Hybrid traffic state estimation and prediction using pattern recognition

Conference paper (2017)

Authors

T.T. Nguyen Transport and Planning - CEG
S.C. Calvert Transport and Planning - CEG
J.W.C. van Lint Transport and Planning - CEG
Research Group
Transport and Planning (CEG) (TU Delft)
Copyright: © 2017 T.T. Nguyen, S.C. Calvert, J.W.C. van Lint
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Published Date

2017

Language

English

Reuse Rights

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Faculty

Civil Engineering & Geosciences

Department

Transport and Planning

Research Group

Transport and Planning

Abstract

Traffic state estimation is an important task that has attracted a lot of research effort in recent decades. The main goal of traffic state estimation is to turn measured data, which is normally noisy and incomplete, into meaningful information for further investigation, either offline or online (e.g. traffic management and control).