Dynamic Bayesian Belief Network to Model the Development of Walking and Cycling Schemes

Dong Ngoduy, David Watling, Paul Timms, Miles Tight

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


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. © 2013 Copyright Taylor and Francis Group, LLC.
Original languageEnglish
Pages (from-to)366-388
Number of pages23
JournalInternational Journal of Sustainable Transportation
Issue number5
Publication statusPublished - Sept 2013


  • causal effects
  • dynamic bayesian belief network
  • walking and cycling (WaC)


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