Page 102 - Dynamic Vision for Perception and Control of Motion

3 Subjects and Subject Classes
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Steering rate u ff (t) = dO / dt ĺ piecewise constant control input:
A, 0, íA íA, 0, A)
A Lateral drift period T D
Point symmetry for steer angle O Time
0
0 W
W 0.5 *T HC T HC
u ff (t)
T SR Steering angle O
íA T SR
(state variable)
Mirror plane for control u ff (t)
Initial pulse Final pulse
{symmetry on time line}
Figure 3.16. High-speed lane change maneuver with two steering “pulses”, including a
central constant lateral acceleration phase of duration W at the beginning and end, as well
as a straight drift period T D in between; the duration T D is adapted such that at the end of
the second (opposite) pulse, the vehicle is at the center of the neighboring lane driving
tangentially to the road. The maneuver control time history u ff (t) = dO/dt for lane change
at higher speeds is [legend: magnitude(duration)]: A(T SR ), 0(W), íA(T SR ), 0(T D ), íA(T SR ),
0(W), íA(T SR )
Table 3.3 shows in column 2 a list of standard maneuvers for ground vehicles
(rows 1 – 6 for longitudinal, 7 – 11 for lateral, and 12 –18 for combined longitudi-
nal and lateral control). Detailed realizations have been developed by [Zapp 1988,
Bruedigam 1994; Mueller 1996; Maurer 2000; and Siedersberger 2003]. Especially the
latter two references elaborate the approach presented here.
The development of behavioral capabilities is an ongoing challenge for autono-
mous vehicles and will need attention for each new type of vehicle created. It
should be a long–term goal that each new autonomous vehicle is able to adapt to its
own design parameters at least some basic generic behavioral capabilities from a
software pool by learning via trial and error. Well-defined payoff functions (quality
and safety measures) should guide the learning process for these maneuvers.

3.4.3.2 Feedback Control

Suitable feedback control laws are selected for keeping the state of the vehicle
close to the ideal reference state or trajectory; different control laws may be neces-
sary for various types and levels of perturbations. The general control law for state
feedback with gain matrix K and 'x = x C í x (the difference between commanded
and actual state values) is
T
u (kT ) = K ˜ ǻx(kT . (3.22)
)
fb
For application to the subject vehicle, either the numerical values of the ele-
ments of the matrix K directly or procedures for determining them from values of
the actual situation and/or state have to be stored in the knowledge base. To
achieve better long-term precision in some state variable, the time integral of the
error 'x i = x Ci í x i may be chosen as an additional state with a commanded value of
zero.
For observing and understanding behaviors of other subjects, realistic expected
perturbations of trajectory parameters are sufficient knowledge for decision–