Abstract
In this study, we characterize traffic density modeled from coarse data by using data signatures to effectively and efficiently represent traffic flow behavior. Using the 2006 North Luzon Expressway Balintawak-North Bound (NLEX Blk-NB) hourly traffic volume and time mean speed data sets provided by the National Center for Transportation Studies (NCTS), we generate hourly traffic density data set. Each point in the data was represented by a 4D data signature where cluster models and 2D visualizations were formulated and varying traffic density behaviors were identified, i.e. high and low traffic congestions, outliers, etc. Best-fit curves, confidence bands and ellipses were generated in the visualizations for additional cluster information. We ascertain probable causes of the behaviors to provide insights for better traffic management in the expressway. Finally, from a finer-grained 6-minute interval NLEX Blk-NB density data set, the coarser-grained hourly density data set were validated for consistency and correctness of results.
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References
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Maravilla, R.G., Tabanda, E.A., Malinao, J.A., Adorna, H.N. (2011). Data Signature-Based Time Series Traffic Analysis on Coarse-Grained NLEX Density Data Set. In: Kim, Th., et al. Communication and Networking. FGCN 2011. Communications in Computer and Information Science, vol 266. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27201-1_24
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DOI: https://doi.org/10.1007/978-3-642-27201-1_24
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