000135711 001__ 135711
000135711 005__ 20190316234530.0
000135711 0247_ $$2doi$$a10.5075/epfl-thesis-4417
000135711 02470 $$2urn$$aurn:nbn:ch:bel-epfl-thesis4417-8
000135711 02471 $$2nebis$$a5778329
000135711 037__ $$aTHESIS
000135711 041__ $$aeng
000135711 088__ $$a4417
000135711 245__ $$aDynamic urban origin-destination matrix estimation methodology
000135711 269__ $$a2009
000135711 260__ $$aLausanne$$bEPFL$$c2009
000135711 300__ $$a192
000135711 336__ $$aTheses
000135711 520__ $$aThe aim of this thesis is to develop a new methodology to determine dynamic Origin-Destination (OD) matrices for urban networks characterized by a high number of traffic hubs, complex route choice possibilities and a high level of traffic controls. By reviewing existing methods, from static to dynamic OD matrix evaluation, deficiencies in the approaches are identified: mainly, the level of detail of the traffic assignment for complex urban networks and the lack in dynamic approaches. The proposed methodology is comprised of a heuristic bi-level approach. Assignment of the initial demand is performed by mesoscopic simulation based on the Dynamic User Equilibrium to model detailed dynamic traffic patterns without numerous calibration parameters. OD flow adjustment is executed by an efficient least square solution which takes into account dynamic aspects of the flow propagation and traffic counts. For this task, a LSQR algorithm has been selected for its capacities to deal with a large matrix and its ability to constrain outputs. Parallel comparison with the most common approach for OD estimation (sequential static approach) has shown: first, the ability of the method to generate OD flows close to the actual demand, compared to the common practice; second, the utilization of the obtained demand by a dynamic traffic model has established its aptitude to reproduce realistic assignment patterns. Finally, applicability and example of utilization of the proposed method has been presented by solving realistic problems using the simulation software AIMSUN in which the proposed methodology is implemented as a plug-in. This research has shown the importance of input data for the OD estimation process and mainly the detection layout configuration used for traffic count data. Sensitivity analysis has shown that a small number of detectors is usually sufficient for efficient OD estimation in short computation time, if the traffic detectors intercept the most critical flows.
000135711 6531_ $$atraffic simulation
000135711 6531_ $$atraffic demand
000135711 6531_ $$aOrigin-Destination matrices estimation
000135711 6531_ $$adynamic traffic assignment
000135711 6531_ $$aurban network
000135711 6531_ $$aITS
000135711 6531_ $$asimulation de trafic
000135711 6531_ $$ademande de trafic
000135711 6531_ $$aestimation de matrices origine-destination
000135711 6531_ $$aassignation dynamique du trafic
000135711 6531_ $$aréseaux urbains
000135711 6531_ $$atélématique
000135711 700__ $$aBert, Emmanuel
000135711 720_2 $$0241970$$aDumont, André-Gilles$$edir.$$g105012
000135711 720_2 $$aChung, Edward$$edir.
000135711 8564_ $$s5028234$$uhttps://infoscience.epfl.ch/record/135711/files/EPFL_TH4417.pdf$$yTexte intégral / Full text$$zTexte intégral / Full text
000135711 909C0 $$0252146$$pLAVOC$$xU10259
000135711 909CO $$ooai:infoscience.tind.io:135711$$pthesis-bn2018$$pDOI$$pENAC$$pthesis$$qDOI2$$qGLOBAL_SET
000135711 918__ $$aENAC$$cICARE$$dEDEN
000135711 919__ $$aLAVOC
000135711 920__ $$b2009
000135711 970__ $$a4417/THESES
000135711 973__ $$aEPFL$$sPUBLISHED
000135711 980__ $$aTHESIS