Identifying the Most Critical Transportation Intersections using Social Network Analysis
Traffic congestion negatively impacts our society. Most of the traditional transportation planning techniquesâ€“though effectiveâ€“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 systemsâ€“as well as developing a model that utilizes different SNA centrality measures within the transportation contextâ€“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.
I. H. El-adaway et al., "Identifying the Most Critical Transportation Intersections using Social Network Analysis," Transportation Planning and Technology, vol. 41, no. 4, pp. 353 - 374, Routledge, May 2018.
The definitive version is available at https://doi.org/10.1080/03081060.2018.1453456
Civil, Architectural and Environmental Engineering
Keywords and Phrases
Intersections; Planning; Social networking (online); Transportation, Case-studies; Centrality measures; Complementary tools; Department of Transportation; Traditional techniques; Transportation network; Transportation planning; Transportation system, Traffic congestion, network analysis; social network; traffic congestion; transportation planning; transportation system, Louisiana; United States
International Standard Serial Number (ISSN)
Article - Journal
© 2018 Routledge, All rights reserved.
01 May 2018