Ngoduy, D, Watling, DP, Timms, PM et al. (1 more author) (2013) Dynamic Bayesian belief network to model the development of walking and cycling schemes. International Journal of Sustainable Transportation, 7 (5). 366 - 388. ISSN 1556-8318
Abstract
This paper aims to describe a model which represents the formulation of decision-making processes (over a number of years) affecting the step-changes of walking and cycling (WaC) schemes. These processes can be seen as being driven by a number of causal factors, many of which are associated with the attitudes of a variety of factors, in terms of both determining whether any scheme will be implemented and, if it is implemented, the extent to which it is used. The outputs of the model are pathways as to how the future might unfold (in terms of a number of future time steps) with respect to specific pedestrian and cyclist schemes. The transitions of the decision making processes are formulated using a qualitative simulation method, which describes the step-changes of the WaC scheme development. In this article a Bayesian belief network (BBN) theory is extended to model the influence between and within factors in the dynamic decision making process.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | (c) 2013, Taylor & Francis Group, LLC. This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Sustainable Transportation on 07/02/13, available online: http://wwww.tandfonline.com/10.1080/15568318.2012.674627 |
Keywords: | Causal effects; Dynamic Bayesian belief network; Walking and cycling (WaC) |
Dates: |
|
Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) > ITS: Spatial Modelling and Dynamics (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 21 May 2015 15:51 |
Last Modified: | 17 Jan 2018 17:57 |
Published Version: | http://dx.doi.org/10.1080/15568318.2012.674627 |
Status: | Published |
Publisher: | Taylor & Francis |
Identification Number: | 10.1080/15568318.2012.674627 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:84523 |