With the development of and advances in smartphones and global positioning system (GPS) devices, travelers’ long-term travel behaviors are not impossible to obtain. This study investigates the pattern of individual travel behavior and its correlation with social-demographic features. For different social-demographic groups (e.g., full-time employees and students), the individual travel behavior may have specific temporal-spatial-mobile constraints. The study first extracts the home-based tours, including Home-to-Home and Home-to-Non-Home, from long-term raw GPS data. The travel behavior pattern is then delineated by home-based tour features, such as departure time, destination location entropy, travel time, and driving time ratio. The travel behavior variability describes the variances of travelers’ activity behavior features for an extended period. After that, the variability pattern of an individual’s travel behavior is used for estimating the individual’s social-demographic information, such as social-demographic role, by a supervised learning approach, support vector machine. In this study, a long-term (18-month) recorded GPS data set from Puget Sound Regional Council is used. The experiment’s result is very promising. The sensitivity analysis shows that as the number of tours thresholds increases, the variability of most travel behavior features converges, while the prediction performance may not change for the fixed test data.


    Access

    Download


    Export, share and cite



    Title :

    Prediction of Individual Social-Demographic Role Based on Travel Behavior Variability Using Long-Term GPS Data


    Contributors:
    Lei Zhu (author) / Jeffrey Gonder (author) / Lei Lin (author)


    Publication date :

    2017




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




    Long-term travel time prediction using gradient boosting

    Chen, Che-Ming / Liang, Chia-Ching / Chu, Chih-Peng | Taylor & Francis Verlag | 2020




    Travel prediction with models of individual choice behavior.

    Koppelman, Frank S | DSpace@MIT | 1975

    Free access