Researchers from the University of Florida, led by Sanjay Ranka, have developed a new tool aimed at improving traffic management in urban areas. The team, which includes Rahul Sengupta, Nooshin Yousefzadeh, Manav Sanghvi, Yash Ranjan, Anand Rangarajan, Yashaswi Karnati, Jeremy Dilmore, Tushar Patel, and Ryan Casburn, has created an open-source framework called BigSUMO to help transportation agencies and city planners analyze large volumes of traffic data and optimize traffic performance.
The BigSUMO framework is designed to ingest high-resolution data from loop detectors and signal states, as well as sparse probe trajectory data. It performs descriptive analytics to understand traffic patterns and detect potential interruptions. The framework then uses the SUMO microsimulator for prescriptive analytics, testing hundreds of what-if scenarios to optimize traffic performance. The modular design of BigSUMO allows for the integration of different algorithms for data processing and outlier detection, making it a versatile tool for traffic management.
One of the key advantages of BigSUMO is its scalability and cost-effectiveness. Built using open-source software and libraries, the framework is easy to deploy and can handle large volumes of traffic data efficiently. This makes it a valuable aid in developing smart city mobility solutions, particularly in urban areas where traffic congestion is a major challenge.
The research was published in the Proceedings of the ACM on Measurement and Analysis of Computing Systems, a peer-reviewed journal that focuses on the design, implementation, and evaluation of computing systems. While the research is primarily focused on traffic management, the framework’s ability to analyze large volumes of data and optimize performance could have potential applications in the energy sector, particularly in smart grid management and demand response programs. By analyzing energy consumption patterns and testing different scenarios, energy providers could optimize energy distribution and reduce waste, ultimately leading to more efficient and sustainable energy systems.
In summary, BigSUMO is a promising tool for traffic management that could also have potential applications in the energy sector. Its open-source nature, scalability, and cost-effectiveness make it a valuable aid in developing smart city solutions and optimizing energy systems.
This article is based on research available at arXiv.