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Using principal curves to analyse traffic patterns on freeways.

By Jochen Einbeck and Jo Dwyer

Abstract

Scatterplots of traffic speed versus flow have caught considerable attention over the last decades due to their characteristic half-moon like shape. Modelling data of this type is difficult as both variables are actually not a function of each other in the sense of causality, but are rather jointly generated by a third latent variable, which is a monotone function of the traffic density. We propose local principal curves as a tool to describe and model speed-flow data, which takes this viewpoint into account. We introduce the concept of calibration curves to determine the relationship between the latent variable (represented by the parametrization of the principal curve) and the traffic density. We apply local principal curves to a variety of speed-flow diagrams from Californian freeways, including some so far unreported pattern

Topics: Fundamental diagram, Capacity, Local principal curves, Smoothing.
Publisher: Taylor & Francis
Year: 2011
DOI identifier: 10.1080/18128600903500110
OAI identifier: oai:dro.dur.ac.uk.OAI2:7546
Journal:

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  1. (2008). A generic characterization of equilibrium speed-flow curves.
  2. (2007). A nested clustering technique for freeway operating condition classification. doi
  3. (2002). A new approach for modelling of fundamental diagrams. doi
  4. (2003). An application of neural network on traffic speed prediction under adverse weather condition.
  5. (2009). Core Team
  6. (2007). Empirical features of congested traffic states and their implications for traffic modelling.
  7. (2004). Freeway performance measurement system (PeMS) version 4.
  8. (2007). Generalized monotonic regression based on B-splines with an application to air pollution data. doi
  9. (2001). Modeling traffic’s flow-density relation: Accomodation of multiple flow regimes and traveler types.
  10. (1989). Principal curves.
  11. (2007). pspline: Penalized Smoothing Splines. R package version 1.0-12. R port by Brian Ripley.
  12. (2008). Realtime merging traffic control with applications to toll plaza and work zone man29 agement.
  13. (2009). Short-term prediction of traffic dynamics with real-time recurrent learning algorithms. doi
  14. (1952). Some theorectical aspects of road traffic research. doi
  15. (1992). Synthesis of recent work on the nature of speed-flow and flow-occupancy (or density) relations on freeways.
  16. (2001). The mathematics of high-tech highways.
  17. (2001). The PeMS algorithms for accurate, real-time estimates of g-factors and speeds from single-loop detectors.

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