1. No category

Bevorzugter Zitierstil für diesen Vortrag!
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!
!
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Axhausen, K.W. (2012) GPS, GSM, Diary: How to capture travel
behaviour?, presentation at Northwestern University, Evanston, July
2012. !
1
GPS, GSM, Diary: How to capture travel behaviour ?
KW Axhausen
IVT
ETH
Zürich
July 2012
Acknowledgements
!
Stated choice and diaries:
•  Claude Weis
•  Alexander Erath
Social networks:
•  Timo Ohnmacht
•  Andreas Frei
•  Matthias Kowald
GPS surveys and analysis:
•  Nadine Rieser – Schüssler
•  Lara Montini
3
Starting point
4
Hypotheses for travel behaviour
Specialisation
+
Migration
+
+
+
Activities +
+
+
Wages
-
+
Fleet
comfort
+
+
+
Housing
consumption
-
vtts et al.
+ Elasticity > 0
- Elasticity < 0
-
Tours
-
+
vkm
+
+
Energy costs
+
+
pkm
+
+
-
-
k
-
Professional and
personal activity space
+
Network
geography
-
Number
of networks
-
-
Network
overlap
+
-
Local
anomie
5
Evidence
6
Productivity growth in Western Europe
3.00
Growth rate [%/year]
dapted from Galor and Weil (2000)
2.50
Productivity
Population
2.00
1.50
1.00
0.50
0.00
1000
1100
1200
1300
1400
1500
1600
1700
1800
1900
2000
Year
7
Scherer, 2004
Road based – Switzerland 1950 and 2000
Quelle: Hess, Erath und Axhausen (2008) S.53!
VTTS all purposes Switzerland 2001 - 2006
9
Real prices of telekommunication
2000
US International and interstate average
revenue per minute
1750
Index [1995 = 100]
1500
1250
Quelle: nach FCC (2001)!
1000
750
500
250
0
1930
1940
1950
1960
1970
Year
1980
1990
2000
What do we need ?
11
Stages – trips – tours - activities
At home
12
Stages – trips – tours - activities
Breakfast!
13
Stages – trips – tours - activities
Walk!
Tram!
Walk!
Bus!
Walk!
14
Stages – trips – tours - activities
Trip 1!
Work!
15
Stages – trips – tours - activities
Tour 1!
16
What should we capture ?
!
!
Elements of the generalised costs of the movement:
• 
• 
• 
• 
Duration of the stages
Routes of the stages
Circumstances of the stages (congested; parking search)
Monetary (decision relevant) costs of the stages
•  Joint activities during the stages
•  Joint travel with whom
•  Time pressure of the stages
17
What should we capture ?
!
!
Elements of the generalised costs of the non-chosen alternatives (modes *
routes/connections):
• 
• 
• 
• 
Duration of the stages
Routes of the stages
Circumstances of the stages (congested; parking search)
Monetary (decision relevant) costs of the stages
18
What should we capture ?
!
!
Elements of the generalised costs of the activity:
• 
• 
• 
• 
Congestion
Price levels
Price worthiness (value for money)
Social mileu
• 
• 
• 
• 
Purpose of the activity
Joint activities during the activity
Joint activity with whom and expenditure sharing, if any
Planning horizon of the activity
19
What should we capture ?
!
!
Elements of the generalised costs of the non-chosen alternatives (locations
* purposes):
• 
• 
• 
• 
Congestion
Price levels
Price worthiness (value for money)
Social mileu
20
Eine Woche eines Zürcher Studienteilnehmers
But how ?
21
But how ?
Dimension
Diary
GSM
GPS
Trips
Easy
Impossible
Post-processing
Completeness
Respondent
dependent
No
Yes, but data
loss possible
Duration
Rounded to the
next 5, 15 min
No
Exactly
Destinations
(Exactly)
Cell tower
Exactly
Purpose
Yes
No
Imputation
Company
Partially
No
No
Routes
Expensively
(Impossible)
Exactly
Recruitment
F(response
burden)
(Easy)
F(response
burden)
Response period
1 (-42) days
(Unlimited)
(1-) 7-14 (- ) days
22
Response rate = f(response burden) @ IVT
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23
Diaries
24
Format: Swiss Mikrozensus (MZ) 2010
•  Geocoded CATI interview (LINK)
•  Person- and household socio-demographics
•  Stage-based travel diary
•  Routes of car/motorcycle-stageswere identified with two waypoints (interviewer had map interface)
•  Add-on modules for sub-samples (LINK)
•  One-day excurions
•  Long-distance travel
•  Attidues to transport policy
•  Integrated, but independent SC questionnaire (IVT)
•  SC mode choice
•  SC route and deperture time choice
25
Innovation in destination choice
1.6
Borlänge GPS Studie; Vollzeit; Alle Zwecke
Mobidrive - Karlsruhe; Alle Befragten; Alle Zwecke
Uppsala; Alle Befragten; Alle Zwecke
12 Wochen Befragung; Alle Befragten; Nur Freizeit
Mobidrive - Karlsruhe; Alle Befragten; Nur Freizeit
Uppsala; Alle Befragten; Nur Freizeit
Anzahl neuer Orte/Tag
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0
1
3
5
7
9
11
13
15
17
19
21
23
25
27
29
31
33
Berichts- oder Beobachtungswoche
26
Sample: MZ 2010
•  Households (59’971)
•  Persons (62’868)
•  Stages (310’193)
•  Car/mc > 3km with 2 way-points
•  Railway connections with HAFAS
•  Recruitment of the SC-experiments (IVT)
27
Protocol: MZ 2010
•  CATI with multiple calls (no incentives) (72% response rate)
•  Recruitment for the SC: 50% willingness
•  Customized SCs for 85% of the recruited within 12 days
•  70% response rate for the SC experiments
28
Research and development needs: Diaries
•  Integration of the “non-chosen” alternatives (Routes, transit service
levels, flight costs, etc.)
•  Trade-off between incentive and participation (“young men with
smatz phones only”)
•  Integration of relevant and standaridsed scales (Environment, risk,
variety seeking)
•  Integration of social networks
•  Integration of multi locality
29
Why social networks in transport/spatial planning ?
30
Example: Number of accompanying travellers
Short vacation
Excursion: nature
Other
Excursion: culture
Meeting friends
Further education (leisure)
Garden/ cottage
Voluntary work
Disco, pub, restaurant, cinema
Meeting relatives/family
Window shopping
Pick up/drop off/attendance
Group/club meeting
Family duty
Cemetery
Axhausen et al., 2007!
Active sports
Education
Long-term shopping
Walk or stroll
Daily shopping
Household members travelling along
Other persons travelling along
Dog travelling along
Private business
Private business (doctor,...
Work
0.0
0.5
1.0
1.5
Mean
2.0
2.5
3.0
31
Example: Required travel for leisure meetings of ego-alter
50
40
30
Percent [%]
Schlich et al., 2002!
20
Important contact
10
No
0
Yes
0 - 10 km
20 - 30 km
50 - 60 km
Abroad
10 - 20 km
40 -50 km 60 - 250 km
Distance between home locations [km]
32
Heterogenity in choice
Location choice
• 
• 
• 
• 
• 
WTP
Taste
Joint choice with family, friends, persons to meet
Schedule constraints
Social constraints
For mode choice in addition
•  Luggage
•  Company
33
Belart, 2011!
Example: Residential location choice in Kt. Zürich
Variable
Rent/Income
log(m2/head)
Frequency weighted mean distance to friends
Exponent (friends)
Mean distance to work/school
Exponent (distance to work)
Travel time to Bürkliplatz
log(transit accessibility) * "No car"
log(car accessibility) * “Car"
Share of equally sized HH within 1 km
Population density within 1 km
Share of empty flats in municipality
N= 683, rho² = 0.2128; * > 0.1; ** > 0.05; *** > 0.01
Beta
t-Test
-5.51
***
0.98
***
-8.16
*
0.22
**
-1.59
**
0.37
**
0.02
**
0.41
**
-0.30
**
0.02
*
0.01
**
-0.11
34
Travel and social networks
35
Benchmarking the current state
• 
• 
• 
• 
Numbers of contacts
Distance distributions
Geographies
Frequency and mode of contact
• 
• 
• 
• 
“Productivity”
Levels of local anomie
Levels of local trust
Level of place attachment
36
Empirical strategy
•  Surveys of social geographies & mobility biographies
•  Egocentric
•  Snowball
•  Travel diaries
•  One-Day
•  Multple days
•  With/without information about the presence of others
•  With/without named co-travellers, co-present persons
37
Social network surveys @ IVT
•  Ohnmacht: 50 egos qualitative/quantitative in Zürich
•  Larsen/Urry: 24 egos qualitative/quantitative in NE England
•  Frei: 300 egos quantitative in Zürich
•  Kowald: snowball; 750 egos quantitative worldwide (starting with
40 egos in Kanton Zürich)(12000 alters in total) (8 day diary
included)
38
Number of contacts reported
10%
Frei and Axhausen, 2007
Per cent
8%
6%
4%
2%
0
10
20
30
40
50
Number of contacts named
39
Frei and Axhausen, 2007
Distances between home locations
40
400
300
200
100
0
Frequency
Daten: Schneeballbefragung IVT, Siehe Kowald et al. 2012
Great circle distances between “leisure” contacts
0.01
0.1
1
10
100
1000
10000
log−transformed distances [km]
41
Example of a social network geography
42
Size of network geometries
40
Percent
30
20
Frei and Axhausen, 2007
10
0
1.E0 1.E1 1.E2 1.E3 1.E4 1.E5 1.E6 1.E7 1.E8 1.E9
1.
E10
95%-confidence ellipse of the social network geography
43
Interactions by mode and distance between homes
100.00
Face-to-face visits/year
Great circle distance [km]
Phone calls/year
Great circle distance [km]
Email messages/year
Great circle distance [km]
SMS messages/year
Great circle distance [km]
80.00
60.00
Frei and Axhausen, 2007
40.00
20.00
0.00
0.
0
0
1
1.00
10.00
100.00
1000.00
10000.00
Great circle distance (km)
44
Fa
Gr
Ph
Gr
Em
Gr
SM
Gr
2010/11 Snowball survey
45
Challenges of snowball sampling
Challenges:
•  Start with representative seeds
•  Avoid selection bias
Kowald and Axhausen, 2011
•  React to homogeneous clusters
•  Correct the overrepresentation of
‚socializers‘ and underrepresentation of
‚isolates‘
46
owald and Axhausen, 2011
Response rate and response burden (IVT surveys)
47
Kowald and Axhausen, 2011
Behind egos’ horizons: The connected ‘snowball’-graph
!
Seed
Ego
Bridging alter
Vertices
Edges
Density
Components
Without sociogram
6‘584
7‘349
0.000
19
With sociogram
6‘584
32‘671
0.002
19
Triangles
0.017
48
0.518
Comparisons
49
Transport motivated social network surveys
East York, Ontario (Wellman, Carrasco et al.)
Eindhoven, Netherlands (Arentze, Van der Berg)
Concepcion, Chile (Carrasco)
City of Zürich (Frei)
Kanton Zürich snowball (Kowald)
50
00
0.2
0.6
Zurich
Eindhoven
Switzerland
Concepcion
Toronto
0
Density
Contact “density” – shares by distance class
0
20
40
60
80
100
Great circle distance [km]
51
Shares of contact by mode
●
●
●
●
0.8
●
●
●
●
●
0.2
0.2
0.0
●
1
10
100
● ●
● ●
●
●
●
●
●
0
●
●
●
0.4
●
0.6
●
●
0.4
0.6
●
Telephone
1000
10000
Great circle distance [km]
●
●
●
●
●
●
0.0
0.8
Face-to-face
●
0
1
10
100
1000
10000
Great circle distance [km]
0.6
0.8
Internet
●
Zurich
●
Eindhoven
0.4
Switzerland
●
0.2
●
●
0.0
●
●
0
1
● ●
●
●
●
●
10
●
●
Concepcion
●
●
●
100
1000
Great circle distance [km]
10000
52
Multi-locality
53
Multi-locality: Multiple reference points
•  Parental “home”
•  “Home”
• 
• 
• 
• 
Student digs
Pied-a-terre
Company dormatory
Hotel (chain)
•  Weekend home(s) (of others)
•  RV (camp ground) (of others)
•  Living apart together
54
GPS self-tracing
55
Current examples
Capurted
with
Where
What
GPS logger
Cincinatti, OH
Regional transport study; purpose
imputation (Ohio DOT)
Jerusalem
Regional transport study; (Israel DOT)
Kanton Zürich Transit route choice (IVT, ETH)
Smartphones Singapore
Bay Area
Capturing activities within and without
building (SMART)
Capturing trips (Joan Walker and UC
Berkeley Kollegen)
56
COST and peacox 7th framwork project: GPS based diary at IVT
GPS unit:
•  Interval: 1Hz
•  3D position
•  Date and time
•  HPOD and other measures of
accuracy
Accelerometer
•  Interval 10 Hz
•  3D accelleration
Battery
•  Multiple days
GSM:
•  Savings every 4 hours on SQL
database server
57
GPS-based prompted recall survey
300 participant for 7 days
Web-survey
•  Socio-demographs
•  Attitudes to risk,
environment, variety seeking
•  Checking and correction of
the automated processing
58
Data processing
Filtering and smooting
Identify stagesand stops
Stops
Stages
Mode detection
Purpose imputation
map-matching
Analysis and application
59
Filtering and smootinh
Filtering
•  VDOP > 5
•  Unrealististic elevations
•  Jumps with v > 50m/s
Smoothing
•  Gauss Kernel smoother over the
time axis
•  Speed as first derivate of the
positions
•  Raw data are kept
60
Detection of stages and stops
Clusters of high density
Longer breaks without points
•  Accelerometer data
•  GPS points
Halte
Etappen
No movement
•  V ≈ 0 km/h
•  No accellerations
Mode change
•  Walk stage as signal
61
Quelle: Schüssler, 2010 (ohne Beschleunigungsdaten
Number of trips/day in comparison with MZ 2005
62
Quelle: Schüssler, 2010 (ohne Beschleunigungsdaten
Trip durations and length in comparison with MZ 2005
Länge [km]
Dauer [min]
63
Comparison with MZ 2005
Quelle: Schüssler, 2010 (ohne Beschleunigungsdaten
ZH
WI
GE
MZ 2005
Number of persons
2 435
1 086
1 361
2 940
Days per persons
6.99
5.96
6.51
1
Trips per day
4.50
3.40
4.26
3.65
7.72
7.37
7.19
8.79
34.74
23.20
29.25
32.13
Trip duration [min]
15.17
13.71
15.05
26.21
Stages per day
1.40
1.31
1.47
1.68
Trip lengths [km]
Daily trip lengths [km]
64
Mode detection
65
Quelle: Schüssler, 2010 (ohne Beschleunigungsdaten
Trip length by mode in comparison with MZ 2005
Zu Fuss
Fahrrad
Städtischer ÖV
Pkw
Bahn
66
Map matching
Car and bike stages
Selection from a set of possible routes
•  At nodes all possible on-going links become
new candidate routes (branches)
•  If the tree has enough branches, it is pruned
based on their total errors
Each candidate branch is assessed by
•  Squared error between GPS and path
•  Deviation between GPS speed and posted
speeds
Transit-stages
•  Route identified as for cars
•  Line identified by time table
67
Quelle: Schüssler, 2010 (ohne Beschleunigungsdaten
Map-Matching: First branches
68
Quelle: Schüssler, 2010 (ohne Beschleunigungsdaten
Map-Matching: Number of branches against computing times
69
Research needs: GPS post processing
•  Test dataset with true values
•  Automatic calibration of the fuzzy logic parameters
•  Further integration between map-matching and mode detection
•  Integration of the logic of the stage – mode – sequences
•  Better imputation of the movement during signal loss
•  More and better purpose imputation (POI – data base; land use
data; frequency over multiple days)
70
What now ? Cost as a function
• 
• 
• 
• 
Rate of usable addresses
Recruitment rate
Response rate
Rate of usable returns
• 
• 
• 
• 
Correlation between household members
Correlation between days
Correlation between tours of a day
Correlation between trips of tour
•  Number of waves with the GPS loggers
•  Rate of loss of the GPS loggers
71
What now ?
Diaries
Advantages All variables
Social contacts
Dis≈15% under reporting of
advantages trips
Rounded times
GPS-self tracing
All movements (but data loss)
Exact times, routes, locations
Longer observation periods
Post-processing and imputation
(Effort of the post-processing)
Approximate routes only
Decreasing response
rates / expensive
response
Unknown response rates
(Costs of the units and their
distribution/collection)
72
Questions ?
!
!
!
!!
www.ivt.ethz.ch
!
www.matsim.org
www.futurecities.ethz.ch
73
Literature and references
Arentze, T.A., M. Kowald and K.W. Axhausen (2012) A method to model population-wide social
networks for large scale activity-travel micro-simulations, paper presented at the 91th
Annual Meeting of the Transportation Research Board, Washington, D.C., January 2012
Axhausen, K.W. (2000) Geographies of somewhere: A review of urban literature, Urban
Studies, 37 (10) 1849-1864.
Axhausen, K.W. (2008) Social networks, mobility biographies and travel: survey challenges,
Environment and Planning B, 35 (6) 981-996.
Axhausen, K.W. (2007) Activity spaces, biographies, social networks and their welfare gains
and externalities: Some hypotheses and empirical results, Mobilities, 2 (1) 15-36.
Axhausen, K.W. and A. Frei (2007) Contacts in a shrunken world, Arbeitsbericht Verkehrs- und
Raumplanung, 440, IVT, ETH Zürich, Zürich.
Botte, M. (2003) Strukturen des Pendelns in der Schweiz, Diplomarbeit, Fakultät für
Bauingenieurwesen, TU Dresden, August 2003.
74
Literature and references
Frei, A. and K.W. Axhausen (2011) Collective location choice model, paper presented
Arbeitsberichte Verkehrs- und Raumplanung, 686, IVT, ETH Zürich, Zürich
Frei, A. and K.W. Axhausen (2007) Size and structure of social netowork geographies,
Arbeitsberichte Verkehrs- und Raumplanung, 439, IVT, ETH Zürich, Zürich.
Dicken, P. (1998) Global Shift: Transforming the World Economy, Paul Chapman Publishing,
London.
FCC (2001) Long distance telecommunication industry, FCC, Washington, D.C.
Grannis, R. (1998) The importance of trivial streets: Residential streets and residential
segregation, American Journal of Sociology, 103 (6) 1530-1564. Kowald M. and K.W. Axhausen (2011) Surveying data on connected personal networks,
Arbeitsberichte Verkehrs- und Raumplanung, 722, IVT, ETH Zürich, Zürich.
Larsen, J., J. Urry and K.W. Axhausen (2006) Mobilities, Networks, Geographies, Ashgate,
Aldershot.
Putnam, R.D. (1999) Bowling Alone: The collapse and revival of American community, Schuster
and Schuster, New York.
Schlich, R., B. Kluge, S. Lehmann und K.W. Axhausen (2002) Durchführung einer 12-wöchigen
Langzeitbefragung, Stadt Region Land, 73, 141-154.
75