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Identifying the most critical transportation intersections using social network analysis

Author

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  • Islam H. El-adaway
  • Ibrahim Abotaleb
  • Eric Vechan

Abstract

Traffic congestion negatively impacts our society. Most of the traditional transportation planning techniques – though effective – require rigorous amounts of data and analysis which consumes time and resources. This paper uses social network analysis (SNA) to analyze transportation networks, and consequently corroborate the effectiveness of SNA as a complementary tool for improved transportation planning. After creating the connection between the language and concepts of SNA and those of transportation systems – as well as developing a model that utilizes different SNA centrality measures within the transportation context – the authors utilize SNA to investigate traffic networks in three case studies in the state of Louisiana, analyze the results and draw conclusions. To this effect, with minimal cost and time, the model identifies the most critical intersections that should be further investigated using traditional techniques. These results are in agreement with the findings of Louisiana’s Department of Transportation and Development.

Suggested Citation

  • Islam H. El-adaway & Ibrahim Abotaleb & Eric Vechan, 2018. "Identifying the most critical transportation intersections using social network analysis," Transportation Planning and Technology, Taylor & Francis Journals, vol. 41(4), pages 353-374, May.
    • Handle: RePEc:taf:transp:v:41:y:2018:i:4:p:353-374
    DOI: 10.1080/03081060.2018.1453456
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    Cited by:

    1. Tu Anh Trinh & Ducksu Seo & Unchong Kim & Thi Nhu Quynh Phan & Thi Hai Hang Nguyen, 2022. "Air Transport Centrality as a Driver of Sustainable Regional Growth: A Case of Vietnam," Sustainability, MDPI, vol. 14(15), pages 1-14, August.
    2. Van Nguyen, Truong & Zhang, Jie & Zhou, Li & Meng, Meng & He, Yong, 2020. "A data-driven optimization of large-scale dry port location using the hybrid approach of data mining and complex network theory," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 134(C).

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