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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/18899

Title: Investigating the Minimum Size of Study Area for an Activity-Based Travel Demand Forecasting Model
Authors: BAO, Qiong
SHEN, Yongjun
CREEMERS, Lieve
KOCHAN, Bruno
BELLEMANS, Tom
JANSSENS, Davy
WETS, Geert
Issue Date: 2015
Publisher: HINDAWI PUBLISHING CORPORATION
Citation: MATHEMATICAL PROBLEMS IN ENGINEERING, 2015, (ART N° 162632)
Abstract: Nowadays, considerable attention has been paid to the activity-based approach for transportation planning and forecasting by both researchers and practitioners. However, one of the practical limitations of applying most of the currently available activity-based models is their computation time, especially when large amount of population and detailed geographical unit level are taken into account. In this research, we investigated the possibility of restraining the size of the study area in order to reduce the computation time when applying an activity-based model, as it is often the case that only a small territory rather than the whole region is the focus of a specific study. By introducing an accuracy level of the model, we proposed in this research an iteration approach to determine the minimum size of the study area required for a target territory. In the application, we investigated the required minimum size of the study area surrounding each of the 327 municipalities in Flanders, Belgium, with regard to two different transport modes, that is, car as driver and public transport. Afterwards, a validation analysis and a case study were conducted. All the experiments were carried out by using the FEATHERS, an activity-based microsimulation modeling framework currently implemented for the Flanders region of Belgium.
Notes: [Bao, Qiong; Shen, Yongjun; Creemers, Lieve; Kochan, Bruno; Bellemans, Tom; Janssens, Davy; Wets, Geert] Hasselt Univ, Transportat Res Inst IMOB, B-3590 Diepenbeek, Belgium.
URI: http://hdl.handle.net/1942/18899
DOI: 10.1155/2015/162632
ISI #: 000353797600001
ISSN: 1024-123X
Category: A1
Type: Journal Contribution
Validation: ecoom, 2016
Appears in Collections: Research publications

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