Reference : An integrated framework for forecasting travel behavior using Markov Chain Monte-Carl...
Scientific congresses and symposiums : Paper published in a book
Business & economic sciences : Special economic topics (health, labor, transportation…)
Engineering, computing & technology : Civil engineering
http://hdl.handle.net/2268/191453
An integrated framework for forecasting travel behavior using Markov Chain Monte-Carlo simulation and profile Hidden Markov Models
English
Saadi, Ismaïl mailto [Université de Liège > Département ArGEnCo > Transports et mobilité >]
El Saeid Mustafa, Ahmed Mohamed mailto [Université de Liège > Département ArGEnCo > LEMA (Local environment management and analysis) >]
Teller, Jacques mailto [Université de Liège > Département ArGEnCo > Urbanisme et aménagement du territoire >]
Cools, Mario mailto [Université de Liège > Département ArGEnCo > Transports et mobilité >]
2016
Proceedings of the 95th Annual Meeting of the Transportation Research Board
Transportation Research Board of the National Academies
Yes
No
International
Washington
DC
95th Annual Meeting of the Transportation Research Board
January 10–14, 2016
Transportation Research Board of the National Academies
Washington
DC
[en] Recent advances in agent-based micro-simulation modelling have further underlined the importance of a thorough full synthetic population procedure to guarantee a correct characterization of the true population. We propose an integrated approach including Markov Chain Monte Carlo (MCMC) simulation and profiling based methods to catch the complexity and the diversity of agents of the true population through representative micro samples. The population synthesis method is capable of building the joint distribution of a given population with its corresponding marginal distributions (e.g. age, gender, socio-professional status etc.) using complete, partial conditional probabilities or both of them at the same time. Particularly, the estimation of socio-demographic variables and characterization of daily activity-travel patterns are included within the framework. Data stemming from the 2010 Belgian Household Daily Travel Survey (BELDAM) are used to calibrate the modelling framework. We illustrate that this framework catches in an efficient way the behavioral heterogeneity of travelers. Furthermore, we show that the proposed framework is adequately adapted to build large scale micro-simulation scenarios of transportation and urban systems.
Lepur : Centre de Recherche sur la Ville, le Territoire et le Milieu rural ; LEMA : Local Environment Management & Analysis
ARC - Floodland
Researchers ; Professionals ; Students ; General public
http://hdl.handle.net/2268/191453

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