Using Probe Person Data for Travel Mode Detection

Authors: Muhammad Awais Shafique, Eiji Hato, Hideki Yaginuma

Abstract:

Recently GPS data is used in a lot of studies to automatically reconstruct travel patterns for trip survey. The aim is to minimize the use of questionnaire surveys and travel diaries so as to reduce their negative effects. In this paper data acquired from GPS and accelerometer embedded in smart phones is utilized to predict the mode of transportation used by the phone carrier. For prediction, Support Vector Machine (SVM) and Adaptive boosting (AdaBoost) are employed. Moreover a unique method to improve the prediction results from these algorithms is also proposed. Results suggest that the prediction accuracy of AdaBoost after improvement is relatively better than the rest.

Keywords: Accelerometer, AdaBoost, GPS, Mode Prediction, Support vector Machine.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1096211

References:

[1] W. Brög, E. Erl, A. H. Meyburg, & M. J. Wermuth, "Problems of Non-reported Trips in Survey of Non-home Activity Patterns.” Transportation Research Record 891. 1982, pp. 1-5.
[2] A. Richardson, & E. Ampt, "Nonresponse Issues in Household Travel Surveys.” Conference Proceedings 10 – Household Travel Surveys: New Concepts and Research Needs. National Academy Press, Washington D.C., USA, 1996, pp. 79-114.
[3] J. P. Zmud, & C. H. Arce, "Item Nonresponse in Travel Surveys: Causes and Solutions.” Paper presented at the International Conference on Transport Survey Quality and Innovation, Grainau, Germany, 1997.
[4] E. Murakami, & D. P. Wagner, "Can using global positioning system (GPS) improve trip reporting?” Transportation Research Part C, 7, 1999, pp. 149-165.
[5] D. Pearson, "Global Positioning System (GPS) and Travel Surveys: Results from the 1997 Austin Household Survey.” Paper presented at the 8th Conference on the Application of Transportation Planning Methods, Corpus Christi, Texas, 2001.
[6] J. Wolf, R. Guensler, & W. Bachman, "Elimination of the Travel Diary: An Experiment to Derive Trip Purpose From GPS Travel Data.” Paper presented at the 80th Annual Meeting of the Transportation Research Board, January 7-11, 2001, Washington, D.C.
[7] P. Stopher, C. Fitzgerald, & J. Zhang, "Search for a Global Positioning System Device to Measure Person Travel.” Transportation Research Part C, 16, 2007, pp. 350-369.
[8] W. Bohte, & K. Maat, "Deriving and validating trip purposes and travel modes for multi-day GPS-based travel surveys: A large-scale application in the Netherlands.” Transportation Research Part C, 17, 2009, pp. 285-297.
[9] H. Gong, C. Chen, E. Bialostozky, & C. T. Lawson, "A GPS/GIS method for travel mode”, 2012.
[10] Y. Asakura, & E. Hato, "Tracking survey for individual travel behavior using mobile communication instruments.” Transportation Research Part C, 12, 2004, pp. 273-291.
[11] M. Bierlaire, J. Chen, & J. Newman, "Modeling Route Choice Behavior from Smartphone GPS data.” Report TRANSP-OR 101016. Transport and Mobility Laboratory, Ecole Polytechnique Fédérale de Lausanne, October 2010.
[12] P. Nitsche, P. Widhalm, S. Breuss, & P. Maurer, "A strategy on how to utilize smartphones for automatically reconstructing trips in travel surveys.” Procedia - Social and Behavioral Sciences 48, 2012, pp. 1033 – 1046.
[13] Statistics Bureau Japan website, Portal site of official statistics of Japan (accessed 16 July 2013). Available from: http://www.e-stat.go.jp/SG1/ estat/NewListE.do?tid=000001039448.
[14] Japan Meteorological Agency website, Historic monthly values (accessed 15 July 2013). Available from: http://www.data.jma.go.jp/obd/stats/data/ en/smp/index.html.
[15] E. Hato, "Development of behavioral context addressable loggers in the shell for travel-activity analysis.” Transportation Research Part C 18, 2010, pp. 55–67.