, and a communication device 24c and information processing of
detection results or communication results. The gyro sensor 5
detects a rotary motion of the vehicle 1. The course of the vehicle
1 can be determined based on the detection result of the gyro
sensor 5, the wheel speed, or the like. The GPS sensor 24b detects
the current position of the vehicle 1. The communication device 24c
performs wireless communication with a server that provides map
information and traffic information and acquires these pieces of
information. The ECU 24 can access a map information database 24a
formed in the storage device. The ECU 24 searches for a route from
the current position to the destination.
[0031] The ECU 25 includes a communication device 25a for
inter-vehicle communication. The communication device 25a performs
wireless communication with another vehicle on the periphery and
performs information exchange between the vehicles.
[0032] The ECU 26 controls a power plant 6. The power plant 6 is a
mechanism that outputs a driving force to rotate the driving wheels
of the vehicle 1 and includes, for example, an engine and a
transmission. The ECU 26, for example, controls the output of the
engine in correspondence with a driving operation (accelerator
operation or acceleration operation) of the driver detected by an
operation detection sensor 7a provided on an accelerator pedal 7A,
or switches the gear ratio of the transmission based on information
such as a vehicle speed detected by a vehicle speed sensor 7c. If
the driving state of the vehicle 1 is automated driving, the ECU 26
automatically controls the power plant 6 in correspondence with an
instruction from the ECU 20 and controls the
acceleration/deceleration of the vehicle 1.
[0033] The ECU 27 controls lighting devices (headlights,
taillights, and the like) including direction indicators 8 (turn
signals). In the example shown in FIG. 1, the direction indicators
8 are provided in the front portion, door mirrors, and the rear
portion of the vehicle 1.
[0034] The ECU 28 controls an input/output device 9. The
input/output device 9 outputs information to the driver and accepts
input of information from the driver. A voice output device 91
notifies the driver of the information by voice (words). A display
device 92 notifies the driver of information by displaying an
image. The display device 92 is arranged, for example, in front of
the driver's seat and constitutes an instrument panel or the like.
Note that although a voice and display have been exemplified here,
the driver may be notified of information using a vibration or
light. Alternatively, the driver may be notified of information by
a combination of some of the voice, display, vibration, and light.
Furthermore, the combination or the notification form may be
changed in accordance with the level (for example, the degree of
urgency) of information of which the driver is to be notified.
[0035] An input device 93 is a switch group that is arranged at a
position where the driver can perform an operation, is used to
issue an instruction to the vehicle 1, and may also include a voice
input device.
[0036] The ECU 29 controls a brake device 10 and a parking brake
(not shown). The brake device 10 is, for example, a disc brake
device which is provided for each wheel of the vehicle 1 and
decelerates or stops the vehicle 1 by applying a resistance to the
rotation of the wheel. The ECU 29, for example, controls the
operation of the brake device 10 in correspondence with a driving
operation (brake operation) of the driver detected by an operation
detection sensor 7b provided on a brake pedal 7B. If the driving
state of the vehicle 1 is automated driving or driving support, the
ECU 29 automatically controls the brake device 10 in correspondence
with an instruction from the ECU 20 and controls deceleration and
stop of the vehicle 1. The brake device 10 or the parking brake can
also be operated to maintain the stopped state of the vehicle 1. In
addition, if the transmission of the power plant 6 includes a
parking lock mechanism, it can be operated to maintain the stopped
state of the vehicle 1.
[0037] The vehicle 1 further includes an in-vehicle detection unit
50 which detects the state in the vehicle. Here, the in-vehicle
detection unit 50 is formed by a camera serving as an image
capturing unit, a weight sensor, a temperature detection sensor,
and the like, and the type is not particularly limited. Note that
the in-vehicle detection unit 50 may be provided for each seat
provided in the vehicle 1, or may be provided by a single
arrangement so that the whole interior of the vehicle can be
overviewed or monitored.
[0038] [Examples of Control Functions]
[0039] The control functions of the vehicle 1 according to this
embodiment include traveling-associated functions associated with
the control of driving, braking, and steering of the vehicle 1, and
notification functions associated with the notification of
information to the driver.
[0040] Examples of traveling-associated functions are lane
maintenance control, lane departure suppression control (road
departure suppression control), lane change control, preceding
vehicle following control, collision reduction brake control, and
erroneous start suppression control. Examples of the notification
functions are adjacent vehicle notification control and preceding
vehicle start notification control. As a kind of notification
function, a conversation service by a voice with an occupant may be
provided. In this conversation service, voice input from an
occupant (driver or the like) may be recognized, and information
may be provided as a response. Alternatively, the system side may
proactively provide information by a voice.
[0041] Lane maintenance control is one of control processes for the
position of the vehicle with respect to a lane, and makes the
vehicle automatically travel (without depending on the driving
operation of the driver) on the track of travel set on a lane. Lane
departure suppression control is one of control processes for the
position of the vehicle with respect to a lane. A white line or a
median strip is detected, and steering is automatically performed
so the vehicle does not go across the line. The function of the
lane departure suppression control and the function of the lane
maintenance control differ in this manner.
[0042] Lane change control is control of automatically moving the
vehicle from the lane on which the vehicle is traveling to an
adjacent lane. Preceding vehicle following control is control of
automatically following another vehicle traveling in front of the
self-vehicle. Collision reduction brake control is control of
supporting collision avoidance by automatically braking the vehicle
when the possibility of collision with an obstacle in front of the
vehicle increases. Erroneous start suppression control is control
of suppressing an abrupt start by limiting the acceleration of the
vehicle in the stopped state of the vehicle when the acceleration
operation by the driver is a predetermined amount or more.
[0043] Adjacent vehicle notification control is control of
notifying the driver of the presence of another vehicle traveling
on the adjacent lane which is adjacent to the travel lane of the
self-vehicle. The driver is notified of, for example, the presence
of another vehicle traveling on a lateral side or the rear side of
the self-vehicle. Preceding vehicle start notification control is
control of notifying the driver that another vehicle ahead has
started when the self-vehicle and the other vehicle ahead are in a
stopped state. These notifications can be made by the
above-described in-vehicle notification devices.
[0044] The outline of processing according to this embodiment will
be described below. In this embodiment, peripheral information and
the information of the driver are acquired based on information
acquired via the in-vehicle detection unit 50 and various kinds of
detection units provided in the vehicle 1. Then, an appropriate
information notification to the driver is made based on the
acquired information.
[0045] [Potential Risk Prediction]
[0046] The control unit 2 acquires peripheral information of the
vehicle 1 via the various kinds of detection units. FIG. 2A shows
an example of an image on the front side in the traveling
direction, which is acquired by performing image acquisition by the
detection unit (camera 41) in the vehicle 1 during traveling. A
description will be made here assuming that the driver in the
vehicle 1 can also visually recognize the same scene. In the
example to be explained below, the front side in the traveling
direction will be exemplified. However, an image in a lateral
direction or rear direction of the vehicle 1 may also be used. In
place of an image, peripheral information may be acquired by a
LiDAR or a radar.
[0047] The vehicle 1 according to this embodiment predicts a
potential risk on the periphery based on various kinds of
information acquired by the detection units. For example, the image
show in FIG. 2A includes a bicycle 201 and another vehicle 202 as
traffic participants. In this case, the bicycle 201 may travel to
avoid the other vehicle 202, as indicated by an arrow 203. In this
embodiment, as shown in FIG. 2B, the behavior of the bicycle 201 is
predicted, and a region 204 according to the likelihood is
predicted as a region where a potential risk exists. FIG. 2B shows
a region of higher likelihood in a darker color.
[0048] As the method of potential risk prediction here, for
example, a prediction method using a learning model of machine
learning such as deep learning can be applied. In the learning
model here, learning for predicting the motion of a target included
in each image is performed using a plurality of image data (data
set). A detailed description of the learning method will be omitted
here, and it is assumed that a known method can be applied. The
learning method is not particularly limited, and a known method may
be used. Here, as the learning data, continuous image data each
including a target are used. When the learning data is used, a
learned model according to this embodiment is generated. By
applying the learned model to an image acquired in a vehicle under
a certain circumstance, the behavior of a target included in the
image is predicted, and a potential risk is predicted based on the
behavior result. Note that to generate a learned model, a large
load is applied. Hence, the model is generated in advance and held
in a storage unit in the vehicle 1. Additionally, as the traffic
participant detection method or image recognition method used in
potential risk prediction as well, known methods can be applied,
and a detailed description thereof will be omitted here. In
addition, as the peripheral information acquisition unit, if data
obtained by a LiDAR or a radar is used in place of an image, the
above-described learning data is not an image but output data from
the LiDAR or radar.
[0049] FIG. 2C is a conceptual view in a case in which FIGS. 2A and
2B are viewed from the upper side. While the vehicle 1 that is the
self-vehicle is traveling in the advancing direction (arrow 206),
the peripheral situation shown in FIG. 2A is detected. FIG. 2C
shows a case in which the region 204 corresponding to behavior
prediction of the bicycle 201 is superimposed in the advancing
direction. Such a superimposed region is handled as a region of a
high potential risk. Note that although not illustrated in FIGS. 2A
and 2B, a region corresponding to the behavior of the other vehicle
202 may further be predicted, as indicated by a region 205 in FIG.
2C.
[0050] [Estimation of Gazing Point]
[0051] Gazing point estimation based on the operation data of a
skilled driver according to this embodiment will be described next.
FIG. 3A shows the same image as that shown in FIG. 2A. By applying
a learned model generated and held in advance to the image, a
region 301 is estimated by gazing point estimation as shown in FIG.
3B.
[0052] The learned model here is a model obtained by a machine
learning method such as a CNN (Convolutional Neural Network) using
the data of the driving history of a skilled driver. A detailed
description of the learning method will be omitted here, and it is
assumed that a known method can be applied. As the data of the
driving history of the skilled driver, which is used here as
learning data, a pair of an image (a front image of the vehicle or
the like) acquired in the vehicle during traveling by the skilled
driver and the position information of the sight line of the
skilled driver for the image is used. That is, the learned model
according to this embodiment is generated based on various kinds of
targets (including traffic participants such as a vehicle and a
person) located on the periphery of the self-vehicle included in
the image and the position of the sight line of the skilled driver
in a situation in which the presences of the targets are
recognized. When the learned model is applied to an image of the
vehicle in a certain situation, the position of the sight line of
the skilled driver in the image is output. Note that to generate a
learned model, a large load is applied. Hence, the model is
generated in advance and held in a storage unit in the vehicle
1.
[0053] With the above-described processing, the position of the
sight line of the skilled driver in a certain traveling situation
is estimated. The position of the sight line is shown in the region
301. In this embodiment, the region 301 will be described as a
"gazing point". Note that the gazing point is not limited to a
point and may be indicated by a range in which the sight line moves
at a predetermined time interval. Also, in this embodiment, the
driver of data to be used to perform learning will be expressed as
a "skilled driver". However, the attribute is not limited.
[0054] [Specifying of Sight Line of Driver]
[0055] Specifying of the sight line of the driver of the vehicle 1
according to this embodiment will be described next. As described
above, the vehicle 1 further includes the in-vehicle detection unit
50 which detects the state in the vehicle. In this embodiment, a
description will be made assuming that the directions of the sight
line and the face of the driver are detected based on information
such as an image acquired by the in-vehicle detection unit 50, and
a description of other detection processes will be omitted.
[0056] FIG. 4A shows an example of an image of the driver of the
vehicle 1. In the image shown in FIG. 4A, a face region 402 is
detected, and a sight line 401 of the driver is further detected.
Note that the method of detecting the face region 402 or the sight
line direction is not particularly limited, and a known method can
be used. Also, the method is not limited to a method of detecting
the sight line direction from one image or an image in one
direction, and the sight line direction may be specified based on a
plurality of images detected at the same timing by a plurality of
in-vehicle detection units 50.
[0057] Based on the detected sight line direction of the driver,
the position of the sight line of the driver in the peripheral
image is specified. FIG. 4B shows a region 403 in which the
position of the detected sight line of the driver in the image is
specified. The image is the same as that shown in FIG. 3A. Note
that since the sight line of the driver is not always constant, a
range in which the sight line is located at a predetermined time
interval may be used. The method of specifying the sight line
direction and the method of specifying the position of the sight
line in the image are not particularly limited, and a known method
can be used.
[0058] [Processing Procedure]
[0059] The processing procedure of control processing according to
this embodiment will be described with reference to FIG. 6. Each
control process of this processing procedure is cooperatively
performed by various kinds of ECUs and the like provided in the
vehicle 1 as described above. To simplify the description, here,
the main constituent of the processing is assumed to be the control
unit 2 of the vehicle 1. For example, this processing may be
started when the vehicle 1 starts traveling. In addition, this
processing may continuously be repeated during traveling of the
vehicle 1.
[0060] In step S601, the control unit 2 acquires a peripheral image
of the vehicle 1 from the camera 41 that is a detection unit. Here,
an image on the front side of the vehicle 1 in the advancing
direction is acquired.
[0061] In step S602, the control unit 2 detects traffic
participants from the image acquired in step S601. Examples of
traffic participants are a person, another vehicle, and a moving
body, and the types are not particularly limited. In the example of
the image shown in FIG. 2A, the bicycle 201 and the other vehicle
202 are detected. Note that the detection contents here are not
limited to plane information by the image, and the information of
the relative distance or positional relationship between the
self-vehicle and each traffic participant may also be detected.
[0062] In step S603, the control unit 2 performs behavior
prediction for each traffic participant detected in step S602.
Also, based on the result of behavior prediction, the control unit
2 predicts a potential risk on the periphery during traveling and
specifies a region where the risk occurs. More specifically, the
region 204 shown in FIG. 2B is predicted. The behavior prediction
method and the potential risk prediction method are not
particularly limited, and, for example, a known method as a risk
prediction function in the automated driving field can be
applied.
[0063] In step S604, the control unit 2 acquires information
concerning the traveling state of the self-vehicle. Examples of the
information concerning the traveling state are the information of
the traveling speed, the acceleration/deceleration amount, and the
advancing direction (steering angle).
[0064] In step S605, using the region of the potential risk
predicted in step S603 and the information concerning the traveling
state of the self-vehicle acquired in step S604, the control unit 2
determines whether the distance between the region of the potential
risk and the traveling position of the self-vehicle is equal to or
smaller than a predetermined threshold A. For example, as shown in
FIG. 2C, it is determined whether the distance between the vehicle
1 and the region 204 or a region 205 is equal to or smaller than
the threshold A. At this time, the position of the self-vehicle
after a predetermined time may be predicted based on the
information acquired in step S604, and the determination may be
performed based on the prediction result and the positional
relationship with the potential risk region. The threshold A is
determined in advance and held in the storage unit of the vehicle
1. If it is determined that the distance is equal to or smaller
than the threshold A (YES in step S605), the process advances to
step S615. If it is determined that the distance is larger than the
threshold A (NO in step S605), the process advances to step
S606.
[0065] In step S606, using the region of the potential risk
predicted in step S603 and the information concerning the traveling
state of the self-vehicle acquired in step S604, the control unit 2
determines whether the distance between the region of the potential
risk and the traveling position of the self-vehicle is equal to or
larger than a predetermined threshold B. The relationship between
the threshold A and the threshold B is given by threshold
B>threshold A. Like the threshold A, the threshold B is also
determined in advance and held in the storage unit of the vehicle
1. If it is determined that the distance is smaller than the
threshold B (NO in step S606), the process advances to step S607.
If it is determined that the distance is equal to or larger than
the threshold B (YES in step S606), contents to be notified to the
driver do not exist, and the processing procedure is ended.
[0066] In step S607, the control unit 2 applies a learned model
generated in advance to the peripheral image acquired in step S601,
thereby estimating a gazing point by a skilled driver. More
specifically, as the processing result of this step, the region 301
as shown in FIG. 3B is output.
[0067] In step S608, the control unit 2 acquires an image of the
driver of the vehicle 1 by the in-vehicle detection unit 50.
[0068] In step S609, the control unit 2 detects the sight line of
the driver based on the image of the driver acquired in step S608.
As the sight line detection method, a known method can be used, and
the method is not particularly limited. In this step, more
specifically, as shown in FIG. 4A, the face region of the driver is
detected, and the direction of the sight line is detected.
[0069] In step S610, based on the sight line of the driver detected
in step S609, the control unit 2 specifies the position of the
sight line of the driver in the peripheral image acquired in step
S601. The position of the sight line here may be specified as a
range. In this step, more specifically, a region of a sight line
position as indicated by the region 403 in FIG. 4B is
specified.
[0070] In step S611, the control unit 2 determines whether
deviation which is the distance between the gazing point of the
skilled driver estimated in step S607 and the sight line of the
driver specified in step S610 in the embodiment is equal to or
larger than a predetermined threshold C. More specifically, as
shown in FIG. 5B, the distance between the region 301 and the
region 403 is calculated, and the calculated distance and the
threshold C are compared. The distance calculation method here is
not particularly limited, and, for example, the shortest distance
between the edges of the regions may be calculated, or the distance
between the center points of the regions may be calculated. If the
regions overlap, the distance may be handled as "0". The threshold
C is determined in advance and held in the storage unit of the
vehicle 1. If it is determined that the distance is equal to or
larger than the threshold C (YES in step S611), the process
advances to step S614. If it is determined that the distance is
smaller than the threshold C (NO in step S611), the process
advances to step S612.
[0071] In step S612, the control unit 2 determines whether the
deviation which is the distance between the potential risk region
predicted in step S603 and the sight line of the driver specified
in step S610 in the embodiment is equal to or larger than a
predetermined threshold D. More specifically, as shown in FIG. 5A,
the distance between the region 204 and the region 403 is
calculated, and the calculated distance and the threshold D are
compared. The distance calculation method here is not particularly
limited, and, for example, the shortest distance between the edges
of the regions may be calculated. The threshold D is determined in
advance and held in the storage unit of the vehicle 1. If it is
determined that the distance is equal to or larger than the
threshold D (YES in step S612), the process advances to step S614.
If it is determined that the distance is smaller than the threshold
D (NO in step S612), the process advances to step S613.
[0072] In step S613, the control unit 2 makes a notification to the
driver by indirect guidance using a notification unit. A detailed
example of indirect guidance according to this embodiment will be
described later. Then, the processing procedure is ended.
[0073] In step S614, the control unit 2 makes a notification to the
driver by direct guidance using a notification unit. A detailed
example of direct guidance according to this embodiment will be
described later. Then, the processing procedure is ended.
[0074] In step S615, the control unit 2 warns the driver that the
possibility of risk occurrence is high because of the positional
relationship between the self-vehicle and the potential risk region
in the peripheral environment. A detailed example of warning
according to this embodiment will be described later. Then, the
processing procedure is ended.
[0075] Note that although a description will be omitted in FIG. 6,
collision reduction and collision avoidance control may be
performed in parallel. For example, a threshold A1 smaller than the
threshold A is set. If the distance between the self-vehicle and a
target on the periphery is smaller than the threshold A1, it may be
judged that the possibility (collision possibility) of collision
occurrence is high, and collision reduction brake control may be
executed with priority over the warning in step S615. In addition,
if the degree of urgency is high, it may be determined that
collision cannot be avoided, and, for example, control may be
performed to operate a collision safety device (airbag) or the like
before the collision.
[0076] In addition, some of the processes shown in FIG. 6 may be
performed in parallel. For example, the processes (steps S601 to
S604) concerning peripheral information and the processes (steps
S607 to S610) concerning the driver may be performed in
parallel.
[0077] Note that in the above example, an image on the front side
of the vehicle 1 in the advancing direction has been exemplified.
However, the image is not limited to this. For example, an image on
a lateral side of the vehicle at the time of a left turn or a right
turn may be used. Alternatively, an image on a lateral side of the
vehicle or on the rear side of the vehicle in advancing backward
may be used. In place of an image, output data from the LiDAR or
radar may be used.
Notification Examples
[0078] Direct guidance, indirect guidance, and warning according to
this embodiment will be described next using detailed examples.
Here, the guidance specifically aims at promoting to direct the
sight line of the driver in a predetermined direction.
[0079] In the warning according to this embodiment, if it is
determined that, for example, the possibility of occurrence of an
event such as collision between the self-vehicle and a traffic
participant is high to some extent, the driver is warned of it. As
detailed contents, the position of a traffic participant close to
the self-vehicle is directly notified.
[0080] The direct guidance according to this embodiment is
performed if the possibility of occurrence of an event such as
collision between the self-vehicle and a traffic participant is
lower than in a case in which warning is performed, but the driver
is caused to directly recognize the presence of the element (for
example, the traffic participant) of the risk. Here, "direct"
means, for example, specifically showing a position where the
element of the risk exists. In this embodiment, the direct guidance
is performed when the sight line of the driver is apart from the
potential risk region or the region of the gazing point of the
skilled driver by a predetermined distance or more.
[0081] The indirect guidance according to this embodiment is
performed if the possibility of occurrence of an event such as
collision between the self-vehicle and a traffic participant is
lower than in a case in which warning is performed, but the driver
is caused to indirectly recognize the presence of the element (for
example, the traffic participant) of the risk. Here, "indirect"
means, for example, showing an attribute (appearance, age, clothes,
behavior, shape (truck or standard-sized vehicle), color, size, or
the like) associated with the element of the risk or information
concerning a target located on the periphery of the element of the
risk. In this embodiment, the indirect guidance is performed when
the sight line of the driver is located at a position within a
predetermined distance from the potential risk region or the region
of the gazing point of the skilled driver.
[0082] FIGS. 7A to 9C are views for explaining detailed examples of
direct guidance and indirect guidance according to this embodiment.
FIG. 7A shows a situation in which a bicycle predicted to avoid a
parking vehicle exists on the front side of the self-vehicle, as in
the peripheral image shown in FIG. 2A. FIG. 7B shows an example of
a notification made when performing indirect guidance in this
situation. This intends to change the sight line of the driver such
that it includes the bicycle. FIG. 7C shows an example of a
notification made when performing direct guidance. In this case, as
compared to the sight line of the driver in FIG. 7B, the initial
sight line is located at a position apart from the position of the
bicycle.
[0083] FIG. 8A shows a situation in which on the periphery of the
self-vehicle, a bicycle that has traveled on a sidewalk moves to
the lane to avoid a pedestrian on the sidewalk. FIG. 8B shows an
example of a notification made when performing indirect guidance
immediately before the situation. This intends to change the sight
line of the driver such that it is directed to the bicycle as well.
FIG. 8C shows an example of a notification made when performing
direct guidance. In this case, as compared to the sight line of the
driver in FIG. 8B, the initial sight line is located at a position
apart from the position of the bicycle.
[0084] FIG. 9A shows a situation in which stopped vehicles are
lined up due to congested traffic or the like on the lane opposite
to the lane on which the self-vehicle is traveling, and a
pedestrian exists between the stopped vehicles. FIG. 9B shows an
example of a notification made when performing indirect guidance in
this situation. This intends to change the sight line of the driver
such that it includes the stopped vehicle side on the opposite
lane. FIG. 9C shows an example of a notification made when
performing direct guidance. In this case, as compared to the sight
line of the driver in FIG. 9B, the initial sight line is located at
a position apart from the positions of the stopped vehicles on the
opposite lane.
[0085] The above-described notification contents are merely
examples, and are not particularly limited. The notification
contents used in the direct guidance and the indirect guidance may
change in accordance with the situation. For example, in the direct
guidance, the intensity of an utterance may be raised as compared
to the indirect guidance. More specifically, the volume at the time
of a notification may be increased, or the notification timing may
be advanced. In addition, the utterance speed or tone of a
notification message may be changed (the speed of speaking is
increased, the way of speaking is changed, or the like).
[0086] As described above, in this embodiment, the contents to
notify are switched in accordance with the positional relationship
between the position of the sight line of the driver and the
potential risk region or the region of the gazing point of the
skilled driver. This makes it possible to perform appropriate
driving support for the driver in consideration of the sight line
of the driver and the peripheral environment of a road during
traveling. In particular, a notification can be made to a degree
that the driver does not feel that the notification is
excessive.
Second Embodiment
[0087] As the second embodiment of the present invention, an
embodiment in which driving support control according to the
position of the sight line of a driver is performed will be
described, in addition to the arrangement of the first embodiment.
Note that a description of the same parts as in the first
embodiment will be omitted, and only different parts will be
described.
[0088] In the first embodiment, direct guidance and indirect
guidance are switched in accordance with the distance between the
sight line of the driver and the potential risk region or the
region of the gazing point of the skilled driver. In the second
embodiment, an embodiment in which the degree of driving support
control is switched in accordance with the distance will be
described.
[0089] As described above, examples of driving support control are
lane maintenance control, lane departure suppression control (road
departure suppression control), lane change control, preceding
vehicle following control, collision reduction brake control,
erroneous start suppression control, adjacent vehicle notification
control, and preceding vehicle start notification control. Other
examples of driving support control associated with the vehicle
speed are vehicle speed maintenance control and
acceleration/deceleration control.
[0090] In this embodiment, a threshold for a control parameter with
which driving support control can be executed is switched in
accordance with the distance (degree of deviation) between the
sight line of the driver and the potential risk region or the
region of the gazing point of the skilled driver. In other words,
if the sight line of the driver is close to the position of the
gazing point of the skilled driver, the range where the driving
support control can be executed is made large. More specifically,
concerning vehicle speed maintenance control, if the sight line of
the driver is close to the position of the gazing point of the
skilled driver, control is performed to maintain the vehicle speed
at a higher speed.
[0091] [Processing Procedure]
[0092] FIG. 10 explains the processing procedure of control
processing according to this embodiment. Each control process of
this processing procedure is cooperatively performed by various
kinds of ECUs and the like provided in a vehicle 1 as described
above. To simplify the description, here, the main constituent of
the processing is assumed to be a control unit 2 of the vehicle 1.
For example, this processing may be started when the vehicle 1
starts driving support control. In addition, this processing may
continuously be repeated during traveling of the vehicle 1. The
same step numbers as in the processing shown in FIG. 6 described in
the first embodiment denote the same steps, and a description
thereof will be omitted.
[0093] In step S611, the control unit 2 determines whether the
deviation of the distance between the gazing point of the skilled
driver estimated in step S607 and the sight line of the driver
specified in step S610 is equal to or larger than a predetermined
threshold C. If it is determined that the distance is equal to or
larger than the threshold C (YES in step S611), the process
advances to step S1002. If it is determined that the distance is
smaller than the threshold C (NO in step S611), the process
advances to step S612.
[0094] In step S612, the control unit 2 determines whether the
deviation of the distance between the potential risk region
predicted in step S603 and the sight line of the driver specified
in step S610 is equal to or larger than a predetermined threshold
D. If it is determined that the distance is equal to or larger than
the threshold D (YES in step S612), the process advances to step
S1002. If it is determined that the distance is smaller than the
threshold D (NO in step S612), the process advances to step
S1001.
[0095] In step S1001, the control unit 2 sets a threshold X for the
parameter of driving support control. Here, the threshold X is
determined in advance for driving support control that can be
executed by the vehicle 1. Then, the processing procedure is
ended.
[0096] In step S1002, the control unit 2 sets a threshold Y for the
parameter of driving support control. Here, the threshold Y is
determined in advance for driving support control that can be
executed by the vehicle 1. Note that the threshold Y has a
limitation stricter than the threshold X. Then, the processing
procedure is ended.
[0097] Note that the limit value switched as the threshold X or the
threshold Y may not be switched for all driving support control
processes executable by the vehicle 1 and may be switched only for
some driving support control processes.
[0098] As described above, in this embodiment, the contents of
driving support control to be executed are switched in accordance
with the positional relationship between the position of the sight
line of the driver and the potential risk region or the region of
the gazing point of the skilled driver. This makes it possible to
provide appropriate driving support to the driver in consideration
of the sight line of the driver and the peripheral environment of a
road during traveling.
[0099] Note that the arrangement of the first embodiment and the
arrangement of the second embodiment are not exclusive, and both
control processes may be performed.
Third Embodiment
[0100] In the above-described embodiments, a predetermined
threshold is used when determining the distance (degree of
deviation) between the position of the sight line of the driver and
the potential risk region or the region of the gazing point of the
skilled driver. As the third embodiment of the present invention,
an embodiment in which the threshold used when determining the
degree of deviation is switched in accordance with a driver will be
described.
[0101] [Threshold Setting Processing]
[0102] FIG. 11 explains the processing procedure of threshold
setting according to this embodiment. Each control process of this
processing procedure is cooperatively performed by various kinds of
ECUs and the like provided in a vehicle 1 as described above. To
simplify the description, here, the main constituent of the
processing is assumed to be a control unit 2 of the vehicle 1. For
example, this processing may be started when the vehicle 1 starts
traveling.
[0103] In step S1101, the control unit 2 acquires an image of the
driver of the vehicle 1 by the in-vehicle detection unit 50.
[0104] In step S1102, the control unit 2 specifies the driver based
on the image of the driver acquired in step S1101. The specifying
method here is not particularly limited, and, for example, matching
processing with a face image registered in advance may be used.
[0105] In step S1103, the control unit 2 determines whether there
is an operation mode set by the driver specified in step S1102. The
operation mode here is an operation mode provided for driving
support control of the vehicle 1 or the like. The contents of the
operation mode are not particularly limited, and include, for
example, an energy saving mode for suppressing energy consumption
at the time of driving support and a mode in which brake control is
performed such that an occupant can be on board comfortably. Each
operation mode may be set using a display device 92 or the like
provided in the vehicle 1. If a set operation mode exists (YES in
step S1103), the process advances to step S1107. If a set operation
mode does not exist (NO in step S1103), the process advances to
step S1104.
[0106] In step S1104, the control unit 2 determines whether the
information of the driving history of the driver specified in step
S1102 is held. As for the driving history, operation contents are
successively held in a storage device or the like at the time of
driving of the vehicle 1. If a driving history exists (YES in step
S1104), the process advances to step S1109. If a driving history
does not exist (NO in step S1104), the process advances to step
S1105. Note that if the data amount (for example, the traveling
distance) of the driving history is equal to or smaller than a
predetermined amount, or if a predetermined period has elapsed from
the last driving, the driving history may be handled as absent.
[0107] In step S1105, the control unit 2 determines whether the
attribute information of the driver specified in step S1102 is
registered. Examples of the attribute information are the rank of a
license and the age. These pieces of attribute information may be
registered in advance using, for example, the display device 92
provided in the vehicle 1. If the attribute information is
registered (YES in step S1105), the process advances to step S1108.
If the attribute information is not registered (NO in step S1105),
the process advances to step S1106.
[0108] In step S1106, the control unit 2 sets a default value
determined in advance as a threshold to be used to determine the
degree of deviation. Then, the processing procedure is ended.
[0109] In step S1107, the control unit 2 sets a threshold held in
association with the set operation mode as a threshold to be used
to determine the degree of deviation. The threshold corresponding
to the operation mode is determined in advance and held. Then, the
processing procedure is ended.
[0110] In step S1108, the control unit 2 sets a threshold based on
the attribute information as a threshold to be used to determine
the degree of deviation. The threshold based on the attribute
information is determined in advance by a table or the like and
held. Then, the processing procedure is ended.
[0111] In step S1109, the control unit 2 sets a threshold based on
the driving history as a threshold to be used to determine the
degree of deviation. The threshold based on the driving history may
be set in accordance with, for example, an operation history of
acceleration/deceleration (brake/accelerator) or steering control,
or a driving technique determination result using the operation
history. For example, the threshold may be set relatively moderate
for a driver determined as having a driving technique of high
level. Then, the processing procedure is ended.
[0112] Using the threshold set by the above-described processing,
the processing shown in FIG. 6 or 10 is performed. Note that the
order of determination in FIG. 11 is not limited to this, and the
determination order (priority order of determination) may be
changed.
[0113] As described above, according to this embodiment, in
addition to the effects of the first and second embodiments, it is
possible to switch the threshold to be used to determine the degree
of deviation in accordance with the driver.
[0114] <Summary of Embodiment>
1. According to the above-described embodiment, there is provided a
driving support apparatus (for example, 2) in a vehicle (for
example, 1), comprising:
[0115] an information acquisition unit (for example, 2, 41)
configured to acquire peripheral information of the vehicle;
[0116] a risk prediction unit (for example, 2) configured to
predict a risk region on the periphery of the vehicle using the
peripheral information;
[0117] a sight line specifying unit (for example, 2, 50) configured
to specify a position of a sight line of a driver of the vehicle in
the peripheral information; and
[0118] a control unit (for example, 2) configured to switch driving
support control based on a degree of deviation between the risk
region predicted by the risk prediction unit and the position of
the sight line specified by the sight line specifying unit.
[0119] According to this embodiment, it is possible to perform
appropriate driving support for the driver in consideration of the
sight line of the driver and the peripheral environment of a road
during traveling. [0120] 2. In the above-described embodiment, the
apparatus further comprises an estimation unit (for example, 2)
configured to estimate the position of the sight line in the
peripheral information using a learned model learned using data of
the position of the sight line of the driver having a specific
attribute at the time of driving,
[0121] wherein the control unit further switches the driving
support control based on the degree of deviation between the
position of the sight line estimated by the estimation unit and the
position of the sight line specified by the sight line specifying
unit.
[0122] According to this embodiment, it is possible to perform
appropriate driving support control based on the degree of
deviation between the sight line of the driver and the position of
the sight line estimated using the learned model learned using the
data of the position of the sight line of the driver having a
specific attribute at the time of driving. [0123] 3. In the
above-described embodiment, the control unit switches contents of a
notification to the driver based on the degree of deviation.
[0124] According to this embodiment, based on the degree of
deviation of the sight line, it is possible to make a notification
to a degree that the driver does not feel that the notification is
excessive. [0125] 4. In the above-described embodiment, switching
of the contents of the notification includes change of one of a
volume, a notification timing, an utterance speed, and a tone.
[0126] According to this embodiment, it is possible to
appropriately switch the notification contents for the driver.
[0127] 5. In the above-described embodiment, switching of the
contents of the notification includes change of words for directly
notifying contents of a risk and words for indirectly notifying the
contents of the risk.
[0128] According to this embodiment, it is possible to notify the
driver of the contents of a risk by switching to direct or indirect
words. [0129] 6. In the above-described embodiment, the contents of
the notification include words used to guide the sight line of the
driver to the risk region.
[0130] According to this embodiment, it is possible to guide the
sight line of the driver to a more appropriate position. [0131] 7.
In the above-described embodiment, the control unit switches a
threshold for a control parameter of the driving support control
based on the degree of deviation.
[0132] According to this embodiment, it is possible to provide more
appropriate contents of driving support based on the degree of
deviation of the sight line. [0133] 8. In the above-described
embodiment, the apparatus further comprises a decision unit (for
example, 2) configured to decide a threshold for the degree of
deviation in accordance with information of the driver,
[0134] wherein the control unit switches the driving support
control using the threshold decided by the decision unit.
[0135] According to this embodiment, it is possible to control the
threshold for the degree of deviation in accordance with the driver
and provide driving support more suitable for the driver. [0136] 9.
In the above-described embodiment, the information of the driver
includes one of an operation mode of the vehicle set by the driver,
a driving history of the driver, and attribute information of the
driver.
[0137] According to this embodiment, it is possible to switch the
driving support control according to information such as the
attribute of the driver. [0138] 10. In the above-described
embodiment, the apparatus further comprises a unit (for example, 2)
configured to predict, using the peripheral information of the
vehicle, a collision possibility between the vehicle and a target
represented by the peripheral information,
[0139] wherein the control unit switches the driving support
control in accordance with the predicted collision possibility.
[0140] According to this embodiment, it is possible to switch the
driving support control in accordance with the collision
possibility. [0141] 11. In the above-described embodiment, if the
predicted collision possibility exceeds a predetermined threshold,
the control unit operates a collision safety device before
collision.
[0142] According to this embodiment, it is possible to operate the
collision safety device in accordance with the collision
possibility. [0143] 12. According to the above-described
embodiment, there is provided a control method of a vehicle (for
example, 1), comprising:
[0144] acquiring peripheral information of the vehicle;
[0145] predicting a risk region on the periphery of the vehicle
using the peripheral information;
[0146] specifying a position of a sight line of a driver of the
vehicle in the peripheral information; and
[0147] switching driving support control based on a degree of
deviation between the risk region predicted in the predicting and
the position of the sight line specified in the specifying.
[0148] According to this embodiment, it is possible to perform
appropriate driving support for the driver in consideration of the
sight line of the driver and the peripheral environment of a road
during traveling. [0149] 13. The above-described embodiment can
also be implemented by a non-transitory computer-readable storage
medium storing a computer program. The non-transitory
computer-readable storage medium stores a program configured to
cause a computer (for example, 2) mounted in a vehicle (for
example, 1) to function as:
[0150] an information acquisition unit configured to acquire
peripheral information of the vehicle;
[0151] a risk prediction unit configured to predict a risk region
on the periphery of the vehicle using the peripheral
information;
[0152] a sight line specifying unit configured to specify a
position of a sight line of a driver of the vehicle in the
peripheral information; and
[0153] a control unit configured to switch driving support control
based on a degree of deviation between the risk region predicted by
the risk prediction unit and the position of the sight line
specified by the sight line specifying unit.
[0154] According to this embodiment, it is possible to perform
appropriate driving support for the driver in consideration of the
sight line of the driver and the peripheral environment of a road
during traveling.
[0155] The invention is not limited to the foregoing embodiments,
and various variations/changes are possible within the spirit of
the invention.
* * * * *