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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/25673

Title: Applying FEATHERS for travel demand analysis: Model considerations
Authors: Bao, Qiong
Kochan, Bruno
Shen, Yongjun
Creemers, Lieve
Bellemans, Tom
Janssens, Davy
Wets, Geert
Issue Date: 2018
Citation: Applied Sciences, 8(2), p. 1-12
Abstract: Activity-based models of travel demand have received considerable attention in transportation planning and forecasting over the last few decades. FEATHERS (The Forecasting Evolutionary Activity-Travel of Households and their Environmental Repercussions), developed by the Transportation Research Institute of Hasselt University, Belgium, is a micro-simulation framework developed to facilitate the implementation of activity-based models for transport demand forecasting. In this paper, we focus on several model considerations when applying this framework. First, the way to apply FEATHERS on a more disaggregated geographical level is investigated, with the purpose of obtaining more detailed travel demand information. Next, to reduce the computation time when applying FEATHERS on a more detailed geographical level, an iteration approach is proposed to identify the minimum size of the study area needed. In addition, the effect of stochastic errors inherently included in the FEATHERS framework is investigated, and the concept of confidence intervals is applied to determine the minimum number of model runs needed to minimize this effect. In the application, the FEATHERS framework is used to investigate the potential impact of light rail initiatives on travel demand at a local network in Flanders, Belgium. In doing so, all the aforementioned model considerations are taken into account. The results indicate that by integrating a light rail network into the current public transport network, there would be a relatively positive impact on public transport-related trips, but a relatively negative impact on the non-motorized-mode trips in this area. However, no significant change is found for car-related trips.
URI: http://hdl.handle.net/1942/25673
DOI: 10.3390/app8020211
ISSN: 2076-3417
Category: A1
Type: Journal Contribution
Appears in Collections: Research publications

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