Simulation of Daily Activity Patterns Incorporating Interactions within Households: Algorithm Overview and Performance. Přibyl, O. & Goulias, K. G. Transportation Research Record, 1926(1):135–141, January, 2005.
Simulation of Daily Activity Patterns Incorporating Interactions within Households: Algorithm Overview and Performance [link]Paper  doi  abstract   bibtex   
Activity-based approaches to travel demand analysis have gained attention in the past few years and rapidly created the need to develop alternative microsimulation models for comparisons. In this paper, one such example simulates an individual's daily activity–travel patterns and incorporates the interactions among members of households. This model uses several tools to simulate the activity patterns, including a new method to extract activity patterns from data and decision trees to take into account personal and household characteristics. The model outputs are the individuals’ daily activity patterns on a detailed temporal scale. These patterns respect individuals’ constraints, which are implicitly embedded in the simulated activity and travel schedules via the intrahousehold interactions. This model was evaluated with data from 1,500 persons in Centre County, Pennsylvania, collected during fall 2002 and spring 2003.
@article{pribyl_simulation_2005,
	title = {Simulation of {Daily} {Activity} {Patterns} {Incorporating} {Interactions} within {Households}: {Algorithm} {Overview} and {Performance}},
	volume = {1926},
	issn = {0361-1981},
	shorttitle = {Simulation of {Daily} {Activity} {Patterns} {Incorporating} {Interactions} within {Households}},
	url = {https://doi.org/10.1177/0361198105192600116},
	doi = {10.1177/0361198105192600116},
	abstract = {Activity-based approaches to travel demand analysis have gained attention in the past few years and rapidly created the need to develop alternative microsimulation models for comparisons. In this paper, one such example simulates an individual's daily activity–travel patterns and incorporates the interactions among members of households. This model uses several tools to simulate the activity patterns, including a new method to extract activity patterns from data and decision trees to take into account personal and household characteristics. The model outputs are the individuals’ daily activity patterns on a detailed temporal scale. These patterns respect individuals’ constraints, which are implicitly embedded in the simulated activity and travel schedules via the intrahousehold interactions. This model was evaluated with data from 1,500 persons in Centre County, Pennsylvania, collected during fall 2002 and spring 2003.},
	language = {en},
	number = {1},
	urldate = {2019-05-24},
	journal = {Transportation Research Record},
	author = {Přibyl, Ondřej and Goulias, Konstadinos G.},
	month = jan,
	year = {2005},
	pages = {135--141}
}

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