Brought to you by the Artificial Intelligence in Transportation Committee of T&DI
Artificial Intelligence in Transportation Cyber-physical Systems
This event does not qualify for professional development hours or continuing education credits.
Transportation Cyber-Physical Systems (TCPS) promise seamless integration of sensing, computation, and communication into physical transportation infrastructure. Due to the underlying big data, computing efficiency, and environmental dynamics issues, TCPS pose unprecedented analytical challenges which may be overcome by Artificial Intelligence (AI). While AI has overcome many of the issues that similarly arise in modern life, such as which product to buy online or which movie to watch, the commonplace between AI and TCPS needs to be extensively explored. This technical session will discuss original AI algorithms and applications related to the operations of TCPS, with a focus on Connected and Autonomous Vehicles (CAVs).
This 90-minute virtual technical session includes a keynote presentation followed by three technical presentations followed by Q&A with attendee participation.
Dr. Chandra Bhat, from the University of Texas at Austin will kick off the event with a keynote address On the Symbiotic Convergence of AI-based Computational Data Science and Transportation Science.
Technical presentations
Dr. Xuegang (Jeff) Ban, the University of Washington Control of Low-level CAVs with Reinforcement Learning
Dr. Robert Patton, Oak Ridge National Laboratory, HPC-Enabled Artificial Intelligence for Autonomous Vehicle Perception.
Dr. Dan Work, Vanderbilt University, Traffic Flow Smoothing at Scale
AI-Enabled Next Generation Transportation Systems
Student Competition Deadline to Submit an Abstract is November 10th
As part of the AI-Enabled Next Generation Transportation Systems Virtual Event series, T&DIs Artificial Intelligence Committee is hosting a virtual student competition. The competition is designed to showcase graduate-undergraduate students' research in Transportation Engineering with the use of Artificial Intelligence or Machine Learning. Students will have the opportunity to engage with industry and academy professionals and share their research with them.
Click here to view rules and submit an abstract.
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