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The transport infrastructures are important elements in the cities, but, as there is a lack of planning, they tear through the urban fabric and leave empty spaces. Due to government and private disinterest, these spaces become vacant, forgotten and degraded. However, these extensive Terrain Vague offer new potential for urban use. To exploit this potential, we need methodologies that can offer personalised, extensive, feasible urban solutions. For this, we propose a computational generative system, following a 4-step methodology: 1) Site analyses and Terrain Vague identification; 2) Site classification according to parameters based on a "visual grammar"; 3) Algorithm associating space properties with geometric transformation to generate solutions: namely transformative operations in public spaces, additive transformations in semi-public spaces and subtractive operations in semi-private spaces; 4) Solution evaluation and development, according to shade criteria, spatial hierarchy and volumetric density. With our own algorithms combined with genetic algorithms, we guided the evolution of 50 volumetric solutions. The exponential increase in information requires new methodologies (Schwab, 2018). Results show the potential of computational methodologies to produce extensive urban solutions. This research, developed in a final graduation project in Architecture, aims at stimulating generative methodologies in undergraduate courses.

A Generative System for the Terrain Vague Transcarioca Bus Expressway in Rio de Janeiro