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SAE for the prediction of road traffic status from taxicab operating data and bus smart card data

Author

Listed:
  • Huang Zhengfeng

    (Faculty of Maritime and Transportation, Ningbo University, P. R. China†National Traffic Management Engineering & Technology Research Center, Ningbo University Sub-Center, P. R. China‡Jiangsu Province Collaborative Innovation Center for Modern Urban Traffic Technologies, P. R. China)

  • Zheng Pengjun

    (Faculty of Maritime and Transportation, Ningbo University, P. R. China†National Traffic Management Engineering & Technology Research Center, Ningbo University Sub-Center, P. R. China‡Jiangsu Province Collaborative Innovation Center for Modern Urban Traffic Technologies, P. R. China§Transportation Research Group, University of Southampton, UK)

  • Xu Wenjun

    (Faculty of Maritime and Transportation, Ningbo University, P. R. China)

  • Ren Gang

    (#x2021;Jiangsu Province Collaborative Innovation Center for Modern Urban Traffic Technologies, P. R. China¶School of Transportation, Southeast University, P. R. China)

Abstract

Road traffic status is significant for trip decision and traffic management, and thus should be predicted accurately. A contribution is that we consider multi-modal data for traffic status prediction than only using single source data. With the substantial data from Ningbo Passenger Transport Management Sector (NPTMS), we wished to determine whether it was possible to develop Stacked Autoencoders (SAEs) for accurately predicting road traffic status from taxicab operating data and bus smart card data. We show that SAE performed better than linear regression model and Back Propagation (BP) neural network for determining the relationship between road traffic status and those factors. In a 26-month data experiment using SAE, we show that it is possible to develop highly accurate predictions (91% test accuracy) of road traffic status from daily taxicab operating data and bus smart card data.

Suggested Citation

  • Huang Zhengfeng & Zheng Pengjun & Xu Wenjun & Ren Gang, 2017. "SAE for the prediction of road traffic status from taxicab operating data and bus smart card data," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 28(10), pages 1-10, October.
    • Handle: RePEc:wsi:ijmpcx:v:28:y:2017:i:10:n:s0129183117501212
    DOI: 10.1142/S0129183117501212
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