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SUMMARY:Route Choice in an Uncertain Environment: Algorithms and Behaviora
 l Studies
DTSTART:20140528T110000
DTEND:20140528T120000
DTSTAMP:20260407T002717Z
UID:6d6ca4703b8568aa85cc63811500cf19058167244e91bc315aa66ce4
CATEGORIES:Conferences - Seminars
DESCRIPTION:Prof. Song Gao\nTransportation systems are inherently uncertai
 n 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 mitigate the adverse effect of u
 ncertainty. Both algorithmic and behavioral studies of adaptive routing ar
 e presented. A series of optimal adaptive routing problems are investigate
 d\, where time-dependent travel times are modeled as correlated random var
 iables and various assumptions on the real-time information accessibility 
 are made. Behavioral studies of adaptive route choice in both one-shot and
  day-to-day learning contexts based on stated preferences data show that t
 ravelers can plan ahead for traffic information not yet available. Two mod
 eling paradigms for route choice under unreliable travel times\, utility m
 aximization 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 utility maximization approach. Th
 e ongoing work of developing a history-dependent route choice learning mod
 el for realistic networks is also discussed.
LOCATION:GC B3 424 http://plan.epfl.ch/?lang=fr&room=gc+b3+424
STATUS:CONFIRMED
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