Analysis of Road Networks Using the Louvian Community Detection Algorithm

  • R. Rashmi
  • Shivani Champawat
  • G. Varun Teja
  • K. LavanyaEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1057)


In today’s world, the population is increasing rapidly that make people move in and out of the countries/states for various reasons. With the evolution of technology, there is an advancement in transportation, and traveling across places has become easier than before. Now, we have various means of transport to move around the world. Though the most preferred way to travel is the roadways, there are roads built that connect cities and states together. But we also have a few disadvantages like increase in the vehicle registrations, amount of pollution, and the number of road accidents. This paper addresses an issue related to the traffic congestion caused due to the vehicles and analyzes the traffic at a particular area based on the threshold using the Louvain community detection algorithm. The Louvain algorithm is a graph algorithm used to detect the communities within a particular region and then form clusters. The algorithm is implemented on a US road network in Neo4j to detect the traffic and provide an alternative route for conveyance.


Clusters Communities Louvain algorithm Neo4j Road network 


  1. 1.
  2. 2.
    Generalized Louvain method for community detection in large networks (Research Article: Pasquale De Meo Published: Nov 2011)Google Scholar
  3. 3.
    Graph Database A Survey (Research Article: Rohit Kumar Kaliyar Published: International Conference on Computing, Communication & Automation ,2015)Google Scholar
  4. 4.
    Tensor-based Document Retrieval over Neo4j with an Application to PubMed Mining (Research Article: G Drakopoulos Published: July 2016)Google Scholar
  5. 5.
    Tensor fusion of social structural and functional analytics over Neo4j (Research Article: G Drakopoulos Published: July 2016)Google Scholar
  6. 6.
    Storage and parallel topology processing of the power network based on Neo4j (Research Article: Xianlong Lv et al Published: 2017)Google Scholar
  7. 7.
    Smart RDF Data storage in Graph Databases: (Research Article: Roberto De Virgilio Published: IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing ,2017)Google Scholar
  8. 8.
    Community detection through likelihood optimization: in search of a sound model (Research Article: Liudmila Prokhorenkova Published: 11 July 20)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • R. Rashmi
    • 1
  • Shivani Champawat
    • 1
  • G. Varun Teja
    • 1
  • K. Lavanya
    • 1
    Email author
  1. 1.School of Computer Science and EngineeringVIT UniversityVelloreIndia

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