Exploring urban traffic flow dynamics

Adam Malcontenti-Wilson; Hai L. Vu; Peter Cadusch; Philip Branch; Hans Van Lint; Serge Hoogendoorn

doi:10.1109/ITSC.2013.6728207

Exploring urban traffic flow dynamics

Adam Malcontenti-Wilson
, Hai L. Vu
, Peter Cadusch
, Philip Branch
, Hans Van Lint
, Serge Hoogendoorn

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

1 Citation (Scopus)

Abstract

Important statistical characteristics of traffic can be examined via the reconstruction of a so-called phase-space where each point in that space represents a state of traffic and vice versa. Statistical tools such as recurrence analysis can then be used to visualize the temporal evolution of traffic and to assess its non-stationarity structure as an indicator for irregular behaviour. In this paper we investigate, examine and analyze the short-term non-stationary features present in traffic flows based on the historical data available from stop-line detectors collected from a small number of intersections in the Melbourne CBD, Australia and demonstrate that recurrence analysis has considerable potential in identifying changes within the temporal behaviour of traffic.

Original language	English
Title of host publication	2013 16th International IEEE Conference on Intelligent Transportation Systems
Subtitle of host publication	Intelligent Transportation Systems for All Modes, ITSC 2013
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	35-40
Number of pages	6
ISBN (Print)	9781479929146
DOIs	https://doi.org/10.1109/ITSC.2013.6728207
Publication status	Published - 2013
Externally published	Yes
Event	IEEE Conference on Intelligent Transportation Systems 2013 - The Hague, Netherlands Duration: 6 Oct 2013 → 9 Oct 2013 Conference number: 16th https://ieeexplore.ieee.org/xpl/conhome/6712176/proceeding (Proceedings)

Conference

Conference	IEEE Conference on Intelligent Transportation Systems 2013
Abbreviated title	ITSC 2013
Country/Territory	Netherlands
City	The Hague
Period	6/10/13 → 9/10/13
Internet address	https://ieeexplore.ieee.org/xpl/conhome/6712176/proceeding (Proceedings)

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10.1109/ITSC.2013.6728207

Cite this

Malcontenti-Wilson, A., Vu, H. L., Cadusch, P., Branch, P., Van Lint, H., & Hoogendoorn, S. (2013). Exploring urban traffic flow dynamics. In 2013 16th International IEEE Conference on Intelligent Transportation Systems: Intelligent Transportation Systems for All Modes, ITSC 2013 (pp. 35-40). Article 6728207 IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ITSC.2013.6728207

@inproceedings{ce5cd6b5ae694aada7db269d6080f76c,

title = "Exploring urban traffic flow dynamics",

abstract = "Important statistical characteristics of traffic can be examined via the reconstruction of a so-called phase-space where each point in that space represents a state of traffic and vice versa. Statistical tools such as recurrence analysis can then be used to visualize the temporal evolution of traffic and to assess its non-stationarity structure as an indicator for irregular behaviour. In this paper we investigate, examine and analyze the short-term non-stationary features present in traffic flows based on the historical data available from stop-line detectors collected from a small number of intersections in the Melbourne CBD, Australia and demonstrate that recurrence analysis has considerable potential in identifying changes within the temporal behaviour of traffic.",

author = "Adam Malcontenti-Wilson and Vu, \{Hai L.\} and Peter Cadusch and Philip Branch and \{Van Lint\}, Hans and Serge Hoogendoorn",

year = "2013",

doi = "10.1109/ITSC.2013.6728207",

language = "English",

isbn = "9781479929146",

pages = "35--40",

booktitle = "2013 16th International IEEE Conference on Intelligent Transportation Systems",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States of America",

note = "IEEE Conference on Intelligent Transportation Systems 2013 , ITSC 2013 ; Conference date: 06-10-2013 Through 09-10-2013",

url = "https://ieeexplore.ieee.org/xpl/conhome/6712176/proceeding",

}

Malcontenti-Wilson, A, Vu, HL, Cadusch, P, Branch, P, Van Lint, H & Hoogendoorn, S 2013, Exploring urban traffic flow dynamics. in 2013 16th International IEEE Conference on Intelligent Transportation Systems: Intelligent Transportation Systems for All Modes, ITSC 2013., 6728207, IEEE, Institute of Electrical and Electronics Engineers, pp. 35-40, IEEE Conference on Intelligent Transportation Systems 2013 , The Hague, Netherlands, 6/10/13. https://doi.org/10.1109/ITSC.2013.6728207

Exploring urban traffic flow dynamics. / Malcontenti-Wilson, Adam; Vu, Hai L.; Cadusch, Peter et al.
2013 16th International IEEE Conference on Intelligent Transportation Systems: Intelligent Transportation Systems for All Modes, ITSC 2013. IEEE, Institute of Electrical and Electronics Engineers, 2013. p. 35-40 6728207.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

TY - GEN

T1 - Exploring urban traffic flow dynamics

AU - Malcontenti-Wilson, Adam

AU - Vu, Hai L.

AU - Cadusch, Peter

AU - Branch, Philip

AU - Van Lint, Hans

AU - Hoogendoorn, Serge

N1 - Conference code: 16th

PY - 2013

Y1 - 2013

N2 - Important statistical characteristics of traffic can be examined via the reconstruction of a so-called phase-space where each point in that space represents a state of traffic and vice versa. Statistical tools such as recurrence analysis can then be used to visualize the temporal evolution of traffic and to assess its non-stationarity structure as an indicator for irregular behaviour. In this paper we investigate, examine and analyze the short-term non-stationary features present in traffic flows based on the historical data available from stop-line detectors collected from a small number of intersections in the Melbourne CBD, Australia and demonstrate that recurrence analysis has considerable potential in identifying changes within the temporal behaviour of traffic.

AB - Important statistical characteristics of traffic can be examined via the reconstruction of a so-called phase-space where each point in that space represents a state of traffic and vice versa. Statistical tools such as recurrence analysis can then be used to visualize the temporal evolution of traffic and to assess its non-stationarity structure as an indicator for irregular behaviour. In this paper we investigate, examine and analyze the short-term non-stationary features present in traffic flows based on the historical data available from stop-line detectors collected from a small number of intersections in the Melbourne CBD, Australia and demonstrate that recurrence analysis has considerable potential in identifying changes within the temporal behaviour of traffic.

UR - https://www.scopus.com/pages/publications/84894384882

U2 - 10.1109/ITSC.2013.6728207

DO - 10.1109/ITSC.2013.6728207

M3 - Conference Paper

AN - SCOPUS:84894384882

SN - 9781479929146

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EP - 40

BT - 2013 16th International IEEE Conference on Intelligent Transportation Systems

PB - IEEE, Institute of Electrical and Electronics Engineers

T2 - IEEE Conference on Intelligent Transportation Systems 2013

Y2 - 6 October 2013 through 9 October 2013

ER -

Malcontenti-Wilson A, Vu HL, Cadusch P, Branch P, Van Lint H, Hoogendoorn S. Exploring urban traffic flow dynamics. In 2013 16th International IEEE Conference on Intelligent Transportation Systems: Intelligent Transportation Systems for All Modes, ITSC 2013. IEEE, Institute of Electrical and Electronics Engineers. 2013. p. 35-40. 6728207 doi: 10.1109/ITSC.2013.6728207

Exploring urban traffic flow dynamics

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