Bernasconi, Claudia, Utpal Dutta, Veronica Allen, and Blake Hill
A study was conducted to capture public preferences for urban scenes that include the Detroit People Mover (DPM) system in Detroit, MI. The goal of the study was to understand the perceived visual aesthetic quality of the DPM stations in relation to the urban environment of downtown Detroit. We employed a perception-based landscape assessment technique to measure preferences for distinct elements characterizing the scenes. We categorized scenes through the identification of a set of attributes defining the urban context and the stations. Perceptions were captured using a rank ordering process of most and least preferred scenes on presented panels and responses were analyzed using correlation and regression statistical techniques. Results indicate that specific design attributes did not emerge as significantly influencing public perception, while the “amount of vegetation” and “street-sidewalk ratio” significantly affected perceptions. The findings improve our understanding of visual strengths and weaknesses of automated transportation structures within the urban environment and indicate that studies on automated transportation should consider the effect of context on the perception of stations. The implications of this work provide advancements in the field of perceptual research through the testing and refining of landscape evaluation approaches in urban environments.