CPS: Medium: Autonomous Driving in Mixed-Traffic Urban Environments

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This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).The objective of this research is to scale up the capabilities of fully autonomous vehicles so that they are capable of operating in mixed-traffic urban environments. Such environments are realistic large-city driving situations involving many other vehicles, mostly human-driven. The approach is to integrate multidisciplinary advances in software, sensing and control, and modeling to address current weaknesses in autonomous vehicle design.With respect to intellectual merit, the research address significant improvements to current methods and tools to enable a number of formal methods to move from use in limited, controlled environments to use in more complex and realistic environments. The theory, tools, and design methods that are investigated have potential application for a broad class of cyber-physical systems consisting of mobile entities operating in a semi-structured environment.With respect to broader impacts, this research has the potential to lead to safer autonomous vehicles and to improve economic competitiveness, the nation's transportation infrastructure, and energy efficiency. The richness of the domain means that expected research contributions can apply not only to autonomous vehicles but, also, to a variety of related cyber-physical systems such as service robots in hospitals and rescue robots used after natural disasters. The experimental research laboratory for the project is used for undergraduate and graduate courses and supports new summer outreach projects for high-school students. Research outcomes are integrated with undergraduate and graduate courses on component-based software.