Big data analytics assembles, stores, and analyzes large amounts of relevant data to monitor performance, and gain insights regarding interrelationships of various components. At the UFTI we are using various methods and tools for transportation data visualization, video analytics and crash risk, Connected and Autonomous Vehicle (CAV) operations, traffic signal control optimization, and transportation planning procedures, among others.

Selected projects, related UFTI events and resources, and bibliographical information of published papers are provided below.

Example Projects

TitlePrincipal Investigator/Co-PIsAgency/SourceDescription
Data Management and Analytics for UF Smart TestbedDr. Sanjay Ranka, Dr. Anand Rangarajan, Dhruv Mahajan, Tania BanerjeeFDOTIn this project we analyze the key requirements for developing a IoT Data Warehousing Platform that seamlessly  collects, stores and provides access to the massive amount of data generated by the different types of sensors such as loop detectors, cameras, radar, LIDAR, etc. The platform will also support deep analytics to discover insight and for decision making.
Optimizing Traffic Grids with Machine LearningDr. Sanjay Ranka, Dr. Anand Rangarajan, Rahul Sengupta, Hoda ShajariFDOTIn this project, we investigate the use of Machine Learning(especially Reinforcement Learning) to the problem of optimizing traffic flow in dense urban grids with signaling mechanisms. We use microscopic traffic simulators(such as SUMO, VISSIM etc.) and recorded field data(Loop detector data, vehicle probe data etc.) to build realistic models of typical peak hour traffic scenarios in hypothetical and real-world grids.
Large-scale Traffic Corridor Identification using Big DataDr. Sanjay Ranka, Dr. Anand Rangarajan, Rahul Sengupta, Vineeth KamisettyFDOTIn this project, we investigate and deploy algorithms to detect recurrent traffic flows in urban traffic grids based on large-scale pre-recoded historical traffic data. We warehouse and preprocess large datasets and then use spatiotemporal clustering techniques on them to detect underlying corridors of traffic flows.

More projects can be found on the TRID database at https://trid.trb.org/

Faculty

Lily Elefteriadou, Ph.D.

Professor Civil and Coastal Engineering
elefter@ce.ufl.edu

Sanjay Ranka, Ph.D.

Professor, Fellow IEEE, Fellow AAS Computer & Information Science & Engineering ranka@cise.ufl.edu

Siva Srinivasan, Ph.D.

Associate Professor Civil & Coastal Engineering
siva@ce.ufl.edu