抖阴旅行射 Boulder part of $5.8M grant to improve cyber-physical transportation systems
Majid Zamani
Researchers at 抖阴旅行射 Boulder are part of a new $6 million grant from the National Science Foundation to help build the intelligent transportation systems of the future.
The five-year, multi-institutional project is led by the University of California Santa Cruz and focuses on improving cyber-physical systems and training the workforce needed to run them smoothly. Research at 抖阴旅行射 Boulder will be conducted by Assistant Professor Majid Zamani and his team from the Department of Computer Science.
Cyber-physical systems involve algorithms, networks and real-world physical components all working in union. Examples of such systems include self-driving cars and power grids, among many other applications in modern life.
Zamani鈥檚 project specifically aims to rethink the modeling, performance and design of a new generation of intelligent cyber-physical transportation systems 鈥 both in aviation and motor vehicles 鈥 so that their algorithms run efficiently and safely, while also reducing their carbon footprint.
Zamani said a key goal is codesigning the algorithms and hardware of these cyber-physical systems so that the physics, hardware and software are unified. By approaching the design holistically, researchers hope to create systems that are much more adaptive than the current state of the art. The new control algorithms will better adapt to the specification and the environment they are deployed on 鈥 learning and adjusting to key factors such as power consumption. The new hardware will also be tailored to provide feedback that can be used by the algorithms to improve performance and safety.
He said his team is specifically tasked with leading the research around the automated synthesis of embedded controllers.
鈥淲e are generating synthesis tools that not only scale, but also allow for models that include features of multiple layers of the design stack,鈥 he said. 鈥淭he proposed tools will provide formal certificates under finite numerical precision, varying sampling time, memory and communication constraints, and computation time in the control synthesis process.鈥
Researchers will also be collaborating with industry and academic partners to advance these systems both in research and education through strong training programs for high school and undergraduate students, with a particular focus on creating research opportunities for students from underrepresented backgrounds.