Tracking daily mobilities: GPS based bicycle data collection, processing, and analysis snapshots


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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"

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Tracking daily mobilities: GPS based bicycle data collection, processing, and analysis snapshots

  1. 1. Cycling Data Challenge Workshop - CDC2013Pre-Workshop of 16th AGILE Conference 2013Leuven – Belgium.Tuesday 14th May 2013“Bisschopskamer” room at Faculty ClubAlvanides1, Yeboah1, Van der Spek2, de Weghe3Northumbria University1; TU Delft2; Ghent University3WELCOME
  2. 2. Cycling Data Challenge Workshop - CDC2013Pre-Workshop of 16th AGILE Conference 2013Alvanides1, Yeboah2, Van der Spek3, de Weghe4Northumbria University1,2; TU Delft3; Ghent University4INTRODUCTIONTRACKING DAILY MOBILITIES: GPS BASED BICYCLE DATACOLLECTION, PROCESSING, AND ANALYSIS SNAPSHOTS
  3. 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 programme3Yeboah & Alvanides, Northumbria University
  4. 4. House keeping4 Internet (see paper in circulation) Exits Fire alarm Where to go for coffee Where to go for lunch Gents/Ladies
  5. 5. Aim of presentation5 To provide evidence on methods used for data collection,processing, and some analysis To share challenges faced during the data collection andprocessing phase To set the scene for subsequent presentations
  6. 6. Strands: Suggestions and demands fromliterature (Why Cycling?) There is demand for sustainable ways of living due to traffic congestion, population growth, climate change, lowphysical 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 perceptionand actual route choice experiences and preferences integrated research methods which recent technologicaladvancements may permit (e.g. GPS+GIS+GISc+ABMS)6Yeboah & Alvanides, Northumbria University
  7. 7. Why primary data collection? Secondary data is aggregated or not detailedenough (e.g. census data; surveys; more recently DfT) Lack of “detailed quality data” limits this research. To make available new scientific data on actual andrevealed route choice preferences of utility cyclistswithin the research area; not existing previously. To enable further research towards understandingconstraints and enablers for cycling; especially inrelation to transport and (indirectly) “well-being”.7Yeboah & Alvanides, Northumbria University
  8. 8. Choosing study area:Analysing UK Census 2001 & 2011801020304050607080901000 20 40 60 80 100Cumulative%ofbase(total)activity(NEEngland2011Censusasbase)Cumulative % of activity(Travel to Work by Bike across NE England )Lorenz Curve for Travel to Work by Bike – Census 2011Travel to work by BikeIndex of Dissimilarity (IoD)= 11Note: Census 2001 IoD = 5North TynesideNewcastle upon TyneSouth TynesideRest of North EastGatesheadSunderland
  9. 9. Choosing study area:Analysing Tyne & Wear Household Travel Survey9From 2003 to 2011
  10. 10. Data collection / methodological issues/ Further workGodwin Yeboah, Northumbria UniversitySTUDY AREAArea:in & aroundNewcastle uponTyneBackground map: Google Maps 2012HOMEWORK/SCHOOLSTUDY AREALEGENDOverviewSlide 10Yeboah & Alvanides, Northumbria University
  11. 11. Fieldwork planning11Extensive piloting ofsurvey instrumentswith 7 participantsEvaluated 4 GPSdevices: i-gotU GT-600;Atmel BTT08; CanmoreGT-750 (L); and QstarzBT-Q1000XT (selected)ScreeningData processing&further analysisStepwise flow(main survey)Stepwise flow(during testing)RecruitmentData collectionPlanning andPreparationInvitationYeboah & Alvanides, Northumbria University
  12. 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 presentationLessons 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 adultswere 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 participantsout of 13 families from three neighbourhoods participated in the study bycarrying GPS devices for one week.12Yeboah & Alvanides, Northumbria University
  13. 13. Space-Time-Cube (STC) based GPS dataprocessing workflow13Yeboah & Alvanides, Northumbria University
  14. 14. Example of visual inspection:GPS raw data (left) & processed data (right)14Visualinspectionof GPS rawdataProcessed/ refineddata
  15. 15. Space-Time-Cube applicability/usability cycle15GAPYeboah & Alvanides, Northumbria University
  16. 16. Gender against number of cycle trips anddistance (km) travelled16Gender No. Over one week period per personFemale distance value is weighted to control for genderTRIPS KM(weighted)AverageKM / TRIPAverageKM /PERSONMIN / MAX(trip)Female 27 319 2137.4 6.7 79.2 0.25 km /13 kmMale 52 622 3373.0 5.4 64.9 0.12 km /36 kmTotal 79 941 5510.4 5.9 69.8
  17. 17. Trips, gender & annual household income1731%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. 18. Cycle trips share per employment status1859%7%16%9% 10%0%10%20%30%40%50%60%70%Participants cycle trips (%)
  19. 19. Reported travel mode by participants - t. diary1943%29%1%5%2%20%1%0%5%10%15%20%25%30%35%40%45%Bike Walk Taxi Train Bus Car OtherNumberofTrips(%)(100%=2432)Travel mode by Participants (Travel Diary)Trip (%)
  20. 20. Challenges in data collection20 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. 21. GPS Logged Points212 378764116231324808 34 20 11 15Points
  22. 22. Challenges in data processing22 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 Tool 2: Must know Java + need to conform to Copenhagen study
  23. 23. Our case: Network route generation23Papinski, D. & D. M. Scott (2011) A GIS-based toolkit for route choice analysis. Journal of Transport Geography, 19, 434-442.
  24. 24. Our case: An example of generatedHome-to-Work Network constrained routes24
  25. 25. Remarks and the rest of the programme Res. design: implemented in few published cycling studies No significant differences between gender and use ofcycling “corridors” Reasonable use of current cycling network (more than halfof trips take place within 20m buffer around cyclingpaths). Network data from Newcastle City Council used. However, need to improve cycling network for the 1/3 oftrips taking place “off” the network => Policy implications25Yeboah & Alvanides, Northumbria University
  26. 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 presentationsand discussions.26Yeboah & Alvanides, Northumbria University
  27. 27. MOVE-COST:Funded CDC2013 WorkshopCHOROCHRONOS:Provided secure platform for the bike data managementAGILE2013 TEAM:Accepted and facilitated this workshopALL CONTRIBUTORS:Organizers, presenters, attendees27Yeboah & Alvanides, Northumbria UniversityPlease keep questions for the morning open discussionAcknowledgements
  28. 28. Other information:About presenter and supervision teamPhD Student:• Blog:• YouTube Channel:• Twitter:!/godwinyeboahSupervision team:• Dr. Seraphim Alvanides• Dr. Emine Mine Thompson & Alvanides, Northumbria University