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Environmental variables in the "moth effect"

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Conference Paper

Environmental variables in the "moth effect"

Abstract

The "moth effect" represents the tendency drivers show to steer in the direction of their fixation, often at night, toward vehicles parked on the roadside. It has been hypothesized that this phenomenon is responsible for a high number of vehicular accidents. Here, this issue is addressed with regard to the nature of the environment and the object of fixation. Prior work was based on a textured, but empty, visual landscape, and a fixation point at one particular location on the viewing screen. Building on this, two experiments were carried out in a driving simulator. Participants were instructed to steer down the center of a straight road, while maintaining fixation, which was controlled at -15, 0, or +15 degrees from center screen. In the first experiment, the richness of the environment was manipulated with the addition of numerous trees on the roadside, thus potentially providing the driver with increased optical flow, depth ordering, and velocity information. In the second experiment, the fixation point was changed from a location in screen coordinates, resembling gaze at an object in the interior of a car (e.g. a spot on the windshield), to a location in the environment. Participants thus fixated an object which was located in the car‘s exterior and drew nearer over the course of a trial. The dependent measure of interest was lateral position on the road. The results confirmed previous findings that drivers exhibit a systematic tendency to steer towards their looking direction (p < 0.05), independent of whether the target of observation was planted in the car‘s interior or exterior. However, we found that the addition of trees to the environment resulted in an attenuation of the "moth effect" (p < 0.05), indicating a compensatory role of a rich visual environment. Currently, we are investigating whether this result may alternatively be explained by a different gaze behavior or reduced fixation time on the target in crowded environments. The present data and eye-movement analyses will be discussed in terms of environmental conditions and driver safety.
VIV 10 MPI for Biological Cybernetics Chatziastros 1
Environmental Variables in the "Moth Effect"
Astros Chatziastros - Wilson Readinger - Heinrich Bülthoff
Max Planck Institute
for Biological Cybernetics
Tübingen, Germany
VIV 10 MPI for Biological Cybernetics Chatziastros 2
Moth Effect?
Term in the popular literature
Used as a metaphor for high involvement
of civil with police cars
Do we steer
where we look?
Driver instructor
manuals
Reports of profes-
sional drivers
Recent EC guidelines
for driving education
Prospective use of gaze
and tight gaze-steering
coordination
Land (90's)
Rogers, Kadar (VIV10)
Anticipatory saccades
in turns while walking
Hollands, 2001
Grasso, 1998
Tight gaze-hand
coordination in manual tasks
Ballard, 92; Pelz, 01
VIV 10 MPI for Biological Cybernetics Chatziastros 3
Paradigm
Observational task: "Press button
when gap of the Landolt-C is right"
Driving task: "Drive in the middle
of the road"
Trial:
0 s: start
5 s: target jumps form 0 to X deg
5-30s: one to six response to make
0-30s: continuously steering
VIV 10 MPI for Biological Cybernetics Chatziastros 4
Paradigm
top down
driver's view
Target fixed on screen
VIV 10 MPI for Biological Cybernetics Chatziastros 5
Typical Result
Factor Ecc.
F(6,42)=10.7 p<0.01
Forward velocity 20 m/s
Dependent Variable: Mean of lateral position 5-30 s
VIV 10 MPI for Biological Cybernetics Chatziastros 6
Small Eccentricities
Factor Ecc.
F(6,42)=7.32 p<0.01
VIV 10 MPI for Biological Cybernetics Chatziastros 7
Reverse Steering
Factor Ecc.
F(6,42)=5.88 p<0.01
... after 50 trials training
VIV 10 MPI for Biological Cybernetics Chatziastros 8
No Forward Speed
... but heading and lateral changes preserved
Factor Ecc.
F(6,42)=9.15 p<0.01
VIV 10 MPI for Biological Cybernetics Chatziastros 9
Summary Uno
Driving where we look?
Lateral deviations towards fixated target
With target eccentricities as small as 5°
Not an effect of body posture
Dependence on speed
Readinger et al. (2002) JEP:Applied
VIV 10 MPI for Biological Cybernetics Chatziastros 10
Limitations
Observational target so far:
fixed in screen coordinates
(~bug on the windscreen)
changes in heading not accompanied by changes in target
location (driver relative)
harder to detect heading changes?
Impoverished environment as well:
open field, no objects
real-world offers more motion parallax information
Do findings generalize when observing targets outside
the car and in visually richer environments?
VIV 10 MPI for Biological Cybernetics Chatziastros 11
Modified Paradigm
Three-factorial repeated-measures design (n=18)
Placement of target (blocked)
(screen / environment)
Complexity of environment
(trees absent / present)
Eccentricity
(-15°, , 15°)
Placement in environment:
Scaled, distant target, at 14°-16°
Trees condition:
On each side, 58 tress in two rows,
at lateral distance of 50-100 m
VIV 10 MPI for Biological Cybernetics Chatziastros 12
Results
Factor Ecc.
F(2,32)=9.66 p<0.01
Interaction
Ecc. x Trees
F(2,32)=9.17 p<0.01
No effect of target placement
VIV 10 MPI for Biological Cybernetics Chatziastros 13
Results
Position difference 15° to -15°
Factor Trees
F(1,16)=12.4 p<<0.01
VIV 10 MPI for Biological Cybernetics Chatziastros 14
Results
Detection performance
response classified as correct, if RT<1500 ms
mean = 0.91 mean = 755 ms
n.s.
n.s.
VIV 10 MPI for Biological Cybernetics Chatziastros 15
Results
Detection performance
However, if target location is at 0°, detection
performance is increased compared to +/- 15°
detection rate: 0.95 vs. 0.91 (p<0.05)
reaction time: 732 vs. 755 ms (p<0.05)
Visually more complex environment did not lead to
decreased detection performance
Reduced effort in the detection task can't account
for the decreased lateral deviations in the more
complex environment with trees
VIV 10 MPI for Biological Cybernetics Chatziastros 16
Results
Standard deviation in 0°-condition
Complex environment > Enhanced motion signal (higher motion energy)
> Deviations from straight ahead easier detected?
If so, lane keeping performance in 0°-condition should be more accurate
n.s.
VIV 10 MPI for Biological Cybernetics Chatziastros 17
Summary Dos
Lateral deviations towards observed target
independent of target location
(interior/exterior)
More complex environment attenuates the
bias to drive towards the fixation (but
doesn't eliminate it)
Reason for this attenuation unclear (not
due to reduced effort or highly
perceptible motion information)
VIV 10 MPI for Biological Cybernetics Chatziastros 18
Thank You
VIV 10 MPI for Biological Cybernetics Chatziastros 19
Current Thinking
... a whole bag of speculations
steering bias ≈ correction of a curvilinear path
reason for a perceived curvilinear path: mismatch
between actual seen and expected motion
when driving straight and looking to the side, we expect to see some motion
an adequate expectation has to take into account three variables,
which determine angular velocity: rel. velocity, distance, and eccentricity
= (sinq)
2
dq
dt
v
x
angular velocity:
when is 'seen' > 'expected'?:
if 'expected' is based on
- slower velocity
- larger distance
- smaller eccentricity
VIV 10 MPI for Biological Cybernetics Chatziastros 20
Current Thinking
... speculations continue
- slower velocity
- larger distance
- smaller eccentricity
general underestimation,
or, simulation artefact
trees condition: does scale
information gives a more veridical
distance estimate?
fading out of eye position signal
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