Using Crowd Sensed Data as Input to Congestion Model

Publication: Research - peer-reviewArticle in proceedings

Documents

DOI

Emission of airborne pollutants and climate gasses from the transport sector is a growing problem, both in indus- trialised and developing countries. Planning of urban transport system is essential to minimise the environmental, health and economic impact of congestion in the transport system. To get accurate and timely information on traffic congestion, and by extension information on air pollution, near real time traffic models are needed. We present in this paper an implementation of the Restricted Stochastic User equilibrium model, that is capable to model congestions for very large Urban traffic systems, in less than an hour. The model is implemented in an open source database system, for easy interface with GIS resources and crowd sensed transportation data.
Original languageEnglish
Title of host publication2016 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops) : The Third International Workshop on Crowd Assisted Sensing Pervasive Systems and Communications
Number of pages6
PublisherIEEE Press
Publication year10 Apr 2016
ISBN (electronic)978-1-5090-1941-0
DOIs
StatePublished - 10 Apr 2016
Event - Sydney, Australia

Workshop

Workshop2016 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops)
LandAustralia
BySydney
Periode14/03/201618/03/2016
Internetadresse

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ID: 108946062