AU2024201599B2 - Vehicle control system and vehicle control method thereof - Google Patents
Vehicle control system and vehicle control method thereofInfo
- Publication number
- AU2024201599B2 AU2024201599B2 AU2024201599A AU2024201599A AU2024201599B2 AU 2024201599 B2 AU2024201599 B2 AU 2024201599B2 AU 2024201599 A AU2024201599 A AU 2024201599A AU 2024201599 A AU2024201599 A AU 2024201599A AU 2024201599 B2 AU2024201599 B2 AU 2024201599B2
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- state
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- Control Of Driving Devices And Active Controlling Of Vehicle (AREA)
Abstract
#$%^&*AU2024201599B220250814.pdf#####
A vehicle control system includes a vehicle state estimator, a delay simulator
and an error compensation optimizer. The vehicle state estimator is configured to
generate an estimated future vehicle state at a future time point. The delay simulator
is configured to determine a delay time based on the estimated future vehicle state
and a current vehicle state, and obtain a delayed future vehicle state based on the
delay time. The error compensation optimizer is configured to generate a driving
parameter estimation compensation to the vehicle state estimator based on a
difference between the delayed future vehicle state and a target vehicle state being
outside the error range.
A vehicle control system includes a vehicle state estimator, a delay simulator
and an error compensation optimizer. The vehicle state estimator is configured to
generate an estimated future vehicle state at a future time point. The delay simulator
is configured to determine a delay time based on the estimated future vehicle state
and a current vehicle state, and obtain a delayed future vehicle state based on the
delay time. The error compensation optimizer is configured to generate a driving
parameter estimation compensation to the vehicle state estimator based on a
difference between the delayed future vehicle state and a target vehicle state being
outside the error range.20
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1
Description
A vehicle vehiclecontrol controlsystem system includes a vehicle state state estimator, a delaya simulator delay simulator 12 Mar 2024
A includes a vehicle estimator,
and an and anerror error compensation compensation optimizer. optimizer. TheThe vehicle vehicle state state estimator estimator is is configured configured to to
generateanan generate estimated estimated future future vehicle vehicle statestate at a at a future future time time point.point. The simulator The delay delay simulator
is configured is configured to to determine determine a a delay time based delay time basedononthe theestimated estimatedfuture futurevehicle vehicle state state
and aa current and current vehicle vehicle state, state, and and obtain obtain a a delayed future vehicle delayed future vehicle state state based on the based on the 2024201599
delay time. delay time. The Theerror error compensation compensation optimizer optimizer is is configured configured to to generate generate a driving a driving
parameter estimation compensation parameter estimation to the compensation to the vehicle vehicle state state estimator estimatorbased based on a on a
differencebetween difference betweenthe the delayed delayed futurefuture vehicle vehicle state state and and a vehicle a target target vehicle state state being being
outsidethe outside theerror errorrange. range.
1/4 1/4
100 2024201599
S5,t' Road surface information acquirer 140
Vehicle-side S4,t'
information provider Sp 160 Vehicle state estimator 110 Inertial sensor S S3",t'
170 S1,t'
S3,t' Delay simulator 120 S2,t td
S3',t' U,t'
Convergence determination element AS Error compensation optimizer 130 150
u
10
FIG. 1
TECHNICAL FIELD 2024201599
[0001] The disclosure relates in general to a vehicle control system and
5 vehicle control method thereof.
[0002] The road conditions for automobiles transportation varies , such as a
slope of the road, a left and right inclination, a curvature of the turning road, a
road surface damage, etc. Usually, the driving of vehicles on variable road
10 surfaces are prone to deviating from an expected driving route. Therefore,
proposing a vehicle control system capable of coping with the aforementioned
circumstance is required.
[0003] According to one embodiment, a vehicle control system is provided.
15 The vehicle control system is disposed on a vehicle. The vehicle control system
includes a vehicle state estimator, a delay simulator and an error compensation
optimizer. The vehicle state estimator is configured to generate an estimated
future vehicle state of a future time point. The delay simulator configured to
determine a delay time according to the estimated future vehicle state and a
20 current vehicle state; and obtain a first delayed future vehicle state according
to the delay time. The error compensation optimizer is configured to generate
a driving parameter estimation compensation based on a difference between
the first delayed future vehicle state and a target vehicle state that is outside an
error range and transmit the driving parameter estimation compensation to the 2024201599
5 vehicle state estimator.
[0004] According to another embodiment, a vehicle control method of a
vehicle control system is provided. The vehicle control method includes the
following steps: generating an estimated future vehicle state of a future time
point by a vehicle state estimator; determining a delay time according to the
10 estimated future vehicle state and a current vehicle state by a delay simulator;
obtaining a first delayed future vehicle state according to the delay time by the
delay simulator; and generating a driving parameter estimation compensation
based on a difference between the first delayed future vehicle state and a target
vehicle state that is outside an error range and transmit the driving parameter
15 estimation compensation to the vehicle state estimator by an error
compensation optimizer.
[0005] According to one embodiment, a vehicle control system disposed on
a vehicle and comprising:
a vehicle state estimator configured to:
20 generate an estimated future vehicle state at a future time point;
a delay simulator configured to:
determine a delay time according to the estimated future vehicle state
and a current vehicle state; and
obtain a first delayed future vehicle state according to the delay time; 2024201599
an error compensation optimizer configured to:
5 generate a driving parameter estimation compensation based on a
difference between the first delayed future vehicle state and a target vehicle
state that is outside an error range, and transmit the driving parameter
estimation compensation to the vehicle state estimator; and
a road surface information acquirer configured to capture a road
10 surface information of a road surface position at the future time point wherein
the road surface information includes at least one of a road surface inclination
angle and a road surface slope,
wherein the delay time is determined at least based on control on
vehicle speed of the vehicle.
15 [0006] In one embodiment, a vehicle control method of a vehicle control
system, comprising:
generating an estimated future vehicle state at a future time point by
a vehicle state estimator;
determining a delay time according to the estimated future vehicle
state and a current vehicle state by a delay simulator;
obtaining a first delayed future vehicle state according to the delay
time by the delay simulator; 2024201599
generating a driving parameter estimation compensation based on a
5 difference between the first delayed future vehicle state and a target vehicle
state that is outside an error range, and transmitting the driving parameter
estimation compensation to the vehicle state estimator by an error
compensation optimizer; and
capturing a road surface information of a road surface position at the
10 future time point wherein the road surface information includes at least one of
a road surface inclination angle and a road surface slope,
wherein the delay time is determined at least based on control on
vehicle speed of the vehicle.
[0007] The above and other aspects of the disclosure will become better
15 understood with regard to the following detailed description of the preferred but
non-limiting embodiment (s). The following description is made with reference
to the accompanying drawings.
[0008] FIG. 1 illustrates a functional block diagram of a vehicle control
system according to an embodiment of the present disclosure;
[0009] FIG. 2 illustrates a schematic diagram of a variety of a road surface
of a road; 2024201599
[0010] FIG. 3 illustrates a schematic diagram of a deviation of the vehicle
5 which use the vehicle control system in FIG. 1 driving on the road R in FIG. 2;
[0011] FIG. 4 illustrates a flow chart of the vehicle control method of the
vehicle control system in FIG. 1; and
[0012] FIG. 5 illustrates a flow chart of the vehicle control method of the
vehicle control system of FIG. 1 in another embodiment.
10 DETAILED DESCRIPTION
[0013] Referring to FIG. 1, FIG. 1 illustrates a functional block diagram of a
vehicle control system 100 according to an embodiment of the present
disclosure. The vehicle control system 100 includes a vehicle state estimator
110, a delay simulator 120, an error compensation optimizer 130, a road surface
15 information acquirer 140, a convergence determination element 150, a vehicle-
side information provider 160 and an inertial sensor 170. The vehicle control
system 100 may be disposed on a vehicle (not shown). For example, the vehicle
includes at least one wheel and a driving system, wherein the driving system
may drive the wheels to rotate so that the vehicle may move on the road. The
20 driving system may operate by, for example, electricity, fuel or a combination
thereof. In addition, the vehicle also includes a steering wheel system, an
accelerator system, a braking system and other system to control the vehicle's
steering and speed. In an embodiment, the vehicle may be a truck, but the
disclosed embodiments are not limited. 2024201599
5 [0014] In an embodiment, at least two of the vehicle state estimator 110, the
delay simulator 120, the error compensation optimizer 130, the road surface
information acquirer 140 and the convergence determination element 150 may
be integrated into a single unit. Alternatively, at least one of the vehicle state
estimator 110, the delay simulator 120, the error compensation optimizer 130,
10 the road surface information acquirer 140, the convergence determination
element 150 and the vehicle-side information provider 160 may be integrated
into a processor or a controller. At least one of the vehicle state estimator 110,
the delay simulator 120, the error compensation optimizer 130, the road surface
information acquirer 140, the convergence determination element 150 and the
15 vehicle-side information provider 160 may be a physical circuits, such as a
semiconductor chip or a semiconductor device package, formed by using at
least one semiconductor process, for example. The inertial sensor 170 may
sense a three-axis angular velocity and a three-axis acceleration of the vehicle.
Furthermore, the inertial sensor 170 is, for example, a gyroscope.
20 [0015] As shown in FIG. 1, the vehicle state estimator 110 is configured to
generate an estimated future vehicle state S1,t' at the t'-th future time point. The
delay simulator 120 is configured to: determine a delay time td based on the
estimated future vehicle state S1,t' and a current vehicle state S2,t; and obtain
a first delayed future vehicle state S3,t' based on the delay time td. The error
compensation optimizer 130 is configured to generate a driving parameter
estimation compensation U,t' for the vehicle state estimator 110 based on a
difference between the first delayed future vehicle state S3,t' and a target vehicle 2024201599
5 state S5,t' which is outside an error range. Through the driving parameter
estimation compensation U,t', the vehicle state estimator 110 may generate the
updated estimated future vehicle state S1,t' at the t’-th future time point, so that
the vehicle approaches the expected control on the vehicle.
[0016] The subscript t' of the symbols in the present disclosure represents a
10 future time point, wherein the value of t' is a positive integer between 1 and N,
and N is, for example, a positive integer equal to or greater than 1. In addition,
the vehicle state estimator 110 may use, for example, a Kalman filter to estimate
the future vehicle state, but the embodiment of the present disclosure is not
limited thereto.
15 [0017] In an embodiment, the vehicle state estimator 110 generates an
estimated future vehicle state group S1 which includes a plurality of the
estimated future vehicle states at a plurality of future time points. The set may
be expressed as: S1=[S1,1, S1,2,…,S1,t',…, S1,N], wherein N is the number of
time points. For example, in case of once sampling per second and lasting for
20 10 seconds, the value of N is 10 and a time interval between the two adjacent
estimated future vehicle states S1,t'+1 and S1,t' is 1 second (i.e., S1,t'+1- S1,t'=1).
The delay simulator 120 calculates all estimated future vehicle states S1,t' one
by one to obtain the corresponding first delayed future vehicle state S3,t'. The
delay simulator 120 may calculate the estimated future vehicle state S1,t', by
using an appropriate mathematical method or a circuit design, to obtain the
corresponding first delayed future vehicle state S3,t'; however, it is not limited
by the embodiment of the present disclosure. 2024201599
5 [0018] In an embodiment, the current vehicle state S2,t, is, for example, the
vehicle state calculated at the current time (for example, in the iteration). The
current vehicle state S2,t includes, for example, at least one parameter, for
example, at least one of a current vehicle position Pt at the current time point t
(expressed by (Xt, Yt, Zt)), a current three-axis angular velocity ω̇ (expressed
10 by (ϕṫ , ψṫ , θṫ )), a current three-axis acceleration At (expressed by (Atx, Aty,
Atz)), a current three-axis angle ω (expressed by (ϕt, ψt, θt) and a current
vehicle speed Vt. The current vehicle state S2,t is, for example, a reference
coordinate system (X, Y, Z), wherein Xt is, for example, the value of X-axis, Yt
is, for example, the value of Y-axis, and Zt is, for example, the value of Z-axis,
15 ACx is, for example, the acceleration value along the X-axis, ACy is, for example,
the acceleration value along the Y-axis, ACz is, for example, the acceleration
value along the Z-axis, ϕt is, for example, the angle value around the X-axis,
ψt is, for example, the angle value around the Z-axis, and θt is, for example,
the angle value around the Y-axis, ϕṫ is, for example, the angular velocity
20 value around the X-axis, , ψṫ is, for example, the angular velocity value around
the Z-axis, θṫ is, for example, the angular velocity value around the Y-axis, and
the current vehicle speed Vt is the speed value of the velocity. The estimated
future vehicle state S1,t' includes, for example, at least one parameter, for
example, at least one of an estimated vehicle position P1 (expressed as (X1,
Y1, Z1)) at the t’-th future time point, an estimated three-axis angular velocity
̇ (expressed by (ϕ1̇ ,ψ1̇,θ1̇)), an estimated acceleration A1 (expressed by ω1
(A1x, A1y, A1z)), an estimated vehicle attitude ω1 (expressed by (ϕ1, ψ1, θ1)) 2024201599
5 and an estimated vehicle speed V1. The estimated future vehicle state S1,t' is,
for example, referring to a coordinate system (X, Y, Z), wherein X1 is, for
example, the value of the X-axis, Y1 is, for example, the value of the Y-axis, Z1
is, for example, the value of the Z-axis, A1x is, for example, the acceleration
value along the X-axis, A1y is, for example, the acceleration value along the Y-
10 axis, A1z is, for example, the acceleration value along the Z-axis, ϕ1 is the
angle value around the X-axis, ψ1 is the angle value around the Z-axis, θ1 is
the angle value around the Y-axis, ϕ1̇ is, for example, the angular velocity
value around the X-axis, ψ1̇ is, for example, the angular velocity value around
the Z-axis, and θ1̇ is, for example, the angular velocity value around the Y-axis.
15 The estimated future vehicle state S1,t' at each future time point is, for example,
the estimated future vehicle state based on the current vehicle state S2,t, which
may be optimized through at least one iterative calculation process (it will be
described later) to make each estimated future vehicle state S1,t' approach the
target vehicle state S5,t'.
20 [0019] In an embodiment, the first delayed future vehicle state S3,t' includes,
for example, at least one parameter, for example, a delayed vehicle position P3
(expressed by (X3, Y3, Z3)) and the delayed vehicle speed V3. The first delayed
future vehicle state S3,t' is, for example, the reference coordinate system (X, Y,
Z), where X3 is, for example, the value of the X-axis, Y3 is, for example, the
value of the Y-axis, and Z3 is, for example, the value of the Z-axis, and the
delayed vehicle speed V3 is, for example, the speed value of the vehicle. The
delay simulator 120 may make the estimated future vehicle state S1,t' more 2024201599
5 consistent with the actual operating state of the vehicle. Furthermore, during
the actual process of controlling the vehicle, when an accelerator pedal of the
vehicle is stepped on, the vehicle does not accelerate immediately, but delays
for a period of time (for example, within 1 second) before starting to accelerate.
The delay simulator 120 may perform a delay operation on the estimated future
10 vehicle state S1,t' according to the delay time td to obtain the first delayed future
vehicle state S3,t' for being consistent with the actual delay situation of the
vehicle. Taking the estimated vehicle speed V1 (belongs to one of the
parameters of the estimated future vehicle state S1,t') at the t’-th future time
point as an example, also at the t’-th future time point, the delayed vehicle
15 speed V3 which is delayed by the delay simulator 120 is different from the
estimated vehicle speed V1. For example, the delayed vehicle speed V3 is
smaller than the estimated vehicle speed V1 (due to the delayed response of
the accelerator, so the vehicle speed becomes smaller), but the delayed vehicle
speed V3 is more consistent with or closer to the actual vehicle speed.
20 [0020] In addition, as shown in FIG. 1, the delay simulator 120 is further
configured to perform a delay calculation on the estimated future vehicle state
S1,t' to generate a second delayed future vehicle state S3',t'. The second
delayed future vehicle state S3',t' includes at least one parameter, for example,
at least one of the delayed vehicle position P3 (expressed by (X3, Y3, Z3)), the
̇ delayed vehicle speed V3, an estimated three-axis angular velocity ω3
̇ , θ3 (expressed by (ϕ3̇ , ψ3 ̇ )), an delayed acceleration A3 (expressed by (A3 , x 2024201599
A3y, A3z)) and a delayed vehicle attitude ω3 (expressed by (ϕ3, ψ3, θ3)) .
5 The parameters included in the aforementioned first delayed future vehicle
state S3,t' are, for example, one of some of the parameters included in the
second delayed future vehicle state S3',t'. The second delayed future vehicle
state S3',t' is, for example, the reference coordinate system (X, Y, Z), wherein
X3 is, for example, the value of the X-axis, Y3 is, for example, the value of the
10 Y-axis, and Z3, for example, is the value of the Z-axis, A3x is, for example, the
acceleration value along the X-axis, A3y is, for example, the acceleration value
along the Y-axis, A3z is, for example, the acceleration value along the Z-axis,
ϕ3 is, for example, the angle value around the X-axis, ψ3 is, for example, the
angle value around the Z-axis, θ3 is, for example, the angle value around the
15 Y-axis, ϕ3̇ is, for example, the angular velocity value around the X-axis, ψ3̇ is,
for example, the angular velocity value around the Z-axis, and θ3̇ is, for
example, the angular velocity value around the Y-axis.
[0021] As shown in FIG. 1, the delay simulator 120 is further configured to
output a third delayed future vehicle state S3'',t' to the road surface information
20 acquirer 140. The third delayed future vehicle state S3'',t' includes, for example,
at least one parameter, for example, the delayed vehicle position P3. The
parameters included in the third delayed future vehicle state S3'',t' are, for
example, one or some of the parameters included in the second delayed future
vehicle state S3',t'. The road surface information acquirer 140 is further
configured to: obtain the target vehicle state S5,t' at the t’-th future time point
based on the third delayed future vehicle state S3'',t', wherein the target vehicle
state S5,t' includes, for example, at least one parameter, for example, the 2024201599
5 vehicle target position P5 (expressed by (X5, Y5, Z5)) and the target vehicle
speed V5.
[0022] As shown in FIG. 1, the delay simulator 120 is further configured to
output the delayed vehicle position P3 of the third delayed future vehicle state
S3'',t' to the road surface information acquirer 140. The road surface information
10 acquirer 140 is further configured to obtain the target vehicle state S5,t' at the t’-
th future time point based on the estimated vehicle position P1, wherein the
target vehicle state S5,t' includes, for example, at least one parameter, for
example, the vehicle Target position P5 and target vehicle speed V5. The target
vehicle state S5,t' is, for example, the reference coordinate system (X, Y, Z),
15 wherein X5 is, for example, the value of the X-axis, Y5 is, for example, the value
of the Y-axis, Z5 is, for example, the value of the Z-axis, and the target vehicle
speed V5 is, for example, the speed value of the vehicle.
[0023] As shown in FIG. 1, the road surface information acquirer 140 is
configured to acquire the road surface information S4,t' of the road surface
20 position at the t’-th future time point. The road surface information S4,t' includes
at least one parameter, for example, at least one of a road surface inclination
angle Φ1 and a road surface slope Θ1. The angle symbol Θ1 here is, for
example, a pitch angle of the road surface, and the angle symbol Φ1 is, for
example, a left-right inclination angle of the road surface. The vehicle state
estimator 110 may generate the estimated future vehicle state S1,t' at the t’-th
future time point based on the road surface information S4,t'. For example, the
road surface information acquirer 140 obtains the road surface roll angle Φ1 2024201599
5 and the road surface gradient Θ1 corresponding to the estimated vehicle
position P1, and determines a vehicle posture of the vehicle at the t’-th future
time point based on the road surface roll angle Φ1 and the road surface
gradient Θ1.
[0024] As shown in FIG. 1, the road surface information acquirer 140
10 captures the road surface information S4,t' of the road surface position at the t’-
th future time point, wherein the road surface information S4,t' is obtained from
the map data of Global Positioning System (GPS), or by analysis of detection
signals from at least one lidar (for example, disposed on the vehicle). In another
embodiment, the road surface information S4,t' of the road surface position at
15 the t’-th future time point may be obtained through a road surface information
database. In other embodiments, at least one roadside device indirectly or
directly transmits the road surface information S4,t' of the surrounding area to
the vehicle control system 100 through communication technology.
[0025] As shown in FIG. 1, the driving parameter estimation compensation
20 U,t' includes, for example, a control command for at least one parameter,
wherein the at least one parameter includes, for example, at least one of a
steering wheel angle AN, an accelerator opening TO, and a braking depth BD.
Taking the steering wheel angle AN as an example, the vehicle driving straight
head may be defined as 0 degrees. The steering wheel angle AN is, for example,
the rotation angle of the steering wheel relative to 0 degrees. Taking the
accelerator opening TO as an example, the accelerator pedal in a free state
(the pedal is not stepped on) may be defined as 0%, the maximum stroke of the 2024201599
5 accelerator pedal is defined as 100%, and the accelerator opening TO is
between 0% and 100%. Taking the braking depth BD as an example, the free
state of the brake pedal (without pressing the pedal) may be defined as 0%, the
maximum stroke of the brake pedal may be defined as 100%, and the braking
depth BD is between 0% and 100%.
10 [0026] As shown in FIG. 1, the convergence determination element 150 is
configured to obtain the difference between the target vehicle state S5,t' and the
first delayed future vehicle state S3,t'. For example, the convergence
determination element 150 may obtain the difference value ΔS between the first
delayed future vehicle state S3,t' and the target vehicle state S5,t'. Furthermore,
15 the convergence determination element 150 obtains a position difference (ΔX,
ΔY, ΔZ) between the vehicle target position P5 and the delayed vehicle position
P3, and obtains a vehicle speed difference (ΔV) between the target vehicle
speed V5 and the delayed vehicle speed V3. The error compensation optimizer
130 determines whether the position difference (ΔX, ΔY, ΔZ) and vehicle speed
20 difference (ΔV) is outside the error range.
[0027] If the position difference (ΔX, ΔY, ΔZ) and vehicle speed difference
(ΔV) is within the error range, it means that the difference between the first
delayed future vehicle state S3,t' and the target vehicle state S5,t' is in line with
expectations. The error compensation optimizer 130 generates a control
command u corresponding to the first delayed future vehicle state S3,t'. The
control command u may, for example, be sent to a vehicle computer 10, and
the vehicle computer 10 controls the vehicle's steering wheels, the brake and/or 2024201599
5 the accelerator with the control command u. The control command u includes
at least one parameter, for example, at least one of a steering wheel angle an,
an accelerator opening to, and a braking depth bd, whose definitions are the
same or similar to the aforementioned steering wheel angle AN, the accelerator
opening TO, and the braking depth BD.
10 [0028] If the position difference (ΔX, ΔY, ΔZ) and vehicle speed difference
(ΔV) is outside the error range, it means that the difference between the first
delayed future vehicle state S3,t' and the target vehicle state S5,t' is not as
expected, the error compensation optimizer 130 may generate the driving
parameter estimation compensation U,t' according to the position difference (ΔX,
15 ΔY, ΔZ) and the vehicle speed difference (ΔV), and transmit the driving
parameter estimation compensation U,t' to the vehicle state estimator 110. The
estimated future vehicle state S1,t' generated by the vehicle state estimator 110
according to the driving parameter estimation compensation U,t' may be closer
to the vehicle target state S5,t’. In other words, the estimated future vehicle state
20 S1,t' at the t’-th future time point may go through at least one iteration or update,
so that the estimated future vehicle state S1,t' after iteration or update is more
closer to the target vehicle state S5,t'.
[0029] As shown in FIG. 1, the vehicle-side information provider 160 is
configured to obtain the current vehicle-side information SP of the vehicle, which
includes, for example, a measurement value of the steering wheel angle, a
measurement value of the vehicle speed and/or a measurement value of
vehicle location information. The vehicle state estimator 110 is further 2024201599
5 configured to output the estimated future vehicle state S1,t' at the t’-th future
time point according to the current vehicle-side information SP. The inertial
sensor 170 is configured to obtain the current motion information SI of the
vehicle, which includes, for example, the vehicle posture (for example, the pitch
angle of the vehicle and the left and right inclination angle of the vehicle), the
10 acceleration of the vehicle and/or the angular velocity of the vehicle.
[0030] In an embodiment, when the vehicle starts from the power-off state,
the vehicle state estimator 110 may obtain the estimated future vehicle state
S1,1 at the 1st future time point by using the current vehicle-side information SP
and/or the current motion information SI. The estimated future vehicle state S1,2
15 at the 2nd time point may be obtained based on the estimated future vehicle
state S1,1 at the 1st future time point, and so on, the estimated future vehicle
state S1,t'+1 at the (t'+1)th future time point may be obtained based on the
estimated future vehicle state S1,t' at the t’-th future time point.
[0031] In an embodiment, during driving, when the driver changes at least
20 one of the steering wheel angle, the accelerator opening and the braking depth,
the vehicle state estimator 110 may obtain the current estimated future vehicle
state S1,t by using the current vehicle-side information SP and/or the current
motion information SI, The next estimated future vehicle state S1,t’+1 may be
obtained based on the estimated future vehicle state S1,t’.
[0032] Referring to FIGS. 2 to 3, FIG. 2 illustrates a schematic diagram of a
variety of a road surface of a road R, and FIG. 3 illustrates a schematic diagram 2024201599
of a deviation of the vehicle which uses the vehicle control system 100 in FIG.
5 1 driving on the road R in FIG. 2.
[0033] The horizontal axis shown in FIG. 2 represents a mileage of the road
R, while the vertical axis represents the left and right inclination angle of the
road surface. As shown in FIG. 3, the horizontal axis represents the mileage of
road R, while the vertical axis represents the deviation of the vehicle relative to
10 a road center line. The value of 0 on the vertical axis is defined as the road
center line, the value greater than 0 represents that the distance of the vehicle
deviating leftward relative to the road center line of the road surface, while the
value less than 0 represents that the distance of the vehicle deviating rightward
relative to the road center line of the road surface. A curve C1 represents a
15 deviation curve of a conventional vehicle without the vehicle control system 100
driving on the road R in FIG. 2, and a curve C2 represents that the deviation
curve of the vehicle using the vehicle control system 100 according to the
embodiment of the present disclosure driving on the road R in FIG. 2.
Comparing the curves C1 and C2, it may be seen that the vehicle using the
20 vehicle control system 100 in the present embodiment of the disclosure has a
smaller degree of deviation when driving on the road. That is, the vehicle using
the vehicle control system 100 in the present embodiment of the disclosure may
remain on the center line of the lane of the road as much as possible.
[0034] Referring to FIG. 4, FIG. 4 illustrates a flow chart of the vehicle control
method of the vehicle control system 100 in FIG. 1.
[0035] In step S110, Referring to FIG. 1, the vehicle state estimator 110 2024201599
generates the estimated future vehicle state S1,t' at the t’-th future time point.
5 As illustrated in FIG. 1, when the vehicle starts from the power-off state, the
vehicle state estimator 110 may obtain the estimated future vehicle state S1,1
at the 1st future time point by using the current vehicle-side information SP
and/or the current motion information SI. In other words, the first estimated
future vehicle state after the vehicle is started from the power-off state is
10 obtained according to the current vehicle-side information SP and/or the current
motion information SI. The estimated future vehicle state S1,2 at the 2nd future
time point may be obtained according to the estimated future vehicle state S1,1
at the 1st future time point, and so on, the estimated future vehicle state S1,t'+1
at the (t'+1)th future time point may be obtained according to the estimated
15 future vehicle state S1,t' at the t’-th future time point.
[0036] In step S120, the delay simulator 120 determines the delay time td
according to the estimated future vehicle state S1,t' and the current vehicle state
S2,t.
[0037] In step S130, the delay simulator 120 obtains the first delayed future
20 vehicle state S3,t' according to the delay time td.
[0038] In step S140, the error compensation optimizer 130 determines
whether the difference between the first delayed future vehicle state S3,t' and
the target vehicle state S5,t' is outside the error range; if so, the process
proceeds to step S150; if not, the process proceeds Step S160. 2024201599
[0039] In step S150, the error compensation optimizer 130 generates the
5 driving parameter estimation compensation U,t' and transmits the driving
parameter estimation compensation U,t' to the vehicle state estimator 110. Then
the process returns to step S110, and the vehicle state estimator 110 obtains
the updated estimated future vehicle state S1,t' according to the driving
parameter estimation compensation U,t'.
10 [0040] In step S160, the error compensation optimizer 130 generates a
control command u corresponding to the first delayed future vehicle state S3,t',
and transmits the control command u to the vehicle state estimator 110.
[0041] Referring to FIG. 5, FIG. 5 illustrates a flow chart of the vehicle control
method of the vehicle control system 100 of FIG. 1 in another embodiment.
15 [0042] In step S212, the vehicle state estimator 110 sets an initial value of j
to 1, wherein j is the iteration number.
[0043] In step S214, in the jth iteration, the vehicle state estimator 110
generates the estimated future vehicle state S1,t' at the t’-th future time point,
wherein t' is a positive integer between 1 and N. For example, the vehicle state
20 estimator 110 generates the estimated future vehicle state group S1=[S1,1,
S1,2, ..., S1,t', ..., S1,N], wherein S1,1 is the estimated future vehicle state at the
1st future time point, S1,2 is the estimated future vehicle state at the 2nd future
time point, and so on, S1,t' is the estimated future vehicle state at the t’-th future
time point. In other words, in one iteration, the vehicle state estimator 110
generates N estimated future vehicle states S1,t' and performs operations on 2024201599
5 them.
[0044] When the vehicle starts from the power-off state, the vehicle state
estimator 110 may obtain the estimated future vehicle state S1,1 at the 1st (t'=1)
future time point by using the current vehicle-side information SP and/or the
current motion information SI. The estimated future vehicle state S1,2 at the 2nd
10 (t'=2) future time point may be obtained based on the estimated future vehicle
state S1,1 at the 1st future time point, and so on, the estimated future vehicle
state S1,t'+1 at the (t'+1)th future time point may be obtained according to the
estimated future vehicle state S1,t' at the t’-th future time point.
[0045] In step S216, the delay simulator 120 determines the delay time td
15 according to the estimated future vehicle state S1,t' at the t’-th future time point
and the current vehicle state S2,t.
[0046] In step S218, the delay simulator 120 obtains the first delayed future
vehicle state S3,t' at the t’-th future time point according to the delay time td.
[0047] In step S220, the road surface information acquirer 140 obtains the
20 target vehicle state S5,t' at the t’-th future time point according to the estimated
vehicle position P1.
[0048] In step S222, the convergence determination element 150 obtains
the jth difference (in the jth iteration difference) between the target vehicle state
S5,t' at the t’-th future time point and the first delayed future vehicle state S3,t'.
For example, the convergence determination element 150 may obtain the 2024201599
5 difference ΔS between the first delayed future vehicle state S3,t'. and the target
vehicle state S5,t' at the t’-th future time point. Furthermore, the convergence
determination element 150 obtains the position difference (ΔX, ΔY, ΔZ) between
the vehicle target position P5 and the delayed vehicle position P3, and obtains
the vehicle speed difference (ΔV) between the target vehicle speed V5 and the
10 delayed vehicle speed V3.
[0049] In step S224, the error compensation optimizer 130 determines
whether the position difference (ΔX, ΔY, ΔZ) and the vehicle speed difference
(ΔV) converge to the error range. For example, compared with the difference
ΔS in the previous iteration (that is, (j-1)th), whether the difference ΔS in current
15 iteration (that is, jth) is reduced and within the error range is determined. If not,
it means that the first delayed future vehicle state S3,t' has not yet met the target
vehicle state S5,t', and the process proceeds to step S2261. The vehicle state
estimator 110 accumulates the value of j (for example, j=j+1) and enters next
iteration. If so, it means that the first delayed future vehicle state S3,t' has met
20 the target vehicle state S5,t', and the process proceeds to step S228.
[0050] In step S2262, the error compensation optimizer 130 generates the
driving parameter estimation compensation U,t' to the vehicle state estimator
110. Then, the process returns to step S214, and by using the driving parameter
estimation compensation U,t', the vehicle state estimator 110 may generate the
updated estimated future vehicle state S1,t' at the t’-th future time point, so that
the vehicle tend to behave as expected. 2024201599
[0051] In step S228, the error compensation optimizer 130 transmits the
5 control signal u corresponding to the first delayed future vehicle state S3,t'.
[0052] In summary, embodiments of the present disclosure propose a
vehicle control system and a vehicle control method thereof. The vehicle control
system includes the vehicle state estimator, the delay simulator and the error
compensation optimizer. The vehicle state estimator may generate at least one
10 estimated future vehicle state at least one future time point. The delay simulator
may determine the delay time according to the estimated future vehicle state
and the current vehicle state, and obtain the first delayed future vehicle state
according to the delay time. The error compensation optimizer may generate
the driving parameter estimation compensation based on the first delayed
15 future vehicle state and the target vehicle state being outside the error range,
and may transmit the driving parameter estimation compensation to the vehicle
state estimator. As a result, through the driving parameter estimation
compensation, the vehicle state estimator may generate the updated estimated
future vehicle state at the future time point, so that the vehicle tends to conform
20 to the expected control on the vehicle.
[0053] It will be apparent to those skilled in the art that various modifications
and variations could be made to the disclosed embodiments. It is intended that
the specification and examples be considered as exemplary only, with a true
scope of the disclosure being indicated by the following claims and their
equivalents. 2024201599
Claims (16)
1. A vehicle control system disposed on a vehicle and comprising: 2024201599
a vehicle state estimator configured to:
generate an estimated future vehicle state at a future time point;
5 a delay simulator configured to:
determine a delay time according to the estimated future vehicle
state and a current vehicle state; and
obtain a first delayed future vehicle state according to the delay
time;
10 an error compensation optimizer configured to:
generate a driving parameter estimation compensation based on a
difference between the first delayed future vehicle state and a target
vehicle state that is outside an error range, and transmit the driving
parameter estimation compensation to the vehicle state estimator; and
15 a road surface information acquirer configured to capture a road
surface information of a road surface position at the future time point
wherein the road surface information includes at least one of a road
surface inclination angle and a road surface slope,
wherein the delay time is determined at least based on control on
vehicle speed of the vehicle.
2. The vehicle control system according to claim 1, wherein the vehicle 2024201599
state estimator is further configured to:
5 generate an updated estimated future vehicle state according to the
driving parameter estimation compensation.
3. The vehicle control system according to claim 1, further comprising:
a road surface information acquirer configured to capture a road surface
information of a road surface position;
10 wherein the vehicle state estimator is further configured to:
obtain the estimated future vehicle state at the future time point
according to the road surface information and the driving parameter
estimation compensation.
4. The vehicle control system according to claim 1, wherein the delay
15 simulator is further configured to:
perform, according to the delay time, a delay calculation on the estimated
future vehicle state to obtain a second delayed future vehicle state;
wherein the error compensation optimizer is further configured to:
generate the driving parameter estimation compensation according
to the second delayed future vehicle state and the difference.
5. The vehicle control system according to claim 1, further comprising: 2024201599
a convergence determination element configured to:
5 obtain the difference between a target vehicle state and the first
delayed future vehicle state.
6. The vehicle control system according to claim 1, wherein the error
compensation optimizer is further configured to:
generate a control command corresponding to the first delayed future
10 vehicle state based on the difference between the first delayed future vehicle
state and the target vehicle state being within the error range.
7. The vehicle control system according to claim 1, further comprising:
a vehicle-side information provider configured to:
obtain a vehicle-side information of the vehicle;
15 wherein the vehicle state estimator is further configured to:
obtain the estimated future vehicle state at the 1st future time point
based on the vehicle-side information when the vehicle is started from a
power-off state.
8. The vehicle control system according to claim 1, further comprising: 2024201599
an inertial sensor configured to:
obtain a motion information of the vehicle;
5 wherein the vehicle state estimator is further configured to:
obtain the estimated future vehicle state at the 1st future time point
based on the motion information when the vehicle is started from a
power-off state.
9. A vehicle control method of a vehicle control system, comprising:
10 generating an estimated future vehicle state at a future time point by a
vehicle state estimator;
determining a delay time according to the estimated future vehicle state
and a current vehicle state by a delay simulator;
obtaining a first delayed future vehicle state according to the delay time
15 by the delay simulator;
generating a driving parameter estimation compensation based on a
difference between the first delayed future vehicle state and a target vehicle
state that is outside an error range, and transmitting the driving parameter
estimation compensation to the vehicle state estimator by an error
compensation optimizer; and 2024201599
capturing a road surface information of a road surface position at the
5 future time point wherein the road surface information includes at least one of
a road surface inclination angle and a road surface slope,
wherein the delay time is determined at least based on control on vehicle
speed of the vehicle.
10. The vehicle control method according to claim 9, further comprising:
10 generating an updated estimated future vehicle state according to the
compensation of the driving parameter by the vehicle state estimator.
11. The vehicle control method according to claim 9, further comprising:
capturing a road surface information of a road surface position by a road
surface information acquirer; and
15 obtaining the estimated future vehicle state at the future time point based
on the road surface information and the driving parameter estimation
compensation by the vehicle state estimator.
12. The vehicle control method according to claim 9, further comprising:
performing a delay calculation on the estimated future vehicle state
based on the delay time to obtain a second delayed future vehicle state by the
delay simulator; and 2024201599
generating the driving parameter estimation compensation based on the
5 second delayed future vehicle state and the difference by the error
compensation optimizer.
13. The vehicle control method according to claim 9, further comprising:
obtaining the difference between a target vehicle state and the first
delayed future vehicle state by a convergence determination element.
10
14. The vehicle control method according to claim 9, further comprising:
generating a control command corresponding to the first delayed future
vehicle state based on the difference between the first delayed future vehicle
state and the target vehicle state being within the error range by the error
compensation optimizer.
15 15. The vehicle control method according to claim 9, further comprising:
obtaining a vehicle-side information of the vehicle by a vehicle-side
information provider; and
obtaining the estimated future vehicle state at the 1st future time point
based on the vehicle-side information by the vehicle state estimator when the
vehicle is started from a power-off state.
16. The vehicle control method according to claim 9, further comprising: 2024201599
obtaining a motion information of the vehicle by an inertial sensor; and
obtaining the estimated future vehicle state at the 1st future time point
5 based on the motion information by the vehicle state estimator when the vehicle
is started from a power-off state.
*****
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| TW112150292A TWI922874B (en) | 2023-12-22 | Vehicle control system and vehicle control method thereof | |
| TW112150292 | 2023-12-22 |
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| AU2024201599A1 AU2024201599A1 (en) | 2025-07-10 |
| AU2024201599B2 true AU2024201599B2 (en) | 2025-08-14 |
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2020152977A1 (en) * | 2019-01-21 | 2020-07-30 | 日立オートモティブシステムズ株式会社 | Vehicle control device, vehicle control method, and vehicle control system |
| US20210188350A1 (en) * | 2019-12-18 | 2021-06-24 | Huyndai Mobis Co., Ltd. | System for road slope compensation using camera information and method thereof |
| WO2023057122A1 (en) * | 2021-10-09 | 2023-04-13 | Robert Bosch Gmbh | Lateral interference prevention module and method for vehicle |
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- 2024-03-12 AU AU2024201599A patent/AU2024201599B2/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2020152977A1 (en) * | 2019-01-21 | 2020-07-30 | 日立オートモティブシステムズ株式会社 | Vehicle control device, vehicle control method, and vehicle control system |
| US20210188350A1 (en) * | 2019-12-18 | 2021-06-24 | Huyndai Mobis Co., Ltd. | System for road slope compensation using camera information and method thereof |
| WO2023057122A1 (en) * | 2021-10-09 | 2023-04-13 | Robert Bosch Gmbh | Lateral interference prevention module and method for vehicle |
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| AU2024201599A1 (en) | 2025-07-10 |
| TW202525625A (en) | 2025-07-01 |
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