Detection of traffic incidents using nonlinear time series analysis.
Autor: | Fragkou AD; Laboratory of Hydromechanics and Environmental Engineering, Department of Civil Engineering, University of Thessaly, 38334 Volos, Greece., Karakasidis TE; Laboratory of Hydromechanics and Environmental Engineering, Department of Civil Engineering, University of Thessaly, 38334 Volos, Greece., Nathanail E; Traffic, Transportation and Logistics Laboratory, Department of Civil Engineering, University of Thessaly, 38334 Volos, Greece. |
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Jazyk: | angličtina |
Zdroj: | Chaos (Woodbury, N.Y.) [Chaos] 2018 Jun; Vol. 28 (6), pp. 063108. |
DOI: | 10.1063/1.5024924 |
Abstrakt: | In this study, we present results of the application of nonlinear time series analysis on traffic data for incident detection. More specifically, we analyze daily volume records of Attica Tollway (Greece) collected from sensors located at various locations. The analysis was performed using the Recurrence Plot (RP) and Recurrence Quantification Analysis (RQA) method of the volume data of the lane closest to the median. The results show that it is possible to identify, through the abrupt change of the dynamics of the system revealed by RPs and RQA, the occurrence of incidents on the freeway and differentiate from recurrent traffic congestion. The proposed methodology could be of interest for big data traffic analysis. |
Databáze: | MEDLINE |
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