Path planning for evasive steering maneuver employing a virtual potential field technique
View Patent ↗A system and method for calculating a virtual target path that is used to calculate an evasive steering path around a target object, such as a target vehicle, stopped in front of a subject vehicle. The method includes determining a potential field using a plurality of scan points that is a summation of two-dimensional Gaussian functions, where each Gaussian function has center defined by target object scan points and other object scan points. The method identifies a mesh grid in an X-Y plane where the mesh grid includes mesh grid points at locations where X and Y plane lines cross. The method identifies a local minimum point of the potential field for each X-plane line at each mesh grid point along the Y-plane crossing that X-plane line, where the local minimum point is a curve point. The method then connects the curve points to define the target path.
1. A method for determining a virtual target path which is used to calculate an evasive steering path for a subject vehicle around a target object in a travel path of the subject vehicle without using lane markings, said method comprising:
a collision avoidance system programmed for:
providing a plurality of scan points identifying detected objects from one or more sensors on the subject vehicle;
separating the plurality of scan points into target object scan points received from the target object and other object scan points received from other objects;
determining a potential field using the plurality of scan points that is a summation of two-dimensional Gaussian functions, where each Gaussian function has a center defined by the target object scan points and the other object scan points;
identifying a mesh grid in an X-Y plane and in a predefined region where the steering path will be located where the mesh grid includes mesh grid points at locations where X and Y plane lines cross, and where X plane lines are in a direction of the travel path of the subject vehicle and Y plane lines are in a perpendicular direction to the X direction;
identifying a potential field value from the potential field at each mesh grid point;
identifying a local minimum point of the potential field for each X plane line at each mesh grid point along a Y plane line crosses that X plane line, where the local minimum point is a curve point and where each X plane line includes a curve point;
calculating a corridor width between the target object and other objects and using the corridor width as a weight coefficient to determine an optimal virtual target path such that a path with a wider corridor width is preferred over a path with a narrow corridor width; and
connecting the curve points to define the virtual target path.
2. The method according to claim 1 wherein determining a potential field that is a summation of the two-dimensional Gaussian functions includes using:
U ( X,Y )=Σ i=1 n U i ( X,Y )+Σ j=1 m U i ( X,Y ),
where U(X, Y) is the potential field, n and m are the number of target object points a i , i=1, 2, . . . , n, and the object points, b j , j=1, 2, . . . , m, respectively, and:
U
i
(
X
,
Y
)
=
A
i
Exp
[
-
(
(
X
-
a
iX
)
2
2
σ
Xi
2
+
(
Y
-
a
iY
)
2
2
σ
Yi
2
)
]
,
U
j
(
X
,
Y
)
=
A
j
Exp
[
-
(
(
X
-
b
jX
)
2
2
σ
Xj
2
+
(
y
-
b
jY
)
2
2
σ
Yj
2
)
]
,
where A is the amplitude and σ X and σ Y are X and Y spreads of the Gaussian function.
3. The method according to claim 1 wherein identifying a local minimum point of the potential field includes using:
{
Y
tg
≤
Y
gmin
≤
Y
bg
if
TD
=
right
Y
bg
≤
Y
gmin
≤
Y
tg
if
TD
=
left
,
where T D is subject vehicle turning direction, Y gmin is the local minimum potential field value, and Y tg and Y bg are a target limit and an object limit, respectively, and are defined to ensure that the local minimum points are found in a safe region either on a desired side of the target object points a i or between the target object points a i and the other object points b j .
4. The method according to claim 3 wherein the identifying a local minimum point of the potential field also includes using:
Y
tg
=
{
{
min
i
a
iy
-
d
t
if
min
i
a
iX
-
d
t
≤
X
g
≤
max
i
a
iX
+
d
t
min
i
a
iY
Otherwise
If
TD
=
right
{
max
i
a
iy
-
d
t
if
min
i
a
iX
-
d
t
≤
X
g
≤
max
i
a
iX
+
d
t
max
i
a
iY
Otherwise
If
TD
=
left
for
g
=
1
,
2
,
…
,
N
where a i are the target object scan points, X g is the X coordinate of a mesh grid point, and d t is a predetermined target safe distance.
5. The method according to claim 4 wherein identifying a local minimum point of the potential field also includes using:
b
^
k
g
=
[
b
^
k
-
1
g
,
b
j
]
if
X
g
-
d
b
≤
b
jX
≤
X
g
+
d
b
,
for
j
=
1
,
2
,
…
,
m
&
k
=
1
,
2
,
…
,
Y
bg
=
{
max
k
b
^
kY
+
d
b
if
TD
=
right
min
k
b
^
kY
-
d
b
if
TD
=
left
,
for
g
=
1
,
2
,
…
,
N
where {circumflex over (b)} is a vector of scan points of the other objects and d b is a predetermined object safe distance.
6. The method according to claim 1 wherein connecting the curve points to define the virtual target path includes fitting a quadratic polynomial function through the points using a least-square process.
7. The method according to claim 1 further comprising reducing the complexity of the plurality of scan points using a clustering algorithm before the scan points are separated into the target object scan points and the other object scan points.
8. The method according to claim 1 further comprising ignoring scan points that are outside of a predetermined safe distance from the subject vehicle.
9. The method according to claim 1 further comprising detecting a target vehicle as the target object from the other objects.
10. The method according to claim 1 wherein calculating a corridor width between the target object and the other objects includes aborting an evasive steering maneuver if the corridor width is less than a predetermined threshold width.
11. The method according to claim 1 wherein the at least one sensor is at least one LiDAR sensor.
12. A method for determining a virtual target path that is used to calculate an evasive steering path for a subject vehicle around a target vehicle in a travel path of the subject vehicle without using lane markings, said method comprising:
a collision avoidance system programmed for:
providing a plurality of scan points identifying detected objects from one or more LiDAR sensors on the subject vehicle;
separating the plurality of scan points into target vehicle scan points received from the target vehicle and other object scan points received from other objects;
determining a potential field using the plurality of scan points that is a summation of two-dimensional Gaussian functions, where each Gaussian function has a center defined by the target vehicle scan points and the other object scan points;
identifying a mesh grid in an X-Y plane and in a predefined region where the steering path will be located where the mesh grid includes mesh grid points at locations where X and Y plane lines cross, and where X plane lines are in a direction of the travel path of the subject vehicle and Y plane lines are in a perpendicular direction to the X direction;
identifying a potential field value from the potential field at each mesh grid point;
identifying a local minimum point of the potential field for each X plane line at each mesh grid point along a Y plane line that crosses the X plane line, where the local minimum point is a curve point and where each X plane line includes a curve point;
calculating a corridor width between the target object and other objects and using the corridor width as a weight coefficient to determine an optimal virtual target path such that a path with a wider corridor width is preferred over a path with a narrow corridor width; and
connecting the curve points to define the virtual target path by fitting a quadratic polynomial function through the points using a least-square process.
13. The method according to claim 12 wherein determining a potential field that is a summation of the two-dimensional Gaussian functions includes using:
U ( X,Y )=Σ i=1 n U i ( X,Y )+Σ j=1 m U j ( X,Y ),
where U(X, Y) is the potential field, n and m are the number of target object points a i , i=1, 2, . . . , n, and the object points, b j , j=1, 2, . . . , m, respectively, and:
U
i
(
X
,
Y
)
=
A
i
Exp
[
-
(
(
X
-
a
iX
)
2
2
σ
Xi
2
+
(
Y
-
a
iY
)
2
2
σ
Yi
2
)
]
,
U
j
(
X
,
Y
)
=
A
j
Exp
[
-
(
(
X
-
b
iX
)
2
2
σ
Xj
2
+
(
y
-
b
jY
)
2
2
σ
Yj
2
)
]
,
where A is the amplitude and σ X and σ Y are X and Y spreads of the Gaussian function.
14. The method according to claim 12 wherein identifying a local minimum point of the potential field includes using:
{
Y
tg
≤
Y
gmin
≤
Y
bg
if
TD
=
right
Y
bg
≤
Y
gmin
≤
Y
tg
if
TD
=
left
,
where T D is subject vehicle turning direction, Y gmin is the local minimum potential field value, and Y tg and Y bg are a target limit and an object limit, respectively, and are defined to ensure that the local minimum points are found in a safe region either on a desired side of the target vehicle points a i or between the target vehicle points a i and the other object points b j .
15. The method according to claim 14 wherein the identifying a local minimum point of the potential field also includes using:
Y
tg
=
{
{
min
i
a
iy
-
d
t
if
min
i
a
iX
-
d
t
≤
X
g
≤
max
i
a
iX
+
d
t
min
i
a
iY
Otherwise
If
TD
=
right
{
max
i
a
iy
-
d
t
if
min
i
a
iX
-
d
t
≤
X
g
≤
max
i
a
iX
+
d
t
max
i
a
iY
Otherwise
If
TD
=
left
for
g
=
1
,
2
,
…
,
N
where a i are the target vehicle scan points, X g is the X direction potential field value at a mesh grid point, and d t is a predetermined target safe distance.
16. The method according to claim 15 wherein identifying a local minimum point of the potential field also includes using:
b
^
k
g
=
[
b
^
k
-
1
g
,
b
j
]
if
X
g
-
d
b
≤
b
jX
≤
X
g
+
d
b
,
for
j
=
1
,
2
,
…
,
m
&
k
=
1
,
2
,
…
,
Y
bg
=
{
max
k
b
^
kY
+
d
b
if
TD
=
right
min
k
b
^
kY
-
d
b
if
TD
=
left
,
for
g
=
1
,
2
,
…
,
N
where {circumflex over (b)} is a vector of the scan points of the other objects and d b is a predetermined object safe distance.
17. The method according to claim 12 further comprising ignoring scan points that are outside of a predetermined safe distance from the subject vehicle.
18. The method according to claim 12 further comprising detecting a target vehicle as the target object from the other objects.
19. The method according to claim 12 wherein calculating a corridor width between the target object and the other objects includes aborting an evasive steering maneuver if the corridor width is less than a predetermined threshold width.