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SUMMARY:Efficient algorithms for DNL and DTA as lower level component in b
 i-level optimization
DTSTART:20140321T121500
DTEND:20140321T131500
DTSTAMP:20260407T113520Z
UID:9d364d0e0a98323339984cde3ed1048f9547a104ce53cc7326ffa702
CATEGORIES:Conferences - Seminars
DESCRIPTION:Prof. Chris M.J. Tampère (KU Leuven\, Belgium)\nMany analyses
  require a large number of DNL/DTA runs as the lower level in a bi-level o
 ptimization: e.g. optimizing network-wide traffic control\, dynamic tollin
 g\, network design and dynamic origin-destination (OD) estimation.\nRepeat
 ed lower level calculations get substantially more efficient by exploiting
  the considerable overlap between successive iterations\, which usually di
 ffer only marginally from a base scenario (e.g. gradient approximation) or
  move progressively (with relatively small steps) in some large solution s
 pace. This is exploited in Marginal Computation (MaC) algorithms for the L
 ink Transmission Model\, a first order macroscopic network simulation mode
 l. It starts from a known DNL/DTA solution\, and changes marginally those 
 state variables that differ between the previous iterate and the current.\
 nThe seminar presents LTM and two MaC versions of it. One uses a tradition
 al\, CFL-consistent calculation scheme. It progresses forward in time\, gu
 aranteeing consistency of traffic propagation immediately at each new time
  step. It is about 40 times faster on mid-sized networks than a full LTM r
 un. But it is quite complex and approximation errors increase as one moves
  further from the base scenario. i-LTM was re-engineered to account from s
 cratch for marginal computation. It iterates to a fixed-point between a fo
 rward propagation stage and a backward stage imposing propagation constrai
 nts. They flag to each other which variables have changed compared to a pr
 evious iteration\, herewith limiting recomputation parsimoniously to only 
 those space-time grid points. Not only does this procedure by-pass CFL req
 uirement on the time step size\, it elegantly computes variations to a pre
 vious DNL/DTA as flagged changes that are iterated parsimoniously to a new
  fixed-point.\nThe seminar presents an application of dynamic OD calibrati
 on\, where MaC allows for numerical jacobian approximation of DNL/DTA in r
 easonable time. Exploiting this sensitivity information increases substant
 ially the quality of the optimization on the upper level.\nBio : Chris M. 
 J. Tampère (°1973\, Antwerp\, Belgium) holds a Masters’ degree in Civi
 l Engineering (1997\, KU Leuven\, Belgium) and a PhD from Delft University
  of Technology (2004\, The Netherlands).\nAt TNO Inro\, Delft (1997-2003) 
 he developed the MIXIC microsimulator for traffic flows with a variety of 
 Advanced Driver Assistance systems and several travel time estimation and 
 prediction algorithms for freeway and urban networks. His PhD research wit
 h TU Delft and TRAIL was on traffic flow theory for ADA systems in congest
 ed flows (2004). As a Postdoc Researcher at KU Leuven\, he developed realt
 ime models for estimation and prediction of urban traffic conditions (IWT 
 postdoc grant)\, and did research on network structures\, travel time reli
 ability\, network traffic management\, Dynamic Network Loading (DNL) and D
 ynamic Traffic Assignment (DTA) models.\nSince 2010\, he is a Tenure Track
  Professor at the CIB – Traffic & Infrastructure unit at KU Leuven. He w
 as co-founder of the master in engineering on traffic\, logistics and ITS 
 (VLITS)\, in which he teaches courses on Transportation Engineering\, Tran
 sport Modeling\, Intelligent Transportation Systems\, and Dynamic Traffic 
 Management. His current research continues with DNL/DTA modeling and calib
 ration\, integrated infrastructure\, demand and traffic management in regi
 onal transportation networks (KUL research fund)\, and network design prob
 lems with multiple transportation service suppliers.
LOCATION:GC B330 http://plan.epfl.ch/?room=GC%20B3%2030
STATUS:CONFIRMED
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