Road traffic states estimation algorithm based on matching of regional traffic attracters
To effectively solve the traffic data problems such as data invalidation in the process of the acquisition of road traffic states, a road traffic states estimation algorithm based on matching of the regional traffic attracters was proposed in this work. First of all, the road traffic running states...
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Published in | Journal of Central South University Vol. 21; no. 5; pp. 2100 - 2107 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Heidelberg
Central South University
01.05.2014
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Subjects | |
Online Access | Get full text |
ISSN | 2095-2899 2227-5223 |
DOI | 10.1007/s11771-014-2159-1 |
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Summary: | To effectively solve the traffic data problems such as data invalidation in the process of the acquisition of road traffic states, a road traffic states estimation algorithm based on matching of the regional traffic attracters was proposed in this work. First of all, the road traffic running states were divided into several different modes. The concept of the regional traffic attracters of the target link was put forward for effective matching. Then, the reference sequences of characteristics of traffic running states with the contents of the target link’s traffic running states and regional traffic attracters under different modes were established. In addition, the current and historical regional traffic attracters of the target link were matched through certain matching rules, and the historical traffic running states of the target link corresponding to the optimal matching were selected as the initial recovery data, which were processed with Kalman filter to obtain the final recovery data. Finally, some typical expressways in Beijing were adopted for the verification of this road traffic states estimation algorithm. The results prove that this traffic states estimation approach based on matching of the regional traffic attracters is feasible and can achieve a high accuracy. |
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ISSN: | 2095-2899 2227-5223 |
DOI: | 10.1007/s11771-014-2159-1 |