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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Marinica, N.E. Sarlette, A. Boel, R.K. |
| Copyright Year | 2000 |
| Abstract | Raw measurement data are too noisy to directly obtain queue and traffic flow estimates usable for feedback control of urban traffic. In this paper, we propose a recursive filter to estimate traffic state by combining the real-time measurements with a reduced model of expected traffic behavior. The latter is based on platoons rather than individual vehicles in order to achieve faster implementations. This new model is used as a predictor for real-time traffic estimation using the particle filtering framework. As it becomes infeasible to let a truly large traffic network be managed by one central computer, with which all the local units would have to communicate, we also propose a distributed version of the particle filter (PF) where the local estimators exchange information on flows at their common boundaries. We assess the quality of our platoon-based PFs, both centralized and distributed, by comparing their queue-size estimates with the true queue sizes in simulated data. |
| Sponsorship | IEEE Intelligent Transportation Systems Society |
| Starting Page | 1918 |
| Ending Page | 1929 |
| Page Count | 12 |
| File Size | 1339540 |
| File Format | |
| ISSN | 15249050 |
| Volume Number | 14 |
| Issue Number | 4 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-01-01 |
| Publisher Place | U.S.A. |
| Access Restriction | One Nation One Subscription (ONOS) |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Bayes methods Particle filters Stochastic systems Feedback control Urban areas urban traffic networks Bayesian estimation hybrid systems parallel particle filters (PFs) stochastic systems |
| Content Type | Text |
| Resource Type | Article |
| Subject | Automotive Engineering Mechanical Engineering Computer Science Applications |
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