Framework for Estimating Congestion performance measures: from data collection to reliability analysis: case study of Stockholm
2008 (English)Licentiate thesis, monograph (Other scientific)
For operational and planning purposes it is important to observe and predict the traffic performance of congested urban road links and networks. Congestion can be defined as traffic conditions caused by a downstream bottleneck or excess in travel time from what is incurred during light or free-flow travel conditions. Factors affecting definitions of congestion for specific studies are reviewed and an inventory of proposed congestion performance measures is presented for both definitions of congestion.
Swedish Road Administration has recognized the reliability of the estimations of congestion levels as an important factor when describing the traffic condition in the road traffic network. Traffic data collected for the Stockholm congestion charging trials was used to estimate selected congestion performance measures and to analyze their statistical characteristics and applicability. A comparative analysis of data collection methods is provided and further recommendations for their using estimating Congestion Performance Measures.
The reliability of the estimations of each Congestion Performance Measure is evaluated for different area networks and different time periods of the day. These series of observations are further studied aiming to identify systematic differences in the reliability of the estimations. A reliability ranking is provided for guiding future studies in the selection of estimators. Further, a simplify methodology for estimating recommended sample sized under budget restricted conditions is provided.
Place, publisher, year, edition, pages
Stockholm: KTH , 2008. , 116 p.
Trita-TEC-LIC, ISSN 1653-445X ; 08:001
IdentifiersURN: urn:nbn:se:kth:diva-4625ISBN: 978-91-85539-28-4OAI: oai:DiVA.org:kth-4625DiVA: diva2:13128
2008-02-13, TLA seminarium, KTH, Teknikringen 78B, 1 tr, Stockholm, 15:00
Hugosson, Muriel Beser, Tekn dr
QC 201011182008-01-312008-01-312012-12-17Bibliographically approved