Seasonal Autoregressive Integrated Moving Average and Support Vector Machine Models: Prediction of Short-Term Traffic Flow on Freeways

Predictions of short-term traffic volume support proactive transportation management and traveler information services. To address the periodicity, nonlinearity, uncertainty, and complexity of short-term traffic forecasting, seasonal autoregressive integrated moving average (SARIMA) and support vector machine (SVM) models are often used separately to forecast the time series of traffic flow. SARIMA can discover intrinsic relations (correlations) in time series data, especially fit for modeling seasonal, stochastic time series. In contrast, SVM has a strong nonlinear mapping ability for input and output, appropriate for solving complex, nonlinear problems. The few combined schemes that have been presented previously tend to be complicated. A simple and effective novel hybrid methodology that combines the SARIMA and SVM models is proposed to take advantage of the individual strengths of the two models. Two key issues in building a hybrid model process are discussed: identification of SVM input dimensions via SARIMA and parameter optimization of the hybrid model with particle swarm optimization. Experimental results with real-world data sets indicated that the hybrid model was superior to the individual SARIMA or SVM model in terms of root mean square error and mean absolute percentage error for the prediction of the short-term traffic flow.

• Record URL:
  https://doi.org/10.3141/2215-09
• Summary URL:
  http://scholar.google.com/scholar_lookup?title=Seasonal+Autoregressive+Integrated+Moving+Average+and+Support+Vector+Machine+Models%3a+Prediction+of+Short-Term+Traffic+Flow+on+Freeways&author=N.+Zhang&author=Y.+Zhang&author=H.+Lu&publication_year=2011
• Availability:
  • Find a library where document is available. Order URL: http://www.trb.org/Main/Blurbs/Information_Systems_Geographic_Information_Systems_165941.aspx
• Authors:
  • Zhang, Ning
  • Zhang, Yunlong
  • Lu, Haiting
• Publication Date: 2011

Language

• English

Media Info

• Media Type: Print
• Features: Figures; Maps; References; Tables;
• Pagination: pp 85-92
• Monograph Title: Information Systems, Geographic Information Systems, and Advanced Computing 2011
• Serial:
  • Transportation Research Record: Journal of the Transportation Research Board
  • Issue Number: 2215
  • Publisher: Transportation Research Board
  • ISSN: 0361-1981

Subject/Index Terms

• TRT Terms: Freeways; Highway traffic control; Traffic flow; Traffic forecasting; Traffic volume; Traveler information and communication systems
• Uncontrolled Terms: Autoregressive integrated moving average models; Hybrid models; Short term forecasts; Support vector machines
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Planning and Forecasting; I71: Traffic Theory;

Filing Info

• Accession Number: 01337556
• Record Type: Publication
• ISBN: 9780309167291
• Report/Paper Numbers: 11-2557
• Files: TRIS, TRB, ATRI
• Created Date: Apr 21 2011 1:10PM