EVALUATION OF INDOOR PATHS BASED ON INDOOR NAVIGATION NETWORK MODELS AND SPACE SYNTAX MEASURES

Indoor navigation networks (models) are an essential way to characterize the navigation patterns of pedestrians. To find the most suitable path existing studies concentrate mostly on the minimization of length and turns. However, they alone may fall short to support one in wayfinding as they only consider the spatial structure of a building. Space syntax measures can reveal the interaction among spatial configurations and visibility-based spatial reasoning of pedestrians. In this paper, our original contribution is to adapt them to evaluate indoor paths. To demonstrate our approach, we first conducted a user experiment to collect the navigation patterns. Then, these navigation patterns were compared with the indoor paths through statistical comparison with respect to space syntax measures. Also, all door-from-door paths were compared by traditional and space syntax measures. The findings of the experimental study show that the visibility-based UCN is the more suitable navigation network by traditional measures. However, space syntax measures suggest that centerline-based navigation networks are more suitable. Considering traditional and space syntax measures together, the centerline-based MPRSSE is found to be the more suitable navigation network to assist one in the wayfinding process for our experimental study.