The research team devised a novel visual assessment methodology termed Casewise Visual Evaluation (CAVE). This process uses a fuzzy set-theory based modeling system. When there are many design parameters, the CAVE process translates community preference for complete designs into preference for each of the elements in that design. Preferred combinations of elements can then be determined. There are many design elements in each scenario, such as building type, open space type, height, density, and so on.
Once the significant design elements are identified and a highly preferred combination is determined using CAVE, virtual reality visualizations are used to display design options and assess community reaction to them.
A Structured Public Involvement protocol was used to gather community input. An iterative series of focus group meetings were organized in partnership with the local transit agency, TARC. Community feedback on the desired features of the development was gathered, and the forthcoming CAVE process was explained.
An electronic scoring system was then used to assess preference for transit-oriented developments (TODs) in other cities, using photographs. This allowed for fair, free, and anonymous evaluation by the community, using a 1 to 10 point preference scale.
The community’s response to these pictures was then used as input to CAVE. To code the photos in terms of inputs useful to professionals, architectural experts were consulted and a design vocabulary was defined. The architects described the TOD images in useful and familiar terms. Using these as input parameters, with public preference as the output, the modeling process was started and a knowledge base was built. This modeled how community preference responded to varying height, density, typology, and open-space type.
The information was used by the design team to determine which combinations of elements were preferred by the residents. In collaboration with architectural experts, the output of the knowledge base provided guidance for design types. These designs were modeled as scenarios in the virtual reality visualization model.
The CAVE methodology has been demonstrated and provided clear design guidance for experts. Moreover, feedback from community participants has been positive. Comments included an expressed appreciation of the power devolved to the focus group in terms of determining which aspects are preferred. Residents have also commented on the importance of increasing participation at the focus group meetings so that more of their neighbors can participate in the design process. This desire of residents to involve others is a positive indicator.
Project Payoff Potential
By providing an efficient, organized public involvement process using decision modeling and visualization, the public's preferences are translated into specific design recommendations quickly and easily. Because the public feels greater ownership of the design product, as evidenced by feedback comments, there is less resistance and more enthusiasm for participation and implementation. These qualitative improvements translate into fewer problems for transit agencies charged with such development. More effective public involvement also leads to a valuable improvement in the local culture of citizens participation for future projects.
Product Transfer
The lessons learned during the project are included in a final report for this project. The research team has submitted several papers on the results of this project to research journals, and presented the research at the Community Design Symposium at Harvard University.
The protocol developed in the project is being used by Arizona DOT and by the Kentucky Transportation Cabinet. The investigators on this project at the University of Kentucky are supporting public involvement processes a number of different areas, using methods developed in this project.
