Review of Incident Duration Prediction Methods
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
www.ijsr.net | Open Access | Fully Refereed | Peer Reviewed International Journal

ISSN: 2319-7064


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Review Papers | Computer Science & Engineering | Iraq | Volume 9 Issue 1, January 2020

Review of Incident Duration Prediction Methods

Zainab Ali Mohammed, Mohammed Najm Abdullah, Imad Hussain Al-Hussaini

Traffic incidents cause a significant loss of life, economy, and productivity over injuries and fatalities, extended travel time and delay, and air pollution. Traffic incidents are one of the main causes of the Non-recurrent congestion which in turn can lead to secondary incidents. Predicting accurately incident duration plays an important role in reducing the influence of the Non-recurrent congestion on road capacity reduction and massive travel time loss. The objective of this paper is to give a thorough review of the studies and researches, mainly include the various phases of incident duration, data resources, and the different methods that are used in the duration time prediction and traffic incident duration influence factor analysis

Keywords: Incident Duration, Prediction, Machine Learning, Influence Factors

Edition: Volume 9 Issue 1, January 2020

Pages: 292 - 298

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How to Cite this Article?

Zainab Ali Mohammed, Mohammed Najm Abdullah, Imad Hussain Al-Hussaini, "Review of Incident Duration Prediction Methods", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=ART20203779, Volume 9 Issue 1, January 2020, 292 - 298

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