Paper Title:
Forecasting Traffic Volume with Space-Time ARIMA Model
  Abstract

The paper proposes a space–time autoregressive integrated moving average (STARIMA) model to predict the traffic volume in urban areas. The methodological framework incorporates the historical traffic data and the spatial features of a road network. Moreover, the spatial characteristics in a way that reflects not only the distance but also the average travel speed on the links. In order to response the time-varying speed, six traffic modes are classified by level of service (LOS) which is updated in 5 minute interval. In the end, with the real traffic data in Beijing for experiments, the model achieves a very good accuracy on the 5 minute interval forecasting, it also provides a sufficient accuracy of 30 minute interval forecasting compared with ARIMA model.

  Info
Periodical
Advanced Materials Research (Volumes 156-157)
Edited by
Jingtao Han, Zhengyi Jiang and Sihai Jiao
Pages
979-983
DOI
10.4028/www.scientific.net/AMR.156-157.979
Citation
Q. Y. Ding, X. F. Wang, X. Y. Zhang, Z. Q. Sun, "Forecasting Traffic Volume with Space-Time ARIMA Model", Advanced Materials Research, Vols. 156-157, pp. 979-983, 2011
Online since
October 2010
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Price
$32.00
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