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Effects of visual and cognitive load on the Lane Change Test – preliminaryresults

Johan Engström &Gustav MarkkulaVolvo Technology Corporation

Driver Metrics WorkshopOttawa October 2-3, 2006

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Background

• Existing results from (HASTE and other studies) show that visual and cognitive tasks have rather different effects on driving• Effects of visual tasks

• Reduced lateral control (increased standard deviation of lane position)

• Reduced event detection performance (e.g. PDT)

• Speed/headway compensation

• Effects of cognitive tasks• Improved lateral control (reduced variance of lane position)

• Gaze concentration towards road centre

• Reduced event detection performance

• No speed/headway compensation

• Visual and cognitive tasks both result in increased LCT normative path deviation – but could this common effect have different origins?

• Discussed at LCT TF meeting in Shonen Village in connection to reference tasks…

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Visual vs. cognitive tasks - definitions

• Purely visual=requires diversion of gaze from the road centre but no cognitive activity (e.g. just looking back and forth…)

• Purely cognitive=does not require gaze diversion (e.g. phone conversation, speech interaction etc.)

• In practice, most visual tasks involve a cognitive component – however, the degree of cognitive load varies (e.g. for the Arrows and Circles tasks the cognitive load could be assumed to be minimal)

• However, many real tasks could be regarded as purely cognitively loading

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Hypotheses tested

• Visual tasks mainly lead to reduced lateral control during the lane changes but also (to a lesser degree) to reduced detection performance

• Cognitive tasks mainly lead to late or erroneous detection

• Thus, both tasks lead to increased deviation from the normative path, but (partly) for different reasons

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Existing work: Mattes et al. (in AIDE D2.2.5, Östlund et al., 2005)

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Results, Mattes et al. (in AIDE)

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Method

• Same data as used by Mattes et al. in AIDE

• 30 subjects (subset of data in the study)

• No task priority in instructions

• Sign: content pop-up

• Secondary tasks:• Cognitive easy: Count up by 2

• Cognitve hard: Count down by 7

• Visual easy: ”Ring detection task” – large difference between rings

• Visual hard: ”Ring detection task” – small difference between rings

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Results: First qualitative analysis, example 1

= detection/interpretation

errors

= loss of control

= Baseline

= Cognitive (easy +hard)

= Visual (easy+ hard)

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= detection/interpretation

errors

= loss of control

= Baseline

= Cognitive (easy +hard)

= Visual (easy+ hard)

Results: First qualitative analysis, example 2

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= detection/interpretation

errors

= loss of control

= Baseline

= Cognitive (easy +hard)

= Visual (easy+ hard)

Results: First qualitative analysis, example 3

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Results: First qualitative analysis – manual classification of errors

Detection/Interpretation errors

0

5

10

15

20

25

30

Baseline Cognitive Visual

Control errors

0

2

4

6

8

10

12

14

16

18

Baseline Cognitive Visual

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First conclusions from qualitative analysis

• Qualitative analysis seems to support the hypothesis:• Visual task mainly leads to errors related to reduced control, but also

some detection errors

• Cognitive task almost only lead to detection/interpretation errors

• But can these effects be quantified?

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Preliminary results of quantitative analysis

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Quantifying loss of control (I): Mean difference of lateral position (~mean lateral velocity)

0.006

0.0065

0.007

0.0075

0.008

0.0085

0.009

0.0095

0.01

0.0105

Baseline CogEasy CogHard VisEasy VisHard

Task

Me

an

dif

fere

nc

e o

f la

tera

l p

os

itio

n

Baseline CogEasy CogHard VisEasy VisHard

Baseline --- 0.668 0.095 0.000 0.000

CogEasy --- 0.995

CogHard ---

VisEasy --- 1.000

VisHard ---

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Quantifying loss of control (II): High-pass filtred standard deviation of lateral position

0.5

0.55

0.6

0.65

0.7

0.75

0.8

Baseline CogEasy CogHard VisEasy VisHard

Task

SD

La

tera

l po

sit

ion

(h

igh

-p

as

s f

ilte

red

0.1

Hz)

Baseline CogEasy CogHard VisEasy VisHard

Baseline --- 0.687 0.233 0.000 0.000

CogEasy --- 1.000 --- ---

CogHard --- --- ---

VisEasy --- 0.790

VisHard ---

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Towards quantifying missed detection/interpretation Fraction consistent lane selected (any single lane selected

>75% of distance between two signs)

0.7

0.75

0.8

0.85

0.9

0.95

Baseline CogEasy CogHard VisEasy VisHard

Task

Fra

cti

on

co

ns

iste

nt

lan

e

se

lec

ted

Baseline CogEasy CogHard VisEasy VisHard

Baseline --- 0.735 0.060 0.000 0.000

CogEasy --- 0.972

CogHard ---

VisEasy --- 0.119

VisHard ---

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Quantifying missed detection/interpretation: Fraction correct lane selected (of those consistently selected)

Baseline CogEasy CogHard VisEasy VisHard

Baseline --- 0.000 0.000 0.000 0.000

CogEasy --- 0.000

CogHard ---

VisEasy --- 0.000

VisHard ---

0.8

0.85

0.9

0.95

1

1.05

Baseline CogEasy CogHard VisEasy VisHard

Task

Fra

cti

on

co

rre

ct

lan

e s

ele

cte

d

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Qualitative analysis of CogEasy vs. CogHard

0 500 1000 1500 2000 2500 3000

-5

0

5

Segment 1 (1 bl, 0 cog easy, 0 cog hard)

3000 3500 4000 4500 5000 5500 6000 6500

-10

0

10

Segment 2 (10 bl, 2 cog easy, 6 cog hard)

6500 7000 7500 8000 8500 9000 9500

-10

0

10

Segment 3 (4 bl, 7 cog easy, 3 cog hard)

0.95 1 1.05 1.1 1.15 1.2 1.25 1.3

x 104

-10

-5

0

5

Segment 4 (6 bl, 5 cog easy, 4 cog hard)

1.3 1.35 1.4 1.45 1.5 1.55 1.6 1.65

x 104

-10

0

10

Segment 5 (18 bl, 2 cog easy, 4 cog hard)

1.6 1.65 1.7 1.75 1.8 1.85 1.9 1.95

x 104

-10

0

10

Segment 6 (16 bl, 4 cog easy, 3 cog hard)

1.95 2 2.05 2.1 2.15 2.2 2.25

x 104

-10

0

10

Segment 7 (8 bl, 0 cog easy, 4 cog hard)

2.25 2.3 2.35 2.4 2.45 2.5 2.55 2.6

x 104

-10

0

10

Segment 8 (13 bl, 5 cog easy, 2 cog hard)

2.6 2.65 2.7 2.75 2.8 2.85 2.9 2.95

x 104

-10

0

10

Segment 9 (6 bl, 3 cog easy, 2 cog hard)

2.95 3 3.05 3.1 3.15 3.2 3.25

x 104

-10

0

10

Segment 10 (8 bl, 2 cog easy, 2 cog hard)

Almost all errorsoccur for CogHard..

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Conclusions

• Cognitive and visual tasks have different effects on lane changes• Cognitive tasks leads only to detection/interpretation errors – changing to wrong

lane or continuing straight ahead (mainly for CogHard)• Visual tasks mainly induce control errors (”overshoots”) but also some

detection/interpretation errors• These different effects clearly visible from qualitative analysis of lane

change plots• The effects can also be differentiated in quantitative analysis• Present quantitative results very preliminary – further analysis needed• Late detections not yet looked at (promising results from Trbovich)

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How can these results be used in the LCT development?

• Provides a stronger scientific basis for the LCT – better understanding of why the deviation metric is so sensitive to both visual and cognitive load

• Consequences for calibration tasks – both visual and cognitive reference tasks needed (at least in theory)

• Specific ”control error” or ”detection error” metrics could be used to quantfy the visual and cognitive components (as complement to the standard LCT metric)