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SUMMARY:Route Choice in an Uncertain Environment: Algorithms and Behaviora
 l Studies
DTSTART:20140528T110000
DTEND:20140528T120000
DTSTAMP:20260916T043719Z
UID:ee255f0c8083763eae17c95f3a9bd03c908392a3bb81f87fcc6afc60
CATEGORIES:Conferences - Seminars
DESCRIPTION:Prof. Song Gao\nUniversity of Massachusetts Amherst\nSong Gao 
 is an associate professor of Civil and Environmental Engineering at the Un
 iversity of Massachusetts Amherst. Dr. Gao's research focuses on optimizat
 ion in stochastic networks\, econometric and psychological models of trave
 l behavior\, equilibrium analysis of stochastic networks with traveler inf
 ormation\, with applications in intelligent transportation systems (ITS)\,
  transportation planning under both normal and emergency conditions\, and 
 sustainable transportation systems. Prior to joining the faculty of the Un
 iversity of Massachusetts Amherst in 2007\, Dr. Gao worked as a transporta
 tion engineer at Caliper Corporation\, Newton\, MA for three years\, and d
 eveloped advanced traffic assignment modules for TransCAD\, a GIS-based tr
 ansportation planning software and provided consultancy to transportation 
 demand forecasting projects of state\, regional and local planning agencie
 s. She has published in scientific journals such as Transportation Researc
 h Parts A\, B\, and C\, IEEE Transactions on ITS and Transportation Resear
 ch Record. Dr. Gao has obtained over $1M in external research funds as the
  principle investigator (PI)\, and over $1.8M as a co-PI from federal and 
 state governments\, regional consortia\, planning agencies\, and private f
 oundations. Dr. Gao was a member of the winning team of the 2010 MacArthur
  Digital Media and Learning Competition. She received an honorable mention
  (second place) in the INFORMS (Institute for Operations Research and Mana
 gement Science) Transportation Science and Logistics Dissertation Prize Co
 mpetition in 2005. Dr. Gao is a member of the Transportation Research Boar
 d (TRB) Committees on Travel Behavior and Values (ADB10) and Transportatio
 n Network Modeling (ADB30)\, and Chair of the TRB Route Choice and Spatio-
 Temporal Behavior Subcommittee (ADB10(2)\, ADB30(3)). She is on the editor
 ial board of the Journal of Intelligent Transportation Systems. Dr. Gao re
 ceived her Ph.D. and M.S. in Transportation from Massachusetts Institute o
 f Technology in 2005 and 2002 respectively. She received her B.S. in Civil
  Engineering from Tsinghua University of China in 1999.\nTransportation sy
 stems are inherently uncertain due to disruptions such as bad weather and 
 incident\, and the randomness of traveler' choices. Real-time information 
 allows travelers to adapt to actual traffic conditions and potentially mit
 igate the adverse effect of uncertainty. Both algorithmic and behavioral s
 tudies of adaptive routing are presented. A series of optimal adaptive rou
 ting problems are investigated\, where time-dependent travel times are mod
 eled as correlated random variables and various assumptions on the real-ti
 me information accessibility are made. Behavioral studies of adaptive rout
 e choice in both one-shot and day-to-day learning contexts based on stated
  preferences data show that travelers can plan ahead for traffic informati
 on not yet available. Two modeling paradigms for route choice under unreli
 able travel times\, utility maximization based on the prospect theory and 
 non-compensatory heuristic\, are compared. The non-compensatory heuristic 
 is found to be potentially a suitable alternative to the conventional util
 ity maximization approach. The ongoing work of developing a history-depend
 ent route choice learning model for realistic networks is also discussed.
LOCATION:GC B3 424 http://plan.epfl.ch/?zoom=21&recenter_y=5864230.47309&r
 ecenter_x=730971.02821&layerNodes=fonds\,batiments\,labels\,information\,p
 arkings_publics\,arrets_metro\,transports_publics&floor=3&q=gc_b3%20424
STATUS:CONFIRMED
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