U.S. patent application number 10/120676 was filed with the patent office on 2003-10-16 for geometric based path prediction method using moving and stop objects.
Invention is credited to Ibrahim, Faroog Abdel-Kareem.
Application Number | 20030195703 10/120676 |
Document ID | / |
Family ID | 22391843 |
Filed Date | 2003-10-16 |
United States Patent
Application |
20030195703 |
Kind Code |
A1 |
Ibrahim, Faroog
Abdel-Kareem |
October 16, 2003 |
GEOMETRIC BASED PATH PREDICTION METHOD USING MOVING AND STOP
OBJECTS
Abstract
A method for estimating the curvature in a road is disclosed.
The method measures an azimuth angle range and relative velocity
between a host and a target vehicle, which determines whether a
host vehicle is changing lanes or whether a target vehicle is
changing lanes. The method calculates a heading angle of the host
vehicle and calculates a corrected azimuth angle by adjusting the
measured azimuth angle by the value of calculated heading angle.
This method selects a curve that minimizes the mean square error
between the curve and selected targets; and determines an equation
that describes the curve, wherein the equation is used to predict
the path head of the host vehicle.
Inventors: |
Ibrahim, Faroog Abdel-Kareem;
(Dearborn, MI) |
Correspondence
Address: |
BRINKS HOFER GILSON & LIONE
P.O. BOX 10395
CHICAGO
IL
60611
US
|
Family ID: |
22391843 |
Appl. No.: |
10/120676 |
Filed: |
April 11, 2002 |
Current U.S.
Class: |
701/301 ;
342/455; 701/96 |
Current CPC
Class: |
B60W 2552/30 20200201;
B60W 2552/20 20200201; B60K 31/0008 20130101; B60W 30/16
20130101 |
Class at
Publication: |
701/301 ; 701/96;
342/455 |
International
Class: |
G06F 017/00 |
Claims
1. A method for estimating a radius of curvature in a road, the
method comprising: measuring a range and an azimuth angle between a
host vehicle and a plurality of target vehicles; determining one of
whether the host vehicle is changing lanes and whether a primary
target vehicle in the plurality of target vehicles is changing
lanes; calculating a heading angle of the host vehicle; calculating
a corrected azimuth angle by adjusting the measured azimuth angle
by the calculated heading angle; selecting a curve that minimizes a
mean square error between the selected curve and a plurality of
measured locations of the plurality of target vehicles; and
determining an equation that describes the curve, wherein the
equation is used to determine the radius of curvature of the road
ahead of the host vehicle.
2. The method of claim 1 further comprising measuring a relative
velocity between the host and target vehicles.
3. The method of claim 1 wherein the heading angle is defined as
the angle between a line tangent to the road and a direction the
host vehicle is heading in.
4. The method of claim 3 wherein calculating a heading angle
(.eta.) further comprises calculating the heading angle as defined
by: 3 V h L x + = - where : V h = the host vechicle speed ; L = the
range between the host vehicle and the target vehicle ; = the
azimuth angle between the host vehicle and the target vehicle .
L=the range between the host vehicle and the target vehicle;
.alpha.=the azimuth angle between the host vehicle and the target
vehicle.
5. The method of claim 1 wherein measuring the azimuth angle
further comprises measuring the azimuth angle between a plurality
of stopped and moving targets.
6. The method of claim 1 wherein determining whether one of a host
vehicle and a primary target vehicle is changing lanes further
comprises determining whether the azimuth angle between the host
vehicle and the plurality of target vehicles is changing in the
same way.
7. The method of claim 1 wherein calculating a corrected azimuth
angle further comprises rotating the measured azimuth angle by the
calculated heading angle.
8. The method of claim 1 wherein selecting a curve further
comprises selecting a circle having a predefined radius.
9. A method for estimating a radius of curvature in a road, the
method comprising: measuring a range and an azimuth angle between a
host vehicle and a plurality of target vehicles and a plurality of
stopped targets; determining one of whether the host vehicle is
changing lanes and whether a primary target vehicle in the
plurality of target vehicles is changing lanes; calculating a
heading angle of the host vehicle; calculating a corrected azimuth
angle by adjusting the measured azimuth angle by the calculated
heading angle; selecting a curve that minimizes a mean square error
between the selected curve and a plurality of measured locations of
the plurality of target vehicles and the plurality of stopped
targets; and determining an equation that describes the curve,
wherein the equation is used to predict the radius of curvature of
the road ahead of the host vehicle.
10. The method of claim 9 wherein the heading angle is defined as
the angle between a line tangent to the road and a direction the
host vehicle is heading in.
11. The method of claim 10 wherein calculating a heading angle
(.eta.) further comprises calculating the heading angle as defined
by: 4 V h L x + = - where : V h = the host vechicle speed ; L = the
range between the host vehicle and the target vehicle ; = the
azimuth angle between the host vehicle and the target vehicle .
L=the range between the host vehicle and the target vehicle;
.alpha.=the azimuth angle between the host vehicle and the target
vehicle.
12. The method of claim 9 wherein determining whether one of a host
vehicle and a primary target vehicle is changing lanes further
comprises determining whether the azimuth angle between the host
vehicle and the plurality of target vehicles is changing in the
same way.
13. The method of claim 9 wherein calculating a corrected azimuth
angle further comprises rotating the measured azimuth angle by the
calculated heading angle.
14. The method of claim 9 wherein selecting a curve further
comprises selecting a circle having a predefined radius.
Description
TECHNICAL FIELD
[0001] The present invention relates to systems and methods for
predicting the path of a host vehicle for safety and non-safety
automotive applications, such as adaptive cruise control (ACC).
BACKGROUND
[0002] Adaptive cruise control systems are gaining wide spread
acceptance in vehicles today. Adaptive cruise control (ACC) systems
utilize a conventional cruise control system, which maintains a
desired vehicle speed. In addition, the adaptive cruise control
system can modify the speed of the vehicle to accommodate for
changes in traffic conditions. The ACC system accomplishes this
through automatic acceleration, deceleration and/or braking. Thus,
the vehicle having the ACC system (which will be referred to herein
as the host vehicle) maintains a safe distance from the vehicle
driving directly in front of the host vehicle (this vehicle will be
referred to the target vehicle) as a function of road speed.
[0003] Typically prior art adaptive cruise control systems include
an adaptive cruise control processor, a radar sensor, a brake
intervention system, a display unit, an engine intervention system,
a plurality of sensors (i.e., wheel speed, yaw rate, steering wheel
angle, lateral acceleration), and a transmission intervention
system. Typically, the radar sensor operates at a frequency of 76
to 77 gigahertz, which was specifically allocated for ACC systems.
In operation, radar beam is emitted by the host vehicle and is
reflected off of the target vehicle back toward the host vehicle.
The propagation time, dopier shift, and amplitude of the emitted
and reflected radar waves are compared. From this comparison, the
range or distance, relative speed and relative position between the
target and host vehicles are calculated.
[0004] One significant problem for ACC systems to overcome is to
ensure reliable operation of the system in varying situations such
as curves in the road and/or during lane changes. For proper system
operation, it is essential that the target vehicle is correctly
identified and the lane in which the target vehicle is located is
also identified. Prior art systems obtain information from a yaw
rate sensor, a steering wheel angle sensor, wheel speed sensors,
and lateral speed sensors to determine the target vehicle's lane
location and curve status. Other systems under consideration for
determining vehicle location are video imaging systems.
[0005] Methods found in literature use the yaw rate and the vehicle
speed to calculate the curvature of the road. The shortcomings of
this method are: first, the path or curvature of the road cannot be
accurately predicted and second, any prediction is highly affected
by the driver behavior. The first shortcoming is due to the fact
that the calculated curvature from the yaw rate and the speed
measurements represents the road curvature at the host vehicle
position, and the sensors used have different kinds of measurements
errors. The latter shortcoming is due to driver habit where he or
she doesn't follow the road curvature, e.g., during a lane change.
Other prior art methods that use target information to estimate the
curvature of the road assume that the host vehicle is always
following the road. Therefore, these methods fail when a host
vehicle maneuvers or changes lanes.
[0006] Therefore, what is needed is a new and improved method for
overcoming these shortcomings. This new and improved method should
accurately predict the location of the target vehicle without the
need for extensive experimental data.
SUMMARY
[0007] The method of the present invention utilizes what will be
referred to as a projected host vehicle reference frame. The
projected host reference frame results from rotating a host vehicle
reference frame to align the host vehicle reference frame with a
road reference frame. This is achieved by determining whether the
host vehicle is changing lanes and accounting for a heading angle
of the host vehicle with respect to the road. In addition, the
present invention utilizes stopped and moving objects to obtain the
maximum benefit of the existing objects in the radar field of view.
Moving objects are perceived in two ways, first as moving object
with history, and second as a stopped object at the current time.
Also, the stopped objects such as a guardrail or a row of trees on
a road side can perceived as a fictitious moving object that
travels at the host vehicle speed.
[0008] In an aspect of the present invention, a method for
estimating the curvature in a road is provided. This method uses an
azimuth angle range and relative velocity between a host and a
target vehicle radar measurement to determine whether the host
vehicle is changing lanes or whether the target vehicle is changing
lanes.
[0009] In another aspect of the present invention, the method
calculates a heading angle of the host vehicle and calculates a
corrected azimuth angle by adjusting the measured azimuth angle by
the value of calculated heading angle
[0010] In a further aspect of the present invention, the method
selects a curve that minimizes the mean square error between the
curve and selected targets, and determines an equation that
describes the curve, wherein the equation is used to predict the
path ahead of the host vehicle.
[0011] These and other aspects and advantages of the present
invention will become apparent upon reading the following detailed
description of the invention in combination with the accompanying
drawings.
BRIEF DESCRIPTION OF THE FIGURES
[0012] FIG. 1 illustrates a host vehicle having an adaptive cruise
control (ACC) system, in accordance with the present invention;
[0013] FIG. 2 illustrates a host vehicle following or tracking a
target vehicle, in accordance with the present invention;
[0014] FIG. 3 is a schematic diagram of a host vehicle traveling
along a road following target vehicles at a time ".kappa." and
".kappa.+1", in accordance with the present invention;
[0015] FIG. 4 illustrates a host vehicle tracking a group of
targets along a path preceding the host vehicle; and
[0016] FIG. 5 is a flowchart illustrating the method for
determining the curvature of a road.
DETAILED DESCRIPTION
[0017] Referring now to FIG. 1, a host vehicle 10 is illustrated
having an adaptive cruise control (ACC) system 12, in accordance
with the present invention. Adaptive cruise control system 12
includes a plurality of vehicle sensors for measuring various
vehicle dynamics parameters. For example, ACC system 12 includes a
yaw rate sensor 14 for measuring the yaw rate of host vehicle 10.
Other vehicle sensors include a speed sensor 16, for measuring
vehicle speed, and a range sensor 18 for detecting objects and
other vehicles (target vehicles) in front of host vehicle 10.
Further ACC system 12 includes, a control module 20 mounted within
host vehicle 10 and in communication with the various sensors, just
described, as well as vehicle subsystems such as the vehicle
braking system 24 and the vehicle acceleration system (not shown).
Preferably a controlled area network (CAN) bus 26 interconnects the
various sensors and vehicle subsystems to control module 20.
[0018] FIG. 2 is a diagram depicting host vehicle 10 following or
tracking a target vehicle 30. Range sensor 18, preferably is a
radar sensor that provides relative speed, azimuth angle and
distance information of target vehicle 30 or a plurality of
vehicles or other objects in the path of host vehicle 10. A fixed
radar beam 32 having a frequency of 76 GHz is transmitted from
radar sensor 18 for detecting moving objects such as target vehicle
30, as well as stopped objects such as guardrail 34.
[0019] In operation, ACC system 12 automatically adjusts the host
vehicle's speed and then returns host vehicle 10 to the set or
desired speed after the traffic clears. The ACC system 12 in order
to operate properly must determine, out of all of the vehicles and
objects in front of the host, which vehicle is the primary target.
In order to identify the primary in-lane target vehicle, a reliable
estimation of road curvature ahead of the vehicle must be
determined.
[0020] Referring now to FIG. 3, a diagrammatic representation of
host vehicle 10 equipped with an ACC system 12 is illustrated
traveling along a road 50, wherein road 50 has a left lane 52 and a
right lane 54. Host vehicle 10 is further shown following a target
vehicle 30. Further, road 50 is curved and has a radius of
curvature "r" about a center point 56. As host vehicle 10 travels
on road 52, radar sensor 18 measures the range, azimuth angle and
relative velocity between host vehicle 10 and target vehicle 30
which is in the same left lane 52 of road 50 as the host vehicle.
These radar measurements occur at a time ".kappa." and at a time
".kappa.+1". At time ".kappa.+1" host vehicle 10 has moved into
right lane 54 of road 50 and as illustrated target vehicle 30 also
has also moved into lane 54.
[0021] FIG. 3 further illustrates azimuth angle ".alpha." and
heading angle ".eta.". Heading angle ".eta." is a result of the
directional motion of host vehicle 10 from a first position
"p(.kappa.)" to a position "p(.kappa.+1)" on road 50. The azimuth
angle ".alpha." is a function of geometry and orientation of host
vehicle 10 with respect to the road 50. The geometry factor is a
result of the relative lateral distance between host vehicle 10 and
target vehicle 30, as well as the range between them. The
orientation of host vehicle 10 with respect to the road is effected
by the maneuvering of host vehicle 10 with respect to road 50. For
example, in the situation where the relative velocity between the
host and the target vehicles is zero, the azimuth angle varies as
the host vehicle is rotating around its axis even though the
geometry is not changing. In the non-zero relative speed situation,
any maneuvering of host vehicle 10 with respect to the road 50
affects the azimuth angle by both the geometry factor and the
orientation factor. On the other hand, the maneuvering of the
target vehicle with respect to the road effects the azimuth angle
measurement by the geometry factor only. Therefore, the geometry
factor variation is a combined result of the host and target
vehicle maneuvering.
[0022] In an aspect of the present invention, a method for
predicting road curvature is provided. As will be described
hereinafter, this method accounts for host vehicle maneuvering,
target vehicle maneuvering, and changes in the curvature of the
road.
[0023] The present invention assumes that the curvature of the road
remains constant between time samples ".kappa." and ".kappa.+1".
Thus, the variation in the curvature of the road is neglected. The
inventor of the present invention believes this to be a valid
assumption since the road curvature doesn't change rapidly.
Furthermore, the curvature of the road is presumed to follow a
circle.
[0024] The present invention addresses the difficult task of
distinguishing between a host vehicle maneuvering and a lead
vehicle maneuvering. This task is not trivial since both types of
vehicle maneuvering have almost a similar effect on the azimuth
angle measurement. One method is to look to the yaw rate
measurement of the host vehicle. This method, however, is not
reliable for two reasons: the first by the difficulty of
distinguishing the source of the yaw rate, i.e., is it a result of
a curve, lane change, or just a yaw rate bias, and second by the
noise and drift imposed on the yaw rate measurement. However, a
method found to be very reliable, is to follow this rule: when host
vehicle maneuvering occurs, all the azimuth angle measurements of
the targets in the radar field of view change in the same way,
while when a target vehicle maneuvers the azimuth angle measurement
of that specific target changes.
[0025] Referring now to FIGS. 4 and 5, a method for determining a
road's curvature will now be described. As shown in FIG. 4, host
vehicle 10 has a group of targets 60, 62 and 64 located at points
xi and yi along a path preceding host vehicle 10. Furthermore, host
vehicle 10 has a heading angle ".eta." that is defined as the angle
between a line tangent to the road and a direction the host vehicle
is heading in. A unique azimuth angle ".alpha." is associated with
each target 60, 62 and 64. Thus, an azimuth angle .alpha.' is the
angle between the road's tangent line and a line drawn between the
host vehicle 10 and target 60. Similarly, azimuth angle .alpha." is
the angle between the road's tangent line and the line drawn
between host vehicle 10 and target 62. Finally, the azimuth angle
.alpha.'" is defined as the angle between the road's tangent line
and a line drawn between host vehicle 10 and target 64.
[0026] With specific reference to FIG. 5, the method for
determining the curvature of a road is further illustrated. The
method is initiated at block 70, and at block 72, the ACC system of
the host vehicle measures the range, azimuth angle, and relative
velocity between the host vehicle 10 and each target. It is first
determined whether the target object, target vehicle or vehicles
are maneuvering, at block 74. At block 76, it is determined whether
the host vehicle is maneuvering. The method determines whether the
target or host vehicles are maneuvering by following predefined
rule: (1) the host vehicle is maneuvering, when all of the azimuth
angle measurements of all of the targets change in the same way; or
(2) that the target vehicle is maneuvering, when only the azimuth
angle of that target is changing and the azimuth angles of the
other targets are not changing. Once it is determined whether the
host vehicle is changing lanes or whether a target vehicle is
changing lanes, the heading angle of the host vehicle with respect
to the road may now be estimated. From the geometry of the road and
dynamics of the host vehicle, the heading angle ".eta." can be
estimated by solving the following differential equation, as
represented by block 80: 1 V h L x + = - where : V h = the host
vechicle speed ; L = the range between the host vehicle and the
target vehicle ; = the azimuth angle between the host vehicle and
the target vehicle .
[0027] L=the range between the host vehicle and the target
vehicle;
[0028] .alpha.=the azimuth angle between the host vehicle and the
target vehicle.
[0029] The targets coordinates of each target are mapped, as
represented by block 82. Further, the method corrects the mapped
target coordinates by adjusting (rotating) the mapped target
coordinates by the calculated heading angle, as represented by
block 84. At block 86, the curvature of the road is calculated
fitting a curve through the mapped target coordinates x.sub.i and
y.sub.i. An optimal curve is selected that minimizes the mean
square error of the differences between the curve and each target
location. The curve is constrained to be a circle. Thus, the
following equation may be used to calculate the center of an
optimal circle through the targets: 2 X c = ( i = 1 N x i 3 + i = 1
N x i y i 2 - i = 1 N x i y i i = 1 N y i 2 ( i - 1 N y i 3 + i = 1
N x i 2 y i ) ) 2 ( i = 1 N x i 2 - ( i = 1 N x i y i ) 2 i = 1 N y
i 2 ) y c = ( i = 1 N y i 2 + i = 1 N x i 2 y i - 2 x c i = 1 N x i
y i ) 2 i = 1 N y i 2
[0030] The radius of curvature of the optimal circle through the
targets may be calculated using the equation:
(x.sub.i-x.sub.c).sup.2+(y.sub.i-y.- sub.c).sup.2=r.sup.2. Next, at
block 88, a conventional method for calculating road curvature
using yaw rate is utilized to identify an alternate road curvature
calculation. This conventional curvature calculation using yaw rate
is for example, similar to the method disclosed in U.S. Pat. No.
5,926,126 entitled "Method And System For Detecting An In-Path
Target Obstacle In Front Of A Vehicle" and is incorporated herein
by reference. Furthermore, a final road curvature is calculated by
fusing (combining) the two calculations mv,x.z. Fusion of the yaw
rate based road curvature calculation and target based road
curvature calculation is achieved by following the following rule
as the change in the yaw rate increases the weight of the yaw-rate
based curvature decreases, and as the number of targets increases
the weight of the target based curvature increases.
[0031] As any person skilled in the art of geometric based path
prediction methods will recognize from the previous detailed
description and from the figures and claims, modifications and
changes can be made to the preferred embodiments of the invention
without departing from the scope of this invention defined in the
following claims.
* * * * *