The University of Michigan

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Visible to the public Correct-by-Design Control Software Synthesis for Highly Dynamic Systems

Abstract:

This project addresses highly dynamic Cyber-Physical Systems (CPSs) understood as systems where a computing delay of a few milliseconds or an incorrectly computed response to a disturbance can lead to catastrophic consequences. Such is the case of advanced safety systems on passenger cars, unmanned air vehicles performing critical maneuvers such as landing, or disaster and rescue response bipedal robots rushing through the rubble to collect information or save human lives.

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Visible to the public CPS Synergy: Collaborative Research: Formal Design of Semi-autonomous Cyber Physical Transportation Systems

Abstract:

The goal of this project is to develop fundamental theory, computationally efficient algorithms, and real-world experiments for the analysis and design of safety-critical cyber-physical transportation systems with human operators. To this end, we propose a modeling, theoretical, and experimental collaborative effort combining human factors, control theory, and computer science. As crashes at traffic intersections account for about 40% of overall vehicle crashes, we will focus on intersection crashes in this project.

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Visible to the public Foundations Of Resilient CybEr-physical Systems (FORCES)

Abstract:

Cyber-Physical Systems (CPS) are being increasingly deployed in critical infrastructures such as electric-power, water, transportation, and other networks. These deployments are facilitating real-time monitoring and closed-loop control by exploiting the advances in wireless sensor-actuator networks, the internet of "everything," data-driven analytics, and machine-to-machine interfaces. CPS operations depend on the synergy of computational and physical components.

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Visible to the public Advances in Driving Research - Models, Data, and New Methods

Abstract:

The current project, collaboration between the MIT and the University of Michigan, concerns the development of complex models to describe driver decision making at intersections. MIT is focused on modeling and Michigan on data collection and method development. Two experiments have been conducted so far (24 subjects/experiment) using a NADS MiniSim driving simulator for which extensive programming was required. Subjects drove through 2 sets of 70 intersections following a lead vehicle (and being followed).