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In this talk I will discuss my work on self-driving vehicles, with an emphasis on accounting for interactions with external counterparts at both the vehicle- and system-levels. Specifically, I will first discuss a decision-making framework that enables a self-driving vehicle to proactively interact with humans to infer their intents, and to use such information for safe and efficient driving. I will then turn the discussion to the operational and economic aspects of autonomous mobility-on-demand (AMoD) systems, with an emphasis on the interaction between AMoD and the electric power network.
Dr. Marco Pavone is an Assistant Professor of Aeronautics and Astronautics at Stanford University, where he is the Director of the Autonomous Systems Laboratory and Co-Director of the Center for Automotive Research at Stanford. Before joining Stanford, he was a Research Technologist within the Robotics Section at the NASA Jet Propulsion Laboratory. He received a Ph.D. degree in Aeronautics and Astronautics from the Massachusetts Institute of Technology in 2010. His main research interests are in the development of methodologies for the analysis, design, and control of autonomous systems, with an emphasis on self-driving vehicles, autonomous aerospace vehicles, and future mobility systems. He is a recipient of a Presidential Early Career Award for Scientists and Engineers, an ONR YIP Award, an NSF CAREER Award, a NASA Early Career Faculty Award, a Hellman Faculty Scholar Award, and was named NASA NIAC Fellow in 2011. His work has been recognized with best paper nominations or awards at the Field and Service Robotics Conference, at the Robotics: Science and Systems Conference, and at NASA symposia.
