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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. [ABSTRACT FROM AUTHOR]

This case study compares the Auto Restricted Zone Policy (ARZ) with price changes for parking permits in Louisiana State University (LSU). We find that ARZ has a more significant effect on the reduction in purchase of parking permits than price increases, albeit with a lag. We also find that while driving continues to be the primary mode of choice, a significant number of students are willing to adopt alternative means of transportation, if facilities associated with them are improved. Since LSU is fairly representative, we believe that this case study contains lessons for other universities in the country facing traffic congestion issues. [ABSTRACT FROM AUTHOR]