In their 2000 article, Hacklay et. al. present a model of impressive complexity – STREETS – to simulate pedestrian movements in central urban areas, relying on the use of several different ‘modules’ to control individual agents as well as interactions with the environment and crowd dynamics. The authors outline a number of shortcomings to their methodology, notably the assumption that the town centre in the simulation is a ‘spatially closed’ (p.10).
Initially skeptical of the model’s use beyond simply confirming or denying existing ideas about pedestrian behaviour, I was reminded (as in previous articles) of our in class discussion about the quantification bias that can legitimize numerical/computational work over more qualitative approaches, and has indisputably helped maintain the relevance of GIS (and now modelling) in contemporary geography. This made me question the relevance of modelling human behaviour; I felt the assumptions in the STREETS model were too damning, and the implied complexity would never be adequately abstracted. To my surprise, this was boldly addressed by the authors through a fascinating discussion of ‘bottom up emergence’ (p.25-26).
In discussing the role of agent-based modelling and its ‘one-way notion of emergence’ (p.26), the authors detach themselves from the notion that inductive research is possible in the STREETS model, and the jump from describing pedestrian movement as ‘plausible’ to ‘self-organizing’ (p. 25) is significant. This discussion peaked my interest, for it suggests that there is more to modelling than increasing its complexity every time advances in computational power allow for it. Clearly, the addition of dozens of modules or parameters is not enough to allow reliable inductive research to be conducted. Nevertheless, the power of modelling hundreds of thousands of agents at a time far exceeds the current possibilities of qualitative research on pedestrian movement, suggesting that modelling will remain highly relevant in the study of pedestrian movement into the future.
At what point will models transition into ‘self-organizing emergent structures’ (p.26)? I honestly cannot say, and my level of understanding doesn’t even allow for an educated guess – all I know for sure is that it won’t be exclusively dependent on computational power. In any case, I look forward to seeing how the field develops.
-XYCoordinator