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arXiv 1609.024092016-09-06cs.CVmath.PRstat.APstat.CO

Comparison of several short-term traffic speed forecasting models

Ateneo de Manila University（马尼拉雅典耀大学）

John Boaz Lee, Kardi Teknomo

备注：: 6 pages, Lee, J. B. and Teknomo, K. (2014) A review of various short-term traffic speed forecasting models, Proceeding of the 12th National Conference in Information Technology Education (NCITE 2014), October 23 - 25, 2014, Boracay, Philippines

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The widespread adoption of smartphones in recent years has made it possible for us to collect large amounts of traffic data. Special software installed on the phones of drivers allow us to gather GPS trajectories of their vehicles on the road network. In this paper, we simulate the trajectories of multiple agents on a road network and use various models to forecast the short-term traffic speed of various links. Our results show that traditional techniques like multiple regression and artificial neural networks work well but simpler adaptive models that do not require prior training also perform comparatively well.

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