Transcript Document 7236252

Issues in measuring sensory-motor
control performance of human drivers:
The case of cognitive load and steering
control
Johan Engström, Volvo Technology Corporation
European Workshop on Advanced Predictive Sensory-motor Control
Joudkrante, Lithuania, 2009-05-21
Outline
 Multitasking in the vehicle
– Secondary tasks – visual and cognitive
– The primary driving task – visual control of steering
 Effects of secondary tasks on steering control
– Different effects of visual and cognitive tasks
– The ”lane keeping improvement” effect of cognitive load
 Possible explanation in terms of satisficing vs. optimising steering
control
 Testing predictions implied by this hypothesis
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Multitasking in the vehicle: Driving + secondary
tasks
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Secondary tasks: Visual vs. cognitive
distraction
 Visual distraction
– Looking off road
– E.g. Visual time sharing when tuning the radio
 Cognitive distraction:
– Engaging in demanding cognitive (working memory) tasks
– E.g. Mobile phone conversation
 Most real-world tasks involve both components…
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The primary driving task: Sensory-motor
control in steering
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The visual control of steering: Optical and
retinal flow
Straight driving,
looking ahead
Straight driving,
looking to the left side
Retinal flow not equal to optical flow
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Wann and Wilke (2000)
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Using retinal flow patterns to guide
steering: Look where you’re going
resulting heading
Underrsteering
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initial heading
Going towards target
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Wann and Wilke (2000)
Oversteering
Gaze angle can be used as a direct cue for
steering through curves (Land, 1998)
1
2
Curvature   2 sin
r
2d
Fixate tangent point and adjust
steering to keep
gaze angle constant
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Combining retinal flow patterns and gaze direction:
”Spring” model (Wann and Wilkie, 2000)
e  k (1RetinalFlo w  2VisualDire ction )  be
Stiffness
Angular
acceleration
Reliance on cues
Damping
Main point: Foveal vision is essential
for accurate steering!
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Effects of secondary tasks on steering
control
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0
0
0
0
0
5
0
Effects of visual distraction on
lateral control
D rive r 7 , stra ight rura l roa d
Baseline
Baseline
50
40
30
20
10
 Looking away
120
130
140
 Heading error builds up
130
140
5
5
5
940
960
Steering wheel
angle
Increased
lane
-0.5
120
130
140
940 position
950
variance
 Large steering wheel correction
 Speed reduction to compensate
70
Lane position
130
140
Time (s)
1000
1010
1020
1000
1010
1020
0
-0.5
960
85
Speed
75
120
1020
0
960
85
5
1010
0.5
0
80
1000
-5
950
0.5
 Looking back
50
40
30
20
10
5
940
0
0
950
-5
120
Visual task, level 3
Gaze angle
 Loosing visual input for steering5
control
0
5
0
Visual time sharing
80
75
70
940
950
960
Time (s)
1000
1010
1020
Time (s)
Engström and Markkula (2006)
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What about purely cognitive distraction?
 Large number of simulator and real-world driving studies found reduced
lane keeping variance during cognitive load (Brookhuis et al., 1991;
Östlund et al., 2004; Jamson and Merat, 2005; Engström et al., 2005;
Mattes, Föhl and Schindhelm, 2007; Merat and Jamson, 2008).
Does talking on the mobile
phone really improve
steering control?
SD lane position
Engström, Johansson and Östlund (2005)
Cognitive task difficulty
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Other effects of cognitive distraction:
Gaze concentration
Victor, Harbluk and Engström (2005)
Normal driving
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Cognitive task
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SW reversals/min
Other effects of cognitive distraction: Increased
steering activity (number of steering reversals
> 2 deg. per minute)
Engström et al. (2005)
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Summary: Effects of cognitive distraction
related to lateral control
 Improved lane keeping (!?)
 Gaze concentration towards the road centre
 Increased number of micro steering corrections (<2 deg)
 How are these effects related? How can they be
explained?
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Possible explanation
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Two key distinctions
1. Satisficing vs. Optimising
2. Top-down (endogenous) vs. Bottom-up (exogenous)
attention selection
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1. Satisficing vs. optimising
Target value
Comfort zone
Optimising: Minimising performance
error relative to a target state.
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Satisficing: Maintaining performance
within acceptable boundaries.
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Example cost functions of optimising and satisficing
in lane keeping
Cost
Optimising
Satisficing
Lane position
Lane centre
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Example dynamics of satisficing and optimising
x  10 x
X_dot
x  0.5 x  0.5 x 3
Satisficing
Comfort
zone
Optimising
X
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Simulations
x  0.5 x  0.5 x 3
x  10 x
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Satisficing
Optimising
2. Bottom-up and
top-down attention
selection
Top-down
attention bias
Top-down
selection
Cognitive task
Other visual
task
Steering
Bottom-up
selection
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Vehicle
dynamics
Normal driving
Steering easy and
automated task,
bottom-up-driven ->
satisficing
Top-down
attention bias
Top-down
selection
Other visual
task
Vehicle
dynamics
Steering
Spare top-down
attentional resources used
for other visual tasks
Bottom-up
selection
visual
time
sharing
•Lane keeping variance
•Distributed gaze
•Only intermittent steering
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Cognitive load
Top-down
attention bias
Top-down attention allocated
to cognitive task
Cognitive task
Other visual
task
No top-down-initiation of
other visual tasks
Steering
Gaze can be fully devoted
to steering (attracted
bottom-up)
Bottom-up
selection
• Reduced lane keeping
variance
• Gaze concentration
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Top-down
selection
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Vehicle
dynamics
Testable predictions
 General: Improved lane keeping should only occur if the
driver is satisficing in baseline condition
 Specific predictions:
1. Improved lane keeping should not occur if the steering task is difficult (so
that satisficing is not possible)
2. Improved lane keeping effect should not occur if the driver is motivated to
optimise lane keeping
 Support for prediction 1
–
–
Cognitive load has been demonstrated to impair performance on tracking
tasks (Creem and Proffitt, 2001; Strayer and Drews. 2001).
These tasks could be expected to be more difficult and/or less automated
than normal driving
 Prediction 2: Tested experimentally…
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Instruction to optimise
steering (baseline)
Top-down attention allocated
to steering task and cognitive task
Top-down
attention bias
Top-down
selection
Other visual
task
Optimising steering
performance
• Reduced lane keeping
variance
• Gaze concentration
• Increased steering
wheel control input
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Steering
Bottom-up
selection
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Vehicle
dynamics
Testing prediction 2: Experimental design
 Simulator study in fixed based simulator (at Saab Automobile, Trollhättan)
 Cognitive task: Count backwards with 7
 48 subjects, split in 4 groups:
Instruction to keep in the
middle of the lane
Cognitive
task
Yes
No
Yes
Group 1
Group 3
No
Group 2
Group 4
 Incentive for group 1 and 2: Two cinema tickets instead of one if meeting some
(unspecified) lane keeping criterion
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Prediction
 Lane keeping improvement effect of cognitive load should only occur
when the driver is not motivated to optimise lane keeping = satisficing
 Interaction between cognitive load and instruction to optimise
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Preliminary results: Lane keeping (HPfiltered SD Lane Position)
No cognitive task
Effect only for non-instructed subjects
Cognitive task
Due to satisficing in baseline condition
No instruction
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Instructed to
optimise lane keeping
Steering wheel reversal rate
Cognitive task
Same effect in both conditions
Cognitive load less efficient optimising:
more steering – same lane keeping
performance
No cognitive task
No instruction
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Instructed to
optimise lane keeping
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Still to be analysed…
 Eye movements
 Speed change
 Performance on cognitive task
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Discussion
 Replicated earlier findings for non-instructed drivers:
– Reduced lane keeping performance
– Increased steering wheel activity
 Predicted effect of instructions found -> improved lane
keeping only for non-instructed drivers – due to satisficing
in baseline condition
 Cognitive load seems to induce less efficient steering while
optimising (more effort in steering, same result on lane
keeping)
 Cognitive task does not really improve steering ability-> the
effect rather reflects ”involuntary” improvement from
”sloppy” baseline driving
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General conclusions
 Caution is needed when interpreting driving performance
measurements – do we compare to a baseline with
satisficing or optimising performance?
 In this case, changing instructions and/or driving task
difficulty may cancel or perhaps even reverse the effect of
cognitive load
 Implies re-interpretation of many existing studies on the
effects of cell phone conversation on driving performance
(e.g. Strayer and Drews, 2001)
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