A Bayesian mixture model for short-term average link travel time estimation using large-scale limited information trip-based data

Accurate estimation and prediction of urban link travel times are important for urban traffic operations and management. This paper develops a Bayesian mixture model to estimate short-term average urban link travel times using large-scale trip-based data with partial information. Unlike typical GPS...

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Veröffentlicht in:	Automation in construction Jg. 72; S. 237 - 246
Hauptverfasser:	Zhan, Xianyuan, Ukkusuri, Satish V., Yang, Chao
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 01.12.2016 Elsevier BV
Schlagworte:	Bayesian analysis Bayesian mixture model Economic models EM algorithm Estimation Path inference Probabilistic methods Probability theory Scale (ratio) Short term Short-term average link travel time estimation Spatial dependencies Traffic engineering Traffic flow Traffic information Traffic management Traffic models Travel Travel time Trip based data with partial information Trip estimation Variance (statistics) Welfare economics Short-term average link travel time estimation Bayesian mixture model EM algorithm Trip based data with partial information Path inference
ISSN:	0926-5805, 1872-7891
Online-Zugang:	Volltext
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