Modelling and predicting patterns of pedestrian movement: using robotics and machine learning to improve the design of urban space.

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In a geographic region that is experiencing increasing urban density, the problems of the pedestrian are rarely considered from a design perspective. One reason for this is that there are few useful tools available for analysing the behaviour of pedestrians in existing urban spaces, and none to assist designers to optimise such spaces. As a result of this, there is an urgent need for the development of design tools to enable a higher level of understanding of pedestrians in public space. This project is a world-first combining urban design theory and machine-learning for creating more socially and culturally responsive environments.