Print Email Facebook Twitter Hybrid traffic state estimation and prediction using pattern recognition Title Hybrid traffic state estimation and prediction using pattern recognition Author Nguyen, T.T. (TU Delft Transport and Planning) Calvert, S.C. (TU Delft Transport and Planning) van Lint, J.W.C. (TU Delft Transport and Planning) Date 2017 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). To reference this document use: http://resolver.tudelft.nl/uuid:5cd9998c-a664-4005-b94f-68c75c1bd74f Source hEART 2017: 6th Symposium of the European Association for Research in Transportation Event hEART 2017, 2017-09-12 → 2017-09-14, Technion Institute of Technology, Haifa, Israel Part of collection Institutional Repository Document type conference paper Rights © 2017 T.T. Nguyen, S.C. Calvert, J.W.C. van Lint Files PDF hEART2017_20170331.pdf 301.92 KB Close viewer /islandora/object/uuid:5cd9998c-a664-4005-b94f-68c75c1bd74f/datastream/OBJ/view