•   When: Monday, April 02, 2018 from 10:00 AM to 11:00 AM
•   Speakers: Guni Sharon, Postdoctoral Researcher in the CS department at the University of Texas at Austin
•   Location: Research Hall 163
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ABSTRACT:
Autonomous driving and communication capabilities are becoming increasingly common on board vehicles. Such capabilities present opportunities for developing safer, cleaner,  and more efficient road networks. Developing relevant  techniques is an important challenge and opportunity for the AI community as it requires synergy between experts in game theory, multiagent systems, behavioral science, mechanism design, and flow optimization. My talk will touch on each of these topics in the context of traffic flow optimization. I will address questions such as: how are traffic networks commonly modeled,  what manipulations can cause self interested drivers to act in an altruistic way, and what performance bounds can be given for applying such manipulations. Finally, I will present my view of the most important computational challenges that need to be overcome when seeking to achieve a sustainable traffic network.

BIO: 

Dr. Guni Sharon is a postdoctoral researcher in the CS department at the University of Texas at Austin. He leads an interdisciplinary group of researchers (including Professors, post-docs, and students) focusing on AI applications for traffic flow optimization. Dr. Sharon has completed his PhD in 2015 at Ben-Gurion University. He won the best paper award at SOCS-12 and AAAI-16 for groundbreaking research in the fields of multiagent path-finding and combinatorial search. He is also well known for his contributions in the fields of real-time search and traffic flow optimization.