Synergy: Collaborative Research: Collaborative Vehicular Systems
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As self-driving cars are being introduced into road networks, the overall safety and efficiency of the resulting traffic system must be established and it must be guaranteed. This project develops methods to analyze and coordinate networks of fully and partially self-driving vehicles that interact with conventional human-driven vehicles on road grids. The outcomes of the research add to the understanding of more general systems with reconfigurable hierarchical structures and they help create designs with minimal computation and communication delay. Furthermore, the research develops a mathematical framework and corresponding software tools that analyze the safety and reliability of a class of systems that combine physical, mechanical and biological components with purely computational ones.
Numerous critical software related recalls in modern automotive systems indicate that the current design practices are not sufficient for the development of dependable intelligent transportation systems. This research sets the foundations for principled engineering of collaborative vehicular systems. The research team has strong ties to the automotive industry and regularly disseminates research outcomes to collaborators there.
The research efforts in this project span four technical areas: autonomous and human-controlled collaborative driving; scheduling over heterogeneous distributed computing systems; security and trust in V2X (Vehicle-to-Vehicle and Vehicle-to-Infrastructure) networks; and Verification & Validation of V2X systems through semi-virtual environments and scenarios. The integrating aspect of this research is the development of a distributed system calculus for Cyber-Physical Systems (CPS) that enables modeling, simulation and analysis of collaborative vehicular systems. The development of a comprehensive framework to model, analyze and test reconfiguration, hierarchical control, security and trust differentiates this research from previous attempts to address the same problem.
Submitted by Umit Ozguner
on
As self-driving cars are being introduced into road networks, the overall safety and efficiency of the resulting traffic system must be established and it must be guaranteed. This project develops methods to analyze and coordinate networks of fully and partially self-driving vehicles that interact with conventional human-driven vehicles on road grids. The outcomes of the research add to the understanding of more general systems with reconfigurable hierarchical structures and they help create designs with minimal computation and communication delay. Furthermore, the research develops a mathematical framework and corresponding software tools that analyze the safety and reliability of a class of systems that combine physical, mechanical and biological components with purely computational ones.
Numerous critical software related recalls in modern automotive systems indicate that the current design practices are not sufficient for the development of dependable intelligent transportation systems. This research sets the foundations for principled engineering of collaborative vehicular systems. The research team has strong ties to the automotive industry and regularly disseminates research outcomes to collaborators there.
The research efforts in this project span four technical areas: autonomous and human-controlled collaborative driving; scheduling over heterogeneous distributed computing systems; security and trust in V2X (Vehicle-to-Vehicle and Vehicle-to-Infrastructure) networks; and Verification & Validation of V2X systems through semi-virtual environments and scenarios. The integrating aspect of this research is the development of a distributed system calculus for Cyber-Physical Systems (CPS) that enables modeling, simulation and analysis of collaborative vehicular systems. The development of a comprehensive framework to model, analyze and test reconfiguration, hierarchical control, security and trust differentiates this research from previous attempts to address the same problem.