Project Summary (NSF Awards 1527097,1527287)
Many of today's vehicles are equipped with GPS, networking capabilities, computational resources, and a variety of environment and vehicle performance sensors. The combination of these technologies and the growing presence of such vehicles offer a powerful platform for large-scale road sensing applications to assist drivers in route planning and safe driving. This project proposes an integrated approach to overcoming algorithmic and systems barriers to the cost and scalability challenges of collaborative road sensing. The project conducts four main research tasks: (1) obtain correlated measurements of vehicle sensor readings and network connectivity, (2) reduce the cost of vehicle-to-cloud (V2C) communication through vehicle-to-vehicle (V2V) message delegation, (3) develop new communication-efficient algorithmic approaches for collaborative road sensing, (4) evaluate the communication and algorithmic solutions in an emulation framework that pulls together vehicle sensor data, measurements of cellular and V2V connectivity, and traffic flow data from a I-90/94 corridor information system. Results of this project will include reliable connected vehicle communication architecture for both urban and rural settings and theoretically sound decentralized algorithms for sensing and estimation that will be of interest to the broader distributed computing systems community.
- Compressed Sensing for Tactile Skins, B. Hollis, S. Patterson, and J. Trinkle, Proceedings of the International Conference on Robotics and Automation , 2016.
- Distributed Semi-Stochastic Optimization with Quantization Refinement, N. McGlohon and S. Patterson, Proceedings of the American Control Conference , 2016.
- Cost-Efficient Elastic Stream Processing Using Application-Agnostic Performance Prediction, S. Imai, S. Patterson, and C. Varela, Proceedings of the16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing: Doctoral Symposium , 2016.
- Elastic Virtual Machine Scheduling for Continuous Air Traffic Optimization, S. Imai, S. Patterson, and C. Varela, Proceedings of the16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, 2016.
- Driving Conditions According to Cars and the Cloud, Inside Rensselaer, Feb. 2016.