Introduction by Organizers Seraphim Alvanides1, Godwin Yeboah1, Stefan Van der Spek2, Nico de Weghe3 1Northumbria University, UK; 2TU-Delft, Netherlands; 3Ghent University, Belgium Topic: "Tracking daily mobilities: GPS based bicycle data collection, processing, and analysis snapshots"

1. Cycling Data Challenge Workshop - CDC2013
Pre-Workshop of 16th AGILE Conference 2013
Leuven – Belgium.
Tuesday 14th May 2013
“Bisschopskamer” room at Faculty Club
Alvanides1, Yeboah1, Van der Spek2, de Weghe3
Northumbria University1; TU Delft2; Ghent University3
WELCOME

2. Cycling Data Challenge Workshop - CDC2013
Pre-Workshop of 16th AGILE Conference 2013
Alvanides1, Yeboah2, Van der Spek3, de Weghe4
Northumbria University1,2; TU Delft3; Ghent University4
INTRODUCTION
TRACKING DAILY MOBILITIES: GPS BASED BICYCLE DATA
COLLECTION, PROCESSING, AND ANALYSIS SNAPSHOTS

3. Overview
 House keeping
 Brief background of project
 Data collection and sample characteristics
 Challenges in data collection
 Challenges in data processing
 Remarks and the rest of the programme
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Yeboah & Alvanides, Northumbria University

4. House keeping
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 Internet (see paper in circulation)
 Exits
 Fire alarm
 Where to go for coffee
 Where to go for lunch
 Gents/Ladies

5. Aim of presentation
5
 To provide evidence on methods used for data collection,
processing, and some analysis
 To share challenges faced during the data collection and
processing phase
 To set the scene for subsequent presentations

6. Strands: Suggestions and demands from
literature (Why Cycling?)
 There is demand for sustainable ways of living due to
 traffic congestion, population growth, climate change, low
physical activity, health related issues (e.g., obesity & non-
communicable diseases), sedentary lifestyles etc.
 Cycling as active transport
 one of the solutions to sustainable ways of living
 Calls for research to focus on understanding cycling through:
 investigation and knowledge discovery of cyclist’s perception
and actual route choice experiences and preferences
 integrated research methods which recent technological
advancements may permit (e.g. GPS+GIS+GISc+ABMS)
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Yeboah & Alvanides, Northumbria University

7. Why primary data collection?
 Secondary data is aggregated or not detailed
enough (e.g. census data; surveys; more recently DfT)
 Lack of “detailed quality data” limits this research.
 To make available new scientific data on actual and
revealed route choice preferences of utility cyclists
within the research area; not existing previously.
 To enable further research towards understanding
constraints and enablers for cycling; especially in
relation to transport and (indirectly) “well-being”.
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Yeboah & Alvanides, Northumbria University

8. Choosing study area:
Analysing UK Census 2001 & 2011
8
0
10
20
30
40
50
60
70
80
90
100
0 20 40 60 80 100
Cumulative%ofbase(total)activity
(NEEngland2011Censusasbase)
Cumulative % of activity
(Travel to Work by Bike across NE England )
Lorenz Curve for Travel to Work by Bike – Census 2011
Travel to work by Bike
Index of Dissimilarity (IoD)= 11
Note: Census 2001 IoD = 5
North Tyneside
Newcastle upon Tyne
South Tyneside
Rest of North East
Gateshead
Sunderland

9. Choosing study area:
Analysing Tyne & Wear Household Travel Survey
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From 2003 to 2011

10. Data collection / methodological issues
/ Further work
Godwin Yeboah, Northumbria University
STUDY AREA
Area:
in & around
Newcastle upon
Tyne
Background map: Google Maps 2012
HOME
WORK/SCHOOL
STUDY AREA
LEGEND
Overview
Slide 10
Yeboah & Alvanides, Northumbria University

11. Fieldwork planning11
Extensive piloting of
survey instruments
with 7 participants
Evaluated 4 GPS
devices: i-gotU GT-600;
Atmel BTT08; Canmore
GT-750 (L); and Qstarz
BT-Q1000XT (selected)
Screening
Data processing
&
further analysis
Stepwise flow
(main survey)
Stepwise flow
(during testing)
Recruitment
Data collection
Planning and
Preparation
Invitation
Yeboah & Alvanides, Northumbria University

12. Tracked sample size
 This work (Northumbria project within Tyneside conurbation):
 One wave: October-November 2011
 118 initially agreed to participate
 In the end: 81 participants out of 111utility cyclists
 79 used in this presentation
Lessons learnt from other related work such as:
 UK National Travel Survey (NTS) GPS Feasibility study (DfT)
 The fieldwork was done in two waves; 66 adults in one wave (October-
November) and 68 adults in the second wave (January-March). In all 96 adults
were interviewed face-to-face across the two waves for the NTS study.
 TU Deft project in the town of Almere
 15 families initially agreed to participate. However, in the end, 40 participants
out of 13 families from three neighbourhoods participated in the study by
carrying GPS devices for one week.
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Yeboah & Alvanides, Northumbria University

13. Space-Time-Cube (STC) based GPS data
processing workflow
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Yeboah & Alvanides, Northumbria University

14. Example of visual inspection:
GPS raw data (left) & processed data (right)
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Visual
inspection
of GPS raw
data
Processed
/ refined
data

15. Space-Time-Cube applicability/usability cycle
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GAP
Yeboah & Alvanides, Northumbria University

16. Gender against number of cycle trips and
distance (km) travelled
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Gender No. Over one week period per person
Female distance value is weighted to control for gender
TRIPS KM
(weighted)
Average
KM / TRIP
Average
KM /
PERSON
MIN / MAX
(trip)
Female 27 319 2137.4 6.7 79.2 0.25 km /
13 km
Male 52 622 3373.0 5.4 64.9 0.12 km /
36 km
Total 79 941 5510.4 5.9 69.8

17. Trips, gender & annual household income
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31%
9%
19%
15%
46%
14%
45%
21%
77%
23%
65%
35%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
High Income
(Distance)
Low Income
(Distance)
High Income
(Trip)
Low Income
(Trip)
Female (f) Male (m) All (f+m)

18. Cycle trips share per employment status
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59%
7%
16%
9% 10%
0%
10%
20%
30%
40%
50%
60%
70%
Participants' cycle trips (%)

19. Reported travel mode by participants - t. diary
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43%
29%
1%
5%
2%
20%
1%
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
Bike Walk Taxi Train Bus Car Other
NumberofTrips(%)
(100%=2432)
Travel mode by Participants (Travel Diary)
Trip (%)

20. Challenges in data collection
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 Planning considerations
 device procurement timing, size, cost, customer support
 Sample, survey response, spatial distribution of trajectories
 Device features
 Battery life and the means to charge/re-charge
 Accuracy
 Memory for storing logged points
 Fix time. The faster the better. Mostly <=35 seconds
 Software for GPS device

21. GPS Logged Points
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2 3
787641
1623132
4808 34 20 11 15
Points

22. Challenges in data processing
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 Non-algorithmic approach
 Space Time Cube usage is limited; Travel diary needed
 Convenient for small to medium datasets
 Algorithmic approach
 Quality assessments
 how reliable is the data without extra information?
 Non-availability of generic algorithmic tools
 Tool 1: Must know Java + MATSim + Eclipse
 http://sourceforge.net/projects/posdap/
 Tool 2: Must know Java + need to conform to Copenhagen study
 https://github.com/bsnizek/JMapMatching

23. Our case: Network route generation
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Papinski, D. & D. M. Scott (2011) A GIS-based toolkit for route choice analysis. Journal of Transport Geography, 19, 434-442.

24. Our case: An example of generated
Home-to-Work Network constrained routes24

25. Remarks and the rest of the programme
 Res. design: implemented in few published cycling studies
 No significant differences between gender and use of
cycling “corridors”
 Reasonable use of current cycling network (more than half
of trips take place within 20m buffer around cycling
paths). Network data from Newcastle City Council used.
 However, need to improve cycling network for the 1/3 of
trips taking place “off” the network => Policy implications
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Yeboah & Alvanides, Northumbria University

26. Rest of the programme
 Let’s go through the workshop programme
 Possible discussions during breaks or sessions
 Keynote presentations
 Methods and findings arising from presenters’ presentation
 Your reasons for attending the workshop
 New ideas emanating from discussions
 Organizers intend to take pictures during the presentations
and discussions.
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Yeboah & Alvanides, Northumbria University

27. MOVE-COST:
Funded CDC2013 Workshop
CHOROCHRONOS:
Provided secure platform for the bike data management
AGILE2013 TEAM:
Accepted and facilitated this workshop
ALL CONTRIBUTORS:
Organizers, presenters, attendees
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Yeboah & Alvanides, Northumbria University
Please keep questions for the morning open discussion
Acknowledgements

28. Other information:
About presenter and supervision team
PhD Student:
• Blog: http://godwinyeboah.blogspot.com/
• YouTube Channel: http://www.youtube.com/SpatialScience
• Twitter: http://twitter.com/#!/godwinyeboah
Supervision team:
• Dr. Seraphim Alvanides
http://www.northumbria.ac.uk/sd/academic/bne/study/aec/
acestaff/seraphimalvanides
• Dr. Emine Mine Thompson
http://www.northumbria.ac.uk/sd/academic/bne/study/aec/
acestaff/eminethompson
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Yeboah & Alvanides, Northumbria University