Cognitive Model of Agent Exploration with Vision and Signage Understanding

Date

2023-03-20

Authors

Johnson, Colin
Haworth, Brandon

Journal Title

Journal ISSN

Volume Title

Publisher

Computer Graphics Forum

Abstract

Signage systems play an essential role in ensuring safe, stress-free, and efficient navigation for the occupants of indoor spaces. Crowd simulations with sufficiently realistic virtual humans provide a convenient and cost-effective approach to evaluating and optimizing signage systems. In this work, we develop an agent model which makes use of image processing on parametric saliency maps to visually identify signage and distractions in the agent's field of view. Information from identified signs is incorporated into a grid-based representation of wayfinding familiarity, which is used to guide informed exploration of the agent's environment using a modified A* algorithm. In areas with low wayfinding familiarity, the agent follows a random exploration behaviour based on sampling a grid of previously observed locations for heuristic values based on space syntax isovist measures. The resulting agent design is evaluated in a variety of test environments and found to be able to reliably navigate towards a goal location using a combination of signage and random exploration.

Description

Keywords

CCS Concepts, Computing methodologies → Multi‐agent systems, Image Manipulation, Applied computing → Computer‐aided design

Citation

Johnson, C. and Haworth, B. (2022), Cognitive Model of Agent Exploration with Vision and Signage Understanding. Computer Graphics Forum, 41: 143-154. https://doi.org/10.1111/cgf.14631