Contents

1. Person-based GPS surveys in France: “Lille Experiment” by ISL, and GPS Subset in the French National Travel Survey (ENTD 2007-2008) Cost 355, WG3 – Torino Meeting, 5 October 2007Philippe Marchal and Pierre-Olivier Flavigny (INRETS)Shuning Yuan (INRETS and ISL)

2. The project « Lille Experiment » by ISL-Lavialle, Survey Institute Processing steps Results of the project GPS Subset in the French National Travel Survey (ENTD 2007-2008) Overview – General Scheme CAPI-Design Next steps Contents

3. The project « Lille Experiment » by ISL-Lavialle, Survey Institute

4. Introduction of the project Processing steps Elimitation of the invalid points Estimation of real speed Results of the project Work in progress The contents

5. Establish a comparison between the traces collected in the study « Mobimétrie 2004 »and those collected by GPS in this project. The experiment in Lille and its surrounding area in 2006 1 second/point Two waves (57+145 interviewees) Eurisko GPS receiver L1, C/A codes, 8 channels, 24 hours Autonomy , 16M SD card five buttons (Walk or bicycle, automobile, public transport, study or work, home), no DOPs recorded Introduction of the project

6. Introduction of the project

7. Convert the format towards Data base dbf (DBASE) Calculate the additional fields: average speed, interval, distance, estimated speed, acceleration Filter invalid points Cut the recordings by date Divide the recordings into segments called « Trace » for each day Remove the recordings on the stop place for each « Trace » Make a list of all « Traces » and a list of all stop places Extract the trips between home and office Data processing steps

8. Data processing steps

9. The method Satellite-HDOP (MSH) Number of Satellite < 3 and HDOP > 10 The Method Acceleration-Speed (MAV) The GPS used for the project test Lille can’t offer the HDOP, so we have to find another way to resolve this problem. Method for filtering the invalid recordings

10. The Method Acceleration-Speed (MAV) Principal ideas If “Vb” >> “Va” Then “C” is badly positioned. Method for filtering the invalid recordings

11. Method for filtering the invalid recordings

12. How is « far more » ? 1) when (Time< 12s): If (Acceleration > 10km/hs) Then: next point is badly positioned 2) when (12s < time<120s): If (Vb - Va>120km/h) Then: next point is badly positioned Method for filtering the invalid recordings

13. The result of MAV Can remove all the extreme points Can’t remove the wrong points with little error Do not work for the mass of points High CPU time Method for filtering the invalid recordings

14. MSH removes the points with high probability to be wrong MAV remove the real wrong points MSH considers only the influence of geometry position of the satelllites MAV consider the others influences. Higher CPU time with MAV than with MSH Method for filtering the invalid recordings

15. If continuous stay in one place > 300 seconds, cut the recordings as two segments Threshold of « stay » When (Time<= records interval) : if ( Vr < 1.8 km/h) then « STAY » When (records interval <Time <= 150 s) : if ( Vr < 2.4 km/h) then « STAY » When ( Time > 150): if ( Vr<0.003436*time+3.0845 ) then « STAY » Collected data segmentation

16. Vr<0.003436*time+3.0845 Collected data segmentation

17. Two different speeds Speed recorded by GPS, Average speed between two successive points Speed recorded by GPS: Real speed during records interval Speed average of two succesive points: Calculated by the position recorded influenced strongly by the position recorded interval↑ speed accuracy↑ Interval ↑ probability of speed change ↑ Estimation of real speed

18. Vr  = P*S + ( 1-P )*Sp P= 1.1^-(( sqrt( Inr )*In/Inr – 1) P: Power to S Inr: Records Interval In: Time between two successive points S: Speed recorded by GPS Sp: Average Speed of two successive points Estimation of real speed

19. Estimation of real speed

20. With the method above, the segment that we get is between the definition of trip and stage It could be a trip a stage several stages in one trip Rarely several trips So We call it « trace » Compare our segment with trip and stage

21. Results of the project

22. Results of the projects

23. Distribution of the traceson the main modes

24. Purpose of the traces

25. Results of the project

26. Overview of the French National Travel Survey (ENTD 2007-2008) Design Key figures Sample size : approx. 17 000 responding households Duration : one full year (6 waves) 2 visits Total length of interview : 125 mn

27. Day D Day D + 7 (or more) General scheme of the GPS component GPS component Yes

28. Given to the respondents Given to the interviewers Equipment and documents for respondents and interviewers

29. Presentation of the GPS units selected • Passive monitoring: the respondant has no graphical interface, for road safety and to avoid an influence of GPS on travel behavior, etc. • Only one button: on/off. The respondent has the possibility to skip some trips, if desired (for confidentiality reasons) • Recorded data every 10 seconds • No data transmitted on real-time: the device is only a datalogger. Data transmitted to the interviewer's laptop during the second visit, and deleted inside the unit • Two types of GPS unit: 100 « normal » and 70 modified, with movement detection and blinking mode 29

30. French Regions with aGPS sub-sample

31. CAPI-GPS design

32. A data collection framework with three combined measurement tools How trips caracteristics for days with no CAPI-GPS can be derived from raw GPS data ?

33. Work in progress • Trip estimation from the GPS recordings • Traces segmentation (smaller and homogenous segments) • Analyse segment ends, and link them to a trip • Modes and trip purpose estimation • Incomplete and missing trips estimation • Modal map-matching

34. Thank you ! INRETS French NTS Team: Jimmy ARMOOGUM, Jean-Paul HUBERT, Philippe MARCHAL, Pierre-Olivier FLAVIGNY Shuning YUAN (PhD student ISL-INRETS) Jean-Loup MADRE