Using Probe Person Data for Travel Mode Detection

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.

• Muhammad Awais Shafique
• Eiji Hato
• Hideki Yaginuma

• Accelerometer
• AdaBoost
• GPS
• Mode Prediction
• Support vector Machine.

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