Way to Go! Automatic Optimization of Wayfinding Design

TL;DR

This paper presents an automated method for designing effective wayfinding signs in virtual and real-world environments, reducing manual effort and optimizing navigation guidance based on human visibility and error considerations.

Contribution

The paper introduces 'Way to Go!', an automated approach that generates optimized wayfinding designs for various layouts by considering human navigation factors.

Findings

Successfully applied to diverse environments like train stations and urban areas.

Generated designs improve navigation efficiency and accessibility.

Helps identify and fix 'blind zones' in wayfinding layouts.

Abstract

Wayfinding signs play an important role in guiding users to navigate in a virtual environment and in helping pedestrians to find their ways in a real-world architectural site. Conventionally, the wayfinding design of a virtual environment is created manually, so as the wayfinding design of a real-world architectural site. The many possible navigation scenarios, as well as the interplay between signs and human navigation, can make the manual design process overwhelming and non-trivial. As a result, creating a wayfinding design for a typical layout can take months to several years. In this paper, we introduce the Way to Go! approach for automatically generating a wayfinding design for a given layout. The designer simply has to specify some navigation scenarios; our approach will automatically generate an optimized wayfinding design with signs properly placed considering human agents' visibility and possibility of making mistakes during a navigation. We demonstrate the effectiveness of our approach in generating wayfinding designs for different layouts such as a train station, a downtown and a canyon. We evaluate our results by comparing different wayfinding designs and show that our optimized wayfinding design can guide pedestrians to their destinations effectively and efficiently. Our approach can also help the designer visualize the accessibility of a destination from different locations, and correct any "blind zone" with additional signs.