Abstract
A large-scale residential-location model of the Greater London region is being developed in which all stages of the model-building process—from data input, analysis through calibration to prediction—are rapid to execute and accessible in a visual and immediate fashion. The model is structured to distribute trips across competing modes of transport from employment to population locations. It is cast in an entropy-maximising framework which has been extended to measure actual components of energy—travel costs, free energy, and unusable energy (entropy itself)—and these provide indicators for examining future scenarios based on changing the costs of travel in the metro region. Although the model is comparatively static, we interpret its predictions in terms of fast and slow processes—‘fast’ relating to changes in transport modes, and ‘slow’ relating to changes in location. After developing and explaining the model using appropriate visual analytics, a scenario in which road-travel costs double is tested: this shows that mode switching is considerably more significant than shifts in location—which are minimal.
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