AUTOSIGN: A multi-criteria optimization approach to computer aided design of signage layouts in complex buildings

Abstract

To improve the efficiency and effectiveness of designing signage systems in buildings, we present AUTOSIGN – a design tool that supports user-in-the-loop and multi-criteria optimization of signage layouts in complex buildings. We formulate signage placement as a multi-objective optimization problem with competing objectives (i.e., total distance travelled, total number of turns, the centrality of decision points, path overlap, and number of decision taken) and constraints (i.e., user-specified sign location and orientation threshold), which we solve using a two-step approach. Firstly, an evolutionary method is used to optimize all combination of navigation paths based on cognitively inspired objective functions weighted by the designers. Secondly, a particle swarm optimization is used to optimize individual sign placement to maximize the exposure of wayfinding information (i.e., signage coverage area) from the optimized navigation graph generated. To evaluate the effectiveness of the tool, we apply it to the design of signage systems across two virtual 3D buildings. We generate signage layouts for both buildings and optimize each of them for user-defined criteria. Both optimized and non-optimized layouts are evaluated using an agent-based simulation. The simulation results demonstrate that even with fewer signs, the signage coverage area for the optimized layout increased by 18% on average. Finally, an expert-based VR walk-through and a System Usability Study is performed to further evaluate AUTOSIGN.