Pushpa Publishing House

Journal Menu

Content

Volume 17 (2018)

Volume 16 (2016)

Volume 15 (2015)

Volume 14 (2015)

Volume 13 (2014)

Volume 12 (2014)

Volume 11 (2013)

Volume 10 (2013)

Volume 9 (2012)

Volume 8 (2012)

Volume 7 (2011)

Volume 6 (2011)

Volume 5 (2010)

Volume 4 (2010)

Volume 3 (2009)

Volume 2 (2008)

	Volume 2, Issue 3 Pg 201 - 284 (November 2008)
	Volume 2, Issue 2 Pg 97 - 199 (July 2008)
	Volume 2, Issue 1 Pg 1 - 96 (March 2008)

Volume 1 (2007)

Advances in Computer Science and Engineering

Advances in Computer Science and Engineering
Volume 2, Issue 1, Pages 15 - 32 (March 2008)

SPATIAL DEPENDENCIES WITH VARIABLE TEMPORAL WINDOWS IN SHORT-TERM URBAN TRAFFIC FLOW
Eleni I. Vlahogianni (Greece)

Abstract:
The present paper provides a statistical probabilistic framework for studying the spatiotemporal patterns of volume and occupancy from sequential locations in signalized arterials. The proposed approach conceptually extends previous research by revealing spatial dependencies with variable temporal windows relative to the prevailing traffic conditions from multiple locations simultaneously. Traffic flow conditions are defined by four distinct regions of volume-occupancy relationship. The methodology implemented is based on the Markov Blanket Bayesian networks. Results reveal different spatio-temporal patterns arising from upstream and downstream locations in terms of the prevailing traffic flow conditions in the location of interest. Occupancy is found to be more critical in the predictive knowledge of traffic flow conditions when comparing to volume. Finally, spatio-temporal dependencies between the location of interest and the near upstream and downstream locations seem to diminish as flow propagates to critical and congested conditions.

Keywords and phrases: short-term traffic flow, spatio-temporal patterns, urban arterials, Bayesian networks, Markov blankets.

Number of Downloads: 281 | Number of Views: 615