Citation

Fragkou AD, Karakasidis TE, Nathanail E. Chaos Solitons Fractals 2018; 28(6): e063108.

Affiliation

Traffic, Transportation and Logistics Laboratory, Department of Civil Engineering, University of Thessaly, 38334 Volos, Greece.

Copyright

(Copyright © 2018, Elsevier Publishing)

DOI

10.1063/1.5024924

PMID

29960398

Abstract

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.

Language: en