Urban Street Retrofitting An Application Study on Bottom-Up Design

Abstract

Urban streets will have to be retrofitted to improve walkability and to provide space for a diversity of transport modes. This paper introduces a framework which combines space syntax and shape grammars in a design support method for generating scenarios for urban street retrofitting. A procedure to hierarchize streets and select priority locations for urban street retrofitting is presented. Four different angular choice analyses with decreasing radii are used to derive the hierarchical structure of target urban areas with the aim of triggering shape grammar rules and generating bottom-up intervention designs. The same measure using a local radius to represent walking modal is then used to determine which streets should be retrofitted to improve pedestrian safety and walkability for the largest number of people. An application study using this procedure is presented and results are compared to street hierarchies from two different sources. This study is the first step towards automating the generation of design scenarios for urban street retrofitting.