Spatiotemporal Reconstruction of the Traffic State

Abstract

A detailed representation of the traffic state in space and time allows us to analyze various aspects of traffic dynamics. However, since traffic data are only available for a small subset of locations and times, the full traffic state can only be reconstructed by spatiotemporal interpolation, which can be formulated in terms of a convolution integral. Since naive “isotropic” interpolation is inadequate for traffic data, we introduce a more refined interpolation method. This adaptive smoothing method yields a detailed and plausible reconstruction of the traffic state. Finally, we discuss the combination and weighting of multiple, heterogeneous data sources for estimating the traffic state (data fusion).

Amazement is the beginning of knowledge.

Plato

Further Reading

• Treiber, M., Helbing, D.: Reconstructing the spatio-temporal traffic dynamics from stationary detector data. Cooper@tive Tr@nsport@tion Dyn@mics 1 (2002) 3.1–3.24 (Internet Journal, www.TrafficForum.org/journal)

• Treiber, M., Kesting, A., Wilson, R.E.: Reconstructing the traffic state by fusion of heterogeneous data Computer-Aided Civil and Infrastructure Engineering 26 (2011), 408–419

• van Lint, J., Hoogendoorn, S.P.: A robust and efficient method for fusing heterogeneous data from traffic sensors on freeways. Computer-Aided Civil and Infrastructure Engineering 24 (2009) 1–17