Dear colleagues,
Please mark your calendars for our next webinar:
Application of deep reinforcement learning for perimeter metering control in urban networks with MFDs
Speaker: Dr. Vikash Gayah, Associate Professor, Penn State University
Date & Time: Thursday, July 9th, 2:30 PM EST
Link: https://gatech.bluejeans.com/2831735251 NOTE: You don't need to install the bluejeans app, just click join with browser.
Abstract:
Various
perimeter control strategies have been proposed for urban traffic networks that
rely on the existence of well-defined relationships between network
productivity and accumulation, known more commonly as network Macroscopic
Fundamental Diagrams (MFD). Most existing perimeter control strategies require
accurate modeling of traffic dynamics with full knowledge of the network’s MFD.
However, such information is generally difficult to obtain and subject to
error. This talk describes recent efforts to alleviate this using deep
reinforcement learning for networks made up of two unique regions. The proposed
methods are completely model free in that they do not require knowledge of the
network’s MFD. The algorithm learns the consequences of different control
actions over time and uses this information to obtain optimal control policies
under different situations. Results from numerical experiments show that the
proposed method: (a) can stably learn perimeter control strategies under
various types of environment configurations; (b) can consistently outperform
the state-of-the-art, model predictive control (MPC); (c) demonstrates
sufficient transferability to a wide range of traffic conditions and dynamics
in the environment; and, (d) exhibits great potential for practical
implementation.
Short Bio:
Dr.
Vikash V. Gayah is an associate professor in the Department of Civil and
Environmental Engineering at The Pennsylvania State University (joined 2012).
He received his B.S. and M.S. degrees from the University of Central Florida
(2005 and 2006, respectively) and his Ph.D. degree from the University of
California, Berkeley (2012). Dr. Gayah currently serves as an editorial
advisory board member of Transportation Research Part C: Emerging
Technologies, an editorial board editor of Transportation Research
Part B: Methodological, an associate editor for the IEEE Intelligent
Transportation Systems Magazine (an international peer-reviewed journal), a
handling editor for the Transportation Research Record and is a member
of the Transportation Research Board’s Committee on Traffic Flow Theory and
Characteristics (AHB 45), where he serves as a paper review coordinator and the
committee research coordinator. He has been recognized with multiple awards for
his research and teaching activities, including the Dwight D. Eisenhower
Transportation Fellowship, Gordon F. Newell Award for Excellence in
Transportation Science, University of California Transportation Center Student
of the Year Award, New Faculty Award by the Council of University
Transportation Centers, the Cunard, Fred Burggraf and D. Grant Mickle
outstanding paper awards by the Transportation Research Board, Harry West
Teaching Award by the Department of Civil and Environmental Engineering at Penn
State, Outstanding Teaching Award by the Penn State Engineering Alumni Society,
and Faculty Early Career Development (CAREER) Award by the National Science
Foundation.