Visible to the public CPS: Medium: Autonomous Driving in Mixed-Traffic Urban Environments

Project Details
Lead PI:Umit Ozguner
Co-PI(s):Bruce Weide
Fusun Ozguner
Ashok Krishnamurthy
Paolo Sivilotti
Performance Period:09/01/09 - 08/31/13
Institution(s):The Ohio State University
Sponsor(s):National Science Foundation
Project URL:
Award Number:0931669
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Abstract: 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 (e.g., in a city such as Columbus or even New York or Istanbul). Such environments are realistic large-city driving situations involving many other vehicles, mostly human-driven. Moreover, such a car will be in a world where it interacts with other cars, humans, other external effects, and internal and external software modules. This is a prototypical CPS with which we have considerable experience over many years, including participation in the recent DARPA Urban Challenge. Even in the latter case, though, operation to date has been restricted to relatively “clean” environments (such as multi-lane highways and simpler intersections with a few other vehicles). The approach is to integrate multidisciplinary advances in software, sensing and control, and modeling to address current weaknesses in autonomous vehicle design for this complex mixed-traffic urban environment. All work will be done within a defined design-and-verification cycle. Theoretical advances and new models will be evaluated both by large-scale simulations, and by implementation on laboratory robots and road-worthy vehicles driven in real-world situations. 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. 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.