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Preferred citation style Axhausen, K.W. (2015) Survey challenges, modelling challenges, keynote presentation at the 3rd IWATS (International Workshop on Advanced Transport Studies) “International workshop on context and social interactions in activity and travel decisions”, University of Hiroshima, March 2015. . IDEC 2015

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Page 1: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Preferred citation style!

!!!!Axhausen, K.W. (2015) Survey challenges, modelling challenges,

keynote presentation at the 3rd IWATS (International Workshop on Advanced Transport Studies) “International workshop on context and social interactions in activity and travel decisions”, University of Hiroshima, March 2015.!

.!

IDEC 2015

Page 2: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Survey challenges, modelling challenges

KW Axhausen IVT ETH Zürich March 2015

Page 3: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Survey challenges

IDEC 2015

Page 4: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Do we know the numbers? e.g. daily activities in Switzerland

0.0

0.5

1.0

1.5

2.0

2.5

3.0

0 10 20 30 40 50 60 70 80 90 100 110

Num

ber

of A

ctiv

ities

Average Cohort Age [Years]

before 1910!

1910-19!

1920-29!

1930-39!

1940-49!

1950-59!1960-69!1970-79!

1980-89!

1990-1999!

after 1999!

IDEC 2015

Page 5: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

What do we want to know?

Who travels

when ?

where ?

with whom ?

how ?

for how long (space and time) ?

for what purpose ?

and spends how much ?

IDEC 2015

Page 6: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Protocols and response

IDEC 2015

Page 7: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Surveys, observations are „talk“

Two speakers

managing their „image“ staying within the rules of talking staying within their socially allocated/identified role fulfilling social expectations

talk and report with/to each other

=>

„Maintaing the willingness of the respondent to report“

IDEC 2015

Page 8: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Response as a function of response burden @IVT, 2013

0"

10"

20"

30"

40"

50"

60"

70"

80"

90"

0" 200" 400" 600" 800" 1000" 1200" 1400" 1600"

AAPO

R"respon

se"ra

te""[%]"

A;priori"es=mate"of"the"response"burden"

None"Only"mo=va=on"call"Prior"recruitment"Prior"recruitment"&"incen=ve"Predicted"

IDEC 2015

Page 9: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Response is a non-random process

0"

200"

400"

600"

800"

0.0"

100.0"

200.0"

300.0"

400.0"

Wave"1" Wave"2" Wave"3" Non1response"survey"

Num

ber""of"

Target"value

"

Observed"True"mean"

Sample"Respondents"

IDEC 2015

Page 10: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Known „error“ generating processes

IDEC 2015

Page 11: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Activities, movement and traces: A full example record

6 12 18

Home Out of home Movement Phone/SMS Email Smart card GPS Bluetooth WiFi IDEC 2015

Page 12: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Active/passive tracing: Many owners, locations, quality levels

6 12 18

Phone/SMS Email Smart card GPS Bluetooth WiFi CCTV

IDEC 2015

Page 13: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Filters imposed/suggested by the study: „Trips“

6 12 18

Home Out of home Movement After “trip” filter:

Home Out of home Movement

IDEC 2015

Page 14: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Filters due to the respondent: Forgetting

6 12 18

Home Out of home Movement After forgetting

Home Out of home Movement

IDEC 2015

Page 15: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Filters imposed by the respondent: Soft non-response

6 12 18

Home Out of home Movement After soft non-response

Home Out of home Movement

IDEC 2015

Page 16: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Filters due to the respondent: Rounding

6 12 18

Home Out of home Movement After rounding

Home Out of home Movement

IDEC 2015

Page 17: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

What is left ?

After all processes 3 at home 2 Out of home 4 trips, 2 tours

True 5 at home 9 Out of home 26 Stages, 11 trips, 1 subtour, 2 tours

IDEC 2015

Page 18: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

What happens next ?

IDEC 2015

Page 19: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Geocoding addresses

Ideal Street addresses identifying the entry to the

network Best-case Unambiguous street addresses State of the art Street address State of practice Street address/mid-street block/street corners;

missing conversion of facility names Still seen in practice Arbitrary zonal centroid, e,g post offices

IDEC 2015

Page 20: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Calculating distances & travel time

Ideal Complete GPS track for distance and times

with pedestrian-networks added Best-case Minimal gaps, and state-of-the-art imputation

of GPS tracks and modes State of the art SUE derived travel times and distances

(navigation network) State of practice DUE derived travel times and distances

(planning networks) Still seen in practice Shortest path on empty planning networks IDEC 2015

Page 21: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

What should we do ?

IDEC 2015

Page 22: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Next steps

•  Query what we really need for

•  Cost-benefit analysis •  Planning of prices and services •  Planning for the slow modes •  Social accounting

•  High-quality multi-modal surveys to establish the measurement errors (add bluetooth and wifi senders, noise profile)

•  Error correction models •  Cross check against third party sources

•  Treat survey data as indicators in a measurement model •  Treat traces as indicators in a measurement model

IDEC 2015

Page 23: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

, but especially

•  Treat respondents as partners in a talk, discussion:

•  Frame your request in a way which addresses them in a clearly defined social role (citizen, driver, customer, etc.)

•  Account for their constraints (readability of text, full guidance through the forms, require no calculations – unless necessary, speak their ‘language’)

•  Be as complex, as the topic warrants, requires, but not more so

•  Don’t surprise them with unannounced requests •  Don’t ask them to do work you can do

•  If appropriate, provide an incentive, acknowledgement

IDEC 2015

Page 24: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Modelling challenges

IDEC 2015

Page 25: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Modelling challenges: The usual worries

Error heterogenity Is it always checked ? Spatial correlations Are they always checked ? Temporal correlations Are they always checked ? Independence Do we check the correlations of the

independent variables (sample) thoroughly enough?

Endogenity Do we fully account for it ? (sample selection) Error of the second Do you calculate it ? kind Validation How often do we ask for out-of-sample tests? Substance or do we talk about t-tests ? IDEC 2015

Page 26: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Modelling challenges: Substance or t-tests ?

Effect size

t-stats 1.96

small

large

Adap

ted

from

Zill

iak

and

McC

losk

ey (2

008)

IDEC 2015

Page 27: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Modelling challenges: Substance or t-tests ?

Effect size

t-stats 1.96

small

large

Adap

ted

from

Zill

iak

and

McC

losk

ey (2

008)

Yes, but anything new ?

IDEC 2015

Page 28: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Modelling challenges: Substance or t-tests ?

Effect size

t-stats 1.96

small

large

Adap

ted

from

Zill

iak

and

McC

losk

ey (2

008)

Yes, but anything new ?

Fair enough, but do we know why?

IDEC 2015

Page 29: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Modelling challenges: Substance or t-tests ?

Effect size

t-stats 1.96

small

large

Adap

ted

from

Zill

iak

and

McC

losk

ey (2

008)

Yes, but anything new ?

Fair enough, but do we know why?

OK, but are there surprises?

IDEC 2015

Page 30: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Modelling challenges: Substance or t-tests ?

Effect size

t-stats 1.96

small

large

Adap

ted

from

Zill

iak

and

McC

losk

ey (2

008)

Yes, but anything new ?

Fair enough, but do we know why?

OK, but are there surprises?

Now, this is interesting

IDEC 2015

Page 31: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Modelling challenges: Substance or t-tests ?

Effect size

t-stats 1.96

small

large

Adap

ted

from

Zill

iak

and

McC

losk

ey (2

008)

Yes, but anything new ?

Fair enough, but do we know why?

OK, but are there surprises?

Now, this is interesting

IDEC 2015

Page 32: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Choice modelling challenges

IDEC 2015

Page 33: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Choice modelling challenges: The usual worries

Error heterogenity Is it always checked ? Spatial correlations Are they it always checked ? Independence Do we check the correlations of the

independent variables (sample) thoroughly enough?

Endogenity Do we fully account for it ? (sample selection) Error of the second Do you calculate it ? kind Validation How often do we ask for out-of-sample tests? Substance or do we talk about t-tests ? IDEC 2015

Page 34: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Choice modelling challenges: less usual concerns

Error heterogenity Why don’t we check them ? Number of non-chosen How much leverage do they have alternatives for your problem? Number of choice sets How stable are our estimates? Capacity constraints Do we check for their impact on the

parameters? (attribute values of the known (non)chosen alternatives)

Unit of analysis Do we have a MAUP problem?

IDEC 2015

Page 35: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Residuals: False positives of a membership model So

urce

: Kop

p (F

orth

com

ng)

IDEC 2015

Page 36: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Residuals: MCDEV model of fleet choice So

urce

: Jäg

gi (F

orth

com

ng)

IDEC 2015

Page 37: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Number of non-chosen alternatives: routes So

urce

: Sch

üssl

er (2

010)

IDEC 2015

Page 38: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Number of choice sets: residential choice Ad

apte

d fr

om: S

chirm

er (F

orth

com

ing)

IDEC 2015

Page 39: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Accounting for consistency

IDEC 2015

Page 40: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Learning approach of the generic one-day transport model

Competition for slots on networks and in facilities

Activity scheduling

k(t,r,j)i,n

qi ≡ (t,r,j)i,n

Mental map

IDEC 2015

Page 41: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Model estimation: betai,0 = betai,n? betai,n-1 = betai,n?

Competition for slots on networks and in facilities

Activity scheduling

k(t,r,j)i,n

qi ≡ (t,r,j)i,n

Mental map

IDEC 2015

Parameter estimation

betai,n

betai,0

Page 42: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

IDEC 2015!

Model estimation: betai,0 = betai,n? Route and mode

-1.5

-1

-0.5

0

0.5

1

Konstante Skalierungsparam. Zeit Preis alfa f. Gem.F.

Par

amet

er

Kalibrationsschritt

Sour

ce: V

frtic

(200

3)

Page 43: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Do we have a MAUP problem ?

IDEC 2015

Page 44: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Do we have a MAUP-like problem for DCM?

•  Location choice, obviously

•  But also, mode choice

•  Stage •  Trip •  Sub-tour •  Tour •  Daily schedule

IDEC 2015

Page 45: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Do we have a MAUP-like problem for DCM?

Stage Trip Subtour Tour Value of Time Walking CHF/h 152 28 26 24 Value of Time Bike CHF/h 194 39 43 40 Value of Time Car CHF/h 135 25 30 27 Value of Time PT CHF/h -30 2 7 6 Value of Time PT access CHF/h 819 15 22 22

TT PT / TT Car - -4.46 12.33 4.07 4.16 TT Walk / Access time PT - 0.19 1.83 1.19 1.09 Transfer / TT PT min -220.43 107.00 31.28 32.92 Interval / TT PT - 0.96 7.00 3.47 6.33 Access time / TT PT - -27.10 7.67 3.02 3.35

Sour

ce: S

chm

ujtz

(201

5)

IDEC 2015

Page 46: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Do we have a MAUP-like problem for DCM? So

urce

: Sch

muj

tz (2

015)

0!

20!

40!

60!

80!

100!

120!

140!

160!

180!

0!

0.1!

0.2!

0.3!

0.4!

0.5!

0.6!

Stage! Trip! Subtour! Tour! Dayplan!R

un ti

me

[s]!

Mod

el fi

t [-] !

ρ2!MNL with route-specific parameters!

ρ2!MNL with mobility tool ownership!

Run time in [s]!MNL with route-specific parameters!

Run time in [s]!MNL with mobility tool ownership!

IDEC 2015

Page 47: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

What should we do ?

IDEC 2015

Page 48: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Next steps

•  Become more systematic •  Test for choice set size effects •  Test for the stability of the estimates wrt choice set •  Test for the stability wrt imputation of the attribute values

•  Check for the right unit of analysis

•  Check for the right set of explanatory variables

IDEC 2015

Page 49: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

Questions ?

www.ivt.ethz.ch

IDEC 2015

Page 50: Axhausen, K.W. (2015) Survey challenges, modelling ...archiv.ivt.ethz.ch/vpl/publications/presentations/v540.pdf · Axhausen, K.W. (2015) Survey challenges, modelling challenges,

References

Jäggi, B. (Forthcoming) Decision modeling on the household level for energy, fleet choice and expenditure, , Dissertation, ETH Zürich, Zürich. Kopp, J. (Forthcoming) GPS-gestützte Evaluation des Mobilitätsverhaltens von free-floating CarSharing-Nutzern, Dissertation, ETH Zürich, Zürich. Schmutz, Simon (2015) Auswirkung von analytische Einheiten und Aggregationsregeln auf die Verkehrsmittelwahlmodellierung, MSc thesis, Zürich, January 2015. Schuessler, N. (2010) Accounting for similarities between alternatives in discrete choice models based on high-resolution observations of transport behaviour, ETH Zürich, Zürich. Vrtic, M. (2003) Simultanes Routen- und Verkehrsmittelwahlmodell, PhD Dissertation, Fakultät für Verkehrswissenschaften, TU Dresden, Dresden. Zilliak, S. and D. McCloskey (2008) The Cult of Statistical Significance: How the Standard Error Costs Us Jobs, Justice, and Lives, University of Michigan Press, Ann Arbor.

IDEC 2015