Model validation is a significant issue for the modelling of social network-based transportation models because of the many interacting components (the individuals, the environment, and now the network) in the model. In this paper we focus on a sensitivity analysis for such a model, which is part of a larger validation approach known as process validation. This approach investigates both the structure and behaviour of the model, to evaluate whether the model can be used for prediction. The paper draws on a novel set of experiments with an agent-based model which was developed to explore the effects of social networks on activity and travel behaviour. Several versions of the model were created, beginning with a single day model with no interaction, and then adding in multi-day runs with interactions, in order to demonstrate the validation process. The paper argues that testing the model at different levels of complexity increases confidence in the model and makes it easier to locate components or functionality that require improvement. It concludes by suggesting that this approach to sensitivity testing should be adopted for validation of complex transportation models.
|Number of pages||9|
|Journal||Computers, Environment and Urban Systems|
|Publication status||Published - 1 Jan 2016|
- Social networks
- Transport modelling