By Topic

An Extended Kalman Filter Application for Traffic State Estimation Using CTM with Implicit Mode Switching and Dynamic Parameters

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Tampere, C.M.J. ; Katholieke Univ. Leuven, Leuven ; Immers, L.H.

This paper presents a traffic state estimation and prediction model based on the cell transmission model (CTM). The nonlinear CTM is transcribed in a closed analytical state-space form for use within a general extended Kalman filtering framework. The state-space CTM switches implicitly between numerous possible linear modes. The paper provides measurement models for the traffic state and model parameters for automatically estimating traffic conditions and model parameters in an online context. The applicability of the approach is illustrated in a real and a simulated case study.

Published in:

Intelligent Transportation Systems Conference, 2007. ITSC 2007. IEEE

Date of Conference:

Sept. 30 2007-Oct. 3 2007