The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Prototype Model of Household Activity-Travel Scheduling
Abstract
The Toronto Area Scheduling Model for Household Agents (TASHA), a new prototype activity scheduling microsimulation model, generates activity schedules and travel patterns for a 24-h typical weekday for all persons in a household. The prototype model is based solely on conventional trip diary data and therefore is applicable in many urban areas where activity data may not be available. The model makes use of the concept of the project, a "container" of activities with a common goal, to organize activity episodes into the schedules of persons in a household. A heuristic, or rule-based, method is used to organize activities into projects and then to form schedules for interacting household members. The TASHA model is considered to be a successful first attempt to operationalize a generalized conceptual model of household decision making, with reasonable correspondence between model and observed trip rates and chain characteristics.
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Cites
ALBATROSS : a learning based transportation oriented simulation system
Arentze, T., & Timmermans, H. J. P. (2000) · Cited by 391
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Research works printed but not linked: 6
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- Miller E. J., 2002, Presented at International Colloquium on the Behavioural Foundations of Integrated Land-Use and Transportation Models: Assumptions and New Conceptual Frameworks
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- EberhardL. K. A 24-Hour Household-Level Activity Based Travel Demand Model for the GTA. M.S. thesis. University of Toronto, 2002.
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Cited by
When Transport Geography Meets Social Psychology: Toward a Conceptual Model of Travel Behaviour
Van Acker, V., Van Wee, B., & Witlox, F. (2010) · Transport Reviews · doi:10.1080/01441640902943453 · Cited by 434
Activity-based models of travel demand: promises, progress and prospects
Rasouli, S., & Timmermans, H. (2014) · International Journal of Urban Sciences · doi:10.1080/12265934.2013.835118 · Cited by 321
Auld, J., Hope, M., Ley, H., Sokolov, V., Xu, B., & Zhang, K. (2016) · Transportation Research Part C: Emerging Technologies · doi:10.1016/j.trc.2015.07.017 · Cited by 281
Generating complete all-day activity plans with genetic algorithms
Charypar, D., & Nagel, K. (2005) · Transportation · doi:10.1007/s11116-004-8287-y · Cited by 273
Collecting Social Network Data to Study Social Activity-Travel Behavior: An Egocentric Approach
Carrasco, J. A., Hogan, B., Wellman, B., & Miller, E. J. (2008) · Environment and Planning B: Planning and Design · doi:10.1068/b3317t · Cited by 260
Self-citation
Metadata
- Authors
- Miller, E. J., & Roorda, M. J.
- Venue
- Transportation Research Record: Journal of the Transportation Research Board
- Publisher
- SAGE Publications
- Published
- 2003-01
- Volume
- 1831
- Issue
- 1
- Pages
- 114-121
- ISSN
- 0361-1981 (ISSN-L)
- 2169-4052
- OpenAlex
- W2113687967
- Cited by
- 381
- References
- 4
- FWCI
- 38.11
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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