A Mesoscopic Traffic Data Assimilation Framework for Vehicle Density Estimation on Urban Traffic Networks Based on Particle Filters
Traffic conditions can be more accurately estimated using data assimilation techniques since these methods incorporate an imperfect traffic simulation model with the (partial) noisy measurement data. In this paper, we propose a data assimilation framework for vehicle density estimation on urban traf...
Main Authors: | Song Wang, Xu Xie, Rusheng Ju |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2019-04-01
|
Series: | Entropy |
Subjects: | |
Online Access: | https://www.mdpi.com/1099-4300/21/4/358 |
Similar Items
-
Gaussian approximations in filters and smoothers for data assimilation
by: Matthias Morzfeld, et al.
Published: (2019-01-01) -
Data Assimilation for Spatial Temporal Simulations Using Localized Particle Filtering
by: Long, Yuan
Published: (2016) -
Robust Data Assimilation in River Flow and Stage Estimation Based on Multiple Imputation Particle Filter
by: Zool Hilmi Ismail, et al.
Published: (2019-01-01) -
Weighted ensemble transform Kalman filter for image assimilation
by: Sebastien Beyou, et al.
Published: (2013-01-01) -
Data Assimilation in Air Contaminant Dispersion Using a Particle Filter and Expectation-Maximization Algorithm
by: Rongxiao Wang, et al.
Published: (2017-09-01)