01590114

Component

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. The authors 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 estimating 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. The authors illustrate that this framework catches in an efficient way the behavioral heterogeneity of travelers. Furthermore, the authors show that the proposed framework is adequately adapted to build large scale micro-simulation scenarios of transportation and urban systems.

This paper was sponsored by TRB committee ADB40 Standing Committee on Transportation Demand Forecasting.

01584066

16-0171

English

20p

2016

Transportation Research Board 95th Annual Meeting

Digital/other

Figures; References; Tables

Activity choices; Demographics; Forecasting; Markov chains; Microsimulation; Monte Carlo method; Travel behavior; Travel demand; Travel surveys

Belgian Household Daily Travel Survey

Planning and Forecasting; Transportation (General); I72: Traffic and Transport Planning

Transportation Research Board Annual Meeting 2016 Paper #16-0171

TRIS, TRB, ATRI

Jan 12 2016 4:19PM