Open AccessCalibration Framework based on Bluetooth Sensors for Traffic State Estimation Using a Velocity based Cell Transmission Model
Author(s) -
Andreas Allström,
Alexandre M. Bayen,
Magnus Fransson,
David Gundlegård,
Anthony D. Patire,
Clas Rydergren,
Mats Sandin
Publication year - 2014
Publication title -
transportation research procedia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.657
H-Index - 40
eISSN - 2352-1465
pISSN - 2352-1457
DOI - 10.1016/j.trpro.2014.10.077
Subject(s) - cell transmission model , calibration , kalman filter , ensemble kalman filter , data assimilation , bluetooth , computer science , transmission (telecommunications) , simulation , extended kalman filter , filter (signal processing) , real time computing , engineering , geography , wireless , mathematics , meteorology , statistics , telecommunications , artificial intelligence , aerospace engineering , computer vision , intersection (aeronautics)
The velocity based cell transmission model (CTM-v) is a discrete time dynamical model that mimics the evolution of the traffic velocity field on highways. In this paper the CTM-v model is used together with an ensemble Kalman filter (EnKF) for the purpose of velocity sensor data assimilation. We present a calibration framework for the CTM-v and EnKF. The framework consists of two separate phases. The first phase is the calibration of the parameters of the fundamental diagram and the second phase is the calibration of demand and filter parameters. Results from the calibrated model are presented for a highway stretch north of Stockholm, Sweden
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