The goal of this project is to further the ability of cities and communities to deploy technology that saves lives through safer transportation systems. The approach is to create open source analytics solutions to enable novel transportation applications that utilize data from low-cost video sensors. Video data are processed using edge computing (inexpensive computing hardware that performs analysis without storing significant amounts of data) in order to reduce the amount of data stored. Social dimensions of the research project emerge from the deep research partnership between the City and the University, with the goal to provide replicable and near-term social impacts. The project aligns with the Vision Zero concept to reduce traffic fatalities, with programs that are based on education, enforcement and design. By understanding the risk profile of an intersection through automated detection of near miss events, communities will be able to proactively design and alter streets and intersections to be safer.
The goal of designing a smart city, when addressing the technical challenges at the intersection, street and system levels, has several research components. (i) Development of new algorithms for multi-target tracking: The problems of occlusion, temporal assignment of features to objects and target motion will be jointly formulated. (ii) Integrated optimization and simulation for signal control: We formulate the problem of estimating signal control parameters (offsets, phasing etc.) in a network as one of global optimization. (iii) Real-time reinforcement learning is a natural choice when online machine learning meets real world feedback from the City. Our ability to obtain and analyze continuous-time data at the network level will provide insights on how conflict points and patterns can change through the network. This is expected to impact decisions in traffic management, smart city planning and safety.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Abstract
Sanjay Ranka
Sanjay Ranka is a Distinguished Professor in the Department of Computer & Information Science & Engineering at the University of Florida. From 1999-2002, as the Chief Technology Officer at Paramark (Sunnyvale, CA), he developed a real-time optimization service called PILOT for marketing campaigns. PILOT served more than 10 million optimized decisions a day in 2002 with a 99.99% uptime. Paramark was recognized by VentureWire/Technologic Partners as a Top 100 Internet technology company in 2001 and 2002 and was acquired in 2002. Sanjay has also held positions as a tenured faculty member at Syracuse University, academic visitor at IBM and summer researcher at Hitachi America Limited.
Research in high-performance computing and big data science is an important avenue for novel discoveries in large-scale applications. The focus of his current research is the development of efficient computational methods and data analysis techniques to model scientific phenomenon, and practical applications of focus are improvements to the quality of healthcare and the reduction of traffic accidents. A core aspiration of his research is to develop novel algorithms and software that make an impact on the application domain, exploiting the interdependence between theory and practice of computer science
He has co-authored one book, four monographs, 300+ journals and refereed conference articles. His recent co-authored work has received a best student paper runner-up award at IGARSS 2015, best paper award at BICOB 2014, best student paper award at ACM-BCB 2010, best paper runner-up award at KDD-2009, a nomination for the Robbins Prize for the best paper in the Journal of Physics in Medicine and Biology in 2008, and a best paper award at ICN 2007.
He is a fellow of the IEEE and AAAS and a past member of IFIP Committee on System Modeling and Optimization. He won the 2020 Research Impact Award from IEEE Technical Committee on Cloud Computing. He is an associate editor-in-chief of the Journal of Parallel and Distributed Computing and an associate editor for ACM Computing Surveys, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Sustainable Computing: Systems and Informatics, Knowledge and Information Systems, and International Journal of Computing. Additionally, he is a book series editor for CRC Press for Bigdata. In the past, he has been an associate editor for IEEE Transactions on Parallel and Distributed Systems and IEEE Transactions on Computers.
He was a general co-chair for ICDM in 2009, International Green Computing Conference in 2010 and International Green Computing Conference in 2011, a general chair for ACM Conference on Bioinformatics and Computational Biology in 2012, and a program chair for the 2013 International Parallel and Distributed Processing Symposium and 2015 High-Performance Computing Conference. He was a co-general chair for DataCom 2017 and co-program chair for ICMLDS 2017 and 2018.
His work has received 12,800+ citations with an h-index of 55 (based on Google Scholar). He has consulted for several startups and Fortune 500 companies.
Performance Period: 05/01/2019 - 04/30/2023
Institution: University of Florida
Sponsor: National Science Foundation
Award Number: 1922782
Core Areas:
Transportation and Personal Mobility