Hybrid traffic state estimation and prediction using pattern recognition
Thien Tin Nguyen (TU Delft - Transport and Planning)
SC Calvert (TU Delft - Transport and Planning)
JWC Lint (TU Delft - Transport and Planning)
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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).