Abstract

We present our latest results on developing and implementing a traffic congestion mode and vehicle density estimator for a segment of Interstate 210 in Southern California. Using a mixture Kalman filtering (MKF) algorithm on the switching-mode traffic model, the estimator is able to provide estimated vehicle densities at unmeasured locations, as well as the congestion statuses (free-flow or congested), which are not directly observed. The program runs efficiently, thus making it possible to carry out estimation in real time.


Original document

The different versions of the original document can be found in:

http://dx.doi.org/10.23919/acc.2004.1383770
http://www.nt.ntnu.no/users/skoge/prost/proceedings/acc04/Papers/0375_ThA05.1.pdf,
https://www.me.berkeley.edu/~horowitz/Publications_files/All_papers_numbered/138c_Sun_MKF_EstimACC_2004.pdf,
https://academic.microsoft.com/#/detail/2156145130
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Published on 01/01/2018

Volume 2018, 2018
DOI: 10.23919/acc.2004.1383770
Licence: CC BY-NC-SA license

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