|Zainal N. Arifin||Institute for Transport Planning and Systems, Swiss Federal Institute of Technology, Wolfgang-Pauli Strasse 15, 8093 Zurich, Switzerland|
|Kay W. Axhausen||Institute for Transport Planning and Systems, Swiss Federal Institute of Technology, Wolfgang-Pauli Strasse 15, 8093 Zurich, Switzerland|
This paper reports on findings regarding the day-to-day dynamic behavior of commuters’ mode and route choices in Jakarta. Ninety-three commuters using Global Positioning System (GPS) devices during a one-week period were observed. The observation proves the presence of dynamic behavior in choosing both modes and routes for commuting in Jakarta. Car drivers and motorcyclists frequently change their routes, especially during work-to-home trips. Motorcyclists were more dynamic in choosing their routes than were car drivers. This case study revealed a unique pattern of mode and route choice behavior, which can be used for developing a mode and route choice model for Jakarta.
Global positioning system (GPS), Jakarta, Mode choice, Route choice, Variability
Chung, E.-H., Shalaby, A., 2005. A Trip Bases Reconstruction Tool for GPS-based Personal Travel Surveys. Transportation Planning and Technology, Volume 28, No. 5, pp. 381–401.
Elango, V.V., Guensler, R., Ogle, J., 2007. Day-to-Day Travel Variability in the Commute Atlanta, Georgia, Transportation Research Record, No. 2014, pp. 39-49.
Guensler, R., Ogle, J., Li, H., 2005. Variability in 2004 Commute Atlanta Instrumented Vehicle Travel Activity, Manuscript submitted to TRB annual meeting 2006.
Kochan, B., Bellemans, T., Janssens, D., Wets, G., 2006. Dynamic Activity-travel Diary Data Collection Using a GPS-Enabled Personal Digital Assistant. Proc., Innovations in Travel Modeling Conference, Austin, Texas.
Li, H., 2004. Investigating Morning Commute Route Choice Behavior Using Global Positioning Systems and Multi-day Travel Data, PhD Dissertation, Georgia Institute of Technology, Atlanta.
Li, H., Guensler, R., Ogle, J., Wang, J., 2004. Using GPS Data to Understand the Day-to-Day Dynamics of the Morning Commute Behavior, paper presented at the 83th Annual Meeting of the Transportation Research Board, Washington, D.C., January 2004.
Pendyala, R. M., & Pas, E. I., 2000. Multi-Day and Multi-Period Data for Travel Demand Analysis and Modeling, Transportation Research Circular E-C008, Transport Surveys: Raising the Standard. TRB, National Research Council, Washington, D.C., 2000, pp. IIB-1–IIB-22.
Schlich, R., Axhausen, K. W., 2003. Habitual Travel Behaviour: Evidence from a Six-Week Travel Diary, Transportation (Netherlands), Volume 30, No. 1, pp. 13–36.
Schüssler, N., Axhausen, K. W., 2009. Processing GPS Raw Data without Additional Information. Transportation Research Record, No. 2105, pp. 28–36.
Stopher, P. R., Jiang, Q., & FitzGerald, C., 2005. Processing GPS data from travel surveys, paper presented at 2nd International Colloqium on the Behavioural Foundations of Integrated Land-use and Transportation Models: Frameworks, Models and Applications, Toronto, June 2005.
Susilo, Y. O., Kitamura, R., 2005. Analysis of Day-to-Day Variability in an Individual’s Action Space: Exploration of 6-Week Mobidrive Travel Diary Data. Transportation Research Record, No. 1902, pp. 124–133.
Tsui, S. Y. A., Shalaby, A., 2006. An Enhanced System for Link and Mode Identification for GPS-Based Personal Travel Surveys. Transportation Research Record, No. 1972, pp. 38–45.
Wagner, D. P., 1997. Lexington Area Travel Data Collection Test: GPS for Personal Travel Surveys, Final Report, Federal Highway Administration, Battelle Transport Division, Columbus, September 1997.
Wolf, J., 2000. Using GPS Data Loggers to Replace Travel Diaries in the Collection of Travel Data, PhD Thesis, Georgia Institute of Technology, Atlanta, Georgia.
Wolf, J., 2006. Applications of New Technologies in Travel Surveys, in P. R. Stopher and C. C. Stecher (eds.) Travel Survey Methods - Quality and Future Directions, 531–544, Elsevier, Oxford.
Zhou, J., Golledge, R., 2000. An Analysis of Household Travel Behavior Based on GPS, paper presented at the 9th International Association for Travel Behavior Research Conference, Gold Coast, Australia, July 2-7.